Contemporary Athletics Compendium, Volume 3

CONTEMPORARY ATHLETICS COMPENDIUM VOLUME 3

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CONTEMPORARY ATHLETICS COMPENDIUM VOLUME 3

JAMES H. HUMPHREY EDITOR

Nova Science Publishers, Inc. New York

Copyright © 2009 by Nova Science Publishers, Inc. All rights reserved. No part of this book may be reproduced, stored in a retrieval system or transmitted in any form or by any means: electronic, electrostatic, magnetic, tape, mechanical photocopying, recording or otherwise without the written permission of the Publisher. For permission to use material from this book please contact us: Telephone 631-231-7269; Fax 631-231-8175 Web Site: http://www.novapublishers.com NOTICE TO THE READER The Publisher has taken reasonable care in the preparation of this book, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of information contained in this book. The Publisher shall not be liable for any special, consequential, or exemplary damages resulting, in whole or in part, from the readers’ use of, or reliance upon, this material. Independent verification should be sought for any data, advice or recommendations contained in this book. In addition, no responsibility is assumed by the publisher for any injury and/or damage to persons or property arising from any methods, products, instructions, ideas or otherwise contained in this publication. This publication is designed to provide accurate and authoritative information with regard to the subject matter covered herein. It is sold with the clear understanding that the Publisher is not engaged in rendering legal or any other professional services. If legal or any other expert assistance is required, the services of a competent person should be sought. FROM A DECLARATION OF PARTICIPANTS JOINTLY ADOPTED BY A COMMITTEE OF THE AMERICAN BAR ASSOCIATION AND A COMMITTEE OF PUBLISHERS. LIBRARY OF CONGRESS CATALOGING-IN-PUBLICATION DATA

ISBN: 978-1-61728-202-7 (E-Book) Available upon request

Published by Nova Science Publishers, Inc.  New York

CONTENTS Preface

ix

Founding Editor Chapter 1

Wrestling with Herpes: A Case Study John J. Miller and John T. Wendt

Chapter 2

Can Spectators’ Mood Be Manipulated and Maintained in a Losing Game?: Interaction between Team Identification and Pre-Game Mood Hyungil Harry Kwon, Chulwon Lee and Sang-il Lee

Chapter 3

Why College Athletes Play through Pain during Competition Jennifer J. Waldron and Nathan White

Chapter 4

A Description and Comparison of Duties and Responsibilities of NCAA Division II Head Baseball and Football Coaches Randy Nichols

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9 25

33

Chapter 5

Identity Foreclosure? A Preliminary Investigation of Self-Complexity in Sport 43 Diane E. Mack, Philip M. Wilson, Kristin G. Oster and Katie E. Gunnell

Chapter 6

Risk Management Strategies at Division I Intercollegiate Football Stadiums: Do Spectators Perceive They Are Protected against Terrorism? John J. Miller, Andy Gillentine and Frank Veltri

Chapter 7

Chapter 8

Chapter 9

The Positive Relationship between Sport Team Identification and Social Psychological Well-Being: Identification with Favorite Teams Versus Local Teams Daniel L. Wann and Jennifer Martin For Love of the Game: The Mediating Potential of Job Satisfaction of College Coaches upon Career Satisfaction Aaron W. Clopton, Tim D. Ryan and Michael Sagas Steroids in Interscholastic Athletics: Does Reasonable Suspicion Exist? John J. Miller, John T. Wendt and Sean Kern

53

65

75 89

vi Chapter 10

Chapter 11

Contents In Demand? Examining Sport Management Faculty Openings and Hires Edward (Ted) M. Kian, Paul M. Pedersen and John Vincent

103

The Importance of Parent Physical Activity Levels and Their Expectations for Their Children’s Health: A Path Analysis Marc Lochbaum, Tara Stevens, Yen To and Sarah Stevenson

111

Chapter 12

Negligent Marketing: “What All Sport Marketers Should Know” Andy Gillentine, John Miller and Austin Stair Calhoun

127

Chapter 13

Investigating Fantasy Sport Participation among College Students Chad Seifried, Corinne Farneti, Brian A. Turner, Martin Brett and Jerry Davis

137

Chapter 14

A Look at Academic Reform, Student Athlete Compensation and the Case for a New Classification of Student-Athlete Frank Adrien Bouchet

149

Motivational Profiles of Sports Fans Attending Different Levels of Baseball Games Amber L. Rickard, Frederick G. Grieve and W. Pitt Derryberry

163

Characteristics of Success in Men’s Football and Men’s Basketball at the Division I Level Shane L. Hudson

177

Chapter 15

Chapter 16

Chapter 17

Alternative Dispute Resolution in Sport: A Conceptual Approach Dan Connaughton

191

Chapter 18

Just Not on My Turf: Student-Athletes’ Perceptions of Homosexuality Amy Sandler

207

Chapter 19

Identification with Multiple Sporting Teams: How Many Teams Do Sport Fans Follow? 219 Frederick G. Grieve, Ryan K. Zapalac, Amanda J. Visek, Daniel L. Wann, Paula M. Parker, Julie Partridge and Jason R. Lanter

Chapter 20

Motivations of International Student-Athletes to Participate in Intercollegiate Athletics Stephanie G. Jones, Gi-Yong Koo, Seungmo Kim, Damon Andrew and Robin Hardin

Chapter 21

Chapter 22

229

Fundraising Responsibilities and Expectations of NCAA Division II Head Baseball and Football Coaches Randy Nichols and Carl Bahneman

243

Athletic Administrators Perceptions of Work-Life Balance Policies: A Divisional Comparison Nancy Lough, Bonnie Tiell and Barbara Osborne

253

Chapter 23

Chapter 24

Contents

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The Impact of Playing Position on Perceptions of Horizontal Interpersonal Power in Sport Daniel L. Wann

269

Stress Factors in the Profession of Coaching: Assessing Their Nature, Scope and Impact Deborah A. Yow, James H. Humphrey and William W. Bowden

281

Expert Commentary New Technology Holds Promise for the Future Application of Psychophysiological Methods for the Enhancement of Performance during Sport and Exercise David L. Neumann Index

293 297

PREFACE This new book is concerned with all levels of athletics - interscholastic, intercollegiate, club, and professional. Articles on all aspects of contemporary athletics are invited. Topics include, but are not limited to, event scheduling, stress, sports medicine, graduation rates, academic eligibility, gender issues, commercialization, funding or the lack of it, sports psychology, sports sociology, parental aggression, coaching, drug use in athletics, teamwork, philosophy, athletic competition/participation in relation to life, spectator behavior, officiating, religion in sports, sports gambling, history of athletics, athlete administration, ethics, sports management, nutrition, and legal issues. Chapter 1 - A recent outbreak of herpes gladiatorum took place in a northern Midwestern state that affected 24 high school athletes from ten different schools who were diagnosed as having herpes gladiatorum (HG). In an unprecedented move the state high school league imposed a statewide shutdown of the sport for eight days in the middle of the season. A previous study indicated that not only are medical personnel not fully trained to diagnose HG but national guidelines are too lax in checking for possible symptoms for it. Because this was not the first time that such an outbreak hasd occurred in wrestling in the state, it should have been a foreseeable issue. The concepts of foreseeability, likelihood and impact will be addressed and applied to the implementation of an effective risk management plan. Through the implementation of a risk management plan such episodes as cited in the case study may be prevented from happening. Chapter 2 - The current study addressed two research questions. First, study 1 examined whether spectators’ mood before they were exposed to a losing game (i.e., pre-game mood) influenced their mood after the game (post-game mood) and their information processing. Secondly, study 2 examined whether the influence of pre-game mood found in Study 1 was modified by personal relevance (i.e., team identification) with a sporting game. The results indicated that pre-game mood influenced participants’ post-game mood and information processing system. The results of the second study also supported the hypotheses that postgame mood and spectators’ information processing were influenced by pre-game mood and personal relevance (i.e., team identification). As hypothesized, two-way interaction between pre-game mood and personal relevance was found in post-game mood whereas no interaction was found in information processing. This study was able to identify a group of people who were more affected by the result of home game and who more effectively responded to mood manipulation.

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Chapter 3 - Within the environment of sport, athletes must often overlook and ignore pain and injury to be successful. In light of this, the current study, using an open-ended question, explored reasons why collegiate athletes made the decision to play through pain during competition. Male (n = 67) and female (n = 60) collegiate athletes from a variety of sports completed a demographic questionnaire and an open-ended question asking the reason why they played through pain during competition. Of the 127 participants, 77 (61%) reported that they had played through pain during competition. Data analysis included two researchers individually coding participants’ answers. Five major labels –for the self, nature of sport, for others, pain, and self-presentation – explained why athletes’ were determined to play through pain during competition. Participants’ responses suggest they have internalized the norms of the sport ethic and the culture of risk. Chapter 4 - The purpose of this study was to: (1) describe the duties and responsibilities of NCAA Division II head football and baseball coaches. The data were collected via a survey. Instrument returned by 41 of 122 head baseball coaches and 38 of 122 football coaches surveyed. Demographic data indicated the following: the majority of NCAA Division II head baseball and football coaches are Caucasian between the ages of 25 and 64 and have a master's degree, the majority of head baseball coaches are responsible for coordinating their programs fund-raising efforts while fewer head football coaches have this responsibility, the role responsibilities of the head coaches outside of coaching varies from teaching, coaching, admissions, residence life and financial aid. The data also revealed that head baseball coaches have more responsibilities outside of coaching than football coaches. Chapter 5 - The primary purpose of this study was to examine whether athletes differed in self-complexity (SC) from non-athletes. A secondary purpose was to examine the relationship between SC and self-presentational concerns in sport. Participants (N = 242) completed a descriptive sorting task to measure SC. The athletic sub-sample (n = 121) further completed the Self-Presentational in Sport Questionnaire (SPSQ; Wilson and Eklund, 1998). Analyses revealed minimal differences in SC between sub-samples implying that athletes do not restrict their identity development. Correlational analyses revealed patterns of relationships between SC and SPSQ scores generally consistent with meta-analytic findings (Rafaeli-Mor and Steinberg, 2002) and the stress buffering hypothesis advanced within the SC framework. Overall, this study supports the contention that athletic participation does not, out of necessity, lead to identity foreclosure. Chapter 6 - The prominence and popularity of American sporting events, encourages an examination of levels of safety. Because of their potential impact on the U.S. economy and culture, American sporting event venues may be considered attractive targets of attack for several reasons. First, the large numbers of people attending sports contests provide potential foes with not only the potential of massive casualties but also increased media exposure. For example, Saturday afternoons during the fall season in the United States, are typified by large gatherings of people, some exceeding 100,000, attending intercollegiate football games. Because an enemy’s choice of targets may include the high probability of mass casualties and infliction of economic loss, these factors may be considered rewards for an attack. Thus, an assault on a major sporting event such as an intercollegiate college football game could produce what a terrorist may seek: mass casualties and economic harm.

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A second reason for concern of a terrorist attack at an athletic event is that sports venues are categorized as "soft targets". Soft targets are susceptible locations that are not wellprotected, offer relatively easy access, great numbers of individuals who continually enter and exit a stadium or arena during a contest and the relative congestion that exists of those spectators in the facility. A third reason relates to previous incidents in which large numbers of individuals have previously been attacked by terrorists in the United States prior to September 11, 2001. An explosive device was detonated under New York’s World Trade Center in 1993, causing over $500 million in structural damage, killing six people and injuring more than 1000. Two years later, the Murrah Federal Office Building terrorist bomb blast occurred in Oklahoma City that ultimately took 168 lives, including 19 children. For all these reasons, it should come as no surprise that terrorists have shown a desire to attack major sporting events such as the Super Bowl or World Series. Chapter 7 - Consistent with the Team Identification – Social Psychological Health Model (Wann, 2006a), research indicates a positive relationship between identification with a local sport team and social psychological health. However, because fans often select the local team as their favorite (Jones, 1997), it remained possible that the findings were due to the target team being one’s favorite team rather than due to the team being local. The current study tested the hypothesis that levels of identification with favorite teams would not be independently related to social well-being unless the favorite team was also a local team. College students (N = 173) completed a questionnaire packet assessing demographics, identification with their favorite sport team (categorized as local or distant), and social psychological health. Regression analyses provided clear support for the hypotheses. Discussion centers on implications of the current study for Wann’s (2006a) model and the possibility that mere sport fandom may also play a role in well-being. Chapter 8 - As demands on today’s coach escalates, the role and presence of job satisfaction increases in significance, as well. Past research has analyzed job satisfaction in both sport and business literature (e.g. Wright, 2006); and linked with diversity (Pastore, 1993; Sagas et al., 2005) and supervisor satisfaction (Chelladurai, 2003). This investigation examined the relationship of supervisor satisfaction with career satisfaction for the coaching sample, a relationship presented in previous research (e.g. Sagas and Cunningham, 2004). Results indicated significant correlations between supervisor, career, and job satisfaction levels (p < .01). An initial regression analysis displayed a significant presence of supervisor satisfaction in predicting coaches’ career satisfaction (β = .31, p < .001). A further regression analysis revealed significant predictability of job satisfaction when added to the model (β = .50, p < .05). This presence signified the mediating potential of job satisfaction on the relationship between supervisor satisfaction and career satisfaction. Chapter 9 - Despite the notoriety that steroid use has attained, relatively little research has been conducted regarding interscholastic athletics. Miller and Wendt (2007) reported that more than twice the number of the state athletic directors perceived that steroid use was extensive throughout the United States than in their state. Additionally, the results indicated that while 40% were uncertain whether interscholastic athletes in their program had taken steroids, 25% of the athletic directors had suspected athletes is in their program had done so. Moreover, nearly 30% had suspected athletes from other athletic programs had used steroids. However, a limitation of this study was that the ascertained information came from only one state. This study expanded this number to three states. The results indicated that 33% of the

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respondents suspected athletes in their programs of taking steroids while 65% had suspected had suspected interscholastic athletes in other programs of taking steroids Chapter 10 - Over the past 25-30 years, sport management has been among the fastest growing academic disciplines in higher education within the United States. However, the few universities producing sport management doctoral graduates have seemingly been unable to meet the demands for qualified individuals to teach at the university level. This study analyzed each of the 124 professorial advertisements for sport management/administration placed by U.S. universities over a one-year period, encompassing the 2005-06 academic year. The majority of the openings were in the Southeast, Northeast, and Midwest, with few listings in the Southwest or West. Nearly half of all listings were at institutions offering sport management only at the undergraduate level. A phone survey revealed only 69% of advertised positions were filled, with 53% of schools with failed searches citing a lack of desired applicants. A majority of schools that did not hire planned to re-post their positions the following academic year. Chapter 11 - Rates of childhood obesity are reaching epidemic levels. The purpose of this investigation was to determine if parent behavior and expectations are associated with estimates of their children’s leisure time activities and their adult body size. Bandura’s (1986) social cognitive theory guided the investigation. Participants were 121 parents of 65 kindergarten and 56 fifth grade students from a midsized rural school district. The majority of parents were minorities with a low percentage of parents having obtained degrees beyond a high school diploma. Parents completed measures to assess their physical activity level, their preferences for their children’s leisure time activity, estimates of time spent in a variety of leisure time activities, and an estimate of their children’s adult body size as an adult. Parents spent very little time in physical activity though their preference was for their children to be active. Path analysis was conducted on a model that described relationships between parents’ activity levels and their preferences for their children’s activity, parents’ activity levels and that of their children, and parents’ preferences for their children’s physical activity and their children’s time spent in physical activity. An association was also posited between parents’ preferences for their children’s physical activity and their children’s body size as an adult. Path analysis goodness of fit indices indicated a good fit (e.g., SRMR = .02, CFI = 1.00). All associations were in the hypothesized direction. In addition, the greater preference for children to be active was associated with a decrease in estimated body size as an adult by the parents. The percent of variance accounted for (< 10%) in the significant paths do suggest that several important variables were missing in our model. Future research longitudinal research that incorporates more extensive measures of both parents and their children are discussed. Chapter 12 - Negligent marketing assumes that promoters should not engage in strategies that increase the risk that patrons may injure either themselves or others (Ausness, 2002). Marketing campaigns portraying a product being consumed in a negligent manner that leads to the development of an unsafe environment may put the service provider at risk (Sebok, 2003). If a defendant can establish the marketing campaign influenced how the product was consumed, service providers could be found liable. Sport organizations allowing companies to deliver such marketing campaigns or that are associated with products that promote dangerous or reckless behavior may also be liable (Rabin, 1999). Sport organizations should be careful not to create the impression that negligent consumption of a product is part of a consumers experience. Sport marketers must evaluate situations to identify potentially

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dangerous actions or behaviors (Gillentine, 2003; Jackson and Polite, 2003; Gillentine and Miller, 2004). On a crisp autumn afternoon, Christine Bearman and her husband causally strolled through the parking lot towards their car. Following an afternoon of college football, the Bearmans decided to leave the event a little early to avoid possible traffic delays on the way home. As the Bearmans made their way through the Notre Dame parking lot, an intoxicated “tailgater” knocked Christina to the ground. Ms Bearman suffered a broken leg in the incident and required medical attention. No security or event management staff was in the vicinity when the incident occurred. Chapter 13 - This project examined fantasy sport participation among the college student population and compared it to previously completed work. Specifically, 155 college students were surveyed from a large midwestern university. The study supports most college student fantasy participants are male and nearly a third of these males participated in paid leagues. Interestingly, most respondents (73.3%) indicated they felt fantasy participation was not gambling. The investigation also revealed 29.9% of students generally read more and 23.5% watched more about a sport when they participate in fantasy leagues. In addition, 77.6% felt the success of their fantasy team did not determine how much they watch sports and another 91.8% of respondents declared the elimination of their fantasy team from playoffs or postseason competition failed to eliminate their desire to watch sports. Similar to other studies, NFL, MLB, and NBA leagues, in that order, emerged as the most popular fantasy leagues. Finally, this study’s college student fantasy league participants come from various backgrounds. For example, many different academic backgrounds/majors were present in the sample population and nearly 91% of fantasy players played high school level athletics or higher. Chapter 14 - This paper discusses student-athletes compensation issues. The author expresses his concern over the unwillingness of the National Collegiate Athletic Association (NCAA) to fairly compensate these athletes. Since the main concerns according to the N.C.A.A. over such a system are workman’s compensation and academic reform we will look into both of those issues as well. A historical perspective will be applied to these issues. We will look into the possibility of some of the main athletic conferences breaking away from the N.C.A.A. and starting a new classification of student-athlete. The advantages and disadvantages of such a move will be looked at as well. The leadership structures of both higher education and the N.C.A.A. will be discussed. Chapter 15 - While a number of studies (e.g., James and Ross, 2004; Mehus, 2005; Wann, Grieve, Zapalac, and Pease, in press) have examined motives sport fans have for attending different sports, few have examined motives for attending different levels of the same sport (Bernthal and Graham, 2003). The present study was designed to examine motives for attending five different levels of baseball games—T-Ball, Little League, High School, College, and Minor League. Participants were 224 adult fans who attended a game at one of the five levels. They completed measures of sport fandom, team identification, and motivation for attending the game. Different motivational patterns were evident among the different levels. Implications for the findings are discussed. Chapter 16 - The push for student-athletes to graduate college has never been greater. Student-athletes are under more pressure to not only complete their degree but, to do it in a timely manner under NCAA guidelines. The intent of this study was to determine if men’s football and men’s basketball coaches at the university or college level utilize an assessment

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instrument when recruiting and evaluating potential student-athletes. Specifically studied through interviews were the characteristics that these coaches look for in successful and unsuccessful student-athletes, how they currently collect information during the recruitment period and whether collecting data on student-athletes is of importance or not. The population for this study consisted of current Division IA men’s football and men’s basketball coaches in the Big 12 Conference. The study helps to define through research and development an assessment instrument to more effectively define the needs of student-athletes prior to entering universities. Chapter 17 - Alternative dispute resolution (ADR) is an integral part of the sport industry. It allows leagues, teams, and players to resolve disputes that arise without using litigation. It is essential for people who work within sports to understand the value of ADR. The purpose of this article is to provide an extensive overview of ADR as it relates to sport. This article takes a conceptual approach in addressing the many aspects of ADR. The two major applications of ADR, arbitration and mediation, are discussed, with a focus towards arbitration. In order to properly utilize ADR one must understand the statutes and cases that give it power. Therefore, federal and international laws, along with the cases that define ADR are discussed. Additionally, this article will examine the benefits of ADR, what distinguishes mediation from arbitration, the arbitration process, how ADR is applied to amateur sports, how the Olympics and international sport community employ ADR, how U.S. professional sports utilize ADR, and how new emerging hybrid forms of ADR are applied to sport-related disputes. In order to illustrate these concepts, recent sport examples are presented. Chapter 18 - NCAA certification guidelines now stipulate that member institutions must have policies, support opportunities, and educational programs in place to ensure a safe environment for student-athletes with diverse sexual orientations. This research measures student-athletes’ general level of homophobia. The results indicate that student-athletes are comfortable with other people being gay or lesbian, but they would not be comfortable if they found themselves attracted to someone of the same-sex, or if someone of the same sex was attracted to them. If coaches and athletic administrators are aware of how student-athletes perceive sexual orientation, they can be more intentional in choosing educational programming to meet specific needs of each team. Chapter 19 - The current study examined the identification with multiple sport teams by sport fans, as a potential means to maintain these positive benefits of identification by switching identification to another sports team. Sport fans were predicted to report following fewer teams closely compared to moderately, and fewer teams moderately compared to casually. Additionally, sport fans were predicted to be higher identified with teams they followed closely compared to those teams moderately followed, and more identified with moderately followed teams compared to teams they followed casually. The first hypothesis was not supported, as participants reported following more teams closely compared to moderately and casually. The second hypothesis was supported, as participants reported being more identified with the teams they closely follow compared to the moderately and casually followed teams. Implications of these findings for sport researchers and sport marketers are discussed. Chapter 20 - The purposes of this study were to (a) explore motives of international student-athletes who come to the United States to participate in intercollegiate athletics, and (b) examine differences in motives of international student-athletes based on selected sociodemographic attributes (e.g., gender, types of scholarship received, types of sports

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participation and region of the world). An exploratory factor analysis revealed four motivation factors: intercollegiate athletics attractiveness, school attractiveness, desire for independency, and environmental attractiveness. Data analysis indicated differences in motivation factors based on types of sports participation and region of the world. The study will help coaches and athletic administrators understand international student-athletes’ motivational factors, which play a critical role in recruiting these international studentathletes. Knowing why an international student-athlete wants to participate in intercollegiate athletics in the United States will aid coaches in developing specific recruiting plans to attract these athletes. This information will also assist coaches in satisfying those needs once the student-athlete is competing in intercollegiate athletics. Chapter 21 - The purpose of this study was to: (1) describe the fundraising responsibilities and expectations of NCAA Division II head baseball and football coaches. The data were collected via a survey instrument returned by 41 of 122 head baseball coaches and 38 of 122 football coaches surveyed. Demographic data indicated the following: the majority of NCAA Division II head baseball and football coaches are Caucasian between the ages of 25 and 64 and have a master's degree. Data indicated that a majority of head baseball coaches are responsible for coordinating their programs fund-raising efforts while fewer head football coaches have this responsibility, the most successful fund-raising activities for baseball programs are fund-raising events, while football programs raise a higher percentage through solicitation of alumni and individuals with athletic interest. Money raised by these programs was used in somewhat different manners with baseball programs using a majority of the money raised for travel and equipment, while football programs used these funds for equipment, capital improvements and recruiting. Data analysis also revealed that head baseball coaches are expected as part of their contract to raise a higher percentage of operating costs than are football coaches. Chapter 22 - Intercollegiate athletics is recognized as a dynamic industry that places high demands on the time and energy of personnel regardless of the competitive division or size of the institution. Personal sacrifices in time and energy for the sake of the program are equated with contributing to high levels of work-life conflict. The purpose of this study was to analyze the perceptions towards work and life conflict among senior woman administrators and athletic directors at NCAA Division I, II, and III institutions regarding the work-life climate within the athletic department and the existence of workplace benefits offered at their institution. The impact of the presence of children on the perception of work-life climate within the athletic department was also examined. There were significant differences noted in the availability of benefits between DI and DII / DIII, but no significant differences in the perceptions of availability of benefits between ADs and SWAs. Chapter 23 - Interpersonal power involves the extent to which an individual has the ability to influence or change the attitudes and behaviors of others (Baron and Greenberg, 1990; Keys and Case, 1990). French and Raven (1959) suggested that there were five common forms of interpersonal power: reward, coercive, referent, legitimate, and expert. The current investigation examined the extent to which teammates possess differential levels of these five power bases. Based on the theoretical framework offered by Whetten and Cameron (1984), it was hypothesized that players occupying positions that were central, critical, flexible, visible, and relevant would be perceived as possessing greater levels of power than teammates playing positions that lacked these characteristics. To test this prediction, college intramural flag football players were asked to rate the power possessed by their team's best

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quarterback (a highly central, critical, flexible, visible, and relevant position) and best offensive lineman. The data indicated that the quarterbacks were viewed as possessing greater amounts of reward, expert, and legitimate power. Quarterbacks and offensive linemen were not perceived as possessing differential levels of coercive and referent power. Chapter 24 - The coaching profession is most appropriately characterized by the profound uniqueness of its nature. A coach is at once a teacher, a psychologist, a father/mother figure and other roles which he or she finds it expedient or necessary to assume at a given time. Clearly, the college athletic coach labors in a distinctly stressful environment. It is a volatile and often unpredictable profession involving numerous and concurrent pressures. These include the need to continuously interact personally and effectively with his or her student athletes regarding myriads of training, competitive, academic and personal issues. There is also the continuous pressure to recruit and develop a winning team and the need for the coach and players to handle defeat. Add to this relational element with student athletes the human relations which must be maintained with his or her sports supervisor (athletic director, assistant athletic director or associate athletic director), the parents of student athletes, individuals in the media, high school coaches, boosters/fans, assistant coaches, athletic department support staff, and myriads of others, then we see the compelling matrix of human relations which must be attended to by the coach (not to mention the personal and family relations which are often challenging to maintain because of the considerable demands and pressure of the profession). Expert Commentary - Psychophysiology is the study of psychological processes through the measurement and interpretation of physiological responses. The realisation of the relationship between the so-called “mind” and “body” has encouraged the application of psychophysiology in various areas of psychology, including sport psychology. Unfortunately, methodological problems have limited the application of psychophysiological techniques to the study of sport. The gross body movements in most sports cause considerable degradation in the quality of the physiological recordings. The obtrusiveness of the electrode attachments and the wiring of the electrodes to a data acquisition system can also severely impede the athlete’s mobility and performance. It is perhaps not surprising that most psychophysiological research has been concerned with sports that involve minimal movements, such as pistol shooting. However, a range of new technological advances are giving encouragement for future applications of psychophysiological methodology in sport.

FOUNDING EDITOR James H. Humphrey James H. Humphrey, professor emeritus of physical education at the University of Maryland. Dr. Humphrey received his bachelor’s degree from Denison University, his master’s degree from Western Reserve University and his doctor’s degree from Boston University. From 1937 to 1949 he was director of health and physical education at Bedford High School in Bedford, Ohio. Dr. Humphrey enlisted in the Navy and served from 1943 to 1945 as an Athletic Specialist at the Great Lakes Naval Training Center in Great Lakes, Illinois. After receiving his doctorate from Boston University in 1951 he became an assistant professor of physical education at Michigan State University. In 1953, he became as associate professor of physical education and health at the University of Maryland in College Park and was promoted to full professor in 1956 where he taught until he retired at age 70. Additionally, he held visiting professorships at Colorado State College, University of Hawaii and Texas A&M. As a notable researcher and author, Dr. Humphrey was the recipient of many honors and awards during his career. He authored or coauthored 63 books and edited 43 others. He also published several children’s books and created a series of educational record albums. His more than 200 articles and research papers have appeared in more than 20 different national and international journals and magazines. The major thrust of Professor Humphrey’s research was in the area of child learning through motor activity. His development of the AMAV Technique of teaching reading through movement was widely used to assist children who had problems in learning to read, perceptual difficulties, motor deficiencies, stress and certain personality dysfunctions. At the time of his death, he was the editor of the Journal of Contemporary Athletics. Dr. Humphrey was inducted as a fellow of the American Academy of Physical Education in 1966. He was also the recipient of the R. Tate McKenzie Award, the highest citation by the American Alliance of Health, Physical Education, Recreation and Dance. As an athlete himself, Dr. Humphrey was recognized as one of the outstanding middle distance runners of the Midwest during his undergraduate days at Denison University. As captain of the Denison Tracksters in 1933, he led his team to the Ohio conference Title by winning the 440 yard dash and the 880 yard dash. Prior to entering the Navy, Dr. Humphrey coached for six years at Bedford High School where he set an enviable coaching record. He

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coached the Varsity Track Team of the U.S. Navy Training Center at Great Lakes and had an undefeated season in 1945. After his retirement, not only did he continue writing and publishing he continued his own personal fitness regimen running three times a week until age 95. In recognition of Dr. Humphrey’s accomplishments the University of Maryland, Department of Kinesiology recently established the James H. Humphrey Graduate Student Published Research Award that is given each spring to the best published paper first authored by a graduate student in Kinesiology.

Contemporary Athletics Compendium, Volume 3 Editor: James H. Humphrey

ISBN: 978-1-60741-561-9 © 2009 Nova Science Publishers, Inc.

Chapter 1

WRESTLING WITH HERPES: A CASE STUDY John J. Miller∗1 and John T. Wendt2 1

2

Texas Tech University, Lubbock, Texas, USA University of St. Thomas, St. Paul, Minnesota, USA

ABSTRACT A recent outbreak of herpes gladiatorum took place in a northern Midwestern state that affected 24 high school athletes from ten different schools who were diagnosed as having herpes gladiatorum (HG). In an unprecedented move the state high school league imposed a statewide shutdown of the sport for eight days in the middle of the season. A previous study indicated that not only are medical personnel not fully trained to diagnose HG but national guidelines are too lax in checking for possible symptoms for it. Because this was not the first time that such an outbreak hasd occurred in wrestling in the state, it should have been a foreseeable issue. The concepts of foreseeability, likelihood and impact will be addressed and applied to the implementation of an effective risk management plan. Through the implementation of a risk management plan such episodes as cited in the case study may be prevented from happening.

It has been acknowledged that between 60% 95% of the global population is infected by one or more viruses of the herpes family (World Health Organization, 1985). Within that family is herpes gladiatorum (HG) that was first described in the mid-1960s as a skin infection caused by the herpes simplex virus. Interscholastic athletes particularly at risk of contracting HG are often wrestlers who utilize the lock-up position, which puts the face, neck, and arms of the opposing wrestler in close contact (American College of Sport Medicine, 2003). Herpes gladiatorum causes a rash that commonly appears on the face, neck, shoulder, and arms and usually occurs when an infected wrestler passes the infection to an uninfected

∗

Send all correspondence to: John J. Miller, Ph.D., Associate Professor, Department of Health, Exercise, and Sport Sciences, Box 41121, Texas Tech University, Lubbock, TX 79409-1121, Phone: (806) 742-3361, Fax: (806) 742-0877. Email: [email protected]

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wrestler by skin contact (Anderson, 1999; Becker, Kodsi, Lee, Levandowski, andNahmias 1988; Whitley, Kimberlin, Roizman, 1998). While herpes gladiatorum it is not a fatal disease, once it is contracted it becomes a permanent condition, and left untreated the infection can lead to serious consequences (Holland, Mahanti, Belongia, et al., 1992; White andGrant-Kels, 1984; Whitley, Kimberlin, Roizman, 1998). These consequences include extreme fatigue, weight loss, permanent visual impairment and conjunctivitis. Young wrestlers exhibiting symptoms such as extreme fatigue or severe weight loss could put themselves in a highly vulnerable position to incur significant injury. Moreover, some cases have been reported in which the athlete required hospitalization as a result of contracting HG (Becker, et al., 1988; Holland, Mahanti, Belongia, et al., 1992; Selling andKibrick, 1964). Because of the extreme potential for recurrent episodes and the ease with which infection can be transmitted, the lives of students and coaches can be significantly disrupted (Maine, 2000). A disruption took place in 2007 at a northern Midwestern state as 24 high school athletes from ten different schools were diagnosed as having herpes gladiatorum. In an unprecedented move the State High School League (SHSL) declared a statewide shutdown of the sport for eight days in the middle of the season. The SHSL took the position that the shutdown was necessary for the protection of the student-athletes. The director of information for the SHSL explained, The safety of the states student athletes is of paramount concern; while the eight-day suspension of all wrestling competition may be considered disruptive by some, it is hoped that controlling the spread of the disease now will minimize the risk of athletes being disqualified during the upcoming section and state tournaments. The suspension period will also allow affected wrestlers to continue their treatment as well as allow school personnel to monitor athletes that may have been exposed but who have not yet shown any symptoms (MSHSL transcript, 2007, p. 8).

Interscholastic wrestling is a major high school competition in the state as more than 7,500 interscholastic athletes from more than 250 schools annually compete (Millea, 2007).

APPLICATION OF RISK MANAGEMENT The concept of risk management has been assigned various definitions, however, the one constant in all of these descriptions has been to prevent harm. In the context of this case study, risk management will refer to identifying foreseeable risks of contracting herpes gladiatorum through wrestling, the likelihood of occurrences, and the impact that contracting such an infectious disease may have on an individual. It is hoped that through the understanding of these ideas, effective risk management plans may be developed, implemented and enforced to avoid other interscholastic wrestlers from contracting herpes gladiatorum in the future.

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Foreseeability of Risks According to Stahl, Lichtenstein, and Mangan (2004) risks are caused by the actions of others by which a danger develops that could have been avoided. Additionally, Makropoulos (1997) promoted the idea that risks are the result of actions that are not necessary (1997). The concept of foresee ability does not address whether a harmful incident could have been averted, but whether a reasonable person could have foreseen the risks that created the incident (Anderson v. Pine Knob Hill, 2003). The herpes simplex virus (HSV) infection, from which herpes gladiatorum stems, appears to be widespread among wrestlers and rugby players although no specific strain has been identified as being blamed for the outbreaks (Anderson, 2003; Dworkin, et al., 1999). According to reports from the National Federation of State High School Associations and National Collegiate Athletic Association more than 7 million athletes annually participate in interscholastic and intercollegiate athletics. As a result it is foreseeable that greater opportunities for infectious diseases to spread exist. Turbeville, Cowan, Greenfield (2006) indicated that football and wrestling were ranked first and second concerning the frequencies of sport specific outbreaks of infectious diseases. The report also revealed that contact athletics such as wrestling and rugby present tremendous environments for the transmission of communicable diseases due to the close physical contact and trauma to the skin that occurs in these sports. Within this case study, risk was indeed a foreseeable issue as the action of an infected high school wrestler giving another competitor herpes gladiatorum. It was also unnecessary in that with proper pre-tournament inspection the infected wrestler would have been identified. Because of the prevalence of HG transmission in wrestling a pre-inspection may be considered more the norm than not, especially when the impact on the young person’s life is added. Further explanation of the concepts of likelihood and impact as essential components of an effective risk management plan will be addressed in the following sections.

Likelihood A recent report indicated that the occurrence of herpes gladiatorium escalates as the experience level of a wrestler increases, as 2.6% of all high school wrestlers, 8-13% of all in college, and 20-40% of those in Division I wrestlers have HG (StarTribune.com, 2007). While the previously described incident recently took place, it is not without a history in the state as 19 high schools sponsoring wrestling in the state’s major city were caught up in a HG outbreak in 1999. The apparent genesis for the outbreak was due to a team entering a wrestling tournament, completely unaware that some of the members were infected. As a result participants on seven other teams initially contracted HG due to wrestling the infected individuals during the tournament. Additionally, it was determined that as those who were unknowingly infected as well those who became infected at the tournament continued to practice and compete afterwards. As a result the number of others who became infected increased dramatically as 61 wrestlers and three coaches were recognized as having contracted HG over a 42-day period (Anderson, 2003). Other cases of HG outbreaks have been cited in the same state in 2000 and 2001 at summer wrestling camps (Anderson, 2003). Of the 300 wrestlers, ranging in age between 13-

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18 who participated in the 2000 camp, 33 or 9% of the entire camp contracted the HG infection by its completion. The origination of this outbreak stemmed from a wrestler who had a history of herpes labialis but chose not to receive suppressive therapy. In 2001, an HG outbreak took place at the same camp, however, this time 330 wrestlers between the ages of 13-18 had signed up. The wrestlers were divided into five groups of 66. Within five days of the start of the camp, three of the groups had an HG outbreak that eventually spread to members of the other groups. Eventually, 57 or 17% of the participants had contracted the HG infection by the end of camp. The HG outbreaks that occurred in 2000 and 2001, while unfortunate, represent the foreseeability of the occurrence of herpes gladiatorum for interscholastically aged participants. As such it is the responsibility of an institution, coach or sponsoring organization to initiate procedures to protect the participants against becoming infected with HG.

Impact The timing was critical in this case as the ban on competition extended to one week prior to sectional championships that served as the qualifying rounds to the state tournament. In other words, wrestlers were not allowed to participate in essential contact practice or competition until the week immediately preceding the qualifying rounds and championships. By preventing them from honing their skills, some young athletes may have been deprived of participating in the state tournament. For example, a coach from a team that has finished very well in recent state wrestling championships did not perceive the situation to be fair, predominately because his team did not have a recorded case of herpes (Millea, 2007). The coach continued to express concern regarding that the lack of preparation could prevent his team from doing as well as he had planned, increase the potential for injuries due to the lack of conditioning, and how this situation may affect individual’s chances of obtaining an intercollegiate wrestling scholarship. Thus, the impact of HG may significantly affect the lives of young interscholastic wrestlers in potentially losing a scholarship or experiencing the thrill of participating or winning a state championship. Another type of impact that may develop in the near future concerns potential litigation. At least one court has recognized a new tort of negligent transmission of herpes gladiatorum – that a wrestler owed another wrestler a duty based on the defendant’s knowledge of his herpes blister and the degree of the skin-to-skin contact inherent in wrestling. In Silver v. Levittown (1999) though the court was “…loathe to create new causes of action in tort, the law must nevertheless adapt to the society in which it exists.” This case was settled out of court with the defendant receiving $190,000. While not precedent setting, the Silver case may provide an insight into the potential future litigation that may occur if schools sponsoring wrestling and wrestling coaches continue to overlook infectious diseases such as herpes gladiatorum.

Implementing Procedures The primary objective of risk management is to allow individuals and organizations to distinguish the risks into discrete categories and to identify possible alternatives to alleviate the impact of the risk. However, some of these risks may be inherent to the sport of wrestling.

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Risk of injury is inherent at all levels of participation in sport. Inherent risk relates to the conduct of the game and the activities that the athletes are required to do. For example, football players are expected to collide into each other to tackle and block, thus creating a potential for injury. However, to take away blocking and tackling would take away the essence of the sport. Thus, injuries due to blocking and tackling cannot be taken out of the sport of football even though they may create situations of injury. In wrestling there are many risks that need to be attended to, such as concussions, strains, and sprains due to collisions. These risks are considered inherent to the sport of interscholastic wrestling and it is understood that they may occur through a season. However, the risk of contracting an infectious disease such as herpes gladiatorum is not one that may be considered as inherent since it is not a required activity within the sport. Yet, as explained earlier it can be a significant risk to an athlete, especially a wrestler. During the traditional wrestling season teams often compete in dual or quadrangular meets during the week as well as weekend tournaments. As a result checks for skin lesions or abrasions that may indicate the presence of HG are sometimes not conducted prior to performed competition. In fact the National Federation for High School Sports (NFHS) guidelines do not require skin checks prior to each contest, although wrestlers found to have obvious lesions are suspended from participation supports this (NFHS, 2000). Additionally, it is enough for a wrestler’s personal physician to provide a statement that the lesion is not transmissible to allow the wrestler to compete (Anderson, 2003). However, Anderson (2003) indicated that certain factors have been shown to increase the likelihood of HG outbreaks. The primary factor cited was the dependence on the physicians of individual wrestlers to diagnose the presence of HG. Yet, many of these physicians do not understand how HG develops and spreads to others (Anderson, 2003). The NATA has recommended that wrestling participants should shower prior and after workouts, wash workout clothes everyday, dry their skin well, avoid wearing street shoes on wrestling mats or wrestling shoes outside and conduct total body skin inspections each day. The NCAA standards also differ from the NFHS in that skin checks are recommended at all wrestling contest. Moreover, a compendium of symptoms is at hand at each contest as a criterion for withdrawal if an individual is suspected of being infected (NCAA, 2003). Finally, NCAA guidelines recommend that only certified athletic trainers or physicians experienced in recognizing the symptoms conduct skin checks.

CONCLUSION As stated earlier, the likelihood of an interscholastic wrestler contracting herpes gladiatorum is relatively high when compared to other high school sports. This is obvious within this case study as three outbreaks of HG have been cited occurring in one specific state. As a result it becomes a foreseeable risk that wrestlers, coaches, and organizations should attempt to better manage, especially since current high school guidelines seem somewhat ineffective in controlling potential HG outbreaks. To better address such outbreaks the recommendations established by the NATA and the NCAA are excellent sources from which to develop an effective risk management plan. Secondly, increased education regarding HG and diagnosis of it of sport medicine personnel

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affiliated with wrestling programs is strongly encouraged. Finally, the authors encourage those involved in interscholastic wrestling to enforce a risk management plan once it has been developed. To do so may prevent a young athlete from unnecessarily contracting a disease that may affect him for the rest of his life.

REFERENCES American College of Sports Medicine. (2003). Organization plan to reduce herpes gladiatorum outbreaks through earlier diagnosis and treatment. Retrieved February 15, 2007, 2007, from http://www.acsm.org/AM/ Template.cfm?Section=Search&template=/CM/HTMLDisplay.cfm&ContentID=4254. Anderson, B. J. (2003). The epidemiology and clinical analysis of several outbreaks of herpes gladiatorum. Medicine andScience in Sports andExercise, 35, 1809-1814. Anderson, B. J. (1999). The effectiveness of valacyclovir in preventing reactivation of herpes gladiatorum in wrestlers. Clinical Journal of Sport Medicine, 9, 86 - 90. Anderson v. Pine Knob Ski Resort, Inc., 469 Mich 20, 664 N.W.2d 756 (2003). Becker, T. M., Kodsi, P., Lee, F., Levandowski, R., andNahmias, A. J. (1988). Grappling with herpes: Herpes gladiatorum. American Journal of Sports Medicine, 16, 665 - 669. Dworkin M.S., Shoemaker P.C., Spitters C., Cent, A., Hobson, A., Vieira, J., Corey, l., Frumkin, L. (1999). Endemic spread of herpes simplex virus type 1 among adolescent wrestlers and their coaches. Pediatric Infectious Disease Journal, 18(12), 1108-1109. Maine Epi-Gram: Infectious Epidemiology Program. (2000). Herpes skin infections among wrestlers: A clinician alert. Retrieved February 15, 2007 from http://www.maine.gov/dhhs/bohepi/Jan%2000.htm#HERPES%20 SKIN%20INFECTIONS%20AMONG%20WRESTLERS:%20A%20CLINICIAN%20A LERT. Makropoulos, M. (1997). Modernitat und Kontingenz. Munich: Wilhelm Fink Verlag. Millea, J. (2007). 7,500 state wrestlers have season put on hold. Retrieved February 15, 2007, from http://www.startribune.com/526/story/969346.html National Collegiate Athletic Association. (2005). NCAA sports medicine handbook, 2005 2006. Retrieved February, 15, 2007, from http://www.ncaa.org/library/sports_sciences/ sports_med_handbook/2005-06/2005-06_sports_medicine_handbook.pdf National Collegiate Athletic Association Wrestling Championships Handbook. (2003). Appendix D, WA-11-14. Indianapolis, IN. National Federation of State High School Associations Wrestling Handbook. (2000). Rule 42-2, 3. Indianapolis, IN. Simmons, A. (2002). Clinical manifestations and treatment considerations of herpes simplex virus infection. Journal of Infectious Diseases, 186, S71-S77. Selling B, and Kibrick, S. (1964). An outbreak of herpes simplex among wrestlers. New England Journal of Medicine, 270, 979-982. Silver v. Levittown Union Free School Dist., 692 N.Y.S.2d 886 (Sup. Ct. Nassau County 1999).

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Stahl, B. C., Lichtenstein, Y., andMangan, A. (2004). The limits of risk management–a social construction approach. Communications of the International Information Management Association, 3(3), 15-22. MSHSL transcript press conference. (2007). Retrieved February 15, 2007 from http://www.startribune.com/526/story/973148.html Turbeville, S., Cowan, L., andGreenfield, R. (2006). Infectious disease outbreaks in competitive sports. American Journal of Sports Medicine, X(X), 1-6. Whitley, R.J., Kimberlin, D.W., Roizman, B. (1998). Herpes simplex viruses. Clinical Infectious Diseases, 26, 541–53. White, W.B., Grant-Kels, J.M. (1984). Transmission of herpes simplex virus type 1 infection in rugby players. Journal of the American Medical Association, 252, 533-535. World Health Organization. (1985). Prevention and control of herpesvirus diseases (part 1). Clinical and laboratory diagnosis and chemotherapy. A WHO meeting. Bull World Health Organization, 63, 185 201.

Contemporary Athletics Compendium, Volume 3 Editor: James H. Humphrey

ISBN: 978-1-60741-561-9 © 2009 Nova Science Publishers, Inc.

Chapter 2

CAN SPECTATORS’ MOOD BE MANIPULATED AND MAINTAINED IN A LOSING GAME?: INTERACTION BETWEEN TEAM IDENTIFICATION AND PRE-GAME MOOD Hyungil Harry Kwon∗1, Chulwon Lee2 and Sang-il Lee3 1

Florida State University, Tallahassee, Florida, USA 2 Yonsei Univeristy, Seoul, South Korea 3 Sookmyung Women’s University, Yongsan-gu, Seoul, South Korea

ABSTRACT The current study addressed two research questions. First, study 1 examined whether spectators’ mood before they were exposed to a losing game (i.e., pre-game mood) influenced their mood after the game (post-game mood) and their information processing. Secondly, study 2 examined whether the influence of pre-game mood found in Study 1 was modified by personal relevance (i.e., team identification) with a sporting game. The results indicated that pre-game mood influenced participants’ post-game mood and information processing system. The results of the second study also supported the hypotheses that post-game mood and spectators’ information processing were influenced by pre-game mood and personal relevance (i.e., team identification). As hypothesized, two-way interaction between pre-game mood and personal relevance was found in postgame mood whereas no interaction was found in information processing. This study was able to identify a group of people who were more affected by the result of home game and who more effectively responded to mood manipulation.

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Correspondence concerning this article should be addressed to Dr. Hyungil Harry Kwon, Assistant Professor, Sport Management, Recreation Management, and Physical Education Department, Florida State University, 120A Tully Gym. P. O. Box 4280. Tallahassee, FL 32306-4280. Phone # (850) 645-2350. Fax (850) 6440975. Electronic mail may be sent via Internet to [email protected].

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INTRODUCTION Marketing scholars and practitioners have been interested in how consumers react to a product trial. In particular, a large body of literature is available in service marketing in relation to customer satisfaction (Alford and Sherrell, 1996; Dube and Menon, 2000; Lijander and Strandvik, 1997; Oliver, 1997). In many different service industries, the causal relationship among affective state of customers, satisfaction, and behavioral intention (e.g., future repatronage) has been found and confirmed repeatedly. In spectating sport service, the relationship between post-game affective state (e.g., enjoyment) and future fan behaviors (e.g., future game attendance, licensed merchandise purchase) has been confirmed through confirmatory manner such as structural equation modeling (i.e., Madrigal, 1995; Trail, Fink, and Anderson, 2003). However, knowing that sport marketers have no control over the performance of a sporting game (i.e., sport marketers cannot guarantee spectators having positive affect after a sporting game), a confirmation of the positive causal relationship between affective state after a game and future repatronage has little practical value to sport marketers. Thus, a line of research regarding how to influence and manipulate the post-game affective state of spectators is necessary for aforementioned relationship to have a practical value. The current study, through two experimental studies, attempted to see whether an affective state of spectators (i. e., mood) can be manipulated, by management, to an extent that they feel less negatively after they watch a losing home game. The first study examined whether a manipulated positive mood can be maintained even after participants had negative product trial (i.e., watching a losing game of a home team) and whether this causes different type of information processing (i.e., amount of cognitive elaboration). The second study attempted to examine the effect of mood state and personal relevance (i.e., team identification) before a product trial on the evaluation of a negative product trial (i.e., a losing game). The second study also examined whether the effect of pre-game mood was modified by personal relevance (i.e., team identification). The ultimate objective of the two studies is to identify the characteristics of the spectators (i.e., in terms of the team identification) who are more susceptible to negative game outcome and mood manipulation. Sport marketers, with this information in their hands, can identify a group of spectators whose negative feeling actually can be remedied, to a certain extent, by receiving any incentive that makes them happy. The study is based on dual information processing (Chaiken, Giner-Sorolla, and Chen, 1996), elaboration likelihood model (ELM, Petty and Cacioppo, 1986), and affect infusion model (AIM, Forgas, 1995) as its theoretical bases.

STUDY 1 Sport Consumers and Game Outcome Sport spectators’ affective state is largely determined by the results of a game (Trail, Fink, and Anderson, 2003). Empirical supports can be found in Madrigal (1995) and Trail, Fink, and Anderson (2003). Madrigal (1995) developed the Model of Fan Satisfaction, in which a causal relationship between expectancy confirmation (i.e., win or loss) and

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enjoyment was hypothesized and confirmed. Trail, Fink, and Anderson (2003) also confirmed a causal relationship between expectancies (dis) confirmation and affective state. Further influence of affective state after a game on satisfaction (Madrigal, 1995) and future fan behavior (Trail et al., 2003) were also confirmed in the literature. Spectators with positive affective state after a confirmation of expectancy are expected to have a positive affective state (e.g., happy) and it leads to customer satisfaction and more repatronage in terms of game attendance and licensed merchandise sales. The causal relationship between game results, affective state, satisfaction, and future fan behavior provided a marketing implication that sport teams need to win every game or, at least, perform well up to the expectation of customers to make them happy, which is quite impossible. For this reason, frameworks in affect and information processing were explored to see whether affective state (e.g., mood) of spectators can be manipulated and maintained using non-performance related variables in spectating sport environment. Among those, major thesis of the current study is based on the evidence that mood of people can be maintained (e.g., Handley, Lassiter, Nickell, and Herchenroeder, 2004; Isen and Patrick, 1983; Isen and Simmonds, 1978).

Mood and Its Maintenance People in positive mood perceive things in a more positive way (Bower, 1981; Carlson and Adams, 1980; Clark and Teasdale, 1985; Forgas, Bower, and Krantz, 1984; Isen, Shalker, Clark, and Karp, 1978). This process of priming puts oneself in a loop of positive thinking. Thus, people in a positive mood evaluate an event more positively than people in neutral or negative mood (Clark and Isen, 1982). The maintenance of the mood depends on how long and how intensively a person can stay in the loop of positive thinking. It is obvious that people can stay longer in a positive mood if he/she experiences more subsequent happy events. The people in positive mood try to engage themselves in a happy situation (e.g., helping others) so that they can extend the time period of being in positive mood (Isen and Simmonds, 1978). Isen, Clark and Schwartz (1976) examined the duration of the effect of a good mood. Their experiment started with mood manipulation; the positive mood was manipulated by giving away a free sample of stationery, which was about 20 cents worth. The participants were divided into two groups; the ones who received the free stationary and the ones who did not receive anything. All the participants received wrong number phone calls during which they could provide help to the caller. They counted the number of subjects who helped and who did not help to determine group differences. Measuring the percentage of subjects who helped in different time after receiving the incentive, the researchers found that participants in the treatment group (i.e., free stationary) helped more than the participants in the control group (i.e., no incentive). They also found that the effect diminished gradually over time; the two groups showed no difference after 20 minutes. The results indicated that the percentage of who helped was greatest in the five minutes condition (100%), while the percentage gradually declined to the same level (10%) as the control group after 20 minutes. Another line of research proposed the same mood maintenance mechanism with the emphasis on information processing. This line of research focuses on how people process incoming information in different mood states. Chaiken et al. (1996) argued that people in a

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positive mood incorporated rapid and less effortful strategies in solving a problem. People want to prolong their positive mood by disengaging themselves from processing any negative information (Batra and Stephens, 1994). This phenomenon was clearly detected in Isen and Simmonds’ (1978) study, in which people in good mood were more likely to help someone if the helping tasking is reading pleasant information but help less if the information is negative. Based on the previous literature it can be conjectured that people in positive mood actively protect the current good mood by engaging themselves in pleasant events or by blocking themselves from negative information. Thus, it is cautiously speculated that if spectators are manipulated to be in a positive mood, they may try to maintain the positive mood and show a better mood after they watch a losing game than the ones who are not manipulated to be in a positive mood. The losing game can provide many different types of negative information to the spectators (e.g., bad formation, bad strategies, bad call, etc.). However, the ones in a positive mood will be blocking negative incoming information more than the ones in a neutral or negative mood. Based on this theorizing, a hypothesis was generated as below. Hypothesis 1: Participants in a positive pre-game mood will show better post-game mood than the participants in a negative pre-game mood group after they are exposed to a losing game.

Negative Product Trial and Information Processing Along with a mood state, this study is also interested in how sport consumers react to a losing game when they are in different mood states. People are expected to incorporate different type of information processing in different situation. This phenomenon has been explained with ‘dual information processing system’ of Chaiken et al (1996). Chaiken and her colleagues suggested that information be processed with either heuristic or systematic information processing system. Heuristic processing is performed by the application of simple decision rules instead of elaborating on all of the incoming information. The simple decision rules can be from a person’s past experience or memory, which facilitate his/her processing similar incoming information. In contrast, systematic processing takes more effort to process the information and results in more elaboration. Therefore, any judgment decision based on systematic processing is thought to be more comprehensive and elaborate (Chaiken et al., 1996). The spectators in a better mood are expected to have less concerns and thoughts on negative product trial (i.e., watching a losing game) than the ones in neutral or negative mood because of the selection of heuristic information processing over systematic information system. Empirical evidence can be found in Batra and Stayman (1990). They measured respondents’ cognitive elaboration by counting the number of statements generated after they were manipulated to be in two different mood states (i.e., neutral mood and positive mood). The authors found that people in a positive mood generated statistically less number of statements than the people in neutral mood. Thus, it can be expected that the spectators in a positive mood engage in a heuristic information processing and, as a result, produce less comments and thoughts about negative incoming information (i.e., a losing game) than the ones in a negative mood group. Thus, a hypothesis was generated as below.

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Hypothesis2: Participants in a positive pre-game mood should generate less statements regarding the losing game than the participants in a negative pre-game mood In the two hypotheses, the term ‘positive mood group’ and ‘negative mood group’ were used in relative sense than absolute meaning. The positive mood group indicates the participants whose mood state is more positive than the participants in a negative mood group. Thus, the participants in negative mood group do not necessarily have negative affect in absolute term. It simply implies that their mood state is less positive than the ones in a positive mood group.

METHOD Participants Data were collected from 73 students (male = 38, female = 35) who were enrolled in two different classes in sport management program at a large Mid-western university in the United States. The average age of the participants was 20.8 (SD = 2.64). A student sample for this study was considered to be viable because of a couple of reasons. First, college students represent a large portion of the spectators of college football games. Second, college spectators’ reaction to a losing game is not expected to be different from other populations’ reaction in an experimental environment.

Covariates This study incorporated two covariates of team identification and familiarity to football based on close relationships with dependent measures of the study. Madrigal (1995) found that the correlation between team identification and enjoyment was as high as .41. Wann and Schrader (1997) found a similar result in that spectators with higher team identification scored higher on sport spectating enjoyment in a winning game. Due to the known high correlation, team identification was incorporated as a covariate in the study design. In addition to team identification, familiarity to football was also included as a covariate in the current study. Familiarity to football variable measured how the participants were familiar to the game of football, its rules, and its strategies. Previous research has showed that spectators with higher team identification are more knowledgeable upon sport and team related information than spectators with lower team identification (Wann, Morris-Shirkey, Peters, and Suggs, 2002). It was conjectured that the spectators with better knowledge about the football should be able to analyze the game more thoroughly. Thus, in case of a losing game, spectators with good knowledge of football will be aware of the poor strategies in the field and errors that players make, which ignorant spectators would not be able to recognize. The level of knowledge should have positive correlation with the quantity of negative information that spectators process in a losing game because spectators with increased knowledge should be able to identify more negative things in a losing game. Based on the

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positive relationships of team identification and familiarity to football with spectators game experience, both variables were included as covariates in this study.

Measurements Three items of Team Identification Index (Trail and James, 2001) were included in the questionnaire to measure the level of psychological attachment to school football team: I consider myself to be a “real” fan of the team; I would experience a loss if I had to stop being a fan of the team; and Being a fan of the team is very important to me. The scale has shown a good validity and internal consistency in previous studies (Fink, Trail, and Anderson, 2002; Trail et al., 2003; Trail and James, 2001). All the items were anchored with seven point Likert scale (1 = strongly disagree, 7 = strongly agree). Three items were developed for this study to measure how participants were familiar to football. The items asked how familiar they were to football, whether they know the strategies used in football, and whether they actually watch football games. Three items were also anchored with seven point Likert scale (1 = strongly disagree, 7 = strongly agree). Participants’ mood was assessed using four items. The items asked whether they were happy, elated, pleased and in good mood. These items were the most common mood items used in previous studies (i.e., Barone, Miniard, and Romeo, 2000; Lee and Sternthal, 1999). The four items were also anchored in seven point Likert scale (1 = strongly disagree, and 7 = strongly agree).

Procedure All the participants were randomly divided into a treatment group ($1 free giveaway) and a control group (no free gift) by drawing numbers randomly. All the participants were given a number before the drawing. From a box that has numbers from 1 to 73, the researcher drew 33 numbers to give away an envelop that included one dollar bill. The drawing method was used to make sure that the participants were chosen randomly into two different groups and the experimental situation was very close to real situation (i.e., sport spectators receiving free stuffs randomly at a sporting game). Free award has been utilized in many mood studies to manipulate participants’ mood when pre-test is not feasible and it has been proven to be successful (i.e., Isen and Levin, 1972; Blevins and Murphy, 1974). This study did not incorporate any mood measure after the participants received $1 bill. That is based on two reasons. First, previous literature incorporated free cookies, dime, 20 cents worth free gift, etc. to put people in a better mood than their counterparts and it was very successful. For example, Isen, Clark, and Schwarts (1976) used a free stationary that was 20 cents worth. If we assume that there has been 3% inflation annually in average. It would be around 50 cents in current value. The study gave away $1 to the participants in a treatment group and it was highly expected that their mood became better than the ones in a control group. The drawing process should have moved the mood of control group further to a negative side because the treatment group received the $1 bill in the presence of control group, who did not get anything. This method should have maximized the gap between the treatment group and control group. The second, the researcher was worried about the participants’ answering two

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similar scales (i.e., pre and post mood scales) in seven minutes. It has been known as a threat to internal validity and external validity of a research (Hyllegard, Mood, and Morrow, 1996). The participants may be sensitized to the scale and it may influence the participants’ answers to the second administration of mood scale. This might be leading to another threat to external validity (i. e., Hawthorne effect) when the participants recognized that they were tested on mood based on the result of a sporting game that they just watched. All participants (a control group and a treatment group) were asked to fill out the Fan Identification Index (Trail and James, 2001) and familiarity to football items before they were exposed to a video clip containing a losing game of the university football team in 1989. This game was chosen because the participants were not likely to remember or have watched the game. The video clip was an edited version of the game lasting seven minutes, in which all the good plays of the opponent team were purposely shown. Even though Isen, Clark and Schwarts (1976) found the effect of positive mood to be around 20 minutes, the length of the video clip was shorter than that. This is because the participants, in the current study, were exposed to negative information for seven minutes whereas the respondents in Isen et al. were kept in their daily routine. It was a very close game in which the home team lost by one point. The opponent has known to have a better football program than the home team. There was no clear rivalry between the two teams. After the participants finished watching the video clip, they were asked to fill out fouritem mood scale. After answering the four mood items, they were asked to write down what they felt about the game for 10 minutes. In the questionnaire, 13 blank lines were provided for the verbal responses. The researcher told the respondents to ask for extra blank paper if they needed it for additional comments. No respondent did so. The participants generated total of 571 statements regarding the team, players, coach, and the plays in the game. The research simply counted the number of statements and coded for further statistical analyses.

RESULTS The data were analyzed with a MANCOVA with two covariates of team identification and familiarity to football. In the analysis, the independent variable of mood had two levels (positive and negative) and dependent variables were post-game mood and total number of statements. The composite mean score of team identification was over the median value of 4 (M = 4.71, SD = 1.93). The level of familiarity to football had composite mean score of 5.04 (SD = .92) on a seven point scale. The minimum value was 3.33, which indicated that most of the participants were very familiar with football. With the composite mean scores of three constructs (team identification, familiarity to football, and mood), Pearson correlation coefficients were calculated (see Table 1) to see if the covariates met the criterion to be an effective covariate. Hair, Anderson, Tatham, and Black (1998) indicate that an effective covariate should have good correlation with dependent measures. The Pearson correlation between FF (familiarity to football) and post-game mood was -.47 (p < .001). The Pearson correlation between TID (team identification) and post-game mood was -.37 (p < .001). Thus, the two covariates included in this study met the criterion of Hair et al. (1998). To examine the equivalence of covariance matrices across the groups, Box’s test of equality was

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Hyungil Harry Kwon, Chulwon Lee and Sang-il Lee

performed. The results indicated that the two groups’ covariance matrices were statistically not different (p = .133). Table 1. Correlations among Dependent Measures (Study 1) 1 Total Number of Statements Number of Strong Counterarguments Number of Moderate Counterarguments **

2 .343**

3 .508** .060

Correlation is significant at the .01 level.

A MANCOVA with two covariates (FF and TID) was performed with the dependent variable of post-game mood and total number of statements. The results indicated that dependent measures were statistically different by groups (Wilks’ Lambda = .357, F = 61.34, p < .001, ηp2 = .643). The analysis maintained good level of power (1.0). Follow up univariate analyses indicated that the treatment group showed better post-game mood than the control group (F = 30.51, p < .001, ηp2 = .307) and provided less statements regarding the home team and the game (F = 98.25, p < .001, ηp2 = .587). The results of the MANCOVA supported the first and second hypothesis.

DISCUSSION The first hypothesis was supported. The participants who received $1 before they were exposed to a losing game showed better mood than the participants in the control group. The partial eta square indicated that pre-game mood manipulation explained 30.7% of the postgame mood. Given the small amount of effect size found in two covariates (.044 for familiarity to football and .001 for team identification), the effect of pre-game mood found to be the most significant factor in this analysis. Along with the first hypothesis, the second hypothesis was also supported by the result of the MANCOVA analysis. The control group had more statements regarding the game and the home team than the treatment group, which supported that the participants in negative mood group utilized more systematic information processing than the participants in positive mood group. Even though study 1 revealed the effect of pre-game mood on post-game mood and cognitive elaboration with good effect size, the study needed to address several limitations before the results could be utilized in more sophisticated manner and with more validity.. The first set of limitations was from its selection of participants. As shown in the studies with student samples, this study also had high level of team identification. Even though the data distribution for TID was quite normal (Skewness: -.50; Kurtosis: -1.16), the lowest value of the composite mean score of TID was 2.67 out of 7 whereas the highest mean score was 7.00. Because of the absence of such cases, data analysis with low end of TID was not feasible. Second, the mean score for FF (familiarity to football) was exceptionally high (M = 5.04). This was also stemmed from the characteristic of the participants. The participants were students majoring sport management. Thus, it can be assumed that they had higher level of interest in sport than other populations on campus.

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Another limitation can be found in the nature of the covariates. The covariates of team identification and familiarity to football were included based on the zero-order correlations with dependent variable. However, the correlations by two levels of independent groups (i.e., treatment group and control group) showed different results. Their part correlations with dependant variable of mood was not significant (r = .10 and -.30 for team identification and familiarity to football respectively). Their correlations to total numbers of statements were not significant either (r = -.11 and .18 for team identification and familiarity to football respectively). Hair et al. (1998) indicated that researchers can eliminate the covariate if there is not any substantial improvement with the covariate. Another MANOVA with mood and total number of statements was performed to examine the quality of the covariates based on Hair et al.’s (1998) suggestion. The comparison between MANOVA and MANCOVA results indicated that the covariates actually increased the within-group variance and resulted in decreasing the F statistics from 73.48 to 61.34. In addition to F statistics, the covariates reduced the partial eta square from .677 to .643. Thus, the covariates in this study were found not to improve the results and could be eliminated from the data analyses based on Hair et al. (1998). Based on the results and limitations of the study 1, study 2 was planned using additional theoretical support from affect infusion model (AIM, Forgas, 1995) and elaboration likelihood model (ELM, Petty and Cacioppo, 1986).

STUDY 2 Study 1 examined whether a manipulated mood before a negative product trial (i.e., a losing home game) influenced consumers’ post-consumption mood and cognitive elaboration. To advance the results of the first study, study 2 incorporated a level of personal relevance to a product in research hypotheses. A previous literature called for a study regarding the effect of the strength of prior preference to a product on the resultant attitude from a negative product trial (Jain and Maheswaran, 2000). Jain and Maheswaran (2000) found that preference-inconsistent information was processed more systematically and was counterargued more than preference-consistent information. The preference-inconsistent information is such information that is incongruent to previously held idea about a product. The authors, however, were not able to examine the effect of the strength of prior preference because they manipulated the prior preference to be high for their study. In addition to Jain and Maheswaran (2000), Batra and Stephens (1994) found that mood and emotions evoked by advertisements appeared to influence brand attitude more in low personal relevance (motivation) situations than under high relevance (motivation) situations. However, they could not examine a main effect of mood because the participants’ mood was set positive across experimental groups. The current study attempted to test what were not tested in Jain and Maheswaran (2000) and Batra and Stephens (1994) because of their research design. Study 2 has its theoretical bases on affect infusion model (AIM) of Forgas (1995), dual information processing (Chaiken et al., 1996), and elaboration likelihood model (ELM) of Petty and Cacioppo (1986). Study 2 was designed to identify the characteristics of sport consumers (i.e., in terms of the level of team identification) who are more affectively influenced by a negative game outcome and susceptible to mood manipulation. If those consumers are identified, sport marketers can target those spectators and provide any

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Hyungil Harry Kwon, Chulwon Lee and Sang-il Lee

incentives to make them feel less negatively about the game outcome. When resource is limited, this strategy should be able to make the most use out the limited marketing resources.

Influence of the Mood in Different Levels of Personal Relevance Previous literature has indicated that the effect of mood should not be the same in different level of personal relevance. As noted earlier, Batra and Stephens (1994) found that mood and emotions evoked by advertisements appeared to influence brand attitude more in low personal relevance situations than under high relevance situation. Theoretical basis can be found in affect infusion model of Forgas (1995). Forgas suggested that the role of mood should be limited when people were performing a task through a preexisting goal, which was termed ‘motivated processing’ in his affect infusion model. Thus, it can be conjectured that people should be influenced more by mood when they are involved in an event that has less personal relevance. In spectating sport, the level of personal involvement and relevance has been termed as ‘team identification’. If the thesis of Forgas can be applied to sport spectating environment, the spectators with low team identification are expected to be influenced more by mood manipulation than the ones with high team identification. This speculation is now linked to the results of the first study, in which a manipulated pre-game mood actually influenced participants’ post-game mood. If pre-game mood manipulation works differently for the high team identification group and low team identification group, an interaction between pre-game mood and fan identification is expected. This is the major objective of the current study and a hypothesis was developed based on this theorizing. Hypothesis 1: Participants in a positive pre-game mood group will show a better mood after watching a losing game than the participants in a negative pre-game mood and this mood effect will be stronger for participants who are low in team identification

Cognitive Elaboration by Different Mood State and Personal Relevance Study 1 measured the total number of statements after a negative product trial to examine consumers’ post-product trial mood and information processing. The number of statements generated by participants differed by their mood states as hypothesized. In addition to dual information processing and affect infusion model, elaboration likelihood model (ELM, Petty and Cacioppo, 1986) can be added to explain how people process incoming information based on personal relevance of the information. Petty and Cacioppo (1986) indicated that people processing incoming information and thus persuaded through two different routes; central route and peripheral route. People can use central route when the information has a certain level of personal relevance and when an individual has a capacity of processing the information. This central route involves high elaboration such as evaluation, recall, critical judgment and inferential judgment. On the other hand, people use peripheral route when the information has little personal relevance and they are not capable of processing information, which involves less cognitive elaboration. Combining dual information processing theory (i. e., different information processing by different mood states) and ELM (i. e., different cognitive elaboration by different level of personal relevance), it can be conjectured that

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cognitive elaboration should be moderated by different mood states of an individual and this effect is expected to be larger in low personal relevance situation. Thus, a group of spectators in a positive mood should be engaged in a less cognitive elaboration (c.f., dual information processing) and, among those, a sub-group with low relevance (i.e., participants with low team identification) should use peripheral route, which results in even less cognitive elaboration. A hypothesis was developed as below. Hypothesis 2: Participants in a positive pre-game mood group will show less cognitive elaboration after watching a losing game than the participants in a negative pre-game mood group and this mood effect will be stronger for participants who are low in team identification. The proposed two hypotheses were tested using a MANOVA. Differently from Study 1, Study 2 did not incorporate any covariate based on the discussion of study1. Instead, personal relevance, measured with team identification, was incorporated as an additional independent variable.

METHOD The manipulation and the measurements for study 2 were very similar to Study 1. The data were collected from a larger number of participants than Study 1 and, thus, it was possible to incorporate another independent variable of team identification maintaining proper cell size. In addition to the size of sample, Study 2 solicited data from non-sport related major students to maximize the variance in team identification and to improve the generalizability of the results.

Participants, Material, and Procedures The data were collected from 127 students (male = 67, female = 62) who were enrolled in the classes in the animal science department and interior design program at a large Midwestern university in the United States. The average age of the participants was 21.03 (SD = 3.35). All participants were randomly divided into a treatment group (positive mood, n = 60) and a control group (negative mood group, n = 69) by drawing. The procedures of the experiment were exactly the same as Study 1. All the participants were asked to fill out a Fan Identification Index (Trail and James, 2001) before they were exposed to the video clip. A manipulation check for mood was not incorporated with the same ground as in the study 1. After the participants finished watching the video clip, they were asked to fill out threeitem mood scale. After answering the three mood items, they were given 10 minutes to write down what they felt about the game and the team. The questionnaire contained 13 blank lines for the verbal responses. The researcher told the respondents to ask for extra blank paper, if needed, for additional comments. No respondent did so. Total of 1,243 statements were generated by the participants.

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RESULTS The data were analyzed using a MANOVA. The analysis included independent variables of pre-game mood (positive and negative) and team identification (high and low). The dependent variables included post-game mood and cognitive elaboration which is represented by the total number of statements. The descriptive statistics were calculated with SPSS. The composite means and standard deviations by groups (pre-game mood and team identification) are presented in Table 2. The MANOVA results indicated, as hypothesized, an interaction between pre-game mood and team identification (Wilks’ Lambda = .898, F(2, 124) = 7.07, p = .001; ηp2 = .102). Follow-up univariate analyses, however, indicated that the interaction was statistically significant only on post-game mood (F(1, 125) = 12.68, p = .001; ηp2 = .092). The difference in post-game mood was larger in a low team identification group than a high team identification group. In both analyses, power levels were maintained above .92. No interaction was found in the dependent measures of total number of statements F(1, 125) = 1.70, p = .195; ηp2 = .013). Thus, only hypothesis 1 was supported. Along with the hypothesized interaction, main effect of team identification and pre-game mood was also examined. The results indicated that main effects also existed. The group differences were found in terms of pre-game mood (Wilks’ Lambda = .317, F (2, 124)= 133.61, p < .001; ηp2 = .683) and team identification (Wilks’ Lambda = .757, F(2, 124) = 19.90, p < .001; ηp2 = .243). Follow up univariate analyses indicated that main effects of pregame mood were found on the three dependent variables. The post-game mood was found to be statistically different by the pre-game mood (F(1, 125) = 140.26, p < .001; ηp2 = .529). The participants with better pre-game mood showed better post-game mood. Table 2. Descriptive Statistics of Dependent Variables by Groups (Study 2)

Mood Total

Positive Pre-game Mood High ID LoID M(SD) M(SD) N= 31 N = 29 5.28 (.54) 6.42 (.36) 7.08 (2.04) 6.89 (2.21)

Neutral Pre-game Mood High ID LoID M(SD) M(SD) N = 42 N = 27 4.06 (1.17) 4.17 (.77) 11.61 (1.21) 10.63 (1.50)

Total High ID M(SD) N = 73 4.58 (1.13) 10.36 (2.02)

LoID M(SD) N = 56 5.34 (1.28) 8.70 (2.66)

The total number of statements generated also had statistically significant group differences (F(1, 125) = 132.75, p < .001; ηp2 = .515). The participants in the treatment group showed less number of statements than the ones in the control group.

DISCUSSION The second study incorporated two independent variables of pre-game mood and personal relevance (i.e., team identification) to examine whether pre-game mood moderated the post-game mood after participants watched a losing game and whether the mood effect was greater in low team identification situations. The results indicated that the participants in the positive pre-game mood showed better post-game mood than the ones in a negative pregame mood group, which replicated the result of study 1 sucessfully. Furthermore, the

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difference in post-game mood was greater in the low team identification group (see Figure 1) than its counterparts, which supported the argument that mood effect is limited in motivated processing (Forgas, 1995). Thus, we can say that the spectators with low team identification may be more influenced by pre-game mood manipulation than the ones with high team identification. The participants with better pre-game mood showed that they actually suppressed the cognitive elaboration and generated less statements regarding the game. The mean score for the total number of statements was statistically lower for the participants with positive pregame mood. The main effect of team identification also followed the pattern. The participants with high identification actually generated more statements regarding the team and the games, which can be explained by their post-game mood. The participants with higher team identification showed worse post-game mood and thus incorporated systematic information system. This result also can be explained with ELM (Petty and Cacioppo, 1986) in that the participants with high level of team identification processed the information with central route that incorporates more cognitive elaboration. Pre-game mood

6.50

Positive Neutral

Post-game Mood

6.00

5.50

5.00

4.50

4.00 Low

High

Team Identification Figure 1. Two-way interaction on post-game mood.

The results partially supported the interaction hypotheses. A two-way interaction effect was statistically significant in multivariate analysis. In addition, a follow up univariate analysis supported an interaction hypothesis for post-game mood. This study also hypothesized that two-way interaction should be found in total number of statements. However, the results did not support this. The pre-game mood was found to moderate two dependent measures (i.e., post-game mood and total statements) but its effect was not modified by team identification when dependent measure was the total number of statements.

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Marketing Implications The results of the study provide several marketing implications. First, even though there were mixed results in terms of cognitive elaboration, the post-game mood itself was clearly maintained as it was shown in study 1 and 2 as well. The participants in the treatment groups showed better mood than the ones in the control groups in both studies. Second, in addition to the effect of pre-game mood, this study was able to segment a group of people who were more vulnerable to pre-game mood manipulation. The results of the interaction between pregame mood and team identification found that the participants with low team identification were more influenced by the pre-game mood manipulation than the ones with high team identification. Thus, price oriented promotion or any incentive in a losing game may have the greatest effect on spectators with low team identification. This information is critical to sport marketers when promotional resource is limited. When such resource is limited, for it to be more efficient, sport marketers need to provide money-oriented promotions to customers with low team identification expecting them to have less negative mood after they watched a losing game.

Limitation and Future Research First limitation came from the length of the video clip used for the studies. The studies revealed, based on the length of the video clip, that the mood of the participants was actually maintained for seven minutes. Not many things can be done seven minutes before a sporting game is over. Thus, to improve practical value of the studies, a future study needs to examine the same effects with longer video clips. Along with the time length of the mood maintenance mechanism, future research also needs to explore possible differences in types of promotion that may manipulate sport spectators mood. This study manipulated the pre-game mood with the free giveaway of $1. However, this kind of promotion is not always feasible for sport organizations. Many different forms of mood manipulation (e. g., sample products from outside sponsors, quality of half-time show, etc.) should be tested for the results to be practically applicable to real spectating environments. Further advancement can be made by improving the variety of the study. This study, even though study 2 has more variety than study1, is quite limited in terms of variety. The study used student samples from one university. This study used American football. Thus, the results of the study cannot be generalized to other populations or different sport settings. Aforementioned shortcomings should be addressed in future research.

REFERENCES Alford, J. B., and Sherrell, L. D. (1996). The role of affect in consumer satisfaction judgments of credence based services. Journal of Business Research, 37, 71-84. Barone, M. J., Miniard, P. W., and Romeo, J. B. (2000). The influence of positive mood on brand extension evaluations. Journal of Consumer Research, 26, 386-400.

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Batra, R., and Stayman, D. M. (1990). The role of mood in advertising effectiveness. Journal of Consumer Research, 17, 203-214. Batra, R., and Stephens, D. (1994). Attitudinal effects of ad-evoked moods and emotions: The moderating role of motivation. Psychology and Marketing, 11, 199-215. Blevins, G., and Murphy, T. (1974). Feeling good and helping: Further phonebooth findings. Psychological Reports, 34 (Feb), 326. Bower, G. H. (1981). Mood and memory. American Psychologist, 36, 129-148. Carlson, T. P., and Adams H. E. (1980). Activity valence as a function of mood change. Journal of Abnormal Psychology, 89, 368-377. Chaiken, S., Giner-Sorolla, R., and Chen, S. (1996). Beyond accuracy: Defense and impression motives in heuristic and systematic information processing. In P. M. Gollwitzer and J. A. Bargh (Eds.). The Psychology of action: Liking motivation and cognition to behavior (pp. 553-578). New York: Guilford Press. Clark, M. S., and Isen, A. M. (1982). Toward understanding the relationship between feeling states and social behaviors. In A. Hastorf and A. M. Isen (Eds.), Cognitive Social Psychology. New York: Elsevier. Clark, M. S., and Teasdale, J. D. (1985). Constraints on the effects of mood on memory. Journal of Personality and Social Psychology, 48, 1595-1608. Dube, J., and Menon, K. (2000). Multiple roles of consumption emotions in post-purchase satisfaction with extended service transactions. International Journal of Service Industry Management, 11, 287-304. Fink, J. S., Trail, G. T., and Anderson, D. F. (2002). An examination of team identification: Which motives are most salient to its existence? International Sports Journal, 6 (Summer), 195-207. Forgas, J. P. (1995). Mood and judgment: The affect infusion model (AIM). Psychological Bulletin, 117(1), 39-66. Forgas, J. P., Bower, G. H., and Krantz, S. E. (1984). The influence of mood on perceptions of social interactions. Journal of Experimental Social Psychology, 20, 497-513. Hair, J. F., Jr., Anderson, R. E., Tatham, R. L., and Black, W. C. (1998). Multivariate data analysis (5th ed.). Upper Saddle River, NJ: Prentice Hall. Handely, I. M., Lassiter, D. G., Nickell, E. F., and Herchenroeder, L. M. (2004). Affect and automatic mood maintenance. Journal of Experimental Social Psychology, 20, 106-112. Hyllegard, R., Mood, D. P., and Morrow, J. R. (1996). Interpreting research in sport and exercise science. St. Louis, Missouri: Mosby-Year Book Inc. Isen, A. M. and Levin, P. (1972). Effect of feeling good on helping: Cookies and kindness. Journal of Personality and Social Psychology, 21, 384-388. Isen, A. M., Clark, M., and Schwartz, M. F. (1976). Duration of the effect of good mood on helping: “Footprints on the sands of time.” Journal of Personality and Social Psychology, 34, 385-393. Isen, A. M., and Patrick, R. (1983). The effect of positive feelings on risk taking: When the chips are down. Organizational Behavior and Human Decision Processes, 31, 194-202. Isen, A. M., and Simmonds, S. (1978). The effect of feeling good on a helping task that is incompatible with good mood. Social Psychology Quarterly, 41, 345-349. Isen, A. M., Shalker, T. E., Clark, M., and Karp, L. (1978). Affect, accessibility of material in memory, and behavior: A cognitive loop? Journal of Personality and Social Psychology, 36, 1-12.

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Jain, S. P., and Maheswaran, D. (2000). Motivated reasoning: A depth-of-processing perspective. Journal of Consumer Research, 26, 358-371. Lee, A. Y., and Sternthal, B. (1999). The effects of positive mood on memory. Journal of Consumer Research, 26, 115-127. Lijander, V., and Strandvik, T. (1997). Emotions in service satisfaction. International Journal of Service Industry Management, 8, 148-169. Madrigal, R. (1995). Cognitive and affective determinants of fan satisfaction with sporting event attendance. Journal of Leisure Research, 27, 205-227. Oliver, R. L. (1997). Satisfaction: A behavioral perspective on the consumer. New York: McGraw-Hill. Petty, R. E., and Cacioppo, J. T. (1986). The elaboration likelihood model of persuasion. New York: Academic Press. Trail, G. T., and James, J. D. (2001). The Motivation Scale for Sport Consumption: Assessment of the Scale’s Psychometric Properties. Journal of Sport Behavior, 24, 108127. Trail, G. T., Fink, J. S., and Anderson, D. F. (2003). Sport spectator consumption behavior. Sport Marketing Quarterly, 12, 8-17. Wann, D. L., and Schrader, M. P. (1997). Team identification and the enjoyment of watching a sporting event. Perceptual and Motor Skills, 84, 954. Wann, D. L., Morris-Shirkey, P. A., Peters, E. J., and Suggs, W. L. (2002). Highly identified sport fans and their conflict between expression of sport knowledge and biased assessment of team performance. International Sports Journal, 6, 153-159.

Contemporary Athletics Compendium, Volume 3 Editor: James H. Humphrey

ISBN: 978-1-60741-561-9 © 2009 Nova Science Publishers, Inc.

Chapter 3

WHY COLLEGE ATHLETES PLAY THROUGH PAIN DURING COMPETITION Jennifer J. Waldron and Nathan White University of Northern Iowa, Cedar Falls, Iowa, USA

ABSTRACT Within the environment of sport, athletes must often overlook and ignore pain and injury to be successful. In light of this, the current study, using an open-ended question, explored reasons why collegiate athletes made the decision to play through pain during competition. Male (n = 67) and female (n = 60) collegiate athletes from a variety of sports completed a demographic questionnaire and an open-ended question asking the reason why they played through pain during competition. Of the 127 participants, 77 (61%) reported that they had played through pain during competition. Data analysis included two researchers individually coding participants’ answers. Five major labels – for the self, nature of sport, for others, pain, and self-presentation – explained why athletes’ were determined to play through pain during competition. Participants’ responses suggest they have internalized the norms of the sport ethic and the culture of risk.

At some point in their career, most athletes will experience some pain due to injury. In order to examine the rate of injuries during practice and competition, the National Collegiate Athletic Association (NCAA) started the Injury Surveillance System (ISS; NCAA, n. d.). Their data reveals that football players had the highest rate of injury, and collegiate injury rates were higher in competition than practice. Perception of and being able to manage pain is an important component of coping with an injury. Furthermore, many athletes are compelled to push through their pain and continue to practice or play in a competition with their pain and injury. Both Nixon’s (1992) notion of sport as a culture of risk and Coakley’s (2004) concept of the sport ethic emphasize the norms and values athletes must adhere to in order to be

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successful. Historically, sport has been a risky venture for men as they have been encouraged to adopt a win-at-all-costs attitude. However, Waldron and Krane (2005) argue that as women gain more acceptance in the sporting environment, they too may adopt the norms and values of the sport ethic and engage in unhealthy behaviors. One of these potentially unhealthy behaviors is playing with an injury or with pain. For example, Buddy Lazier won the Indianapolis 500 in 1996 with a broken back (Coakley, 2004). This attitude was also exemplified when 29% of student athletes in a research study reported using painkilling drugs to cope with pain during competition was an acceptable action (Tricker, 2000). Within the environment of sport, athletes must often overlook and ignore pain and injury to be successful. Previous theorists have suggested that collegiate men and women may respond to athletic injuries differently (Wiese-Bjornstal and Shaffer, 1999). For example, female athletes, compared to male athletes, were more concerned about how the coach treated them after the injury and how the injury would influence their future health (Granito, 2002). Thus, it is possible that female athletes have different reasons for playing through pain than their male counterparts. Research with a youth corecreational basketball league determined that boys, as compared to girls, were held to a more limiting criterion of how to correctly respond to pain (Singer, 2004). Therefore, the purpose of the current study was to explore, using an openended question, reasons why collegiate athletes made the decision to play through pain during competition. Additionally, we examined gender differences in the reasons why athletes play through pain. It was hypothesized that a relationship between gender and reason for playing through pain exists.

METHOD Participants and Procedures After Institutional Review Board approval, coaches of collegiate teams were contacted to set up times for administration of the questionnaires to athletes. Male (n = 67) and female (n = 60) collegiate athletes from a variety of sports (e.g., softball, basketball, swimming, and wrestling) completed a demographic questionnaire as well as an open-ended question asking the top three reasons they decided to play through pain during competition. Of the 127 participants, 77 (61%) reported that they had played through pain during competition and 28 (36%) of the 77 had sustained further injury. Thus, data analysis was based on the 77 participants who had competed with pain during competition. Seventy-seven participants responded with a top reason, 69 participants responded with a second reason, and 61 participants responded with a third reason for playing through pain during competition.

Data Analysis In order to examine reasons athletes played through pain, data analysis included two researchers individually coding participants’ responses. A reliability coefficient was

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27

calculated using a percentage (Granito, 2002). That is, the number of coded agreements between the two researchers for the first, second, and third response was divided by the total number of respective responses. The reliability coefficient ranged from 89% to 95%. Five major labels and nine minor labels emerged from the data and explained why athletes’ were determined to play through pain during competition. To facilitate the examination of gender differences, each athlete’s response was entered into the Statistical Package for the Social Sciences (SPSS). That is, the nine minor labels (e.g., desire, win, team) for the first, second, and third reason were coded for each participant. A chi-square test for independence was then conducted to determine if there was a relationship between gender and reason for playing through pain.

RESULTS Results showed that athletes competed with pain for a variety of reasons. Specifically, five major labels and nine minor labels emerged for why athletes play through pain during competition (see Table 1). Of the 77 participants who competed with pain during competition, 24 (31.1%) reported the top reason was for themselves. Some of the athletes proposed that they competed with pain due to their own desire; for example, athletes stated they “wanted and needed to,” “would regret not trying,” and “had never quit anything in my life.” The other athletes reported their need to display continual effort and improvement in sport. Among these responses, athletes detailed wanting the “opportunity to play,” “doing well,” and “reach my goals.” Within the first reason, 21 (27.2%) of the athletes reported they decided to play through pain because of the nature of the sport. For example, intracollegiate competition (“proving I am worth what I get paid to do,” and “fight for spot”), intercollegiate competition (“it was nationals” and “end of season”), and winning reflected the nature of sport. Nineteen (24.6%) of the played with pain because other people. Overwhelmingly, athletes were compelled to play through pain because of their teammates, while a couple of athletes played because of their parents and coaches. Common responses included, “didn’t want to let team down,” “wanted to help team,” and “team needed me.” Finally, 13 (16.8%) of the athletes reported playing with pain during competition because of the nature of their pain. For example, athletes expressed that the “pain was bearable,” that they had “done it before,” or that they were “physically able to.” The second and third reasons for playing through pain during competition reported by athletes closely reflected the first reason specified above with one exception. Both the second and third reasons included a category labeled presentation to the team, where athletes wanted to portray a certain image to their teammates, coaches, or fans. Namely, athletes “didn’t want teammates to look down on me,” “show was tough,” or “didn’t want to be seen as weak.” A second purpose of the current study was to examine if gender differences existed among the reported responses. To answer this question, a chi-square analysis was conducted for the nine minor labels emerging from the first, second, and third reason. No significant gender differences were revealed within the first, χ2 (8, n = 77) = 7.19, p = .52, or the second reason, χ2 (9, n = 69) = 12.38, p = .19. However, a significant gender difference was found in the third reason reported for playing through pain during competition, χ2 (9, n = 61) = 18.07,

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Jennifer J. Waldron and Nathan White

p = .034. Upon closer examination, more men than expected provided reasons within the minor labels of intercollegiate competition (end of the season, for my record, etc.), wanting to win, and team presentation, while women were overrepresented in the minor label of competing for the team. Table 1. Major and Minor Labels for First, Second, and Third Reason for Playing with Pain during Competition

Major and Minor Labels For Self Desire Effort and Improvement Nature of Sport Intracollegiate Competition Win Intercollegiate Competition For Others Team Parents and Coaches Pain Bearing Pain Lack of Pain Presentation to the Team

Men

First Reason Women Total

Second Reason Men Women Total

Men

Third Reason Women Total

12 7

12 8

24 15

7 7

15 12

23 19

12 11

11 6

23 17

5

4

9

1

3

4

1

5

6

13

8

21

3

3

6

7

2

9

4

5

9

0

1

1

0

2

2

4

2

6

1

1

2

3

0

3

5

1

6

2

1

3

4

0

4

9 8

10 9

19 17

7 6

11 9

18 15

3 3

7 6

10 9

1

1

2

2

1

3

0

1

1

7 6 1

6 2 4

13 8 5

13 12 1

3 2 1

16 14 2

4 4 0

7 5 1

11 9 1

0

0

0

2

4

6

6

3

9

DISCUSSION Previous research has found that a majority of athletes believe that an athlete has to be willing to accept risks (Nixon, 1993). One of these risks is playing with pain and injury during competition. In the current study, 61% of the participants admitted to and justified why they decided to compete with pain. This suggests that the athletes had been socialized to value the culture of risk or the sport ethic. In the current study, the most frequent reported motivation was for reasons concerning the self, including desire and effort and improvement. This category indicates that athletes have internalized the importance of being competitive, having pride, and loving their sport uncritically to such an extent that they are willing to play through pain. Many athletes also responded that they were motivated to compete with pain because of the nature of sport. That is, the structural support for playing with pain, such as recognition and financial rewards (Nixon, 2004), encourage some athletes to play through pain.

Why College Athletes Play Through Pain During Competition

29

Teammates, and to a lesser degree coaches and parents, also place covert pressure on athletes. Many athletes believe that if they refused to play with an injury they would be letting their teammates down. Similarly, Charlesworth and Young (2004) reported that the most frequent motivator reported by English, female, university athletes for playing with an injury was not wanting to let down their teammates. A number of athletes also commented that they often could withstand the pain while they were playing or had play with pain in the past. Essentially, athletes have learned the culture of risk and injury. Within this culture, they ignore pain and continue to play with the pain even though this decision may result in further injury. Although the lowest number of responses emerged from the team presentation category, it is an intriguing category. Some athletes were concerned that they would present the wrong image to their teammates if they did not play in pain. In other words, athletes wanted to show their toughness and prove they were truly deserving of the athlete label. The second purpose of the research was to examine gender differences in the responses that male and female athletes give for playing through pain. Counter to the hypothesis, the chi-square analysis revealed no differences between the first and second responses given by men and women. The observed number of responses for the first and second reasons from men and women matched the expected number for each minor label. However, the chi-square analysis uncovered a significant gender difference in the third reason given for playing through pain. Specifically, men were overrepresented in the minor labels of intercollegiate competition (end of the season, for my record, etc.), wanting to win, and team presentation, while women were overrepresented in the minor label of competing for the team. Both men and women appear to possess similar motives for playing through pain during competition. This would provide evidence that women are adopting the norms and values of the sport ethic (Waldron and Krane, 2005). Gender differences did not emerge until the third reason given by the athletes. Gender differences revealed in the minor labels of the third reason reflects, to some degree, gender norms and stereotypes in our society. Gender stereotypes often suggest that women, as compared to men, value interpersonal relationships or living connected to others (DeBoer, 2004). Within the third reason, more women than expected replied they played through pain because of their teammates, which reflects the stereotype of women. On the other hand gender stereotypes often imply that men, as compared to women, do not want to be helpless and are concerned with proving themselves (DeBoer, 2004). It follows, then, that men were overrepresented in the minor labels of intercollegiate competition, wanting to win, and team presentation. There are limitations to the current study. Neither pain perceptions nor examination of different pain experiences of the athletes were measured. First, individual athletes may perceive pain differently. For example, catastrophizing via rumination, intensification, and helplessness is associated with increased pain (Sullivan, Tripp, Rodgers, and Stanish, 2000). If pain perception was accounted for, it is possible that the findings would change. Second, pain in sport can stem from the training aspects or actual injury. Participants in the current study were specifically asked about pain caused from injury; however, Safai (2003) argues that in the sport culture athletes are not taught to distinguish one pain from the other. Therefore, it is possible that some athletes responded in terms of pain from training aspects rather than actual injury. Future research could examine the relationship between pain perception or different types of pain and athletes’ motivations for playing with pain

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Jennifer J. Waldron and Nathan White

The current study contributes to the larger literature examining pain, injury, and gender. From athletes’ responses to an open-ended question, five major and nine minor labels emerged for why they played through pain. Additionally, very few gender differences emerged regarding motives for playing through pain. In particular, the findings suggest that collegiate athletes were socialized into the culture of sport and were willing to accept risks associated with being an athlete. When embedded in the culture of sport, it may be difficult for an athlete to assess when acceptance of risk and playing through pain is resulting in damage to one’s body, health, and well being. As practitioners working with athletes, it is crucial that we understand this culture of risk and the sport ethic to help athletes avoid long term damage to their health.

REFERENCES Charlesworth, H., and Young, K. (2004). Why English female university athletes play with pain: Motivations and rationalisations. In K. Young (Ed.), Sporting bodies, damaged selves. (pp.163-180). Boston: Elsevier. Coakley, J. (2004). Sports in society: Issues and controversies (8th ed.). Boston: McGrawHill. DeBoer, K. J. (2004). Gender and competition: How men and women approach work and play differently. Monterey, NJ: Coaches Choice. Granito, V. J. (2002). Psychological response to athletic injury: Gender differences. Journal of Sport Behavior, 25, 243-260. National Collegiate Athletic Association Retrieved April 17, 2007, from http://www1.ncaa.org/membership/ed_outreach/health-safety/iss/index.html Nixon, H. L. (1992). A Social Network Analysis of Influences on Athletes to Play With Pain and Injuries. Journal of Sport and Social Issues, 16(2), 127-135. Nixon, H. L. (1993). Accepting the risks of pain and injury in sport: Mediated cultural influences on playing hurt. Sociology of Sport Journal, 10, 183-196. Nixon, H. L., (1996). Explaining pain and injury attitudes and experiences in sport in terms of gender, race, and sports status factors. Journal of Sport and Social Issues, 20(1), 33-44. Nixon, H. L. (2004). Cultural, structural, and status dimensions of pain and injury experiences in sport. In K. Young (Ed.), Sporting bodies, damaged selves. (pp. 81-97). Boston: Elsevier. Safai, P. (2003). Healing the body in the “culture of risk”: Examining the negotiation of treatment between sport medicine clinicians and injured athletes in intercollegiate sport. Sociology of Sport Journal, 20, 127-164. Singer, R. L. (2004). Pain and injury in a youth recreational basketball league. In K. Young (Ed.), Sporting bodies, damaged selves. (pp. 223-235). Boston: Elsevier. Sullivan, M. J. L., Tripp, D. A., Rodgers, W. M., and Stanish, W. (2000). Catastrophizing and pain perception in sport participants. Journal of Applied Sport Psychology, 12, 151-167. Tricker, R. (2000). Painkilling drugs in collegiate athletics: Knowledge, attitudes, and use of student athletes. Journal of Drug Education, 30, 313-324. Waldron, J. J., and Krane, V. (2005). Whatever it takes: Health compromising behaviors in female athletes. Quest, 57, 315-329.

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Wiese-Bjornstal, D., and Shaffer, S. (1999). Psychosocial dimensions of sport injury. In R. Ray and D. Wiese-Bjornstal (Eds.), Counseling in sport medicine. (pp. 23-40). Champaign, IL: Human Kinetics.

Contemporary Athletics Compendium, Volume 3 Editor: James H. Humphrey

ISBN: 978-1-60741-561-9 © 2009 Nova Science Publishers, Inc.

Chapter 4

A DESCRIPTION AND COMPARISON OF DUTIES AND RESPONSIBILITIES OF NCAA DIVISION II HEAD BASEBALL AND FOOTBALL COACHES Randy Nichols1 and Carl Bahneman2 1

Slippery Rock University, Slippery Rock, Pennsylvania, USA West Virginia University, Morgantown, West Virginia, USA

2

ABSTRACT The purpose of this study was to: (1) describe the duties and responsibilities of NCAA Division II head football and baseball coaches. The data were collected via a survey. Instrument returned by 41 of 122 head baseball coaches and 38 of 122 football coaches surveyed. Demographic data indicated the following: the majority of NCAA Division II head baseball and football coaches are Caucasian between the ages of 25 and 64 and have a master's degree, the majority of head baseball coaches are responsible for coordinating their programs fund-raising efforts while fewer head football coaches have this responsibility, the role responsibilities of the head coaches outside of coaching varies from teaching, coaching, admissions, residence life and financial aid. The data also revealed that head baseball coaches have more responsibilities outside of coaching than football coaches.

Today’s coaches are under many pressures (Lyle, 1999). They try to win games, recruit and retain athletes, prepare facilities, raise money, travel to contests and perform a variety of other duties assigned by the athletic director (Judd, Kelley, and Pastore, 1993). Many Division II coaches are asked to perform other duties or functions at their institutions, including teaching, student affairs and admissions duties (NCAA, 2003b). As the number of programs expand along with the level of competition, so does the amount of administrative duties performed by the athletic director required for each program. To this end, responsibilities that often were handled by an athletic administrator have now been shifted to

34

Randy Nichols and Carl Bahneman

head coaches (Jones, 2001). In making this shift, the head coach must accept greater responsibility and accountability for his or her program (Swank, 1995). With little or no administrative, or management experience, the head coach is now expected to complete administrative duties (Protrac, Brewer, Jones, and Hoff, 2000). The role of the coach becomes even more complex when you add teaching or other administrative type activities to his or her coaching assignment. Division II coaches are responsible for teaching, class preparation, advising students, committee work, scholarly activities and all other duties associated with faculty positions and the tenure process as well as all of the administrative duties that go along with coaching. Dual role positions can cause stress because of role ambiguity due to the lack of clear job descriptions and the expectations that go along with both teaching and coaching, along with carrying out policy and raising money (Chu, Segrave, and Becker, 1985).

PROCEDURES Selection of the Participants All of the institutions (n= 122) that offer both baseball and football at the NCAA Division II level were asked by letter to participate in the study.

Selection of the Instrument The questionnaire was designed to assess the demographic framework, including institutional standing, institutional size, and the number of sponsored intercollegiate athletic programs. This information provided the researcher with a brief, yet informative, profile of the participants and the institution. The primary areas examined included the current role responsibilities of the head baseball and football coaches at these institutions. The questionnaire was developed with the help of a panel of coaches from Slippery Rock University. Their comments and recommendations were solicited in order that the questionnaire could be refined and develop content validity. The panel received the list of research questions developed by the researcher, and sample survey questions. The panel was asked to develop what they judged to be relevant questions. The questionnaire was then examined for face validity by faculty members of the Slippery Rock University Sport Management Department. Questionnaires were sent to these individuals and they were asked to rate the questions within the instrument using a four point rating system. A four on the rating system indicated that a question was excellent and that it should be retained on the survey. A rating of three indicated a good question and that it could be retained on the survey. A rating of two indicated an average question that could possibly be retained if revised. A rating of one indicated a poor question that should be completely revised or removed from the questionnaire. The samples were returned and examined and the questionnaire was revised according to their comments. The questionnaire is comprised of 40 questions related to demographic information, and the role responsibilities of the head coaches in these programs. Content validity was established by conducting a pilot study using

A Description and Comparison of Duties and Responsibilities of NCAA…

35

one coach from each of the eight NCAA Division II regions. The coaches who were selected for the pilot study were asked to complete the survey and return it to the researcher within two weeks.

Data Collection A cover letter requesting completion of the survey was sent to the head baseball and football coaches of the NCAA Division II institutions. A thorough explanation of the nature and purpose of the study was provided in the letter along with a self-addressed, stamped envelope. Respondents were assured that all responses would be kept confidential. A twoweek deadline was established from the date of the initial mailing and a second letter, along with an additional questionnaire, was sent as a reminder to all participants following the twoweek deadline. The data were collected and analyzed by the researcher. In turn, the participants were asked to answer each question thoroughly and accurately, and when necessary, talk about the specific fundraising practices utilized by the baseball and football programs. All respondents were given the opportunity to receive results.

RESULTS Survey Return Rate The participants for this study were head coaches of NCAA Division II baseball and football programs. One hundred and twenty two institutions sponsor baseball and football at the NCAA Division II level. Of the 122 that were mailed to both head baseball and head football coaches, 41 were returned by head baseball coaches for a return rate of 33.6% and a total of 38 were returned by head football coaches for a return rate of 31.1%.

Head Baseball and Football Coaches Demographics Survey questions 1 through 4 provided information regarding head coaches’ demographics. These items included questions pertaining to the sport coached, ethnic background, age and level of education. Among the coaches who responded, the sport coached distribution was nearly equal with 51.9% (n= 41) head baseball coaches and 48.1% (n=38) head football coaches. Table 1 depicts the sport coached of the head coaches who responded to the survey. Table 1. Sports Coached by Respondents

Baseball Football Total

Frequency 41 38 79

Percent 51.9% 48.1% 100%

36

Randy Nichols and Carl Bahneman

Survey responses to ethnic background revealed that the most prevalent ethnicity was Caucasian with 79.7% (n=63). African American was next with 11% (n=11). Table 2 shows the overall composition of the ethnic background among the respondents. Table 3 shows the age ranges of the head coaches who responded to the survey. Results showed that the responses fell into mostly two categories with 49.3% (n=39) in the 25 to 44 age range and 41.7% (n=33) in the 45 to 64 age range. Table 2. Ethnic Backgrounds of Respondents

Asian African American Caucasian Hispanic Other Total

Frequency 2 11 63 2 1 79

Percent 2.5% 13.9% 79.8% 2.5% 1.3% 100%

Table 3. Age of Respondents

18 to 24 25 to 44 45 to 64 64 or older Total

Frequency 1 39 33 6 79

Percent 1.3% 49.4% 41.8% 7.5% 100%

Results about the level of education revealed that 72.2% (n=57) of the coaches who responded had earned a master’s degree as their highest level of education, while 20.3 % (n=16) had earned a bachelors degree. Table 4 displays the level of education. Table 4. Level of Education of Respondents

Some College Undergraduate Degree Master’s Degree Doctorate Total

Frequency 1 16 57 5 79

Percent 1.3% 20.3% 72.2% 6.2% 100%

The last demographic item dealt with the winning percentage of respondents. Results from the baseball coaches showed that 53.6% (n=22) had a winning percent of .500 or better, while the results from the football coaches showed a percent of 47.4% (n=18) had a winning percent of .500 or better. Table 5 represents the winning percentage of coaches who responded.

A Description and Comparison of Duties and Responsibilities of NCAA…

37

Table 5. Winning Percentage of Respondents’ Teams

Baseball Coaches Football Coaches

.000-.300 2

.301-.500 17

.501-.700 19

.701-.900 3

.901-1.000 0

Total 41

3

17

10

8

0

38

College and University Demographics Survey questions 5, 6 and 7 provided information regarding demographics of the colleges and universities in which the coaches were employed. These questions included information on category (private or public), location and enrollment. Results showed that 65.9% (n=27) of the responding baseball coaches are employed at public institutions, and 34.1% (n=14) are employed at private institutions. Results also show that 60.5% (n=23) of the football coaches who responded are employed at public colleges and universities, while 39.5% (n=15) are employed at private institutions. Table 6 depicts these results. Table 6. Public or Private Institutions of Respondents

Baseball Coaches Football Coaches

Public 27 23

Percent 65.9% 60.5%

Private 14 15

Percent 34.1% 39.5%

Survey responses to institution location revealed that 53.7% (n=22) of the baseball coaches are employed at urban institutions, while 36.8% (n=14) of the football coaches are employed at urban institutions. Table 7 represents these findings. Table 7. Institution Location of Respondents

Baseball Coaches Football Coaches Total

Rural 8 10 18

Percent 19.5% 26.3%

Suburban 11 14 25

Percent 26.8% 36.8%

Urban 22 14 36

Percent 53.7% 36.8%

Reponses to institution size show that a high percent of both baseball coaches (34.1%) and football coaches (28.9%) are employed at institutions with student enrollment between 4001 and 6000 students. Table 8 displays the current enrollment status of the institutions where the coaches who responded are employed. An analysis of Table 9 reveals that 41.5 % (n=17) of baseball coaches who responded hold faculty rank, while 36.8% (n=14) of football coaches who responded hold faculty rank.

38

Randy Nichols and Carl Bahneman Table 8. College and University Enrollment of Respondents

Less than 2,000 2,001 to 4,000 4,001 to 6,000 6,001 to 8,000 8,001 to 10,000 Greater than 10,000 Total

Baseball Coaches 5 6 14 7 4 5 41

Percent 12.2% 14.6% 34.1% 17.1% 9.8% 12.2% 100%

Football Coaches 9 7 11 8 1 2 38

Percent 23.7% 18.4% 28.9% 21.1% 2.6% 5.3% 100%

Table 9. Head Coaches who Hold Faculty Rank - Baseball and Football Coaches

Baseball Coaches Football Coaches

Frequency 17 14

Percent 41.5% 36.8%

Tables 10 and 11 represent the analysis of the coaching/teaching duties for those baseball and football coaches who responded. An analysis of these results show that a higher percentage of baseball coaches have some teaching responsibilities as part of their contract 31.7% (N=13) when compared to football coaches 26.3% (N=10). Table 10. Coaching/Teaching Duties - Baseball Coaches

Teach full-time with no release time for coaching Teach full-time with release time for coaching Have no teaching responsibilities Omitted Total

Frequency 2 11 18 10 41

Percent 4.9% 26.8% 44 % 24.4% 100%

Table 11. Coaching/Teaching Duties - Football Coaches

Teach full-time with no release time for coaching Teach full-time with release time for coaching Have no teaching responsibilities Omitted Total

Frequency 0 10 22 6 38

Percent 0.0% 26.3% 57.9% 15.8% 100%

Table 12 represents an analysis of coaches who are assigned other duties outside of coaching and/or teaching.

A Description and Comparison of Duties and Responsibilities of NCAA…

39

Table 12. Coaches with Other Assigned Duties - Baseball and Football Coaches Frequency 33 10

Baseball Coaches Football Coaches

Percent 80.5% 26.3%

Table 13 represents the results of the areas in which coaches were assigned additional duties/responsibilities? Coaches’ response choices were admissions, financial aid, residence life, athletics, intramurals/campus recreation and other. An analysis of Table 18 reveals that 34.1% (n=14) of baseball coaches who responded have additional duties within the athletic department. Table 13. Additional Duties - Baseball Coaches

Admissions Financial aid Residence life Athletics Intramurals Other Omitted Total

Frequency 3 3 5 14 2 4 10 41

Percent 7.3% 7.3% 12.2% 34.1% 4.9% 9.8% 24.4% 100%

Table 14 reveals that 15.8% (n=6) of football coaches who responded have additional duties within the athletic department. Coaches were asked if they were required to participate in scholarly activities, (publications and presentations). The response choices were yes or no. Table 15 reveals that 29.3 % (n=12) of the baseball coaches who responded and 23.7% (n=9) of the football coaches who responded are expected to be involved in scholarly activities. Table 14. Additional Duties - Football Coaches

Admissions Financial aid Residence life Athletics Intramurals Other Omitted Total

Frequency 3 0 1 6 0 0 28 38

Percent 7.9% 0.0% 2.6% 15.8% 0.0% 0.0% 73.7% 100%

40

Randy Nichols and Carl Bahneman Table 15. Involvement in Scholarly Activities - Baseball and Football Coaches

Baseball coaches Football coaches

Frequency 12 9

Percent 29.3% 23.7%

Additionally coaches were asked if they were required to conduct academic advisement for students other than their athletes. The response choices were yes or no. Table 16 reveals that 14.6 % (n=6) of the baseball coaches who responded and 15.8% (n=6) of the football coaches who responded are expected to be involved in academic advisement. Finally, coaches were asked wether or not they advise any student groups (club/organizations) other than their own athletes? Table 16. Involvement in Academic Advisement – Baseball and Football Coaches

Baseball coaches Football coaches

Frequency 6 6

Percent 14.6% 15.8%

Table 17. Advisement of Student Groups (Clubs/Organizations) – Baseball and Football Coaches

Baseball coaches Football coaches

Frequency 3 1

Percent 7.3% 2.6%

The response choices were yes or no. Table 17 reveals that 7.3% (n=3) of the baseball coaches who responded and 2.6% (n=1) of the football coaches who responded are involved with advising student clubs or organizations.

DISCUSSION An analysis of Table 30 reveals that 41.5 % (n=17) of baseball coaches hold faculty rank, while 36.8% (n=14) of football coaches hold faculty rank, and 31% of the baseball coaches teach full-time with release time for coaching and 26.3% of football coaches teach full-time with release time for coaching. Survey question 31 asked coaches if they had other assigned duties. Results showed that 80.5% (n=33) of baseball coaches had other assigned duties, while only 26.3% (n=10) of football coaches had other assigned duties outside of coaching. These additional duties can be expected to takeaway from time spent on developing a competitive program or enhancing fund-raising endeavors. In reviewing the results, one can see that 34.1% (n=14) of baseball coaches who have additional duties are assigned to those duties within the athletic department. The results also reveal that 15.8% (n=6) of football coaches who have additional

A Description and Comparison of Duties and Responsibilities of NCAA…

41

duties are assigned within the athletic department; however, 73.7% (n=28) of the football coaches left this question blank, which leads one to believe that most of these coaches are not assigned additional duties. Scholarly activities are usually expected of full-time university faculty, and the results showed that 29.3 % (n=12) of the baseball coaches and 23.7% (n=9) of the football coaches are expected to be involved in scholarly activities. These results are considered typical when you look at the fact that 31% (n=13) and 26.3% (n=10) of the baseball coaches and football coaches were considered full-time faculty. These results represent a workload expectation of coaches in some programs that goes beyond coaching. These additional responsibilities can result in putting coaches in positions with expectations that are in conflict with the time and energy it takes to manage and oversee a NCAA Division II athletic program.

REFERENCES Chu, D., Segrave, J.,and Becker, B.J. (1985). Sport and higher education. Winning and giving. Human Kinetics, Champaign, Il. 114-125. Jones, R.L. (2001) Applying empowerment in coaching. In Developing decision makers: An empowerment approach to coaching (pp.83-94). Innovative Communications. Judd, M., Kelley, B. and Pastore, D. (1993). Reduce and prevent coaching burnout. Strategies, 15-16. Lyle, J. (1999) The coaching process. Oxford, England: Butterworth Heinemann. 272. NCAA. (2003) NCAA division II operating manual. Indianapolis, IN. Potrac, P., Brewer, C., Jones, R. and Hoff, J. (2000). Toward a holistic understanding of the coaching process. Quest, 52, 186-199. Swank, M. (1995). Athletic directors sharing thoughts and actions. Athletic Administration, 21, 26-27.

Contemporary Athletics Compendium, Volume 3 Editor: James H. Humphrey

ISBN: 978-1-60741-561-9 © 2009 Nova Science Publishers, Inc.

Chapter 5

IDENTITY FORECLOSURE? A PRELIMINARY INVESTIGATION OF SELF-COMPLEXITY IN SPORT Diane E. Mack∗, Philip M. Wilson, Kristin G. Oster and Katie E. Gunnell Department of Physical Education and Kinesiology Brock University, St. Catharines, Ontario, L2S 3A1 Canada

ABSTRACT The primary purpose of this study was to examine whether athletes differed in selfcomplexity (SC) from non-athletes. A secondary purpose was to examine the relationship between SC and self-presentational concerns in sport. Participants (N = 242) completed a descriptive sorting task to measure SC. The athletic sub-sample (n = 121) further completed the Self-Presentational in Sport Questionnaire (SPSQ; Wilson and Eklund, 1998). Analyses revealed minimal differences in SC between sub-samples implying that athletes do not restrict their identity development. Correlational analyses revealed patterns of relationships between SC and SPSQ scores generally consistent with metaanalytic findings (Rafaeli-Mor and Steinberg, 2002) and the stress buffering hypothesis advanced within the SC framework. Overall, this study supports the contention that athletic participation does not, out of necessity, lead to identity foreclosure.

Academic interest in the “self” has a longstanding presence in psychological inquiry. Early theorists identified the self as a unitary cognitive entity (James, 1890; Rogers, 1951) with the content of its structure (e.g., global self-esteem) being the central empirical focus. More recent conceptualizations have identified the self as multi-faceted and dynamic (Kelly, 1955; Markus and Wurf, 1987). One mechanism through which the structure of the self has been considered is through attention to a differentiated and an integrated self (Campbell, ∗

Correspondence concerning this article should be addressed to Diane E. Mack, Department of Physical Education and Kinesiology, 500 Glenridge Avenue, Brock University, St Catharines, Ontario, L2S 3A1 Tel: (905) 6885550 Ext. 4360, Fax: (905) 688-8364, e-mail: [email protected]

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Diane E. Mack, Philip M. Wilson, Kristin G. Oster et al.

Assanand, and Di Paula, 2003). Self-complexity (SC) has been defined as the dimensionality underlying the self-concept and embodies both aspects (Campbell et al., 2003; Linville, 1985; 1987). Consistent with differentiation, the self is reflected in the number of aspects comprising the self-structure (or idiographic representations) which correspond to various roles, relationships, and contexts. The degree of overlap between aspects of the self is reflective of integration. Compared to those low in SC, highly complex individuals report a greater number of self-aspects with minimal overlap between dimensions (Linville 1985;1987). Previous commentary has suggested that involvement in high level athletics and competitive sport requires athletes to focus their attention on a limited number of activities (Danish, 1983). Results of empirical research testing the above assertion have been equivocal, with some studies indicating that athletes exhibit a dysfunctional commitment to the athlete role at the expense of other life roles (Hughes and Coakley, 1991; Murphy, Petitpas, and Brewer, 1996).Whereas other research has not reported restricted development as a result of athletic participation (Horton and Mack, 2000). With the sampling frames of the aforementioned studies restricted only to athletes the extent to which the structure of SC within athletes, in comparison to non-athletes, is currently unknown. It has been suggested that the value of SC lies in its role as a buffer from affective variability, negative feedback, and stress (Dixon and Baumeister, 1991; Linville, 1987). As such, higher SC may serve an adaptive or protective function to offset or counterbalance stressful events. Meta-analytic findings offer some support for this protective function as a small, negative effect size between SC and various indices of well-being were reported (Rafaeli-Mor and Steinberg, 2002). Examination of the heterogeneity surrounding the effect size suggested that results of individual studies varied. Therefore further inquiry into the stress buffering role of SC seems appropriate. Researchers interested in the psychological underpinnings of sport performance have attempted to increase understanding of the sources of athletes' competitive stress with selfpresentational concerns often implicated (James and Collins, 1997; Leary, 1992). Selfpresentation reflects the processes by which individuals attempt to monitor and control the impressions others form of them (Schlenker and Leary, 1982). Emerging research has demonstrated moderate relationships between competitive stress (as defined by trait anxiety) and self-presentational concerns (Hudson and Williams, 2001; Lorimer and Westbury, 2006; Martin and Mack, 1996; Wilson and Eklund, 1998). Research to date, however, has not examined the role of SC as a buffer against self-presentational concerns germane to sport performance. The primary purpose of the present investigation was to examine differences in SC between athletes and non-athletes. A secondary purpose was to examine the pattern of relationship between SC and self-presentational concerns for competitive athletes. Previous literature is complemented and extended along a number of meaningful dimensions by addressing these purposes. First, studies examining the self in sport contexts have focused in large part on the content of self-concept rather than its structural properties, one of which is SC. Second, a number of measurement concerns have been identified in the SC literature including reliance on the H-statistic (Constantino et al., 2006; Rafaeli-Mor and Steinberg, 2002) and the restrictive operationalization of SC via negatively valenced trait adjectives (Woolfolk, Novalany, Gara, Allen, and Polino, 1995). The present investigation used measurement recommendations advocated by Rafeli-Mor, Gotlib, and Revelle (1999) to

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address the above mentioned issues. Given inconclusive findings with respect to identity development in athletic samples (e.g., Horton and Mack, 2000; Murphy et al., 1996), no formal hypotheses were advanced specific to group-based differences on SC. However, based on effect sizes reported by Rafaeli-Mor and Steinberg (2002) small negative correlations were hypothesized between SC and self-presentation scores.

METHODS Participants A purposive sample of 121 athletes (nfemale = 76; nmale = 45) and 121 non-athletes (nfemale = 69; nmale = 52) currently enrolled in university were recruited. Intercollegiate athletes competed either at the National Collegiate Athletic Association (NCAA) Division 1 level (n = 98) or for the Canadian Inter-University Sport (n = 23) system. Athletes competed in diverse sports, with the majority representing track and field (n = 25), softball (n = 15), wrestling (n = 15), basketball (n = 12), and baseball (n = 9). No differences by gender or university sport system (p > .05) across dimensions of SC were found. As such, subsequent analyses were collapsed across these variables.

Measures Demographics. Participants self-reported personal information regarding athletic status and gender. Self-descriptive sorting task. The sorting task was based on recommendations from Linville (1985) and Rafaeli-Mor et al. (1999). Participants were given a packet of 44 randomly ordered card-stock cards, each printed with a trait adjective derived from pretesting, 10 blank cards, and a two-sided recording sheet with blank columns1. Trait words were obtained in a pre-testing procedure and were selected to include markers of the Big-5 personality dimensions (Goldberg, 1992). The trait list was balanced between positively and negatively valenced traits (23 and 21 respectively). Consistent with Rafaeli-Mor et al., (1999), SC was determined by the number of self-aspects (NAS) reported and their overlap (OL). Greater SC was operationalized by the number of trait groups formed by the participant. OL was operationalized as the average overlap between two groups over all possible pairs of trait groups with higher scores reflective of lower self-complexity2. Self-presentation in sport questionnaire (SPSQ). The SPSQ is a 33-item scale developed to assess a variety of self-presentational concerns in sport competition (Wilson and Eklund, 1998). Following the stem “During competition I worry that other people may perceive me 1 2

The trait adjective list can be obtained from the first author. The computation of overlap was consistent with that advocated by Rafaeli-Mor et al., 1999. Computation of Overlap OL = (Σi(ΣjCij)/Ti)/n*(n -1), whereby C = number of common features in 2 aspects; T = total number of features in the referent aspect and; N = total number of aspects in the person’s sort and i and j vary from 1 to n (i and j are unequal). Due to the nature of the trait-sorting task, estimates of internal consistency (i.e., Cronbach alpha (α) cannot be computed as estimates of total scale score variance and individual item variances cannot be computed.

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as” participants are asked to rate each item along a 5 point Likert-type scale anchored at the extremes by 1 (never) and 5 (often). Wilson and Eklund (1998) used confirmatory factor analytic procedures to support a multidimensional measurement model comprised of four self-presentational concerns: Appearing Fatigued (FAT), Physical Appearance (PA), Appearing Athletically Untalented (UNTAL) and Performance/Composure Inadequacies (PCI)3. Internal consistency reliability estimates ranged from 0.90 to 0.93 across SPSQ subscale scores (Wilson and Eklund, 1998).

Procedure Following research ethics board approval, intercollegiate coaches and faculty members were contacted for permission to survey their teams/classes. At the start of a regularly scheduled practice/class participants were informed of the purpose of the study, given an opportunity to ask questions, and invited to participate. Following approval, all participants completed the demographic information and the measure of SC. Participants sorted the cards into meaningful groups, such that each group was descriptive of an aspect of their life. Descriptive groups were recorded in the blank columns of the recording sheet and participants were asked to provide a label for each group. No limits were placed on the number of groups or on the number of cards (i.e., traits) within each group, although the number could not exceed the total number of traits (i.e., 44). Adjectives may be used once, several times in different groups, or not at all. Blank cards were used for the repetition of traits. Only the athletic sample completed the SPSQ. Standard instructions were used by the principle investigator to all participants to minimize response bias. Completion of data collection took between 20 and 40 minutes.

Data Analysis Data analyses proceeded in the following sequence. First, data was screened for errors and patterns of missing data as well as examined for conformity with statistical assumptions. Second, internal consistency estimates and descriptive statistics were calculated. Third, independent samples t-tests were conducted to examine whether athletes differed from nonathletes on NAS and OL and a discriminant function analysis determined the ability of SC to predict group membership. Finally, bivariate correlations (Pearson’s r) were computed to examine the relationships between study variables.

3

A confirmatory factor analysis (CFA) as computed on SPSQ scores to determine the viability of the measurement model proposed by Wilson and Eklund (1998) in the present sample’s data. The results of the CFA provided partial support for the structural validity of SPSQ scores across an a priori four-factor first order measurement model (χ2 = 991.76; df = 489; Comparative Fit Index = 0.87; Incremental Fit Index = 0.87; Root Mean Square Error of Approximation = 0.09 (90% confidence interval = [0.08-0.10]). The pattern of standardized factor loadings ranged from 0.50 to 0.92 (Mean = 0.81; SD = 0.08) across the target latent SPSQ factors and minimal evidence of over- or under-estimation of fitted correlations was noted in the distribution of standardized residuals (100% z < |3.00|).

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RESULTS Data Screening and Internal Consistency Estimates Initial examination of study variables (see Table 1) indicated that NAS scores deviated from univariate normality. No study variable had more than 5 percent of cases missing (Tabachnick and Fidell, 2001) and no systematic pattern of non-response was evident. Consequently, the person mean substitution method advocated by Hawthorne and Elliot (2005) was employed to replace missing data. Internal consistency reliability estimates (Cronbach’s coefficient α; Cronbach, 1951) ranged from 0.94 to 0.95 across SPSQ subscale scores (see Table 1).

Table 1. Descriptive statistics, reliability estimates, and bivariate correlations between study variables Nonathlete

Athlete

Variables

M

SD

Skew.

Kurt.

M

SD

Skew.

Kurt.

α

1

2

NAS

5.54

1.11

1.56

5.21

5.26

1.12

1.00

3.66

OL

0.62

0.15

-0.75

0.45

0.63

0.14

-0.46

-0.08

--

--

SPSQ –

--

--

--

--

2.13

0.83

0.93

1.04

.94

-.12

-.05

SPSQ – PA

--

--

--

--

2.16

1.13

1.01

0.19

.94

-.13

-.10

SPSQ –

--

--

--

--

2.29

1.08

0.63

-0.67

.95

-.07

-.10

--

--

--

--

2.45

0.91

0.51

-0.29

.94

-.05

-.16

--

FAT

UNTAL SPSQ – PC-I

Note. NAS = number of self-aspects, OL = overlap, SPSQ = Self-presentation in Sport Questionnaire (Wilson & Eklund, 1998), FAT = Fatigue, PA = Physical Appearance, UNTAL = Athletically Untalented, PC-I = Performance/Composure Inadequacy, M = Item/Subscale Mean. SD = Item/Subscale Standard Deviation. Skew. = Univariate Skewness. Kurt. = Univariate Kurtosis, α = Cronbach’s Coefficient (Cronbach, 1951). All rs greater than |.18| were statistically significant at p < .05 (two-tailed). Correlations in the matrix are based on pairwise comparisons and sample size is equivalent across each element in the matrix.

Do Athletes and Non-Athletes Differ in Self-Complexity? Descriptive statistics for relevant study variables can be found in Table 1. Separate independent samples t-tests indicated no meaningful differences between athletes and nonathletes on NAS (t(240) = -1.90, p =.06, d = .25) or OL (t(240) = .34, p =.73, d = .07) scores. A discriminant function analysis was performed using NAS and OL scores as predictors of athletic status. One discriminant function emerged (χ2 (2) = 3.67, p = .16). Classification

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Diane E. Mack, Philip M. Wilson, Kristin G. Oster et al.

procedures indicated that 55.8 percent of the originally grouped cases were classified correctly. Classification results revealed 60.3 percent of the athletes and 51.2 percent of the non-athletes were correctly classified through SC scores.

Relationships between SC and Self-Presentation The results of the correlational analyses (see Table 1) revealed weak relationships between NAS and OL scores for the athlete (r = -.09) and non-athlete (r = .07) samples implying minimal relationship between dimensions of SC.A consistent pattern of small to negligible negative correlations across dimensions of SC and self-presentational concerns (rs ranged from -.05 to -.16) was found in the athletic sample.

DISCUSSION The primary purpose of the present investigation was to explore differences in SC in athletes and non-athletes. A secondary aim was to examine the pattern of relationships between SC and self-presentational concerns in competitive athletes. This study extends previous research (e.g., Horton and Mack, 2000; Murphy et al., 1996), through its comparison of SC in competitive athlete and non-athletic samples, and its consideration of recent recommendations for the measurement and operationalization of SC (Rafaeli-Mor et al., 1999). Results of the present investigation demonstrated that athletes and non-athletes did not differ meaningfully across dimensions of SC. Descriptive statistics for NAS and OL, and the magnitude of the relationship between these dimensions, is generally consistent with other SC literature using undergraduate student cohorts (e.g., Constantino et al., 2006; Rafaeli-Mor et al., 1999; Rothermund and Meiniger, 2004). Consistent with Cohen’s (1992) guidelines, a small effect for NAS was found suggesting that non-athletes, on average, reported a greater number of self-aspects than did the athletic sample. As such, claims that athletic participation may restrict the development of other life roles out of necessity (e.g., Danish, 1983) may be somewhat premature. Competitive stress in athletes has been linked to the self-presentational implications of sport behavior (James and Collins, 1997; Leary, 1992). Descriptive statistics in the present investigation indicated that self-presentational concerns were comparable to those reported by Wilson and Eklund (1998) for physical appearance and performance/composure inadequacy; however, the present sample of athletes reported marginally greater concerns regarding fatigue and lack of athletic talent than previously noted (Lorimor, 2006; Wilson and Eklund, 1998). Sampling variability may account for these observed differences between these studies and future research would do well to examine the self-presentational concerns representing the most salient sources of competitive stress for athletes involved in different sports and varied levels of sport involvement. Examination of the pattern of relationships between dimensions of SC and selfpresentational concerns suggests a small to negligible relationship regardless of whether SC was conceptualized as NAS or OL. Consequently, higher SC is, at best, weakly associated

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with lower levels of self-presentational concerns. The magnitude of these relationships is consistent with Rafaeli-Mor and Steinberg’s (2002) meta-analytical review and previous nonsport research examining relationships between SC and variables typically linked to selfpresentation including self-monitoring and protective social comparison (Miller, Omens, and Delvadia, 1991). While the results of the present investigation offer insight into the structure and role of SC in athletes, certain limitations and future research directions are worth noting. The present study utilized a non-probability based sample of intercollegiate athletes who generally reported low-to-moderate self-presentational concerns. Future research may want to extend this line of inquiry to a more diverse sample of athletes across varied demographic subgroups (e.g., age, ethnicity) or those reporting higher self-presentational concerns. The study employed a cross-sectional design which offers limited ability to test the SC-self-presentation relationship. Linville’s (1985; 1987) original model suggested a moderating, as opposed to a direct effect of SC, which implies that SC will be of benefit only in response to negative events. Although proposed as a mechanism to buffer positive events (Rafaeli-Mor and Steinberg, 2002), relatively little research has tested this contention which seems worthy of exploration. As such, cross-sectional designs may be insufficient to elucidate the aforementioned relationship. Future researchers may want to conduct prospective studies to address the potential buffering effects of SC in athletes following negative events (e.g., injury, losing season, etc). SC as defined represents a broad, structural variable and may more accurately predict overall levels of coping, but not necessarily coping within a specific area (i.e., sport) (Koch and Shepperd, 2004). Finally, Cohen, Pane, and Smith (1997) suggest that the level of SC to any one domain may be irrelevant when that domain is not deemed personally important. Along similar lines, Ryan, LaGuardia, and Rawsthorne (2006) argued that it was the degree of authenticity embedded within the true (as opposed to contingent) self, as opposed to SC, which may influence well-being. The level of importance ascribed to athletics, either in isolation from, or compared to other life roles, nor the degree to which each self aspect was considered authentic was not investigated herein but represent useful avenues for further inquiry into the role of SC in athlete’s lives. In sum, this study highlights the similarity between athletes and non-athletes on the structure of self as defined as the number, and degree of overlap among self-aspects provided by a SC framework. As such, the belief that high level sport performance necessitates a restricted sense of self may be premature. Further, SC was weakly related to selfpresentational concerns in sport demonstrating that the degree of SC was not essential in buffering the stress associated with the self-presentational implications of sport.

REFERENCES Campbell, J. D., Assanand, S., and Di Paula, A. (2003). The structure of the self-concept and its relation to psychological adjustment. Journal of Personality, 71, 115-140. Cohen, L. H., Pane, N., and Smith, H. S. (1997). Complexity of the interpersonal self and affective reactions to interpersonal stressors in life and in the laboratory. Cognitive Therapy and Research, 21, 387-407. Cohen, J. (1992). A power primer. Psychological Bulletin, 112, 155-159.

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Constantino, M. J., Wilson, K. R., Horowitz, L. M. (2006). The direct and stress-buffering effects on self-organization on psychological adjustment. Journal of Social and Clinical Psychology, 25, 333-360. Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 6, 297-334. Danish, S. J. (1983). Musing about personal competence: The contributions of sport, health, and fitness. American Journal of Community Psychology, 11, 221-240. Dixon, T. M., and Baumeister, R. F. (1991). Escaping the self: The moderating effect of selfcomplexity. Personality and Social Psychology Bulletin, 17, 363-368. Fox, K. R. (1997). The physical self and processes in self-esteem development. In K. R. Fox (Ed.), The physical self: From motivation to well-being (pp. 111-139). Champaign, IL: Human Kinetics. Goldberg, L. R. (1992). The development of markers for the Big-Five factor structure. Psychological Assessment, 4, 26-42. Hawthorne, G., and Elliot, P. (2005). Imputing cross-sectional missing data: Comparison of common techniques. Australian and New Zealand Journal of Psychiatry, 39, 583-590. Horton, R. S., and Mack, D. E. (2000). Athletic identity in marathon runners. Functional focus or dysfunctional commitment? Journal of Sport Behavior, 23, 101-119. Hudson, J., and Williams, M. (2001). Associations between self-presentation and competitive A-trait: A preliminary investigation. Social Behavior and Personality, 29, 1-9. Hughes, R., and Coakley, J. (1991). Positive deviance among athletes: The implications of overconformity to the sport ethic. Sociology of Sport Journal, 8, 307-325. James, W. (1950). The Principles of Psychology (Vol 1.). New York: Holt (Original work published in 1890). James, B., and Collins, D. (1997). Self-presentational sources of competitive stress during performance. Journal of Sport and Exercise Psychology, 19, 17-35. Kelly, G. A. (1955). The Psychology of Personal Constructs. New York: Norton. Koch, E. J., and Shepperd, J. A. (2004). Is self-complexity linked to better coping? A review of the literature. Journal of Personality, 72, 727-760. Leary, M. R. (1992). Self-presentational processes in exercise and sport. Journal of Sport and Exercise Psychology, 14, 339-351. Lorimer, R. (2006). The relationship between self-presentational concerns and competitive anxiety: The influence of gender. International Journal of Sport Psychology, 37, 317329. Lorimer, R., and Westbury, T. (2006). Physical self-presentation and competitive anxiety in male master divers. Psychological Reports, 99, 773-780. Linville, P. (1985). Self-complexity and affect extremity: Don’t put all your eggs in one cognitive basket. Social Cognition, 3, 94-120. Linville, P. (1987). Self-complexity as a cognitive buffer against stress-related illness and depression. Journal of Personality and Social Psychology, 52, 663-676. Markus, H., and Wurf, E. (1987). The dynamic self-concept: A sociological perspective. Annual Review of Psychology, 38, 299-337. Martin, K. A. and Mack, D. (1996). Relationships between physical self-presentation and sport competition trait anxiety: A preliminary study. Journal of Sport and Exercise Psychology, 18, 75-82.

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Miller, M. L., Omens, R. S., and Delvadia, R. (1991). Dimensions of social competence: Personality and coping styles. Personality and Individual Differences, 12, 955-964. Murphy, G. M., Petipas, A. J., and Brewer, B. W. (1996). Identity foreclosure, athletic identity, career immaturity in intercollegiate athletes. The Sport Psychologist, 10, 239246. Rafaeli-Mor, E., Gotlib, I. H., and Revelle, W. (1999). The meaning and measurement of selfcomplexity. Personality and Individual Differences, 27, 341-356. Rafaeli-Mor, E., and Steinberg, J. (2002). Self-complexity and well-being. A review and research synthesis. Personality and Social Psychology Review, 6, 31-58. Rogers, C. R. (1950). Client-centred therapy. New York: Houghton Mifflin. Rothermund, K., and Meiniger, C. (2003). Stress-buffering effects of self-complexity: Reduced affective spillover or self-regulatory processes? Self and Identity, 3, 263-281. Ryan, R. M., LaGuardia, J. G., and Rawsthorne, L. (2005). Self-complexity and the authenticity of self-aspects: Effects on well-being and resilience to stressful events. North American Journal of Psychology, 7, 431-448. Schlenker, B. R., and Leary, M. R. (1982). Social anxiety and self-presentation: A conceptualization and model. Psychological Bulletin, 92, 641-669. Tabachnick, B. G., and Fidell, L. S. (2001). Using Multivariate Statistics (4th Ed.), Needham Heights, MA: Allyn and Bacon. Wilson, P., and Eklund, R. C. (1998). The relationship between competitive anxiety and selfpresentational concerns. Journal of Sport and Exercise Psychology, 20, 81-97. Woolfolk, R. L., Novalany, J., Gara, M. A., Allen, L. A., and Polino, M. (1995). Selfcomplexity, self-evaluation, and depression: An examination of form and content within the self-schema. Journal of Personality and Social Psychology, 68, 1108-1120.

Contemporary Athletics Compendium, Volume 3 Editor: James H. Humphrey

ISBN: 978-1-60741-561-9 © 2009 Nova Science Publishers, Inc.

Chapter 6

RISK MANAGEMENT STRATEGIES AT DIVISION I INTERCOLLEGIATE FOOTBALL STADIUMS: DO SPECTATORS PERCEIVE THEY ARE PROTECTED AGAINST TERRORISM? John J. Miller1, Andy Gillentine2 and Frank Veltri 1

2

Texas Tech University, Lubbock, Texas, USA University of Southern Mississippi, Hattiesburg, Mississippi, USA

The prominence and popularity of American sporting events, encourages an examination of levels of safety. Because of their potential impact on the U.S. economy and culture, American sporting event venues may be considered attractive targets of attack for several reasons. First, the large numbers of people attending sports contests provide potential foes with not only the potential of massive casualties but also increased media exposure (Wade, 2000). For example, Saturday afternoons during the fall season in the United States, are typified by large gatherings of people, some exceeding 100,000, attending intercollegiate football games. Because an enemy’s choice of targets may include the high probability of mass casualties and infliction of economic loss, these factors may be considered rewards for an attack (Schneider, 2002). Thus, an assault on a major sporting event such as an intercollegiate college football game could produce what a terrorist may seek: mass casualties and economic harm. A second reason for concern of a terrorist attack at an athletic event is that sports venues are categorized as "soft targets" (Levitin, 1998). Soft targets are susceptible locations that are not well-protected, offer relatively easy access, great numbers of individuals who continually enter and exit a stadium or arena during a contest and the relative congestion that exists of those spectators in the facility (Clonan, 2002; Picarello, 2005). A third reason relates to previous incidents in which large numbers of individuals have previously been attacked by terrorists in the United States prior to September 11, 2001. An explosive device was detonated under New York’s World Trade Center in 1993, causing over $500 million in structural damage, killing six people and injuring more than 1000 (Fischbach, 2001). Two

54

John Miller, Andy Gillentine and Frank Veltri

years later, the Murrah Federal Office Building terrorist bomb blast occurred in Oklahoma City that ultimately took 168 lives, including 19 children (Rosenblatt, 2000). For all these reasons, it should come as no surprise that terrorists have shown a desire to attack major sporting events such as the Super Bowl or World Series (Fallon, 2003).

FORESEEABILITY The potential for a terrorist assault at a sporting event is an issue for the foreseeable future (Hurst, Zoubek, and Pratsinakis, 2002). Thus, it is becoming more foreseeable that even in a free democracy the best available security may not impede a terrorist assault. Bethune (2002) summed up this concept by stating: Today's reasonable man is not the same man he was before September, 11th. What the public - the community that is the reasonable man - considers foreseeable with respect to terrorism and what it regards as reasonable steps to prevent terrorist attacks have been fundamentally altered (p. 24).

The foreseeable danger of terrorism conveys potential implications for those who own or operate sport stadiums. Previous court rulings have stated that a facility manager has a duty to act on threats of violence as if they had actually occurred (Bishop v. Fair Lanes, 1986). According to Isaacs v. Huntington Memorial Hospital (1985), “… authorities who know of threats of violence that they believe are well-founded may not refrain from taking reasonable preventive measures simply because violence has yet to occur” (pp. 125-126). Foreseeability may be regarded as the most significant consideration in determining the extent to which a person is owed a duty of reasonable care (Dobbs, 2000). Reasonable security measures are viewed in light of any specific warnings given to the venue indicating that an attack was foreseeable. To assist in alerting potentially foreseeable terrorist actions, the Department of Homeland Security has enacted a multi-level color-coding ranking system that identifies potential security threats to the public. The five levels and their accompanying colors are: low (green); guarded (blue); elevated (yellow); high (orange); and severe (red). Each level and color identifies the potential threat of an attack and a set of recommended procedures for federal departments and agencies (Homeland Security Advisory System, 2004). If a risk is perceived to be high or severe, an attack may be extremely foreseeable during that time (Barkett, 2003).

Concept of Risk To understand how to manage it, the concept of risk must be addressed. Some have recognized risk as the potential harm of valuable items resulting from an individual’s actions (Kates and Kasperson, 1983). Slovic and Peters (2006) delineated risk into two categories: risk as feelings and risk as analysis. Risk as feelings relates to a person’s innate reaction to a harmful situation. Risk as analysis incorporates items such as logic, reason, and scientific forethought to determine how to handle a dangerous situation. Klinke and Renn (2002) referred to risk as:

Risk Management Strategies at Division I…

55

… the experience of something that people fear or regard as negative. It is also clear that this fear is extended to an event or situation that has not yet occurred but could occur in the future (p. 1076).

Moreover, risk can include such items as uncertainty, catastrophic potential, and controllability (Slovic, 2000). Certainly the catastrophic potential of a terrorist assault may be perceived as immeasurable in regards to loss of life and economic considerations. This immeasurability strongly relates to the concept uncertainty (Nohria and Stewart, 2006). It is through uncertainty that fear arises (Lerner, Gonzalez, Small, and Fischhoff, 2003; Lerner, and Keltner, 2000). To the extent that an attack is thought to be unique or isolated, the immediate impact may be limited and fleeting (Liesch, Steen, Knight, and Czinkota, 2006). This may result in uncertainty and accompanying fear to be contained at a lesser level. If on the other hand, attacks are perceived by fans to be directed to more vulnerable or ‘soft targets’ such as the sport stadium, the more insidious the uncertainty would be thereby increasing the level of fear among the people (Ip, 2004).

Risk Management Components While intercollegiate stadiums have not been victimized by a terrorist attack, other researchers have indicated that the potential for one exists (Baker and Connaughton, 2005; Miller, Veltri, and Phillips, 2007). Moreover, previous research has indicated that security personnel seldom possess sufficient anti-terrorist training (Goss, Jubenville, and MacBeth, 2003). Because sport events generally have large numbers of individuals in a heightened state of excitement continually moving in, out and throughout a facility that is hard to supervise it is imperative that organizations are adequately prepared for emergencies. According to Decker (2001), the most accepted approach that can guide an organization’s effort in preparing against attacks is through the appropriate development and enforcement of risk management policies. Risk management is concerned with addressing potential, foreseeable risks that are tied to the prospect of injury or loss through a blend of several distinct approaches such as threat, vulnerability, and criticality assessments. A threat assessment may be used as a decision support tool to assist in creating and prioritizing security-program requirements, planning, and resource allocations (Decker, 2001). When an organization embarks on a threat assessment effort, it is primarily searching for potential sources of concern and determine its’ credibility. Since not every threat might be identified or threat information may be incomplete, vulnerability assessments are essential to better prepare against threats. A vulnerability assessment estimates the susceptibility of a potential attack by those desiring to create physical or psychological harm to an organization’s infrastructure, including employees or patrons (Hall, 2004). Thus, a vulnerability assessment assists in the identification of weaknesses that may be exploited and suggests options to eliminate or address those weaknesses (Decker, 2001). The third component of managing risks is determining which assets, structures, or functions are the most critical to protect. Identifying the criticality of these items provides the sport facility manager to better direction of resources to areas of highest priorities (Decker,

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John Miller, Andy Gillentine and Frank Veltri

2001). Once the priorities have been developed the risk event manager would be able to identify potential targets and implement appropriate risk management measures.

Public Inclusion in Risk Management Because the word “risk” has many connotations, problems in communications exist. Despite this confusion, probabilities and outcomes of adverse occurrences have usually been thought of as being quantifiable through the assessments of risk management. However, the social science analysis does not accept this concept by arguing that the objectivity of potential outcomes is lacking or false (Slovic and Weber, 2002). According to Slovic and Weber (2002) it is the perceptions of both public and officials that have played a significant role in the ability of Americans to prepare and deal with the threat of terrorism. A key issue in deciding the most effective course to follow in managing a risk is the contribution of the public in delineating appropriate levels of risk and safety (Slovic and Peters, 2006). In theory, since it is the individuals who are most affected by a foreseeable harm, they should be allowed to participate with an organization in determining levels of acceptable safety (Webler, 1999). Slovic (2000) revealed that as the societies in industrialized countries have attempted to make lives healthier and safer, more people have become more concerned about risks. Slovic goes on to state that early investigations about risk perception exhibited the public apprehensions could not merely be placed on ignorance or irrationality. More precisely, people are now viewing themselves as being exposed to more severe risks than ever before and that the state of affairs in regards to facing significant risks is increasing.

PURPOSE OF THE STUDY An important aspect for risk management research is to provide policy-makers with the information that they need to identify potential threats, determine vulnerabilities, and prioritize critical aspects to aid in the development and implementation of innovative risk management strategies through the insights of the general public (Slovic, 1987; Slovic and Weber, 2002). While previous reports have addressed risk management issues in intercollegiate sports (Fried and Metchick, 2005; Gillentine and Miller, 2006; Miller and Gillentine, 2006), research regarding risk management strategies of NCAA Division I affiliated universities from the general public, specifically, event spectator’s viewpoint are non-existent. This investigation attempted to determine whether spectators attending games at selected NCAA Division I football stadiums perceived that risk management procedures were being effectively implemented to protect them against a terrorist-related attack.

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METHOD Instrument The authors for this investigation developed a 1-5 Likert scale 20-item questionnaire. The Likert scale responses ranged from 1=strongly agree, 2=agree, 3=unsure, 4=disagree, and 5=strongly disagree. The questionnaire consisted of sections relating to the following areas: demographic information, overall perceptions of security at intercollegiate football games from previous experience, perceptions of security practices at intercollegiate football games, and perceptions of security personnel at intercollegiate football games. In order to ensure the reliability of the questionnaire, a test-retest protocol was conducted with two present and three former sport event managers. Several changes regarding item inclusion and item wording were suggested and implemented on the questionnaire. The re-test was accomplished two weeks later with the same group of professionals and no additional modifications were recommended. To determine the validity of the instrument, a Pearson product-moment correlation coefficient (Pearson’s r) was employed. The reliability coefficient was determined to be .82, which is well within the acceptable range for the interpretation of scores for individuals (Patten, 2000). To ensure consistency, each investigator and their teams distributed the surveys at two pre-selected intercollegiate home football games at each institution. The investigative teams were made up of 3-4 sport management graduate students from each institution in addition to the authors. Since the questionnaires were distributed at multiple games, each investigative team member was instructed to ask each potential respondent if they had previously filled it out. While somewhat rudimentary, this process was utilized to prevent duplication of respondents. Confidentiality was assured in a short written statement given to the potential respondent as well as a verbal promise given by the respective team member. A total of 1102 surveys were returned to the respective investigative teams, of this total 1048 surveys were deemed usable for the study. Reasons for not using a survey included incomplete answers, inappropriate responses, indecipherable responses and non-attendance to an intercollegiate football contest at the selected site prior to September 11, 2001. Indecipherable answers occurred when the respondent circled the response so that it appeared to have included two different answers (e.g. the answer could have been agree or unsure). Rather than selecting what potentially could have been an incorrect response, the survey was discarded even if only one such response existed on the instrument. Additionally, due to the nature of the study if a respondent had not attended an intercollegiate football game prior to September 11, 2001 the survey was discarded.

RESULTS Demographics The first part of the survey asked the respondents to indicate demographic information such as gender, age, and number of intercollegiate football games previously attended in the past two years. The results indicated that 629 (60%) were males and 418 (40%) were females.

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In descending order 409 (39%) were between 26-33 years of age, 325 (31%) were between the ages of 34-42, 199 (19%) were 18-25 years old, and 115 (11%) were over 42 years old. The respondents were asked how many intercollegiate football games they have averaged attending over the previous 2 years. The results revealed that 587 (56%) attended 4-5 home football contests, 398 (38%) were present at 2-3 games while 63 (6%) attended either 1 or no games in the previous years. Since all of the respondents had attended games prior to September 11, 2001 they were asked to indicate their perceived level of safety while attending an intercollegiate football game within a year after the attacks as well as four years later. Whereas 817 (78%) believed that they were safe attending games from 2001-2002, 964 (92%) revealed they felt safe four years after the attacks. When asked whether they thought that an attack on a football stadium could occur, 985 (94%) felt that such an incidence was now improbable. However, 1027 (98%) believed that should an attack occur, a significantly negative and catastrophic impact would be felt.

Threat, Vulnerability, and Criticality Assessments Seven hundred and sixty (69%) perceived that multiple targets, which may have been considered an additional threat for an attack, were present in the community. When asked about potential vulnerabilities 796 (76%) felt that security systems were given priority and attention to detail before, during, and after an intercollegiate football game. However, 629 (60%) agreed that avenues of ingress and egress to/from the facility were given significant attention prior to, during and after a contest. When asked if the distance from the facility to the parking lots are given significant attention prior to, during and after a contest, 597 (57%) agreed that enough attention was given to this potential vulnerability. Seven hundred and eighty-six (75%) agreed that intercollegiate football stadiums might be considered targets of symbolic significance. Finally, 639 (61%) agreed that intercollegiate sporting events were considered critical functions within their community.

Perceptions of Risk Management Practices Over a period of time, risk management plan enforcement may become less stringent (Alston, 2003). The results of the survey supported this contention as 534 (51%) respondents agreed that risk management procedures were overly apparent at intercollegiate football games which may be the result of 943 (90%) had observed security presence either in the stadium or in areas immediately outside the stadium. However, 573 (52%) perceived that the enforcement of risk management procedures had become more lax since 9/11. Thus, it would appear that although safety personnel are present on the premises the enforcement of risk procedures were not stringent. Interestingly, 566 (54%) indicated that they would be willing to pay more for increased safety at sporting events. Respondents were asked to identify their perception of the adequacy of risk management practices that were communicated through signage or verbal announcements. Four hundred and nineteen (40%) believed that risk management procedures had been adequately

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communicated through signage or announcements at intercollegiate football games previously attended.

DISCUSSION The findings of this survey revealed a significant number of sports fans felt safer attending contests now than they did more immediately after the attacks of September 11th. However, American sporting events are subject to the real and present threat of a terrorist attack and must remain at a heightened state of alert. This is substantiated by a recent report in which the Department of Homeland Security (DHS) identified a dozen possible strikes it viewed most devastating, including a truck bombing of a sports arena (Lipton, 2005). Since a sports venue operator has a legal duty to warn the invitees about reasonably foreseeable and credible threats (Dobbs, 2000; Mallen, 2001), it is disturbing that less than half of the respondents revealed that risk management practices through communication and announcements procedures had been followed. If a credible or foreseeable threat exists on a premises and it cannot be corrected an invitee must be warned of such a threat so they may avoid it (Montgomery and Nahrstadt, 2004). Signage and verbal communications can be used, in dire circumstances, for directional purposes. For example, identification of the most expeditious exit routes as well as manner of conduct can be explained by signage and verbal communication. This may result in not only minimizing confusion but also potential injuries among the spectators. The results also indicated that while the probability of an attack was unlikely, the impact would likely be catastrophic. Risks may be regarded as the chance of something happening that will have a negative impact upon organizational objectives. These risks can be measured in terms of probability and impact. The amount of risk is produced by its impact (e.g., low, medium, high) and the probability of occurrence (e.g. never, sometime, and often). In the event that the risk producing harmful incidents is considered improbable, it may be perceived that the management of risks would be relatively unimportant. However, if the risks were considered severe enough in producing events that could negatively impact the organization, the ability to manage such a risk would be important. Over half of the respondents perceived that risk management procedures had become more lax in the past five years. This may relate to the theory of the threshold of effective zerohood (Rescher, 1983), often referred to as the theory of probability which states that once the probability of an incident becomes small enough, the potential of the incident occurring may be viewed as outside the range of appropriate concern. In other words, if it hasn’t ever occurred or hasn’t happened in a long time the probability of it occurring may be negligible. Since no intercollegiate football stadiums have ever been attacked the perceived likelihood of an attack occurring is construed as zero. This could lead the event sport manager, the organization and potentially spectators to fall into the risk of complacency. After the first attack on the World Trade Center and the Oklahoma City bombing but prior to the 9/11 attacks, Gips (2000) warned: While the World Trade Center and Oklahoma City bombings may be gradually receding into the collective subconscious, leading the public to become complacent, more recent events

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If the probability of an incident occurring is considered to be close to zero, the perception may very well be to set aside the need for the assessment and management of risk. However, the assessment of whether a situation is considered a risk and the resulting management of those actions depend on the perception of the risk (Lyytinen, Mathiassen, and Ropponen, 1998). If the analysis of the impact were the primary concern, the scope of the risk would increase. In other words if the organization can foresee the realization of a threat occurring as well as negative impact that an attack could create, the level of the management of risks would be elevated. As such, when a plausible danger is multiplied by the potentially harmful impact, the level of risk increases (credible threat x potential negative impact = level of risk increases). If an organization possessed credible information indicating that an attack was foreseeable such as a red alert from the Department of Homeland Security, but did not respond to respond suitably, they may have breached their reasonable duty of care (Picarello, 2005). Although all of the areas that could injure a spectator cannot be totally eliminated, they can be managed with the appropriate amount of attention, monitoring and intervention. A goal of risk management is to enable individuals and organizations to isolate risks and to recognize potential mitigation options. An acceptable method for alleviating possible risks is through the vigilant application of threat, vulnerability, and criticality assessment procedures and the resulting enforcement of risk management procedures. A threat assessment allows the organization to recognize potentially foreseeable hazards and compare the probability of an injurious situation occurring (Alston, 2003). As such, threats are examined on the basis of the likelihood of occurrence relating to the impact of the threat. The results indicated that almost 70% of the respondents perceived that multiple targets, which may also be considered as a target for an attack, existed in the community. Although one of the locations where a survey was conducted was in a major metropolitan area, the other two schools were situated in much smaller markets. This may indicate that universities that support Division IA football may have additional attractions for an attack regardless of city size. The information gleaned from a vulnerability assessment plan allows sport facility managers to decide which option would be most appropriate and act to either eliminate or minimize the risk. Among potential areas of weakness include closed-circuit security systems, avenues of entrance and exit, and potential distance of vehicles from the stadium. A prior investigation reported that avenues of ingress and egress to/from intercollegiate football stadiums as well as security systems were given sufficient attention prior to, during and after a contest (Miller, Veltri, and Phillips, 2007). This investigation supports that finding as a majority of the respondents in this study believed that these avenues were satisfactorily addressed by the organization. It is important that organizations provide detailed attention to this area as the lack of this risk management protocol could expose the organization to potential vulnerabilities as avenues of ingress and egress, or the distance from parking lots to important buildings as being so close that a car bomb detonation would damage or destroy the buildings and the people working in them (Decker, 2001). The criticality assessment permits the organization decision-makers to prioritize the assets. Previous research has indicated that event managers of large intercollegiate football

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stadiums believe that the stadiums are considered to be of symbolic significance and intercollegiate sporting events are considered as critical functions within their community (Miller, Veltri, and Phillips, 2007). The results of this study supported that contention as three-quarters of the respondents in this investigation believed that intercollegiate football stadiums might be considered targets of symbolic significance and over half perceived intercollegiate contests as being critical functions within their community. Should organizational decision-makers overlook the perceived importance of the contests, lack risk awareness or simply ignore the need to develop, implement and enforce safeguards, it may be only a matter of time before an incident occurs (Alston, 2003).

Research Limitations As with any research study, limitations exist. First, it can only be assumed that the subjects responded in a truthful and honest manner. Second, these findings may not be generalized to the greater population of NCAA Division I athletic departments that sponsor intercollegiate football. However, the information from this investigation should only be construed as the “tip of the iceberg”. This will be addressed in the next section.

Future Research Future investigations could be conducted regarding spectator perceptions of risk management procedures attending NCAA Division I intercollegiate football games at the majority of universities and colleges in the United States. Secondly, an investigation dealing with the university/college athletic department’s familiarity and understanding of current risk assessment procedures as recommended by State and Federal agencies could be examined. Finally, future studies could be conducted to determine how university/college athletic departments develop, implement and assess event risk management policies and procedures.

CONCLUSION Risk does not exist in a nebula as an autonomous aspect, waiting to be measured. While it is impossible to predict exactly where the next terrorist attack may occur, this study indicates that intercollegiate football venues appear to be managing potential risks well as perceived by the spectators attending. To further assist in preventing, limiting, detecting and responding to potential risks, the public should be involved in the risk management process. It has been reported that as efforts to make life safer have been developed, a large percentage of the general public has become increasingly concerned about risks (Slovic, 2002b). With this knowledge, innovative viewpoints and approaches to influence public perceptions may be required to manage risks efficiently by the sport venue operators. Early investigations indicated that the public’s perception of risk and subsequent concern cannot simply be blamed on ignorance or irrationality (Covello, Flamm, Rodricks, and Tardiff, 1983). However, recent reports have indicated that public perceptions of risk have

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been important in assisting the establishment of priorities and legislative agendas of regulatory bodies such as the Environmental Protection Agency (Slovic, 2002a). The involvement of more people recognizing and reporting potentially harmful situations or events increase the knowledge base about potential areas of concern. This in turn may create an opportunity for the decision-maker to gain greater amounts of insights and knowledge to efficiently apply or implement the best possible solutions to the problem area. To meet these goals the effective development, implementation and enforcement of a risk management program should be foremost in the minds of sport event managers. Loewenstein, Weber, Hsee, and Welch (2001) have stated that the perceptions of risks are as much driven by affective processes as reasoned-based quantifiable processes. This is an important concept for sport facility managers to embrace. For example, while quantifiable assessments are important in some decision-making situations, relying on the affective process is often quicker and more efficient method of addressing potential risks (Slovic and Peters, 2006). If a sport facility manager can promote a risk management program to spectators attending intercollegiate football games to develop an attitude of taking a conscious approach to assessing potential threats and vulnerabilities and relaying them to the appropriate authority, the potential for creating a reasonably safe environment may increase significantly. This inclusionary process can then help move risk management from the domain of the accidental to the domain of the proactive.

REFERENCES Alston, G. (2003). How safe is safe enough? Burlington, VT: Ashgate Publishing. Baker, T.A. and Connaughton, D.P. (2005). Terrorism: A foreseeable threat to U.S. sport facility owners and operators. Journal of Contemporary Athletics, 1(2), 109-124. Barkett, J. M. (2003). If terror reigns, will torts follow? Widener Law Symposium Journal, 9, 485-543. Bethune, E. (February 4, 2002). What's expected now: The "reasonable man" standard for liability is much higher since Sept. 11. Legal Times, 24. Bishop v. Fair Lanes Georgia Bowling, Inc., 803 F.2d 1548 (11th Cir. 1986). Clonan, T. (October 26, 2002). Any time any place, Irish Times, W1. Covello, V. T., Flamm, W.G., Rodricks, J. V., Tardiff, R. G. (1983). The analysis of actual versus perceived risks. New York: Plenum. Decker, R. J. (October, 2001). Homeland security: A risk management approach can guide preparedness efforts. Retrieved on January 29, 2006 from http://www.gao.gov/cgibin/getrpt?GAO-03-102. Dobbs, D. B. (2000). The law of torts. St. Paul, MN; West Group. Emergency Survival Program Home Page. (2001). ESP Bulletin. Retrieved on March 13, 2007 from www.cert-la.com/ESP/Terrorism2001.pdf. Fallon, R. H. (2003). Legal issues in sports security. Fordham Intellectual Property, Media, and Entertainment Law Journal, 13, 349-401. Fischbach, A. F. (2001). Towering security. Electrical Construction and Maintenance, 100(3), 46-56.

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Fried, G. and Metchick, R. (Winter 2005). Camp Randall Memorial stadium case study: University of Wisconsin – October 1993. Journal of Legal Aspects of Sport, 15(1), 139176. Gillentine, A. and Miller, J. (2006). Legal issues associated with tailgating. International Journal of Sport Management, 7(1), 100-109. Gips, M. (May, 2000). Building in terrorism’s shadow. Security Management [Online]. Retrieved on February 2, 2007 from http://www.securitymanagement.com/. Goss, B.D., Jubenville, C.B., and MacBeth, J.L. (2003). Primary principles of post-9/11 stadium security in the United States: Transatlantic implications from British practices. Retrieved on December 12, 2006 from www.iaam.org/CVMS/Post%20911% 20Stadium%20Security.doc Hall, T. (March, 2004). You've completed your vulnerability assessment...now what? Public Works, 135(3), 34-36. Homeland Security Advisory System. (2004). Retrieved on February 17, 2006 from http://www.dhs.gov/dhspublic/display?theme=29. Hurst, R. Zoubek, P. Pratsinakis, C. (2002). American sports as a target of terrorism. Sport and the Law Journal, 10(1), 134-139. Ip, G. (March, 2004), "Terror in Madrid: the aftermath: after September 11, the US learned about its economic resilience; attacks shocked markets, but the overall impact was milder than expected", The Wall Street Journal, A15. Isaacs v. Huntington Memorial Hospital, 695 P.2d 653 (Cal. 1985). Kates, R. W. and Kaperson, J.X. (1983). Comparative risk analysis of technological hazards: A review. National Academy of Sciences, 80(22), 7027-7038. Klinke, A. and Renn, O. (2002). A new approach to risk evaluation and management: Riskbased, precaution-based, and discourse-based strategies. Risk Analysis, 22(6), 1071-1094. Lerner, J.S., Gonzalez, R. M., Small, D.A., and Bischoff, B. (March, 2003). Effects of fear and anger on perceived risks of terrorism: A national field experiment. Psychology Science, 14(2), 144-150. Lerner, J. S., and Keltner, D. (2000). Beyond valence: Toward a model of emotion-specific influences on judgment and choice. Cognition and Emotion, 14(4), 473-493. Levitin, H. (December, 1998). Preparing for terrorism: What every manager needs to know, Public Management, 4-6. Lipton, E. (2005, March 16). U.S. report lists possibilities for terrorist attacks and likely toll. New York Times, A1. Liesch, P., Steen, J., Knight, G. and Czinkota, M.R. (2006). Problematizing the internationalization decision: Terrorism-induced risk. Management Decision, 44(6), 809823. Loewenstein, G. F., Weber, E. U., Hsee, C. K., Welch, E. (2001). Risk as feelings. Psychological Bulletin, 127, 267-286. Lyytinen, K., Mathiassen, L., and Ropponen, J. (1998). Attention shaping software risk- A categorical analysis of four classical risk management approaches. Information Systems Research, 9(3), 233-255. Mallen, S.A. (2001). Touchdown! A victory for injured fans at sporting events? Missouri Law Review, 66(2), 487-505.

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Miller, J. and Gillentine, A. (Summer 2006). An analysis of risk management policies for tailgating activities at selected NCAA Division I football games. Journal of Legal Aspects of Sport, 16, 197-215. Miller, J. Veltri, F. and Phillips, D. (2007). Preparing against a terrorist attack: The application of risk management at intercollegiate football stadiums. Journal of Contemporary Athletics. Montgomery, C. B. and Nahrstadt, B.C. (Spring, 2004). A primer for the entertainment community: Legal and practical issues about venue safety - what you should know. Virginia Sports and Entertainment Law Journal, 3, 257-283. Norhia, N., Stewart, T.A. (February, 2006). Risk, uncertainty, and doubt. Harvard Business Review, 84(2), 35.

Patten, M. L. (2000). Understanding research methods: An overview of the essentials. Los Angeles: Pyrczak Publishing. Rescher, N. (1983). Risk: A philosophical introduction to the theory of risk evaluation and management. Washington, D.C.: University Press of America. Rosenblatt, R. (May 29, 2000). How we remember. Time, 155(22), 26-30. Schneider, R. (2002, September). American anti-terrorism planning and design strategies: Applications for Florida growth management, comprehensive planning and urban design. Nelson Symposium on Growth Management Legislation, Fredric G. Levin College of Law, University of Florida. Slovic, P. (1987). Perception of risk. Science, 236, 280-285. Slovic, P. (2000). The perception of risk. London: Earthscan. Slovic, P. (2002a). Terrorism as hazard: A new species of trouble. Risk Analysis, 22, 425-426. Slovic, P. (2002b). The risk game. Journal of hazardous materials, 86(1), 17-25. Slovic, P. and Peters, E. (December, 2006). Risk perception and affect. Current Directions in Psychological Science, 15(6), 322-325. Slovic, P. and Weber, E.U. (April 11, 2002). Perception of risk posed by extreme events. Paper presented at the conference of Risk Management Strategies in an Uncertain World. Palisades, New York. Wade, J. (December, 2002). Safeguarding the Meadowlands. Risk Management, 18. Webler, T. (1999). The craft and theory of public participation: A dialectical process. Journal of Risk Research, 2(1), 55-71.

Contemporary Athletics Compendium, Volume 3 Editor: James H. Humphrey

ISBN: 978-1-60741-561-9 © 2009 Nova Science Publishers, Inc.

Chapter 7

THE POSITIVE RELATIONSHIP BETWEEN SPORT TEAM IDENTIFICATION AND SOCIAL PSYCHOLOGICAL WELL-BEING: IDENTIFICATION WITH FAVORITE TEAMS VERSUS LOCAL TEAMS Daniel L. Wann∗ and Jennifer Martin Murray State University, Murray, Kentucky, USA

ABSTRACT Consistent with the Team Identification – Social Psychological Health Model (Wann, 2006a), research indicates a positive relationship between identification with a local sport team and social psychological health. However, because fans often select the local team as their favorite (Jones, 1997), it remained possible that the findings were due to the target team being one’s favorite team rather than due to the team being local. The current study tested the hypothesis that levels of identification with favorite teams would not be independently related to social well-being unless the favorite team was also a local team. College students (N = 173) completed a questionnaire packet assessing demographics, identification with their favorite sport team (categorized as local or distant), and social psychological health. Regression analyses provided clear support for the hypotheses. Discussion centers on implications of the current study for Wann’s (2006a) model and the possibility that mere sport fandom may also play a role in wellbeing.

Recently, Wann (2006a) presented a theoretical model designed to account for the welldocumented positive relationship between sport team identification (defined as the extent to ∗

Address correspondence to Daniel L. Wann, Department of Psychology, Murray State University, Murray, KY 42071 or to [email protected] via Internet.

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which a person feels a psychological connection with a specific team, see Wann, Melnick, Russell, and Pease, 2001) and social psychological well-being. According to Wann’s framework, labeled the Team Identification – Social Psychological Health Model (TI-SPHM), team identification results in valuable social connections with others. Two forms of connections result from identification: enduring and temporary. Enduring social connections occur when a fan of specific team resides in a community where other fans of that team are readily apparent and salient (e.g., a New York Yankees fan who lives in New York). Temporary social connections occur when a person who does not reside in a community with enduring connections momentary finds him or herself in the presence of other fans of that team (e.g., a Boston Red Sox fan who lives in New York but is currently watching a Red Sox game on television with several other Red Sox fans). According to the model, the increased social connections are then expected to increase social psychological well-being at either the state (temporary connections) or trait (enduring connections) level. Furthermore, because fans often feel distressed by their team’s poor performance (Hirt, Zillmann, Erickson, and Kennedy, 1992; Schwarz, Strack, Kommer, and Wagner, 1987), the TI-SPHM postulates that social identity threat (e.g., poor team performance) and strategic coping mechanisms (e.g., biased attributions) moderate the relationship between social connections and well-being. That is, fans cope with the threat of poor team performance and maintain appositive level of well-being through the use of coping strategies (see Wann, 2006a, for a detailed list and discussion of various coping mechanisms). Research support for the TI-SPHM (Wann, 2006a) is strong. In one of the first examinations of the relationship between identification and well-being, Branscombe and Wann (1991) found that higher levels of identification with a sport team were related to lower levels of alienation. In a follow-up study, Wann (1994) found a positive relationship between team identification and social (i.e., collective) self-esteem. Subsequent studies have extended the research to include other forms of social well-being. Specifically, researchers have found that team identification is related to lower levels of loneliness (Wann, Dimmock, and Grove, 2003), higher levels of extroversion (Wann, Dunham, Byrd, and Keenan, 2004), higher levels of social life satisfaction (Wann and Pierce, 2005), and higher levels of trust in others (Wann and Polk, 2007). In addition, the aforementioned relationships have been replicated in a variety of settings (e.g., classroom, dormitory, athletic event, see Wann, Walker, Cygan, Kawase, and Ryan, 2005) and longitudinal research suggests a causal pattern in which team identification directly effects well-being (Wann, 2006b). It each of the previously cited investigations of the team identification – social well-being relationship, researchers assessed participants’ levels of identification with a local sport team. As noted, according to Wann’s (2006a) model, identification with a local sport team should result in enduring social connections and, ultimately, positive levels of well-being (identification with a distant and thus, non-salient team should not produce such effects, see Wann, 2006a; Wann and Pierce, 2005). However, while the research is supportive of Wann’s model, it is likely that for many of the participants the local team was also their favorite team. The possibility existed that is was the fact that the target team was a favorite team that was the key to the effect, rather than the fact that the team was local (and thus, the enduring social connections were salient). That is, imagine a hypothetical fan whose favorite team is the men’s varsity basketball team for the university in which he (or she) is currently enrolled and where he currently lives. For this fan, the team would be both a local team and a favorite team. The TI-SPHM contends that this fan would likely report higher levels of social well-

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being because by following and supporting this local team, the fan would generate social capital. However, it remains possible that the positive relationship between identification and well-being is due to the fact that the team in question was the fan’s favorite rather than simply being a local team. Given that fans often support local teams (Jones, 1997; Wann, Tucker, and Schrader, 1996), this possibility warrants investigation. Such an investigation was the focus of the current study. Specifically, this study was designed to rule out the possibility that previous research documenting a positive relationship between team identification and well-being was due to the team in question being a favorite team and that, rather, the key was whether or not the team was local. This was accomplished by testing the following three hypotheses. First, it was hypothesized that levels of identification with favorite teams would not be independently related to social well-being. That is, the previously detected positive relationship between level of identification with a local team and social psychological health was not expected to be replicated with one’s favorite team (some of which would likely be local, some of which would not). Second, it was hypothesized that for those persons whose favorite team was the local team there would be a significant relationship between identification and well-being. And finally, Hypothesis 3 predicted that for fans with a favorite team that is not local, there would not be a significant independent relationship between identification and social psychological health.

METHOD Participants Participants were 173 (60 male; 113 female) college students receiving extra course credit in exchange for participation. They had a mean age of 22.84 years (SD = 5.42).

Materials and Procedure Upon entering the testing session and providing their consent, participants (tested in small groups) were handed a questionnaire packet containing four sections. The first section contained two demographic items assessing age and gender. The second section contained the Sport Fandom Questionnaire (SFQ), a psychometrically sound, five-item (Likert scale format) instrument assessing level of sport fandom (Wann, 2002). Response options to the SFQ ranged from 1 (low fandom) to 8 (high fandom). Thus, higher numbers indicated greater levels of fandom. The third portion of the packet contained the Sport Spectator Identification Scale (SSIS; Wann and Branscombe, 1993). The SSIS contains seven Likert-scale items with response options ranging from 1 (low identification) to 8 (high identification). Thus, higher numbers represented greater levels of identification. The SSIS has been used in a number of studies involving sport fans, has strong reliability and validity, and has been translated into many languages (Melnick and Wann, 2004; Theodorakis, Vlachopoulos, Wann, Afthinos, and Nassis, 2006; Wann and Branscombe, 1993; Wann et al., 2001). Participants were asked to list their favorite sport team and to target this team when completing the SSIS. Participants’

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favorite teams were classified as local if the team could be found within the local county (e.g., one of the local university’s teams, a local high school team, etc.). All other teams were classified as a non-local team. The fourth and final section of the questionnaire packet contained a pair of reliable and valid instruments assessing social psychological health. First, participants completed the 16item Collective Self-esteem Scale (CSES; Luhtanen and Crocker, 1991). Response options to the CSES ranged from 1 (strongly disagree) to 7 (strongly agree). Second, respondents completed the 20-item UCLA Loneliness Scale (UCLALS; Russell, Peplau, and Cutrona, 1980). The UCLALS contained response options ranging from 1 (never) to 4 (often). Both the CSES and the UCLALS were coded so that higher numbers reflected better psychological health (i.e., higher levels of collective self-esteem and lower levels of loneliness). These two measures were selected for three reasons. First, these measures had been successfully used in past research examining the psychological health of sport fans (Wann et al., 2003; Wann, and Pierce, 2005). Second, these scales assess components of social well-being (Keyes and Lopez, 2001) and group memberships and associations with sport teams should be more closely related to social well-being than personal well-being. Consequently, researchers investigating this area are advised to employ measures of social psychological health (Rubin and Hewstone, 1998; Wann, 2006a). And third, these measures assess trait levels of well-being (rather than state). Because we were interested in the consequences of enduring (i.e., chronic) social connections, assessments of trait well-being were more appropriate (Wann, 2006a). After completing their questionnaire packet (approximately 15 minutes), participants were debriefed and excused from the testing session.

RESULTS Preliminary Analyses Items contained in each scale were summed to establish scale scores for each measure. The two measures of social well-being were highly correlated (r = .567, p < .001). Thus, scores on these scales were converted to z scores and combined to form a single index of social psychological health. The means, standard deviations, and Cronbach’s reliability alphas for each scale are listed in Table 1. A series of Analyses of Variance (ANOVAs) were used to examine potential gender differences. These analyses revealed several significant effects. Specifically, males were found to have higher levels of sport fandom, F(1, 171) = 42.67, p < .001, and team identification, F(1, 171) = 20.95, p < .001. Conversely, females reported higher levels of collective self-esteem, F(1, 171) = 6.78, p < .01 and more positive levels of well-being as assessed by the index, F(1, 171) = 5.43, p < .05. Due to the significant gender effects, gender was included in the regression analyses described below.

Favorite Teams, Team Identification, and Social Well-being Correlations among the dependent variables appear in Table 2. Hypothesis 1 (levels of identification with favorite teams would not be independently related to social well-being)

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was testing using a regression analysis in which sport fandom, team identification, and gender were included as predictor variables and the social psychological well-being index served as the dependent variable. The combined effect of the three predictors was significant, F(3, 169) = 8.94, p < .001. With respect to independent contributions to well-being, consistent with expectations team identification with one’s favorite team (local or distant) was not independently related to social well-being, Beta = .176, t = 1.39, p > .15. Sport fandom also failed to account for a significant proportion of variance in well-being, Beta = .198, t = 1.49, p > .10. However, gender did account for a significant proportion of the variance in social well-being, Beta = .322, t = 4.02, p < .001. Table 1. Means, Standard Deviations, and Cronbach’s Reliability Alphas for the Dependent Measures by Gender and for the Entire Sample

Sport fandom (SFQ)1

Team Identification with favorite team (SSIS)1

Collective self-esteem (CSES)2

Loneliness (UCLALS)3

Total social well-being2

Alpha

Males

Females

Entire Sample

.96

28.45

18.52

21.97

(10.26)

(9.10)

(10.61)

42.92

33.26

36.61

(13.28)

(13.18)

(13.96)

86.03

91.12

89.36

(13.20)

(11.70)

(12.44)

67.67

69.68

68.98

(9.24)

(7.79)

(8.35)

-.425

.226

.000

(1.90)

(1.66)

(1.77)

.96

.88

.90

N/A

Notes: Standard deviations appear in parentheses below each mean. 1 indicates a significant gender effect in which males scored higher than females. 2 indicates a significant gender effect in which females scored higher than males. 3 indicates no significant gender differences.

As noted, participants’ favorite teams were classified as either local (n = 38) or non-local (n = 135). A series of ANOVAs were used to examine potential differences on the dependent variables by team (i.e., local versus non-local). The analyses failed to indicate any significant differences. The only analysis which approached significance involved identification scores, in which identification for local teams (M = 40.13; SD = 13.44) was marginally higher than for non-local teams (M = 35.62; SD = 13.99), F(1, 171) = 3.14, p = .08.

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Table 2. Simple Correlations among the Scales for All Participants and Separately for Local and Non-local Favorite Teams --------------------------------------------------------------------------------------------------------------------------------------------All Participants

1

Sport fandom (1)

--

2

Team Identification (2)

.82***

--

Social Psychological Well-being (3)

.20**

.23**

Gender (4)

-.45*** -.33***

Favorite Team is Local

1

Sport fandom (1)

--

Team Identification (2)

.82***

Social Psychological Well-being (3)

.26

Gender (4)

-.45**

Favorite Team is Non-local

1

Sport fandom (1)

--

Team Identification (2)

.84***

Social Psychological Well-being (3)

.19*

Gender (4)

2

3

4

-.18*

--

3

4

-.41** -.29

2

--.02

--

3

4

-.17*

-.44*** -.37***

-.23**

--

---------------------------------------------------------------------------------------------------------------------------------------------

Notes: Gender was coded as 1 = male, 2 = female. * p < .05. ** p < .01, *** p < .001.

Separate regression equations were then conducted for those with a local favorite and those whose favorite was a non-local team (see Table 2 for correlation matrices). Once again, sport fandom, team identification, and gender were included as predictor variables while social psychological well-being was the dependent variable. For participants listing a local team as their favorite, the combined effect of the three predictor variables was marginally significant, F(3, 34) = 2.74, p = .06. With respect to independent contributions to well-being, consistent with Hypothesis 2, team identification (Beta = .607, t = 2.23, p < .05) was the only variable to be independently related to social well-being. Neither sport fandom (Beta = -.215, t = -0.74, p > .45) nor gender (Beta = .060, t = 0.35, p > .70) accounted for a significant proportion of the variance in social well-being. As for respondents listing a non-local team as their favorite, the combined effect of the three predictor variables was significant, F(3, 131) = 7.91, p < .001. With respect to independent contributions to well-being, consistent with Hypothesis 3, team identification (Beta = .046, t = 0.37, p > .75) was not independently related to social well-being. Sport fandom (Beta = .317, t = 2.05, p < .05) and gender (Beta = .384, t = 4.26, p < .001) each accounted for a statistically significant proportion of the variance in social well-being.

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DISCUSSION Consistent with the Team Identification – Social Psychological Health Model (Wann, 2006a), previous research had reliably found significant relationships between levels of identification with a local sport team and various indices of social psychological well-being, such as loneliness and alienation (e.g., Wann, 2006b; Wann et al., 2004; Wann et al., 2003; Wann and Polk, 2007). However, it seemed possible that for many of the subjects in the previous investigations, the local team serving as the target team may also have been their favorite team. This possibility appeared particularly likely given reports indicating that fans often root for local teams (Jones, 1997; Wann et al., 1996). Thus, it was unclear if the aforementioned relationships involving identification and well-being were due identification with a local team as proposed in Wann’s model or, rather, were due to identifying with a favorite team. By examining identification with local and distant favored teams, the current investigation was designed to investigate this research void. The results revealed strong support for the TI-PSHM (Wann, 2006a) as data from a college student sample revealed that it was identification with the local team and not simply one’s favorite team that was uniquely related to well-being. This pattern supports Wann’s hypothetical framework because, as noted previously, it is not team identification per se that is posited to result in positive well-being but, instead, the enduring and temporary social connections generated via the team identification. Identification with a local team should generate social capital because other fans of the team are salient and easy to identify in one’s environment. Conversely, identification with a favorite team does not assure the establishment of social capital because one’s favorite team may or not be a local team. Indeed, although past research indicates that geography can play a key role in one’s choices of teams to support (Jones, 1997; Wann et al., 1996), in our sample tested here participants were more likely to have a distant team as a favorite (n = 135) than to list a local team (n = 38). Thus, it is not identification with one’s favorite team that would lead to social well-being but, instead, identification with a local team. An unexpected finding involved the significant unique contribution of sport fandom to well-being among those persons with a non-local team as a favorite. Wann’s (2006a) model predicts that mere fandom per se will not lead to gains in social well-being because mere fandom should not generate social capital and research substantiates this expectation (e.g., Wann, Inman, Ensor, Gates, and Caldwell, 1999; Wann and Pierce, 2005). However, the current research suggests that there may be potential benefits to mere sport fandom after all. Specifically, the current data suggest that for persons who support distant teams, their interest in fandom may assist in their well-being by generating social capital, namely, other sport fans. Thus, perhaps identifying with a local sport team and being a sport fan rooting for a distant team both lead to social capital (and ultimately social well-being). Certainly, future research is needed to replicate and thus substantiate this possibility. However, if this should be the case, slight modifications to Wann’s Team Identification – Social Psychological Health Model would be warranted.

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REFERENCES Branscombe, N. R., and Wann, D. L. (1991). The positive social and self-concept consequences of sports team identification. Journal of Sport and Social Issues, 15, 115127. Hirt, E. R., Zillmann, D., Erickson, G. A., and Kennedy, C. (1992). Costs and benefits of allegiance: Changes in fans' self-ascribed competencies after team victory versus defeat. Journal of Personality and Social Psychology, 63, 724-738. Jones, I. (1997). A further examination of the factors influencing current identification with a sports team, a response to Wann, et al. (1996). Perceptual and Motor Skills, 85, 257-258. Keyes, C. L. M., and Lopez, S. J. (2001). Toward a science of mental health: Positive directions in diagnosis and interventions. In C. R. Snyder and S. J. Lopez (Eds.), Handbook of positive psychology (pp. 45-59). New York: Oxford. Luhtanen, R., and Crocker, J. (1991). Self-esteem and intergroup comparison: Toward a theory of collective self-esteem. In J. Suls and T. A. Wills (Eds.), Social comparisons: Contemporary theory and research (pp. 211-234). Hillsdale, NJ: Erlbaum. Melnick, M. J., and Wann, D. L. (2004). Sport fandom influences, interests, and behaviors among Norwegian university students. International Sports Journal, 8(1), 1-13. Rubin, M., and Hewstone, M. (1998). Social identity theory’s self-esteem hypothesis: A review and some suggestions for clarification. Personality and Social Psychology Review, 2, 40-62. Russell, D., Peplau, L. A., and Cutrona, C. E. (1980). The revised UCLA Loneliness Scale: Concurrent and discriminant validity evidence. Journal of Personality and Social Psychology, 39, 472-480. Schwarz, N., Strack, F., Kommer, D., and Wagner, D. (1987). Soccer, rooms, and the quality of your life: Mood effects on judgments of satisfaction with life in general and with specific domains. European Journal of Social Psychology, 17, 69-79. Theodorakis, N. D., Vlachopoulos, S. P., Wann, D. L., Afthinos, Y., and Nassis, P. (2006). Measuring team identification: Translation and cross-cultural validity of the Greek version of the Sport Spectator Identification Scale. International Journal of Sport Management, 7, 506-522. Wann, D. L. (1994). The "noble" sports fan: The relationships between team identification, self-esteem, and aggression. Perceptual and Motor Skills, 78, 864-866. Wann, D. L. (2002). Preliminary validation of a measure for assessing identification as a sport fan: The Sport Fandom Questionnaire. International Journal of Sport Management, 3, 103-115. Wann, D. L. (2006a). Understanding the Positive Social Psychological Benefits of Sport Team Identification: The Team Identification – Social Psychological Health Model. Group Dynamics: Theory, Research, and Practice, 10, 272-296. Wann, D. L. (2006b). Examining the potential causal relationship between sport team identification and psychological well-being. Journal of Sport Behavior, 29, 79-95. Wann, D. L., and Branscombe, N. R. (1993). Sports fans: Measuring degree of identification with the team. International Journal of Sport Psychology, 24, 1-17.

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Wann, D. L., Dimmock, J. A., and Grove, J. R. (2003). Generalizing the Team Identification – Psychological Health Model to a Different Sport and Culture: The Case of Australian Rules Football. Group Dynamics: Theory, Research, and Practice, 7, 289-296. Wann, D. L., Dunham, M. D., Byrd, M. L., and Keenan, B. L. (2004). The five-factor model of personality and the psychological health of highly identified sport fans. International Sports Journal, 8(2), 28-36. Wann, D. L., Inman, S., Ensor, C. L., Gates, R. D., and Caldwell, D. S. (1999). Assessing the psychological well-being of sport fans using the Profile of Mood States: The importance of team identification. International Sports Journal, 3, 81-90. Wann, D. L., Melnick, M. J., Russell, G. W., and Pease, D. G. (2001). Sport fans: The psychology and social impact of spectators. New York: Routledge Press. Wann, D. L., and Pierce, S. (2005). The relationship between sport team identification and social well-being: Additional evidence supporting the Team Identification – Social Psychological Health Model. North American Journal of Psychology, 7, 117-124. Wann, D. L., and Polk, J. (2007). The positive relationship between sport team identification and belief in the trustworthiness of others. North American Journal of Psychology, 9, 251-256. Wann, D. L., Tucker, K. B., and Schrader, M. P. (1996). An exploratory examination of the factors influencing the origination, continuation, and cessation of identification with sports teams. Perceptual and Motor Skills, 82, 995-1101. Wann, D. L., Walker, R. G., Cygan, J., Kawase, I, and Ryan, J. (2005). Further replication of the relationship between team identification and psychological well-being: Examining non-classroom settings. North American Journal of Psychology, 7, 361-366.

Contemporary Athletics Compendium, Volume 3 Editor: James H. Humphrey

ISBN: 978-1-60741-561-9 © 2009 Nova Science Publishers, Inc.

Chapter 8

FOR LOVE OF THE GAME: THE MEDIATING POTENTIAL OF JOB SATISFACTION OF COLLEGE COACHES UPON CAREER SATISFACTION Aaron W. Clopton∗1, Tim D. Ryan2 and Michael Sagas3 1

Marshall University, Huntington, West Virginia, USA 2 University of Memphis, Memphis, Tennessee, USA 3 Texas A&M University, College Station, Texas, USA

ABSTRACT As demands on today’s coach escalates, the role and presence of job satisfaction increases in significance, as well. Past research has analyzed job satisfaction in both sport and business literature (e.g. Wright, 2006); and linked with diversity (Pastore, 1993; Sagas et al., 2005) and supervisor satisfaction (Chelladurai, 2003). This investigation examined the relationship of supervisor satisfaction with career satisfaction for the coaching sample, a relationship presented in previous research (e.g. Sagas and Cunningham, 2004). Results indicated significant correlations between supervisor, career, and job satisfaction levels (p < .01). An initial regression analysis displayed a significant presence of supervisor satisfaction in predicting coaches’ career satisfaction (β = .31, p < .001). A further regression analysis revealed significant predictability of job satisfaction when added to the model (β = .50, p < .05). This presence signified the mediating potential of job satisfaction on the relationship between supervisor satisfaction and career satisfaction.

∗

Correspondence: Aaron W. Clopton, Ph.D. Marshall University, Division of Exercise Science, Sport, and Recreation, One John Marshall Drive, Huntington, WV 25755-2450. E-mail: [email protected]. (304) 696 – 5405

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INTRODUCTION The daily experience of a worker’s employment environment has, not surprisingly, been found throughout past research to significantly impact many affective outcomes that can influence the landscape of the larger profession. Outcomes of a worker’s experience, including such aspects as job and career satisfaction (e.g. Abraham, 1999; Cotton and Tuttle, 1986; Igbaria and Greenhaus, 1992; Michaels and Spector, 1982), organizational commitment (Davy, Kinicki, and Scheck, 1991; Williams and Hazer, 1986), and turnover intentions (Ding and Lin, 2006; Michaels and Spector, 1982) are a few of the many components that have been significantly linked with such work environmental factors as supervisor support (Durham et al., 1997), teamwork (Griffin, Patterson, and West, 2001), work performance (Bauer and Green, 1996; Vroom, 1964) and workplace accidents (Porac et al., 1983). Protruding most fervently out of the organizational literature is impact of the supervisor, most likely due to the pertinence of their impact upon the structuring of the work environment and their ability to provide information and feedback back to their employees (Griffin et al., 2001). For this reason, the supervisor behavior has been found to significantly impact the affective reactions of team members under them (Durham et al., 1997). Not surprisingly, then, the role of the supervisor has often been penned as a major contributor to job and career satisfaction of the subordinate (e.g. Gerstner and Day, 1997; Greenhaus, Parasuraman, and Wormely, 1990), thus, possessing the ability to shape not only the existence of one’s department or company, but of the overall profession due to the supervisor’s ability to directly influence both the professional and organizational commitment (Wakabayashi, Graen, Graen, and Graen, 1988) and the turnover intentions (Abraham, 1999; Greenhaus et al., 1990).

Supervisor Satisfaction Operationally defined here as the relationship between a subordinate worker and his or her supervisor and the perception of the subordinate that the relationship positively contributes to his or her career development (Kram, 1985); supervisor satisfaction maintains a consistent influence over many work outcomes. In fact, a tight web connects the aforementioned factors and outcomes such that significant, positive relationships exist between supervisor support/satisfaction and job and career satisfaction (i.e. Greenhaus et al., 1990) and organizational commitment (Ding and Lin, 2006; Kanter, 1979), while significant negative relationships exist between turnover intentions and supervisor support/satisfaction (Greenhaus, 1987). Further depicting the meticulous relationship is both the mediating (Griffin et al., 2001) and moderating (Erdogan and Enders, 2007) ability of supervisor support upon job satisfaction and working relationships, as well as the mediating role that organization commitment plays between job satisfaction and turnover intentions (Lin and Ma, 2004; Lin and Chen, 2004).

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Career Satisfaction On a much broader scope than job satisfaction, career satisfaction besets the all the jobs that an individual has worked (Williamson, Pemberton, and Lounsbury, 2005), or about 100,000 hours for a typical American (Career Strategists, 2006). Thus, career satisfaction includes a wide array of feelings and emotions on all of the experiences related to one’s career (Lounsbury, Moffitt, Gibson, Drost, and Stevens, 2007). Because of this positive orientation towards one’s career, then, career satisfaction has often been significantly linked with such outcomes as commitment and turnover (Gupta, Guimaraes, and Raghunathan, 1992; Igbaria, Greenhaus, and Parasuraman, 1991). This same relationship has matriculated through in the coaching profession, as well, with satisfaction with the coaching profession and one’s career being connected with turnover intention (e.g. Chelladurai, 2003). Notably, coaches have been found to possess moderately-high career satisfaction (e.g. Sagas and Cunningham, 2004) as well as moderately-high or high job satisfaction (Sagas and Cunningham, 2004; Sagas, Paetzold, and Cunningham, 2005).

Job Satisfaction Additionally, job satisfaction has been shown to play a significant secondary role in many relationships in the organization literature. Cogently defined as the extent to which a worker feels positively or negatively about his or her job (Odom, Boxx, and Dunn, 1990), job satisfaction was discovered to mediate the influences of role conflict and role ambiguity on various facets of organization commitment including affective, continuance, and normative commitment (Yousef, 2002). Todd and Kent (2006) found, using employees from a sporting goods manufacturer, that job satisfaction partially mediated the effect of intrinsicallysatisfying tasks on helping behavior, as well as partially mediating the influence of task significance on helping behavior. The same research also established job satisfaction as full mediator upon the relationship between task autonomy and sportsmanship (Todd and Kent, 2006). Other literature in organizational theory have shown job satisfaction to mediate the relations between self-leadership behavioral-focused strategies and team performance (Politis, 2005), positive affectivity and turnover intention (Chiu and Francesco, 2002), as well as moderating the existence between hesitation and self-management performance (Diefendorf, Richard, and Gosserand, 2006). Therefore, any research endeavor into one of the aforementioned job elements, such as satisfaction or role of supervisor, must be prepared to elucidate the roles and position of each element in the relationship. While research in the sport management literature has included the elements of job and career satisfaction and supervisor support (e.g. Clopton, Sagas, and Sosa, 2006), little depth exists that clearly explicates the mediating roles of each work-outcome, specifically for the work environment of intercollegiate athletic coaches. Sagas and Ashley (2000) did, however, discover a differential existence in gender and satisfaction where male coaches exhibited significantly higher levels of job satisfaction than female coaches, something that led to significantly lower levels of turnover intention for the male coaches. Thus, as the “primary employees of intercollegiate athletics” (Chelladurai and Ogasawara, 2003, p. 62), many socio-cultural issues have arisen within the profession college coaching, including gross inequities in gender (Acosta and Carpenter, 2006) and race (Sagas and Cunningham, 2004;

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Cunningham and Sagas, 2005). Thus, perhaps, further investigation into the work environment of college coaches might illuminate some of the current tribulations of the coaching landscape. The purpose of the current research, then, was to explore the impact of a coach’s satisfaction with his or her supervisor upon the coach’s career satisfaction and the extent to which job satisfaction mediated the aforementioned impact.

THEORETICAL FRAMEWORK Leader-Member Exchange Theory (LMX) The conceptualization for this study was drawn from both the leader-member exchange theory (LMX theory, or LMX; Graen, 1976), and the career satisfaction research model (Jiang and Klein, 2000). One of the earliest leadership theories based upon relationships, LMX suggests that the quality of interaction between both leader and subordinate significantly shapes the work experience and, thus, appropriate work outcomes (Graen, 1976; Graen and Cashman, 1975). When LMX relationships are of high quality, leaders and subordinates share mutual trust, respect, and obligation (Graen, 1976; Graen and Schieman, 1978), and positive support, common bonds, and shared loyalty (Dienesch and Liden, 1986; Graen and Uhl-Bien, 1995). Originating from what organizational literature terms Vertical Dyad Linkages (VDL), LMX theory has focused on the specific connection that leaders form individually with their subordinates (Dansereau,, Graen, and Haga, 1975). The individual dyadic linkage, or relationship, is defined, then, by the exchanges between leader and follower. Inevitably through these relationships, in-groups and out-groups emerge dependent upon the quality with which the leader-subordinate dyads operate (Dansereau et al., 1975; Northouse, 2001). Leaders develop only a select number of followers as their in-group members to function within the work setting, as each leader is constrained by his or her personal resources as a leader (Graen and Uhl-Bien, 1995). With this in-group selection comes a high degree of mutual trust, respect, obligation, and loyalty, to name a few (Dienesch and Liden, 1986). As the “trusted assistants,” in-group members receive more information, influence, and confidence from their leader (Zalensky and Graen, 1987), thus, shaping a much different work experience. It is within this in-group that previous literature has determined potential sources behind the gender and racial inequities in collegiate coaching, including homologous reproduction (Stangl and Kane, 1991) and the similarity-attraction paradigm (Sagas et al., 2005), to list a couple. Regardless, the impetus for most coaching environment research involves, albeit towards a varied extent, some relationship and exchange with a coach and his or her supervisor, or leader. Because of the aforementioned significant relationship between the leader-member exchange and a positive work experience, leaders and supervisors play a direct role in the matriculation of the future work force, thus, possessing the ability to actively shape the potential demography of the profession. What has not been established, though, is to what extent the inherent satisfaction one derives from the performing their job is able to override the impact that their leader-member exchange has upon their overall satisfaction with their career.

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Applying the LMX theory of leadership towards today’s landscape of college coaches, we offer the following initial hypothesis: Hypothesis 1: A significant, positive relationship will exist between the coaches’ satisfaction with their supervisor and their career satisfaction. LMX has been significantly linked to job satisfaction as a strong, direct relationship (Stringer, 2006) and, indirectly, through perceptions of the degree of empowerment (Sparrowe, 1994), trust in leader (Dirks and Ferrin, 2001), and positive feelings about their work context (Wayne et al., 1997). Notably, job satisfaction has been found to moderate the effects of initial low LMX (Scandura and Graen, 1984), thus further contributing to the satisfaction triumvirate of supervisor, job, and career.

Career Satisfaction Research Model This satisfaction triumvirate has been copiously arranged within the conceptual framework by the career satisfaction research model (Jiang and Klein, 2000). The relationship between the three measures of satisfaction within the model is triplicate, with supervisor support directly influencing the outcome of career satisfaction, a path in accord with LMX. The alternate routes to career satisfaction extend from the supervisor position into, and through, both external career opportunities and internal career anchors (Jiang and Klein, 2000). Here, internal career anchors are defined by the needs, values, and talents that deemed necessary for one’s career existence. Examples of internal career anchors include autonomy, identity, and security (Delong, 1982; Schein, 1975). A subordinate’s internal career anchors allow one to envision his or her perceptions of the future, career orientation, impact of work experiences, and more. External career opportunities, then, become defined by an organization’s ability to bolster the internal career anchors of the individual employee (Jiang and Klein, 2000). Thus, external career opportunities exist within the environment created by the organization. Organizational effectiveness in supporting the internal career anchors of employees, of which supervisors are a part, lies within the organization’s ability to adjust its structure to meet the needs and desires of its employees (Igbaria and Baroudi, 1993). Accordingly, then, the second path into career satisfaction originates from the supervisor and is shaped directly by a subordinate’s perceptions of external career opportunities. Most notably, though, is mediating influence provided by the third path into career satisfaction. Also originating from the supervisor, a subordinate experiences are shaped by the relationship between one’s perceived external career opportunities and the extant internal career anchors. It is afterward that the resulting experience defines one’s career satisfaction (Jiang and Klein, 2000). Using this tertiary path, then, we can deductively operationalize job satisfaction as the extent to which an employee has established quality internal career anchors and by the magnitude to which an employee’s organization is meeting said anchors by opportunities. Further, because of the significant existence between the ubiquitous job satisfaction measure and both supervisor satisfaction and career satisfaction, job satisfaction will now be expected to supersede the relationship between the coaches’ supervisor satisfaction and their satisfaction with their career, in accordance with the career satisfaction research model (Jiang and Klein, 2000). Moreover, the intercollegiate athletic coaching profession is a unique

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profession in that many demands upon personal and family time, personal resources, and more are enacted upon each coach. While a small percentage of today’s college coach receives overwhelming financial rewards, the vast majority of coaches are drawn to the profession for the love and enjoyment of competing and performing the intricacies of the very job of coaching itself (Chelladurai, 2003). Thus, the following hypothesis is included: Hypothesis 2: Job satisfaction will mediate the relationship between supervisor satisfaction and career satisfaction.

METHODOLOGY Participants As part of a larger study, data were collected through a mailed questionnaire as part of larger study assessing the quality of employment in college coaching. A stratified simple random sample of 800 head coaches were selected to participate in the study (400 men’s team coaches; 400 women’s team coaches), and represented coaches from all three NCAA divisions. A total of 261 usable responses were collected after one round of data collection and a mailing to non-respondents resulted in another 83 responses (N = 344, 43.1% response rate). To assess potential response bias, we tested differences between early and late responders. No significant mean differences were noted between the early and late respondents on any of the main study variables. The three NCAA divisions were represented in the usable sample in a proportion similar to that of the general population (Division I = 123; Division II = 76; Division III = 145, see DeHass, 2003). The age of the responding coaches ranged from 23 to 73, and the male coaches were older (M = 44.41, SD = 11.35) than female coaches (M = 36.56, SD = 8.85). In addition to the amount of organization tenure, male coaches in the sample possessed more years as a college coach (M = 13.75, SD = 9.00) than the women in the sample (M = 12.01, SD = 8.09). Finally distinguishing the two genders of the respondents, males were more likely to be married, with 74.8% of the male respondents reporting to be married where a mere 34% of female respondents were married. Further, the sampling of head coaches had been at their current college or university over nine years (M = 9.42; SD = 8.28) and in their current supervisorhead coach dyad for five years (SD = 4.60). Moreover, 71.2% of the male head coaches were in gender-similar dyads (N = 178) while only 37.2% of the female head coaches worked under a female supervisor (N = 35). It should be noted that no differences were found in gender or NCAA division echoing the sentiments of past literature (Pastore, 1993).

Survey Instrumentation The survey instrument contained a series of questions assessing numerous outcomes related to the quality of employment as an intercollegiate coach in the NCAA. The supervisor satisfaction, job satisfaction, and career satisfaction measures were embedded within the larger survey instrument. The concept of supervisor satisfaction was measured with a four-

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item scale exploring the perceptions each head coach held on his or her supervisor (Spector, 1985). The questions included such items as “My supervisor is quite competent in doing his/her job” and “My supervisor is unfair to me,” and provided a highly-reliable estimate (α=.93). To establish the presence of job satisfaction, the three-item Overall Job Satisfaction Questionnaire was used (Cammann et al., 1983). The job satisfaction variable was also determined to be highly-reliable (α = .91). The Overall Job Satisfaction Questionnaire included items like “In general, I am satisfied with my job.” Finally, the career satisfaction variable was determined by the five-item Career Satisfaction Scale (Greenhaus et al., 1990), such items as “I am satisfied with the success I have achieved in my career.” The career satisfaction measure was also established with acceptable reliability (α=.81).

Data Analyses Initially, descriptive statistics were ran to obtain demographical information on the respondents regarding age, education level, gender, marital status, and coaching experience. The research question then explored, using linear regression, the relationship of perceived supervisor satisfaction and the resultant career satisfaction of the coaches. To investigate the mediating potential of job satisfaction on the predictability of supervisor satisfaction upon career satisfaction, Pearson correlations were obtained between the dependent variable (career satisfaction), the independent variable (supervisor satisfaction) and the potential mediator (job satisfaction). Results were calculated via Sobel’s test to determine possible mediation (Baron and Kenny, 1986; Preacher and Hayes, 2004; Sobel, 1982).

RESULTS Results indicated significant bivariate correlations between supervisor, career, and job satisfaction levels (p < .01), and are given in Table 1. In the testing of the first hypothesis, an initial regression analysis displayed a significant presence of supervisor satisfaction in predicting coaches' career satisfaction (β= .31, p < .001, R2 = .10). This supported the first hypothesis. In examining the mediating effects of job satisfaction on the relationship of supervisor support to career satisfaction of college coaches, as predicted in the second hypothesis, four separate conditions needed to be satisfied, as suggested by Baron and Kenny (1986). The first two steps were to find significant relationships between the predictor variable and the outcome variable, and the predictor variable and the mediator. Again, Table 1 shows these significant relationships. Additionally, the first step was also satisfied by the first regression analysis used to test Hypothesis 1. The next step is to include the mediating variable, job satisfaction, along with the predictor variable, supervisor support, in the linear regression to predict the outcome, career satisfaction. This analysis revealed significant predictability of job satisfaction when added to the model (β = .50, p < .05). This presence negated the significant presence of supervisor satisfaction in the relationship, thus, suggesting the mediating potential of job satisfaction on the relationship between supervisor satisfaction and

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career satisfaction (R2 = .27). Confirming hypothesis 2 that job satisfaction mediated the relationship between supervisor support and career satisfaction. Table 1. Descriptive Statistics, Correlations, and Reliability Estimates of All Variables Used in Analysis (N= 344) ______________________________________________________ Variable

1

2

3

1. Supervisor satisfaction

(.93)

2. Job satisfaction

.56*

(.91)

3. Career satisfaction

.3 1*

.5 2*

(.81)

Mean

4 .99

5 .54

4 .56

Standard deviation

1 .54

1 .19

1 .07

______________________________________________________ Notes. * p< .01. Reliability estimates given in diagonal.

Table 2. Results of Regression Analysis ________________________________________________________ Step

b

R2

S.E

F

________________________________________________________ 1. Intercept

3.52

.15

.22

.04

2. Intercept

1.95

.24

Supervisor satisfaction

.02

.04

.03

Job Satisfaction

.45

.05

.50** .27

Supervisor satisfaction

.31** .10

37.22**

62.83**

________________________________________________________ Notes. *p < .05. ** p< .01.

DISCUSSION The aims of this study were to explore the impact of a coach’s satisfaction with his or her supervisor upon the coach’s career satisfaction, and to specifically examine the extent to which job satisfaction mediated the aforementioned impact. As was expected through the initial hypothesis, the satisfaction with supervisor by the responding coaches significantly

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impacted the coaches’ career satisfaction. This finding concurred with both the LMX and the career satisfaction research models, in addition to previous organizational literature (e.g. Gerstner and Day, 1997; Greenhaus, Parasuraman, and Wormely, 1990). More importantly, though, the supervisor satisfaction-career satisfaction relationship, as predicted in hypothesis 2, was superseded by the by mediating influence of the coaches’ job satisfaction. This finding adds to the widely-established mediating ability of job satisfaction in organizational literature (e.g. Politis, 2005; Todd and Kent, 2006).

Implications Because of the connection between career satisfaction and turnover intention, a greater impetus for control of the coaching landscape is placed within the control of today’s intercollegiate athletics administrator. Not only does the administration impact career satisfaction through support, but by shaping the job description of the coach, thus, impacting the amount of satisfaction the coach has with his or her specific coaching position. Further responsibility might be distributed, as well, into the hands of national coaching associations i.e. NABC, AFCA, NFCA, etc. Here, the national coaching associations are charged with enhancing their respective coaching professions through support and education. Perhaps, now aware of the ability of job satisfaction to mediate relationships with career satisfaction, thus influencing rates of turnover intention and impacting the coaching profession, a more profound examination into the factors that influence job satisfaction will ensue. This examination should, potentially, rank higher than other items on a coaching association’s agenda, such as sport structure, playing rules, or sport promotion. Findings from this article might also provide additional insight into perpetual inequities in the intercollegiate coaching profession (e.g. Acosta and Carpenter, 2006). It should be noted that satisfaction levels were fairly high and that there were no significant differences in levels of satisfaction between the male and female coaches. This finding is both refuted in past literature (Sagas and Ashley, 2000) and supported (Pastore, 2003; Sagas et al., 2005). Sagas and Ashley (2000) discovered that male coaches recorded significantly higher levels of job satisfaction than their female counterparts, and displayed significantly lower levels of occupational turnover intention. While no significant gender differences existed here, the inevasible discrepancy between male and female coaching numbers does (see Acosta and Carpenter, 2006). While it was beyond the scope of the current study, future research should examine more thoroughly the multi-faceted construction of job satisfaction for male and female coaches. A similar approach would be merited for race in the coaching profession, as well.

Limitations and Future Directions The use of the sample of head coaches exists as a potential limit upon the external validity of the findings. The mean organizational tenure of the respondents was nearly nine years, indicating at least a moderate level of job satisfaction. Utilizing a sample with graduate assistants and assistant coaches might offer more diverse results, particularly if the coaches had shorter organizational or professional tenures. In the same vein, the head-coach sample

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limited the results as we were unable to reach out towards those coaches that had either left the profession due to lack of job or career satisfaction. For further exploration, the internal career anchors of the career satisfaction research model (Jiang and Klein, 2000) should be more fully-integrated and applied towards the coaching profession. Ideas of identity, autonomy, and more are imperative towards the individual in the coaching profession and, therein, might contain potential gender and racial differences for which past sport management literature has searched. A larger sampling of intercollegiate coaches would also make possible the ability to disaggregate the sample of respondents by level NCAA affiliation. Potential differences in perceived gender discrimination or perceived promotional opportunities between the three broad NCAA divisions (I, II, and III) would be able to illuminate the culture of athletics at each level that might contribute to such differential outcomes. Additionally, care needs to be taken when interpreting any questionnaire results, especially those cross-sectional in nature. In an attempt to control for common method variance, several questions were reversed scored. Additionally, care needs to be used when interpreting the results. While the results suggest satisfaction with supervisor may lead to career satisfaction through job satisfaction, alternative interpretations are possible. One possibility may be that those who are satisfied with their career choice may find their work environment more pleasant. This could lead to higher rating of satisfaction with coworkers, including a supervisor. While the sample involved college coaches, we would suggest that the findings would generalize past college coaches, but also to high school and professional coaches. At the high school level, this may be of significance to athletic directors and school administration as a reduction in coaching migration may reduce general turnover for teachers (Ryan and Sagas, 2006). It is further suggested here as the results in this study reinforce Jiang and Klein’s (2000) findings for information technology professionals that the findings are generalizable to much of the working population. Future work, both within sport and outside sport, should continue examining internal and external career anchors through the testing of the Career Satisfaction Research Model (Jiang and Klein, 2000). Additionally, as mentioned above, potential difference in career anchors for those from different race, gender, backgrounds, etc., should be examined. While this study examined the effect of satisfaction with supervisor, further work needs to be done on how the different needs and backgrounds of workers affect their perceived satisfaction with a supervisor. Finally, the general quality of work life for coaches needs to continually be explored through a variety of methods. It is suggested that qualitative work be used to deepen the understanding of the specific ways that supervisory support effects satisfaction with the supervisor. Moreover, examine specific factors within athletic departments and schools that lead to dissatisfaction which may affect career satisfaction. It is suggested that quantitative methods be used to examine the broadness of phenomena discovered through qualitative exploration.

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Contemporary Athletics Compendium, Volume 3 Editor: James H. Humphrey

ISBN: 978-1-60741-561-9 © 2009 Nova Science Publishers, Inc.

Chapter 9

STEROIDS IN INTERSCHOLASTIC ATHLETICS: DOES REASONABLE SUSPICION EXIST? John J. Miller∗1, John T. Wendt2 and Sean Kern1 1

2

Texas Tech University, Lubbock, Texas, USA University of St. Thomas, St. Paul, Minnesota, USA

ABSTRACT Despite the notoriety that steroid use has attained, relatively little research has been conducted regarding interscholastic athletics. Miller and Wendt (2007) reported that more than twice the number of the state athletic directors perceived that steroid use was extensive throughout the United States than in their state. Additionally, the results indicated that while 40% were uncertain whether interscholastic athletes in their program had taken steroids, 25% of the athletic directors had suspected athletes is in their program had done so. Moreover, nearly 30% had suspected athletes from other athletic programs had used steroids. However, a limitation of this study was that the ascertained information came from only one state. This study expanded this number to three states. The results indicated that 33% of the respondents suspected athletes in their programs of taking steroids while 65% had suspected had suspected interscholastic athletes in other programs of taking steroids

Evidence about performance-enhancing drugs, specifically anabolic steroids abounds in many recent news reports. While most of the media reports have been on professional sports, another area of focus is developing in interscholastic athletics (Latiner, 2006; Miller and Wendt, 2007). This attention is not unwarranted as interscholastic athletes have been caught using steroids in Texas and Arizona, among other states (Dickerson, 2005; Moore, 2005). Additionally, the commissioner of the Florida High School Athletic Association stated that, ∗

Send all correspondence to: John J. Miller, Ph.D., Associate Professor, Department of Health, Exercise, and Sport Sciences, Box 41121, Texas Tech University, Lubbock, TX 79409-1121, Phone: (806) 742-3361, FAX: (806) 742-0877; Email: [email protected]

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“You begin to worry about how widespread the problem is at the professional level. You know that there has to be a trickle-down effect when it comes to that, and that would be to the colleges and high schools” (Kallestad, 2005). For many high school athletes the drive to win, sometimes at all costs, is all encompassing. Aside from bragging rights and personal satisfaction, a young athlete may be driven to obtaining a Division I scholarship or professional contract. To achieve such goals, athletes may incorporate supplements and performance-enhancing drugs into their training. According to an Arizona high school athlete, “The people who just have natural talent and work really hard almost can’t compete. You’re either really gifted or taking steroids to get really mean and strong” (Dickerson, 2005). Devoid of any consequences, a potential message being sent is that performance enhancing drugs such as steroids are essential to achieve success. This perception was very evident as a young athlete confessed to his father just prior to committing suicide that was linked to steroid use: I’m on steroids, what do you think? Who do you think I am? I'm a baseball player, baseball players take steroids. How do you think Bonds hits all his home runs? How do you think all these guys do all this stuff? You think they do it from just working out normal? (Fainaru-Wada, 2004, p. 1A).

ESTIMATED NUMBER OF STEROID USERS IN HIGH SCHOOL It has been estimated that 1 to 3 million athletes in the United States had taken steroids (Silver, 2001). Another study by Blue Cross/Blue Shield (2003) indicated more than 1 million adolescents between the ages of 12-17 had taken performance-enhancing supplements and drugs. A more significant result of the study revealed that all youths surveyed knew someone using performance-enhancing substances such as steroids. A 2002 study by Texas AandM University estimated that up to 42,000 Texas high school aged students were abusing steroids (Livingstone, 2005). An investigation by the American College of Sports Medicine (ACSM) (2004) stated that more than one out of every ten students in the United States would have used steroids by 2010. The Center for Disease Control and Prevention (CDC) (2004) has indicated that illegal steroid use between ninth through twelfth grade students has more than doubled in the last decade from 2.7% in 1991 to 6.1% in 2003. Another study by the CDC illustrated an alarming steroid use of adolescents in which 11.2% of high school males in Louisiana and 5.7% of high school girls in Tennessee had taken steroids (Office of the National Drug Control Policy, 2005). While these reports point toward the potential likelihood of the use of steroids by high school students, they may identify the proverbial “tip of the iceberg” for steroid use in interscholastic sports. Moreover, it is alarming that significantly few high school students perceive steroids as being harmful (Johnston, O’Malley, Bachman, and Schulenberg, 2003). “Everyone knows it, but they hide it. It’s a win-win situation for everybody, so no one’s going to admit anything” (Dickerson, 2005).

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STATE STEROID TESTING LEGISLATION In response to testing interscholastic athletes for steroids a Michigan legislator stated, “Is it a problem right now? I think we’re naive to think that it’s not with the competitive nature of sports, especially among the kids who want to go on to the next level” (States consider high school steroid testing, 2005). It has been reported that 13% of high schools test for drugs nationally, but less than one-third of those schools test for steroids (National Federation of State High School Associations, 2003). Despite this traditional practice, some states (New Jersey, Florida and Texas) and counties (Polk County, Florida) have recently enacted legislation requiring interscholastic athletes to submit to steroid testing (Moore, 2005). New Jersey was the first state to implement drug testing for steroids on the high school level at an estimated cost of$100,000. On December 20, 2005 then acting Governor Richard Codey, by Executive Order, directed the New Jersey Department of Education to work with the New Jersey Interscholastic Athletic Association (NJSIAA), “… to develop and implement a program of random testing for steroids of teams and individuals qualifying for championship games” to commence with the 2006-2007 school year” (State of New Jersey, 2005). Under the NJSIAA plan, the high school league randomly tested approximately 500 student athletes that qualified for state championship tournaments or competition, primarily in football, wrestling, baseball, track and field, swimming and diving, and lacrosse (NJSIAA Steroid FAQ, 2007).

It is interesting that NJSIAA mandated that no student may participate in NJSIAA competition unless the student and their parent/guardian signed a random testing consent form. The consent form stipulated that if the student or the student’s team qualified for a state tournament, the participant may be subject to testing for banned substances (NJSIAA Policy, 2007). If a student-athlete tests positive for steroid use the penalty for such an offense is a one year suspension. In 2007 the Florida State Legislature allocated $100,000 for the testing and ordered the Florida High School Athletic Association (FHSAA) to facilitate a one year anabolic steroid testing program (2007-08) for students in grades 9 through 12 who participate in boy’s football, girls’ flag football, girls’ softball, boys’ baseball, or boys’ and girls’ weightlifting (Florida Statutes, 2007). State Representative Marcelo Llorente, the bill’s sponsor, said that those sports were chosen because they are sports where muscle mass most enhances performance (Kallestad, 2007). Under the Florida plan each student-athlete who participated in the identified sport, was required to sign a consent form (FHSAA Consent Form, 2007). It was estimated that 59,000 Florida high school students who participated in one of the three sports would be affected and be required to submit to random drug tests under the bill (Bender, 2007). If a student-athlete tested positive for steroids, a 90 day suspension penalty would be assessed. Texas has perhaps the most ambitious plan as the state legislature allocated an estimated at $3 million to implement high school steroid testing policies and procedures. As a result, the Texas University Interscholastic League (UIL), which governs interscholastic athletics, plans to test a minimum 3% of the approximately of the 740,000 student athletes students who participate in UIL athletic activities annually. To put this number into perspective, the three

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percent of the 740,000 represents 22,000 high school students which is more than those tested in the NCAA and Olympics from 2004 (International Herald Tribune, 2007). Under the Texas program each student and their parent/guardian agrees that as a prerequisite to participation in UIL athletic activities, they will, if selected, submit to steroid testing. As opposed to the three month suspension that a Florida athlete who tests positive would have to serve, the consequences in Texas are more severe. For example, the punishment for the first time an athlete tests positive for steroids is a 30 day suspension. If that same student-athlete tests positive a second time a one year ban is assessed. Finally, a third time offender will be banned from any type of competition for the remainder of his/her career. The Texas testing protocol was scheduled to begin before the high school football season ended in the fall of 2007. However, it is still in the review process. UIL spokeswoman Kim Rogers said, “We don’t know when it will begin and when it will end.” Texas State Representative Dan Flynn, House sponsor of Senate Bill 8, which created the $3 million a year steroid-testing program said, “Nothing has happened. Football season is over, and we did not test one kid” (Sharrer, 2007).

REASONABLE SUSPICION With all of the concern surrounding who might be taking steroids, the concept of reasonable suspicion may occur. Reasonable suspicion may be regarded as the degree of knowledge that would cause a reasonable person, under similar circumstances, to believe a student-athlete is involved in using or abusing a banned substance. In such cases an athletic director, athletic trainer, or coach may request a drug test. As a result, school officials need only have reasonable suspicion that a particular test will verify that a student-athlete has violated or is violating the law (Shulter, 1996; Yamaguchi, O’Malley, and Johnston, 2004; Zirkel, 2000). Although reasonable suspicion may be present, to be permissible, the scope of the search must be such that the measures used are reasonably related to the purpose of the search, and not excessively intrusive in light of the age and gender of the student and the nature of the suspected infraction. The New Jersey v. T.L.O (1985) court stated, A school official may properly conduct a search of a student’s person if the official has a reasonable suspicion that a crime has been or is in the process of being committed or reasonable cause to believe that the search is necessary to maintain school discipline or enforce school policies. (New Jersey v. T.L.O., p. 329, 1985).

In Schaill v. Tippecanoe County School Corporation (1988) the court held that the school's interest in protecting health, safety, and integrity of sport and school outweighed an athlete's diminished expectations of privacy. In Schaill, the school board chose to employ a random drug-testing program for all extracurricular participants including interscholastic athletes and cheerleaders. The court reported the drug testing policy to be reasonable because

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it was commonly conducted in intercollegiate athletics and Olympic sports. Moreover, the students had previously consented to the testing procedure. Drug testing of a student by a public school official is a search that must adhere to the stipulations of the Fourth Amendment that prohibits all unreasonable searches and seizures by state officers. Reasonableness is determined by balancing the governmental interest behind the search against the privacy intrusion of the search. Generally, courts have ruled that drug testing for athletic teams is allowed due to a diminished expectation of privacy of a studentathlete. For example, it is not uncommon for student-athletes to disrobe in front of others or use communal showers after a practice or game. Because these are normal practices the courts have reported that those who choose to participate in interscholastic sports have a diminished expectation of privacy (Knapp, 1990). The court in Vernonia v. Acton (1995) indicated that urine collection and testing compromised a search. To determine the constitutionality of searches, three steps are required. The first aspect to be considered is whether a search and seizure was conducted by a government entity. The second step needs to identify if the officials have the power to conduct the search. The third piece addresses whether the search was reasonable depending upon the type of search. In shaping the idea of reasonableness in searching high school students the Supreme Court stated that: The legality of a search of a student should depend simply on the reasonableness, under all the circumstances, of the search. Determining the reasonableness of any search involves a twofold inquiry: first, one must consider whether the action was justified at its inception, second, one must determine whether the search as actually conducted was reasonably related in scope to the circumstances which justified the interference in the first place. Under ordinary circumstances, a search of a student by a teacher or other school official will be justified at its inception when there are reasonable grounds for suspecting that the search will turn up evidence that the student has violated or is violating either the law or the rules of the school (New Jersey v. T.L.O., 1985, p. 341).

While upholding the drug testing policy in Vernonia (1995), the Supreme Court balanced the school's interest in conducting the drug test against the privacy interest upon which the test intrudes. In the Court's opinion, safety risks were especially great in sports: Finally, it must not be lost sight of that this program is directed more narrowly to drug use by school athletes, where the risk of immediate physical harm to the drug user or those with whom he is playing his sport is particularly high. Apart from psychological effects, which include impairment of judgment, slow reaction time, and a lessening of the perception of pain, the particular drugs screened by the District's Policy have been demonstrated to pose substantial physical risks to athletes (p. 661).

Finally, the Board of Education v. Earls (2002) permitted urinalysis drug testing for all high school extracurricular participants. By doing so, the Earls decision expanded the scope identified in Vernonia by permitting a school district to test high school students with less of a foundation.

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PURPOSE OF THE STUDY Despite the notoriety that steroid use has attained, relatively little research has been conducted regarding interscholastic athletics. Miller and Wendt (2007) reported that more than twice the number of the state athletic directors perceived that steroid use was extensive throughout the United States than in their state. Additionally, the results indicated that while 40% were uncertain whether interscholastic athletes in their program had taken steroids, 25% of the athletic directors had suspected athletes is in their program had done so. Moreover, nearly 30% had suspected athletes from other athletic programs had used steroids. However, a limitation of this study was that the ascertained information came from only one state. Thus, it is the purpose of this study to determine the level, if any, of interscholastic directors in multiple states of suspecting student-athletes of using steroids.

METHOD Design and Procedure The authors for this investigation developed a 1-5 Likert scale 20-item questionnaire. The Likert scale responses ranged from 1=strongly agree, 2=agree, 3=unsure, 4=disagree, and 5=strongly disagree. The questionnaire consisted of sections relating to the following areas: demographic information, suspicion of interscholastic athlete use of steroids, reasons for the suspicions. In order to ensure the reliability of the questionnaire, a test-retest protocol was conducted with two present and three retired high school athletic directors. Several changes to the questionnaire regarding item inclusion and item wording were suggested and implemented. The re-test was accomplished two weeks later with the same group of professionals and no additional modifications were recommended. To determine the validity of the instrument, a Pearson product-moment correlation coefficient (Pearson’s r) was employed. The reliability coefficient was determined to be .78, which is well within the acceptable range for the interpretation of scores for individuals (Patten, 2000). The population for this study was 345 randomly selected interscholastic athletic directors from three states. One state is located in the southwestern part of the United States, the second is located in the mid-south, and the third is located in the upper Midwest. To maintain confidentiality, all surveys were sent en masse and all results were accumulated using a SelectSurvey ASP online survey tool. Thus, those specific individuals who completed and returned the survey could not be determined thereby ensuring anonymity and confidentiality. After the initial email, 63 responses were received indicating that the individual was no longer at that address. To ensure that all representatives were given an opportunity to participate in this study, one of the investigators went to the each school’s website to determine if that person was still employed at the school. If another individual had become the athletic director a survey was electronically sent to that individual. If no response had been received after one week following the initial contact, a follow-up email was sent. In 15 cases, the email address of the athletic director no longer appeared thus the total population of the study was 330. Of the 330 athletic directors contacted, 117 (35%) from three states

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responded to the online survey. Even though the investigators had hoped for a higher return, the response rate was within the parameters for effective online surveys (Paolo, Bonaminio, Gibson, Patridge, and Kallail, 2000).

RESULTS Demographic Information A demographic breakdown of the respondents revealed that 44 (38%) resided in the midSouth, 39 (33%) from the Southwest, and 34 (29%) from the upper Midwest. Occupationally, 71 (61%) had been an athletic director for 1-5 years. This result corresponds to the finding that 64 (55%) had been at their present position for 1-5 years. Seventy-three (62%) of the respondents reported that they were reasonably knowledgeable about interscholastic sports, including the ability to identify symptoms of steroid use. For this study, a reasonably knowledgeable person was one who understood all aspects of interscholastic sports. Thus, it appeared that the majority of respondents were well-informed regarding steroids but relatively new in interscholastic athletic administration.

Suspicion of Athletes Taking Steroids The athletic directors were asked if they had reason to suspect interscholastic athletes in their own programs of using steroids. While 64 (55%) did not suspect their athletes of steroid use it is noteworthy that 39 (33%) had suspected such a practice. Interestingly, 76 (65%) had suspected interscholastic athletes in other programs of taking steroids and 23 (20%) did not. To determine if any relationships existed among the states, a Pearson r correlation was employed (p=.05). The results indicated a significant relationship (p=.008) appeared between the states and athletic directors who suspected athletes in other interscholastic programs of using steroids. Although a relationship between states and suspecting their own athletes of taking steroids did not meet the established level of significance, a correlation of .074 pointed towards the significant level. The respondents were given opportunities to provide open-ended answers for their suspicions. The primary reasons given were extraordinary gains in size (82%), perceived strength (78%), speed (73%), or a combination (68%). Also, such items as increased aggression, unexplainable facial hair and/or deepened voice were cited as reasons for suspicion. Finally, the population was asked to identify the gender of the student-athlete(s) they had suspected. More than 97% male and approximately 2% female were identified.

DISCUSSION The use of performance enhancing drugs is not a new trend (Bahrke and Yesalis, 2002). For example, the winner of the 1904 Olympic marathon purportedly received an injection of the performance-enhancing drug, strychnine, while the race was occurring. However, the

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performance enhancing abilities of today’s drugs are much more advanced and effective today than in the days of strychnine. Current media coverage has created a greater awareness of performance enhancement drug from the general public to the governing bodies of sport. The issue of performance enhancing drugs, especially anabolic steroids has attracted worldwide attention. Taking steroids to enhance athletic performance is not a new topic in interscholastic sports. This history can be traced back to the early 1950s during which Russian Olympic athletes started to outperform their counterparts from the United States due to steroid use. Soon thereafter a physician associated with the U.S. Olympic team worked with chemists to create the steroid Dianabol for the Americans (McDevitt, 1994). The use of steroids spread to the point that the first documented case of a high school football athlete taking steroids to improve his performance in the late 1950’s (Sturmi and Diorio, 1998). While the use of performance enhancing drugs such as steroids have attained notoriety in professional sports, the use of such drugs in interscholastic athletics is of significant concern today since about 57% of all high school students play on formal sports teams (Grunbaum, Kann, Kinchen, Ross, Hawkins, Lowry, Harris, McManus, Chyen, and Collins, 2004). Yet, the results of a national survey revealed that less than 30% of high schools had tested for steroids (National Federation of State High School Associations, 2003). While many question the effectiveness and legality of steroid testing, Frank Uryasz, president of the National Center for Drug Free Sport, has stated that testing ultimately will be needed to put teeth into any anti-steroid plan (Moore, 2005). Even the United States Olympic Committee has taken notice. USOC spokesman Darryl Seibel said, The high school athletic associations and the legislatures are absolutely doing the right thing by taking a serious look at this problem. The reported rates of steroid use at the high school level are not only alarming, they reveal the extent to which this is becoming a societal problem” (Pells, 2007).

For testing to occur, however, reasonable suspicion needs to exist. The concept of reasonable suspicion, as put forth by the U.S. Supreme Court, requires significantly more substantiation than mere curiosity, rumor or general suspicion. Items that have been recognized by courts for searching a student include observing particular and quantifiable behavior that would lead a reasonably knowledgeable professional to believe that a student is engaged or has engaged in illicit behavior. While a previous study has indicated relatively few interscholastic directors have been reported to be knowledgeable about performanceenhancing drugs (Tokish, Kocher, and Hawkins, 2004), they possess a duty to diminish exposing an athlete to foreseeable harm, including ingesting illegal substances (Heckman, 2000). The results of this study indicate that the majority of athletic directors have suspected athletes in other programs of being “on” steroids. The reasons for their suspicion such as extraordinary gains in size, strength, speed or a combination have been recognized as potential symptoms of steroid use (Bhasin, Storer, Berman, et al., 1996; Miller, 2000; National Institute on Drug Abuse [NIDA], 2004). Also, such items as increased aggression, unexplainable facial hair and/or deepened voice appear to be valid symptoms of steroid use (Pope, Kouri, and Hudson, 2000). While it is interesting that the majority of respondents

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believed that “others athletes” were taking steroids, it is noteworthy that one-third of the athletic directors believed that some their “own athletes” had taken steroids. To make doubt tangible, school officials may consider testing student-athletes for steroids under the auspices of reasonable suspicion. A primary criticism of steroid testing in interscholastic athletics is that only a few athletes will be submitted to them. For example, in New Jersey only the athletes on teams competing in the state final will be asked for a steroid test. As a result some, if not many, of the offenders may avoid detection due to prior knowledge of when a test might occur. Yet, Robert DuPont, president of the Institute for Behavior and Health and first director of the National Institute on Drug Abuse, recently described the need for drug testing in high schools, The schools that have, at least the ones that I know who have used random student drug testing, are all convinced that it makes a big difference in the quality of the school life. One study done by Linn Goldberg found that when he compared athletes in two schools, one that used student drug testing and one that didn’t, and the school that did use the drug testing had one-quarter the drug use of the school that was not using drug testing. I don’t know whether it reduced it by 75%, which is what the study found, but it surely does. And it flies in the face of reason to think it wouldn’t. It would be a little bit like arguing that if you enforce the speed limit on the highway, won’t slow down. That fact is that when there is a reason not to use, in this case random student drug testing, the students do less drugs (Justice Talking, 2006).

CONCLUSION This study should not be construed as advocating for testing as the only method to curb steroid use in interscholastic athletics. In fact, the authors have previously proposed a threestep approach to limit the use of steroids in interscholastic athletics. The proposal included mandating administrators or others in charge of extracurricular activities to become knowledgeable about performance enhancing drugs such as steroids; educating the studentathlete about the consequences of taking steroids; and incorporating random steroid drug testing for interscholastic athletics. There is a serious question about the efficacy to which testing is successful in decreasing the use of performance-enhancing substances, as opposed to merely generating new ways to avoid detection. For example, in cases when testing occurred for announced, in-season or unannounced, out-of-competition training the results indicated that users were not being identified (Jacobs and Samuels, 1994). However, it should be pointed out that these tests were being conducted on older professional or Olympic athletes who had the knowledge and wherewithal to avoid detection. It may be reasonable to believe that most interscholastic athletes do not adequately possess the background or information to mask taking the substance. Presently, only New Jersey, Florida and Texas have passed state legislation requiring high school students to submit to drug testing for steroids. Steroid testing in interscholastic activities has even received attention from the White House. In October, 2007 John Walters, Director of National Drug Control Policy (ONDCP) (2007), hailed the results of New Jersey’s plan as a successful example of preventing drug use among youth,

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John J. Miller, John T. Wendt and Sean Kern Results from New Jersey’s steroid testing program demonstrate the immense prevention power of random student testing and should provide an impetus for other communities to consider implementing programs of their own. Building on the success of this program, New Jersey and other States with steroid testing programs should consider expanding the random drug tests to include other drugs commonly abused by young people, like marijuana and prescription pain killers (White House Office of National Drug Control Policy, 2007).

One of the problems of these steroid testing policies has been that only a few athletes would be selected to take the test and only after a championship. For example, according to the New Jersey State Interscholastic Athletic Association only one high school athlete out of 500 tested positive for steroid use during the testing process. This type of suspicionless random testing, however, may permit those who had taken steroids to “slip through the cracks” by not being selected. This argument provides even greater fodder for state high school associations to increase the educational process of athletic administrators, coaches, and athletes so as to better understand the symptoms and consequences of steroid use. The results of this study revealed that athletic directors suspected that athletes, primarily from other teams, had used steroids at the interscholastic level. Although some may perceive this information as simple allegations against the competition, the fact that many of the respondents recognized several valid symptoms of steroid use is important to note. Additionally, it is significant that a majority of the respondents felt confident in recognizing the signs of steroid use. It is hoped that through this increased knowledge that athletic administrators will have an even greater basis on which to reasonably suspect steroid use in interscholastic athletics. It has been alleged that drug-testing procedures violate a student-athlete’s their right of privacy and breaches their right to participate, yet, the courts have held that participation in sports is considered a privilege and not a right (Palmer v. Merluzzi, 1988). The implementation of random suspicionless drug-testing of interscholastic athletes may have a significant outcome on thwarting or decreasing steroid use. If those in charge of the program suspect that interscholastic athletes of taking steroids, the need for testing along with education, is clear. Since high school is a place where adolescent patterns develop that may lead into adulthood, it should be the first place that school officials make certain that student are aware of the consequences of taking illicit drugs such as steroids (Vernonia v. Acton, 1995). The Supreme Court has stated the safety of students to be a valid government interest that outweighs the students’ constitutional protection from unreasonable searches and seizures (Board of Education v. Earls, 2002; Vernonia v. Acton, 1995). It would be logical, therefore, for the Supreme Court to authorize testing in high schools for performance-enhancing drugs, as long as the privacy and safety of the students are considered. It is also true that the steroid use may immediately present a risk to the health and safety of the student-athlete, but those risks may be judged to be within acceptable limits than the risk of losing a game, championship or scholarship. Just as bad money drives out good, athletes using performance-enhancing drugs will ultimately make those who choose not to a minority at the interscholastic level unless educational and testing regulations are stringently implemented and enforced.

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Limitations and Future Research As with many investigations there are limitations. First, we examined the responses of athletic directors of only three state interscholastic associations. Therefore, the results of this study cannot be generalized to a national basis. However, it should be noted that the response rate was 35%, which is above the acceptance rate for online survey research (Anderson and Gansneder, 1995). Second, it can only be assumed that the respondents responded in a truthful and honest fashion. Lastly, the athletic directors that did not participate in the study may have in fact possessed suspicions or beliefs regarding steroid use and testing but simply choose not to disclose it. Future research may include athletic directors in all 50 state associations regarding their perceptions of steroid use in interscholastic athletics to determine whether the results of this survey can be applied to a greater population. Additional research could further explore the idea regarding the perceived use of steroids by interscholastic athletes as well as others involved in extracurricular high school activities. Finally, given the increased opportunities that exist to continue competition at the intercollegiate and professional levels, a study could deal with the female interscholastic athletes who may be or have taken performanceenhancing drugs such as steroids.

REFERENCES American College of Sports Medicine. (2004). The use of anabolic-androgenic steroids in sports. Retrieved September 5, 2007 from http://www.acsm.org/ publications/newsreleases2004/steroids071404.htm. Anderson, S. E., and Gansneder, B. M. (1995). Using electronic mail surveys and computer monitored data for studying computer mediated communication systems. Social Science Computer Review, 13(1), 33-46. Bahrke, M. S. and Yesalis, C. E. (November, 2002). The future of performance-enhancing substances in sport. The Physician and Sportsmedicine, 30(11), 51-53. Bhasin, S., Storer, T.W., Berman, N., Callegari, C., Clevenger, B., Phillips, J., Bunnell, T. J., Tricker, R., Shirazi, A., and Casaburi, R. (1996). The effects of supraphysiological doses of testosterone on muscle size and strength in normal men. New England Journal of Medicine, 335(1), 1-7. Blue Cross Blue Shield. (2003). Blue Cross/Blue Shield says 1.1 Million teens have used performance enhancing sports supplements and drugs. Retrieved on September 24, 2007.from http://www.supplementquality.com/news/ ephedra_teens_BCBS.html Board of Education v. Earls, 2002 U.S. LEXIS 4882. Centers for Disease Control and Prevention. (May 2004). National youth risk behavior survey: 1991-2003. Morbidity and Mortality Weekly Report. Retrieved on October 25, 2007 from http://www.cdc.gov/ mmwr/PDF/SS/SS5302.pdf. Dickerson, J. (2005). Shooting stars. Retrieved on December 7, 2007, from http://www.timespublications.com/sept05-feature1.asp

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Fainaru-Wada M. (December 19, 2004). Dreams, steroids, death: A ballplayer's downfall. San Francisco Chronicle, A1. Florida High School Athletic Association. (2007). 2007-08 state of Florida/FHSAA anabolic steroid testing program. Retrieved on December 3, 2007, from http://www.fhsaa.org/ compliance/steroid_testing/drug_test_ prog_info.pdf Florida High School Athletic Association. (2007). Consent of member school to participate in random testing of student-athletes in grades 9-12 for use of anabolic steroids. Retrieved on December 3, 2007, from http://www.fhsaa.org/compliance/steroid_testing/ drug_school_consent_form.pdf Florida Statutes. (2007). 1006.20 athletics in public K-12 schools. Retrieved on December 3, 2007, from http://www.leg.state.fl.us/statutes/index.cfm? App_mode=Display_StatuteandURL=Ch1006/ch1006.htm Grunbaum, J. A, Kann. L, Kinchen, S. A, Ross, J., Hawkins, J., Lowry, R., Harris, W.A., McManus, T., Chyen, D., and Collins, J. (2004).Youth risk behavior surveillance: United States - 2003. Morbidity and Mortality Weekly Reports Surveillance Summaries, 53, 1 – 96. Heckman, D. (2003). The evolution of drug testing of interscholastic athletes. Villanova Sports and Entertainment Law Journal, 9, 209-228. International Herald Tribune. (2007). Doping: China cracking down on the drug industry: Drugs. Retrieved on December 3, 2007, from http://www.iht.com/articles/ 2007/11/08/sports/DRUGS.php#end_main Jacobs, J. B. and Samuels, B. (1994). The drug testing project in international sports: Dilemmas in an expanding regulatory regime. Hastings International and Comparative Law Review, 18, 557- 590 . Johnston, L. D., O’Malley, P. M., Bachman, J. G., and Schulenberg, J. E. (2003). Monitoring the future: National results on adolescent drug use, overview of key findings. Retrieved on October 14, 2007 from http://www.monitoringthefuture.org/pubs/monographs/overview2003.pdf. Justice Talking Radio Transcript. (August 21, 2006). Does drug testing student athletes deter drug use? Retrieved on November 1, 2007 from http://www.justicetalking.org/transcripts/060821_drugsstudents_transcript. pdf. Kallestad, B. (2005). Steroid cleanup takes aim at teens. Retrieved October 23, 2007 from http://www.washtimes.com/national/20050425-122712-5045r.htm. Latiner, C. (Summer, 2006). Steroids and drug enhancement in sports: The real problem and the real solution. DePaul Journal of Sports Law and Contemporary Problems, 3, 192219. McDevitt, E. R. (2003). Ergogenic drugs in sports. In: DeLee, J. and Drez, D.(eds.), Orthopaedic Sports Medicine: Principles and Practice. 2nd ed. (471 –483). Philadelphia, PA: WB Saunders. Miller, J. and Wendt, J.T. (2007). Interscholastic athletic directors perceptions of steroid use: A state study. Journal of Contemporary Athletics, 2(3), 207-224. Miller, J., Wendt, J. T. and Seidler, T. (in press). Tackling steroid abuse in interscholastic athletics: Perceptions of athletic directors. International Journal of Sport Management.

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Moore, D. L. (May 5, 2005). As steroid use doubles, a school fights back: How one high school is educating coaches and students is at the heart of a policy California might adopt this week, U.S.A. Today, 1A. National Federation of State High School Associations. (2003). Sports medicine: high school drug-testing programs. Retrieved on November 30, 2007 from www.nfhs.org. National Institute on Drug Abuse. (2004). Research report series – Anabolic steroid abuse 1. Retrieved on December 11, 2007 from http://www.nida.nih.gov/PDF/RRSteroi.pdf. New Jersey State Interscholastic Athletic Association. (2007). NJSIAA steroid testing policy. Retrieved December 3, 2007, from http://www.njsiaa.org/NJSIAA/07steroidmemo.pdf New Jersey State Interscholastic Athletic Association. (2007). NJSIAA steroid testing policy: Consent to random testing. Retrieved December 3, 2007, from http://www.njsiaa.org/NJSIAA/07policyconsent.pdf New Jersey State Interscholastic Athletic Association. (2007). NYJSIAA steroid testing policy: Frequently asked questions. Retrieved December 3, 2007, from http://www.njsiaa.org/NJSIAA/Steroid-FAQ.pdf New Jersey v. T.L.O., 469 U.S. 325, 338 (1985). Palmer v. Merluzzi, 689 F. Supp. 400, 412, 415 (D.N.J. 1988). Paolo, A. M., Bonaminio, G. A., Gibson, C., Patridge, T., and Kallail, K. (2000). Response rate comparisons of e-mail and mail distributed student evaluations. Teaching and Learning in Medicine, 12 (2), 81-84. Patten, M.L. (2000). Questionnaire research: A practical guide. Los Angeles, CA: Pyrczak Publishing. Pells, E. (2007). States find difficulty imposing high school steroid tests. Retrieved December 7, 2007, from http://www.southcoasttoday.com/apps/pbcs.dll/ article?AID=/20070708/SPORTS/707080377. Pope, H. G, Kouri, E. M, and Hudson, J. I. (2000). Effects of supraphysiologic doses of testosterone on mood and aggression in normal men: A randomized controlled trial. Archives of General Psychiatry, 57(2), 133-140. Schaill v. Tippecanoe County School Corporation, 864 F.2d 1309 (7th Cir. 1988). State of New Jersey. (2005). Executive order #72, acting governor Richard J. Codey. Retrieved December 3, 2007, from http://www.state.nj.us/ infobank/circular/eoc72.htm Scharrer, G. (2007). School steroid-testing plan may be posted today. Retrieved December 7, 2007, from http://www.chron.com/disp/story.mpl/metropolitan /5330838.html. Shutler, S.E. (Summer, 1996). Random, suspicionless drug testing of high school athletes. Journal of Criminal Law and Criminology, 86(4), 1265-1304. States consider high school steroid testing. (2005). Retrieved September 21, 2007, from http://www.msnbc.msn.com/id/7628183/. Sturmi, J. E. and Diorio, D. J. (1998). Anabolic agents. Clinical Sports Medicine, 17, 261282. University Interscholastic League. (2007). UIL banned substance testing questions and answers. Retrieved December 3, 2007, from http://www.uil.utexas.edu/athletics/forms/ pdf/policy/steroid_testing_faq.pdf

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University Interscholastic League. (2007). UIL parent and student Notification/Agreement form: Illegal steroid use and random steroid testing. Retrieved December 3, 2007, from http://www.uil.utexas.edu/ athletics/forms/pdf/policy/steroid_agreement.pdf. University Interscholastic League. (2007). UIL testing protocol. Retrieved December 3, 2007, from http://www.uil.utexas.edu/athletics/forms/pdf/ policy/UIL_testing_protocol.pdf. Vernonia School District 47J v. Acton , 515 U.S. 646, 115 S. Ct. 2386, 132 L. Ed. 2d 564, 1995 U.S. LEXIS 4275, 63 U.S.L.W. 4653, 9 Fla. L. Weekly Fed. S 229, 95 Cal. Daily Op. Service 4846 (1995). White House Office of National Drug Control Policy. (2007). White House drug czar heralds results of New Jersey random student steroid testing. Retrieved December 3, 2007, from http://www.whitehousedrugpolicy.gov/news/ press07/101007.html. Yamaguchi, R., O’Malley, P.M., and Johnston, L.D. (Winter, 2004). Relationships between school drug searches and student substance use in U.S. Schools. Educational Evaluation and Policy Analysis, 26(4), 329-341. Zirkel, P. A. (2000). Suspicionless searches. Principal, 79(5), 57–61.

Contemporary Athletics Compendium, Volume 3 Editor: James H. Humphrey

ISBN: 978-1-60741-561-9 © 2009 Nova Science Publishers, Inc.

Chapter 10

IN DEMAND? EXAMINING SPORT MANAGEMENT FACULTY OPENINGS AND HIRES Edward (Ted) M. Kian∗1, Paul M. Pedersen2 and John Vincent3 1

University of Central Florida, Orlando, Florida, USA 2 Indiana University, Bloomington, Indiana, USA 3 University of Alabama, Tuscaloosa, Alabama, USA

ABSTRACT Over the past 25-30 years, sport management has been among the fastest growing academic disciplines in higher education within the United States. However, the few universities producing sport management doctoral graduates have seemingly been unable to meet the demands for qualified individuals to teach at the university level. This study analyzed each of the 124 professorial advertisements for sport management/administration placed by U.S. universities over a one-year period, encompassing the 2005-06 academic year. The majority of the openings were in the Southeast, Northeast, and Midwest, with few listings in the Southwest or West. Nearly half of all listings were at institutions offering sport management only at the undergraduate level. A phone survey revealed only 69% of advertised positions were filled, with 53% of schools with failed searches citing a lack of desired applicants. A majority of schools that did not hire planned to re-post their positions the following academic year.

Keywords: Academic Positions, Faculty Jobs, Announcements, Hires ∗

Please send all correspondence to: Edward (Ted) M. Kian, Ph.D. Sport Leadership – Graduate Program Coordinator. University of Central Florida, PO Box 161250. Orlando, FL 32816-1250. Email: [email protected]. Office: 407-823-4631. Cell: 407-927-5403. Fax: 407-823-3859

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The exponential growth of the academic field of sport management/sport administration over the last 25-30 years has been well-documented (e.g., Cuneen, 2004; Mahony, Mondello, Hums, & Judd, 2006). Parkhouse and Pitts (2001) noted the number of sport management programs offered at universities and colleges in North America grew from 20 in 1980 to more than 200 in 2000. While there is no exact figure for the number of institutions currently offering sport management degrees, Cuneen (2006) noted there were more than 300 sport management or related programs at universities throughout the world. The discipline is most popular with students seeking employment in the sport industry and intercollegiate athletes (Crockett, 2005). Possibly due to the rapid rise of sport management as an academic discipline, university graduate programs appear to be having difficulty producing enough qualified future professors to teach within these sport management programs (Costa, 2005; Mahony, Mondello, Hums, & Judd, 2004). Several authors have noted a lack of qualified professors to teach sport management courses, leading to universities facing supply-and-demand difficulties in hiring and retaining sport management faculty (e.g., Cuneen, 2004; Mahony et al., 2006; Mondello, Mahony, Hums, & Moorman, 2002; Mondello, Mahony, Judd, & Hums, 2006; Stier, 2001; Weese, 2002). Jisha and Pitts (2004) found only eight North American universities that either issued doctoral degrees in sport management or a closely related field, or offered concentrations for doctoral degrees in those areas. Related to this shortage of Ph.D. programs, Mahony et al. (2004) found sport management programs collectively produced only 15 doctoral graduates per year. However, several universities have since implemented Ph.D. programs in sport management/administration. In 2007, the North American Society for Sport Management (NASSM) Web site listed 22 North American universities or colleges that advertised doctoral programs in sport management/administration, with 19 of those schools based in the United States. Several authors have examined sport management academic job openings. In general, this research has shown the number of openings seems to be increasing annually. Mahoney et al. (2004) found there was an average of 75 sport management faculty openings per academic year from 1996-97 through 2000-01, which included an increase each year from a low of 48 positions in 1996-97 to a high of 112 openings in 2000-01. Pedersen and Schneider (2003) found 128 international sport management faculty/teaching positions that were advertised during the 2000-01 academic year, while Pedersen, Whisenant, and Schneider (2005) found a slight increase to 131 openings the following academic year. In the most comprehensive study of sport management academic job openings to date, Pedersen, Fielding, and Vincent (2007) examined sport management/administration faculty position announcements from 2001-02 through 2005-06 at colleges and universities in 12 countries. The authors found a total of 655 total openings over that five-year period, with 594 of those either fulltime sport management teaching or research jobs, or sport management teaching positions that included other duties. The number of postings increased from 131 in the 2001-02 academic year to a five-year high of 158 in 2005-06. Overall, 594 (91%) of the 655 openings were at schools based in the U.S. Therefore, the increasing popularity of this academic field appears to be centered predominately within the U.S., and thus examinations of job opportunities in this discipline should focus on the U.S. The work of Pedersen and Schneider (2003) is the only published article that attempted to determine how many posted sport management academic positions were actually filled. Using a written questionnaire and telephone calls, the authors received a 91% response rate for the

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128 posted positions during the 2000-01 academic year, 117 (91%) of which were located in the U.S. They found only 62% of those positions were actually filled to begin employment during the following academic year. The majority of those hires (65%) were at the assistant professor level, with 10% hired at the associate professor level, and 7% as lecturers. No other researchers have attempted a similar study since. While the number of open positions has increased since Pedersen and Schneider’s (2003) examination of the 2000-01 openings, so have the number of programs offering doctoral degrees in sport management/sport administration. Seemingly, those schools should be able to produce more students with doctoral degrees to provide a broader applicant pool to potentially fill faculty positions. Therefore, new data is needed to determine if sport management in U.S. academia remains a “buyers’ market” for doctoral students, as well as current faculty considering positions at other schools.

METHOD This study consisted of two parts. First, a content analysis was employed to locate posted job openings from universities within the United States and then to determine which of these jobs should be classified as sport management/sport administration academic positions. Second, a phone survey was conducted to see how many of those positions were actually filled. Two researchers, working independently of each other, searched from August 1, 2005, through July 31, 2006, for any academic postings in sport-related fields from three sources: The Chronicle of Higher Education Internet site, HigherEdJobs.com, and the Sport Management Listserv e-mail service. Areas searched for potential listings included sport(s) management, fitness management, sport(s) administration, athletic(s) administration, sport(s) leadership, sport(s) marketing, sport(s) studies, physical education, and recreation management. All listings for department chairs, associate or assistant professors, instructors, lecturers, and full-time adjunct professors were included for potential examination. Jobs that stated primary teaching and/or research responsibilities in sport or fitness management, sport or athletics administration, or sport leadership were automatically included in the study. Other listings were only included if it was determined by the researchers that 50% or more of the duties were in sport management-related areas. For example, a job posting for a professor in a school of business that listed sport marketing as one of several potential teaching areas was not included in this study if no other sport courses were listed as teaching areas. In contrast, an advertisement that listed primary teaching duties in both physical education and sport management was included. Sport studies positions were included if the job listings entailed teaching or research duties in any sport management core areas as set by NASSM (i.e., budget and finance in sport, communication in sport, economics in sport, governance in sport, legal aspects of sport, management and leadership in sport, marketing in sport). However, three sport studies positions that specifically stated primary teaching/research responsibilities in the sport social sciences (e.g., history, sociology) were not included for examination. One researcher compiled an initial list of 140 openings that could be included in the study, including multiple job positions at some universities. The second researcher’s initial

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list included 120 openings, including three that were not on the first researcher’s list. Thus, the initial intercorder agreement in this study was 83.6% between independent researchers. Through further analysis of the posted listings, discussions between the two primary researchers, and phone calls to selected universities in question, a final list of 125 different job postings from 111 universities were determined to fall within the parameters of this study and thus be classified as sport management/sport administration academic job openings at U.S. universities or colleges. A brief phone survey was formulated. Respondents were first asked if a hire was made for the stated position. If so, respondents were asked if the hired candidate was on a tenured or tenure-track line, employed full-time, and the incoming rank or title of the individual hired. If the respondents answered that a hire was not made, they were then asked if the line was scheduled to or had been re-listed, if the lack of hiring was due to financial considerations and/or a lack of desired applicants, and if the position had been offered to at least one person. From September 25, 2006, through, November 14, 2006, a representative who was able to answer each of these questions was reached from all 111 colleges or universities that posted advertisements, resulting in a 100% response rate. Depending on the size of the school and program, and the availability to reach someone via phone, respondents included deans of colleges, department chairs, program heads, associate and assistant professors in the same department, and program administrators. It should be noted the decision to re-list a position may have changed in either direction after respondents were reached. In addition, two different representatives from one school on the list for the 125 job postings said they never had an opening that could be classified under sport management/administration and no new hires in their department were made. Finally, 16 additional postings were advertised through these three outlets that may have fallen within the study’s parameters of a sport management opening but were offered by universities located outside of the United States. These listings were for positions in Australia (5), Canada (3), Great Britain (4), New Zealand (1), Singapore (1), South Korea (1), and Turkey (1).

RESULTS Content Analysis The content analysis revealed a final total of 124 sport management openings at U.S. universities posted on at least one of three sources used to locate positions. Overall, 56 (45%) of those job openings were at private institutions, while 68 (55%) were at public universities or colleges. A total of 57 positions (46%) were at schools that offer only an undergraduate degree, major, emphasis, or specialization in sport management or a related area. A single position at one school offered only an undergraduate minor in sport management. A total of 43 job postings (35%) were at colleges or universities that offer both undergraduate and master’s degrees, majors, specializations, or an emphasis in sport management. Institutions that field only master’s programs accounted for 11 openings (9%), while nine job postings (7%) were at universities that offer sport management degrees at all three levels: undergraduate, master’s, doctorate. Only two openings (2%) were at schools that offer both master’s and doctoral degrees but not one at the undergraduate level. One opening was at an

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institution that had no sport management program at any level. However, a representative from that particular college said the school plans to add such a program in the near future. The majority of the 124 postings were colleges or universities located in the Southeast (n=44, or 35%), Northeast (n=40, or 32%), and Midwest (n=23, or 19 %). There were fewer job postings for openings in the Southwest (n=10, or 8%) or West (n=7, or 6%). Institutions in New York had the most openings of any state with 14 (11%), followed by Florida with 12 (10%), and Pennsylvania with 10 (8%). No other state had more than six openings. Schools from 41 different states had at least one opening, while 22 states had multiple job postings.

Phone Survey Of the 124 job postings, the phone survey revealed 86 (69%) of those were filled. All 86 hires were for full-time employment, and 65 (76%) of those positions were filled by an individual who was hired on a tenure line. The 86 hires included 60 (70%) at the assistant professor level, 14 (16%) associate professors, three (3%) visiting lecturers, two instructors (2%), two lecturers (2%), and one each with the titles of adjunct professor, assistant athletic director, clinical assistant professor, department chair, and program director. Among the 68 job postings from public colleges or universities, approximately 46 (68%) were filled. Private colleges filled 40 (71%) of their 56 openings. Hires were made for 34 (77%) of the 44 posted positions at schools in the Southeast. Colleges or universities in the Northeast made 25 hires (63%) from their 40 posted positions. Schools in the Midwest filled 17 (74%) of 23 openings. There were approximately six hires (60%) for the 10 posted positions in the Southwest and four position fillings (57%) among the seven openings in the West. Colleges or universities that offered sport management/sport administration programs only at the undergraduate level filled 37 (65%) of 57 posted positions. Schools with programs only at the master’s level made eight hires (73%) for 11 posted positions. Colleges or universities that fielded programs at both the undergraduate and master’s level made 34 hires (79%) for 43 posted positions. Approximately six hires (67%) were made for the nine positions posted from universities or colleges that fielded programs at all three levels. One hire (50%) was made among the two postings at schools which offered programs at the master’s and doctorate levels only. No hires were made at the school that only offered a sport management undergraduate minor, or at the school that fielded no programs but has plans to do so in the future. Of the 38 positions not filled, school representatives at 29 (76%) of those colleges or universities said they planned to or had already re-posted the same position during the 200607 academic calendar year, with a position starting date of January, 2007, in three cases, or for the start of the 2007-08 academic year for the remaining 26 positions. Representatives from seven schools (18%) among the 38 that did not hire said they would not re-list the position the following year, while two (5%) more program reps were unsure if their positions would be re-listed the following year. Representatives from six (16%) of the 38 positions that were not filled said inadequate finances played a part in not hiring anyone, while financial issues were not cited as a factor for the other 32 schools (84%) that did not hire. Finally, 20 representatives (53%) of schools that did not fill their respective vacancies said that a lack of

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desired applicants factored into departments’ decision not to hire anyone for the posted position.

CONCLUSIONS AND DISCUSSION The data from the content analysis revealed there continues to be a high demand for qualified candidates applying for sport management/sport administration academic openings. This study found 124 advertisements for academic positions in sport management at U.S. colleges or universities posted during the 2005-06 academic year. Pedersen et al. (2007) found an average of 119 sport management/sport administration academic job openings per year from their examination of job listings from 12 countries over five years of academic calendars. Therefore, the number of sport management academic positions in the U.S. appears to still be on the rise as had been noted by previous researchers (Mahony et al., 2004; Pedersen et al., 2007). The majority of job postings in 2005-06 were at academic institutions that offer only an undergraduate degree in sport management or related field (n=57, or 46%), or at schools that offered both an undergraduate and a master’s degree in sport management (n=43, or 35%).This reinforces the notion of sport management as a practitioner-based academic discipline, while recognizing the scarcity of schools that offer doctoral programs in this area (Jisha and Pitts, 2004; Mahony et al., 2004; Mondello et al., 2002). This project was the second known study that attempted to determine how many sport management academic job postings were filled in an academic calendar year. Just 69% of the 124 openings posted during the 2005-06 academic year resulted in hires. This marked an improvement from the 62% of hires Pedersen and Schneider (2003) found in their analysis of jobs posted during the 2000-01 academic year. However, there appears to still be a shortage of quality candidates to fill these positions. Only six (16%) of the 38 failed or cancelled searches were attributed in part due to financial reasons. More disturbing for deans, department chairs, and search committee chairs who are attempting to hire sport management faculty, at least 29 (76%) of the openings that resulted in failed searches were slated to be reposted during the 2006-07 academic year. Moreover, 53% of the schools that did not fill their positions advertised during the 2005-06 academic year were not satisfied with their applicant pool. Based on the results of this phone survey, it appears the lack of programs producing doctoral students cited by previous researchers has resulted in a shortage of quality candidates (Mahony et al., 2006; Weese, 2002). It remains a fruitful market for recent sport management doctoral graduates and current sport management faculty considering relocation to another school. In contrast, universities seeking to hire faculty in this area may need to offer more incentives to entice qualified candidates, who will likely be sought by other universities as well. Failed searches likely diminish the quality of specific sport management programs, possibly resulting in a shortage of quality teachers and researchers in specific areas, enrollment caps, and larger classes (Pedersen & Schneider, 2003; Stier, 2001). This research did not attempt to find out how many of the 86 hires were gainfully employed at other universities before accepting these positions. However, it is plausible several schools that lost faculty members to other universities during this period may have

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waited until the following year to post their vacancies. Amazingly, this implies sport management academics may be even more in demand than the one-sided statistics discovered in this study. A high number of positions (n=57, or 46%) were at schools offering a sport management degree at only the undergraduate level, so it was not surprising the vast majority of hires (n=69, or 80%) were as assistant professors, lecturers, instructors, or fulltime adjunct professors. This could also be in part due to the relative newness of sport management, resulting in a lack of experienced job applicants. Overall, the results of this study re-affirmed previous research, which found that sport management academia remains a viable market for doctoral graduates and faculty who are open to considering positions at other universities (Mahony et al., 2006; Mondello et al., 2006; Pedersen & Schneider, 2003). It is clear there still remains a need for sport management doctoral programs to produce more qualified graduates to fill these vacant positions.

REFERENCES Crockett, S. S. (2005). Why undergraduate students choose sport management as a major: Factors influencing college choice decisions. Unpublished master’s thesis. Florida State University. Costa, C.A. (2005). The status and future of sport management: A Delphi study. Journal of Sport Management, 19(2), 117-142. Cuneen, J. (2006). From the editor. Sport Marketing Quarterly, 15(3), 1. Cuneen, J. (2004). Managing program excellence during our transition from potential to merit. Journal of Sport Management, 18(1), 1-12. Jisha, A., and Pitts, B. (2004). Program choice factors of sport management doctoral students in North America. Sport Management and Related Topics Journal, 1(1), 2-14. Mahony, D.F., Mondello, M., Hums, M.A., and Judd, M. (2006). Recruiting and retaining sport management faculty: Factors affecting job choice. Journal of Sport Management, 20(3), 414-430. Mahony, D.F., Mondello, M., Hums, M.A., and Judd, M.R. (2004). Are sport management doctoral programs meeting the needs of the faculty job market? Observations for today and the future. Journal of Sport Management, 18(2), 91-110. Mondello, M., Mahony, D.F., Hums, M.A., and Moorman, A.M. (2002). A survey of search committee chairpersons: Candidate qualifications preferred for entry-level sport management faculty positions. International Journal of Sport Management, 3(4), 262281. Mondello, M.J., Mahony, D., Judd, M., and Hums, M. (2006). Sport management doctoral students in North America: Perceptions of their graduate training. International Journal of Sport Management, 7(2), 160-173. Parkhouse, B. L., and Pitts, B. G. (2001). Definition, evolution, and curriculum. In B.L. Parkhouse (Ed.), The management of sport: Its foundation and application (3rd ed., pp. 2-14). New York: McGraw-Hill.

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Pedersen, P.M., Fielding, L., and Vincent, J. (2007). A five-year content analysis of academic positions in sport management: Professorial announcements and advertisements from 2001-02 through 2005-06. International Journal of Sport Management, 8(4), 447-461. Pedersen, P.M., and Schneider, R.G. (2003). Investigating the academic openings in sport management: An analysis of the field’s professorial position announcements and hires. International Sports Journal, 7(1), 35-47. Pedersen, P.M., Whisenant, W.A., and Schneider, R.G. (2005). Analyzing the 2001-02 sport management faculty openings. International Journal of Sport Management, 6(2), 154164. Stier, W.F. (2001). The current status of sport management and athletic (sport) administration programs in the 21st century at the undergraduate and graduate levels. International Journal of Sport Management, 2(1), 60-97. Weese, W.J. (2002). Opportunities and headaches: Dichotomous perspectives on the current and future hiring realities in the sport management academy. Journal of Sport Management, 15(1), 1-17.

Contemporary Athletics Compendium, Volume 3 Editor: James H. Humphrey

ISBN: 978-1-60741-561-9 © 2009 Nova Science Publishers, Inc.

Chapter 11

THE IMPORTANCE OF PARENT PHYSICAL ACTIVITY LEVELS AND THEIR EXPECTATIONS FOR THEIR CHILDREN’S HEALTH: A PATH ANALYSIS Marc Lochbaum∗, Tara Stevens, Yen To and Sarah Stevenson Texas Tech University, Lubbock, Texas, USA

ABSTRACT Rates of childhood obesity are reaching epidemic levels. The purpose of this investigation was to determine if parent behavior and expectations are associated with estimates of their children’s leisure time activities and their adult body size. Bandura’s (1986) social cognitive theory guided the investigation. Participants were 121 parents of 65 kindergarten and 56 fifth grade students from a midsized rural school district. The majority of parents were minorities with a low percentage of parents having obtained degrees beyond a high school diploma. Parents completed measures to assess their physical activity level, their preferences for their children’s leisure time activity, estimates of time spent in a variety of leisure time activities, and an estimate of their children’s adult body size as an adult. Parents spent very little time in physical activity though their preference was for their children to be active. Path analysis was conducted on a model that described relationships between parents’ activity levels and their preferences for their children’s activity, parents’ activity levels and that of their children, and parents’ preferences for their children’s physical activity and their children’s time spent in physical activity. An association was also posited between parents’ preferences for their children’s physical activity and their children’s body size as an adult. Path ∗

Correspondence for this manuscript should be addressed to: Marc Lochbaum, Ph.D. Department of Health, Exercise and Sport Sciences, Texas Tech University, Box 43011. Lubbock, Texas 79409-3011. Email: [email protected]. 806.742.3371 (phone). 806.742.1688 (fax)

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Marc Lochbaum, Tara Stevens, Yen To et al. analysis goodness of fit indices indicated a good fit (e.g., SRMR = .02, CFI = 1.00). All associations were in the hypothesized direction. In addition, the greater preference for children to be active was associated with a decrease in estimated body size as an adult by the parents. The percent of variance accounted for (< 10%) in the significant paths do suggest that several important variables were missing in our model. Future research longitudinal research that incorporates more extensive measures of both parents and their children are discussed.

Keywords: social cognitive theory; childhood obesity; adult obesity.

INTRODUCTION It is far too common to hear parents to say to their children "do as I say, not as I do." Most likely these parents are failing to serve as appropriate role models for their children's behavior, and thus, their development. Social cognitive theory emphasizes the role of models and observational learning in children's development (Bandura, 1986). Social cognitive theory ostensibly supports the importance of actual parent behavior when considering parents' influence on their children’s development. It is important to note that Bandura (1986, 2001) has also described individuals as agents in their own behavior. That is, individuals (children) who observe models (their parents) will process the models' behavior and make determinations about the reproduction of the behavior. The determination about reproduction depends upon the context of personal characteristics and considerations of rewards and consequences. This explanation suggests that children do have the capability of avoiding behavior learned through observation, even when the model is a parent. The American public is now well aware that an obesity epidemic is plaguing the country. Not only are American adults growing larger (U.S. Census Bureau, 2007), but so also are American children (CDC, 2007; Deckelbaum and Williams, 2001). The National Center for Health Statistics (2006) reported that approximately 25 million American children were currently obese or overweight revealing a 300% increase in childhood obesity rates since 1980. Currently, at least 15 states are reported to have at least 26% of their adult population as obese (TFAH, 2007). Even more shocking, 32 states are reported to have 60% of their adult population classified as either overweight or obese (TFAH, 2007) with the majority of these states being in the southwestern region of the country. In addition, it is not surprising to find that the states with the highest rates of obesity are generally the same states with the highest rates of physical inactivity (TFAH, 2007). The current cost in healthcare and physical and mental well-being is staggering as our society continues to grow predominantly obese. Adult obesity and physical inactivity is linked to numerous health care problems ranging from hypertension, coronary heart disease, diabetes, stroke, and some cancers (CDC, 2006a; Flegal, Carroll, Kuczmarski, and Johnson, 1998; TFAH, 2007). Consequentially, the annual cost of obese and overweight adults to that nation’s health care system fluctuates from a low of $69 billion to a high of $117 billion (DHHS, 2003). According to researchers the cost of adult physical inactivity, overweight, and obesity accounts for over 25% of total health care costs in the U.S. (Anderson, Martinson, Crain, Pronk, Whitebird, O’Connor, et al., 2005). For children, ages 6 to 17 years, one study

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revealed the associated hospital costs of obesity amplified three-fold from a cost of $35 million in 1979 to more than $127 million in 1999 (Wang and Dietz, 2002). The CDC reported in 2006 that more than 22% of the adult population in the U.S. report not engaging in any physical activity (CDC, 2006b). In addition more than half of adults do not engage in 20 minutes of vigorous activity three times per week, the CDC’s recommended level of physical activity. Many have considered that the lack of parents' physical activity is influencing the sedentary lifestyle of their children (Arluk, Branch, Swain, and Dowling, 2003; Fogelholm, Nuutinen, Pasanen, Myöhänen, and Säätelä, 1999; Polley, Spicer, Knight, and Hartley, 2005). Parents are modeling a sedentary lifestyle absent of vigorous activity for their children; however, parents are also showing their preference for their children's physical activity through their increased support of organized sports as 20 to 25 million children participate in organized youth sports each year and an additional 25 in organized public/private school sports (Hutchinson and Ireland, 2003; Tanji, 1991). It is very important to gain an understanding as to whether or not children are more likely to develop physical activity habits based on what they observe their parents doing or based on what they hear their parents saying? Hence, the purpose of our research is to address this question through the evaluation of a path model based on theoretical propositions that posits relationships between parents' levels of physical activity, parents' preferences for their children's physical activity, and estimates of the time the children actually spend engaged in vigorous physical activity.

BACKGROUND OF PRESENT INVESTIGATION Through social interactions, individuals develop self-perspectives and beliefs that influence their behavioral choices and selection of environments. Although children observe their parents' physical activity levels, this information is routed through their self-perspectives and beliefs. Thus, a bidirectional relationship exists between individuals, their behavior, and the environment to create triadic reciprocal causality (Bandura, 1986). When considering the problem of obesity, children will likely observe the physical activity of a wide variety of individuals; however, children are most frequently exposed to their parents (Moore, Lombardi, White, Campbell, Oliveria, and Ellison, 1991). Also, during the elementary years, parents still provide an important influence on their children's behavior (Coley, 1998; Singer and Miller, 1999). Therefore, one would expect parents to be a model higher in status than the others, which would make it more likely that young children would select to model their parents' behavior. Additionally and critical to social cognitive theory, the frequent exposure children have to their parents would assist in children's ability to recall and reproduce the behavior. Specifically, based on recall and reproduction of observed behaviors, one would expect that children who observe highly active parents will be more active than children who observe their parents being mainly sedentary. Interestingly, researchers have failed to find a significant relationship between parents' levels of physical activity and that of their children (e.g., Anderssen, Wold, and Torsheim, 2005; Trost, Sallis, Pate, Freedson, Taylor, and Dowda, 2003). Anderssen et al. (2005) conducted a longitudinal study of 557 adolescents across an eight year period. The researchers assessed both the parents and their children's self-reported levels of leisure-time

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physical activity. The researchers also evaluated the associations between changes in parents' physical activity and the changes in their adolescents' physical activity over the eight year period. Results did not reveal statistically significant associations and indicated the presence of either weak or non-existent relationships. Similar to Anderssen and colleagues (2005), Trost et al. (2003) evaluated the physical activity levels of adolescents utilizing a sample of 380 middle and high school students as well as their parents. In addition to assessing physical activity levels of all participants, the authors assessed parental support for physical activity and their children’s self-efficacy perceptions related to physical activity participation. These variables were assessed to test a theoretical model positing a relationship between parent physical activity orientation and their children's physical activity that was routed through parental support and self-efficacy for physical activity. The authors reported that the model failed to provide adequate fit to the data, but identified parental support as an important correlate of children’s physical activity through its association with self-efficacy in a revised model with path coefficients ranging from 0.17 to 0.24. Thus, the authors did not find parental levels of physical activity to be an important factor in the prediction of children's physical activity, but found parents’ capacity to provide motivational support to be important. In addition to Trost and colleagues (2003), Davison, Cutting, and Birch (2003) reported that parent support of physical activity was associated with children's physical activity. Davison and colleagues utilized a sample of 180 nine-year-old girls and their parents to evaluate the relationship between activity-related parenting strategies and children's physical activity patterns. Significantly higher levels of physical activity were observed in girls who had at least one parent who reported high levels of physical activity support when compared to girls who had no parent providing such support. The findings suggest that parents' modeling of physically active behavior tends to be much less influential than their support of their children’s participation in physical activity concerning their children’s physical activity behavior. Social Cognitive Theory's triadic reciprocal causation gives credence to models and observational learning; however, not only does the model influence the viewer but the viewer has the opportunity to evaluate the model. Anderssen et al., (2005) and Trost et al., (2003) both investigated adolescents who likely had opportunities to interact with peers as well as other adults. As a result, these children likely had multiple models from which to choose behavior. Moreover, as children enter into adolescence they tend to be less interested in their parents as their peers begin to gain more influence over their decisions (Biddle, Bank, and Marlin, 1980; Eccles, 1999). The failure to find a relationship between parent physical activity and the physical activity of adolescents could be explained by these issues; however, elementary children typically spend more time with their parents than do adolescents. In addition, children tend to identify with their parents (Peretti and Statum, 1984a, 1984b) more so than with their peers. Hence, parents tend to be more important models than peers for younger children than for adolescents. Finally, one must consider that although the influence of parents' physical activity on the activity level of their children is questionable, parents' physical activity is likely related to parents' preferences for their children's physical activity. This relationship seems plausible as inconsistency between beliefs and behavior can result in discomfort (Festinger, 1957). Parents who engage in physical activity likely possess some beliefs about the value and importance of such behavior. To not ascribe similar beliefs to the activity levels of their children would be

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unusual; thus, parents who are physically active likely encourage or support their children in such endeavors.

Purpose and Hypotheses of Present Investigation The purpose of the present study was to simultaneously evaluate the importance of both parent activity level and parent encouragement of children’s physical activity in the prediction of children’s time spent in vigorous physical activity as well as to evaluate the role of parent encouragement in the prediction of children’s expected body size. A path model was developed that evaluated these relationships. A positive association was hypothesized between parents' level of physical activity and parent preference for their children's physical activity as well as children’s time spent in physical activity. Finally, parents' expectations of their children's adult body size, was included in the model to gain insight into the specific problem of obesity. We hypothesized parents' preferences for their children's physical activity would be negatively associated to their estimation of their children's body size as an adult.

METHOD Participants Participants were 121 parents of 65 kindergarten and 56 fifth grade students who were attending a rural, yet midsized, school district in the Southwestern United States. The average age of the mothers was 33.16 (SD = 6.35) and the average age of the fathers was 35.81 (SD = 7.83). The mothers' ethnicity was most frequently described as Hispanic/Latino (56.2%), followed by White (37.2%), Black/African American (1.7%), American Indian/Alaskan Native (.8%), and Asian (.8%). Four (3.3%) of the parents described the mother's ethnicity as other or failed to endorse a category. Similarly, the fathers' ethnicity was most frequently described as Hispanic/Latino (56.2%), followed by White (32.2%), Black/African American (5.0%), and American Indian/Alaskan Native (.8%). Four (3.3%) of the parents described the father's ethnicity as other or failed to endorse a category. The educational level of both mothers and fathers in the sample was typically less than a bachelor's degree. The majority of the mothers (36.4%) were described as being a high school graduate. The remainder was reported as having some college but no degree (28.9%), less than a high school education (17.4%), a bachelor's degree (10.7%), an associate's degree (5.0%), a master's degree (.8%), and doctoral degree (.8%). Similar to the mothers, the majority of the fathers (39.7%) were described as being a high school graduate. However, in contrast to the mothers, a larger number of fathers were reported as having less than a high school education (28.9%). The remaining fathers were described as having some college but no degree (13.2%), a bachelor's degree (5.8%), an associate's degree (5.0%), a master's degree (1.7%), and doctoral degree (.8%).

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Instruments Parents' Physical Activity. The International Physical Activity Questionnaire (2005 [IPAQ]) Short Form was utilized to evaluate parents' physical activity levels. The IPAQ was developed for use with individuals ranging from 15 to 69 years of age and designed to yield both categorical and continuous estimates of adult physical activity. The IPAQ requested that parents record the number of days during the last seven that they engaged in vigorous physical activity, moderate physical activity, and walking. In addition, they were asked to estimate how much time in hours and minutes that they typically spent doing those types of activities. A final question asked parents how much time they spent on a typical day sitting during the last seven. The volume of activity was computed by weighting each type of activity (i.e., vigorous, moderate, and walking) by its energy requirements which are defined in multiples of the resting metabolic rate or MET. These MET values for each activity were derived from the Ainsworth et al. Compendium (2000). MET values are not calculated for the sitting question as the MET is an estimate of energy expenditure, which is limited in sitting. Instead, the sitting score simply reflects the minutes parents engaged in sitting. The IPAQ has frequently been utilized to assess adult physical activity (e.g., Al-Hazzaa, 2007; Meriwether, McMahon, Islam, and Steinmann, 2006; Timperio, Salmon, Rosenberg, and Bull, 2004), and the evaluation of the reliability and validity associated with IPAQ scores has extended across countries (e.g., Craig, Marshall, Sjostrom, Bauman, Booth, Ainsworth, et al., 2003; Ekeland, Sepp, Brage, Becker, Jakes, Hennings, and et al., 2006; McFarlane, Lee, Ho, Chan, and Chan, 2006) and special populations (e.g., Faulkner, Cohn, and Remington, 2006). Brown, Trost, Bauman, Mummery, and Owen (2004) found evidence supporting acceptable levels of test-retest reliability for both activity status and sedentary behavior. Craig et al. (2003) also found support for reliability and validity of scores through the assessment of test-retest correlations and concurrent correlation with another measure of activity. These results are consistent with those of the test developers (IPAQ, 2007) who assessed 2,450 adults from 14 countries and reported Spearman's Rho that clustered around .8 for repeat administrations over a three to seven day period and a median rho of .30 with the CSA accelerometer for minutes of vigorous, moderate, walking, and sitting behavior. Parents' Preferences for Children's Activity. To assess parent preferences for their children's engagement in physical activity, parents were asked to rate the types of after school activities in which they preferred their children to participate in for leisure. Parents rated 10 activities from three domains; vigorous activity (e.g., Working out at a gym at school or other location), cognitive activity (e.g., Reading a book or magazine), and sedentary activity (Watching television); using a scale ranging from 1 “strongly discourage” to 10 “strongly encourage.” The subscales were calculated by summing the item scores. Principal components analysis using Promax rotation was employed to evaluate the presence of the three expected factors. Confirmatory factor analysis was not utilized as the small sample size was not appropriate for the evaluation of a model including more than 10 parameters (see Kline, 1998). A clean factor structure resulted with the three factors accounting for 62.53% of the variance (see Table 1). The first factor was indicated by three items associated with vigorous physical activity, the second factor was indicated by three items associated with cognitive activity, and the third factor was indicated by four items associated with sedentary behavior. Internal consistency estimates of Cronbach's alpha for each subscale were .71, .67, and .74, respectively.

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Children's Time Spent in Activity. Children's time spent engaged in physical activity was assessed in a manner parallel to that of parents' preferences for children's activity. Parents were asked to record how much time (i.e., hours and minutes) their children actually spend engaging in the activities identified in the preferences measure during a typical week. Totals in minutes were calculated for each domain; vigorous activity, cognitive activity, and sedentary behavior. Children's Adult Body Size Expectation. Children's expected adult body size was estimated by their parents through the use of a set of gender specific pictures ranging from an adult of slight build (i.e., 1) to one that is clearly obese (i.e., 9). These pictures were similar to those of Thompson and Gray (1995). With nine body sizes included, parents were asked to circle the image that they believed their child's body will look like as an adult. The researchers then recorded the associated number between one and nine that corresponded to the parents' response. Table 1. Factor Loadings for Parents’ Preference for Children’s Activity Measure

Items Attending specialized activity classes (e.g., gymnastics, karate, ballet, etc.) Playing on an organized sports team Working out at a gym (at school or other location) Reading a book or magazine Playing a game outside with friends Playing board games (puzzles, checkers, etc.) Playing video games Watching television Watching videos or movies Playing on the computer (surfing the internet, etc.)

Vigorous

Factor Cognitive

Sedentary

.86 .81 .51 .82 .78 .61 .85 .79 .69 .66

Procedure Upon receiving permission from the superintendent and administrative personnel, parent contact information was collected from all kindergarten and fifth grade campuses in a school district located in the Southwest. Parents were mailed a consent form requesting their participation as well as the questionnaire in both Spanish and English. A self-addressed envelope was also included in the mailing for parents to return the forms directly to the researchers. In addition to the mail out, consent forms and questionnaires were distributed from the school several weeks later as a reminder. The return rate was approximately 14%, which reflected the schools' stated response rate for similar information requests.

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RESULTS Descriptive Statistics Means and standard deviations for each variable are presented in Table 2. Consistent with the research describing the use of the IPAQ, the present scores were extremely skewed with the majority of parents expending limited amounts of energy through vigorous, moderate, or walking activity. Due to concern for restricted range in the IPAQ subscales and this effect on correlational analyses (see Table 3), including path analysis, the total IPAQ score was transformed using logarithmic transformation and a constant of one to bring the smallest value, which was zero, to one (Tabachnick and Fidell, 2001). Table 2. Means and Standard Deviations for All Variables in Model Variable

M

SD

Vigorous activities

21.77

6.39

Cognitive activities

23.13

4.99

Sedentary activities

15.38

6.44

Vigorous activities

272.36

296.67

Cognitive activities

783.34

779.02

Sedentary activities

885.25

1578.68

Expectation of Body Size

3.36

1.30

Time spent Sitting

249.97

177.99

Preference

Time spent

Note: Values are listed in units of minutes.

A review of the means and standard deviations for the remaining variables indicated that although parents expressed a greater preference for activities that were vigorous physically and cognitive in nature over those activities that were sedentary, parents reported that their children spent the majority of their leisure time engaged in sedentary activities. In fact, children spent the least amount of time, only about 4.54 hours, engaged in vigorous activity each week. This is in sharp contrast to the 14.75 hours each week they spent involved in sedentary tasks, such as watching television, playing video games, and surfing the Internet. The correlation matrix in Table 3 revealed that parent preferences for their children's activity did not always correlate with their report of how their children actually spent their

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leisure time. Two of the relationships, one relating to vigorous activity and the other to sedentary activity, were statistically significant; however, the associations were somewhat small. Interestingly, parents' sitting behavior was more strongly related to their activity preferences for their children in comparison to their level of physical activity or IPAQ total score. This was true for the original IPAQ scores as well as for the transformed scores. Parents' sitting behavior was also related to parent estimates of their children's adult body size. Based on the aforementioned descriptive analyses and concern for the lack of expected correlations between the IPAQ total score, both transformed and not, we decided to proceed with the path analysis using the estimate of parent sitting behavior to represent their activity levels. In addition, we decided to evaluate only vigorous activity in the path analysis as it is the central focus of the paper and tended to be more strongly associated with the expected variables.

Path Analysis The theoretical model described in Figure 1 was evaluated using LISREL 8.52 (Joreskog and Sorbom, 2002) and the Simplis programming language. Goodness of fit indices were selected based on the recommendations of Hu and Bentler (1999). A two-index presentation strategy that involved an estimate of close to .09 for the maximum likelihood (ML) based standardized root mean squared residual (SRMR) and close to .95 for the ML based comparative fit index (CFI) was employed. Modifications to the path model were not considered as this model was specified based on theory. The model fit the data well considering the Hu and Bentler (1999) guidelines (SRMR = .02; CFI = 1.00) as well as other standards for the evaluation of goodness of fit. For example, the estimate of χ2(2) was .52, which was not statistically significant (p = .77), and the Tucker Lewis Fit Index or Non Normed Fit Index reached 1.19. The former signals good model to data fit when statistical significance is not achieved and the latter indicates good fit when values are greater than .90 (Tabachnick and Fidell, 2001).

Figure 1. Theoretical model.

Table 3. Correlation Matrix for IPAQ Scales, Parent Preference, and Time Child Spent Variable

1

2

3

4

5

6

1.Parent Sitting 2.Walk MET 3.Moderate MET 4.Vigorous MET 5. Total MET 6. Transformed TOT Preference 7. Vigorous

---.15 -.15 -.16 -.19 -.16

--.18 .38** .71** .48**

--.50** .66** .44**

--.88** .51**

--.63**

---

-.26**

.16

.10

.13

.16

.14

---

8. Cognitive 9. Sedentary Time Child Spent 10. Vigorous

.09 .21*

-.03 .06

.08 -.003

-.003 -.10

-.01 -.06

.07 -.06

.43** .03

-.003

-.03

.01

-.01

-.003

.14

.28**

.08

-.10

---

11. Cognitive 12. Sedentary

.14 .08

-.08 -.05

-.02 -.05

-.01 -.08

-.03 -.07

.10 .02

-.06 -.11

.16 .06

.17 .32**

.20* .09

Note: Multiples of the resting metabolic rate (MET). * p < .05, **p < .01.

7

8

9

--.30**

---

10

11

12

--.74**

---

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Figure 2. Parameter estimates: Vigorous activity.

All parameter estimates were statistically significant with the exception of the path from parent sitting behavior to children's time spent in vigorous activity (see Figure 2). The remaining variables were related as expected with an increase in sitting behavior associated with a decrease in parent encouragement of their children's vigorous activity and an increase in parent preference for their children's vigorous activity associated with an increase in their children's actual time spent in vigorous activity. Finally, parents' preference for their children's engagement in vigorous activity was negatively related to their estimates of their children's body size as adults. That is, if parents encouraged the vigorous physical activity of their children, they also expected their children to be smaller in body size once they reach adulthood. Despite the presence of good model to data fit and statistically significant parameters, the amount of variance accounted for in any path was relatively low (less < 10%). The amount of variance in parents' estimates of their children's adult body size accounted for by their preference for their children's vigorous physical activity was 5.5%. Parents' preference for their children's vigorous activity and parents sitting behavior accounted for 7.8% of the variance in children's time spent engaged in vigorous physical activity and parents' sitting behavior accounted for 8.9% of the variance in their preferences for their children's vigorous physical activity.

CONCLUSION The purpose of the present study was to simultaneously evaluate the importance of both parent activity level and parent encouragement of children’s physical activity in the prediction of children’s time spent in vigorous physical activity as well as to evaluate the role of parent encouragement in the prediction of children’s expected adult body size. A path model was developed and tested to evaluate our purpose. First before integrating our results with theory and past research, the present findings lend support to the growing concern about the shocking number of Americans who live sedentary lifestyles. The level of inactivity of both the parents and children in the present investigation was staggering. Overwhelmingly, participating parents failed to engage in vigorous, moderate, or walking activity. Although

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this finding is consistent with physical activity trends for adults (Pratt, Macera, and Blanton, 1999), the socioeconomic as well as educational status of parents may have skewed the distribution even further as both are well known factors associated with greater inactivity. The majority of parents in the present sample did not have a college degree. Also, 28.9% of the fathers and 17.4% of mothers reported earning less than a high school diploma. In sharp contrast to their self-reported physical inactivity, the parents tended to prefer that their children engage in vigorous physical activity, which is encouraging at some level. Fortunately, from Bandura’s (1986, 2001) SCT perspective parent encouragement may be more important or at least counteract a poor model in this case a model of physical inactivity. It is important to be reminded that though the parent encouragement that resulted from this preference was associated with higher levels of vigorous physical activity in their children, overall, the children engaged in far more sedentary types of activities than vigorous physical activities. Again, socioeconomic status and or the combination of educational level are factors that could play a role in this discrepancy. Parents might desire that their children be involved in organized sports and work out at the gym; however, they might not have the resources, such as time or money required for transportation or fees, for their children to do so. If parents spend a lot of time at work to compensate for low wages, they likely have less time to support their children's involvement in physical activity. Thus, their encouragement is most likely conveyed verbally rather than through action, which would account for the small amount of variance in children's actual time spent in vigorous physical activity by parent preference for their children's activity. Parents' preference for their children's vigorous physical activity was more important in the prediction of children's actual time spent in vigorous activity than parents' activity levels, and the parents in the present study did seem to recognize that their preferences in their children's activity would likely influence their children's adult body size. As parents reported providing more encouragement for vigorous physical activity, their estimate of their children's body size as adults declined. Parents do appear to understand the importance of providing support to their children's vigorous activity, which further suggests that other factors tend to prevent children from actually engaging in those types of activities. Therefore, the old adage that indicates children should do as their parents say and not as they do seems to have some validity in the case of physical activity. The present results support those of Andersson (2005) and Trost et al. (2003). Importantly, the current study extends the lack of an association between parental activity and children's activity to elementary school age children. Although the overall nature of the findings validate concerns for the health of both parents and their children, understanding that parents are able to influence their children's activity levels regardless of their own modeling of physical activity is encouraging. In addition, the results highlight the need for future research. One would expect parent behavior and preferences related to physical activity to have a strong association with the physical activity of children. With researchers consistently finding conflicting results (e.g., Gustafson and Rhodes, 2006), future research is warranted to continue to investigate the influence of peers, school and after school programs, and the media on children's activity levels while also including parental influence in the theoretical framework. The continued employment of a social cognitive theoretical framework in future research also appears advantageous. Social cognitive theory focuses on individuals as agents in their development (2001), which offers an explanation for children's ability to choose to avoid

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modeling parent behavior while at the same time heeding their encouragement. In other words, children possess the ability to evaluate the information in their environment and react to it in order to regulate their own behavior. Understanding the apparent self-regulation that appears to be present in the current study should be a focus of future work. “Most of the selfregulation models focus mainly on predicting health behavior, but they offer little operative guidance how to change and maintain it” (Bandura, 2005, p. 248). Bandura (2005) suggested that the cognitive determinants most recently studied in the field can easily be reduced to knowledge of health risks and benefits, self-efficacy or the belief that one can use his/her skills and knowledge to successfully influence health behavior, outcome expectations, health goals, and perceived sociostructural facilitators and impediments. However, no theoretical order is apparent across these cognitive determinants (Bandura, 2005). Furthermore, researchers have predominately studied adults who possess greater control over their choices in activity than do children. The purpose of the present study was to investigate the influence of sociostructural facilitators (i.e., parents) on children's activity, and the goal of future research should be to understand self-regulation in relationship to this influence as selfregulation can be taught to positively impact children's health behavior.

Limitations Future researchers will also be further guided by the recognition of the present investigation’s limitations. First, the sample size was somewhat small and was comprised of individuals living in a rural location in the Southwest. In conjunction with the rural location, the economic opportunities in the area of data collection support mainly unskilled labor. Thus, the socioeconomic status of the majority of participants was somewhat depressed. Low socioeconomic status is a well known factor being associated with lower physical activity patterns. Our measurement of parents' physical activity definitely reflected this association as the self-reported physical activity data was significantly skewed. Researchers in the future should collect data across the range of socioeconomic status that will require purposeful and thoughtful recruitment. The extremely low parent self-reported physical activity patterns were also problematic in at least on one more way. For instance, these self-reported physical activity patterns were not at all consistent with parent reported beliefs about the importance of physical activity for their children. It could be that for these parents that watching a sporting event is similar to actually participating in that sport though this is hypothetical. For instance, many males played football at some level as adolescents, but as adults few play university level football and almost none play professionally, but the game at both the university and professional levels are very popular television events. It could be that the value of participating in sports such as football is conveyed to children by discussing while viewing the sport on television or attending a local high school game. This behavior of watching a game with one’s child or children may be important in predicting their children's activity levels and should be measured (i.e., time spent watching sports together). Finally, the present study was static in nature. The evaluation of parent influence was at only one time point or cross sectional in nature. To best understand the relationship between parent physical activity and the physical activity of children, several important issues should be addressed. First, researchers should work to follow both the physical activity patterns of

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parents and their children over time in a more comprehensive manner. For instance, pedometers would greatly assist in gaining a more accurate representation of daily activity. Several psychometrically sound measures of weekly or smaller units of the week exit to provide validation of the pedometer measurement of physical activity. Intervention research would be the last logical step in the research process to examine whether it is the parent actual engagement in physical activity, discussion of the importance of physical activity, or some combination that effects their children’s physical activity patterns the most. Though the present research was just an evaluation of a single time point in time, the research has provided provocative results that should excite and guide future research on this topic of extreme urgency.

REFERENCES Al-Hazzaa, H. M. (2007). Health-enhancing physical activity among Saudi adults using the International Physical Activity Questionnaire (IPAQ). Public Health Nutrition, 10, 59-64. Ainsworth, B. E., Haskell, W. L., Whitt, M. C., Irwin, M. L., Swartz, A. M., Strath, S. J., et al. (2000). Compendium of Physical Activities: An update of activity codes and MET intensities. Medicine and Science in Sports and Exercise, 32(9), 498-504. Anderson, L. H., Martinson, B. C., Crain, A. L., Pronk, N. P., Whitebird, R. R., O’Connor, P. J., and et al. (2005). Health care charges associated with physical inactivity, overweight, and obesity. Preventing Chronic Disease, 2(4), 1-12. Anderssen, N., Wold, B., and Torsheim, T. (2005). Tracking of physical activity in adolescence. Research Quarterly for Exercise and Sports, 76, 119-129. Arluk, S. L., Branch, J. D., Swain, D. P., and Dowling, E. A. (2003). Childhood obesity’s relationship to time spent in sedentary behavior. Military Medicine, 168(7), 583-586. Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice Hall. Bandura, A. (2001). Social cognitive theory: An agentic perspective. Annual Review of Psychology, 52, 1–26. Bandura, A. (2005). The primary of self-regulation in health promotion. Applied Psychology: An International Review, 54, 245-254. Biddle, B. J., Bank, B. J., and Marlin, M. M. (1980). Parental and peer influence on adolescents. Social Forces, 58(4), 1057-1079. Brown, W. J., Trost, S. G., Bauman, A., Mummery, K., and Owen, N. (2004). Test-retest reliability of four physical activity measures used in population surveys. Journal of Science and Medicine in Sport, 7, 205-215. Centers for Disease Control and Prevention (CDC). (2006a). Overweight and obesity: Home. Retrieved from U.S. Department of Health and Human Services on September 20, 2006, http://www.cdc.gov/nccdphp/dnpa/obesity/ Centers for Disease Control and Prevention (CDC). (2006b). Behavioral Risk Factor Surveillance System. Retrieved from U.S. Department of Health and Human Services on October 25, 2007, http://www.cdc.gov/brfss/ Centers for Disease Control and Prevention (CDC). (2007). Prevalence of overweight among children and adolescents: United States 2003-2004. Retrieved from U.S. Department of

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Health and Human Services on October 23, 2007, http://www.cdc.gov/nchs/products/pubs/pubd/hestats/overweight/overwght_child_03.htm Coley, R. L. (1998). Children’s socialization experiences and functioning in single-men households: The importance of fathers and other men. Child Development, 69,219-230. Craig, C. L., Marshall, A. L., Sjostrom, M., Bauman, A., Booth, M., Ainsworth, B. E, et al. (2003). International Physical Activity Questionnaire: 12-country reliability and validity. Medicine and Science in Sports and Exercise, 35(8), 1381-1395. Davison, K. K., Cutting, T. M., and Birch, L. L. (2003). Parents’ activity-related parenting practices predict girls’ physical activity. Medicine and Science in Sports and Exercise, 35(9), 1589-1595. Deckelbaum, R. J., and Williams, C. L. (2001). Childhood obesity: The health issue. Obesity Research, 9(4), 239-243. Ekelund, U., Sepp, H., Brage, S, Becker, W., Jakes, R., Hennings, M., et al. (2006). Criterionrelated validity of the last 7-day, short form of the International Physical Activity Questionnaire in Swedish adults. Public Health Nutrition, 9, 258-65. Eccles, J. S. (1999). The development of children ages 6 to 14. The Future of Children, 9(2), 30-44. Faulkner, G., Cohn, T., and Remington, G. (2006). Validation of a physical activity assessment tool for individuals with schizophrenia. Schizophrenia Research, 82, 225-231. Festinger, L. (1957). A theory of cognitive dissonance, Evanston, IL: Row and Peterson. Flegal, K. M., Carroll, M. D., Kuczmarski, R. J., and Johnson, C. L. (1998). Overweight and obesity in the United States: Prevalence and trends, 1960-1994. International Journal of Obesity, 22, 39-47. Fogelholm, M., Nuutinen, O., Pasanen, M., Myöhänen, E., and Säätelä, T. (1999). Parentchild relationship of physical activity patterns and obesity. International Journal of Obesity, 23(12), 1262-1268. Hutchinson, M. R., and Ireland, M. L. (2003). Overuse and throwing injuries in the skeletally immature athlete. Instructional Course Lectures, 52, 25-36. Joreskog, K., and Sorbom, D. (2002). LISREL 8.52. Scientific Software International, Inc. Gustafson, S. L., and Rhodes, R. E. (2006). Parental correlates of physical activity in children and early adolescents. Sports Medicine, 36, 79-97. U.S. Department of Health and Human Services (DHHS). (2003). Prevention makes common “cents.” Retrieved from U.S. Department of Health and Human Services on October 23, 2007, http://healthproject.us/documents/Centscondensed.pdf Hu, L. T., and Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1-55. International Physical Activity Questionnaire (IPAQ). (2007). Reliability and validity study. Retrieved from The International Physical Activity Questionnaire Homepage on May 31, 2007, http://www.ipaq.ki.se/IPAQ.asp?mnu_sel=GGDandpg_sel=JJG. Kline, R. B. (1998). Principles and practice of structural equation modeling. New York: Guilford. McFarlane, D. J., Lee, C. C., Ho, E. Y., Chan, K. L., and Chan, D. (2006). Convergent validity of six methods to assess physical activity in daily life. Journal of Applied Physiology, 101, 1328-1334.

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Contemporary Athletics Compendium, Volume 3 Editor: James H. Humphrey

ISBN: 978-1-60741-561-9 © 2009 Nova Science Publishers, Inc.

Chapter 12

NEGLIGENT MARKETING: “WHAT ALL SPORT MARKETERS SHOULD KNOW” Andy Gillentine∗1, John Miller2 and Austin Stair Calhoun3 1

University of Miami, Coral Gables, Florida, USA 2 Texas Tech University, Lubbock, Texas, USA 3 Washington and Lee University, Lexington, Virginia, USA

ABSTRACT Negligent marketing assumes that promoters should not engage in strategies that increase the risk that patrons may injure either themselves or others (Ausness, 2002). Marketing campaigns portraying a product being consumed in a negligent manner that leads to the development of an unsafe environment may put the service provider at risk (Sebok, 2003). If a defendant can establish the marketing campaign influenced how the product was consumed, service providers could be found liable. Sport organizations allowing companies to deliver such marketing campaigns or that are associated with products that promote dangerous or reckless behavior may also be liable (Rabin, 1999). Sport organizations should be careful not to create the impression that negligent consumption of a product is part of a consumers experience. Sport marketers must evaluate situations to identify potentially dangerous actions or behaviors (Gillentine, 2003; Jackson and Polite, 2003; Gillentine and Miller, 2004). On a crisp autumn afternoon, Christine Bearman and her husband causally strolled through the parking lot towards their car. Following an afternoon of college football, the Bearmans decided to leave the event a little early to avoid possible traffic delays on the way home. As the Bearmans made their way through the Notre Dame parking lot, an intoxicated “tailgater” knocked Christina to the ground. Ms Bearman suffered a broken ∗

Contact Information: Andy Gillentine, Ph.D. Associate Dean, University of Miami, Dept. Exercise and Sport Sciences, P.O. Box 248065. Coral Gables, FL 33124. (O) 305-284-3102. (FAX) 305-284-5168. [email protected]

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Andy Gillentine, John Miller and Austin Stair Calhoun leg in the incident and required medical attention. No security or event management staff was in the vicinity when the incident occurred.

Sport marketers are constantly challenged to find new and innovative ways of marketing their sport product or services to the consumer. Marketing strategies and campaigns are often designed to take advantage of the latest consumer trends in order to attract specific market segments. Often, these trends are influenced by current pop culture figures, events and symbols. The use of celebrities and popular music may help expose the sport product to a broader or specific group of consumers. The use of Kid Rock and “the Twins” in Coors Beer commercials and depictions of painted and costumed raucous groups simulating fans attending a “typical” sporting event are examples of these trendy marketing strategies. Sport marketers also often design an alternative version of the marketing campaign which targets a different demographic group. This portion of the marketing campaign frequently features images of athletic events including school mascots playing with children, families picnicking on university grounds and the promise of a Family Fun Zone or Family Friendly atmosphere, implying that the event is a safe, wholesome environment for the sport consumer. These dichotomously different representations can often cloud the issue of regarding products or services actually being promoted and sold. These mixed images fail to paint the complete picture for either segment, as to what type environment the consumer might actually find at the sporting event. Tailgate parties have been acknowledged as an important component of intercollegiate as well as professional athletic events. Previous research examining motives for participating in tailgating events identified alcohol consumption as a primary motivating factor and also indicated that subjects had missed an event due to tailgating related activities (Gillentine, 2003). Additional research has indicated that drinking alcohol can increase an individual’s violent tendencies, especially when placed in an emotionally charged atmosphere (Harford, Wechsler, and Muthen, 2003; Leonard, Quigley, and Collins, 2002; Graham, Larocque, Yetman, Ross, and Guistra, 1980). This research may be further exemplified by recent incidents where fatalities were attributed to drinking at tailgate parties (Romig, 2004). Sport organizations should understand and acknowledge that alcohol consumption will and does take place at their events. This relationship should alert university athletic officials about the potential for inappropriate and disruptive actions of participants, which may endanger themselves and/or others. The principles of tort law specify that before a person or organization can be held liable for unlawful activity, that entity must breach an affirmative duty (Dobbs, 2000). Supporters attending an athletic event and/or its subsequent activities (i.e. tailgating) are considered business invitees. As such, the university has a duty to take reasonable measures to warn or protect the business invitees from foreseeable harmful or criminal acts committed by a third party (Miller, Gillentine, and Malhorn, 2006; Gillentine and Miller, 2006; Mallen, 2001; Dobbs, 2000). By issuing an invitation to attend these athletic activities (e.g. marketing campaigns; event promotions, etc), the sport organizations signifies that the premises and related activities to be safe (Wong, 2002). The failure to provide a safe environment for invitees through misleading marketing of the event may lead to their actions being regarded as negligent marketing.

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NEGLIGENT MARKETING The principle of negligent marketing assumes that promoters should not engage in strategies that increase the risk that patrons may injure either themselves or others (Ausness, 2002). Negligent marketing is typically categorized into three areas of identification: 1) product design, 2) inadequate supervision and 3) advertising and promotional activities (Ausness, 2002). While legal precedence in the area of negligent marketing has most frequently been cited in reference to the manufacturing and sale of firearms, it has also been applied to events in which patrons are invited to participate in an activity about which they have not been adequately informed (Merrill v. Navegar Inc., 2001). Marketing campaigns that portray a product being consumed in a negligent manner that leads to the development of an unsafe or dangerous environment may put the service provider at risk of negligent marketing. If a defendant can establish that the marketing campaign influenced how the product was consumed, service providers could be charged with contributory negligence. Additionally, sport organizations that allow companies to deliver such marketing campaigns or that are associated with a product that promotes dangerous or reckless behavior may also be liable for negligent behavior of consumers (Rabin, 1999).

ENABLING TORTS Sport organizations should be careful not to create the impression that negligent consumption of a product is part of a consumers experience when they consume the sport product. Sport marketers also need to ensure that they are not creating an unsafe environment that has potential impact on all sport consumers (Sebok, 2003). While sport marketers may maintain that they are not responsible for the inappropriate actions of consumers, they may be held accountable if the environment in which the sport product is offered and consumed is not safe from foreseeable harm. It is the responsibility of the sport marketer to evaluate situations to identify potentially dangerous actions or behaviors. Previous research has suggested that additional policies and regulations regarding the marketing and hosting of sport events need to be instituted (Miller, Gillentine, and Malhorn, 2006; Gillentine and Miller, 2006; Gillentine, 2003; Jackson, Polite, and Barber, 2003). The cavalier attitude that such matters are the responsibility of event management staff or security is simply unacceptable. By providing an environment through which the sport product may inappropriately consumed, the sport marketer may have enabled the consumer to be at significantly higher risk of harm. This concept is referred to as an enabling tort (Rabin, 1999). An enabling tort is an emerging concept that provides a broader view of proximate cause. Sport marketers may find themselves in violation of this enabling tort concept if they have engaged in marketing activities that will increase the likelihood that their product will be purchased and/or consumed by customers who are more likely to injure either themselves or others (Ausness, 2002). Rabin (1999) further describes this evolving concept and its potential application to the sport industry, “…the erosion of the proximate cause limitation for intervening acts can be regarded as a temporal shift in moral sensibilities from a more individualistic era to one in which tort

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Andy Gillentine, John Miller and Austin Stair Calhoun law…increasingly reflects more expansive notions of responsibility for the conduct of others” (p. 441-442.).

This concept further implies that no special relationship needs to exist in order to establish responsibility (Rabin, 1999). It does place great emphasis on the placement of the patron in a position posing a foreseeable risk of harm. This expands the level of expected responsibility of the sport marketer to be even more inclusive than the previously established designation of patrons as business invitees.

SOCIAL HOST LIABILITY In addition, the creation of an environment in which unsupervised alcohol consumption is allowed and/or tolerated the sport organization may find itself in violation of social host expectations. Social host liability refers to statute or case law that imposes potential liability on social hosts as a result of their serving alcohol to obviously intoxicated persons or minors who subsequently are involved in crashes causing death or injury to third-parties. The expectation of the social host may be extended from the actual sale or serving of alcohol to the prevision of the environment for its consumption. Through this interpretation, sport organizations must develop and implement specific policies for those patrons attending athletic events and activities in order to demonstrate appropriate levels of control.

RECENT TAILGATE EVENT INCIDENTS In October of 1999, Ronald and Fazila Verni, accompanied by their daughter Antonia, were driving back from selecting a pumpkin for Halloween when a truck driven by Daniel Lanzaro struck the Vernis. As a result Antonia, who was 2 years old at the time, was paralyzed from the neck down. Lanzaro, who had been attending New York Giants football game, was found to have a blood-alcohol content that was three times the legal limit. He was eventually sentenced to 5 years in prison. Subsequently, the Verni’s filed a lawsuit naming Lanzaro, the Giants, Aramark (the company in charge of concessions at Giants Stadium), and the National Football League. According to the attorney for the Vernis, Lanzaro gave a vendor a $10 tip so the vendor would sell him (Lanzaro) six beers at the same time. The vendor did so even though it violated the two beer maximum rule at the stadium. A jury awarded $75 million in punitive damages and $60 million in compensatory damages. The compensatory damages were assessed equally against Lanzaro and Aramark Corporation, the Giants Stadium concessionaire that sold beers to him at the game. The jury ruled that Aramark was liable for the additional $75 million. According to a research group that examines developments in personal injury lawsuits, the award was the largest alcohol liability award in the United States in at least 25 years (CourtTV.com, 2005). The Verni’s attorney stated that what the NFL is doing is promoting the idea that, “We’re having a party, so park you car in our backyard, drink as much as you want, come into the stadium, get more wasted and then drive home.” Additional evidence presented by the

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plaintiff’s attorney revealed showed that vendors continually violated rules against selling more than two beers to a single patron at a time. There were hardly any occasions, in what the attorney referred to as "the culture of intoxication" at the stadium, in which drunken patrons were stopped from ordering more drinks. "The name of the game was to sell as much beer as possible," the attorney continued (Gottlieb, 2005). Intercollegiate sports are not immune to these kinds of unfortunate events occurring as a result of tailgating. Bearman v. Notre Dame (1983) should serve as the benchmark ruling upon which sport marketers evaluate control issues involved in event development and promotion. The Bearman’s filed suit against Notre Dame for damages resulting from that incident. In 1983, the Third District Indiana Court of Appeals ruled that, Notre Dame was aware that alcoholic beverages are consumed on the premises before and during football games. They also were aware that tailgate parties are held in the parking areas around the stadium. Thus, even though there was no showing that the University had reason to know of the particular danger posed by the drunk who injured Bearman, it had reason to know that some people will become intoxicated and pose a general threat to the safety of other patrons. Therefore, Notre Dame is under a duty to take reasonable precautions to protect those who attend its football games from injury caused by acts of third parties.

In Bearman v. Notre Dame (1983), the university acknowledged that individuals attending tailgating parties may become intoxicated, thus posing a threat to others on the premises. Yet, the university did not provide any warning or supervision for the patrons attending and participating in the pre-game activities. (Mellowitz, 1983). At a minimum, “…sponsored activities require some type of increased safety measures.” (Wong, 2002, p. 125). Moreover, the Restatement of Torts (Second) (1965) comment f explicitly states Since the possessor is not an insurer of the visitor’s safety, he is ordinarily under no duty to exercise any care until he knows or has reason to know that the acts of the third person are occurring, or are about to occur. He may, however know or have reason to know, from past experience, that there is a likelihood of conduct on the part of third persons in general which is likely to endanger the safety of the visitor, even though he has no reason to expect it on the part of any particular individual.

A more recent incident occurred in 2004 when a North Carolina State University student and his brother were charged with the shooting deaths of two men at a tailgating party. In a split verdict, one of the defendants was recently found guilty of first-degree murder (Mason and Calloway, 2004).

Threat Matrix Control of alcohol beverage use, limiting or supervising the practice of tailgating in pregame and post-game situations, warning signs or providing an adequate number of trained security personnel to be present at tailgating events would minimize the likelihood of a harmful incident occurring (Miller, Gillentine, and Seidler, 2003). These control measures require specific acknowledgement on behalf of sport marketers when athletic events and activities are evaluated through the premises of a threat matrix. The threat matrix helps to

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identify foreseeably harmful incidents that may threaten an event or organization and places them into categories that help imply the frequency (often, average, seldom) and severity (high loss, moderate loss, low loss) of the potential threat. An example of a threat matrix that may be used by a sport marketer to identify potential harmful incidents is provided. It should be kept in mind that many other instances could occur and as such Table 1 supplies potential occurrences and should not be construed as an absolute example. Through this matrix, a sport marketer can recognize the foreseeability of a specific threat and recommend actions to prepare or adjust for the threat. Additionally, the marketer may adjust the marketing plan for the event in order to minimize the likelihood of negligent marketing. Failure to identify foreseeable risks involved with an athletic event can lead to costly litigation for the sport organization.

Implications and Responsibilities for Sport Marketers The application and recognition of potential legal pitfalls is an area of relatively new concern for sport marketers. Despite the newness of these concerns the sport marketer is nonetheless responsible for becoming educated regarding legal aspects of sport marketing and the development of effective and efficient plans for adhering to these legal concerns. Often a different advertisement will depict fans tailgating with alcoholic beverages; others painted from head to toe in school colors involved in raucous behavior or seas of the fans storming the field after a big win and tearing down the goal posts. Table 1. Threat Matrix Risk of Occurrence Seriousness of Injury or Damages

Minor Medium Significant

Likely

Possible

Unlikely

E B C

F A H

D I G

A- Fisticuffs are reported between tailgaters supporting opposing teams. B- Patron has leg broken due to actions of an inebriated tailgater. C-Grill is tipped over causing coals to spill under a car. D- A tent is blown over scraping a vehicle. E- A tailgater scrapes elbows on pavement playing “tag” football. F-A patron receives cuts on leg from falling on broken glass. G-Tailgater(s) shoot and kill other tailgaters H-Patron becomes inebriated at tailgating party; kills/paralyzes another while driving home. I-Tailgater becomes over-intoxicated, passes out and becomes comatose.

These images are in stark contrast to the aforementioned family fun zone depiction often offered and promoted. Each method of advertising is aimed at a different market segment, yet both are selling the same product. By confusing the public regarding the actual product being sold or the actual nature of the product, the marketer may be guilty of negligent marketing.

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A primary concern to the sport marketer must be to ensure an appropriate environment for the athletic event is established. To facilitate the development of an appropriate environment, the sport marketer should incorporate the following seven action steps: 1) Develop a comprehensive marketing plan. This plan should be developed not only with the promotion of the specific event in mend but also with concern for the safety and well being of the patrons. 2) Play an active role in the development and promotion of specific policies for participation and attendance at athletic events (i.e. tailgating policies) to further minimize the risk to patrons, the marketer must 3) Coordinate marketing plans and the specific event policies with existing organizational policies. Policies that are not in concert with existing organizational policies will present additional legal concerns and will most likely be rendered inefficient and ineffective. Perhaps the only thing worse than none existent policies are contradictory ones. 4) Implement effective communication systems to promote adherence to plans and policies. This communication process should involve the education of event and marketing staff. 5) Gather feedback from patrons regarding the understanding and enforcement of the policies. 6) Educate the athletic staff and/or the event patron and relate the consequences for policy violations as well as promote the positive aspects of adhering to the policies. 7) Design an evaluation component to determine the effectiveness of the marketing and/or event plan. This must be done to ensure the effectiveness of the marketing and event plan as well as to ensure that the plans themselves are not promoting potentially harmful activities. Good marketing and event management plans are adaptable and dynamic processes that should be frequently communicated and documented. As the number of potential risks associated with athletic events are never static, nor should the plans for promoting and administrating sporting events. When the presumption that previous success guarantees future achievement, the organization will eventually fail to provide the environment for a successful and safe consumer event. This failure can lead to consumers avoiding doing to sport venues based on the owners’ lack of assurance that they are committed to safe and secure venues (Toohey, Taylor, and Ki-Lee, 2003).

CONCLUSION Athletic events are often correctly marketed as an exciting and fan-friendly event appropriate for patrons of all ages. In order to ensure this, it is the duty of sport marketers to engage in the ethical marketing and planning of athletic events and activities. This demands that the marketer keep the safety and well being of the patron as the foremost concern for any plan or event. Regardless of outcome, litigation can take a tremendous financial toll on the sport organization and its product as well as negatively impacting its reputation. These

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damaging implications can potential affect the marketability of the sport organization and its product. Without this understanding, the near perfect opportunity for sport promotion may become a near perfect opportunity for litigation.

REFERENCES Ausness, R.C. (2002) Will more aggressive marketing practices lead to greater liability for prescription drug manufacturers? Wake Forrest Law Review, 37(1), 97-139. Bearman v. University of Notre Dame, 453 N.E.2d 1196 (Ind. Ct. App. 1983). CourtTv.com. (2005). Group: $135 million jury award a warning to vendors and teams. Retrieved from http//: www.courttv.com/news/2005/0121/aramark_ap.html. Dobbs, D. B. (2000). The law of torts. St. Paul, MN; West Group. Gillentine, A. (2003). Factors associated with participation in pre-game activities. Paper presentation at Southern District AHPERD. Savannah, GA. Feb. Gillentine, A. and Miller, J. (2006). The legal implications of tailgating at athletic events. International Journal of Sport Management. 7(1), 102-111. Gillentine, A. and Miller, J. (2004). Bearman vs. Notre Dame – Twenty years later:The implications for sport marketers. Paper presentation at the North American Society for Sport Management Conference. Atlanta, GA. Gottlieb, H. (2005). Jury duns stadium beer vendor $105 million for injuries caused by drunken fan. New Jersey Law Journal. Retrieved from http//: www.freerepublic.com/ focus/f-news/1326439/posts Graham, K., Larocque, L., Yetman, R., Ross, T.J. and Guistra, E. (1980). Aggression and barroom environments. Journal of Studies on Alcohol, 41, 277-292. Harford, T.C., Wechsler, H. and Muthen, B.O. (2003). Alcohol-related aggression and drinking at off-campus parties and bars: a national study of current drinkers in college. Journal of Studies on Alcohol, 64(5), 704-711. Jackson, N., Polite, F. and Barber, A. (2003). Crossing the legal line: Issues involving tailgating. Paper presentation at the Society for the Study of Legal Aspects of Sport and Physical Activity. Atlanta. Leonard, K.E., Quigley, B.M, and Collins, R.L. (2002). Physical aggression in the lives of young adults: Prevalence, location, and severity among college and community samples. Journal of Interpersonal Violence, 17, 533-550. Mallen, S.A. (2001). Touchdown! A victory for injured fans at sporting events? Missouri Law Review, 66(2), 487-505. Mason, S. and Calloway, V. (2004, September 6). Brothers in custody following fatal shootings outside NCSU game. WRAL.com. Retrieved on September 23, 2005 from http://www.wral.com/news/3707350/detail.com. Mellowitz, J. (October 10, 1983). Tailgate parties in jeopardy? Court remands injured fan's suit. The National Law Journal, p. 4. Merrill v. Navegar, Inc., 28 P.3d 116, 119 (Cal. 2001). Miller, J., Gillentine, A, and Malhorn, N. (2006). An investigation of tailgating policies at Division 1A Schools. Journal of Legal Aspects of Spor, 16(2), 197-215..

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Miller, J., Gillentine, A. and. Seidler, T., (2003). Is the National Football League responsible for injuries due to third party acts?. Paper presentation at the Society for the Study of Legal Aspects of Sport and Physical Activity. Las Vegas, NV. Rabin, R.L. (Winter 1999). Enabling torts. DePaul Law Review, 49, 435-453. Restatement of Torts (Second) § 344 Comment F (1965). Romig, J. (2004). Niles man sentenced in hit-and-run death. South Bend Tribune (Indiana), June 26, 4A. Sebok, A.J. (Winter 2003). What’s law got to do with it? Designing compensation schemes in the shadow of the tort system. DePaul Law Review, 53, 501-525 Toohey, K., Taylor, T., and Lee, C. K. (2003). The FIFA World Cup 2002: The effects of terrorism on sport tourists. Journal of Sport Tourism, 8(3), 167-185. Wong, G. M. (2002). Essentials of sports law. 3rd Ed. Greenwood Publishing Group.

Contemporary Athletics Compendium, Volume 3 Editor: James H. Humphrey

ISBN: 978-1-60741-561-9 © 2009 Nova Science Publishers, Inc.

Chapter 13

INVESTIGATING FANTASY SPORT PARTICIPATION AMONG COLLEGE STUDENTS Chad Seifried∗1, Corinne Farneti1, Brian A. Turner1, Martin Brett2 and Jerry Davis1 1

2

The Ohio State University, Columbus, Ohio, USA DeSales University, Center Valley, Pennsylvania, USA

ABSTRACT This project examined fantasy sport participation among the college student population and compared it to previously completed work. Specifically, 155 college students were surveyed from a large midwestern university. The study supports most college student fantasy participants are male and nearly a third of these males participated in paid leagues. Interestingly, most respondents (73.3%) indicated they felt fantasy participation was not gambling. The investigation also revealed 29.9% of students generally read more and 23.5% watched more about a sport when they participate in fantasy leagues. In addition, 77.6% felt the success of their fantasy team did not determine how much they watch sports and another 91.8% of respondents declared the elimination of their fantasy team from playoffs or postseason competition failed to eliminate their desire to watch sports. Similar to other studies, NFL, MLB, and NBA leagues, in that order, emerged as the most popular fantasy leagues. Finally, this study’s college student fantasy league participants come from various backgrounds. For example, many different academic backgrounds/majors were present in the sample population and nearly 91% of fantasy players played high school level athletics or higher.

Fantasy sports are games in which a people serve as coach, owner, and general manager of his or her own team by drafting and managing individual players from a professional or college organization (Felps, 2000; Hiltner & Walker, 1996; Standen, 2006; Williams, 2006). The fantasy sport player usually participates in a league and competes against other players’ ∗

Send Correspondence to: Dr. Chad Seifried, The Ohio State University, A248 PAES Building, 305 W. 17th Ave., Columbus, OH 43210, Phone: 614-247-8971, Fax: 614-688-3432, Email: [email protected]

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teams, based on the professional athletes’ statistics. Each league creates its’ own rules for play through its’ league “commissioner” or agreement among participant members. The rules usually determine the point value assigned to each statistical category (Felps, 2000). Leagues can produce weekly winners or culminate with one award for winning the entire season. The rewards vary and in many cases depend on the entry fee (Miller, 2005). Fantasy sport competitions remain attractive to today’s audiences because they utilize the actual performance of real players in real time (Hiltner & Walker, 1996; Williams, 2006). The majority of completed research on fantasy sport(s) focuses on its’ explosive popularity over the last decade and a half. For example, Schwarz (2004) and Ballard (2004) suggest fantasy sport accounts for roughly $1.5 billion in spending a year and approximately 15 million adults participate in at least one fantasy sport league annually. Similarly, a Fantasy Sports Trade Association survey in 2003 reported a total of $1.65 billion generated from fantasy sports. Included in these figures are league entry fees, advertising/branding deals, game-play web services, fantasy publications, and web tip/expert services (Ballard, 2004). Other recent data also demonstrates a huge participation rate. Specifically, according to Fanball.com, about 30 million fans worldwide played fantasy sports in 2000 (Felps, 2000). In 2002, 15% of Americans over 18 enjoyed participation in at least one fantasy sports league (Reilly, 2002). Interestingly, the portion of revenue surfacing from these media-driven sources appears substantial and likely to increase in future years. For instance, in 1996, CBS SportsLine employed three people to run its fantasy operation; as of 2004, 50 worked on the fantasy site (Ballard, 2004). Fantasy leagues exist for the four “big” sports in the U.S. (i.e. Major League Baseball, National Football League, National Basketball Association, National Hockey League) as well as for other sports such as NASCAR, golf, bass fishing, cricket, pro wrestling, soccer, and thoroughbred racing. The NFL and MLB enjoy the most popularity (Ballard, 2004). College Sports Telvision (CSTV) recently introduced college football fantasy leagues, but experienced problems in making it as popular as its pro counterpart. This likely occurs because attractive fantasy college athletes leave early for the professional ranks and the NCAA only allows the drafting of a school and a position, not the specific name of a studentathlete (Miller, 2005). While very few academic studies exist on topics related to fantasy sport, plenty of information surfaces on the evolution and legality of fantasy participation in mainstream publications and media outlets. The purpose of this study aims to examine fantasy sport participation among the college student population and compare it to previously completed work. Appropriately, the investigation intends to determine the status of a variety of subtopics. Primarily, the questions sought to identify the sport(s), which enjoys the most participation, whether fantasy participation generated any money for them and if they thought paying to participate was gambling. Other questions sought to discover the level of effort respondents placed in organizing their team and if participation in fantasy sport influenced their interest in sport(s). Finally, this research project also asked students to indicate if they found following sport(s) more enjoyable because of fantasy league participation and if their level of interest in sport(s) was directly influenced by the success rate of the team they managed.

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LITERATURE REVIEW The introduction of fantasy sport appeared at least two decades ago. For example, Felps (2000) and others suggested fantasy contests started around the 1960s (Miller, 2004; Schwarz, 2004). Specifically, Schwarz (2004) pointed out Harvard professor William Gamson developed a baseball seminar in 1960, which prompted him and some of his colleagues to draft players onto a team and select a winner based on their end of the year statistics. Additionally, in 1963, Bill Wikenbach, a limited partner of the American Football League (AFL) Oakland Raiders, introduced his friends to a game he devised called fantasy football. Many other sources point to Daniel Okrent, editor of the New York Times, as the founding father of fantasy sports leagues, specifically fantasy baseball (Ballard, 2004; Horgan, 2005; Hruby, 2003, Schwarz, 2004). Reports indicate Okrent thought up the game while on a flight to Austin, Texas on November 17, 1979 (Ballard, 2004). Upon arrival back to his New York home, he called a meeting of his fellow members in the “Phillies Appreciation Society” to explain his new idea. Apparently, they liked what he said and the group met monthly at La Rotisserie Francaise Restaurant, for what they dubbed Okrent’s “Rotisserie League.” The Rotisserie League idea spread like wildfire across the country via the members’ media connections. By 1983, major league baseball players acknowledged awareness of the game; and by the early 1990s, Rotisserie baseball led to similar football and basketball leagues (Ballard, 2004). In any event, none successfully patented the game, which remains so popular today (Ballard, 2004). A major step in legitimizing and increasing the awareness fantasy sport occurred on August 1, 1998 at the Fantasy Insights '98 Fantasy Football Convention. During the convention, a group of five diverse media members joined together to discuss various issues in the fantasy sport industry. Most notably, they decided to establish a trade association called the Fantasy Sports Trade Association (FSTA). Appropriately, the twelve-member board and its elected officers developed the following mission to help the growth of fantasy sport: …a non-profit trade organization, was founded for the betterment of the fantasy sports industry and to encourage participation in Fantasy Sports Leagues. The FSTA will look to protect the commercial and consumer rights of individual players and business owners, address government regulations and serve as the unified voice of the Fantasy Sports Industry. (Fantasy Sports Trade Association, 2006)

Interestingly, the FSTA holds bi-annual conferences to discuss issues in the industry, network, and of course, hold the seasonal draft. The FSTA also formed a Fantasy Sports Hall of Fame and gives out awards semi-annually to promote the awareness and attractiveness of fantasy sport participation (Fantasy Sports Trade Association, 2006). Fantasy sport participations increased dramatically in recent years as media units multiplied, embraced athletics into their mediums, and ultimately changed the way they present sporting events (Razzano, 2006; Williams, 2006). For instance, the “sports ticker” provides more diverse statistics and resources directly aimed at the fantasy players (Horgan, 2005). Additionally, the media often dedicates an entire on-air segment to fantasy sports like ESPN News does for baseball (Hruby, 2003). Felps (2000) suggests the Internet and numerous other technology and communication mediums contributed towards much of this growth mentioned above.

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Advancements in technology helped revolutionize fan interaction to change how we think about sport. Furthermore, better technology allowed fans instantaneous updates on teams and player statuses when in the past long and arduous calculations would prevent individuals from managing a fantasy team. Essentially, communication technology and advanced sophisticated software packages facilitated the explosive growth of fantasy sport participation. Many fantasy team owners utilize some kind of service to manage their teams and leagues. Typically, these services developed software packages, which help fantasy league managers in a user-friendly format track statistics, injuries, trades, free agents, weather patterns, and other elements. In many cases, participants pay fees to these service organizations to enjoy access to their software. For example, CDM Sports, a fantasy league software manufacturer out of St. Louis, MO, uses its software to format actual player stats into a user-friendly league (Montagne, 2006). Within the past two years, the NFL partnered with CBS Sportsline.com for fantasy games at NFL.com. Furthermore, they launched a $7.99 fantasy preview magazine and the first fantasy TV special on the NFL cable channel (Petrecca, 2005). ESPN followed suit by producing a $6.99 fantasy football guide and plans on launching fantasy TV program of its own. Fox Sports offers a weekly television show dedicated completely to fantasy sports, while Sirius Satellite Radio also regularly runs a three-hour fantasy football show. EchoStar’s Dish Network offers fantasy racing and a football challenge on its interactive satellitetelevision channel (Vuong, 2005). This trend also extends to the print media because at least three times as many fantasy football preview magazines exist over actual football preview magazines (Ballard, 2004). The boom in fantasy sport provided an opportunity for outside companies to profit as well. For example, Jostens now offers rings that fantasy leagues can award to their annual winners (Grimaldi, 2004). Electronic Arts appears as another company benefiting from fantasy sports because they designed fantasy-based video games and added special features to several games, like Madden NFL, which lets players track their fantasy teams while playing (Petrecca, 2005). The General Motors Company (GMC) emerged as one of the first non-sport corporations to latch onto fantasy sport websites. They began by sponsoring fantasy baseball on Yahoo! and now added football, basketball, and Mexican Soccer to their portfolio. Stoffer (2005) suggested the large number of visits to hosting sites provide corporations like GMC a great benefit through sponsorships (Stoffer, 2005). Overall, Petrecca (2005) posited these products not only bring in money from their sale but also serve to drive fantasy players to use their respective websites.

METHOD While much appears written about the current controversy regarding fantasy sport participation, little prior research determined the current extent of the relationship between fantasy sport and college students. The researchers developed several items to examine college student fantasy sport participation. Respondents were asked questions regarding: (a) if they operated a fantasy team(s) and in what sport(s); (b) if they paid money to participate in a fantasy league(s), achieved financial success, and if they consider this gambling; (c) what sport(s) do they dedicate most of their time and effort organizing; (d) whether their

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participation in a fantasy league(s) influences their interest of sport(s); (e) if fantasy sport participation prompted individuals to watch and read more about their team(s); (f) if fantasy sport made following the sport(s) more enjoyable; and (g) if the success rate of a fantasy team impacted the participants’ continued level of interest in sport(s). Questions related to D through G utilized a Likert Scale where respondents were asked to indicate their level of agreement. The investigators provided questionnaires along with a cover letter explaining the purpose of the research to 155 college students in a class about spectator sports at a large midwestern university. All 155 responses were used in the analysis of data. Respondents ranged in age from 18 to 28 (M = 20.63; SD = 1.63). Males produced 121 of the responses (76.6%) while 30 females (19.0%) completed the rest (four individuals failed to specify their gender). The respondents were primarily Caucasians (86.1%) but African-Americans (8.6%), Asian-Americans (3.2%), Hispanics (0.6%) and Native American (0.6%) also completed the survey. The academic standing varied among the students but sophomore, junior, and senior totals accounted for 143 (90.4%) responses in the sample population. Interestingly, we found the sample group enrolled in several different colleges at the institution. They fell in this order: 1) College of Business (33.5%); 2) Arts and Sciences (18.1%); 3) Social Sciences (11.4%); 4) Food, Agricultural, and Environmental Science (7.0%); 5) Humanities (6.3%); 6) Engineering (5.7%); 7) Medicine and Education (3.2%); 8) Graduate School (1.3%); and 9) Social Work (0.6%). The sample population also showed 91 individuals (57.6%) enjoyed a cumulative grade point (GPA) average between 3.0 and 4.0 while another 47 (29.7%) reported a GPA between 2.5 and 2.99. Finally, when asked about the highest level of sport participation, 18 (11.4%) reported they participated on college varsity teams, 18 others indicated university club experience, 104 (65.8%) responded they partake in high school athletics, while 15 (9.5%) fulfilled only recreational competition. Several works indicate purposive sampling appears suitable for exploratory research like this because it aims to generate new thoughts and perspectives on a phenomenon (Gratton & Jones; 2004; Salant & Dillman, 1994). Trochim (2001) and others also promoted the effectiveness of purposive sampling when the proportionality of a population appears as a minor concern because of the homogeneity of the group (Gratton & Jones, 2004; Kerlinger, 1986; Patton, 1990; Salant & Dillman, 1994). We feel the demographic information provided above in regard to race, G.P.A., college enrollment, and highest level of sport participation offer an adequate representation of college campus.

RESULTS Nearly half (52.5%) of the respondents stated they operated no fantasy team. Over 20% (n=33) managed one team with another 17 (10.8%) and 11 (7.0%) directing two and three teams respectively. Expectedly, few individuals, only 8 (5.3%) led more than three teams (Table 1). Of those participating in fantasy leagues, 21 (30.4%) indicated they paid to compete against others for their league championship. Fourteen of these individuals stated they paid to participate in only one league. Four more managed teams in two leagues. When asked the question if they thought paid fantasy league participation was gambling 26.7% of respondents answered “yes” while the remaining 73.3% answered “no.” Most respondents

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(89.4%) also indicated they received no money or return on their investment for their participation. Only 7.1 % agreed they obtained financial gain for their fantasy sport participation. Professional sport enjoyed the most fantasy league participation from the sample population (Table 2). The National Football League (NFL) saw 51 (73.9%) fantasy participants utilize statistics for its leagues competitions. Nearly 30 (42.0%) individuals participated in Major League Baseball (MLB) fantasy leagues. About half that number (n= 14; 20.3%), emerged to utilize National Basketball Association (NBA) statistics. The National Hockey League (NHL) and NASCAR also prompted another five (7.2%) individuals to join fantasy leagues. The researchers also asked students to indicate whether they participated in fantasy sports with college players. A total of twelve responses (7 college football 5 college basketball) appeared to indicate they operated teams based on college performance. Predictably, fantasy league participants spent the most time and effort closely following and organizing leagues based on the NFL (n= 28; 37.3%) and MLB (n= 19; 25.3%) but many also they indicated they followed college football (n= 19; 25.3%) as well despite the low participation rate found here. Most respondents felt their fantasy sport participation impacted little on their level of interest with a sport. For example, 86.9% fantasy sport participants stated they would still watch an activity if they failed to participate in a related fantasy league. Furthermore, more than two-thirds (68.3%) of respondents disagreed they would watch more games and read more about a sport because of their fantasy interests. Still, almost one-third indicated the opposite. Our sample population also generally defended a position they were not more concerned about their fantasy team then their favorite team. Specifically, 77.6% of respondents held this position. In a related question, 77.6% also disagreed their fantasy team’s success determined how much they watched a sport. Additionally, 91.8% opposed the proposal that their interest in a sport would cease when an opponent eliminated their fantasy team from the playoffs. Table 1. Number of Fantasy Teams Operated # of Fantasy Teams 0 1 2 3 4 5 6 7 10 or more TOTAL

Frequency

Percent

83 33 17 11 2 3 1 1 1 152

52.5 20.9 10.8 7.0 1.3 1.9 .6 .6 .6 96.2

Valid Percent 54.6 21.7 11.2 7.2 1.3 2.0 .7 .7 .7 100.0

Cumulative Percent 54.6 76.3 87.5 94.7 96.1 98.0 98.7 99.3 100.0

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Table 2. Self-Identification of Fantasy League Participation Types of Fantasy Teams

Frequency

Percent of Fantasy Participants

1 2 3 4 5 5 5 8 9 9

51 29 14 7 5 5 5 1 0 0

73.9 42.0 20.3 10.1 7.2 7.2 7.2 1.4 0 0

NFL MLB NBA College Football NASCAR NHL College Basketball Pro Golf MLS Other

Finally, when asked if participation in fantasy sport led to a greater level of enjoyment, nearly one-third (31.8%) suggested fantasy membership raised their delight. Not surprisingly, a similar number (34.1%) advocated fantasy sport participation made watching a sport more enjoyable. Furthermore, 41.2% felt fantasy sport membership provided them something to talk about during the day with their friends and peers.

DISCUSSION The results produced by this survey generate a number of topics to discuss. First, while nearly 51% of males surveyed participated in a fantasy league only seven of the 30 females (23.3%) directed a fantasy team and none controlled more than one. This percentage of female participation is larger than previous studies. For example, Ballard (2004) stated 93% of all fantasy sport participants are male. We should acknowledge our sample population is likely more interested in sport and thus more prone to have female fantasy league participants because the survey population comes from a class that is an elective on spectator issues related to sport. Still, this work and others suggests fantasy league organizers or providers could do a better job in the future of marketing fantasy sport to females because they appear as a potential untapped market. Specific evidence comes from Wilner (2005) and others who found females constitute more than 40% of the fans for the NFL, NHL, and MLS (Hofacre, 1994; Meyers, 1997; Mihoces, 1998). Significant monetary loss appears as a negative consequence of fantasy sport. Again, if a participant plays in more than one league, these fees and other costs like website subscriptions, long distance phone calls, and preview magazines add up (Hruby, 2003). A 2003 Harris poll indicated fantasy sports players spend $110 a year per sport (Hruby, 2003), and on average, those who participate in fantasy sport belong to more than two leagues (Yi, 2004). Expectantly, we discovered nearly a third of fantasy members participated in paid leagues; however, few participants paid for two or more teams. Surprisingly, one individual marked they paid to operate 20 teams. We found participation in paid fantasy leagues interesting because of the likely limited financial resources available to college students the

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fact that each knows they can expect little financial success. On average, the typical fantasy player tends to be 37 – 41 year-old professionals with a bachelor’s degree and a household income over $80,000 and thus likely more able to participate in paid leagues (Petrecca, 2005; Stoffer, 2005). Expectantly, college individuals were more likely to be concerned about their team and sport and followed it closely on a regular basis when they paid to participate. Some criticize the time invested in fantasy sports as wasted. In other words, participating in fantasy sports might not act as the best way to maximize your productivity or contribution to society (Ballard, 2004). This criticism appears especially noticeable and somewhat appropriate when it comes to work productivity. For instance, almost two-thirds of fantasy football players say they check their fantasy teams online during work hours (Petrecca, 2005). This practice shows little signs of slowing down. In 2002, players spent two hours, 45 minutes per week on their teams. In 2004, the number rose to two hours, 58 minutes. Overall, these respondents indicated they think about fantasy sports 38 minutes per day, on average (Petrecca, 2005). According to data based on only 10 minutes of fantasy research per day, employers lose $196.1 million in productivity (Vuong, 2005). Applying this figure to Petrecca’s average, employers would lose approximately $600 million in productivity per year, a troubling figure. For the college student, fantasy sport could provide an unnecessary distraction away from their studies. This study discovered 29.9% of students generally read more and 23.5% watched more about a sport because of their fantasy participation. However, we do not feel the students surveyed demonstrated an unnecessary or detrimental amount of time on fantasy participation because most indicated little change in their behavior. Specifically, 87% of respondents stated the lack of a fantasy team would not affect their attention to sport and 77.6% felt the success of their fantasy team did not determine how much they watch sports. In addition, another 91.8% of respondents declared the elimination of their fantasy team from playoffs or postseason competition failed to eliminate their desire to watch sports. Both researchers and government officials alike identified problems classifying fantasy sport. For example, some regard fantasy sport as similar to playing the stock market because financial risks are involved, research is very helpful, and unforeseen events can positively or negatively affect outcomes (Aamidor, 2005). Appropriately, debate persists on whether or not fantasy sport should be considered gambling. Some say fantasy sport seems addictive for the same reasons as gambling. Specifically, both foster a pathology of promise and a neurotic assurance victory can surface just around the corner (Hruby, 2003). When the topic of whether fantasy sport participation was gambling or not, most respondents (73.3%) indicated they felt it was not gambling. The reasoning behind this basically surrounds fantasy sports being considered games of skill, not chance. Thus, because of this philosophy, the Internet Gambling Prohibition Act of 1997 was amended in 1999. This new proposal exempted fantasy sports leagues from state gaming laws and thus likely influenced a generation of students, like the one from this sample, into believing fantasy sport participation was not gambling (Hruby, 2003). To support the claims fantasy leagues were contests of skill and educationally valuable, companies and entrepreneurs worldwide now offer fantasy sports “camps” to the fantasy player for a hefty fee. These camps include chances to receive tips from sports legends and the option to try your skills at professional venues (Piore, Brooks, Flynn, & Sparks, 2004). The literature also notes fantasy sports serve as educational learning tools. For example, Gillentine and Schulz (2001) use simulation fantasy football to enhance marketing concepts,

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while Einolf (2001) utilizes it as a tool to teach economics of sports courses at Mount Saint Mary’s College. In the future, we could see more opportunities for people to join fantasy sports camps based on its educational and entertainment value. Fantasy sports leagues obviously encourage participants to be abreast of player statistics and injuries. Appropriately, it causes an increase in viewership and overall interest in sporting events. For example, fantasy participants watch two to three more hours of football than nonfantasy players (Snel, 2005). Participation also helps fans gain appreciation for the innerworkings of a sport. By acting as a coach and manager, they experience the day-to-day decisions that take place in a sports league (Ballard, 2004). Standen (2006) and others suggested some fantasy participants enjoy acting as the general manager as much as watching or playing the sport itself (Hiltner & Walker, 1996; Razzano, 2006). Clearly, professional teams at all levels should recognize the benefit of promoting fantasy sport in this manner. For instance, it is possible leagues or associations could improve merchandise sales through fantasy sport specific items, raise attendance figures through special fantasy player promotions, and improve game attendance satisfaction through incorporate more advanced personal seat technology (i.e. smart or choice seats) at their facilities. An interesting study from this perspective would focus on if fantasy sport participation effects brand loyalty. Within this study, professional football (NFL) followed by MLB and the NBA emerged as the three most popular fantasy sports to play but college football replace the NBA as the third most sport they focus their time and efforts. Overall, the NFL, MLB, and college football grabbed the attention of 88% of respondents. This matches other findings offered by the literature. For example, one-third of fantasy players begin participating in a football league because it requires only a modest time commitment but move onto other sports such as baseball and basketball that conduct contests much more frequently (Hruby, 2003). Other sports, in this survey, like college basketball, professional hockey, golf and NASCAR, also enjoyed fantasy leaguer participation but again they remained far behind the NFL, MLB, and NBA. Obviously, these leagues could do more to catch the NFL and MLB. Perhaps making efforts to capture the female market would be a start. Roberts (2006) reports 82% of fantasy players played sports in high school or beyond. This survey produced similar supportive results. Roughly 91% of fantasy players in this survey played high school, college club, or college varsity athletics. This dispels the myth “geeks” rule the fantasy sport realm (Ballard, 2004). This number also supports the proposition that communication networks established between league members can eventually lead to camaraderie among participants, which often turns into friendship, despite their lack of an introduction beforehand because participants/competitors establish a sense of social support from friends made in their fantasy leagues (Ballard, 2004). Fantasy sport participants typically include individuals who want social opportunities with others. They are not traditionally the stereotypical “superfan” (Schwarz, 2004). Our research also supports the friendship concept as 41.1% of respondents declared they felt fantasy sport participation provided them something to talk about with others. Still, as Ballard (2004) pointed out, issues such as trade or rule disputes possess the possibility of ruining friendships for members of highly competitive leagues.

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REFERENCES Aamidor, A. (2005, June 14). National fantasy pastime: Millions draft imaginary squads to score virtual victories. The Indianapolis Star. Retrieved March 2, 2006, from http://www.indystar.com Ballard, C. (2004, June 21). Fantasy world: These three play (Jennie Finch, Dan Marino and Michael J. Fox). Your neighbor plays. Your boss plays. Everybody plays. Once the secret preserve of stats geeks, fantasy sports are now a billion dollar business. Sports Illustrated, 100(25), 80-89. Einolf, K.W. (2001). Turn fantasy into reality: Using fantasy football in an economics of sports course. In Teaching Economics: Instruction and Classroom Based Research. Irwin/McGraw Hill Publishers. Felps, P. (2000, September 20). Fantasy sports players getting a big assist from the internet. The Dallas Morning News. Retrieved February 27, 2006, from http://www.dallasnews.com/ Fantasy Sports Trade Association. History. Retrieved March 3, 2006, from http://www.fsta.org/history.shtml Gillentine, A. and Schulz, J. (2001). Marketing the fantasy football league: Utilization of simulation to enhance sport marketing concepts. Journal of Marketing Education, 23(3), 178-186. Gratton, C. and Jones, I. (2004). Research methods for sport studies. New York: Routledge. Grimaldi, P. (2004, September 9). Jostens hopes to score with fantasy football rings. The Providence Journal. Retrieved February 27, 2006, from http://www.projo.com Hiltner, J.R. and Walker, J.R. (1996). Super frustration Sunday: The day’s prodigy’s fantasy baseball died; An analysis of the dynamics of electronic communication. Journal of Popular Culture, 30 (3) 103-117. Hofacre, S. (1994). The women's audience in professional indoor soccer. Sport Marketing Quarterly, 3, 25-27. Horgan, S. (2005, December 17). The fantasy game: The man credited with starting it all. Sun News. Retrieved February, 27, 2006, from http://www.myrtlebeachonline.com/mld/ myrtlebeachonline/. Hruby, P. (2003, April 29). The case against fantasy sports. The Washington Times. Retrieved February 27, 2006, from http://www.washtimes.com Kerlinger, F.N. (1986). Foundations of behavioral research (3rd. ed.). Fort Worth, TX: Holt, Rinehart, and Winston. Meyers, B. (1997, August 28). Feminine touches planned but blood and guts remain. USA Today, pp. Al, A2. Mihoces, G. (1998, May 7). Women checking in more as NHL fans. USA Today, pp. C1, C2. Miller, S. (2005, December 12). The real revenue in fantasy sports: The statistics, players and profits are authentic; just the teams aren’t. Multichannel News. Retrieved February 27, 2006, from http://www.multichannel.com/article/CA6290241.html?display=Special+Report Patton, M. Q. (1990). Qualitative evaluation and research methods (2nd ed.). Newbury Park, CA: Sage Publications.

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Petrecca, L. (2005, August 25). Marketers tackle participants in fantasy football. USA Today. Retrieved February 27, 2006, from http://www.usatoday.com/ Piore, A, Brooks, A., Flynn, E., and Sparks, J.D. (2004). Play like pros. Newsweek, 143 (16/17), 76-80. Razzano, R.T. (2006). Intellectual property and baseball statistics: Can Major League Baseball take its fantasy ball and go home? University of Cincinnati Law Review, 74, 1157-88. Reilly, R. (2002, April 22). Rotisserie roast. Sports Illustrated, 96 (17), 92. Roberts, B. (2006, January 13). Power Figures. Sporting News, 230(2), 32-33. Salant, P. and Dillman, D.A. (1994). How to conduct your own survey research. New York: John Wiley and Sons, Inc. Schwarz, A. (2004). The numbers game: Baseball’s lifelong fascination with statistics. New York: Thomas Dunne Books. Snel, A. (2005, September 13). Fantasy leagues make real cash. Tampa Tribune. Retrieved February 27, 2006, from http://www.tampatrib.com Standen, J. (2006). The beauty of bets: Wagers as compensation for professional athletes. Willamette Law Review, 42 (4), 639-668. Stoffer, H. (2005, May 16). GMC makes a play for millions of fantasy sports fans. Automotive News, 79 (6147), 38. Trochim, W.M.K. (2001). The Research Methods Knowledge Base. (2nd ed.). Mason, OH: Atomic Dog Publishing. Vuong, A. (2005, September 6). Fantasy football turns into big business. The Denver Post. Retrieved February 27, 2006, from http://www.denverpost.com/ Williams, J.F. (2006). The coming revenue revolution in sports. Willamette Law Review, 42 (4), 669-709. Wilner, B. (2005). Fueling the female fan base. Sportbusiness International, 101, 20-21. Yi, M. (2004, June 17). EA takes a run at fantasy football: Firms’ Madden video game expected to drive interest. San Francisco Chronicle. Retrieved February 27, 2006, from http://www.sfgate.com

Contemporary Athletics Compendium, Volume 3 Editor: James H. Humphrey

ISBN: 978-1-60741-561-9 © 2009 Nova Science Publishers, Inc.

Chapter 14

A LOOK AT ACADEMIC REFORM, STUDENT ATHLETE COMPENSATION AND THE CASE FOR A NEW CLASSIFICATION OF STUDENT-ATHLETE Frank Adrien Bouchet Texas A&M University, College Station, Texas, USA

ABSTRACT This paper discusses student-athletes compensation issues. The author expresses his concern over the unwillingness of the National Collegiate Athletic Association (NCAA) to fairly compensate these athletes. Since the main concerns according to the N.C.A.A. over such a system are workman’s compensation and academic reform we will look into both of those issues as well. A historical perspective will be applied to these issues. We will look into the possibility of some of the main athletic conferences breaking away from the N.C.A.A. and starting a new classification of student-athlete. The advantages and disadvantages of such a move will be looked at as well. The leadership structures of both higher education and the N.C.A.A. will be discussed.

A LOOK AT THE HISTORY OF STUDENT-ATHLETES COMPENSATION The following paper will focus on student-athlete compensation in today’s world of intercollegiate athletics. We will look at the higher education governance and leadership systems under both the university and the National Collegiate Athletic Association (N.C.A.A.) banner. The question Does the degree outweigh the dollar will be examined. Does learning, goal setting, and team work, all of which have been legs on which college athletics stood for still matter? Or have they been replaced by the quest for the dollar? Is the “new vision” of learning really how to make the dollar work for the university at the expense of student athletes? We will drill down on the decision making process as it relates to compensating student-athletes. We will also look into the reform movement at both the higher

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education and N.C.A.A. level as well as the various schools that make up the N.C.A.A. The Knight Foundation Commission on Higher Education report (1993) as well as the recently implemented Academic Progress Report will be examined. In the later part of the paper we will look at the student-athlete as a workforce and explore all the changes that have taken place over the last fifty years that have brought us to the place where examining the compensation structure of the current N.C.A.A. is a much needed exercise. In 2002 the Association of American Colleges and Universities launched an initiative called Greater Expectations: The Commitment to Quality as a Nation Goes to College. This initiative brought to the forefront the need for meaningful reform in higher education. “The report calls for a dramatic reorganization of undergraduate education to ensure that all college aspirants receive not just access to college, but an education of lasting value”(National Panel Report, 2002, p1). Like athletics, many people have different opinions about what exactly the college experience should entail. Many students and parents see college as a springboard to employment; they want job related courses. Policy makers view college as a spur to regional economical growth, and they urge highly targeted workforce development. Business leaders seek graduates who can think analytically, communicate effectively, and solve problems in collaboration with diverse colleagues, clients, or customers. Faculty members want students to develop sophisticated intellectual skills and also to learn about science, society, the arts, and human culture. For the higher education community as a whole, college is a time when faculty and students can explore important issues in ways that respect a variety of viewpoints and deepen understanding (National Panel Report, 2002 p. 2).

As one can see from the above paragraph defining what needs a college should meet are as tough as defining the needs of the campus athletic department. One of the focuses of this paper will be the need to include the overhaul of college athletic departments in this topic. The last fifty years has brought drastic changes to the university and its central mission. Perhaps no other department in a university has seen its overall mission changed as much as the campus athletic department. Like the university as a whole, today’s athletic department differs drastically from the one started in the early 1900’s. As the university has battled increasing responsibilities in areas such as affordability, access, and relevant education, the athletic department is facing such issues as commercialism, spiraling cost and academic reform. To add to these responsibilities there is growing concern among college stakeholders that if a university is not going to educate their student-athletes than they need to compensate then in other forms.

HISTORY OF LEADERSHIP AND GOVERNANCE OF HIGHER EDUCATION Although college athletics have only been around since the late 1800’s universities have been in existence since the late 1600’s when the legislature of the Massachusetts Bay Colony established Harvard. They subsequently established a committee of overseers including the state governor, treasurer as well as three magistrates and six ministers. This would later serve

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as the first governing board. The College of William and Mary was the second college to be formed. William and Mary took a slightly different route in their formation and that of their governing board. “Virginia was a royal colony dependant on officials from London, and the colony itself was dominated by plantation owners, many of whom did not rank public education as a high priority (Cohen, 1998 p.41). In the early 1690’s a group from the Anglican church in Virginia went to London to seek permission to charter a college. Their charter, which was authorized in England, included eighteen Virginia men to serve as “visitors” of the college. These visitors were authorized to charter a school and to set rules and regulations. The third college, Yale, was formed by a group of Connecticut Congregational ministers. They were authorized to manage the schools funds and to grant degrees without consent of the church. “The 1701 charter thus established a college operating without the direct participation of secular officials, even though the General Court promised to grant an annual sum to sustain the institution” (Cohen, 1998 p. 41). Brown University in Rhode Island was the next college formed although its board was predominantly composed of Baptists it also included many different denominations. The College of New Jersey, later renamed Princeton, was the first school formed that advocated religious freedom specifically requiring that all religious parties be accepted. Although graduates of these institutions were free to pursue any career they wished many chose the clergy or public service. A good many of this first group of college graduates would go on to become leaders in their state legislature. During the 1800’s hundreds of college were formed as states started to take over from what had been predominantly church financed colleges. The federal government also rewarded state colleges by offering land as an incentive to the schools thus starting the land grant colleges. This record growth in the number of colleges also helped start intercollegiate athletic events between schools. The first athletic competition of record was a crew event between Harvard and Yale in 1852. Over the next thirty years almost all colleges were competing in some form of intercollegiate athletics. It’s interesting to note that the universities in Europe experienced almost a similar growth in athletics with one major difference. “Athletics were part of the collegiate experience in English and German universities as well, but they were different in the United States because of commerzation” (Cohen, 1998 p. 122).

HISTORY OF THE NCAA The origins of the modern National Collegiate Athletic Association (NCAA) began with President Teddy Roosevelt comments “No student shall represent a college or university in any intercollegiate game or contest….who has at any time received, either directly or indirectly, money or any other consideration” (Byers, 1995). These comments were made in the year 1907 after athletic representatives had been summoned to the White House because of a Presidential inquiry into the deaths of several players. Thanks to Teddy Roosevelt and the fledgling N.C.A.A., deaths among football players became rare, and academic cheating and pay-for-play were kept sufficiently under control for the games to go on. One of the country’s most prestigious organizations, the Carnegie Foundation commissioned a report in 1929 on the state of college athletics in particular football. The

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report was a scathing indictment on the way universities ran their football programs. The report called for a de-emphasis of football because of an attitude of win at all cost coaches, increased commercialization and illegal players. In the early 1940’s University of Chicago President Robert Maynard Hutchins noted: “Education is primarily concerned with training of the mind, and athletics and social life, though they may contribute to it are not the heart of it and cannot be permitted to interfere with it… An educational institution can make one unique contribution, one denied to a fraternal order or a bodybuilding institute: It can educate. It is by its successes in making this unique contribution that it must be judged.” (Byars, 1995) Perhaps President Hutchins foresaw the anti academic pressures on student-athletes better than most, as the University of Chicago withdrew from the Big Ten athletic conference in 1946. Such statements document the fact that today’s student-athlete compensation issues have been in discussion since the beginning of intercollegiate sports. “Although the N.C.A.A. was promoted as the guardian of amateur principles and integrity in sports, since it was dominated by coaches and athletic directors, its primary purpose increasingly became that of defending college sports against true reform” (Duderstadt, 2000, p.72). This would become more of a problem in the coming years as television began to exert its control over the college sports essentially turning what was a regional sport into a national one. “Television networks found that by promoting and marketing college sports much as they would other commercial – generating great media hype, hiring sensationalistic broadcasters, urging colleges to arrange even more spectacular events – they could build major nationwide audiences” (Duderstadt, 2000 p.73). It would not be until the next century that college president’s would take back control of the N.C.A.A. Like there forefathers today’s college presidents show little inclination toward compensating student-athletes. There argument is that the student-athlete is compensated by receiving a college education in exchange for his/her athletic talents (Duderstadt, 2002, p.75). This argument only has merit if the student-athlete is in reality receiving an education. While it is true that the academic success of most athletic department mirrors closely the student body as a whole the situation in the main revenue sports of football and basketball is much different. The average academic achievement of student-athletes in football and basketball programs ranks below that of the student body in general (Duderstadt, 2000, p.199). The numbers decrease even further when you take out the football statistics. Only 41 percent of all student-athletes graduate and the graduation of black basketball players have dropped to 33 percent, the lowest level in 15 years (Duderstadt, 2002, p.199). It is obvious from these numbers that universities are not graduating student-athletes at an acceptable rate.

ACADEMIC REFORM WITHIN THE N.C.A.A. “It has been difficult of late for an academician to read an issue of the Chronicle of Higher Education without concluding that the most interesting collegiate sports news is no longer made on the fields of play” (Porto,1985). While that comment was first made in 1985 little has changed in the last twenty years to change how an academician views college athletics. This section will focus on the leadership systems in place at the college level and how their actions affect student-athletes. The N.C.A.A. recently passed an academic reform package designed to address the troubling issue of graduation rates at member schools

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(N.C.A.A., 2004). While on the surface it would appear that academic reform has little to do with the compensation of student-athletes if one looks deeper into the problem you will see that the two issues are intertwined. One of the main arguments against the so called “pay for play” is that student-athletes are receiving a free education. It is only after looking at the dismal graduation rates that the conversation about student-athlete compensation gets more serious. Another of N.C.A.A. President Myles Brand major initiatives is the Academic Progress Rate (APR). The A.P.R. is a real time assessment of a particular team’s academic performance. The scoring system consists of two points for each term a student-athlete meets academic eligibility requirements and who remains enrolled at the institution. A particular team’s A.P.R. is earned by the team at a given time divided by the total points possible. The N.C.A.A. has set a rate of 925 as the score with which teams must achieve. This number takes into account an expected graduation rate of 50 percent of all student-athletes competing for the university. If teams fail to score 925 points contemporaneous penalty are assessed. These contemporaneous penalties might include the loss of a scholarship for an academic year. The next level of penalties is the historically based penalties. These penalties are assessed to teams that have repeatedly been penalized for academic deficiencies. These penalties might result in additional scholarship reductions, recruiting restrictions, lack of access to postseason competition and loss of N.C.A.A. membership. The recently passed academic reform package also show that the current structure within the N.C.A.A. is one in which the university presidents have clearly taken control. Prior to the presidents taking control of the N.C.A.A. during the 1996 convention the organization had been controlled by athletic directors and coaches. It was obvious to all that these parties cared much more about their own empire building than about student-athletes. Under the new reform package, schools that have student-athletes who do not meet specific academic standards would lose athletic scholarships, recruiting opportunities, and post season revenues. Schools that obtain repeat offender status could eventually risk losing post season invitations or N.C.A.A. membership rights. These reforms are important to college athletics for three main reasons. The first reason is that receiving a free education is often cited as one of the main reasons behind the universities not wanting to monetarily compensate student-athletes. The second reason is that they strengthen the chances of academic success and the third reason is that they hold institutions accountable for the academic success of their student athletes. The measure, which passed last summer, has been in the works for the past three years is seen as a major victory in the agenda of N.C.A.A. President Myles Brand. The N.C.A.A. prior to 1996 was one in which voting on specific reforms was handled in a “town hall” type setting. In 1997 the voting was changed to a format with more presidential input. This change in voting was due in part on recommendations by the Knight Commission. While these new academic standards are a key component to true academic reform, the jury remains out on their effectiveness in raising graduation rates of football and basketball student-athletes. The Knight Commission was a high powered commission designed to study ways to bring academics back to the forefront of college athletics. One of the main focuses of the Commission was that university presidents needed to take back control and oversight of their college athletic departments. This sent an important message that university presidents who had long held the party line of no compensation for student- athletes were firmly in control.

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The Knight Commission was formed in 1989 by the trustees of the John S. and James L. Knight Foundation. The trustees concern grew as abuses increased in college athletic departments. They believed the abuses and the greater number of infractions that were threatened the very integrity of higher education. In 1989 the foundation created a Commission on Intercollegiate Athletics with one main focus: propose an agenda designed to reform college athletics. It should be noted that the Knight Foundations main goal was to reform the culture of college athletics, the commission did not partake in any study on the compensation of student-athletes (Knight, 1993). However, this report was an important step towards academic reform which serves as the main argument against monetary compensation for studentathletes. While the Commission had no formal governing rights over college athletics, it was clear from the start that it had the full support of the N.C.A.A. and its member institutions. To further illustrate this point it is worth noting that in 1993, a full four years after the Commission published its findings, nearly two thirds of its specific recommendations had been endorsed by the N.C.A.A. The commission appeared to go out of its way to stressing that it was not out to abolish intercollegiate athletics. James L. Knight, Chairman of the Foundation said “We have a lot of sports fans on our board, and we recognized that intercollegiate athletics have a legitimate and proper role to play in college and university life” (Knight, 1993). He added “Our interest is not to abolish that role but to preserve it by putting it back in perspective”(Knight) The climate concerning intercollegiate athletics in the late 1980’s and early 1990’s that the Knight Commission found was one of increasing violations. In the N.C.A.A.’s Division I 57 of the 106 member schools were cited with infractions between the years of 1980 through 1990. In addition to the constant barrage of infractions, 48 member institutions had graduation rates under 30% for their men’s basketball and 19 universities had the same low rate for football players (N.C.A.A., 2004) With monetary incentives tied to ever increasing television-rights fees, universities are under constant pressure to perform. The Knight Commission noted: “The current practice of shared governance leads to gridlock. Whether the problem is with the presidents who lack the courage to lead an agenda for change, trustees who ignore an institutions goals in favor of the football team, or faculty members who loath to surrender the status quo, the fact is that each is an obstacle to progress” (Knight, 1993, p.11). The Knight Foundation Commission on Intercollegiate Athletics met over the course of five years (1998 – 2003) and produced three reports. They found one of the main problems in the college ranks was one of university presidential neglect. Presidential oversight was also the main focus of reform for the Commission. The Commission recommended a “one-plusthree” model which consisted of presidential control directed toward academic integrity, financial integrity, and independent certification. The key component of this new model required that university presidents be held accountable for their athletic departments. The first initiative after presidential control was academics. The key point in the academic integrity initiative was that students that participate in athletics deserved the same rights and responsibilities as all other students. Financial integrity was the second initiative discussed in the report. Regarding financial integrity the report stated: “The central point with regard to expenditures is the need to insist that athletic departments’ budgets be subject to the same institutional oversight and direct control as other university departments” (Knight, 1993). Among the concerns were reducing football and basketball expenditures and aligning coaches compensation within the context of the

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academic institutions that employee them. The last of the main initiatives was independent certification. Independent certification of the athletic department would be accomplished through periodic assessments by an independent auditor. The audit would cover the entire range of academic and financial issues pertaining to intercollegiate athletics. The report freely admitted that most presidents were historically uncomfortable with athletic department oversight and all to willing to turn over that responsibility to athletic directors. In order for these new reforms to work it was clear that presidents had to take back control of their athletic departments. The Commission stated: “the presidents goal must be nothing less than the restoration of athletics as healthy and integral part of the athletic enterprise” (Knight, 1993). The Commission recognized that there was not a “magic pill” that would cure all the ills of intercollegiate athletics when they stated: “Reform is not a destination but a never ending process” (Knight Report, 1991). By publicly stating this they appeared to realize that these changes would have to be implemented over a long period of time. A positive sign that the N.C.A.A. was taking a serious stance towards these reforms occurred in 1996 when the N.C.A.A. adopted a governance structure which placed all planning and policy activities including budgets with the college presidents instead of with athletic administrators. After the final report was released the Commission was disbanded but not before agreeing to monitor the situation and meet periodically to review the progress being made. In 2001 the Commission did indeed meet to discuss the state of intercollegiate athletics. By stating that “Reform is not a destination but a never ending process” the general consensus was the committee gave themselves some leeway in determining whether or not the recommendations had been a success. The selection of Indiana University President Myles Brand to lead the N.C.A.A. was seen as a step in the right direction. Prior to his appointment the N.C.A.A. had for the most part been led by former college athletic directors. The appointment of Myles Brand, a university president, sent notice to the college athletic community that reform was on its way and that critical issues regarding student-athletes and academics would be addressed. As one might have determined this move has elicited response from people on both sides of the issue. While reformers such as Brand contend “In college athletics, the focus is on the individual athlete, he or she is a student-athlete first. Their primary reason for being in college or university is – or should be – to obtain an education.” (N.C.A.A., 2004) Brand continued to say that “these are strong and well thought out reforms that are critically necessary to ensuring that college athletes are academically successful.” (N.C.A.A., 2004). Although the Presidents have exercised their power concerning academic reform there still remains a hierarchy with athletic directors on top followed by the coaches and then the student-athletes. Within the last ten years there has been a tremendous rise in the salaries of both athletic directors and coaches from revenue generating programs without an obvious increase in either extra duties or increased performance. Within the corporate ranks salary increases have usually been in line with superb performance or increased responsibilities. This is clearly not the case within an athletic department. Perhaps no other position has benefited from the rise in commercialization more so than the head coaches in both football and basketball. Over the past fifteen years the average salary for the respected head coaches in these sports has increased sizably. The one area that has not changes is the compensation structure for student-athletes.

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STUDENT ATHLETES AS A WORKFORCE In this section we will look at the student-athlete as a workforce. The one constant in college athletics is the monetary value of the student-athletes scholarship. While college athletic administrators and coaches salaries have continued to climb, the incentives for student-athletes have stayed the exact same. This has put an increased strain on the relationship between the student-athlete and the institutions in which they serve. Increasingly student-athlete’s view themselves as an uncompensated workforce. In a country that relies on the court system to guide us on legal matters the courts are at an impasse on this issue. In an article for the Journal of Sport and Social Issues, Porto (1985) writes: In raising the issue of whether or not a college scholarship was a contract of employment which entitled an injured athlete to worker’s compensation, this case has produced two very different interpretations of the relationship which exists between scholarship athletes and the universities. Both constructions are seriously flawed: while one would create unnecessarily onerous financial, administrative, and educational implications for the universities, the other ignores the close resemblance which participation in big-time intercollegiate sports bears to employment and the extent to which the integrity of university athletic programs has been compromised as a result (p. 20).

According to University of New Haven Professor Allen Sack (1985) The view that scholarships are quid pro quo contracts becomes more convincing when one examines factors often used in worker’s compensation cases to determine whether there exists an expressed or implied contract for hire (Sack, p. 2)

The workman’s compensation issue is cited primarily because it is one of the main arguments against monetarily compensating student-athletes. The argument is not a new one in fact it’s been discussed since colleges and universities started participating in athletics. It has been well documented that certain language has been deliberately omitted from the actual scholarship papers a student-athlete signs due to the ever increasing concern that it might be construed as an employment agreement. “With grants-inaid increasingly in vogue in the 1950’s, college officials found that the term employee was being interpreted by state officials applying state laws in the interest of the people, not college faculty representatives and athletic directors interpreting college rules in the interest of the college” (Byers, 1995 p. 69). It is clear that the lower courts tend to view student-athletes as employees of the university while the appellate courts have overturned this view time and time again. “At many universities, including the University of Michigan, graduate student teaching assistants, who are compensated for classroom teaching, not only are recognized legally as employees but allowed to form unions for collective bargaining” (Duderstadt, 2000 p.198). It is ironic that those students compensated for academic activities are considered employees, while those students compensated for performing in highly profitable athletic “business” are not” (Duderdstadt, 2000 p.198). As James Duderstadt, the President of the University of Michigan, stated in the above sentence the last ten years has seen a rise in the on campus union activity of graduate assistant students. In Los Angeles there has been an effort to form a union which represents the

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student-athletes interest. In early 2000 former University of California Los Angeles linebacker Ramogi Huma started the Collegiate Athletes Coalition (C.A.C.). The C.A.C. was formed to help student-athletes gain much needed benefits from the N.C.A.A. According to the N.C.A.A., student-athletes should feel grateful to be receiving a “full ride”. The C.A.C. position is that a full ride doesn’t begin to justify the long hours spent earning money that benefits the university. While their public position is that they are an organization not a full fledged union it should be noted they have joined forces with the United Steelworkers of America to provide an infrastructure for their agenda. By definition a union is any organization that seeks to gain collective bargaining. This definition certainly seems to fit with the C.A.C.’s charter. While it has never recognized the C.A.C. publicly the N.C.A.A. has taken steps to pass legislation designed to appease current student-athletes. One of the main goals of the C.A.C. is to get the N.C.A.A. to pass legislation proposed by California Senator Kevin Murray called the Student Athletes’ Bill of Rights. This bill would insure that student-athletes have year round health coverage as well as additional spending money that would cover the cost of college attendance. The bill which was authored by former University of Colorado football player Jeremy Bloom would also give student-athletes a percentage of the sales of their athletic jerseys. The jersey royalty issue is an issue that continues to be a sore spot with current and former student-athletes. While N.C.A.A. rules prohibit the names of current players on the backs of jerseys it doesn’t prohibit their number from being displayed. The main grievance of the C.A.C. is that the N.C.A.A. refuses to reform its rules to actually benefit the student-athlete. Although this organization has been around for only a few short years it has made some significant strides in the current reform movement. One of the C.A.C. main problems is getting student-athletes to sign up for its services. Unlike professional baseball players who have struggled for years in the minor leagues before they start to make money college athletes tend to be more reserved. College athletes, especially in the major revenue sports tend to be pampered all through school. This fact makes them extremely reluctant to speak out against the system. The argument against compensating student-athletes for their talents is similar to the one argued for years against university technology transfer rules. With technology transfer, universities along with faculty are allowed to profit from the discoveries made by professors in university owned facilities by patenting an idea and then commercializing it when the product goes to market. Roger Noll, an economist at Stanford University writes in Rethinking College Athletics (1991): College sports are already professionalized at universities that house their athletes separately, that advertise themselves as preparatory schools for a career in professional sports, and that fails to graduate nearly all its players. Professionalization does not lie in how much someone is paid; it lies in the nature of the bargain between the university and a player. If athletes play little or no role in campus life, if they are not in any meaningful sense students, and if they are associated with the university only to participate in its athletic program, they are professionals, regardless of the amount they are paid (p. 208)

College athletics has become expensive. The cost of operating a Division I athletic department has more than doubled in the years 1993 – 2003 (Fizel, Fort, 2004, p.37). The revenue generated from the B.C.S. and the N.C.A.A. basketball championship has helped

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create an atmosphere of placing the importance of winning over the student-athletes best interest. “And each institution, once entered, will face powerful incentives to increase its expenditures in search of a competitive edge. This logic is in harmony with the observation that the revenues generated directly by college athletic programs fall far short of covering the costs in the overwhelming majority of cases” (Frank, 2004). The creation of the Bowl Championship Series (B.C.S.) and other revenue generating mechanisms has established a new monetary goal which has replaced the athletic quest for excellence. “A frantic money oriented modus operandi that defies responsibility dominates the structure of big time college football and basketball” (Knight Report, 2002). Recent data has disputed an arms race in college athletics as it relates to operating budgets it clearly indicating spiraling costs related to both coaches salaries and facilities. A study by the Brookings Institute and commissioned by the N.C.A.A., states: “Increased spending on men’s football and basketball does not produce medium term increases in winning percentages, and winning percentages does not produce medium term increases in net operating revenue” (Orszag, 2003). Although the value of a college scholarship has remained unchanged the actual college scholarship has undergone many different changes over the years. One must take a historical look at the evolution of the scholarship to fully understand the changes that have taken place. In 1948 the N.C.A.A.’s athletic scholarship took the form of a Sanity Code. The Sanity Code included tuition and fees if the student-athlete showed financial need and met the schools entrance requirements like an ordinary student. According to most universities this amounted to a merit award in exchange for their athletic requirements. The student-athlete would be eligible for an athletic scholarship if he ranked in the top 25 percent of his high school graduating class. This was a guaranteed scholarship regardless of whether or not the student decided not to play. This rule failed in 1950 when many of the southern schools believing that the well endowed schools from the north could circumvent this rule due to an influential alumni base. It deserves mentioning that the Ivy League and the Big Ten supported the Sanity Code. This fact shows the growing mistrust not just between schools but between conferences as the academically oriented schools fought to keep the Sanity Code and the southern schools fought to adopt a grant-in-aid system. It was at the N.C.A.A. convention of 1956 that a grantin-aid system was adopted by almost all universities participating in collegiate athletics. This was seen by most of academia as the first step toward a “pay for play” model. It was at this convention in 1956 that the delineation between an athletic scholarship and need based financial aid began to assert itself into college athletics. Prior to this convention most studentathletes attended school on need based financial aid. Need based financial aid amounts to a contractual agreement between the student and the institution (Gerdy, 2005). Under the contract, the student will continue to receive his or her financial aid regardless of what transpires on the athletics field As a result, the student is less beholden to the athletic departments competitive and business motives and thus freer to explore the wide diversity of experiences college offers. (Gerdy, 2005) After the convention of 1956 what began to replace need based financial aid were athletic scholarships. These athletic scholarships represent a contractual agreement between the student-athlete and the coach. This contract has little to do with education and everything to do with athletic performance and control (Gerdy, 2005) In this arrangement a coach tends to view the student-athlete as an employee that he or she has control over. The fact is when you are paid to play, regardless of the form of “payment”, everything takes a back seat to the athletes performance (Gerdy, 2005)

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It was during this time that the term student-athlete was adopted primarily to deal with the problem of trying to circumvent state employment laws which increasingly saw studentathletes as employees of universities. “One typical state law of that era provided that an employee is any person who engages to furnish his services for remuneration, subject to the direction and control of an employer” (Byars, 1995, p. 70). As the definition of an athletic scholarship has changed over the years so has the way college coaches award them. “Coaches took another step toward professionalism in1973, up until then grants were for four years and could not be revoked. But the coaches wanted more control over athletes, including the ability to terminate their scholarship for poor performance” (Duderstadt, 2000, p197). In today’s college sports world the scholarships offered by coaches are typical one year renewable scholarships. These scholarships can be revoked for any reason be it either academically or athletically as long as the coach notifies the player prior to July1 of the upcoming year. Over the last decade the N.C.A.A. has abolished symbols of athletic employment such as athletic dorms and limited the hours a team can practice. They have continued to make sweeping changes designed to ease the growing pressures on the student-athlete. This pressure is caused by an ever increasing commercialization of college athletics. Although college coaches and administrators are the monetary benefactors of the student-athletes work, there seems to be a growing sentiment among coaches that some form of compensation is overdue. One suggestion that has gained a certain amount of momentum lately is the paying of college athletes that participate in the major revenue generating sports. This plan would create a new classification of student-athlete. Under this plan the so called B.C.S. conferences, which include the Big Ten, Big Twelve, Southeastern, Atlantic Coast, Pac Ten and Big East conferences, would become actual professional leagues and college athletes would be paid a salary. They could either accept this salary or take a scholarship from the school. The proposal has some advantages as it would fairly compensate athletes for their talents. It would also do away with the hypocrisy that currently surrounds college athletics by eliminating the fairly tale of the “student-athlete”. It would serve to fairly compensate those athletes that have no desire to attend classes. “Since they would pay for play rather than for an education, they would not be cheated if they never received a degree or developed academic skills (Simon, 1985, p. 58). The time has come to compensate our student-athletes for their services. Because of the talents of the student-athletes the universities athletic directors, coaches and school officials are paid more than they would in an open market. The N.C.A.A. could make some modest concessions such as a monthly stipend, year round health coverage and travel expenses. These concessions would go along way in appeasing current and future student-athletes who are starting to realize their value to the university. One could draw a sharp correlation between today’s student-athletes and major league baseball players in the 1960’s. In the early days of the major league baseball players association the union was asking the team owners for reasonable requests. It was only after not getting any concessions from the owners that baseball players began making major demands and threatening strikes. In retrospect it would be interesting to see what would have happened had the baseball owners listened to the players and tried to form a compromise.

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However, this proposal has some detractions as well. For one thing it would exclude all but the main revenue sports, therefore drawing a sharp distinction between revenue and non revenue sports. Something the NCAA has to date been loath to admit. One potential problem that is seldom discussed is the question of whether or not stakeholders such as alumni, faculty and other university supporters would support such a professional league concept. This is an important question as much of the pageantry of college athletics revolves around this groups. There are also potential ramifications for this move that deserve mentioning. At most Division I institutions the major revenue sports like football and basketball fund the non revenue sports. If the money making sports form their own league where is the funding for the non revenue sports going to come from? A long time NCAA executive once was quoted as saying that the NCAA does two things well. The first is put on championships. The second is enforcing rules and regulations. If the major schools do ever decide to break off and form their own league then the question must be asked: What purpose will the NCAA have? Another major question is what defines a revenue sport? When this plan is mentioned it almost always includes just football and basketball. Universities define what makes a revenue sport differently. The University of Tennessee certainly considers women’s basketball to be a revenue sport. The same could be said for hockey at the University of Wisconsin, softball at the University of Arizona and lacrosse at Johns Hopkins University. In its currently state a university athletic department does not operate as a legitimate business per se with a profit motive bottom line. Business school professors would use the term “sustain the enterprise” in describing the mission of an athletic department. This term simply means the athletic departments chief concern is to pay its employees, host games and spend its budget. If the proposed idea were implemented it would change the mission of the athletic department to a profit oriented business. “Once the university consciously enters professional sports where the major goal is profit, doesn’t its character change as well? (Simon, 1985, p.59). While this idea is probably not feasible under the current N.C.A.A. leadership implementing some aspects of this plan make sense. Reasonable people can agree or disagree upon which model best suits college athletics however most people agree that college athletes needs to be properly compensated for their work. How that compensation is administered remains to be seen. While the rise in TV revenues as well as gate receipts continues to increase so does the belief that the compensation should come in a monetary form. Perhaps most important is the belief that the N.C.A.A. needs to take a leadership position on this issue before a decision is made for them. As many third world dictators have learned, power is accrued to the organizations that parcel out benefits not hoard them. Those organizations that hoard power are usually overthrown.

REFERENCES Andre, J. and James, D. (1991) Rethinking College Athletics Philadelphia: Temple University Press. Byers, W. (1995). Unsportsmanlike Conduct Ann Arbor: University of Michigan Press.

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Cohen, A. (1998). The Shaping of American Higher Education San Francisco: John Wiley and Sons. Duderstadt, J. (2000) Intercollegiate Athletics and the American University: Ann Arbor: University of Michigan Press. Fizel, J. and Fort, R (2004) Economics of College Sports: Westport: Praeger Publishing. Frank, R. (2004) Challenging the Myth, Knight Foundation Commission On Intercollegiate Athletics Retrieved from knightfdn.org. Friday, William C. and Hesburgh, Theodore (March 1991 – March 1993) Commission on Intercollegiate Athletics, Knight Foundation Retrieved March 10, 2005 from knightfdn.org. Gerdy, J. (2005, January 5). Collegiate model needs more separation N.C.A.A. News Online. National Collegiate Athletic Association. (2004) APR Questions and Answers Retrieved April 2, 2005 from ncaa.org/academics_and athletics. Porto, B. (1985) Athletic Scholarship as Contracts of Employment. Journal Of Sport and Social Issues, 9, 20. Sack, A. (1985) Worker’s Compensation for College Athletes. Journal Of Sport and Social Issues, 9, 2. Sperber, M. (1990) College Sports Inc. New York: Henry Holt and Company Thelin, J. (1994) Games Colleges Play Baltimore: The Johns Hopkins Press.

Contemporary Athletics Compendium, Volume 3 Editor: James H. Humphrey

ISBN: 978-1-60741-561-9 © 2009 Nova Science Publishers, Inc.

Chapter 15

MOTIVATIONAL PROFILES OF SPORTS FANS ATTENDING DIFFERENT LEVELS OF BASEBALL GAMES Amber L. Rickard, Frederick G. Grieve∗ and W. Pitt Derryberry Western Kentucky University, Bowling Green, Kentucky, USA

ABSTRACT While a number of studies (e.g., James and Ross, 2004; Mehus, 2005; Wann, Grieve, Zapalac, and Pease, in press) have examined motives sport fans have for attending different sports, few have examined motives for attending different levels of the same sport (Bernthal and Graham, 2003). The present study was designed to examine motives for attending five different levels of baseball games—T-Ball, Little League, High School, College, and Minor League. Participants were 224 adult fans who attended a game at one of the five levels. They completed measures of sport fandom, team identification, and motivation for attending the game. Different motivational patterns were evident among the different levels. Implications for the findings are discussed.

Sport fans report attending different types of sports for a number of different reasons (Bilyeu and Wann, 2002; James and Ross, 2004; McDonald, Milne, and Hong., 2002; Mehus, 2005; Wann, 1995; Wann, Grieve, Zapalac, and Pease, in press). However, what is less well known is whether motivational patterns differ across different levels of the same sport. The present study was designed to address this lack. Perhaps not surprisingly, sport fans report that they attend different types of sporting events for different reasons. Many of the reasons revolve around the qualities of the sport. For example, fans attending soccer games report higher levels of social and excitement motives

∗

Please address correspondence to: Frederick G. Grieve, Department of Psychology, Western Kentucky University, 1906 College Heights Blvd, #21030. Bowling Green, KY 42101-1030. e-mail: [email protected]

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for attending than fans who attend ski jump competitions (Mehus, 2005), which could reflect the qualities of the two sports. James and Ross (2004) surveyed fans of collegiate sports and found significant differences among motives for attending different sporting events. Nine motives were examined: Entertainment, Skill, Drama, Team Effort, Achievement, Social Interaction, Family, Team Affiliation, and Empathy. Results indicated that there were significant differences across three sports. Spectators at the wrestling matches rated all of the motives higher than spectators at the baseball and softball games. Spectators at softball games rated all motives except social interaction higher than spectators at baseball games. Spectators at men’s baseball, women’s softball, and men’s wrestling rated the sport-related motives (entertainment, skill, drama, and team effort) higher than the self-definition motives (achievement, empathy, and team affiliation). Consumers of men’s baseball, women’s softball, and men’s wrestling also rated the sport related motives higher than personal benefit motives (social interaction and family). McDonald, Milne, and Hong (2002) examined the motivational factors of consumers who watch and play sports. Using Maslow’s five human needs as a framework, they developed a scale that evaluated 12 types of motivations for sport participation and spectatorship (achievement, competition, social facilitation, skill mastery, physical risk, affiliation, aesthetics, aggression, value development, self esteem, self actualization, and stress release) and surveyed 1,611 people about the reasons why they watch nine different sports (automobile racing, college baseball, professional baseball, college basketball, professional basketball, college football, professional football, golf, and ice hockey). There were significant differences for nine of the motivations across sport. Participants who were fans of golf rated the achievement motive lower than fans of all other sports. Fans of auto racing and golf rated skill mastery as higher than fans of the other sports. Fans of auto racing and ice hockey rated physical risk as more important than fans of other sports. Affiliation was important for fans of auto racing moreso than fans of the other sports. Fans of basketball, hockey, and golf rated the aesthetic motive more highly than fans of other sports. Aggression was rated more highly by fans of auto racing and ice hockey than fans of other sports. The other motives did not display much variance, perhaps because they are more suited for participation in sports rather than spectating. In a comprehensive examination of sport fan motives, Wann et al. (in press) examined the motives fans report for watching a given sport. They assessed eight different motives (escape, economic, eustress, self-esteem, group affiliation, entertainment, aesthetic, and family reasons) for watching 13 sports (professional baseball, college football, professional football, figure skating, gymnastics, professional hockey, boxing, auto racing, tennis, professional basketball, college basketball, professional wrestling, and golf). Participants included 1372 college students who completed the survey. Participants only responded to sports that they enjoyed and followed frequently. The results indicated that aesthetic motivation was more important for fans of individual sports (e.g., figure skating, golf) while eustress, self-esteem, group affiliation, entertainment, and family reasons were more important motives for fans of team sports (e.g., football, baseball). For fans of nonaggressive sports (e.g., figure skating, baseball), aesthetics, again, was rated highly. For fans of aggressive sports (e.g., wrestling, football), economic, eustress, group affiliation, and entertainment were highly rated motives. Aesthetic motivation was also a high motive for fans of stylistic sports (e.g., figure skating, gymnastics). Fans of nonstylistic

Motivational Profiles of Sports Fans Attending Different Levels of Baseball Games 165 sports (e.g., hockey, tennis) rated economic, eustress, self-esteem, group affiliation, entertainment, and family reasons highly. Finally, the profiles of motives across sports were noted. To date, only one study has examined fan motivation for attendance at different levels of a given sport. Bernthal and Graham (2003) explored the difference in fan motivation factors among fans attending Minor League baseball games and collegiate baseball games. A total of 522 fans, 188 from a Minor League game and 334 from a collegiate baseball game, completed an 11-item survey of the reasons they attended the game. From the survey, four motivational factors were established: Baseball (rivalries, quality of play, viewing outstanding players), Value (ticket price, overall cost of attendance including parking, concessions), Added Entertainment (promotions/giveaways, in-game entertainment such as mascots, sound effects.), and Community (family involvement, allegiance to home team). Results indicated that Minor League fans consider Value and Added Entertainment to be more important than collegiate fans. Collegiate fans considered Baseball and Community to be more important than did Minor League fans (Bernthal and Graham, 2003). Two other factors that could influence attendance at a sporting event include team identification and level of sport fandom. Team identification is the extent to which a fan feels a psychological connection to a team and the team's performances are viewed as self-relevant (Branscombe and Wann, 1991). A number of positive outcomes have been associated with high levels of team identification, including feelings of self worth and life satisfaction (Branscombe and Wann, 1991), high self-esteem and social well-being (Lanter and Blackburn, 2004), and low levels of loneliness, depression, and other negative emotions (Wann, Dimmock, and Grove, 2003). In fact, Wann (2006) proposed the Team Identification Social Psychological Health Model as an explanation for the positive relationship between identification with a local sport team and social psychological health. In addition to, or perhaps because of, the psychological benefits they receive from identification, people who are highly identified with a specific team are more likely to attend sporting contests that involve that specific team than people with low levels of identification (Wann, Bayens, and Driver, 2004), regardless whether the game location was home or away (Wann, Roberts, and Tindall, 1999). A second factor that could influence game attendance is sport fandom. People who describe themselves as fans of a given sport will be more likely to attend events in that sport than people who are not fans. While the extant research on motivation to attend sporting events examines reasons people attend different types of sport, it does not address reasons people attend different levels of the same sport. For example, it is quite conceivable the fans attend children’s sporting events (e.g., Little League baseball games) for different reasons than they attend professional games (e.g., Major League Baseball games). This study was designed to begin an examination of fan motivations for attending games at different levels of the same sport. The research was designed to answer the question, “What motivates fans to attend sporting events of different levels?” There were two hypotheses for the current research. Hypothesis 1: It was expected that there would be different motivation profiles for fans attending different levels of sporting events. Hypothesis 2: It was expected that fans attending lower level sporting events would report lower identification with the teams than fans attending higher level sporting events.

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METHOD Participants The sample consisted of 224 fans in the mid-south who attended five different baseball games at different levels. Of the 224 participants 122 were male and 102 were female. The sample was divided between five different levels of baseball. The sample consisted of 46 fans from a T-Ball game, 40 fans from a Little League baseball game, 46 fans from a High School baseball game, 48 fans from a College baseball game, and 44 fans from a Minor League baseball game. The sample contained 199 Caucasian participants, 14 African American participants, 4 Hispanic participants, 2 Native American participants, 2 Biracial/multiracial participants, and 2 participants that classified themselves as other for ethnicity. The demographic characteristics of participants attending the different level of baseball games are presented in Table 1. Table 1. Demographics by Level Motive

T-Ball

Little League

High School

College

Minor League

Age

43.50

39.18

45.98

49.27

41.05

Financial Status

3.83

3.23

4.10

3.91

3.54

Gender (%Male)

69.6%

70.0%

54.3%

27.1%

54.5%

Education (BA or less) 67.4%

89.7%

89.1%

64.6%

93.0%

Ethnicity (Caucasian) 78.3%

80%

95.7%

100.0%

88.6%

Notes: For Age the mean age is reported. For Financial Status the mean status is reported. Financial Status ranged from 1 (Very Poor, Not Enough to Get By) to 6 (Extremely Well To Do). For Gender the percent male and percent female is reported. For Education the percent with a Bachelors Degree or less is reported. For Ethnicity the percent that were Caucasian is reported.

Measures Demographics. The demographics section consisted of 6 items to identify the age, gender, ethnicity, education level, and financial status of participants. Motivation. The Sport Fan Motivation Scale-Revised (SFMS-R; Bilyeu and Wann, 2002) consists of 33 items that assess 11 different fan motives for attending sporting events: escape, economic, eustress, self-esteem, group affiliation, entertainment, family, aesthetic, similarity, representation, and support/perceived greater equality. Each subscale contains three items, with the exception of the family, similarity and representation subscales, which contain two items and the support subscale which contains six items. An example of an item from the SFMS-R is, “I like the stimulation I get from watching sports” The response options range

Motivational Profiles of Sports Fans Attending Different Levels of Baseball Games 167 from 1 (low motivation) to 8 (high motivation). The items on each subscale were summed and the total was divided by the number of items in the subscale. High scores on a subscale indicate high motivational level for that particular subscale (Wann, 1995). The SFMS-R is a reliable instrument, with Cronbach reliability coefficients for the 11 factors/subscales ranging from .61 to .94 for all the subscales. Team Identification. The Sport Spectator Identification Scale (SSIS; Wann and Branscombe, 1993) contains seven items that assess the level of identification with a particular team; an additional item assesses which team the fan is supporting at the game. The responses range from 1 (not important or low level of identification) to 8 (very important or high level of identification). An example of an item is “How important to you is it that this team wins?” The items were summed to create a total score, and higher total scores indicate a high level of identification with a particular team. The SSIS is a valid and reliable instrument with an internal consistency of .91 and it related to other relevant variables as expected (Wann and Branscombe, 1993). Fandom. The Sports Fandom Questionnaire (SFQ; Wann, 2002) contains five items that assess fans identification with his or her role as a sport fan. The responses range from 1 (strongly disagree or low level of role identification) to 8 (strongly agree or high level of role identification). An example of an item is “My life would be less enjoyable if I were not allowed to follow sports.” The five item scores were summed to create a total score. Higher total scores indicate higher levels of fandom. The SFQ is a valid and reliable instrument with internal consistency of .96 and .94 test-retest reliability (Wann, 2002).

Procedure Permission from the baseball team or league was obtained through a phone contact or email before recruiting participants. The participants were recruited by asking fans over the age of 18 attending selected sporting events to participate in the research study. After providing verbal consent, participants were asked to complete a questionnaire packet. Within the packet were the demographics section, the SFMS, SSIS, and the SFQ. The participants completed the packet in one session that took 10 to 15 minutes.

RESULTS Preliminary Analysis Prior to examining the impact of different levels of a sport on motivational patterns preliminary analyses were completed. First, the five items of the SFQ were summed to create a single index of level of fandom for the participants. Next, the seven items of the SSIS were summed to create a single index of level of identification with the participants chosen team. Items for each of the SFMS-R motivation subscales were summed to create indices of motivation. Cronbach’s Alpha was conducted on the three measures and all were found to have acceptable internal consistency. Cronbach’s Alpha for the SFQ was .93. Cronbach’s Alpha for the SSIS was .87. Cronbach’s Alpha for the SFMS-R Aesthetic subscale was .78.

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Cronbach’s Alpha for the SFMS-R Group Affiliation subscale was .67. Cronbach’s Alpha for the SFMS-R Economic subscale was .86. Cronbach’s Alpha for the SFMS-R Representation subscale was .87. Cronbach’s Alpha for the SFMS-R Escape subscale was .93. Cronbach’s Alpha for the SFMS-R Similarity subscale was .81. Cronbach’s Alpha for the SFMS-R Selfesteem subscale was .67. Cronbach’s Alpha for the SFMS-R Support/Equality subscale was .87. Cronbach’s Alpha for the SFMS-R Family subscale was .57. Cronbach’s Alpha for the SFMS-R Eustress subscale was .82. Table 2. Means (and Standard Deviations) for the Motivation Subscales by Level Motive

T-Ball

Little League

High School

College

Minor League

AES

3.55a (1.67)

3.90ac (1.83)

4.91bc (2.02)

4.82bc (1.89)

4.12ac (1.72)

GA

4.02a (1.63)

4.66ac (1.88)

5.08bc (1.74)

5.04bc (1.86)

4.68ac (1.43)

ECO

1.21abc 0.69)

1.81ab (1.77)

1.29abc 0.86)

1.19ac (0.55)

1.40abc (0.96)

REP

2.66a (2.08)

3.68ab (2.54)

4.33ab (2.66)

3.24b (2.24)

2.95ab (2.26)

ESC

2.14a (1.53)

3.28ab (2.29)

2.96ab (1.99)

3.94b (2.20)

3.23ab (2.05)

SIM

2.27a (1.58)

3.53bc (2.19)

3.84bc (2.27)

3.95b (2.07)

2.65ac (1.93)

S-E

2.51a (1.34)

4.04bcd (1.87)

3.60bcd 1.72)

4.40bc (1.60)

3.10ad (1.64)

ENT

5.47a (2.04)

5.90ab (2.04)

6.32ab (1.38)

6.90b (1.16)

6.23ab (1.73)

S/E

2.68a (1.59)

3.82a (2.14)

3.64a (1.98)

3.75a (1.95)

2.87a (1.69)

FAM

4.38a (2.19)

5.59ab (1.93)

5.77b (1.80)

4.64ab (2.21)

5.31ab (2.10)

4.46bc (2.10)

5.17bc (1.92)

EUS

3.00a (1.56)

4.63bc (2.17)

4.16ac (2.26)

Notes: Standard deviations appear in parentheses below each mean. SFMS-R subscale scores range from 1 (low motivation) to 8 (high motivation). AES = aesthetic, G A = group affiliation, ECO = economic, REP = representation, ESC = escape, SIM = similarity, S-E = self-esteem, ENT = entertainment, S/E = support/equality, FAM = family, and EUS = eustress. Means with different superscripts are significantly different at the p < .05 level.

Motivational Patterns Comparisons across different levels. The first set of examinations involved a Multivariate Analysis of Variance (MANOVA) in which the levels served as the grouping variables and motivation subscale scores were employed as the multiple dependent measures. Means and

Motivational Profiles of Sports Fans Attending Different Levels of Baseball Games 169 standard deviations for SFMS-R subscales by levels appear in Table 2. The MANOVA yielded a significant multivariate effect, Wilks’ Lambda F (10, 224) = 2.78, p < .001, η2 = .17. Since the MANOVA was significant, a series of univariate one-way Analyses of Variance (ANOVAs) was completed using each motivation subscale as the dependent variable. These tests were followed up by Scheffe post hoc tests to determine which levels differed from each other. The univariate one-way ANOVA on the aesthetic subscale resulted in a significant between-subjects effect, F (4, 213) = 4.51, p = .002, η2 = .09. The post hoc analysis indicated that aesthetic motivation subscale scores were significantly higher for the high school (p = .007) and college (p = .012) level than the T-Ball level. The univariate one-way ANOVA on the group affiliation motivation subscale resulted in a significant between-subjects effect, F (4, 218) = 2.80, p = .027, η2= .05. Post hoc analysis indicated that group affiliation subscale scores were significantly higher for the High School (p = .04) and College (p = .05) level than for the T-Ball level. The univariate one-way ANOVA on the economic subscale resulted in a significant between-subjects effect, F (4, 219) = 2.57, p = .039, η2 = .05. Post hoc analysis indicated that economic subscale scores were significantly lower for College level (p = .05) than for the Little League level. The univariate one-way ANOVA on the representation subscale resulted in a significant between-subjects effect, F (4, 221) = 3.46, p = .009, η2 = .06. Post hoc analysis indicated that representation subscale scores were significantly higher for the College level (p = .009) than the T-Ball level. The univariate one-way ANOVA on the escape subscale resulted in a significant between-subjects effect, F (4, 214) = 3.46, p = .009, η2 = .09. Post hoc analysis indicated that escape subscale scores were significantly higher for the College level (p < .001) than the TBall level. The univariate one-way ANOVA on the similarity subscale resulted in a significant between-subjects effect, F (4, 220) = 3.46, p = .009, η2 = .11. Post hoc analysis indicated that Similarity subscale scores were significantly higher for the Little League (p = .05), High School (p = .003), and College (p = .001) level than the T-Ball level. Post hoc analysis also indicated that Similarity subscale scores were significantly higher for the Minor League level (p = .025) than the College level. The univariate one-way ANOVA on the self esteem subscale resulted in a significant between-subjects effect, F (4, 216) = 3.46, p = .009, η2 = .18. Post hoc analysis indicated that self esteem subscale scores were significantly higher for the Little League (p < .001), High School (p = .02), and College (p < .001) level than the T-Ball level. Post hoc analysis also indicated that self esteem subscale scores were significantly higher for the Minor League level than the College level. The univariate one-way ANOVA on the entertainment subscale resulted in a significant between-subjects effect, F (4, 217) = 3.46, p = .009, η2 = .08. Post hoc analysis indicated that entertainment subscale scores were significantly higher for the College level (p = .001) than the T-Ball level. One-way ANOVA analysis on the support/equality subscale resulted in a significant between-subjects effect, F (4, 216) = 3.46, p = .009, η2 = .07. Post hoc analysis indicated that support/equality subscale scores were lower for the T-Ball level than all the other levels, although none were statistically significant.

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The univariate one-way ANOVA on the family subscale resulted in a significant between-subjects effect, F (4, 214) = 3.46, p = .009, η2 = .07. Post hoc analysis indicated that family subscale scores were significantly higher for the High School level (p = .018) than the T-Ball level. The univariate one-way ANOVA on the eustress subscale resulted in a significant between-subjects effect, F (4, 217) = 3.46, p = .009, η2 = .13. Post hoc analysis indicated that eustress subscale scores were significantly lower for the T-Ball level than all the other levels (all ps < .05). A one-way within-subject ANOVA was conducted on each motive by level. The univariate one-way ANOVA for the T-Ball level resulted in a significant within-subjects effect, F (10, 220) = 32.54, p < .001. The analysis for T-Ball level indicated that all motives were different from one another. The highest motive for fans at the T-Ball level games was the Entertainment motive as shown in Figure 1. The lowest motive for fans at the T-Ball level game was the Economic motive. The repeated measure within-subjects ANOVA for the Little League level resulted in a significant within-subjects effect, F (10, 360) = 24.81, p < .001. The analysis for Little League level indicated that all motives were different from one another. The highest motive for fans at the Little League level games was the Entertainment motive as shown in Figure 1. The lowest motive for fans at the Little League level game was the Economic motive. The repeated measure within-subjects ANOVA for the High School level resulted in a significant within-subjects effect, F (10, 410) = 38.73, p < .001. The analysis for High School level indicated that all motives were different from one another. The highest motive for fans at the High School level games was the Entertainment motive as shown in Figure 1. The lowest motive for fans at the High School level game was the Economic motive. 8 7 6 5 4 3 2 1

T-Ball

Little League

High School

S EU

M FA

S /E

T EN

S -E

S IM

C ES

P RE

O EC

GA

AE

S

0

College

Figure 1. Means for the Motivation Subscales by Level. Notes: AES = Aesthetic Motivation, G A = Group Affiliation Motivation, ECO = Economic Motivation, REP = Representation Motivation, ESC = Escape Motivation, SIM = Similarity Motivation, S-E = Self-Esteem Motivation, ENT = Entertainment Motivation, S/E = Support/Equality Motivation, FAM = Family Motivation, and EUS = Eustress Motivation.

The repeated measure within-subjects ANOVA for the College level resulted in a significant within-subjects effect, F (10, 430) = 34.09, p < .001. The analysis for College level indicated that all motives were different from one another. The highest motive for fans

Motivational Profiles of Sports Fans Attending Different Levels of Baseball Games 171 at the College level games was the Entertainment motive as shown in Figure 1. The lowest motive for fans at the College level game was the Economic motive. The repeated measure within-subjects ANOVA for the Minor League level resulted in a significant within-subjects effect, F (10, 400) = 39.51, p < .001. The analysis for Minor League level indicated that all motives were different from one another. The highest motive for fans at the Minor League level games was the Entertainment motive as shown in Figure 1. The lowest motive for fans at the Minor League level game was the Economic motive. A MANOVA was conducted to determine if there were any differences between levels and resulted in F (4, 202) = 5.94, p < .001, η2 = .10. This test was followed up by Scheffe’s post hoc test to determine which levels differed from one another. Post hoc analysis also indicated that the T-Ball level is significantly different from the Little League, High School, and College levels but not the Minor League level (all ps < .05). The Little League, High School, College, and Minor League levels were not statistically different from one another.

Identification and Fandom Two univariate one-way ANOVAs were conducted for the SSIS and the SFQ. These tests were followed up by Scheffe post hoc tests to determine which levels differed from each other. The results of these analyses are found in Table 3. The univariate one-way ANOVA on the SSIS resulted in a significant between-subjects effect, F (4, 215) = 16.02, p < .001, η2 = .06. The univariate one-way ANOVA on the post hoc analysis indicated that the SSIS scores were significantly higher for the High School, and College levels than the T-Ball level (all ps < .001). Post hoc analysis also indicated that the SSIS score for the College level was significantly higher than the Little League level andthe Minor League level (p < .001).

DISCUSSION The current study was designed to examine fan motivation for attending different levels of the same sport. There were two specific hypotheses under study. First, it was expected that there would be different motivation profiles for fans attending different levels of sporting events. Second, it was expected that fans attending lower level sporting events would report lower identification with the teams than fans attending higher level sporting events. The following results partially supported each hypothesis. The first hypothesis was partially supported in that participants from the T-Ball and Minor League levels did not score highly on any of the motivation subscales. Overall, participants from the T-Ball level scored lower on all motives than the other levels. This could be due to fans at T-Ball games not being very invested in being a fan of the team. The SFQ mean, shown in Table 3, was lower for the fans at the T-Ball level than the other levels, which indicates that participants at the T-Ball games do not perceive themselves as baseball fans. The SSIS mean, shown in Table 3, was lower for T-Ball than all levels except the Minor League level, which indicates that people attending T-Ball and Minor League games are not highly identified with any particular T-Ball team.

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Amber L. Rickard, Frederick G. Grieve and W. Pitt Derryberry Table 3. Means and Standard Deviations for the SSIS and SFQ by level Level

SSIS Total

SFQ Total

T-Ball

27.98 (10.43)

16.65 (9.29)

Little League

36.92 (8.03)

21.84 (9.47)

High School

39.98 (9.35)

27.16 (10.02)

College

37.84 (12.95)

30.37 (8.73)

Minor League

26.36 (12.32)

22.48 (10.64)

Notes: Standard deviations appear in parentheses below each mean. SSIS = Sport Spectator Identification Scale responses range from 1 (not important or low level of identification) to 8 (very important or high level of identification). The total SSIS score ranges from 7 to 56. SFQ = Sports Fandom Questionnaire responses range from 1 (strongly disagree or low level of role identification) to 8 (strongly agree or high level of role identification). The total SFQ score ranges from 5 to 40.

An analysis of the different levels revealed that the participants at the High School, Little League, and College levels scored higher than the other levels on the motivation subscales. It is possible that fans at High School, Little League, and College level games are more invested in being a fan of the team. The SFQ mean, shown in Table 3, was higher for the High School and College levels than the other levels, which indicates that participants at the High School and College are invested in perceiving themselves as baseball fans. The SSIS mean, shown in Table 3, was higher for Little League, High School, and College levels than the Minor League and T-Ball levels, which indicates that people attending Little League, High School, and College games are highly identified with one of the teams playing in the game. The second hypothesis was partially supported. An analysis of the different levels level of identification, see Table 2, revealed that fans attending High School games had higher identification with the team than other levels. College and Little League level fans also had a high level of identification with their teams. Fans attending Minor League and T-Ball games had the lowest level of identification with the team than other levels. The results show that Little League, High School, and College baseball fans are similar in their motivational patterns and identification with being a baseball fan and a fan of a particular team. Also shown by the results is that T-Ball and Minor League Fans are very similar in their motivational patterns and identification with being a baseball fan and a fan of a particular team. It does not appear that the type of baseball played at each of these levels is similar—Minor League baseball differs in both quality and quantity from T-Ball baseball. However, it appears as though the importance that fans place on identification with the team and importance of attending games is similar between the two. Future research should examine why these similarities in identification and motivation exist. The results show that, for all levels, statistically significant differences existed for the motives on the SFMS-R. However, the overall pattern of results was very similar. For all the levels of baseball, entertainment was the strongest motive and economic was the weakest

Motivational Profiles of Sports Fans Attending Different Levels of Baseball Games 173 motive for attendance. This indicates that the sport itself draws people to view it for specific reasons. When the current research is compared to the Wann et al. (in press) findings for professional baseball, a similar pattern emerges. However, the pattern is not identical. The results of the current study indicate a much higher mean for the Family motivation than Wann et al. Such a difference could be because Wann et al. examined fans of Major League Baseball while the current study only examined up through the Minor League level. Thus, people could be motivated to watch Major League Baseball baseball for different reasons than Minor League baseball, just as they attend Minor League and College level baseball games for different reasons (Bernthal and Graham, 2003). Additionally, the difference could also be due to where the data was collected. The present study collected the data from fans who were actually in attendance at a baseball game, while Wann et al. collected data from fans away from the baseball park, and asked them why they usually attend games. Collecting data at the game could yield more valid results, because it is easier for the fans to note why they are attending a game rather than recall why they usually go to games once they are away from them. The present results also parallel the findings of other researchers. Similar to the present findings, James and Ross (2004) found that consumers of men’s baseball rated the Entertainment motive higher than other motives for following their respective teams. McDonald et al. (2002) found that the Self-Esteem motive was the lowest reported motive across all the sports. The current results also indicate that the Self-Esteem motive is the lowest motive. In terms of identification, the results of the current study indicate that team identification is stronger for fans attending lower level baseball games than for those attending higher level baseball games. This stronger connection to the team for lower levels may be due to proximity to the team; that is most fans attending lower level games were more likely to have a close friend or family member who is on the team. With the higher levels, fans may not feel as connected to the teams because they do not personally know the players. These results are limited because the sample did not include people attending a Major League Baseball game, where identification with the team could be higher. Still, these findings hold implications in regards to Wann’s (2006) Team IdentificationSocial Psychological Health Model, which shows that high identification with a team increases a person’s social psychological health. According to the model, social psychological health increases as a result of the social connections that people make because of their identification with a local team. However, to date, this model has only been tested by examining identification with college or professional teams. Based on these results, it is expected that the Team Identification—Social Psychological Health Model should also work with lower level teams. While it is not likely that people will encounter enough others identified with a Little League team, it is likely that this model will work with identification with high school teams. While the data presented furthers our understanding of the motivational patterns found among fans at different levels of a sport, there is still much to be discovered about sport fan motivation. For instance, the current research only addressed fan motivation at different levels of baseball; fans of other types of sports could have different patterns of motivation. In addition, the participants for the study were drawn from those over the age of 18 in the mid-

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south United States; fans with different demographic characteristics may have different motives for attending sporting events. Table 4. Means (and Standard Deviations) by Gender for Motives, Team Identification, and Fandom Motives

Men

Women

F

P

Eta2

AES

3.82 (1.82)

4.96 (1.75)

19.53

<.001

.092

GA

4.56 (1.65)

4.88 (1.75)

1.69

.195

.009

ECO

1.34 (1.07)

1.43 (1.10)

.319

.573

.002

REP

3.17 (2.40)

3.50 (2.39)

.920

.339

.005

ESC

2.72 (1.92)

3.68 (2.21)

10.40

.001

.051

SIM

2.72 (2.02)

3.81 (2.11)

13.59

<.001

.066

S-E

3.31 (1.81)

3.85 (1.64)

4.74

.031

.024

ENT

5.88 (1.84)

6.64 (1.26)

10.84

.001

.053

S/E

3.12 (1.84)

3.54 (1.88)

2.40

.123

.012

FAM

5.48 (1.98)

4.86 (2.13)

4.45

.036

.023

EUS

3.88 (2.10)

4.32 (1.99)

10.61

.001

.052

FANtot

20.98 (10.23)

27.45 (9.72)

20.24

<.001

.095

Idtot

33.21 (11.66)

33.47 (12.30)

.024

.878

.000

Notes: Standard deviations appear in parentheses next to each mean AES = aesthetic, G A = group affiliation, ECO = economic, REP = representation, ESC = escape, SIM = similarity, S-E = selfesteem, ENT = entertainment, S/E = support/equality, FAM = family, and EUS = eustress, FANtot = fandom total, Idtot = team identification total.

The results of the current study only partially support the hypotheses. All the levels had differences within individual motives. However, the motivational patterns were similar in that the fans at all of the levels ranked Entertainment as their highest motive and Economic as their lowest motive. These similarities in levels show that baseball fans do not need to go to higher level games to obtain the entertainment that the results show fans desire. Fans can go to local or youth games and have the same entertainment without the cost or distance. In fact, the similarities found in this study could at least partially explain the popularity of youth

Motivational Profiles of Sports Fans Attending Different Levels of Baseball Games 175 sports, such as little league baseball, and high school sports with people who do not have children participating. In conclusion, sport fans of all levels are highly motivated to attend baseball games for the entertainment value as well as to spend time with their friends and family. The sport itself seems to draw people to attend games with other individual factors also contributing to attendance. Fans attend baseball games for enjoyment of the game regardless of the teams they support. Fans may be in support of a particular team but, regardless of the game outcome the entertainment value of the game is not lost.

REFERENCES Bernthal, M. J., and Graham, P. J. (2003). The effects of sport setting on fan attendance motivation: The case of Minor League vs. collegiate baseball. Journal of Sport Behavior, 26, 223-240. Bilyeu, J. K., and Wann, D. L. (2002). An investigation of racial differences in sport fan motivation. International Sports Journal, 6, 93-106. Branscombe, N. R., and Wann, D. L. (1991). The positive social and self concept consequences of sports team identification. Journal of Sport and Social Issues, 15, 115127. James, J. D., and Ross, S. D. (2004). Comparing sport consumer motivations across multiple sports. Sport Marketing Quarterly, 13, 17-25. Lanter, J. R., and Blackburn, J. Z. (2004, September). The championship effect on college students’ identification and university affiliation. Paper presented at the annual meeting of the Association for the Advancement of Applied Sport Psychology, Minneapolis, MN. McDonald, M. A., Milne, G. R., and Hong, J. (2002). Motivational factors for evaluating sport spectator and participant markets. Sport Marketing Quarterly, 11, 100-113. Mehus, I. (2005). Sociability and excitement motives of spectators attending entertainment sports events: Spectators of soccer and ski-jumping. Journal of Sport Behavior, 28, 333350. Wann, D. L. (1995). Preliminary validation of the sport fan motivation scale. Journal of Sport and Social Issues, 19, 377-395. Wann, D. L. (2002). Preliminary validation of a measure for assessing identification as a sport fan: The sport fandom questionnaire. International Journal of Sport Management, 3, 103115. Wann, D. L. (2006). Understanding the positive social psychological benefits of sport team identification: The Team Identification-Social Psychological Health Model. Group Dynamics: Theory, Research, and Practice, 10, 272-296. Wann, D., Bayens, C., and Driver, A. (2004). Likelihood of attending a sporting event as a function of ticket scarcity and team identification. Sport Marketing Quarterly, 13, 209215. Wann, D. L., and Branscombe, N. R. (1993). Sports fans: Measuring degree of identification with the team. International Journal of Sport Psychology, 24, 1-17.

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Wann, D. L., Dimmock, J. A., and Grove, J. R. (2003). Generalizing the Team Identification – Psychological Health Model to a Different Sport and Culture: The Case of Australian Rules Football. Group Dynamics: Theory, Research, and Practice, 7, 289-296. Wann, D. L., Grieve, F. G., Zapalac, R. K., and Pease, D. G. (in press). The impact of target sport on the motivational profiles of sport fans. Contemporary Athletics. Wann, D., Roberts, A., and Tindall, J. (1999). Role of team performance, team identification, and self-esteem in sport spectators’ game preferences. Perceptual and Motor Skills, 89, 945-450.

Contemporary Athletics Compendium, Volume 3 Editor: James H. Humphrey

ISBN: 978-1-60741-561-9 © 2009 Nova Science Publishers, Inc.

Chapter 16

CHARACTERISTICS OF SUCCESS IN MEN’S FOOTBALL AND MEN’S BASKETBALL AT THE DIVISION I LEVEL Shane L. Hudson∗ Texas A&M University, College Station, Texas, USA

ABSTRACT The push for student-athletes to graduate college has never been greater. Studentathletes are under more pressure to not only complete their degree but, to do it in a timely manner under NCAA guidelines. The intent of this study was to determine if men’s football and men’s basketball coaches at the university or college level utilize an assessment instrument when recruiting and evaluating potential student-athletes. Specifically studied through interviews were the characteristics that these coaches look for in successful and unsuccessful student-athletes, how they currently collect information during the recruitment period and whether collecting data on student-athletes is of importance or not. The population for this study consisted of current Division IA men’s football and men’s basketball coaches in the Big 12 Conference. The study helps to define through research and development an assessment instrument to more effectively define the needs of student-athletes prior to entering universities.

Through its first ten years, the Big 12 Conference has claimed 28 team and 310 individual NCAA titles and currently has over 4,600 student-athletes in 21 sports. Due to their athletic accomplishments and size the Big 12 Conference was used to determine whether coaches in men’s basketball and football utilize an assessment instrument in recruiting that helps define the character and potential success of the student-athlete. The ability to predict success is important because of statistics such as those put forward by the Knight Foundation Commission on Intercollegiate Athletics. According to their combined reports (1999), ∗

Phone: (979) 845-8832; FAX: (979) 862-6489; Email: [email protected]

178

Shane L. Hudson Nearly a third of present and former professional football players responding to a survey near the end of the decade said they accepted illicit payments while in college, and more than half said they saw nothing wrong with the practice. Another survey showed that among 100 big-time schools, 35 had graduation rates under 20 percent for their basketball players and 14 had the same low rate for their football players. (p. 4)

Today student-athletes are under more pressure to stay in school and complete their degrees and coaches are under more pressure to recruit student-athletes who will stay in school and out of trouble.

In the Classroom According to The NCAA News (2005), the philosophy of the NCAA is that colleges and universities should educate and graduate the student-athletes they recruit to their campuses. The NCAA has raised the stakes through aggressive legislation for recruiting student-athletes who are better prepared for collegiate life. Unfortunately there has been more talk than research on predicting the success of student-athletes (Sedlacek and Adams-Gaston, 1992). Crouse and Trusheim (1988) argued that high-school grades are better than the SAT at predicting college performance and that, while the SAT improves prediction significantly over high-school grades alone, the improvement is too small to be worth the effort (Baron and Norman, 1992). Without the ability to predict or assess student-athletes through standardized test scores, high school or junior college grades, universities must find alternative methods that best predict success from a holistic perspective.

Off the Field and Outside the Classroom One cannot argue that athletes at colleges and universities are often in the news for scandalous, criminal, disruptive and controversial issues. Greg Auman (2005) begins an article, “With scandals alleging criminal behavior at Colorado, Baylor and elsewhere focusing attention on the athletes schools recruit, universities are re-evaluating how they screen for character” (St. Petersburg Times online, 1). In 2006 there was the side-line clearing brawl between Miami and Florida International where Tim Reynolds from the Associated Press stated that this “was the third on-field incident in Miami’s past seven games” (15). Officials from Miami, FIU, the Sun Belt and Atlantic conferences then issued 31 one-game suspensions. This trend is not new. In the 1980’s a commission on intercollegiate athletics was formed so as to reform the current state of college athletics. According to the President of this commission, now called the Knight Commission on Intercollegiate Athletics, from 19881998, Creed C. Black stated that “In 1989, as a decade of highly visible scandals in college sports drew to a close, the trustees of the John S. and James L. Knight Foundation (then known as Knight Foundation) were concerned that athletics abuses threatened the very integrity of higher education” (1999, p. 2). Since then this foundation has done a positive job of correctly reporting the current state of college athletics, both the good and the bad.

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PURPOSE OF THE STUDY The intent of this study was to determine if men’s football and men’s basketball coaches at the university or college level utilize an assessment instrument when recruiting and evaluating potential student-athletes. Specifically studied through interviews were the characteristics that these coaches look for in successful and unsuccessful student-athletes, how they currently collect information during the recruitment period and the importance of collecting data on student-athletes. The study helps to define through research and development an assessment instrument to more effectively define the needs of studentathletes prior to entering universities and coaches will have additional data for meeting the needs of student-athletes. Coaches and staff members that recruit at the university level should look at a multilevel performance model such as Swanson’s Performance Diagnosis Matrix. Multilevel performance models were developed to reduce the “complexity of organizational systems to a more manageable form by creating taxonomic models of key performance variables” (Swanson and Holton, 2001, p. 188). This model in particular focuses on the organization, the process, and the individual as performance levels. “In order to achieve organization and individual performance, it is critical that all three performance levels are aligned” (Rummler, 1996, p. 29). The performance variables for each level are goals, system design, capacity, motivation and expertise. “These performance variables, matrixed with the levels of performance - organization, process, and/or individual - provide a powerful perspective in diagnosing performance” (Swanson and Holton, 2001, p. 194). The diagnosis of successful performance at each level can be determined by the answers to particular questions, which therefore can be used by institutions who seek to develop and encourage a performance based program. In as much, “the questions presented in the performance variable matrix help the diagnostician sort out the performance overlaps and disconnects” (Swanson and Holton, 2001, p. 194). For example, based on how a student-athlete answers these questions an organization can determine whether that particular student-athlete is the right fit for that particular institution, whether they can thrive and succeed, whether they have the drive to obtain a degree, and whether they have the motivation to succeed on the field. Therefore, identifying whether a recruit has those characteristics of success or performance variables prior to a university’s investment in him or her could prove to be of great value.

METHOD The goal in the data collection was to conduct unstructured interviews with the head coaches of each of the Big 12 teams to find out what they feel are predictors of success in student-athletes. Because the information is not directly observable, interviews were used to collect data. As Patton (2002) points out, “open-ended questions and probes yield in-depth responses about people’s experiences, perceptions, opinions, feelings, and knowledge. Data consists of verbatim quotations with sufficient context to be interpretable” (p. 4). A pilot study was conducted in July 2006 to help work out any possible problems with questions as well as method. The focus at this time was on contacting three coaches, not head coaches. Each coach conveyed the importance of the research and stated they were anxious to

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Shane L. Hudson

hear the results. As a condition of entry a letter of introduction was sent prior to asking for an interview. In as much, one of the pilot study coaches also suggested that the letter express an interest in an interview for research purposes. This coach was then used as a reference. The letter was simple, understandable and most importantly let the coaches know that there was something “in it for them.” Just as Erlandson et al. (1993) stated, “the accomplishment of successful entry also partially revolves around the field researcher’s ability to explain his interests in terms that make sense to the members of the setting” (p. 72). The letter also had a former Division IA head football coach from the pilot study who endorsed the study and left his contact information if anyone felt the need to contact him. The letters were mailed to each head coaches’ office on July 25th 2006. Out of the 24 letters that were mailed, two responses were logged the following week. During the next month there were about two responses per week with the total sample response ending up at 9. A code system was used in order of responses, R 1-9. The R is coded for “respondent” and each one received a number in the order in which they were interviewed. Therefore, the first coach interviewed is coded R1 while the last coach interviewed is coded R9. The phone interviews ranged from July 14th to September 18th and lasted anywhere from twelve minutes to thirty five minutes in length. Most head coaches referred the interviews to their assistant coaches whom the head coach trusted to provide accurate information therefore only on head coach was interviewed. The genders of the coaches interviewed were all male. Each interview took an extraordinary amount of time to coordinate due to the busy occupations of Division I A coaches. The data collection was started in early fall when Division I A football have two-a-day camps in preparation for the upcoming football season. Basketball was out of season and at first glance should have made contact less time consuming on their part. Rarely did the head coaches call personally; that happened only twice during the data collection process. The first head coach had his secretary call and setup an appointment 2 weeks in advance. The interview questions were: 1. What are the characteristics of a successful student-athlete (On and off the playing field)? 2. What are the characteristics of an unsuccessful student-athlete (On and off the playing field)? 3. How do you collect information regarding student-athletes prior to the studentathletes enrollment? Describe your current process? 4. Discuss the current issues involved in assessing student-athletes prior to college enrollment? Understanding that data analysis is a messy and ambiguous process, emergent category designation was used to organize data into categories of ideas. These ideas were then formed into themes or constructs which illustrated what the coaches feel are predictors of studentathlete success. Consequently, a database was developed where topics, categories and statements moved around throughout the entire process. The ability to use thematic analysis appears to involve a number of underlying abilities, or competencies. One competency can be called pattern recognition. It is the ability to see patterns in seemingly random information (Swanson and Holton, 2001). Patton cites content analysis as an example of analyzing text (interview transcripts, diaries, or documents) rather

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than observation-based field notes. Patton goes on to say that “content analysis is used to refer to any qualitative data reduction and sense making effort that takes a volume of qualitative material and attempts to identify core consistencies and meanings” (Patton, 2002, p. 453). In as much, content analysis was used to establish patterns in the interview transcripts.

FINDINGS From analyzing the data the research found that the coaches utilize different methods of assessing successful student-athletes, most of which are not formalized, and that this is the toughest part and most important aspects of their jobs. The coaches tend to just go with a feeling or with their experience as to what would indicate success. Every respondent made a statement or comment about one of these overall findings. One respondent stated that “there was no specific process” (R7) while another stated “no process is used” (R2). Others said that they “try to collect data but it is very difficult to do” (R4) and another said that all they have is a “regular line of questions” (R5) that they ask. According to (R1), he stated that trying to find successful students “is the toughest job that they have”. Another respondent said “it is difficult to assess a high school student who is only 17 or 18 years old” (R9) while another coach stated that this process “is extremely important, everything ties into it” (R8). A coach said that they “will not offer until they get to know the kid, coach and family” (R3) while another coach said they “use a questionnaire to assess” student-athletes (R6). Therefore from the data analysis the research indicated a need for an assessment instrument with which coaches could utilize in assessing successful student-athletes.

Interview Question #1 The first interview question asked, “What are the characteristics of a successful studentathlete (On and off the playing field)?” From this question the data revealed that successful student-athletes, according to the nine respondents, are competitive, hard working, have some sort of family support, are leaders, take academics seriously, have character and are honest. “Driven to succeed in all areas. The best ones have a presence and are self motivated” (R8). Coaches, like student-athletes, are competitive and the research found that this specific characteristic, competitiveness, emerged from the data as most sought after by the coaches. Therefore, the first characteristic was identified as competitiveness. The constructs that support this theme were recognized as presence, self-motivation and determination. When this particular coach talked about success in all areas, he was referring to a student-athletes athletic ability, academic work, social life, and his character. When he talks about presence this refers to the student-athletes leadership abilities and how he handles himself on and off the field of play. Self-motivated athletes take care of business in the classroom, on the field and in the weight room. “Competitiveness drives them to do academic work better than they would if they weren’t in athletics” (R7). In the competitive world of Division I college athletics, coaches are just as concerned about academics as they are about athletics. This particular coach felt that the student-athletes competitive nature gives him the extra determination and resolve he needs to achieve his academic and athletic goals. Other coaches

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clearly made a statement regarding the athletic realm by stating “We are looking for a guy who wants to win championships and comes from a good program” (R3). This coach doesn’t appear to be as worried about how competitive this student is in the classroom and this aspect, academics, was not brought up during this part of the interview. Another respondent stated that he was looking for a young man who “hated to loose and loved to win” (R7). Again this was a direct reference to sports and being competitive. The competitive nature that studentathletes bring to their universities is for the most part a trait that is admired by their peers. Competitiveness is a quality that people look for in student-athletes and in people that are hired for jobs in almost every aspect of the highly competitive world in which we live. It is something that can be observed and has emerged as the most important aspect of success in student-athletes by the coaches contacted in the interview. The next characteristic that emerged was that of hard worker. This doesn’t seem too far removed from competitive but it emerged as a major theme under this research question. Furthermore, this characteristic is supported by the constructs of commitment, motivation and good work habits. This aspect seemed to be brought up regarding the student-athletes commitment to sport and everyday life. According to one respondent “players need to be motivated to work hard, and to play in the NBA is motivation” (R7). In order for athletic programs to be successful you need a “motivated athlete” (R2) and athletes with “good work habits” (R9). Without these essential elements coaches will likely struggle in the win and loss column and run the risk of being fired from their jobs before the student-athlete matriculates from a freshman to a senior. Research on the student-athlete begins in high school and the coaches are looking at every aspect of the meaning of work ethic. “We call the high school counselors and ask them if the student-athlete is in school everyday” (R6). From the coaches’ perspective if a student-athlete can not get out of bed and go to school everyday, this directly relates to their motivation to succeed both academically and on the field or court. The theme of family was important to the coaches interviewed and emerged from the research. It encompassed several constructs such as caring, having parents who are active in their lives, a good support system, stability, ability to adjust to adversity and having both a mother and father at home. This theme appeared to be a characteristic of successful studentathletes that some of the respondents were very passionate about. According to one respondent they are looking for “good guys that care about family and people. One or two parents with a solid household and are the parents active in the learning process” (R3)? When the parents have been active in the learning process the coaches feel that they will adjust easier to the pressures of making the grade academically at a major Division I A university. During the interviews the coaches made note of not only a strong presence of family but having both a mother and father at home. “We are looking for guys that have a support system in place with two parents” (R9). “Family is big. With mother and father, there is more emphasis on grades” (R6). Stability at home leads to students who adjust to adverse situations like the combination of academic rigor and intercollegiate athletics. It is up to the coaches to observe that environment when they visit the potential student-athletes home and when the student-athlete comes to campus for an official visit. Unfortunately, there is not enough time to observe the family in depth. The NCAA allows for limited contact with student-athletes during the recruiting process. The theme of leadership is an important element and the coaches interviewed recognized that this intangible is very important to the success of their student-athlete. During the interview process the coaches did not go into detail of what leadership meant to them.

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However, I did identify the constructs of politeness, good citizenship and social ability as supportive of this theme. One respondent simply stated that “leadership was important” (R1). Another respondent stated that he wanted his student-athletes to be “polite and good citizens” (R3). “Poor social aspects and poor leadership” (R3) are under the microscope during the recruiting process and serve as an indicator for non-selection. The academic aspect of a student-athlete was the next theme that emerged. Students who want to graduate and are responsible and who are a good fit with the university are the constructs that support this theme of academics. According to one respondent the studentathlete must be a “good fit with the university” (R1). This can encompass many variables and each coach will evaluate this differently at their institution. The academic fit would need to be a high priority. Another respondent stated that he is looking for student-athletes who “want to graduate and that it’s not just about football” (R3). This construct is in correlation with the previous construct of being a hard worker. There is a correlation to being a hard worker on the field and in academics. He went on to say that “this is something that coaches talk about all the time” (R3). Most coaches want the best of both worlds. Great athletes and great students in the sports of men’s football and men’s basketball exist but with, for example, 119 Division I university’s recruiting them; the competition to get these student-athletes on their campus is rigorous. Character rounded out the information that emerged from this question and was recognized as a theme with the constructs of commitment, character, trustworthiness, no substance abuse and stays out of trouble. I had anticipated that the construct of “character” would be the number one topic that emerged due to the word character in the question that was asked to the coaches. One school in particular covered a lot on character and it was apparent during our conversation that the coach and their program were deeply committed to this one aspect. When he spoke his voice raised and he went into detail so quick and furiously that it was difficult to cover it all. According to this respondent, “character comes first (R6). They want to know every detail about a student-athlete before they bring him to their school. When looking at document analysis I found that they (R6) have a questionnaire and ask questions such as: • • • •

Has he been suspended from school? Has he ever used drugs? Has he given a reason not to trust him? Would you worry if you allowed him to babysit your children?

If the answer is yes to 3 out of 4 questions then that is sufficient and they would not recruit or take him. Other respondents simply wanted to know if the student-athlete was “an honest person” (R2). According to this respondent the coaching staff had a mental checklist that they used during the recruitment of a student-athlete. A formal process or checklist of what the coaches are looking for in regard to this question only existed with two out of the nine coaching staff interviewed. The rest simply went off their instincts or a mental checklist they developed after spending years in the field evaluating talent.

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The constructs that support these characteristics or themes of a successful student-athlete are descriptive. The findings in the table show that there are several predictors that the coaches are looking for in prospective student-athletes.

Interview Question #2 When the coaches were asked the second question of “What are the characteristics of an unsuccessful student-athlete (On and off the playing field)?” they responded in much the same manner as in the previous question. According to (R3) “coaches are not looking for underachievers in the classroom, and personal life.” This can only mean one thing if you look at the NCAA graduation rates for men’s football and men’s basketball. Coaches are not looking for underachievers in the classroom but student-athletes who underachieve are attending college and are struggling. Therefore the five themes that developed with this question were; undisciplined, lack of character, no competitive nature, and unstable family. In the undisciplined theme, coaches found that student-athletes who were undisciplined in behavior at home or within their family were also that way when they came to college. During the recruiting process coaches will visit the home on a “home visit” of the studentathlete. “If there is lack of discipline in the family” (R1) that is observable to coaches during this visit and the student-athlete can hurt his chances of attending that school. The manner in which a student-athlete treats his mother or father is a measure of how he will respond to authority figures on campus. Consequently, the constructs which support the theme of undisciplined is lack of family, respect for authority and following rules and guidelines, along with poor attendance at school or class, and laziness. In as much, (R2) stated that he looked for student-athletes that were not “lazy.” This may seem easy to detect but he felt that one must spend a substantial time recruiting a student-athlete to clarify if this characteristic is factual. Coaches stated that they periodically talk to counselors and administrators regarding behavior in school. One respondent was concerned with “how they interact with their family and coach” (R6). Overall behavior and in some cases “not responding to authority” (R5) are factors during recruiting. Student-athletes often fail to realize how important their behavior is in the class room. A respondent defined undisciplined as “he doesn’t go to school” (R5) and went on to say that without high school you can’t go on to college. Life has parameters and boundaries and before a student-athlete enters a Division I institution coaches try to measure how well they have succeeded “following rules and guidelines” (R5). “Undisciplined studentathletes” (R2) often make it on to college campuses but many will not graduate due to the rigor and discipline required to complete a four year degree. Emerging as the next theme was a lack of character. The constructs that support this theme of lacking in character are running with the wrong crowd, lack of trust, and inconsistencies or gaps in academics or character. For most of the coaches who I interviewed felt that in the recruiting of student-athletes, poor character was important in the decision to bring this student to campus. (R1) stated that character was important and “running with the wrong crowd was a sign of poor character” (R1). Trust was another major issue in any form and one respondent stated that recruiters want to know “can he be trusted” (R3)? “Has the kid been in trouble” (R3) is another routine question coaches ask when recruiting studentathletes. “Is there a gap (academic or character) wise” (R3)? This same respondent went on to

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say that “gaps get exposed in college” and recruiters can not afford to make many mistakes of this nature. No competitive nature emerged from the interviews as the next theme, with constructs such as apathy, and intimidation. Overall the coaches made it apparent that student-athletes in the sport of men’s football and basketball need to be competitive due to the competitive nature of the sports. Under no circumstance can student-athletes be “intimidated by competition on and off the field or lacking in competitive nature” (R4). Therefore, “apathy” (R2) is not a trait desired in the highly competitive nature of these sports. An unstable family theme emerged as being a characteristic of an unsuccessful studentathlete. Coaches believe in a “good support system at home” (R4), thus providing an extra support system for coaches and administrators when the student-athlete arrives to campus. Therefore, the constructs in this theme were lack of role models and no foundation at home. Many factors play a role in the success of a student-athlete including a “foundation, with church as a factor and coaches as role models” (R6). This respondent stressed another particular aspect that was stressed is the “lack of role models in their lives” (R6). In as much, (R9) stated that they paid “close attention to how the student interacts with their family and coaches.” What was found in looking at the data through several methods is that there are particular characteristics that the coaches are looking for. In this question the research found several themes and constructs that are the opposite of what was stated in the previous question. When looking at the themes that were created between the two questions one can see that they are the opposites of each other (see Table 1). Out of the data given as characteristics of a successful student-athlete the themes that developed were ones of that student-athlete being competitive, having a supportive family structure and good character. While the themes that developed out of the data on characteristics of unsuccessful student-athletes were that of the student-athlete being undisciplined, lacking in character and having an unstable family. The other themes of a successful student-athlete; a hard worker, a leader, being honest, and supportive of academics, are also the opposite of the other theme of unsuccessful studentathletes, undisciplined. Table 1. Comparison of themes for characteristics of successful and unsuccessful student-athletes Successful Characteristics Competitive Hard Worker Family Support Leadership Support Academics Good Character Honesty

Unsuccessful Characteristics Undisciplined Lack of Character No Competitive Nature Unstable Family

Therefore the data from the first two questions show that coaches are looking for studentathletes who are competitive, have a strong family support, have good character and are disciplined or hard workers.

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Interview Question #3 In the third question, “how do you collect information regarding student-athletes prior to the student-athletes enrollment and what is your current process?” it was found that most of the coaches did not have a formal process. Therefore, the theme with this question focused on how the coaches currently collect data on recruits. What the research found is that data is collected through discussions and talking, observing and using a questionnaire or form. Talking about or discussing the student-athlete with “as many people as you can” (R2) came up quite often. The most valuable people to discuss an athletes’ potential for a program were coaches and high school counselors. Some respondents also liked to talk to anyone associated with the athlete to get a “random snapshot.” Therefore the constructs that support this aspect of data collection were talking to coaches, counselors at their high school and others such as family and friends. It was also found that talking to student-athletes was very hard and difficult to do. A respondent stated that he always “talked to the high school coach first” but that it can be tough seeing that there are “1200 high school football players in the state alone” (R1). Another one also stated that he focused on “talking to the high school coach” (R7). Others went on to state that it “goes beyond the high school coach, recruiters need to talk to people walking in the hall of the school” (R8). A coach stated that he has to “talk to as many people as he can” to learn about the student (R2). In essence, (R2) felt that really hearing from multiple sources about a student was a good thing. The next construct was the counselor. Several coaches mentioned the fact that “they have a regular line of questions for them” and they usually prove to be valuable sources (R5, R9). One coach said “they gather athletic information after the students’ sophomore year and try to get the students on campus as a junior” (R8). Due to NCAA rules, (R4) stated that they were limited in the amount of phone calls they can make to each student. According to one respondent, he felt that there was just not enough time and contact with the student-athletes and that he feels “we never really get to know them” (R5). He also went on to state that this process is so difficult because sometimes this student could be a “fifty, sixty, or seventy thousand dollar investment” (R5). This aspect correlates with the final construct of this process being difficult to do as studentathletes are being recruited earlier and earlier in their high school careers. The next construct for assessing student-athletes was student-athletes can be observed at camps, while at practice and on the playing field. I also noted that several of the coaches stated that one criterion they were observing was character. According to (R8), the camps “created a great avenue for athletic evaluation”. It was also a place that he stated the coach could look at participation and “gain new leads” to learn about that particular student-athlete. Another respondent stated that observation is “the way coaches stay informed, by watching a player for up to three years” at practices and even “AAU games” (R7). He went on to state that “he wanted to see how that student reacts to certain situations” (R7). The character of the student-athlete was mentioned throughout the answers of the coaches as it had been brought up as well in the prior questions. When asked how they collect information, two coaches referred to fact that they sometimes focus on character. “Character is so important. We look at drug issues and so forth” (R5). Another respondent stated that “character is extremely important as part of the process” (R8). The coaches identified three main methods of collecting information; talking with people, observing the student-athlete, and sending a questionnaire. As stated earlier, most of the respondents acknowledged that this was the hardest part of their jobs and that there was not a specific process used. Most of the coaches

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indicated they used their instincts to determine whether a student-athlete would be successful at their institution. In as much, most of the coaches indicated their method of gaining information on prospective student-athletes was through talking to people.

Interview Question #4 In the fourth question, “discuss the current issues involved in assessing student-athletes prior to college enrollment?” the coaches identified once again that this was a tough part of their job. “This is the toughest job that we have” stated (R1). With this question four issues emerged from the interviews with many categories to support them. The issues of effects of the Academic Progress Rate (APR), it being a tough job, early commitment factors and character emerged. With the issue of APR the categories that developed from the data were increased pressure, having to be more selective and academics, or in other words, can this student make it academically? “The APR is a real-time assessment of a team’s academic performance, which awards two points each term to scholarship student-athletes who meet academic-eligibility standards and who remain with the institution. A team’s APR is the total points earned by the team at a given time divided by the total points possible” (Brown, 2005, 5). One coach stated that “APR is putting more pressure on everyone” (R5). During the recruiting process coaches are asking “can we keep him in school?” This of course makes recruiting student-athletes much more difficult in that they do not want to make a mistake during recruiting. He also went on to say that he would never compromise the program because of APR (R5). An example would be a student who makes the program suffer but the team keeps him so as not to loose points in the new APR system” (R5). One coach stated that “APR has no effect at this point” (R7). The issue of assessing student-athletes as being a tough job emerged as the next category with constructs such as everything tying into it, it is difficult to do, one bad player affects everyone on the team, reflection of you, and product. Coaches spoke very passionately regarding this question and several felt it was the toughest job they have because of the consequences that at the very least could cost them their job. One coach described the process by stating that “it is difficult to assess a high school student who is 17 or 18 years old. The NFL, National Football League, misses on this all the time” (R9). His advice regarding the current process was to “take advantage of every phone call” (R9). Another coach felt that it was the “toughest job they have” and went on to say that “you just don’t know the product you are getting” (R1). Continuing the same discussion (R1) stated that he felt that “there is no science to it. Three hundred and fifty kids in the state of Texas sign as Division I studentathletes.” “The most important part is the total evaluation of the player” (R1). During the conversations about this the coaches’ voices would raise and then abruptly lower back to normal. One respondent pointed out that it was “extremely important and everything ties into it” (R8). When he spoke further he also commented that “it is the life line” in coaching (R8). Early commitment emerged as the next issue within this question. The constructs that support this theme were that of increased pressure, a need to start earlier, and maturity. “The problem with early commitments is that maturity is an issue. Physical development is big” (R7). Coaches have adapted to early commitments but many feel that “they are forced to make snap decisions” (R1). Student-athletes are growing mentally and physically during the recruiting process. In many cases it can be hard to predict the future and coaches are only

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permitted to have contact with student-athletes for short periods of time therefore making an assessment very difficult. According to one respondent, he felt that “more contact was good” (R4). This early commitment pressure on student–athletes does not help much and the fact is that student-athletes “feel the pressure to commit early” (R3). He went on to say that they will not offer until they get to know the kid, coach, and family. “Even though they commit early, coaches still evaluate” (R6). Coaches have adapted to this process by “getting to know student-athletes in the 9th and 10th grade” (R4). Another coach said that “they started tracking student-athletes in the 11th grade” (R6). The final issue that developed with this question was the coaches’ responses on the student-athletes character. They mentioned areas such as work ethic, academics, personality test and commitment. Character is an issue that has emerged throughout and this category remains consistent. One respondent felt that “academics, athletics, and character were important” (R1). Another felt that “character and work ethic were important and went on to say that he felt a personality test might have some merit. The question to the coaches would be, are they (the student-athletes) real” (R2)? Commitment is important and (R5) made the comment “don’t bring people in that don’t have the commitment.” When it comes to assessing character issues two schools mentioned they had a formalized process. A respondent commented, We have four keys to success. Kids are rated and are given stars for how well they rate. They put all of this on a recruiting board, green is good, yellow is hold on, and red is stop. Character and ability are big as well as interest in the school (R3).

CONCLUSIONS AND RECOMMENDATIONS What were identified through this research were the characteristics that coaches are looking for when recruiting student-athletes to their campuses. It was found that most coaches do not utilize a formal method or assessment tool when evaluating prospective studentathletes. However, with increased pressure on the institutional level for the sports of men’s basketball and men’s football to succeed and with increased pressure from the NCAA to have student athletes succeed academically, it is important for coaches to look at who they are recruiting. Recruiting successful student-athletes will not only benefit the organization or university but also have positive results for the team and the student-athlete themselves. Swanson informs us of the relationship between an individual and organization as well as the process that is chosen that predicts or produces positive performance. As Rummler and Brache (1988) state, an individual “is part of a human performance system. At issue is whether the job outputs have been correctly identified as the ones needed to support the process and whether the performance system will support the employee’s efforts to achieve those outputs” (p. 49). Just as in this study, student-athletes are part of a system, the university. In addition, does the student-athlete have the characteristics, what will be outputs once they get on campus, to succeed? In as much, does the university have what it needs, the process, to help that student succeed once they get on campus? As in Human Capital Theory, this study focuses on the capital of the student-athlete to a university or college. Therefore the more investments a university might put into a studentathlete the greater the return for the organization. In as much the same applies to the student-

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athlete, the more investments he makes on his education, athleticism, and character, the more positive the outcome will be. “Human capital theory suggests that individuals and society derive economic benefits from investments in people” (Sweetland, 1996, p. 341). In collegiate athletics this is very apparent. “Football success can greatly affect the overall welfare of a university” (Mandel, 2003, p. 5). Mandel goes on to quote the Kansas State president, Jon Wefald, who inherited the Division I A’s losingest program and turned it into a top-ten contender; When I got here, there was a sense of futility…If the old administration had stayed on here for three more years, I think football would have been dropped. We would have no marching band, and we’d be at about 12,000 students today. (p. 5) “Instead, since 1986 Kansas State’s enrollment has increased from about 13,000 to 23,000, its fundraising has gone from $7 million a year… to $83 million … and the city of Manhattan’s economy has grown exponentially” (Mandel, 2003, p. 5). Consequently, one can see the value of human capital society and the university can gain from the investment in these student-athletes. In as much one can see the detriment or consequences of a team who recruits individuals who do not measure up or even cause “bad publicity” for a university. Therefore, the ability to predict success in student-athletes is integral.

RECOMMENDATIONS FOR FURTHER RESEARCH AND LIMITATIONS As for my recommendations for further research I suggest that my assessment instrument be field tested at select universities where coaches gather data during recruiting. This study should be replicated in a different conference using the same criteria to determine if results are similar. Further research should be conducted on all NCAA sponsored sports as well as the information gathered from coaches in the areas of (character, family, discipline, and leadership).

REFERENCES Auman, Greg. (2005). Background checks vary; schools fear surprises. St. Petersburg Times Online. Retrieved March 8, 2005, from http://www.sptimes.com/2005. Baron, J., and Norman, F. (1992). SATs, achievement tests, and high-school class rank as predictors of college performance. Educational and Psychological Measurement, 52, 1047-1055. Brown, G. T. (2005, February 14). APR 101. The NCAA News. Retrieved October 5, 2005, from www.ncaa.org/wps/portal. Crouse, J. and Trusheim, D. (1988). The Case Against the SAT. Chicago, IL: The University of Chicago Press. Erlandson, D., Harris, E., Skipper, B., Allen, S. (1993). Doing Naturalistic Inquiry. Newbury Park, CA: Sage Publications. Knight Foundation Commission on Intercollegiate Athletics. (1999). A call to action: Reconnecting college sports and higher education. Retrieved August 25, 2006, from www.knightfdn.org.

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Mandel, S. (2003). College football’s stakes, climate provoke serious battle. 2003 College Football Preview. Available from http://sportsillustrated.cnn.com. NCAA News Online (2005). APR 101. Retrieved March 10, 2005, from the World Wide Web: http://www2.ncaa.org/media_and_events/association_ news/ncaa_news_online/2005/02_14_05/front_page_news/4204n01.html Patton, M. (2002). Qualitative Research and Evaluation Methods. Thousand Oaks, CA: Sage Publications. Rummler, G. A. (1996). In search of the holy performance grail. Training and Development, 50(4), 26-32. Rummler, G. A. and Braache, A. P. (1988). The systems view of human performance. Training, 25(9), 45-53. Sedlacek, W. E., and Adams-Gaston, J. (1992). Predicting the academic success of studentathletes using SAT and noncognitive variables. Journal of Counseling and Development, 70, 724-727. Swanson, R. A. and Holton, E. F. III. (2001). Foundations of Human Resource Development. San Francisco, CA.: Berrett-Koehler. Sweetland, S.R. (1996). Human capital theory: Foundations of a field of inquiry. Review of Educational Research, 66(3), 341-359.

Contemporary Athletics Compendium, Volume 3 Editor: James H. Humphrey

ISBN: 978-1-60741-561-9 © 2009 Nova Science Publishers, Inc.

Chapter 17

ALTERNATIVE DISPUTE RESOLUTION IN SPORT: A CONCEPTUAL APPROACH Dan Connaughton∗ Department of Tourism, Recreation and Sport Management, University of Florida, Gainesville, Florida, USA

ABSTRACT Alternative dispute resolution (ADR) is an integral part of the sport industry. It allows leagues, teams, and players to resolve disputes that arise without using litigation. It is essential for people who work within sports to understand the value of ADR. The purpose of this article is to provide an extensive overview of ADR as it relates to sport. This article takes a conceptual approach in addressing the many aspects of ADR. The two major applications of ADR, arbitration and mediation, are discussed, with a focus towards arbitration. In order to properly utilize ADR one must understand the statutes and cases that give it power. Therefore, federal and international laws, along with the cases that define ADR are discussed. Additionally, this article will examine the benefits of ADR, what distinguishes mediation from arbitration, the arbitration process, how ADR is applied to amateur sports, how the Olympics and international sport community employ ADR, how U.S. professional sports utilize ADR, and how new emerging hybrid forms of ADR are applied to sport-related disputes. In order to illustrate these concepts, recent sport examples are presented.

The problem has arisen in sport countless times; a team decides to suspend their player for conduct unfit for the organization, or a player believes s/he should be paid more money based on their recent performance, or the construction of a new multi-million dollar stadium is being halted because of a disagreement between financier and contractor. If these matters were taken to court and resolved through traditional litigation, the case would likely not be decided within a short timeframe. All of the above issues, and the majority of disputes in ∗

D. Connaughton, EdD, University of Florida, Dept. of Tourism, Recreation and Sport Management, P.O. Box 118208, Gainesville, FL 32611, (352) 392-4042, ext. 1296. E-mail: [email protected]

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sports, are often time sensitive (Greenberg, 2005). Even though the formal legal process will produce a resolution for the dispute, there is no saying how long, or how much money, it will take to get there. That is why businesses, especially those involved with sports, are increasingly utilizing alternative dispute resolution (ADR). ADR is an umbrella term that includes all of the “procedures for settling disputes by means other than litigation” (Epstein, 2002 p. 154). ADR incorporates two major subgroups: mediation and arbitration; with arbitration being the most often used (Epstein, 2002). The goal of ADR is to resolve a dispute between parties, by meeting those parties’ needs within a timely fashion (Epstein, 2002). This paper will examine the benefits of ADR, what distinguishes mediation from arbitration, the arbitration process, the federal statutes that give power to arbitration, the case law that helped define arbitration statutes in America, how ADR is applied to amateur sports, how the Olympics and international sport community employ ADR, how U.S. professional sports utilize ADR, and how new emerging hybrid forms of ADR are applied to sport facility disputes.

BENEFITS OF ADR Why would anyone use ADR instead of taking the issue to court? In other words, what are the benefits of ADR to the sport professional? As stated before, the issues that arise in sports are usually time-sensitive and demand immediate resolution (Greenberg, 2005). Disputes with sports are considered time sensitive for two reasons. First, any delay in a sport dispute will cause both sides to lose large sums of money; both sides will save money every day they do not spend litigating. Secondly, there are disputes in sports that determine whether or not an athlete can continue competing. If it is not determined in a timely fashion whether an athlete can compete, the competitor may miss the game or tournament. Because of this, sports are turning to ADR more frequently to solve a variety of problems. There are five major benefits of using ADR over more traditional avenues of dispute resolution, such as litigation. These include speed, informality, privacy, finality, and cost effectiveness (Greenberg, 2005). ADR is much faster then traditional litigation because it eliminates the delay tactics commonly used by lawyers (Greenberg, 2005). Even without any interference from lawyers, it can take months for a case just to be assigned a trial date. Delay tactics, such as motions, can extend this time period even more. Unlike the litigation process, ADR processes have strict timelines the parties must follow regarding filing of grievances, and a strict timetable that is followed concerning procedure. This includes the selection of a mediator or arbitrator, discovery period, and time allotted to reach a decision. According to the American Arbitration Association (AAA) a decision must be rendered within thirty days of the evidence period closing (Commercial Arbitration Rules, 2007). The amount of time that a decision must be rendered is decided prior to arbitration ever beginning. The second benefit of ADR is the informality involved. Contrary to the formal hearings of a courtroom, ADR usually takes place in a conference room occupied by both parties, and the mediator or arbitrator. This type of informal atmosphere may be less intimidating to an organization or athlete than the typical judge ruled courtroom. Although evidence in ADR hearings is presented in a similar fashion to traditional litigation, the evidence presentation process is far more casual. Thirdly, ADR

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provides an important concern of sport organizations and athletes, privacy. Since the only people usually present in an ADR hearing are the two disputing parties and the person/people presiding over the case, very little information typically reaches the public. This is extremely important for sport organizations and players because their disputes are closely observed by the media and public. Settlements are only made public if the contract between the two parties calls for it. This is usually the case in salary arbitration. The fourth benefit of ADR, in the case of arbitration, is the finality of the decisions rendered. An arbitrator’s decision is usually final and binding, and only available for appeal for a few reasons, all of which will be addressed later. Lastly, ADR is cost effective. The hearing is shorter, with less legal presence, if any, needed, and the possibility of appeals is minuscule. The combination of all of the aforementioned benefits makes ADR a cheaper option over litigation for dispute resolution (Greenberg, 2005).

MEDIATION AND ARBITRATION DISTINGUISHED Mediation is, “… the submission of a dispute to an impartial facilitator who assists the parties in negotiating a voluntary, consensual settlement of their dispute” (Epstein, 2002 p. 158). In mediation, the two quarreling parties are essentially in control of the discussions. They are able to cease talks whenever they please. The purpose of mediation is to generate an environment that will contribute to the settlement of the argument at hand (Epstein, 2002). Ultimately, the relationship of the two parties involved must be preserved in order to continue closing in on a possible solution (Cotten and Wolohan, 2007). A mediator can accomplish this by trying to establish an open, respectful line of communication between the parties (Epstein, 2002). The mediation process involves meetings between the two parties, overseen by a mediator. The mediator is responsible for strictly facilitating the talks; he or she can not impose a solution on the parties (Cotten and Wolohan, 2007). Mediation talks can be divided into two different methods, caucus and conference (Fried and Hiller, 1997). In caucus talks the two parties are separated from one another, and talk to the mediator individually, while conference meetings consist of all parties discussing the issues together in one room (Fried and Hiller, 1997). During these meetings the parties are expected to discuss the problems they are experiencing, and what they believe should be done to resolve the conflicting issues. Hopefully, the two parties can agree on a viable solution on their own, although many times a mediator is requested to give his or her opinions and suggestions on possible solutions. Although typically not binding, mediation solutions can be written in the form of a contract, the violation of which could result in litigation (Epstein, 2002). Mediation can lead to dispute resolution, but this is not guaranteed. When a decision must be unequivocally resolved, businesses often turn to arbitration. Arbitration, the most popular aspect of ADR in sports, is used to resolve a plethora of disputes, by a wide array of organizations. Unlike mediation, arbitration will always result in a final solution to the problem. Arbitration is not concerned with preserving the relationship between the two parties as much as the mediation process is. It does not matter if the parties involved continue to talk after the arbitration hearing because the problem is resolved; however it would be beneficial for business if the relationship remains intact. During mediation you are not sure when and if the problem will be resolved so it is more essential to

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the process to keep the two parties in ongoing conversations. This can only happen if a relationship between the parties exists. Arbitration is “the submission of a dispute to a neutral decision maker (an arbitrator) for a final resolution of a disagreement” (Epstein, 2002 p.157). This decision can be binding or non-binding. This is determined within the contract or agreement the two parties have previously entered into. The contract or agreement between the parties can also determine whether the arbitration is voluntary or mandatory (Epstein, 2002). Epstein (2002) offers a sample arbitration clause that could appear in a contract, “Any controversy or claim arising out of or relating to this contract, or the breach thereof, shall be settled by arbitration administered by the American Arbitration Association in accordance with its Commercial [or other] Arbitration Rules [including the Emergency Interim Relief Procedures], and judgment on the award rendered by the arbitrator(s) may be entered in any court having jurisdiction thereof (p. 170).”

This sample of an arbitration clause touches on issues that will be discussed in the arbitration process.

THE ARBITRATION PROCESS The first aspect of the arbitration process is the notice of arbitration. This is done in the form of a written document. Most notices of arbitration have statutes of limitations that are outlined in the parties’ contracts or agreements (Greenberg, 2005). The next step in the arbitration process is the response. The written response outlines whether the party responding to the initial notice agrees to the fact that the issue at hand is in fact subject to arbitration (Cotten and Wolohan, 2007). Once the notice and response is established, an arbitrator must be selected to oversee the proceedings and make the final ruling. The process of determining or selecting an arbitrator or panel of arbitrators can differ greatly from case to case. First, the manner in which an arbitrator is selected will almost always be defined in the contract or agreement the two parties have between them (Greenberg, 2005). Both parties are equally involved in the selection of a neutral arbitrator in order to ensure fairness (Epstein, 2002). The AAA is a nongovernmental organization that provides neutral arbitrators to the public (Commercial Arbitration Rules, 2007). This is the most popular place that parties can secure an arbitrator, but is not the only organization of its kind. Typically, the two parties will either agree on one arbitrator to oversee the hearing, or each party may select their own arbitrator from an approved list. The two selected arbitrators will secure a third arbitrator to secure an arbitration panel (Greenberg, 2005). This selection process can be done numerous ways, but the result is always a mutually agreed upon arbitrator or panel of arbitrators. A benefit of selecting an arbitrator is that the parties can select an individual(s) with expertise in the field, instead of a judge or jury that might not be familiar with sport practices. After the arbitrator(s) are appointed, the hearing commences. The AAA has created the Commercial Arbitration Rules in order to regulate how arbitration hearings should be conducted (Epstein, 2002). Following these rules is extremely important because they are designed to maintain efficiency and fairness, while reducing the possibility of appeal. During the hearing, both parties will present documents, briefs, and witnesses like a normal trial, but it differs from a

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normal trial by being more relaxed and not providing transcripts in the fashion a trial would. In traditional litigation, the court compiles an ongoing transcript of what happens during the hearing. The transcript documents everything that is said and done over the course of a trial. The transcript is primarily designed to supply the appellate court with a description of whether the procedural rules were followed. Since an arbitration decision is rarely allowed to be appealed, there is no need for a transcript (Report of the Study Committee, 2003). Once both parties have presented their arguments, the arbitrator(s) will make a decision. The decision made is usually final and binding; however certain contracts allow for appeals, while others stipulate the decision as not appealable.

FEDERAL LAW The U.S. statute that initially outlines and defines arbitration, including why an arbitrator’s decision can be appealed, is the U.S. Federal Arbitration Act (FAA) of 1925 (U.S. Federal Arbitration Act, 1925). The FAA applies to any contract or agreement between two parties, excluding those involving transportation workers. The purpose of the FAA was, and still is, to encourage businesses to utilize ADR as an alternative to traditional litigation (Epstein, 2002). Title 9, U.S. Code, Sections 1-16 deals with domestic applications of the FAA. The foreign applications of arbitration within the United States are outlined in Sections 205-208 and 301-307 of the same U.S. Code. Sections 205-208 deal with the enforcement and adoption of the Convention on the Recognition and Enforcement of Foreign Arbitral Awards of 1958; while Sections 301-307 are concerned with enforcing the Inter-American Convention on International Commercial Arbitration of 1975 (Federal, 1925). These statutes allow arbitration to be used in all areas of business, including sports. In regards to when an arbitrator’s decision can be appealed and possibly dismissed, 9 U.S.C. § 10 states that a decision can be vacated if: “(1)… the award was procured by corruption, fraud, or undue means;" (2) "where there was evident partiality or corruption on the part of the arbitrators ... ;" (3) "where the arbitrators were guilty of misconduct in refusing to postpone the hearing upon sufficient cause shown[;]"(4) "where the arbitrators were guilty ... in refusing to hear evidence pertinent and material to the controversy;" (5) "where the arbitrators were guilty ... of any other misbehavior by which the rights of any participant have been prejudiced;" or (6) "where the arbitrators exceeded their powers, or so imperfectly executed them that a mutual, final and definite award upon the subject matter submitted was not made."

In summation, 9 U.S.C. § 10’s requirements for dismissal all concern misconduct on behalf of the arbitrator(s). This is why arbitration decisions are so hard to appeal. Unless the arbitrator commits one of the six aforementioned actions, the decision rendered is final and binding. Without one of these infractions, the arbitrator’s decision will not be dismissed. Although the FAA of 1925 was the first U.S. statute concerning arbitration, it was not the last. In 1955, the American Bar Association ratified the Uniform Arbitration Act (UAA) (Uniform Arbitration Act, 1955). The purpose of this Act was to institute legal procedure and policy pertaining to arbitration (Cotten and Wolohan, 2007). The UAA has been implemented by 35 states (Uniform Arbitration, 1955). What the UAA does is create law that can legally

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support the enforcement of an arbitrator’s decision (Uniform Arbitration Act, 1955). More recently the United States has enacted the Administrative Dispute Resolution Act of 1990 (ADRA), 5 U.S.C.A. § 571-583 (Administrative Dispute Resolution Act, 1990). The ADRA was endorsed in order to require federal agencies to establish policies in regards to using ADR as a possible option for dispute resolution. The ADRA states that all government agencies have a “dispute resolution specialist” who determines in what situations it is appropriate to use ADR as a viable dispute resolution (Administrative Dispute Resolution Act, 1990). The objective of employing a specialist is to ensure actions are being taken that are in the best interest of both the public, and the agency. This Act forces governmental agencies to have policies in place for ADR’s possible use concerning, “formal and informal adjudication, rulemakings, enforcement actions, the issuance and revocation of licenses or permits, contract administration, litigation brought by or against the agency, and other agency actions” (Epstein, 2002). The ADRA has expanded ADR from the businesses of America, to the government itself.

CASE LAW INTERPRETATIONS OF ADR STATUTES Since the FAA, UAA, and ADRA have been passed, there have been several landmark cases that helped define their rules and purpose. The most well known and significant litigation consisted of three United States Supreme Court cases referred to as the Steelworker’s Trilogy. On June 20, 1960, the Supreme Court gave their rulings on United Steelworkers of America v. Warrior and Gulf Navigation Co., United Steelworkers of America v. Enterprise Wheel and Car Corp., and United Steelworkers of America v. American Manufacturing Co. In all three of these cases, the Supreme Court enforced the arbitration clause in the collective bargaining agreements between the parties. The Steelworker’s Trilogy initiated principles “regarding the judicial review of arbitration awards” (Greenberg, 2005). These three cases are credited for allowing courts to enforce arbitration clauses found in collective bargaining agreements. The trilogy of cases had an additional impact on the way arbitration is conducted and judicially reviewed today. Within its ruling, the Supreme Court found that parties are only subject to arbitration of matters that were contractually agreed upon by both parties (Baker and Connaughton, 2005). Both Greenberg (2005) and Lipinski (2003) contend that there are two general rules that can be taken from the Steelworker’s Trilogy. First, the cases establish that “grievances are presumed to be arbitrable” (Malin, 1990 p. 551). Secondly, the Steelworker’s Trilogy further acknowledges that the decision of an arbitrator is extremely limited within a judicial review (Greenberg, 2005; Lipinski, 2003). Another Supreme Court case that helped define the judicial review or appeal of an arbitrator’s decision was United Paper Workers International Union v. Misco, Inc. In this case, a hazardous machine operator was found in the parking lot of his place of employment, in the back seat of a car containing marijuana smoke and a marijuana cigarette in the front ashtray. According to the collective bargaining agreement he had entered into, the use of narcotics or drugs at the workplace, or being under the influence at the workplace, would result in an immediate dismissal. The man’s employer did in fact fire him once they were notified by the police about the arrest made on their property. As per the collective bargaining

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agreement, this grievance was set to be settled through arbitration. Once hearing both sides, the arbitrator found that the employee should be reinstated with pay for time missed, and returned to his previous seniority. The Arbitrator believed that the employer had not proved that the employee had ever possessed or used the marijuana, and therefore was not in violation of the drug rule within the collective bargaining agreement. After hearing the arbitrator’s decision, the employer appealed their case to United States District Court for the Western District of Louisiana. The district court reversed the arbitrator’s decision stating that the award went against public interest, a reason some lower courts believe is cause for an arbitration award to be vacated, because having a hazardous machine operator on drugs was unsafe. The Court of Appeals which heard the case agreed with the District Court’s decision. Eventually, the case reached the Supreme Court. The Supreme Court’s decision reinforced the stance they had on judicial review of arbitration during the Steelworker’s Trilogy cases. The Supreme Court ruled that the District Court and Court of Appeal erred in deciding what was against public policy. Even if they had the authority to do so, which the Supreme Court did not state, they both did not show enough evidence to even prove this was the case. Citing the fact that the arbitrator acted without fraud, and did not violate any of the outlined causes for vacating an arbitrator’s award, the Supreme Court reversed the Court of Appeals decision, and allowed the arbitrator’s original decision to stand.

ADR APPLICATION TO AMATEUR SPORTS With ADR benefits, procedures, and statutes discussed, we now turn to the application of ADR as it pertains to sports. First is the use of ADR within amateur sport, specifically college athletics and the National Collegiate Athletic Association (NCAA). Since the United States does not recognize student-athletes as employees, student-athletes can not enter into collective bargaining agreements. Therefore, ADR is often overlooked as a dispute resolution option (Greenberg, 2005). However, many scholars claim that ADR can be a viable option for student-athletes and universities because they enter into various contractual agreements, some of which might be interpreted as availing themselves to the arbitration clause. Fried and Hiller (1997) contend that three documents, The National Letter of Intent, scholarship agreements, and the student code of conduct, can all be used by student-athletes to explore ADR prior to litigation. Although there is a modern push for the use of ADR in intercollegiate athletics by scholars, the use of ADR in college athletics is extremely rare. However, one well known case involving the NCAA did address ADR. In Law v. NCAA (1995), coaches challenged the NCAA’s Restricted Earnings Coach Rule that stated restricted earnings coaches were only allowed to earn $12,000 in an academic year, and $4,000 throughout the summer (Law v. NCAA, 1995). Law, and the other coaches, believed this rule violated the Sherman Antitrust Act. The District Court granted summary judgment in favor of the coaches, stating that the Restricted Earnings Coach Rule violated the Sherman Act. The NCAA then motioned to appeal the judgment. Between the time of the District Court’s decision, and the start of the appellate trial, the NCAA and Law entered into ADR via mediation. Through the mediation process the two parties were able to reconcile their disputes in the form of a $54.5 million settlement paid to the coaches (Epstein, 2002). Although the history of ADR and NCAA is brief, there is a potential for greater use of ADR if the NCAA starts including arbitration and

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mediation clauses in their three contractual documents. The NCAA itself has realized the benefits and possibilities that ADR represents for their Association. Since 2004, the NCAA has been discussing the possibility of introducing both arbitration and mediation for a variety of issues. They have submitted and voted on proposals that would require all members of the NCAA to agree to binding arbitration instead of legislation under the protection of the FAA. Although many subcommittees have been commissioned to help determine the best manner to initiate ADR practices, none have been officially enacted to date (Report of the NCAA, 2005; Condition of Membership, 2004).

ADR APPLICATION TO OLYMPIC AND INTERNATIONAL SPORTS ADR in amateur sports is not limited to the collegiate level; in fact one of the most prestigious levels of sport competition in the world is considered an amateur sport, the Olympics. Unique predicaments arise concerning international competition. First, different nations have different legislative systems and laws, so international sport competitions and competitors face the problem of whose laws should be adhered to, the host nation or the athlete’s country of origin (Cotten and Wolohan, 2007). The other major issue is that the problems that arise in international sport competition such as “positive drug tests of athletes, the challenges to technical decisions of officials made during competition, and the eligibility of athletes to compete in the Olympic Games,” need to be decided under severe time constraints in order for an athlete to participate as scheduled (Gilson, 2006 p. 504). Just as in the U.S., international legislative processes are not quick, and the expedited process and binding finality of arbitration suits itself well for these situations. Both the United States and international communities have addressed the issue of ADR in international amateur sport competitions. First, the United States compiled the Amateur Sports Act of 1978 (ASA), 36 U.S.C.S. § 220501-220512 and §220521-220529, originally the Ted Stevens Olympic and Amateur Sports Act. The ASA not only established the United States Olympic Committee (USOC), it also outlined and defined its powers and obligations (Epstein, 2002). The ASA defines what constitutes an amateur athlete, international sport competitions, the purpose of national organizations pertaining to sports, and powers held by those organizations (36 U.S.C.S. § 220501-220512). Additionally, the ASA requires the USOC to find “swift resolution of conflicts and disputes involving amateur athletes, national governing bodies, and amateur sports organizations...” (Epstein, 2002 p. 160). This part of the ASA shows why arbitration is a desired method of dispute resolution within U.S. international competition. In 1983, five years after the U.S. enacted the ASA, the International Olympic Committee (IOC) established the Court of Arbitration for Sport (CAS) (Epstein, 2002). The purpose of the CAS is to remedy the problem international competitions face with jurisdiction, by offering the same arbitration process to all nations and athletes. In order to maintain a neutral status, and be independent from the IOC, the International Council of Arbitration for Sport (ICAS) began overseeing the CAS in 1993 (Nafgizer, 2006). The CAS is recognized as the leader in international dispute resolution (Gilson, 2006). An important fact that supports CAS being a leader is the fact that their decisions are “recognized as developing a lex sportive,” which means their rulings establish precedence concerning international sport law (Gilson,

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2006). The CAS hears cases brought forth by “international athletes, national governing bodies, national Olympic committees, and sport federations” (Cotten and Wolohan, 2007 p. 47). Much like the typical arbitration process, CAS arbitration must be agreed upon by both parties prior to the hearing. In order to secure arbitration as the only dispute resolution method used by Olympic participants, the Olympic Games began requiring athletes to sign a document that binds them to arbitration through the CAS if a grievance should arise (Gilson, 2006). Similarly, International Federations that govern sports also demand athletes to sign a contract ensuring all grievances will be appeased through the CAS (Nafziger, 2002). Arbitrators are selected in a similar fashion to what was discussed during the arbitration process; parties can choose an arbitrator(s) from a list provided by the CAS. The CAS has three separate divisions that hear disputes: Ordinary Arbitration, Appellate Arbitration, and Ad Hoc (Gilson, 2006). A typical case would first go to the Ordinary Division of the CAS, then, if one party disagrees with the decision they can take their case to the CAS’s Appellate Division. These divisions of the CAS are located in Lausanne, Switzerland; New York City, New York; and Sydney, Australia (Cotton and Wolohan, 2007). The Ad Hoc Division of the CAS was established in 1996. Its purpose is to solve any disputes that arise during the Olympic Games, Commonwealth Games, and other international competitions (Nafziger, 2002). The CAS’s Ad Hoc division establishes a presence at the Games themselves, so that arbitration hearings can be conducted onsite, and in an expedited fashion (Nafziger, 2002). Since 2001, the CAS has decided over 250 arbitration hearings, and that number only continues to rise (Nafziger, 2002). Although originally designed to resolve Olympic issues, the CAS will also hear cases from other organizations such as the World Anti-Doping Agency (WADA) and European Football Championships. One such case, decided January 24, 2007, involved WADA and a Portuguese soccer player Mr. Nuno Assis Lopes de Almeida. Mr. Almeida was initially suspended by the Portuguese Football Federation (FPF) for six months, but that punishment was eventually dismissed by the federation’s judicial board. One month later WADA sought a 2 year suspension in the CAS. The FPF, on behalf of Almeida, defended against the suspension by arguing that WADA lacked authority to appeal the dismissal, the testing procedure was unreliable, the sample was not transported quickly enough, and any suspension should not exceed the original six month suspension. The CAS ruled in favor of WADA, and suspended Almeida for 12 months. They also ruled that the FPF must cover the legal and other costs of WADA in the amount of 5,000 Swiss Franc (WADA v. Almeida, CAS 2006/A/1153, 2007).

ADR APPLICATION TO U.S. PROFESSIONAL SPORTS Although all four of the United States major sport leagues, the National Basketball Association (NBA), the National Hockey League (NHL), Major League Baseball (MLB), and the National Football League (NFL), and their teams, are governed by themselves, within their respected leagues, they still require ADR in order to function efficiently and effectively. This section will address the NHL’s and MLB’s use of salary/labor arbitration and the NBA’s and NFL’s use of arbitration for disciplinary decisions.

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In any business, labor disputes will eventually develop between management and its labor force. Professional sports are no exception. Recently, the NHL became the first professional sports team to cancel their entire season due to a labor dispute. This labor dispute was over the discrepancy between the amount of money and benefits the players wanted, compared to what owners and management were willing to give. The resolution of the dispute led to a new CBA, with new arbitration provisions. There was a collective bargaining agreement (CBA) in place between the owners and players prior to the season’s cancellation (Yoost, 2006). The CBA was, and still is, an agreement between the NHL and the National Hockey League Players Association (NHLPA), the players’ union. The other three major U.S. leagues also utilize a CBA to govern the business relationship between owners and the players. However, only the NHL and MLB utilize arbitration in salary disputes, but they both have their own unique versions. The NHL was the first league to use arbitration to resolve a salary dispute back in 1970, three years prior to the MLB adding arbitration to their CBA (Yoost, 2006). In both leagues, arbitration starts with the two parties disagreeing on the salary of a player. Both parties inherently agree to decide all salary disputes via arbitration because this is defined in their CBA. In the NHL, only players were allowed to file for arbitration under the old CBA; under the new CBA both owners and players can file for an arbitration hearing. The only other difference under the NHL’s new CBA agreement pertaining to salary arbitration is the fact that players are eligible to request arbitration after four years in the league, instead of three. In both the NHL and the MLB, once the parties agree that arbitration is necessary to resolve the salary dispute, an arbitrator(s) must be selected. The leagues differ in the manner in which they do this. The NHL has a system in place wherein the NHL and NHLPA annually select eight arbitrators from the National Academy of Arbitrators to hear all disputes that arise in that year, with only one arbitrator presiding over a case. While the MLB and its players’ association also select a group of arbitrators annually, each case has a panel of three arbitrators that hears the dispute. In the NHL and MLB, both parties in a dispute have an equal role in the arbitrator selection process. Another difference between the two leagues is the amount of salary that can be awarded (Yoost, 2006). The MLB has a “final-offer” system. The final-offer system states that each party in the dispute suggests the salary they believe appropriate; once hearing their cases, and looking at the salaries of other players in the league with comparable statistics and performance, an arbitrator can choose one of the two amounts. Yoost (2006) provides the following example, “… [if] the ballplayer asks for $750,000 and the owner offers $500,000, the arbitrator must choose either $750,000 or $500,000, one or the other (p. 501).” The amount the arbitrator chooses is final and binding, and not available for appeal. A real life parallel to this example is the San Diego Padres second baseman Todd Walker, and his February 21, 2007 salary arbitration. At the beginning of the arbitration proceedings Todd Walker submitted his request of $3.95 million to the arbitration panel, while the club was asking his salary be $2.75 million (Staff, 2007). After analyzing Walker’s career numbers, the arbitration panel decided that the $3.95 million he requested was closer to the value that Walker deserved. As a result of the hearing, Walker is now earning $3.95 million a year to play second base for the Padres (Staff, 2007). Although an arbitrator in the NHL goes through a similar process of analyzing the salaries, performance, and statistics of comparable players in the league, the arbitrator is given the power to grant any amount they please. Also, the amount awarded is not binding. The owner’s of the NHL have the opportunity to utilize the “walk-away” clause, which

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allows them to disregard the arbitrator’s decision within 72 hours of its announcement. However, if the team has multiple ongoing arbitration hearings, they are permitted to wait until all of the hearings have been concluded before deciding whether or not to walk-away. The teams can only do this three times in a two season span. If the contract being arbitrated was for one-year, then the player would become an unrestricted free agent. If it was for two years and the team chose to walk-away, then the player would remain on the team for one year under the salary awarded by arbitration, and then become an unrestricted free agent (Yoost, 2006). An example of the “walk-away” clause being used by a team is the August 5, 2006 salary arbitration decision of David Tanabe. At the time of the $1.275 million decision, Tanabe was a defenseman for the Boston Bruins. In an effort to keep their payroll below $36 million, the Bruins decided it would be in their best interest to walk-away from the arbitrator’s decision. As a result, Tanabe became an unrestricted free agent, and less than a month later signed with the Carolina Hurricanes (Bruins Walkaway, 2006). The NHL CBA states that the salary of a player who signed a contract as an unrestricted free agent, testimonials, videos and media reports, the financial state of the team, and the team's payroll as it relates to the salary cap, are not admissible as evidence at a salary arbitration hearing (Fitzpatrick, 2006). Although salary arbitration is usually the type of ADR one hears most about on the news, it is not the only reason why a team, player, or league may use arbitration. By nature sport is an aggressive activity. Knowing this, professional sport leagues establish clauses within their CBA that outlines what on-the-field and off-the-field actions warrant disciplinary action. The groups responsible for handing down a disciplinary action can either be the athlete’s team or the league office they belong to. Two highly publicized disciplinary cases, one from the NBA and the other from the NFL, will be examined in order to show how players use arbitration to appeal punishments they receive. The first case concerns the suspensions handed down by the NBA’s Commissioner, David Stern, regarding a fight that took place in a game between the Indiana Pacers and the Detroit Pistons. On November 19, 2004, in Detroit, a brawl erupted between members of the Indiana Pacers and both the Pistons players and fans. In total, 9 suspensions were handed down by Commissioner Stern, with Ron Artest, Stephen Jackson, and Jermaine O’Neal receiving the harshest punishments. As a result, the National Basketball Players Associations (NBPA) filed an appeal to the NBA’s Grievance Arbitrator (Baker and Connaughton, 2005). According to Article XXXI, section 8, of the NBA’s CBA, only the commissioner is allowed to hear an appeal for “on the court” disciplinary violations, making the request to the Grievance Arbitrator unusual (NBA CBA, 2006). In this special situation the Grievance Arbitrator contended he had arbitrability over the dispute (Baker and Connaughton, 2005). However, Commissioner Stern believed that Article XXXI, section 8, of the NBA’s CBA applied to this case and refused to attend the hearings. In the end the Grievance Arbitrator decided, “the dispute is arbitrable before the Grievance Arbitrator, and is not within the exclusive jurisdiction of the Commissioner, because the conduct in question did not take place "on the playing court" within the meaning of Article XXXI, Section 8 of the Collective Bargaining Agreement; and (iii) the Commissioner had just cause for his suspensions of defendants Artest, Jackson and Johnson, but did not have just cause to suspend defendant O'Neal for twenty-five games. The Grievance Arbitrator reduced defendant O'Neal's suspension to fifteen games.” (NBA v. NBPA, 2005)

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Commissioner Stern appealed the Grievance Arbitrator’s decision to New York’s District Court. As seen in previous appeals of arbitrator’s awards in court, the District Court upheld all of the arbitrator’s decisions. Although on the court disciplinary rulings are rarely subject to arbitration in the NBA pursuant to their CBA, this example highlights both arbitrability, and how in the right situation arbitration can be called upon to resolve disciplinary disputes. The second case involves the NFL, the Philadelphia Eagles, Terrell Owens, and the National Football League Player’s Association (NFLPA). In this case, the Philadelphia Eagles suspended Owens, a wide receiver, for four games, and then informed Owens that he would not play for the remainder for the season. The Eagles felt this was necessary because Owens was affecting the team negatively by “…skipping mini-camp and team meetings, ignoring coaches and fellow players and publicly criticizing the team, the Eagles organization and his colleagues” (Matter, 2005 p. 3). The NFLPA, on the behalf of Terrell Owens, immediately filed for appeal to the Notice Arbitrator. According to Article IX, Section 6 of the NFL CBA, the arbitration hearing will be heard by a panel of 4 arbitrators that were all decided upon by both the NFLPA and the NFL Management Council (NFL CBA, 2006). Article XXVII, Section 7, states that if the two sides cannot agree on a panel of arbitrators, then they will be selected from the list of currently serving Non-Injury Grievance Arbitrators (NFL CBA, 2006). In this dispute the arbitrator was asked to answer two questions, “[1] Was the fourweek disciplinary suspension for just cause; if not, what should the remedy be [2]Was it a violation of the CBA for the Club to exclude the Player from games and practices, following the four-week suspension” (Matter, 2005 p. 1). The arbitrator ruled that the suspension was for just cause. The arbitrator also determined that because of Owens’ disruptive behavior, compounded with the fact that he would be paid while being benched for the remainder of the season, the punishment would not violate the NFL’s CBA (Matter, 2005).

HYBRID FORMS OF ADR AND SPORT FACILITY LEASES Although traditional sport and business arbitration occurs between management and its labor force, a recent trend in sports is to utilize arbitration to resolve contract disputes in facility leases. Although litigation has been the traditional venue for solving lease disputes in the past, the new trend is to include what disputes and controversies will be alleviated through ADR, and mainly arbitration. Some sport facility leases, such as the Minnesota Wild, require the two parties enter mediation for a specific amount of time before an issue can proceed to litigation (Greenberg, 2005). Facility lease disputes tend to use new hybrid forms of ADR such as Mediation-Arbitration (Med-Arb) and Arbitration-Mediation (Arb-Med). Med-Arb is usually used when several issues are being disputed. What happens is the two parties enter mediation talks and resolve any issues they can. Any issues that remain after the mediation period are subject to arbitration. The same is true for Arb-Med, except that the arbitration process is held prior to mediation (Epstein, 2002). An example of Med-Arb in a sport facility lease is the Carolina Hurricanes’ lease clause that states, “If the parties have not resolved the Dispute through the Mediation within 60 days after the Request… [then] the Dispute shall be submitted to arbitration (the "Arbitration") for resolution by an arbitrator or a panel of arbitrators ...(p. 106)”

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Facility leases often have clauses within them that state specific situations, usually constructional disagreements, which are eligible for expedited arbitration (Greenberg, 2005). Expedited arbitration is similar to normal arbitration, except the timeframe in which it is conducted is even faster. The reason construction is usually subject to expedited arbitration, as supposed to normal arbitration, is that the delay of construction has the potential of costing both parties millions of dollars. The amount of time between the initial notice and the hearing is reduced greatly, and the arbitrator may be predetermined. The Philadelphia Phillies have an arbitrator that presides over any expedited arbitration hearing until “he resigns or is replaced by written agreement of the parties” (Greenberg, 2005 p. 110). With its expansion to new facets of sport, it is easy to see that ADR will continue to impact the sport industry in new ways.

CONCLUSION As long as there is sport, ADR will be utilized as an efficient, cheap alternative to litigation. From the statutes that established it, to the cases that define it, ADR continues to gain more legal backing. It is used in amateur sports such as the Olympics, and is a vital aspect of all four major sports’ CBAs. ADR can solve a gambit of problems from doping and fighting, to off-the field issues like salaries. Some ADR resolutions have extended to outside the sport itself. Sport organizations have come to appreciate the value of ADR so much that they now use it in other areas of their business such as facility lease agreements. With its prolonged use, ADR will continue to evolve, hence the new practices of Med-Arb and ArbMed. Without arbitration, sport franchises would have to pass the additional costs of litigation to ticket holders and fans. Fans see arbitration cases on ESPN and are unaware that the hearing is actually saving them money. Additionally, sports will never stop searching for disputes that can be effectively settled via ADR. Sports will always have disputes between its participating members, and ADR will always have a place in sports.

REFERENCES Administrative Dispute Resolution Act of 1990, 5 U.S.C.A. 581. Baker, T. A., and Connaughton, D. (2005). The Role of Arbitrability in Disciplinary Decisions in Professional Sports. Marquette Sports Law Review, 16(1), 123-155. Bruins Walkaway From Tanabe. (2007). Retrieved August 25, 2007, from http://puckstopshere.blogspot.com/2006/08/bruins-walkaway-from-tanabe.html. Commercial Arbitration Rules, (2007). Section R-41: Time of Award. Retrieved October 21, 2007, from http://www.adr.org/sp.asp?id=22440#R41. Condition of Membership–Mandatory Binding Arbitration, (2004). Retrieved August 12, 2007, from http://www.ncaa.org/membership/governance/ divsion_III.management_council/2004-4/s36_arbitration.htm. Cotten, D. J., and Wolohan, J. T. (eds.).(2007). Law for Recreation and Sport Managers (4th ed.). Dubuque: IA: Kendall/Hunt.

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Epstein, A.. (2002). Alternative Dispute Resolution in Sport Management and the Sport Management Curriculum. Journal of Legal Aspects of Sport, 12, 153-173. Federal Arbitration Act of 1925, 9 U.S.C. Retrieved March 24, 2007, from http://www.adr.org/sp.asp?id=29568. Fitzpatrick, Jamie (2006). NHL Salary Arbitration Explained. Retrieved August 25, 2007, from http://proicehockey.about.com/od/nhlfreeagents/a/ arbitration.htm Fried, G., and Hiller, M. (1997). ADR in Youth and Intercollegiate Athletics. Brigham Young University Law Review, 631-652. Gilson, E. T. (2006). Exploring the Court of Arbitration for Sport. Law Library Journal, 98, 503-514. Greenberg, M. J. (2005). Alternative Dispute Resolution in Sports: Alternative Dispute Resolution in Sport Facility Leases. Marquette Sports Law Review, 16, 99-122. Law v. NCAA, 134 F.3d 1010 (10th Cir. 1998). (1995). Lipinski, T. (2003). Major League Baseball Players Ass’n v. Garvey Narrows the Judicial Strike Zone of Arbitration Awards. Akron Law Review, 36, 325-362. Malin, M. H. (1990). Labor Arbitration Thirty Years After the Steelworkers Trilogy. Chicago-Kent Law Review, 66, 551-570. Matter of the Arbitration Between Terrell Owens and the National Football League Players Association v. the Philadelphia Eagles and the NFL Management Council, (2005). Retrieved March 24, 2007, from http://tom.mcallister.ws/2005/11/24/full-text-of-the-terrellowens-arbitration-settlement/. Nafziger, J. A. R. (2002). Dispute Resolution in the Arena of International Sports Competition. The American Journal of Comparative Law, 50, 161-179. Nat’l Basketball Ass’n v. Nat’l Basketball Players Ass’n, No. 04 Civ. 9528, 2005 WL 22869(S.D.N.Y Jan. 3, 2005). National Basketball Association Collective Bargaining Agreement. (2006). Retrieved March 24, 2007, from http://www.nbpa.com/cba_articles.php. National Football League Collective Bargaining Agreement. (2006). Retrieved March 24, 2007, from http://www.nflpa.org/CBA/CBA_Complete.aspx. Report of the NCAA Executive Committee Subcommittee on Mandatory Binding Arbitration. (2005). Retrieved August 12, 2007, from http://www.ncaa.org/Membership/governance/assocwide/executive_committee/docs/2005/2005-08/s10_mand-bind.htm. Report of the Study Committee on Trial Transcripts. (2003). Retrieved October 21, 2007, from http://www.mass.gov/courts/trialtransrep.pdf. Staff. (2007). Final 2007 Arbitration results. Retrieved August 25, 2007, from http://www.bizofbaseball.com/index.php?option=com_contentandtask=viewandid=719an dItemid=78. Ted Stevens Olympic/Amateur Sports Act of 1978, 36 U.S.C.A. 383. Uniform Arbitration Act of 1955. United Paperworkers International Union, Afl-Cio, Et Al. v. Misco, Inc., 484 U.S. 29 (1987). United Steelworkers of America v. Am. Mfg. Co., 363 U.S. 564 (1960). United Steelworkers of America v. Enter. Wheel and Car Corp., 363 U.S. 593 (1960). Retrieved March 24, 2007, from Lexis Nexis database. United Steelworkers of America v. Warrior and Gulf Navigation Co., 363 U.S. 574 (1960).

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World Anti-Doping Agency (WADA) v. Portuguese Football Federation (FPF), CAS 2006/A/1153 (January 24, 2007). Retrieved August 12, 2007, from http://www.sportsarbitration.com/tp-070129105711/post-070130152038. shtml. Yoost, S. M. (2006). The National Hockey League and Salary Arbitration: Time for a Line Change. Ohio State Journal on Dispute Resolution, 21, 485-537.

Contemporary Athletics Compendium, Volume 3 Editor: James H. Humphrey

ISBN: 978-1-60741-561-9 © 2009 Nova Science Publishers, Inc.

Chapter 18

JUST NOT ON MY TURF: STUDENT-ATHLETES’ PERCEPTIONS OF HOMOSEXUALITY Amy Sandler∗ University of Nevada, Las Vegas, Nevada, USA

ABSTRACT NCAA certification guidelines now stipulate that member institutions must have policies, support opportunities, and educational programs in place to ensure a safe environment for student-athletes with diverse sexual orientations. This research measures student-athletes’ general level of homophobia. The results indicate that student-athletes are comfortable with other people being gay or lesbian, but they would not be comfortable if they found themselves attracted to someone of the same-sex, or if someone of the same sex was attracted to them. If coaches and athletic administrators are aware of how student-athletes perceive sexual orientation, they can be more intentional in choosing educational programming to meet specific needs of each team.

Gay, lesbian, and bisexual (GLB) student-athletes often face marginalization from their closest associates on campus: their coaches, teammates, and fellow student-athletes. Rotella and Murray (1991) found that both athletes and coaches are tremendously homophobic and heterosexist, with the mere mention of the subject often resulting in strong emotions and apprehension. But the male and female student-athlete experience around sexual orientation tends to be vastly different due to particular gender assumptions and expectations. For female student-athletes, the lesbian label stems from their athletic success as women in a maledominated environment. When it comes to sexual orientation, they often enter their specific athletic environment under a cloud of suspicion until they prove their heterosexuality. Male student-athletes, however, face the opposite predicament. Because they have reached what ∗

Contact Information: 2229 Ramsgate Drive, Henderson, NV 89074, [email protected], 702-917-8991 (cell) 702-895-5700 (fax)

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many consider to be the pinnacle of masculinity as elite athletes, societal expectations dictate that they must therefore be heterosexual. Although the expectations around sexual orientation differ for male and female student-athletes, all who face these circumstances feel the emotional consequences. Scholarly research reveals a hostile climate for GLB student-athletes, coaches, and administrators (e.g., Kauer and Krane, 2006; Rotella and Murray, 1991; Wolf-Wendel, Toma, and Morphew, 2001). These studies offer accounts of student-athletes, coaches, and administrators’ experiences around issues of sexual orientation in the athletic environment. Rotella and Murray (1991) claim that any person who is concerned about athletic performance and human ability must be sensitive to the impact of homophobia because of its negative impact on team cohesion. When student-athletes feel accepted as they are, Schlossberg’s (1989) theory of mattering and marginality dictates that a positive and effective transition results. Schlossberg’s work should be of particular interest to athletic administrators and coaches who aspire for their student-athletes to succeed both inside and outside of the athletic arena. Essentially, Schlossberg (1989) asserts that students are more prone to succeed when they feel that others care about them as individuals. Conversely, they may fail or fall short of their potential when they feel marginalized. Rotella and Murray (1991) align with Schlossberg’s (1989) claim, noting the positive effect that all forms of diversity can have on personal achievement and team success. For this research, the following definitions apply. Homophobia is “the affective, irrational dislike of lesbians and gay men" (Hill, 2006, p.4). Homonegativism concerns “learned beliefs and behaviors towards nonheterosexuals and is demonstrated through negative stereotypes, prejudice, and discrimination” (Krane, 1997, p. 145). Heterosexism is “the assumption that the world is and must be heterosexual at the same time that it rationalizes the existing distribution of power and privilege that flows from this assumption,” (Rothenberg, 2007, p.120). If coaches and administrators are aware of how student-athletes perceive sexual orientation, they can be more intentional in choosing co-curricular educational programming specific to the needs of a team. Whereas prior studies address individual experiences with or perceptions about issues related to sexual orientation in athletics, the purpose of this study is to assess specific team climates around sexual orientation.

BACKGROUND Jacobson (2002) considers athletic departments to be the most homophobic environment on the college campus. Wolf-Wendel, Toma, and Morphew (2001) said, “The extent to which those in athletics openly express hostility to gay men and lesbians seems above and beyond that found on other parts of campus” (p.466). In their research, an example of such enmity is highlighted in Gill et al.’s (2006) study of attitudes and sexual prejudice in sport and physical activity. In surveying 150 exercise and sport science students, the Kinsey Scale was utilized to determine the sexual orientation of the sample population. The Kinsey Scale uses a rating continuum from zero to six for respondents to indicate their sexual identity, with zero indicating an exclusively heterosexual identity and six indicating an exclusively homosexual

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identity. In the results, Gill at al. (2006) shared that on the Kinsey Scale question, a number of respondents circled the “zero” multiple times in addition to noting that they were “definitely, exclusively” heterosexual (p.559). The respondents took no such action for any other demographic question. The results reflected an attitude toward gay men and lesbians significantly lower than the other seven inquired upon populations in that study. More specifically, males expressed the most negative attitudes toward gay men. Such findings are consistent with previous research and spark the need for further inquiry regarding climate around issues concerning sexual orientation in athletic environments (Wolf-Wendel, Toma, and Morphew, 2001). Specific examples of homophobia in athletics facilitate a framework that addresses where, how, and finally why such perceptions are fostered. Wolf-Wendel, Toma, and Morphew (2001) found that men and women responded differently when asked about homosexuality in athletics. Additionally, they found that men were more likely to share whether or not they would feel comfortable with a gay team member. Female coaches and student-athletes, however, were well aware of the stereotypes attributed to them specifically as women in athletics and were more likely to address it. Wolf-Wendel, Toma, and Morphew (2001) shared how homophobia directly affected one athletic director’s decision to add a women’s swimming team. When faced with adding another sport to meet the terms of Title IX, “he chose swimming over softball because they did not want to bring a lot of those [lesbian] people” (p.469). Whether or not administrators and coaches are consciously aware of the situation, research reveals that athletic departments are fostering a hostile climate for GLB student-athletes (e.g., Gill et al. 2006; Jacobson, 2002; Rotella and Murray, 1991; WolfWendel, Toma, and Morphew, 2001).

Different Assumptions for Male and Female Athletes When asked about the issue of homosexuality, one male football player stated, “Myself, I can communicate with a gay person but I am not for communicating with them every day and letting them touch me. I don’t want to talk about their sexual tendencies…that is their problem” (Wolf-Wendel, Toma, and Morphew, 2001, p.469). A female student-athlete said that when she was being recruited by her coach, “the coach made it clear that there were no lesbians on the team” (Wolf-Wendel, Toma, and Morphew, 2001, p.469). In their study on stereotypes with 15 female student-athletes, Kauer and Krane (2006) found that the most common stereotype women encountered was the lesbian label. One heterosexual basketball player in their sample noted the following: “One night, I was at a club and a [male basketball player] came up to me, and he was like, ‘aren’t you guys like all gay, why are you guys dancing, shouldn’t you be home” (p.46). A softball player in their research suggested that if she turned down an interested male, then she was automatically assumed to be gay. Furthermore, two student-athletes in the study implied that having short hair only escalated lesbian assumptions. Another softball player in the study, a bisexual, said, “If someone is rude to us and we make a comment back, the first thing out of their mouths is, ‘oh you stupid dyke’…” (Kauer and Krane, 2006, p.46). Essentially, these comments reflect that female athletes have to prove their heterosexuality, often facing dire consequences until attaining heterosexual status. But regardless of their sexual orientation, the homonegativism imparted

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on female student-athletes causes unnecessary frustration and harm and can have significant effects inside and outside of the sporting arena. Baird (2002) says that when a woman outwardly displays athletic characteristics, her femininity becomes suspect. Griffin (1992) emphasizes the fears associated with such perceptions, reporting female athletes’ shame associated with the lesbian image of women’s sports. For males, Jacobson (2002) notes the opposite assumption. Male athletes are presumed to be heterosexual because of their athleticism. In fact, Baird says that for men, “Athleticism and homosexuality have come to be seen as mutually exclusive” (p.33). As a result, there are negative consequences for male athletes as well in that the presumption of heterosexuality marginalizes gay male athletes and fosters a heterosexist, homonegative, and homophobic atmosphere.

Religion and Sport In her book, Strong Women, Deep Closets, Griffin (1998) introduces the conflict that emerges when athletic organizations grant fundamentalist Christian organizations access to coaches and student-athletes. Athletes in Action (AIA) and Fellowship of Christian Athletes (FCA) are two of the more prominent organizations that recruit student-athletes to help spread fundamentalist Christian teachings. In discussing the FCA’s affiliation with the Women’s Basketball Coaches Association, Griffin (1998) says, “By providing a forum for the FCA to distribute antigay literature and air their views on homosexuality, the WBCA and other sports governing bodies who sponsor FCA events provide tacit, if not explicit, approval of discrimination…” (p.118). One example was at the 1996 WBCA national conference when then University of Alabama assistant basketball coach, Cheryl Littlejohn, was on a panel in which she shared her beliefs on the contradictions between homosexuality and the Bible’s teachings (Griffin, 1998). Despite this opposition, the WBCA continues to foster an amicable working relationship with both the FCA and AIA (e.g., WBCA, 2007). More recently, the University of Florida settled a lawsuit with a former lesbian student-athlete who was kicked off the softball team after she alleged that the head coach “created an atmosphere of alienation for anyone not sharing her Christian beliefs and outed other coaches and players as lesbians…” (Buzinski, 2005). These examples expose the impact that fundamentalist religious organizations and coaches can have on student-athletes’ experiences and personal development.

Conceptual Framework This literature review presents the so-often invisible climate around sexual orientation in college athletics. Schlossberg’s theory of mattering and marginality is significant because it offers an appropriate framework for understanding the importance of seeing each studentathlete as an individual. Student-athletes who are marginalized or ‘considered other’ begin to feel as if they do not matter (Krane, 2001; Schlossberg, 1989). One symptom of marginalizing practices that Schlossberg (1989) identifies is that “individuals become ‘obsessed’ with the problem of marginality and this becomes their dominant mode of thinking and behavior” (p.7). Thus, GLB student-athletes in a homonegative environment often feel

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compelled to negotiate their sexual orientation at a time when they simply might want to be validated for their athletic skills or for their multiple identities. It is critical, however, to note that this research presents only one side of this issue. The researcher was unable to find scholarly research demonstrating results from athletic environments that are inclusive of all student-athletes, regardless of sexual orientation.

METHOD Participants and Sampling Participants in this study included 34 male and female student-athletes (all representing the same sport) from an urban, NCAA division one institution in the southwestern portion of the United States. Descriptive statistics were compiled for each respondent’s year in college, race/ethnicity, religion, and religious importance. For this study, the researcher utilized purposive sampling. Babbie (2007) suggests that this sampling method allows the researcher to determine the most appropriate and representative population for the study. Because the researcher was looking to understand student-athletes perceptions about sexual orientation, student-athletes were intentionally sought out as survey respondents for the study.

Instrumentation The student-athletes were administered the Index of Attitudes Toward Homosexuals (IAH). According to Hudson and Ricketts (1980), the IAH is a 25-item survey with five-point likert scale responses that range from strongly agree to strongly disagree. Once the responses to the 25 statements are tallied, total scores will range between zero and 100. The lower the score, the less likely the respondent is to experience anxiety about being in close environment with someone who is homosexual. The inverse is true for those who score higher.

Validity and Reliability To control for respondents’ biases, the survey instrument offers both positive and negative statements about gay people and their social relations. According to Walmyr Publishing (n.d.), the IAH received scores of .90 or better for its reliability and has a “very good to excellent validity coefficient.” Hinkle, Wiersma, and Jurs (2003) consider a reliability value of .90 or better to signify a “very high correlation” (p.109). In a pilot study of 300 college students, Hudson and Ricketts (1980) determined the IAH to have an alpha coefficient of .90. In the same study, the IAH had high content and factorial validity. According to Babbie (2007), “validity refers to the extent to which an empirical measure adequately reflects the real meaning of the concept under consideration” (p.146). A similarity between the Hudson and Ricketts study and this study is that both samples drew from adults in a university setting.

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Procedures Upon consultation with the participating institution’s associate athletic director, the researcher contacted and subsequently met with the men and women’s coaches, at which time any issues concerning the survey were openly addressed. The coaches agreed to allow the student-athletes to be surveyed; however, they asked that the teams be separately surveyed. In addition, one of the coaches specifically requested that the researcher not ask the studentathletes to indicate their sexual orientation in the demographic section. While the researcher honored these requests, future research should examine what environmental factors led to the coaches’ wishes. With permission from the coaches, the researcher met with the two teams separately, where intentions for conducting the study and an informed consent letter were read prior to distributing the surveys. Approval was granted from the Institutional Review Board at the institution’s Office for the Protection of Human Subjects.

RESULTS For all data analyses, the statistical package for the social sciences (SPSS) version 15.0 (2007) was utilized. This study population (N=34) included nearly equal numbers of male (18, 52%) and female (16, 48%) student-athletes, all of whom were in good academic standing. The respondents were mostly first-year (14, 41.2%), second-year (9, 26.5%) and third-year (10, 29.4%) students, with only one (2.9%) fourth-year student in the sample. Seventy-nine percent (27) of the respondents identified as Caucasian/non-Hispanic, with the Hispanic (3, 8.8%) and African American (3, 8.8%) representation totaling approximately 18 percent of the study population. One student (2.9%) self-identified as multi-racial/bi-racial. A majority of the students identified as Catholic (16, 47.1%), with Protestant/Christians (10, 29.4%) being the second largest religious identity amongst the student-athletes. Seven students (20.6%) indicated that they did not identify with any religion at all, and one student (2.9%) circled the “other” option, but did not indicate a specific religion. The majority of the respondents indicated that their religion was either somewhat important (15, 44.1%) or important (12, 35.3%). Nearly equal numbers indicated that religion was either very important (3, 8.8%) or not important at all (4, 11.8%). There were no statistical differences among the athletes according to race/ethnicity, religion, religious importance, or year in college. Utilizing the t-test and a significance level of p < .05, the means of the men’s team and women’s team were significant regarding their level of homophobia. The mean for the men’s team was 54.22 (SD = 15.73, p = .05) and the mean for the women’s team was 41.31 (SD = 14.46, p = .05). According to Hudson and Ricketts (1980), these results suggest that as a group, the men’s team is considered low-grade homophobic and the women’s team is considered low-grade non-homophobic (see Figure 1). More than one-fourth (9) of the respondents indicated that they would feel comfortable being seen in a gay bar. However, additional t-test results indicated that as a team, male student-athletes would be significantly (p = .03) less comfortable ( x = 3.83, SD = 1.20) being seen in a gay bar than female student-athletes (x = 2.88, SD = 1.20).

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Mean Score, By Team 100

Level of Homophobia

90 80 70 60

Men

50

Women

Series1

40 30 20 10 0 Men

Women Gender

Note. 0 = Non-Homophobic, 100 = Homophobic. Figure 1. Mean score comparisons on the Index of Attitudes Toward Homosexuals.

Both the men’s team (x = 2.56, SD = .98) and the women’s team (x = 2.56, SD = 1.26) agreed that they would be comfortable if they learned that their daughter had a lesbian teacher. However, as a team the men indicated that they would be significantly (p = .02) less comfortable (x = 3.72, SD = .96) than the women (x = 2.75, SD = 1.39) if they learned that their son’s male teacher was homosexual.

Frequencies The mean scores reveal that members of both teams indicated that they would be uncomfortable if they found themselves attracted to a person of the same sex (men, x = 4.67, SD = .49; women, x = 3.81, SD = 1.22). Only three student-athletes (8.8 %) said that they would be comfortable, and 30 student-athletes (88.2 %) indicated that they would be uncomfortable if they found themselves attracted to a person of the same sex. In response to the statement, “I would feel comfortable knowing I was attractive to members of the same sex,” as a team (although non-significant), the women leaned toward the “neither agree nor disagree” response (x = 3.13, SD = 1.20) and the men reflected a “disagree” response (x = 4.00, SD = .97). For the statement, “I would feel comfortable if I learned that my best friend of my sex was homosexual,” 70.6 percent (24) of the student-athletes indicated that they either agreed, strongly agreed, or were indifferent and 29.4 percent (10) indicated that they disagreed or strongly disagreed.

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DISCUSSION When the researcher proposed the study to the head coach of the men’s team, the coach suggested that he believed his sport to be one of the more liberal sports. Contrary to his perception, this study confirms previous research findings, which hold that men have negative attitudes towards gay men (e.g., Gill et al., 2006; Wolf-Wendel, Toma, and Morphew, 2001). The mean scores for both the men and women’s teams in this study indicated that studentathletes are comfortable working with both male and female homosexuals in the context of their sport. But as a team, the men are significantly less comfortable working with male homosexuals than they are working with female homosexuals. The male student-athletes hold similar beliefs regarding their future children, particularly their male children. As a team, the female student-athletes indicated that they would be comfortable if they learned that their daughter’s female teacher was a lesbian or if their son’s male teacher was homosexual. These findings raise an important question: Why would male student-athletes be comfortable if they learned that their daughter’s teacher was a lesbian, but uneasy if a male homosexual was teaching their son?

Homophobia: A Symptom of Sexism Pharr (1988) notes that there are two realms where it is acceptable for men to be affectionate with one another: These two exceptions occur in competitive athletics and during wartime crises. Though such expressions might be considered natural after a critical turning point in a game or battle, it is culturally unacceptable to carry such behaviors beyond these two settings. Pharr indicates that when gay men are affectionate towards one another outside of the cultural boundaries, they are considered to not be “real men,” thus denigrating male dominance and superiority over women. Perhaps Pharr’s (1998) point explains why the majority of the men in this study tend to be homophobic towards other men.

Riddle Homophobia Scale The Riddle Homophobia Scale is an attempt to expand the notion of homophobia through the use of different points along a scale (Riddle, 1985). Although the Riddle Scale was not created to complement IAH results but rather to understand levels of homophobia in a social setting, conceptually it appears that the student-athletes in this sample fall across the spectrum of the Riddle Homophobia Scale. The majority of them, however, are between acceptance and support of gay men and lesbians (see Figure 2). Characteristics of the acceptance stage include that there is still something to be accepted. Individuals in this stage might say, “I don’t care if you are gay or lesbian, just don’t shove it in my face.” Individuals in the support stage might not themselves be comfortable with the idea of homosexuality, but they recognize and might work to reverse the inequalities imposed upon on those who do not identify as heterosexual.

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Note. M = men; W = women. Figure 2. Conceptualizing the Riddle Homophobia Scale.

The results suggest that the student-athletes appear to be more at ease with homosexuality when it does not threaten or compromise their own sexual identity. The researcher asserts that movement along the scale will be dependant upon two factors: (1) positive interactions with gay male and lesbian peers and role models, and (2) intentional, departmentally supported educational programming around GLB concerns. Although the men’s team is less accepting than the women’s team, the athletes’ openness in certain stated scenarios and the reasons stated above indicate that great potential exists for positive movement along the Riddle Homophobia Scale.

Discomfort with Personal Identity Although the study population was limited not only in number but also to one team sport, the findings unveil new data regarding how these student-athletes would feel if they found themselves attracted to or attractive to someone of the same sex. These two issues sparked the most angst from the respondents. A significant majority of the student-athletes in this sample either disagreed or strongly disagreed with the statement: I would be comfortable if I found myself attracted to members of my sex. Only three students indicated that they would be comfortable. Secondly, when the table was turned and the survey said, I would be comfortable knowing I was attractive to members of my sex, the women were significantly more comfortable. However, both teams revealed discomfort with these two statements. There are explanations for why the students responded this way. First, most literature focusing on sexual orientation issues in college athletics maintains that the athletic environment is either the most homophobic place on the college campus or that athletes and coaches are tremendously homophobic and heterosexist (e.g., Jacobsen, 2002; Wolf-Wendel, Toma, and Morphew, 2001; Rotella and Murray, 1991). Schlossberg’s (1989) theory of mattering and marginality encompasses the notion that all students, including those who identify as GLB or who are questioning their sexual orientation, are more likely to succeed when their individual identity is valued. This inverse is true for those who feel marginalized. Regardless of one’s sexual identity, the mindset of the student-athletes and behaviors consistent with such beliefs inherently sets up an atmosphere in which the student-athletes might accept homophobia, homonegativism, and heterosexism as the norm and therefore choose not to challenge it. Thus, while they demonstrate that they are comfortable with others’ being GLB, it appears that their identity development, particularly if they might be questioning their sexual orientation, is not fostered in this environment and therefore hindered.

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Limitations Although some of the results are consistent with previous research (e.g., males are more homophobic than females and tend to be less comfortable with male homosexuals), the sample is limited in number and therefore generalizing beyond the scope of this inquiry should be done with caution. Also, the majority of the students surveyed were Caucasian and Christian. The population lacks racial diversity and reflects the cultural encapsulation that these particular student-athletes may experience.

IMPLICATIONS FOR FUTURE RESEARCH AND POLICY The findings are consistent with previous research in that negative perceptions about gay men and lesbians exist in college athletics, with males holding more hostile views towards other gay men (Jacobsen, 2002; Wolf-Wendel, Toma, and Morphew, 2001; Rotella and Murray, 1991). It is important to comprehend why these perceptions continue as well as how they are fostered. In addition, how does environment, particularly with an emphasis on “team”, impact student-athletes’ identity development? Results from this study motivate the question: In team sports, are individual identities marginalized in an effort to encourage student-athletes to conform to perceived team norms? Other areas for inquiry include the difference in perceptions of sexual orientation between religious affiliations and/or between Caucasian students and students of color in college athletics. Inquiry into these populations can help researchers and practitioners understand the origins of perception. For example, Wall and Washington (1995) state that “much of the heterosexism and homophobia that is experienced or felt is justified first by religious teachings” (p.70). Their research focuses particularly on the relationship between the African American community and the Christian Church, noting that “for many years the church has been one of the central places of truth, goodness, and solidarity (p. 70). These statements unveil the complexities concerning homophobia and heterosexism in the African American and religious communities, and in many cases, the intersection of both. In addition, inquiries into athletic environments that are inclusive of GLB students could potentially inform best practices.

CONCLUSION Homophobia, homonegativism, and heterosexism affect individuals no differently than racism, sexism or any other systemic oppression against a minority population. Those sensitive to or on the receiving end of these acts understand the unnecessary harm that it causes. In college athletics, the proactive option is to create a safe and inclusive environment for all student-athletes. In fact, the National Collegiate Athletic Association (NCAA) not only includes sexual orientation as a protected class in its non-discrimination policy, for certification it now requires that member institutions report policies, support opportunities, and educational programs that are in place to ensure a safe environment for student-athletes with diverse sexual orientations (NCAA, 2006).

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Education as a Tool for Learning and Inclusion Townsend (1997) considers education to be one of the greatest impetuses in the struggle to end homophobia. Despite the new NCAA certification guidelines, Gill et al. (2006) says that diversity training and multicultural instruction is minimal for future sport and physical education professionals. The NCAA, the National Center for Lesbian Rights (NCLR), and the Women’s Sports Foundation’s – It Takes a Team Project, each offer tailored educational programming around these issues. Additionally, the National Association for Girls and Women in Sport endorses Barber and Krane’s (2007) recommendations for creating a positive climate for girls and women in sport. Although the road to equality remains uncertain, it appears that the NCAA recognizes the importance of diversity. But for many in college athletics, the topic of sexual orientation remains divisive, if not off limits. Unfortunately, those personally affected are often silenced for fear of losing their job, their friends, or their position on the team. In aspiring to promote the development of all student-athletes, athletic administrators and coaches should intentionally integrate strategies for providing educational opportunities around sexual orientation awareness and understanding.

REFERENCES Babbie, E. (2007). The practice of social research. (11th ed.). Belmont, CA: Thomson Wadsworth Baird, J.A. (2002). Playing it straight: an analysis of current legal protections to Combat homophobia and sexual orientation discrimination in intercollegiate athletics. Berkeley Women’s Law Journal, 31-67. Barber, H., and Krane, V. (2007). Creating Inclusive and Positive Climates in girls and Women’s sport: position statement on homophobia, homonegativism, and heterosexism, 16, 1, 53. Buzinski, J. (2005). Florida settles with lesbian athlete. Retrieved October 27, 2007, from http://www.outsports.com/campus/20040227zimbar disettlement.htm Gill, D.L., Morrow, R.G., Collins, K.E., Lucey, A.B., and Schultz, A.M. (2006). Attitudes and sexual prejudice in sport and physical activity. Journal of Sport Management, 20, 554-564. Griffin, P. (1992). Changing the game: homophobia, sexism, and lesbians in sport. Quest, 44, 251-265. Griffin, P. (1998). Strong women, deep closets: Lesbians and homophobia in sport. Windsor, ON: Human Kinetics. Hill, R.J. (2006). Challenging homophobia and heterosexism: Lesbian, gay, bisexual, Transgender, and queer issues in organizational settings. New Directions for Adult and Continuing Education, 112. Hinkle, D.E., Wiersma, W., and Jurs, S.G. (2003). Applied statistics for the behavioral Sciences. (5th ed.). Boston: Houghton Mifflin

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Hudson, W.W., and Ricketts, W.A. (1980). A strategy for the measurement of homophobia. Journal of Homosexuality, 5, 4, 357–372). Jacobson, J. (2002, November 1). The loneliest athletes. The Chronicle of Higher Education, 49, 10, pA33. Kauer, K.J., and Krane, V. (2006, Spring). “Scary dykes” and “feminine queens”: Stereotypes and female college athletes. Women in Sport and Physical Activity Journal, 15, 1, 42-55. Krane, V. (2001). One lesbian feminist epistemology: Integrating feminist standpoint, queer theory, and feminist cultural studies. The Sport Psychologist, 15, 401-411. NCAA. (2006). Division one athletics certification self study instrument. Retrieved September 3, 2007, from NCAA Web site: http://www.ncaa.org/library/ membership/d1_self-study_instr/2006-07/2006-07_self-study_instrument.pdf Pharr, S. (1988). Homophobia: A weapon of sexism. Iverness, CA: Chardon Press. Riddle, D. (1985). "Homophobia Scale." In Opening Doors to Understanding and Acceptance. In K. Obear and A. Reynolds. Boston: Unpublished essay. Rotella, M., and Murray, M. (1991). Homophobia, the world of sport, and sport psychology consulting. The Sport Psychologist, 5, 355-364. Rothenberg, P.S. (2007). Race, class, and gender in the United States: An integrated study (7th ed.). New York: Worth Publishers. Schlossberg, N.K. (1989). Marginality and mattering: Key issues in building community. New Directions for Student Services, 48, 5-15. Townsend, K.D. (October, 1997). Coaches wanted: lesbians need not apply. Lesbian News, 23, 3, p.24. Wall, V.A., and Washington, J. (1995). Understanding gay and lesbian students of color. In Evans, N.J., and Wall, V.A. (1995). Beyond tolerance: gays, lesbians and bisexuals on campus. Pp. 67-78. Lanham, MD: American College Personnel Association. Walmyr Publishing Company. (n.d.). Assessment Scales. Retrieved September 20, 2007, from http://www.walmyr.com/scales.html. Wolf-Wendel, L.E., Toma, J.D., and Morphew, C.C. (2001). How much difference is too much difference? Perceptions of gay men and lesbians in intercollegiate athletics. Journal of College Student Development, 42, 5, 465-479. Women’s Basketball Coaches Association (2007). WBCA Convention Schedule 2007. Retireived October 27, 2007, from http://www.wbca.org/upload/Convention%20Program% 20Schedule%202007.pdf

Contemporary Athletics Compendium, Volume 3 Editor: James H. Humphrey

ISBN: 978-1-60741-561-9 © 2009 Nova Science Publishers, Inc.

Chapter 19

IDENTIFICATION WITH MULTIPLE SPORTING TEAMS: HOW MANY TEAMS DO SPORT FANS FOLLOW? Frederick G. Grieve1∗, Ryan K. Zapalac2, Amanda J. Visek3, Daniel L. Wann4, Paula M. Parker5, Julie Partridge6 and Jason R. Lanter7 1

Western Kentucky University, Bowling Green, Kentucky, USA 2 Sam Houston State University, Huntsville, Texas, USA 3 The George Washington University, Washington, DC, USA 4 Murray State University, Murray, Kentucky, USA 5 East Stroudsburg University, East Stroudsburg, Pennsylvania, USA 6 Southern Illinois University, Carbondale, Illinois, USA 7 Kutztown University, Kutztown, Pennsylvania, USA

ABSTRACT The current study examined the identification with multiple sport teams by sport fans, as a potential means to maintain these positive benefits of identification by switching identification to another sports team. Sport fans were predicted to report following fewer teams closely compared to moderately, and fewer teams moderately compared to casually. Additionally, sport fans were predicted to be higher identified with teams they followed closely compared to those teams moderately followed, and more identified with moderately followed teams compared to teams they followed casually. The first hypothesis was not supported, as participants reported following more teams closely compared to moderately and casually. The second hypothesis was supported, as participants reported being more identified with the teams they closely follow compared to the moderately and casually followed teams. Implications of these findings for sport researchers and sport marketers are discussed.

∗

Please address correspondence to: Frederick G. Grieve, Department of Psychology, Western Kentucky University, 1906 College Heights Blvd, #21030. Bowling Green, KY 42101-1030. [email protected]

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Identification with a local sport team has been shown to have important psychological consequences (Wann, 2006). Sport fans who highly identify with a team, or who feel a strong psychological connection with the team (Wann and Branscombe, 1993), report higher levels of psychological health, including lower levels of loneliness (Wann, Dimmock, and Grove, 2003; Wann, Martin, Grieve, and Gardner, in press), higher levels of social self-esteem and social well-being (Lanter and Blackburn, 2004), lower levels of depression, alienation, and experiences of negative emotion (Wann et al. 2003), higher levels of openness, conscientiousness, and extroversion (Wann, Dunham, Byrd, and Keenan, 2004), and lower levels of fatigue, anger, tension, and confusion (Wann, Inman, Ensor, Gates, and Caldwell, 1999). These benefits are derived through the social connections, or social support, highly identified fans experience vis a vis their identification (Wann, 2006). However, in order to benefit from being strongly, or highly, identified with a local sports team, individuals must cope with team losses. Fans who are not highly identified with a team are not affected by a team loss as the loss is not meaningful to them (Branscombe, Ellemers, Spears, and Doosje, 1999). Highly identified fans, on the other hand, are often strongly affected by team losses, as noted by the intense negative emotional reactions many have to a team loss (Bernhardt, Dabbs, Fielden, and Lutter, 1998). Thus, they have a need to cope with a team loss in order to continue to receive the psychological and physiological benefits of team identification. There are a number of coping mechanisms available for highly identified fans. One coping method is through derogating the outgroup (Wann, 2006). Fans of a team that loses are more likely to become angry with game officials, members of the opposing team, or even fans of the opposing team (Rubin and Hewstone, 1998). Another coping method is through Cutting Off Reflected Failure (CORFing; Snyder, Lassegard, and Ford, 1986), in which fans emotionally and psychologically distance themselves from teams after a team failure. The opposite of CORFing is Basking In Reflected Glory—BIRGing (Cialdini et al., 1976); thus, fans often refer to “us winning” and “them losing” when discussing team performances. Finally, fans can Cut Off Future Failure (COFF; Wann, Hamlet, Wilson, and Hodges, 1995), in which they do not become overly excited about a team’s current performance due to the possibility of poor performance in the future. One form of CORFing (i.e., distancing oneself from a team) is to change the cognitive focus from one team to another. For example, if a fan is identified with two National Football League teams, such as the Tennessee Titans and the Detroit Lions, and one of these teams were to lose on a given Sunday while the other team won, that fan could, conceivably, change focus from the losing team to the winning team. There is some data to suggest that this phenomenon occurs. Grieve, Wann, and Zapalac (in press) presented participants with a vignette describing the end of the season and asked participants to indicate to what extent they would perform seven different activities. Several of the activities involved changing focus from the losing team to another team, such as rooting for the team that defeated their favorite team or changing their focus from one sport to another. Participants were likely to indicate that they would participate in many of these activities. However, in order for this switch in focus to take place, sport fans must follow more than one team. Such a phenomenon seems likely. With the expansion of the competitive seasons in virtually all sports (e.g., baseball’s spring training begins in February while the World Series has been pushed back to late October) and the creation of new sport leagues (e.g., Arena Football League, Major League Soccer, Women’s National Basketball Association), there are

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multiple sport seasons occurring concurrently. It seems logical, then, that sport fans would be following, and would be identified, with more than one team at any given time. However, to date, there is no empirical support for this hypothesis. Therefore, the present study was designed to address the gap in this area of the literature. Two hypotheses were formulated. First, it was hypothesized that participants would report following fewer teams very closely than they would report following teams either moderately or casually; further, participants would report following fewer teams moderately than casually. Second, it was hypothesized that identification would be strongest for teams that participants follow closely than for teams they follow moderately or casually; further, participants would report higher identification for teams they follow moderately than casually.

METHOD Participants Participants for this study included 986 college-age participants from seven different universities in the eastern United States. Participants for the study included 445 women (45.1%) and 538 men (54.6%), while 3 participants (0.3%) did not indicate gender. In terms of racial/ethnic background, 810 participants (82.2%) identified themselves as Caucasian, 113 (11.5%) identified themselves as African American, 18 (1.8%) identified themselves as Asian American, 2 (0.2%) identified themselves as American Indian, 3 (0.3%) identified themselves as Pacific Islander, 20 (2.0%) identified themselves as Hispanic, and 2 (0.2%) people did not indicate race/ethnicity. The mean age of the sample was 20.74 years (SD = 2.89) and the mean education level fell at the sophomore year of college (M = 14.23 years; SD = 1.33).

Measures Demographics. Participants completed a short demographic survey that included questions about age, race, gender, education level, and home town. Team Survey. Participants also completed three questions that asked them to list the teams that they follow at different levels (i.e., closely, moderately, and casually). Specifically, the first question asked them to list the teams that they follow closely (e.g., know the teams’ records, can name most of the players on the teams). The second question asked participants to list the teams that they follow moderately (e.g., generally know if the teams are playing well or not, but not the exact record; know some, but not all of the players on the teams). The final question asked participants to list all of the teams that they follow casually (e.g., are interested in having the teams do well, but do not actively follow them; may look up the teams’ records every once in a while; know one or two players on the team). In the cases of all three levels of followship, the teams cited could have been from multiple levels of competition (i.e., collegiate, professional, etc.). Thus, participants were not directed to focus their responses on one specific level, but were asked to take a more holistic view on the teams they choose to follow closely, moderately, and casually.

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Team Identification. The Sport Spectator Identification Scale (SSIS; Wann and Branscombe, 1993) was used to measure participants’ degree of identification with their selfreported sport teams. The SSIS contains seven self-report items rated on an eight-point Likert-type scale (1-low, 8-high; scale anchors vary depending on the item). Higher scores indicate higher levels of team identification. The SSIS has been shown to have sound psychometric properties (Wann, Melnick, Russell, and Pease, 2001) in a wide range of cultural settings (e.g., Theodorakis et al., 2006; Uemukai et al., 1995). Internal consistency scores (e.g., Cronbach’s alpha) for the SSIS are consistently at or greater than .90 and the scale has documented test-retest reliability as well as criterion validity (Wann and Branscombe, 1993).

Procedure Following Institutional Review Board (IRB) approval participants were recruited to voluntarily participate in the study. After giving informed consent, participants completed the demographic questionnaire followed by the Team Survey. Participants were then instructed to select the first team they listed from the Team Survey for each of the three different levels (i.e., closely, moderately, casually) and asked to complete the SSIS for each team. The SSIS was thus completed once each for the first team listed in the closely, moderately, and casually lists. Participants were then debriefed and released. Data collection sessions lasted approximately 15 to 20 minutes.

RESULTS Cronbach’s alpha was calculated for the SSIS. Alpha reliability coefficients for the SSIS were consistently high across all different measurement points. The alpha for the SSIS for teams participants followed closely was α = .88; for teams participants followed moderately, α = .90; and for teams that participants followed casually, α = .92. Participants reported a large range of teams that they followed closely, from 0 teams to 20. They reported following from 0 to 22 teams moderately, and from 0 to 11 teams casually. Ranges for the SSIS at all levels (closely, moderately, and casually) ranged from 7 to 56. To evaluate the first hypothesis, a series of paired t-tests was conducted using the number of reported teams at each level as the dependent measure. Because three different t-tests were performed, a Bonferroni correction (Pedhazur, 1982) was used to decrease the chance of a Type I error. Therefore, alpha was set at p < .016. Results of the paired t-tests indicated that participants reported following significantly more teams closely (M = 2.83, SD = 2.01) than they did moderately (M = 2.20, SD = 1.58), t (953) = 9.59, p < .001, d = .40. Results also indicated that participants reported following significantly more teams closely (M = 2.80, SD = 2.02) than they did casually (M = 1.61, SD = 1.13), t (917) = 17.57, p < .001, d = 1.08. Finally, results indicated that participants reported following significantly more teams moderately (M = 2.23, SD = 1.60) than they did casually (M = 1.61, SD = 1.13), t (917) = 12.20, p < .001, d = .52. Please note that the different Ns resulted because some participants

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did not list a team under one of the three categories, and, therefore, there were different numbers of participants for each of the analyses. To evaluate the second hypothesis, a series of paired t-tests was conducted using reported identification with teams at each level as the dependent measure. Again, a Bonferroni correction was calculated to decrease the change of Type I error and alpha was set at p < .016. As shown in Figure 1, results indicated that participants were significantly more identified with teams they followed closely (M = 46.71, SD = 7.98) than with teams they followed moderately (M = 31.17, SD = 10.36), t (873) = 39.94, p < .001, d = 1.50. Results also indicated that participants reported that they were significantly more identified with teams they followed closely (M = 46.71, SD = 7.99) than with teams they followed casually (M = 20.33, SD = 10.84), t (809) = 58.06, p < .001, d = 2.43.

50 40 30 20 10 0 Follow Close

Follow Moderately

Follow Casually

Figure 1. Reported level of team identification, as measured by the SSIS, for the first team that fans reported to follow closely, moderately, and casually.

Finally, results indicated that participants reported that they were significantly more identified with teams that they followed moderately (M = 30.93, SD = 10.15) than teams they followed casually (M = 20.39, SD = 10.81), t (840) = 26.54, p < .001, d = .97.

DISCUSSION The present study was conducted to better understand the degree to which fans follow and identify with multiple sport teams. Specifically, it was hypothesized that: (1) participants would report following fewer teams closely than they would report following either moderately or casually; with participants reporting following fewer teams moderately than casually; and (2) team identification would be strongest for teams participants follow closely than for teams they follow moderately or casually, with participants reporting higher identification for teams they follow moderately than casually. Interestingly, results did not support the first hypothesis. In fact, the results were the exact opposite of what was proposed: fans reported following more teams closely and fewer teams moderately and casually. Results would suggest that sport fans in this sample allocate

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most of their cognitive resources to following teams closely than to following teams moderately or casually. This could also be a matter of time and resources. Meaning, individuals do not have an infinite amount of time to devote to following all teams of interest. Therefore, they may decide to allocate their time to following the teams with which they are highly identified and those that are most meaningful to them. Any remaining time is then spent following teams that are not as meaningful to them. The results indicated that people in this sample follow approximately three teams closely, two teams moderately, and one and a half teams casually. Thus, in terms of being able to switch focus (or identification; see Grieve et al., in press), results would suggest that individuals do have some latitude. For instance, if one of the teams they follow closely is performing poorly, they can CORF with that team by switching their focus to another team. However, this coping strategy only works if the teams they follow are in-season and competing at the same time (i.e., both teams are football teams or one team is a football team and one is a basketball team). If the teams are not active at the same time (i.e., one team is a football team and another is a baseball team, or what could be termed “dormant identification”), the switching strategy becomes more difficult to perform. Future research should examine whether sport fans are able to switch focus from one sport season to another. These findings may also further explain findings by Hirt and colleagues (1992). In this study, the authors found that individuals that strongly identified with a sport team can often find it difficult to dissociate with a team when that team is unsuccessful, thus impacting their perceived self-competencies and self-esteem. This may connect with the findings of the current study through the number of teams that participants follow closely. For instance, by utilizing the switching strategy, or CORFing with the unsuccessful team, the participant can then alter focus to another one of the teams they follow closely, thus protecting their own self-esteem and positively impacting their own psychological health and well-being (Wann, 2006). Future research should examine this switching strategy in more depth to determine: (a) whether a relationship exists between the performance of the team, (b) the number of teams a fan is highly identified with, and (c) the point at which they switch their focus to another one of “their” teams. Further, the finding that fans report high levels of identification with multiple teams has interesting implications for Wann’s (2006) Team Identification – Social Psychological Health Model. According to Wann’s framework, fans acquire important social connections via their identification with sport teams which, ultimately, can facilitate social well-being. Empirical support for the positive relationship between team identification and well-being in strong, as noted previously (e.g., Lanter and Blackburn, 2004; Wann, Martin et al., in press; Wann et al., 2003). However, Wann, Keenan, and Page (in press) recently found that college students with high levels of identification with two of their university’s sport teams reported a more positive well-being profile than those identifying strongly with only one team (the most negative profiles were reported by persons with low levels of identification with both teams). Thus, fans may reap additional benefits by identifying strongly with multiple teams. The current research indicates that this benefit may be available for many fans because such a large proportion of the current sample reported strong attachments to multiple teams. Results supported the second hypothesis. Participants reported being more highly identified with the teams that they follow closely than teams they follow moderately or casually. While it is tempting to state that identification precedes level of following, this relationship is correlational in nature. For instance, perhaps fans begin following a team

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closely and through doing so later develop an identification with the team. This would be consistent with what Kolbe and James (2000) describe as an internalization process whereby sport fans come into contact with the team before becoming identified with it. Regardless of how the team identification occurs, the differences between levels of identification were highly meaningful. The effect size difference (Cohen’s d) for team identification between teams fans follow closely and teams fans follow moderately and casually were on the order of one to two standard deviations difference. While these findings may seem to be common sense (e.g., of course people are going to be more highly identified with teams that they follow more closely), this is the first empirical evaluation of different levels of identification. Most sport fan research (i.e., Grieve et al., in press; Kolbe and James, 2000; Lanter and Blackburn, 2004; Wann et al., 2004; Wann and Grieve, 2005) has examined identification with a single team. So, while it was anticipated that people would identify at different levels with teams they follow at differential rates, this question had not been empirically evaluated to date.

Practical Implications These findings also have some rather significant marketing implications. For example, the findings of the current study suggest that not only are fans highly identified with the teams they follow closest, but they are also identifying with additional teams, which is of significant interest. This propensity of a fan to be highly identified with many teams provides the sport marketer with an accessible population to help drive revenue generation as opposed to the fan that is only identified with one team. In such cases, Mahony, Madrigal, and Howard (2000) suggest that reinforcement strategies should be utilized in which the fan’s high level of identification is maintained and cultivated in order to increase yield and promote brand loyalty. The authors suggest that economic incentives and intrinsic rewards can be effective marketing tactics to help maintain consumer loyalty to the team the person is identified with. This could be an especially useful approach when a fan is identified with two teams that compete in a similar league or geographical area. For example, a highly identified fan of both the New York Jets of the National Football League (NFL) and the New York Mets of Major League Baseball (MLB) could be influenced by a marketing approach that provides certain economic incentives that the other team might not. As a result, the fan may choose to become a more dedicated consumer of the team that has made a more demonstrative effort to reinforce their identification, which can then result in other ancillary benefits such as decreased price sensitivity and decreased performance-outcome sensitivity (Sutton, McDonald, Milne, and Cimperman, 1997). Through such marketing tactics, attendance and consumption patterns often increase resulting in additional revenue for the sport organization(Mullin, Hardy, and Sutton, 2007). It is also interesting to note that although respondents were not as highly identified with the other teams they followed less frequently (i.e., teams they followed ‘moderately’ and ‘casually’), they still listed them as teams of interest. This could be a rather visible example of the escalator concept (Mullin, Hardy, and Sutton, 1993; 2007) in practice. Briefly, the escalator concept often classifies sport spectators and fans into three broad categories (with further classification provided within certain categories) based on their attendance and participation patterns. These three categories include: (a) nonconsumers (i.e., nonaware,

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minsinformed, and aware), (b) indirect (or media) consumers, and (c) consumers (i.e., light, medium, and heavy). The level of attendance and participation increases along a linear path with nonconsumers being classified as those that choose not to participate or attend while the heavy consumer is very active. It could be that participants in the sample are being “moved” up or down the escalator based on the organization’s marketing efforts. Unfortunately, where participants in the current study may be classified on the “escalator” cannot be discerned because factors such as attendance, participation, and purchasing variables were not measured. Further, all participants were college students, and they may differ in their identification with sport teams and consumption of sporting events than people who are not college students. However, the findings of the present study do provide an exciting foundation for future research to examine consumption patterns for spectators and fans that follow multiple teams closely, moderately, and casually. Future research such as this may assist sport marketers in devising marketing tactics that would help move the moderate or casual fan up the sport consumer escalator and potentially expand the customer base for a given franchise or team. In addition, future research could focus on seasonal factors related to sport followship and identification. Such research may focus on whether a sport consumer shifts their identification to another team that is currently “in season” or if they maintain the same level of interest even when their team is not engaged in competition (i.e., “offseason”).

REFERENCES Bernhardt, P. C., Dabbs, J. M., Fielden, J. A., and Lutter, C. D. (1998). Testosterone changes during vicarious experiences of winning and losing among fans at sporting events. Physiology and Behavior, 65, 59-62. Branscombe, N. R., Ellemers, N., Spears, R., and Doosje, B. (1999). The context and content of social identity threat. In N. Ellemers, R. Spears, and B. Doosje (Eds.), Social identity (pp. 35-58). Oxford, UK: Blackwell. Cialdini, R. B., Borden, R. J., Thorne, A., Walker, M. R., Freeman, S., and Sloan, L. R. (1976). Basking in reflected glory: Three (football) field studies. Journal of Personality and Social Psychology, 34, 366-375. Grieve, F. G., Wann, D. L., and Zapalac, R. K. (in press). Sport fans’ responses to the end of the season. International Journal of Sports Marketing and Management. Hirt, E., Zillmann, G., Erickson, G.A., and Kennedy, C. (1992). Costs and benefits of allegiance: Changes in fans’ self-ascribed competencies after team victory versus defeat. Journal of Personality and Social Psychology, 63(5), 724-738. Kolbe, R. H., and James, J. D. (2000). An identification an examination of influences that shape the creation of a professional team fan. International Journal of Sports Marketing and Sponsorship, 2, 23-37. Kolbe, R. H., and James, J. D. (2003). The internalization process among team followers: Implications for team loyalty. International Journal of Sport Management, 4, 25-43. Lanter, J. R., and Blackburn, J. Z. (2004, September). The championship effect on college students’ identification and university affiliation. Paper presented at the annual meeting of the Association for the Advancement of Applied Sport Psychology, Minneapolis, MN.

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Mahony, D. F., Madrigal, R., and Howard, D. (2000). Using the Psychological Commitment to Team (PCT) Scale to segment sport consumers based on loyalty. Sport Marketing Quarterly, 9(1), 15-25. Mullin, B.J., Hardy, S., and Sutton, W.A. (1993). Sport marketing. Champaign, IL: Human Kinetics. Mullin, B.J., Hardy, S., and Sutton, W.A. (2007). Sport marketing (3rd ed.) Champaign, IL: Human Kinetics. Pehazur, E. J. (1982). Multiple regression in behavioral research: Explanation and prediction (2nd Edition). Ft. Worth, TX: Holt, Rinehart, and Winston. Rubin, M., and Hewstone, M. (1998). Social identity theory’s self-esteem hypothesis: A review and some suggestions for clarification. Personality and Social Psychology Review, 2, 40-62. Snyder, C. R., Lassegard, M., and Ford, C. E. (1986) Distancing after group success and failure: Basking in reflected glory and cutting off reflected failure. Journal of Personality and Social Psychology, 51, 382-388. Sutton, W. A., McDonald, M. A., Milne, G. R., and Cimperman, J. (1997). Creating and fostering fan identification in professional sports. Sport Marketing Quarterly, 6(1), 15-22. Theodorakis, N. D., Vlachopoulos, S. P., Wann, D. L., Afthinos, Y., and Nassis, P. (2006). Measuring team identification: Translation and cross-cultural validity of the Greek version of the Sport Spectator Identification Scale. International Journal of Sport Management, 7(4), 506-522. Uemukai, K., Takenouchi, T., Okuda, E., Matusmoto, M., and Yamanaka, K. (1995). Analysis of the factors affecting spectators’ identification with professional football teams in Japan. Journal of Sport Sciences, 13, 522. Wann, D. L. (2006). Understanding the positive social psychological benefits of sport team identification: The Team Identification – Social Psychological Health Model. Group Dynamics: Theory, Research, and Practice, 10, 272-296. Wann, D. L., and Branscombe, N. R. (1993). Sports fans: Measuring degree of identification with the team. International Journal of Sport Psychology, 24, 1-17. Wann, D. L., Dimmock, J. A., and Grove, J. R. (2003) Generalizing the Team Identification– Psychological Health Model to a different sport and culture: The case of Australian rules football. Group Dynamics: Theory, Research, and Practice, 7, 289-296. Wann, D. L., Dunham, M. D., Byrd, M. L., and Keenan, B. L. (2004) The five-factor model of personality and the psychological health of highly identified sport fans. International Sports Journal, 8, 28-36. Wann, D. L., and Grieve, F. G. (2005). Biased evaluations of in-group and out-group spectator behavior at sporting events: The importance of team identification and threats to social identity. The Journal of Social Psychology, 145, 531-545. Wann, D. L., Hamlet, M. A., Wilson, T., and Hodges, J. A. (1995). Basking in reflected glory, cutting off reflected failure, and cutting off future failure: The importance of identification with a group. Social Behavior and Personality: An International Journal, 23, 377-388. Wann, D. L., Inman, S., Ensor, C. L., Gates, R. D. and Caldwell, D. S. (1999). Assessing the psychological well-being of sport fans using the Profile of Mood States: The importance of team identification. International Sports Journal, 3, 81-90.

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Wann, D. L., Keenan, B., and Page L. (in press). Testing the Team Identification – Social Psychological Health Model: Examining non-marquee sports, seasonal differences, and multiple teams. Journal of Sport Behavior. Wann, D. L., Martin, J., Grieve, F. G., and Gardner, L. R. (in press). Social connections at sporting events: Attendance and its positive relationship with state social psychological well-being. North American Journal of Psychology. Wann, D. L., Melnick, M. J., Russell, G. W., and Pease, D. G. (2001). Sport fans: The psychology and social impact of spectators. New York: Routledge Press.

Contemporary Athletics Compendium, Volume 3 Editor: James H. Humphrey

ISBN: 978-1-60741-561-9 © 2009 Nova Science Publishers, Inc.

Chapter 20

MOTIVATIONS OF INTERNATIONAL STUDENT-ATHLETES TO PARTICIPATE IN INTERCOLLEGIATE ATHLETICS Stephanie G. Jones1, Gi-Yong Koo1, Seungmo Kim1, Damon Andrew2 and Robin Hardin1∗ 1

University of Tennessee, Knoxville, Tennessee, USA 2 Troy University, Troy, Alabama, USA

ABSTRACT The purposes of this study were to (a) explore motives of international studentathletes who come to the United States to participate in intercollegiate athletics, and (b) examine differences in motives of international student-athletes based on selected sociodemographic attributes (e.g., gender, types of scholarship received, types of sports participation and region of the world). An exploratory factor analysis revealed four motivation factors: intercollegiate athletics attractiveness, school attractiveness, desire for independency, and environmental attractiveness. Data analysis indicated differences in motivation factors based on types of sports participation and region of the world. The study will help coaches and athletic administrators understand international studentathletes’ motivational factors, which play a critical role in recruiting these international student-athletes. Knowing why an international student-athlete wants to participate in intercollegiate athletics in the United States will aid coaches in developing specific recruiting plans to attract these athletes. This information will also assist coaches in satisfying those needs once the student-athlete is competing in intercollegiate athletics.

The number of international athletes has increased substantially in Major League Baseball (MLB), the National Hockey League (NHL), and the National Basketball ∗

Correspondence to: Robin Hardin, Ph.D. University of Tennessee, 1914 Andy Holt Avenue, 335 HPER Bldg. Knoxville, TN 37996-2700. (865) 974-1281 Office. (865) 974-8981 Fax ; E-mail : [email protected]

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Association (NBA) over the past decade. The MLB commissioner announced that the opening day of the 2007 MLB season featured 246 international players on the 25-man rosters of the 30 MLB teams. The number indicated that 29% of the MLB players were not born in the United States, which resulted in a 2% increase compared to the 2006 season. More surprisingly, 3,098 international baseball players accounted for 46.2% of the players in the Minor League Baseball (MiLB) (National pastime takes on international flavor, 2007). There were 82 international players in the NBA on the 2005-06 season rosters, accounting for 19% of the total players. This was an 8.9% increase compared to the 2000-01 season (NBA Players from around the World, 2006). The NHL had approximately 30% of its 720 players born outside North America for the 2007-08 season (Burnside, 2007). Professional sports teams have pursued competitiveness through recruiting the most talented international athletes who are performing at high levels in their own countries’ leagues. The phenomenon of recruiting international athletes to improve team performance is not limited to professional sports. It has occurred and become common in intercollegiate athletics and even high school sports in the United States (Ridinger, 1996). According to the latest National Collegiate Athletic Association (NCAA) report on international student-athletes, which was published in 1996, the number of international student-athletes at all NCAA institutions increased from 6,883 to 8,851 and the average number also increased from 8.55 students per institution to 10.52 between 1991-1992 and 1995-1996. Even though updated data regarding the number of international student-athletes has not been reported since 1996 by the NCAA, it is easily noticed that the number of international student-athletes has drastically increased in various sports for the past 10 years. In some sports like tennis and soccer, the roles of international student-athletes have become extremely important for their team’s performance due to their superior talent over domestic athletes. The Intercollegiate Tennis Association (ITA) reported in April 2004, that 65 of America’s best 100 college tennis players were international student-athletes, and some universities, such as Baylor, Virginia Commonwealth, and Tulane, rarely have American tennis players in their programs (Greviskes, 2004). Given the situation highlighted above, international student-athletes are without a doubt an integral part of American intercollegiate sports. However, there have been only few studies (Bale, 1991; Berry, 1999; Ridinger, 1996; Ridinger and Pastore, 2000a; Ridinger and Pastore, 2000b; Ridinger and Pastore, 2001; Stidwill, 1984) in the sport management literature on the issue of international student-athletes. The present study empirically attempts to examine influencing factors of international student-athletes in deciding to attend colleges in the United States to compete in intercollegiate athletics.

INTERNATIONAL STUDENT-ATHLETES The first appearance of international student-athletes in intercollegiate athletics in the United States occurred when a small number of Canadian student-athletes participated in track and field competitions in the early 1900s (Ridinger and Pastore, 2000a). However, the recruitment of international student-athletes was uncommon and only limited to Canadian athletes in a small number of sports until World War II (Stidwill, 1984). Some sport-oriented universities began to have a growing interest in recruiting international student-athletes in the 1960s and 1970s. African countries were targeted because of the success those athletes had in

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track and field, and universities won several national championships due to the dominant performance of African runners (Stidwill, 1984). As many universities rushed to recruit African runners to be competitive in track and field, especially long distance events, 35% of the men’s NCAA track and field athletes were athletes from African countries by 1978 (Hollander, 1980). The successful stories of these international student-athletes naturally stimulated coaches and institutions who simply wanted to be competitive against other opponents to recruit international student-athletes in not only track and field, but also in sports such as golf and tennis (Berry, 1999). Usually, the primary reason or benefit that coaches prefer to recruit international student-athletes is that international student-athletes have experience at higher levels of competitions in their countries before they come to the United States. In some sports, their outstanding abilities and experiences in their early competitions are good enough to take the team to a championship level (Ridinger & Pastore, 2001). Some coaches also insist that international student-athletes are more mature and work harder for their goals than American athletes. Thus, the attitudes of international studentathletes could become an example for American student-athletes (Asher, 1994). Meanwhile, there are also some controversial issues surrounding the recruiting of international student-athletes. First, some people argue that domestic students and international students are not on a level playing field. European athletes playing tennis or soccer have been trained by club sport systems which often provide much higher levels of competition. These student-athletes end up dominating games and matches with better skills and experiences over United States student-athletes, who primarily had scholastic-level experiences. Second, the eligibility issue of foreign student-athletes has received attention because many European athletes have played in professional leagues while they were participating in the club sport system. In the early 1960s, student-athletes in their late 20s or even 30s from other countries were competing in intercollegiate competitions against young domestic athletes who had just graduated from high school (Ridinger, 1996). This situation initiated arguments on age limits of student-athletes and about allowing individuals play in the NCAA if they had been playing professionally. Finally, international student-athletes take athletic scholarships away from United States students. For example, 30% of tennis scholarships go to international student-athletes (Greviskes, 2004). Even though the NCAA has yet to consider any restrictions on the amount of grant funding for international studentathletes, some athletic associations have tried to protect domestic student-athletes by instituting a rule to limit amount of grant funding toward international student-athletes. For example, the National Junior Collegiate Athletic Association (NJCAA) instituted a rule that no more than 25% of grant funding should be awarded to international student-athletes in 1991 (Ridinger & Pastore, 2001).

MOTIVES OF INTERNATIONAL STUDENT-ATHLETES Little research on international student-athletes in American intercollegiate athletics has been conducted, although the number of international student-athletes have continuously increased and played vital roles throughout various collegiate sports. One topic of study has been to investigate the motivations of international student-athletes to participate in intercollegiate athletics in the United States (Bale, 1991; Berry, 1999; Stidwill, 1984). Most

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studies (Bale, 1991; Berry, 1999; Ridinger, 1996; Stidwill, 1984) found that one of the primary motivations of international student-athletes who come to American colleges is to gain an education via a scholarship opportunity. International student-athletes are attracted by the fact that they can become educated, while still participating in sport activities through athletic scholarships in the United States (Ridinger, 1996). Unlike other countries, the United States has developed a unique educational system offering opportunities to gain both academic and athletic achievement simultaneously. Stidwill (1984) researched track and field athletes in his study and found that having the opportunity of experiencing high levels of competition and the well-organized training by expert coaches in American colleges were motives for coming to American colleges, as well as gaining an education. His findings could be supported by the fact that athletic programs in American colleges provide better facilities and coaching staffs that international athletes are not able to experience in their countries. The endless support from the institution is attractive to international student-athletes. In addition, Stidwell found no differences between domestic student-athletes and international student-athletes in terms of being motivated by receiving an education and gaining experience and training. Bale (1991) studied 200 swimmers and track athletes from Britain, Sweden, and the Netherlands to examine the stressors that might lead an international athlete to come to the United States and participate in an NCAA athletics program. Bale found that international student-athletes wanted to come to the United States for their athletic career because of poor training facilities, lack of quality coaches, and limited training time in their own countries. He also found that the student-athletes were also attracted by the level of competition in the United States, and that American culture and lifestyle had an impact on the decision. Other significant factors identified by Bale were the influence of friends in the United States, the sport and academic reputation of the college, and the influence of coaches. Berry (1999) examined these motivational factors using 61 international student-athletes from 11 different sports and three different regions of the world. While the previous two studies only focused on one or two sports to understand the motivations of international student-athletes, Berry collected data from various sports. He classified the motivational factors into four categories: athletic, academic, influence-related, and social/environmental. Berry compared the means of those factors and concluded that the athletic motive was most important over academic, influence-related, and social/environmental motives. Male and female student-athletes generally showed similar patterns. In addition, Berry found that student-athletes showed different patterns of motivations based on their region of the world. For example, South African students reported higher social/environmental factors and academic reasons, while English students were motivated to hone their athletic skills in the United States. Ridinger and Pastore (2000b) proposed a framework to identify factors associated with international student-athletes’ adjustment to American colleges. In the strict sense, the study was not about the motivations of why international student-athletes come to the United States, but the motivations of international student-athletes from previous motive studies were utilized to interpret the findings by the authors in this study. Five adjustment elements were proposed by the researchers: academic adjustment, athletic adjustment, social adjustment, personal-emotional adjustment, and institutional adjustment. Ridinger and Pastore (2000b) also compared the level of adjustment to college among three sub groups in their follow-up study: international student-athletes, international non student-athletes and domestic student-

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athletes. The authors found international student-athletes reported the highest mean score among sub groups in terms of academic and other adjustments to college. International student-athletes tend to work hard academically because they primarily have chosen to come to the United States in order to receive an education with financial support while participating in their chosen sport (Bale, 1991; Ridinger, 1996; Stidwill, 1984). Even though previous research had identified possible motivations of international student-athletes to migrate into the United States, there were several limitations. First, most studies, except one (Berry, 1999), only examined one or two specific sports, and these motives may be sport-specific. Second, there was no research including all regions of the world due to the small number of international student-athletes in their study samples. Third, much of the research that has been conducted on the motivations of international studentathletes is quite dated and may not accurately reflect the motives of today’s athletes. Finally, the methods that the studies utilized to analyze their data strongly relied on descriptive statistics, which are limited in their ability to examine statistical differences among group, so it is difficult to say that their findings really existed as they concluded. Therefore, the primary purposes of this study were to extend past research by measuring international studentathletes’ motivations to come to the United States to participate in intercollegiate athletes, and to expand the knowledge of international student-athletes by examining differences in motives according to socio-demographic attributes. The current study attempted to recruit a large number of international student-athletes from three NCAA Division I – Football Bowl Subdivision conferences and incorporate more sophisticated statistical techniques to examine motivations in terms of gender, type of sport, and regions of world origin. The following research questions were proposed in relation to the foregoing discussion. 1. Why do international student-athletes come to the United States to participate in intercollegiate athletics? 2. Are there differences in motives of international student-athletes to come to the United States to participate in intercollegiate athletics based on selected sociodemographic attributes?

METHODOLOGY Instrument Development The questionnaire for the current study consisted of two parts. The first part consisted of seven demographic questions including age, gender, region of world origin and scholarship status. The second part consisted of 29 items that may have contributed to the international student-athletes’ decision in coming to the United States in order to participate in intercollegiate athletics. The researchers included selected items from a previous survey by Berry (1999) and added related items based on qualitative interviews with international student-athletes in order to attempt to get a wider range of motivation items on the questionnaire. All of Berry’s original items were included in a pilot test to check for the validity of the questionnaire. Based on participant feedback from the pilot study, some of those items were deleted, thus leaving 29 items for motivational factors. The items for the

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motivations were developed with seven point Likert-type scales anchored by “Not important at all” (1) and “Extremely important” (7).

Participants and Survey Procedure The sample for this study consisted of international student-athletes at institutions from three NCAA Division I – Football Subdivision conferences. International student-athletes were identified on the rosters of the athletic teams of the particular institutions chosen for study. Internet survey methodologies were incorporated in this study (Dillman, 2000). E-mail addresses for 397 international student-athletes from the three conferences were obtained through their institutes’ Web sites. E-mails containing the link to the online survey and related instructions were sent to the selected sample. E-mail reminders were sent three times, five days apart, to the sample. The response was rate 53.4% (N = 212).

Data Analysis The analysis of the data from the online survey was completed using the SPSS 13.0 computer program. Descriptive statistics were employed to assess the respondents’ gender, types of scholarship received, types of sports participation, and region of world origin, while an exploratory factor analysis (EFA) was used to identify the underlying structure of a relatively large set of international student-athletes motivation variables. Since the classification of international student-athletes based upon socio-demographic attributes did not result in enough number of observations for each group in order to employ parametric statistics, the Mann-Whitney and Kruskal-Wallis tests were applied to examine how international student-athletes’ motivation factors are different according to the sociodemographic attributes, respectively (Siegel and Castellan, 1988). Therefore, for this analysis, socio-demographic attributes (e.g., gender, types of scholarship received, types of sports participation, and region of the world) were considered as the independent variables and four identified motivation factors as the dependent variables.

RESULTS Demographics of International Student-Athletes Table 1 shows the socio-demographic profile of international student-athletes participating in this study. The mean age of the respondents was 20.47 (SD = 1.59) and all respondents’ ages ranged from 18 to 25. Of the 212 respondents, more than half (63.3%) were females, and the majority (93.4%) of international student-athletes received a partial (24.8%) or full (68.6%) scholarship. The group of international student-athletes was comprised of 61.4% of individual-sports participants and 38.6% of team-sports participants. Respondents in this study competed in 17 different sports, but 73.3% of them participated in the top five sports: tennis (20.5%), swimming and diving (15.7%), rowing (14.3%), track and field

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(12.4%), and golf (10.5%). Finally, while the respondents came from 49 different countries, 45.7% of them were from countries in Europe, followed by 38.6% of them from countries in North and South America. Table 1. Demographics of International Student-athletes (N = 212) Mean Age

M 20.47

SD 1.59

Gender Male Female

N 77 133

% 36.7 63.3

Scholarship Full-scholarship Partial-scholarship No-scholarship

N 144 52 14

% 68.6 24.8 6.7

Top five sports Tennis Swimming and diving Rowing Track and field Golf

N 43 33 30 26 22

% 20.5 15.7 14.3 12.4 10.5

Home continents Europe America Oceania Africa Asia

N 96 81 14 10 9

% 45.7 38.6 6.7 4.8 4.3

Substructures of International Student-Athletes Motives Exploratory factor analysis (EFA) using a principal-component analysis extraction technique was conducted to assess factors that help explain how international student-athletes characterize their motivation in their participation in intercollegiate athletics in the United States. It was expected that student-athlete motives would be intercorrelated so an oblique (OBLIMIN) rotation with a default delta parameter of 0 was utilized. In Table 2, the results of the EFA identified a four-factor model providing a reasonable compromise between model parsimony and adequacy of fit according to the “Kaiser rule.” The assumed factor model accounted for 66.14% of the total variance of the variables and

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almost all of the individual variables explained reasonably well, possessing communalities ranging from 0.54 to 0.78. The four factors were labeled as intercollegiate athletics attractiveness, school attractiveness, desire for independency, and environmental attractiveness. Table 2. Exploratory Factor Analysis Motivation Factors

Factor Loadings 1

2

3

4

Factor 1 – Intercollegiate Athletics Attractiveness competition level of United States athletics

.791

NCAA college conference

.747

sport season schedule

.691

Factor 2 – School Attractiveness athletic therapy resources / personal trainers

.848

closeness of athletic facilities to campus

.827

academic advising opportunity

.799

campus dining and meal plan opportunities

.737

information technology operations

.737

library resources

.697

Factor 3 –Desire for Independency possibility to leave parental influence at home

.875

chance to gain independence from home

.870

chance to leave hometown

.863

Factor 4 – Environmental Attractiveness location of U.S. College

.860

size of city

.833

weather/climate of city

.738

The percent variance explained by the model was higher compared to Mathes and Gurney's (1985) five-factor model, which only explained 51% of the total variance of studentathletes’ choices of schools. In this study, intercollegiate athletics attractiveness explained 31.23% of the variance followed by school attractiveness which explained 15.06%. Desire for independency accounted for 11.60%, and environmental attractiveness explained 8.24% of the variance. Three items associated with the attractive features of U.S. intercollegiate sports loaded on the first factor, which was labeled intercollegiate athletics attractiveness. Statements for the intercollegiate athletics attractiveness factor included: “competition level of U.S. athletics,”

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“sport season schedule,” and “NCAA college conference.” Six items related to the various academic and athletic services provided from an institution loaded on the second factor, which was labeled school attractiveness. Statements for the school attractiveness factor included: “library resources,” “campus dining and meal plan opportunities,” “closeness of athletic facilities to campus,” “athletic therapy resources/personal trainers,” “academic advising opportunity,” and “information technology operations (e.g. wireless campus).” Three items related to the possibility of being independent loaded on the third factor, which was labeled desire for independency. Statements for the desire for independency factor included: “chance to gain independence from home,” “chance to leave hometown,” and “possibility to leave parental influence at home.” Finally, three items related to the living environment loaded on the fourth factor, which was labeled environmental attractiveness. Statements for the environmental attractiveness factor included: “location of university,” “size of city,” and “weather/climate of city.”

Means, Standard Deviations, and Correlations of Motives The means, standard deviations, and correlation matrix of spectator motives are shown in Table 3. Intercollegiate athletics attractiveness (M = 5.02, SD = 1.28) was the most important motivation factor for international student-athletes followed by school attractiveness (M = 4.85, SD = 1.32), environmental attractiveness (M = 4.41, SD = 1.31), and desire for independency (M = 3.94, SD = 1.71). Internal consistency was examined for each of the four motivation factors. Initial reliabilities of each category for the instrument ranged from .76 for environmental attractiveness to .86 for school attractiveness, exclusive of the measure of intercollegiate athletics attractiveness (α =.62), indicating an acceptable level of reliability (Nunnally & Bernstein, 1994). While all four motives were significantly correlated to each other, these correlations fell within the recommended threshold of r < .50, which satisfied the issue of linear dependency (George & Mallery, 2000). Thus, an examination of the correlation coefficients indicated good discriminant validity among the four motivation factors. Table 3. Correlation Matrix, Means, and Standard Deviations of Spectator Motives Motivation Factors

Factor 1

Intercollegiate athletics attractiveness

(.616)

School attractiveness Desire for independency Environmental attractiveness

Factor 2

Factor 3

.415***

(.862)

.296***

.191**

(.843)

.296***

.251***

.192**

Factor 4

Mean

Std. Dev.

5.02

1.28

4.85

1.32

3.94

1.71

4.41

1.31

(.756)

Notes. * p < .05, ** p < .01, *** p < .001; Cronbach Alphas in parentheses and italics along the diagonal.

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Effects of Demographics on Motivational Factors The study examined potential motivation difference on the basis of four sociodemographic attributes: gender, region of the world, types of scholarship received, and types of sport participation. Results of the Mann-Whitney test and Kruskal-Wallis test indicated that the equality of the average rank of type of sport participation and region of world origin were statistically different while gender and types of scholarship received were not significantly different. Differences in motives based on the participation of team vs. individual sports. In order to examine the differences in motives based on the types of sports participation, student-athletes were classified as either team-sports participants or individual-sport participants. As seen in Table 4, the average ranks for intercollegiate athletics attractiveness, school attractiveness, desire for independency, and environmental attractiveness were listed separately for both groups. Since the rank of 1 is assigned to the smallest value, the average rank was smaller for team sports participants for all motivation factors, excluding desire for independency. Results of the Mann-Whitney Test showed that the main effect of types of sports on intercollegiate athletics attractiveness (U = 4179.50, p = .014) and environmental attractiveness (U = 4209.50, p = .017) were statistically significant at the .05 level while those on school attractiveness (U = 4843.00, p = .373) and desire for independency (U = 4712.00, p = .231) were not statistically significant. Thus, international student-athletes participating in individual-sports were more motivated by intercollegiate athletics attractiveness and environmental attractiveness than international student-athletes participating in team sports. Table 4. Differences in Motives based on Sport Type Motivation factors Intercollegiate athletics attractiveness School attractiveness Desire for independency Environmental attractiveness

Types of Sports

N

Mean Rank

Mann-Whitney-U

p

Team

81

92.60

4179.50*

.014

Individual Team Individual Team Individual

129 81 129 81 129

113.60 100.79 108.46 111.83 101.53

4843.00

.373

4712.00

.231

Team

81

92.97

4209.50*

.017

Individual

129

113.37

Notes. Grouping variable: Gender; *p < .05, **p < .01, ***p < .001.

Differences in motives based on the region of the world. The average ranks for intercollegiate athletics attractiveness, school attractiveness, desire for independency, and environmental attractiveness are separately shown in Table 4 in terms of the region of world origin of the international student-athletes. Descriptively, the average rank was higher for student-athletes from Africa than those from other areas in relation to the four motivation factors, excluding school attractiveness. Results of the Kruskal-Wallis test indicated a significant main effect of region of world origin on intercollegiate athletics attractiveness, χ2(4, 210) = 13.09, p = .011, and environmental attractiveness, χ2(4, 210) = 13.40, p = .009, with no significant effects on

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school attractiveness, χ2(4, 210) = 7.15, p = .128, and desire for independency, χ2(4, 210) = 2.06, p = .724. Further analysis from the Mann-Whitney test provides additional support for results of the Kruskal-Wallis test. For instance, support for the main effect of region of the world was found by the differences in intercollegiate athletics attractiveness and environmental attractiveness being statistically significant between: (a) Africa and America (U = 758.50, p = .004; U = 225.00, p = .022), (b) Africa and Europe (U = 257.00, p = .015; U = 192.00, p = .002), and (c) Africa and Oceania (U = 27.50, p = .011; U = 14.50, p = .001). As a result, student-athletes from Africa were more motivated by intercollegiate athletics attractiveness and environmental attractiveness than student-athletes from America, Europe, and Oceania. Table 5. Differences in Motives based on World Origin by Continent

Intercollegiate athletics attractiveness

School attractiveness

Desire for independency

Environmental attractiveness

Continents

N

Mean Rank

χ2

p

Europe

96

109.91

13.09*

.011

America Oceania Africa Asia Europe America Oceania Africa Asia Europe America Oceania Africa Asia

81 14 10 9 96 81 14 10 9 96 81 14 10 9

93.92 89.71 156.55 130.56 106.76 99.94 86.54 135.40 138.33 107.28 102.72 90.79 121.10 117.06

7.15

.128

2.06

.724

Europe

96

96.26

13.40**

.009

America Oceania Africa Asia

81 14 10 9

112.36 83.11 159.15 117.56

Notes. Grouping variable: Continents; *p<.05, **p<.01, ***p<.001.

DISCUSSION AND CONCLUSION In this line of research, previous studies had examined the motivations of international student-athletes to participate in intercollegiate athletics in the United States (Bale, 1991; Berry, 1999; Stidwill, 1984). For coaches and athletic administrators to recruit and attract international student-athletes, it is very important to identify why international studentathletes participate in intercollegiate athletics. Results from this study identified a four-factor model explaining the international student-athletes’ motives (e.g., intercollegiate athletics

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attractiveness, school attractiveness, desire for independency, and environmental attractiveness) and indicated differences in motives attributable to the types of sport participation and region of world origin of the international student-athletes. The present study uncovered a number of important findings. First, the motivational factors extracted from this study were similar to some of the results in other studies. The previous studies revealed that one of the major motives of international student-athletes is to gain academic and athletic achievement (Bale, 1991; Berry, 1999; Ridinger, 1996; Stidwill, 1984). These findings supported the notion that the potential opportunities related to the academic and athletic success (e.g., athletic therapy resources/personal trainers, closeness of athletic facilities to campus, academic advising opportunity, campus dining and meal plan opportunities, information technology operations, library resources) motivate international student-athletes to come to the United States to participate in intercollegiate athletics. The United States has developed a unique educational system offering opportunities to gain both academic and athletic achievement at the same time, thus placing them in an ideal setting to recruit international student-athletes. Stidwill (1984) indicated international student-athletes in track and field would like to experience the high levels of competition and well-organized training from the American intercollegiate athletics system. Bale (1991) also demonstrated international student swimmers and track athletes from Britain, Sweden, and the Netherlands have an inclination to come to the United States as a consequence of poor training facilities, lack of quality coaches, limited training time, and the level of competition in their own countries. This was consistent with the findings of the present study in that international student-athletes were motivated by intercollegiate athletics attractiveness, andintercollegiate athletic programs in the United States have been known to offer a better intercollegiate athletic system and schedule and higher level of competition. Environmental attractiveness was also an important motive for international studentathletes, as it was the third highest motive among the four extracted. Environmental attractiveness was consistent with Berry’s (1999) social/environmental factor. This motive describes the influence that environmental attributes have on international student-athletes’ school consideration. In other words, international student-athletes might want to participate in American intercollegiate athletics because of the location of school, size of city, and climate of the city. The last motive was desire for independency. This factor ranked as the lowest motive among the four extracted, and its mean score was lower than the scale average. The findings indicated that the possibility of leaving their parental influence, gaining independence, or leaving their hometown might be motives for international student-athletes to come to the United States to participate in intercollegiate athletics, but this motive is not strong compared to the others identified in this study. Second, the differences that emerged in motivational factors in individual sports and team sports provide some interesting insight into the motivations of international student-athletes. Respondents participating in individual sports are more motivated by intercollegiate athletic attractiveness and environmental attractiveness that respondents participating in team sports. The notion of intercollegiate athletic attractiveness does fit with individual sports. The competition level at the intercollegiate level is high and athletes from other countries may not be able to get the same level of competition in their home countries as they can in the United States. These student-athletes want to improve their skills, and the way to do that is to

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compete against competitors with equal or higher skill levels. While this is not such an issue with team sports, individual development cannot be measured as easily in a team setting than in an individual setting. In addition, environmental attractiveness is important because the climate varies throughout the United States, so golfers can choose a university that allows for year-round play. Tennis players can play year-round in many parts of America as well. Track and field is also dependent on weather conditions for student-athletes to train year-round. The majority of the respondents in the study participated in individual sports that are primarily contested outdoors, so location and weather were justifiably more important for individual sport participants. Third, in this study, the international student-athletes from Africa were significantly motivated by intercollegiate athletics attractiveness and environmental attractiveness than student-athletes from other areas (e.g., America, Europe, and Oceania). These findings were partially supported by Berry’s (1999) study. He employed four motivational factors (e.g., athletic, academic, influence-related, and social/environmental) and concluded that international student-athletes showed different patterns of motives based on the region they call home. In particular, he found that South African students were highly motivated by social/environmental factors. This phenomenon could be explained by the reasons that the majority of student-athletes from Africa participated in individual sports (e.g., golf, tennis, track and field, and swimming and diving). The notion of intercollegiate athletic attractiveness and environmental attractiveness are understandably more significant for individual sport participants, as discussed previously. Therefore, the significantly different motives derived from African student-athletes were closely related to the differences emerged in motivational factors in individual sports and team sports. In view of the fact that an understanding of international student-athletes’ motives has been recognized as a crucial strategy for coaches and institutions who want to be competitive in their sports, the significant motives derived from this study will play a vital role in the success of recruiting international student-athletes. However, the current study only focused on international student-athletes in NCAA Division I schools and does not represent entire international student-athlete population. Therefore, further research on this topic should be conducted at Division II and Division III institutions as well in order to better understand motives of international student-athletes in those competitive divisions. In addition, most research, including the current study, on international student-athletes has been limited to understand motivational factors of international student-athletes to participate in intercollegiate athletics in the United States. Researchers should examine other aspects of international student-athletes other than motives. For example, future studies should examine international student-athletes’ satisfaction after experiencing intercollegiate athletics. Additionally, future studies might examine the perception of domestic student-athletes regarding the recruitment of foreign student-athletes because, as discussed earlier, there have been some controversial issues surrounding the recruiting of international student-athletes.

REFERENCES Asher, K. (1994). Multi-cultural cultivation. Coaching Volleyball, 18-23.

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Bale, J. (1991). The Brawn Drain: Foreign Student-Athletes in American Universities, Urbana, IL: University of Illinois Press. Berry, J. R. (1999). Foreign student-athletes and their motives for attending North Carolina NCAA Division I institutions: Unpublished master’s thesis. University of North Carolina at Chapel Hill. Burnside, S. (2007). By traveling to London, Ducks, Kings taking one for the team. Retrieved November 30, 2007, from http://sports.espn.go.com/espn/print?id=3036914andtype =story. Dillman, D. A. (2000). Mail and internet surveys (2nd ed.). New York: John Wiley and Sons. Inc. George, D., and Mallery, P. (2000). SPSS for windows step by step: Allyn and Bacon. Massachusetts. Greviskes, A. (2004, May 5). The evolution of college tennis. Daily Illini. (U. Illinois). Retrieved November 1, 2005 from http://www.cstv.com/sports/m-tennis. Hollander, T. R. (1980). A Geographic Analysis of Intercollegiate Foreign Track and Field Athletes in the United States. Unpublished master’s thesis. Eastern Michigan University. National pastime takes on international flavor. (2007). Retrieved November 25, 2007, from http://sports.espn.go.com/mlb/news/story?id=2824295. Mathes, S., and Gurney, G. (1985). Factors in Student Athletes. Journal of College Student Personnel, 26(4), 327-333. NBA Players from around the World. (2006). Retrieved November 30, 2007, from http://www.nba.com/players/international_player_directory.html. National Collegiate Athletic Association (1996). 1996 NCAA study of international studentathletes. NCAA Eyes Overseas Recruiting (2001). Retrieved Dec. 31, 2007 from http://www.ncaa.org/wps/portal/!ut/p/kcxml/04_Sj9SPykssy0xPLMnMz0vM0Y_QjzKLN4 g3NPUESUGYHvqRaGLGphhCjggRX4_83FR9b_0A_YLc0NCIckdFACrZHxQ!/delta/bas e64xml/L3dJdyEvUUd3QndNQSEvNElVRS82XzBfMTVL?New_WCM_Context=/wps/wc m/connect/NCAA/NCAA+News/NCAA+News+Online/2001/Associationwide/NCAA+eyes+overseas+recruiting+-+7-2-01. Nunnally, J. C., and Bernstein, I. H. (1994). Psychometric Theory. New York: McGraw-Hill. Ridinger, L. L. (1996). Recruiting foreign student-athletes: Creating international awareness of American animosity? Future Focus, 17(2), 20-26. Ridinger, L.L., and Pastore, D.L. (2000a). International student-athletes adjustment to college: A preliminary analysis. NACADA Journal, 20(1), 33-41. Ridinger, L.L., and Pastore, D.L. (2000b). A proposed framework to identify factors associated with international student-athlete adjustment to college. International Journal of Sport Management, 1, 4-24. Ridinger, L. L., and Pastore, D. L. (2001). Coaches Perceptions of Recruiting International Student-Athletes. Journal-of-the-International-Council-for-Health,-Physical-Education,Recreation,-Sport,-and-Dance- 37(1), 18-25. Siegel, S., and Castellan, N. J. (1988). Nonparametric statistics: For the behavioral sciences (2nd). Boston, MA: McGraw-Hill, Inc. Stidwell, H.F. (1984). Motives towards track and field competition of foreign and domestic grant-in-aid student-athletes in NCAA Division 1 colleges and universities. Unpublished doctoral dissertation. Oregon State University.

Contemporary Athletics Compendium, Volume 3 Editor: James H. Humphrey

ISBN: 978-1-60741-561-9 © 2009 Nova Science Publishers, Inc.

Chapter 21

FUNDRAISING RESPONSIBILITIES AND EXPECTATIONS OF NCAA DIVISION II HEAD BASEBALL AND FOOTBALL COACHES Randy Nichols1 and Carl Bahneman2 1

Slippery Rock University, Slippery Rock, Pennsylvania, USA West Virginia University, Morgantown, West Virginia, USA

2

ABSTRACT The purpose of this study was to: (1) describe the fundraising responsibilities and expectations of NCAA Division II head baseball and football coaches. The data were collected via a survey instrument returned by 41 of 122 head baseball coaches and 38 of 122 football coaches surveyed. Demographic data indicated the following: the majority of NCAA Division II head baseball and football coaches are Caucasian between the ages of 25 and 64 and have a master's degree. Data indicated that a majority of head baseball coaches are responsible for coordinating their programs fund-raising efforts while fewer head football coaches have this responsibility, the most successful fund-raising activities for baseball programs are fund-raising events, while football programs raise a higher percentage through solicitation of alumni and individuals with athletic interest. Money raised by these programs was used in somewhat different manners with baseball programs using a majority of the money raised for travel and equipment, while football programs used these funds for equipment, capital improvements and recruiting. Data analysis also revealed that head baseball coaches are expected as part of their contract to raise a higher percentage of operating costs than are football coaches.

Today’s coaches are under many pressures. They are trying to win games, recruit and retain athletes, prepare facilities, raise money, travel to contests and perform a variety of other duties assigned by the athletic director (Protrac, Brewer, Jones, and Hoff, 2000). Many Division II coaches are asked to perform other duties or functions at their institutions, including teaching, student affairs and admissions duties (NCAA, 2003b). As the number of

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programs expand along with the level of competition, so does the amount of administrative duties performed by the athletic director required for each program. To this end, responsibilities that often were handled by an athletic administrator including fundraising have now been shifted to head coaches (Jones, 2001). In making this shift, the head coach must accept greater responsibility and accountability for his or her program which includes funding the program sometimes at a substantial level.

PROCEDURES Selection of the Participants All of the institutions (n= 122) that offer both baseball and football at the NCAA Division II level were asked by letter to participate in the study.

Selection of the Instrument The questionnaire was designed to assess the demographic framework, including institutional standing, institutional size, and the number of sponsored intercollegiate athletic programs. This information provided the researcher with a brief, yet informative, profile of the participants and the institution. The primary areas examined included the current fundraising responsibilities and expectations of the head baseball and football coaches at these institutions. The questionnaire was developed with the help of a panel of coaches from Slippery Rock University. Their comments and recommendations were solicited in order that the questionnaire could be refined and develop content validity. The panel received the list of research questions developed by the researcher, and sample survey questions. The panel was asked to develop what they judged to be relevant questions. The questionnaire was then examined for face validity by faculty members of the Slippery Rock University Sport Management Department. Questionnaires were sent to these individuals and they were asked to rate the questions within the instrument using a four point rating system. A four on the rating system indicated that a question was excellent and that it should be retained on the survey. A rating of three indicated a good question and that it could be retained on the survey. A rating of two indicated an average question that could possibly be retained if revised. A rating of one indicated a poor question that should be completely revised or removed from the questionnaire. The samples were returned and examined and the questionnaire was revised according to their comments. The questionnaire is comprised of 40 questions related to demographic information, and the role responsibilities of the head coaches in these programs. Content validity was established by conducting a pilot study using one coach from each of the eight NCAA Division II regions. The coaches who were selected for the pilot study were asked to complete the survey and return it to the researcher within two weeks.

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Data Collection A cover letter requesting completion of the survey was sent to the head baseball and football coaches of the NCAA Division II institutions. A thorough explanation of the nature and purpose of the study was provided in the letter along with a self-addressed, stamped envelope. Respondents were assured that all responses would be kept confidential. A twoweek deadline was established from the date of the initial mailing and a second letter, along with an additional questionnaire, was sent as a reminder to all participants following the twoweek deadline. The data were collected and analyzed by the researcher. In turn, the participants were asked to answer each question thoroughly and accurately, and when necessary, talk about the specific fundraising practices utilized by the baseball and football programs. All respondents were given the opportunity to receive results.

RESULTS Survey Return Rate The participants for this study were head coaches of NCAA Division II baseball and football programs. One hundred and twenty two institutions sponsor baseball and football at the NCAA Division II level. Of the 122 that were mailed to both head baseball and head football coaches, 41 were returned by head baseball coaches for a return rate of 33.6% and a total of 38 were returned by head football coaches for a return rate of 31.1%.

Head Baseball and Football Coaches Demographics Survey questions 1 through 4 provided information regarding head coaches’ demographics. These items included questions pertaining to the sport coached, ethnic background, age and level of education. Among the coaches who responded, the sport coached distribution was nearly equal with 51.9% (n= 41) head baseball coaches and 48.1% (n=38) head football coaches. Table 1 depicts the sport coached of the head coaches who responded to the survey. Table 1. Sports Coached by Respondents

Baseball Football Total

Frequency 41 38 79

Percent 51.9% 48.1% 100%

Responses show that 80.5% (n=33) of baseball coaches are responsible for fund-raising activities for their program, while 55.3% (n=21) of football coaches are responsible for fundraising for their programs.

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Baseball coaches responded with 70.7 % (n=29) having fiscal control of money raised, while 81.6 percent (n=31) of football coaches reported having fiscal control. Table 2. Individual Responsible for Coordinating Fund-Raising Activities - Baseball Coaches

Head Coach Assistant Coach Graduate Assistant Student Assistant Athletic Department Rep. Total

Frequency 33 3 0 0 5 41

Percent 80.5% 7.3% 0.0% 0.0% 12.2% 100%

Table 3. Individual Responsible for Coordinating Fund-Raising Activities - Football Coaches

Head Coach Assistant Coach Graduate Assistant Student Assistant Athletic Department Rep. Total

Frequency 21 6 0 0 11 38

Percent 55.3% 15.8% 0.0% 0.0% 28.9% 100%

Table 4. Fiscal Control of Money Raised

Baseball Coaches Football Coaches

Frequency 29 31

Percent 70.7% 81.6%

Table 5. Percentage of Budget that Baseball Coaches are Expected to Raise

0% 10% 15% 20% 25% 30% 40% 50% 55% 60% Total

Frequency 10 3 2 7 4 7 2 3 1 2 41

Percent 24.4% 7.3% 4.9% 17.1% 9.8% 17.1% 4.9% 7.3% 2.3% 4.9% 100%

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Of those coaches who responded, 78% (n= 32) of baseball coaches are expected as part of their contract to raise money, while 60.5% (n=23) of football coaches are expected to raise money. Those coaches who are expected to raise money varied by the amount expected to be raised. Baseball coaches range from 0% to 60%, while football coaches range from 0% to 40%. Tables 5 and 6 report these findings. The coaches were given nine different events and asked to rank in order their top three events based on success of the event, which was defined as raising at least five percent of their operating budget. These event choices included auction, baseball tournament, golf tournament, raffle, banquet, camps/clinics, food sales, thons (hit, dance, walk/run, etc.), facility rental, and other. Results are based on the number of coaches who completed these items. Table 7 lists the fund-raising events in order of success for baseball programs based on the mean score calculated from the baseball responses of their most successful events. Table 6. Percentage of Budget that Football Coaches are Expected to Raise Frequency 20 4 4 1 3 5 1 38

0% 5% 10% 15% 20% 30% 40% Total

Percent 52.6% 10.5% 10.5% 2.6% 7.8% 13.3% 2.6% 100%

Table 7. Successful Fund-Raising Events - Baseball Coaches Frequency Camp/Clinic Raffle Golf Tournament Thon (marathon game/ Hit-a-thon) Facility Rental Auction Baseball Tournament Banquet Food Sale Other

26 21 20 15

Ranked Order of Success (Mean) 1.7 1.9 2.5 3.8

9 4 3 1 1 0

4.5 0

Table 8 lists the fund-raising events in order of success for football programs based on the mean score calculated from the football responses of their most successful events. An analysis of the data indicated fund-raising events were the category used to raise the highest amounts of funds for baseball programs with over 60.9% (n=25) raising over 20% of there operating budget, 10.5 % (n= 4) of the football programs raised over 20% of their budget through fund raising events.

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Other (game fee) Other (media guide) Golf Tournament Camp/Clinic Raffle Auction Banquet

Frequency 19 25 24 20 13 6 3

Ranked Order of Success (Mean) 1.4 1.8 2.4 2.6 -

Table 9. Percentage of Operating Budget Raised Through Fund-Raising Events – Baseball

0-10% 11-20% 21-30% 31-40% 41-50% 51-60% Total

Frequency 4 12 8 11 4 2 41

Percent 9.7% 29.3% 19.6% 26.8% 9.8% 4.8% 100%

Table 10. Percentage of Operating Budget Raised Through Fund-Raising Events – Football

0-10% 11-20% 21-30% Total

Frequency 26 8 4 38

Percent 68.4% 21.1% 10.5% 100%

Table 11. Percentage of Operating Budget Raised Through Solicitation of Alumni and Representatives with Athletic Interest – Baseball

0-10% 11-20% 21-30% 31-40% Total

Frequency 29 6 4 2 41

Percent 70.9% 14.8% 9.7% 4.8% 100%

An analysis of the data from question number 23 indicates football programs raised a higher percentage of their operating budget through solicitation of alumni and representatives with athletic interest with 18.4 % (n=7) raising more than 20% of their operating budget through this method. Results also showed that 14.6% (n=6) of baseball programs raised 20%

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or more of their operating budget through solicitation of alumni and representatives with athletic interest. Tables 11 and 12 depict the results from survey question 23. Table 12. Percentage of Operating Budget Raised Through Solicitation of Alumni and Representatives with Athletic Interest – Football Frequency 22 9 7 38

0-10% 11-20% 21-30% Total

Percent 57.9% 23.6% 18.5% 100%

Results showed that of those who responded, football programs had a higher allocated budget (mean=$378,736) than did baseball programs (mean=$64,487), which would be expected due to the greater number of players involved with football programs. Results also showed that football programs spent more (mean= $392,789) than did baseball (mean = $92,817). Finally, results show that baseball programs have a higher deficit when the operating budget is compared to the amount spent for both programs, showing that baseball programs on average had to fund 32% of the their expenses, while football programs had to fund 4% of their expenses. Table 13 displays these results. Table 13. Allocated Budget and Expenses - Baseball and Football

Baseball Football

Allocated Budget (mean) $64,487 $378,736

Expenses (mean) $92,817 $392,789

Percent Difference 32% 4%

Response choices for questions 19, 24 and 27 included athletic scholarships, capital improvements, coaching staff salaries, team travel, equipment, recruitment and other. An analysis of the data indicated that coaches used the money raised in somewhat different manners. Tables 14 and 15 display the use of money raised through fund-raising events. Table 14. Use of Money Raised Through Fund-Raising Events – Baseball

Scholarships Capital Improvements Salaries Travel Equipment Recruiting Other

Frequency 10 10 4 33 30 9 0

Percent 24.3% 24.3% 9.7% 80.4% 73.1% 21.9% 0.0%

Baseball coaches responding to question 19 used money raised through fund-raising events primarily for travel 80.4% (n=33) and equipment 73.1% (n=30), while football

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coaches used money raised through fund-raising events for equipment 57.8% (n=22), capital improvements 39.4% (n=15) and recruiting 31.5% (n=12). It should be noted that respondents could choose more than one category. Table 15. Use of Money Raised Through Fund-Raising Events – Football

Scholarships Capital Improvements Salaries Travel Equipment Recruiting Other

Frequency 11 15 3 14 22 12 0

Percent 28.9% 39.4% 7.8% 36.8% 57.8% 31.5% 0.0%

Baseball coaches responding to question 24 used money raised through solicitation of alumni and individuals with athletic interest primarily for travel 58.5% (n=24), equipment 58.5% (n=24) and scholarships 36.6% (n=15), while football coaches used money raised through solicitation of alumni and individuals with athletic interest for equipment 52.6% (n=20), capital improvements 31.5% (n=12) and travel 28.9% (n=11). Tables 16 and 17 display the use of money raised through solicitation of alumni and individuals with athletic interest. Table 16. Use of Money Raised Through Solicitation of Alumni and Individuals with Athletic Interest –Baseball

Scholarships Capital Improvement Salaries Travel Equipment Recruiting Other

Frequency 15 9 2 24 24 4 0

Percent 36.6% 22.0% 4.9% 58.5% 58.5% 9.8% 0.0%

Table 17. Use of Money Raised Through Solicitation of Alumni and Individuals with Athletic Interest – Football

Scholarships Capital Improvement Salaries Travel Equipment Recruiting Other

Frequency 11 12 3 11 20 12 0

Percent 28.9% 31.5% 7.9% 28.9% 52.6% 31.6% 0.0%

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Table 18. Percentage of Operating Budget Expected to Raise

Baseball Football

Mean + standard deviation 21.88 + 17.9 * 9.06 + 12.6 *

Range (low and high) 0-60 0-40

t value 3.421 3.421

* Indicates significant difference between groups p<.05.

The mean amount expected to be raised for baseball coaches who responded was 21.88% (sd=17.9), and the mean amount expected to be raised for football coaches who responded was 9.1% (sd=12.6). Analysis of the data shows that responses varied greatly with extreme levels of high and low fund-raising expectations for both baseball and football coaches, which accounts for the high standard deviation levels. The difference in the percentage of the operating budget expected to be raised between baseball coaches and football coaches was statistically significant at the .001 level. Table 18 represents these results.

DISCUSSION The results of this study show that baseball coaches are being expected as part of the job to raise a higher percentage of operating budget and 80.5% (n=33) of baseball coaches are responsible for fund-raising activities for their program while 55.3% (n=21) of football coaches are responsible for fund-raising for their program. 70.7 % (n=29) of baseball coaches who responded have fiscal control of money raised, while 81.6 percent (n=31) of football coaches reported having fiscal control. One can conclude from these findings that baseball coaches are expected to raise a higher percentage of their operating costs, funds raised are used more for essential needs within baseball programs when compared to football programs, baseball coaches have less control of how money raised is used and finally baseball coaches are directly responsible for doing so along with the other duties that are associated with being a head coach and any other duties that may be assigned to them.

REFERENCES Jones, R.L. (2001) Applying empowerment in coaching. In Developing decision makers: An empowerment approach to coaching (pp.83-94). Innovative Communications. NCAA. (2003) NCAA division II operating manual. Indianapolis, IN. Potrac, P., Brewer, C., Jones, R. and Hoff, J. (2000). Toward a holistic understanding of the coaching process. Quest, 52, 186-199.

Contemporary Athletics Compendium, Volume 3 Editor: James H. Humphrey

ISBN: 978-1-60741-561-9 © 2009 Nova Science Publishers, Inc.

Chapter 22

ATHLETIC ADMINISTRATORS PERCEPTIONS OF WORK-LIFE BALANCE POLICIES: A DIVISIONAL COMPARISON Nancy Lough∗, Bonnie Tiell** and Barbara Osborne*** *

University of Nevada, Las Vegas, Nevada, USA ** Tiffin University, Tiffin, Ohio, USA *** University of North Carolina, Chapel Hill, North Carolina, USA

ABSTRACT Intercollegiate athletics is recognized as a dynamic industry that places high demands on the time and energy of personnel regardless of the competitive division or size of the institution. Personal sacrifices in time and energy for the sake of the program are equated with contributing to high levels of work-life conflict. The purpose of this study was to analyze the perceptions towards work and life conflict among senior woman administrators and athletic directors at NCAA Division I, II, and III institutions regarding the work-life climate within the athletic department and the existence of workplace benefits offered at their institution. The impact of the presence of children on the perception of work-life climate within the athletic department was also examined. There were significant differences noted in the availability of benefits between DI and DII / DIII, but no significant differences in the perceptions of availability of benefits between ADs and SWAs.

Keywords: Work-Life balance, climate, divisions, administrators, work-family conflict. Intercollegiate athletics is recognized as a dynamic industry that places high demands on the time and energy of personnel regardless of the competitive division or size of the

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institution (Tiell, 2006). Collegiate coaches, athletic support staff, and administrators working in the twenty-first century are experiencing less and less “down” time due to factors such as increases in allowable off-season activities, overlapping sport seasons, and lengthened recruiting periods (Bruening and Dixon, 2007). Also contributing to a demanding work environment is the perceived role expectation of intercollegiate athletics employees in superceding personal needs to adhere to the needs of the department and/or athletes. Personal sacrifices in time and energy for the sake of the program are equated with contributing to high levels of work-life conflict. In addition, the culture of collegiate coaching and management is one that demands non-traditional work hours on nights and weekends thus further adding to work and life conflict (Dixon and Bruening, 2007). As the largest and most recognizable national governing body for the majority of higher education institutions with athletics programs, the National Collegiate Athletic Association (NCAA) uses financial award structures, sport sponsorship minimums, and to an extent, stadium/arena capacities to sanction three divisions known as Division I, Division II, and Division III (NCAA, 2005). When considering media attention, revenue streams (especially television), and staffing, Division I athletic departments are highly distinctive from Division II and III athletic programs. DI schools are the major athletic powers, with larger budgets, more elaborate facilities, and higher numbers of athletic scholarships (Shulman and Bowen, 2001). Whereas, Division II programs often find student-athletes supplementing athletic scholarships with academic scholarships or part time jobs, demonstrating a reduced financial commitment on the part of the institution. Philosophically, Division III holds to a distinctly different set of values when compared to DI or DII; academics are given much higher priority and athletic scholarships are prohibited. Student-athletes are expected to focus the majority of their time on academic pursuits, with sport training serving as a release from the stress of academic rigor (Shulman and Bowen, 2001). Regardless of division, each institution sponsoring athletics designates an “athletic director” (AD) as the department supervisor. This highest ranking position in the department is occupied predominantly by men (Acosta and Carpenter, 2008). There is a NCAA constitutional bylaw (4.02.4) which further requires each institution to designate a senior woman administrator (SWA) who is “the highest ranking female involved with the management of an institution's intercollegiate athletics program” (NCAA Bylaws, 2006). Due to their status as the highest ranking administrators within the department organizational structure, the AD and SWA are likely candidates to have knowledge of the existence of institutional workplace benefits to potentially influence work-life conflict and have a sense of the general climate present in his or her department with regards to promoting work-life balance policies and benefits. While the AD is recognized as the department head, the senior woman administrator reports to the AD except in the few instances when the AD also is designated as the institutional SWA. Research has noted differences between ADs and SWAs regarding their decision-making authority (Tiell, 2004, 2006; Lough and Grappendorf, 2007; Claussen and Lehr, 2002), but both groups are in positions to report their knowledge of work-life benefits offered by their institution and department, along with the perceived work climate. ∗

Address All Correspondence to: Dr. Nancy Lough, Associate Professor. University of Nevada Las Vegas, 4505 Maryland Parkway Box 453031, Las Vegas, NV 89154-3031. Phone: 702-895-5392. Fax: 702-895-5056. [email protected]

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In their 2008 study, Bruening, Dixon, Tiell, Osborne, Lough and Sweeney found that athletic administrators viewed work-life balance as an issue. Specifically, this study pointed to greater concern for women leaving and/or not entering the profession due to the inherent work-life conflict. One study that focused specifically on Division I administrators was found that addressed the question of whether ADs would report differences when compared with reports from SWAs relative to work climate and knowledge of work-life benefits offered (Dixon, Tiell, Lough, Osborne, Sweeney and Bruening, 2008). With both ADs and SWAs reporting the availability of most benefits, differences were found relating to the use of benefits based on the gender of the employees, and the climate effecting use. Still, this study examined strictly the high profile Division I programs, which represent only 119 of the total 1018 NCAA sanctioned athletic programs (NCAA.org). The stark difference in divisions beckons the question whether there are significant differences between the three divisions relative to the availability of work-life benefits and perceived climate. Finally, since research has noted that employees with significant dependent care responsibilities report higher levels of work-family conflict (Dixon and Bruening, 2005), the question remains whether the presence of children impacts the perception of administrators towards their knowledge of work-life benefits and the perceived department climate. Thus, the purpose of the study was to analyze the perceptions towards work and life conflict among senior woman administrators and athletic directors at Division I, II and III institutions regarding the work-life climate within the athletic department and existence of work place benefits offered at their institution. The impact of the presence of children on the respondent’s perception of the work-life climate within the athletic department was also examined.

Research Questions The following three research questions further guided inquiry into the subject. 1. Is there a difference between the perceptions of the athletic director and senior woman administrator in NCAA division I, II and III programs regarding the existence of workplace benefits? 2. Is there a difference between the perceptions of these high ranking administrators in NCAA division I, II, and III programs regarding the work-life climate within the athletic department? 3. Is there a difference in the perceptions of work-life climate among ADs and SWAs based upon parental / non-parental status?

LITERATURE REVIEW Characteristics of NCAA Membership Divisions When considering media attention, revenue streams (especially television), and staffing, Division I (DI) athletic departments are highly distinctive from Division II and III athletic

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programs. Typically, DI schools are represented by the recognized athletic power programs with larger budgets more elaborate facilities and a significant number of students on full athletic scholarships (Shulman and Bowen, 2001). NCAA DII athletics programs try to find a balance between supporting highly competitive athletics teams by providing athletics related grant in aid, but also emphasizing student-athlete academic success and integration into the social fabric of the campus (DII Philosophy Statement, 2007). Finally, DIII athletics programs focus on the overall participation experience of the student-athlete with a greater emphasis on their academic experience (DIII Philosophy Statement, 2007). The NCAA is federated into these three separate divisions with distinct philosophies and membership requirements. Division I schools offer athletic scholarships and sponsor at least seven sports for men and women, with contest and participant minimums for each sport. DI schools must play 100% of the minimum schedule against DI opponents. DI is further divided by sport and levels of scholarships. The Football Bowl Subdivision (formerly DIA) schools are those that the media focus on, the general public thinks of, and most academic research focuses on. At 119 schools, the Football Bowl Subdivision schools are actually just a little more than 10% of all NCAA intercollegiate athletic programs. The 118 Football Championship Subdivision (formerly D1AA) schools do not have minimum attendance requirements for football and have lower scholarship expectations, while the remaining 92 DI schools do not sponsor football teams. The smallest division is Division II, with 282 schools that sponsor at least five sports each for men and women. DII schools offer athletic scholarships and play at least 50% of their schedule in football and basketball against DII or DI opponents. The largest division is DIII with 422 members that sponsor at least five sports each for men and women but do not offer scholarships based on athletic ability (NCAA, 2007-2008). From an administrative perspective, DI institutions generally have well funded programs with a fairly large administrative support structure and personnel working in positions that are delineated and unique. In contrast, DII and DIII programs have administrators and sometimes coaches that fill numerous positions (ie. marketing, rules compliance, sports information) while trying to accomplish similar goals with far fewer resources. The Athletic Director is typically the top administrator or manager within each of these intercollegiate athletics departments. In DI there may also be several additional upper level administrators (ie. Senior Associate Athletic Directors) who report to the AD, yet only a few additional athletic administrators in a DII or DIII organizational structure. Additionally, the NCAA requires that each institution designate a Senior Woman Administrator (SWA) who is the highest ranking female involved with the management of an institutions athletics program (NCAA Bylaw 4.02.4). Yet, it is important to mention that SWA is a designation or acronym and not a formal position, therefore the role that the SWA plays within each athletic department varies. Ideally, there is a strong relationship and good communication between the AD and SWA, regardless of divisional status. “In theory, athletic administrators are expected to serve as liaisons between institutional policymakers and the employees who could potentially benefit from policies and programs related to work-life balance” (Bruening, et.al., 2008, P. 251). Therefore, these administrators serve as the conduit to both policy utilization and climate creation. Still the issue of work life balance has become more than an individual or even institutional issue. With implementation of a specific Work-Life Task Force, the issue has become one of concern for the entire NCAA membership and Association (NCAA Work-Life Task Force, 2007).

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Work Life Conflict There has been a significant body of research conducted on work-family conflict, which has evolved to work-life balance. The first studies sought to identify the phenomenon in the workplace and concluded that work-family conflict is bi-directional whereas work affects family and family affects work (Boles, et al, 2001; Greenhaus and Powell, 2003). The next wave of research looked at identifying the factors associated with work-life balance, and although both men and women experience work-life conflict, a majority of the studies concluded that women are more affected than men (Bruening, et.al., 2008; Hollenshead et al, 2005; Kossek, Colquitt and Noe, 2000). Within intercollegiate athletics, the notion that women coaches may be more affected by this issue than male coaches seems apparent from the consistent decline in the representation of women in college coaching. Dixon and Bruening (2007) examined the experiences of coaching mothers and found that personal “attitudes and behaviors reflected larger structural and social forces at work, and not simply individual choice” (p. 377). Thus, the relationship between the decline in the representation of women as collegiate coaches and work-life conflict appears to be validated. The list of positive outcomes resulting from effective work-life supportive policies including increased job satisfaction (Eby, Caper, Lockwood, Bordeaux, and Brinley, 2005; Guest, 2002; Thomas and Ganster, 1995), increased productivity (Solomon, 1996), and decreased turnover (Eby, et al., 2005; Galinsky and Stein, 1990; Kingston, 1990), points to a win-win opportunity for organizations as well as employees. Yet, tradition rich cultures that dictate the work-life climate for employees can be slow to change. As Bruening, et al. (2008) found, most athletic administrators continue to believe that their environment is not one that can be conducive to work life balance.

Organizational Climate In 2006, the NCAA implemented the “Life and Work Balance Inventory” using a tool similar to the instrument used in the current research and completed by over 4,000 athletics personnel. Of the responses received, 42% of the sample agreed that they were able to adequately balance their current life and athletics commitments effectively, while 40% of the sample disagreed (NCAA Digest, 2006). This study included both genders and multiple positions within an athletic department. When longitudinal data specific to women in college athletics collected by Acosta and Carpenter (2008) are considered, there is reason to believe that women may be leaving intercollegiate athletic positions, or not entering the field, due to the unique challenges placed on women in this profession. While men may also aspire to be parents, typically their work life balance is not as directly affected by parental status when compared to women. Kaufman-Rosen and Kalb (1995) noted that this conflict often led to job exit. They argued that women opted out of corporate jobs because they were unable to “reconcile the punishing schedule with family life” (p. 24). Bruening and Dixon (2007), Dixon and Bruening (2007) and Dixon and Sagas (2007), have all looked at work-life balance issues in college athletics and retention of female coaches. Work-life conflict was found to be a contributing factor to women leaving the coaching profession. As women become mothers the demands of both professional and personal obligations lead to a decision to “opt out” of the profession. Contrastingly, research

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has found women coaches are no less committed to their careers than are men (Sweeney and Lough, 2005). For those who try to reconcile the two, the conflict may be felt most internally. Dixon and Bruening (2007) found family members tend to be more “forgiving” for work obligations, versus the opposite; creating family compromise and guilt for women coaches. Research examining programs and policies that organizations provide to encourage or support work-life balance for their employees has been initiated to address the situation for both male and female employees who seek success in both realms (Dixon, et al. 2008). Still, the availability of policies alone does not ensure their use or their helpfulness toward worklife balance (Allen, 2001). While research suggests that such benefits as flexible scheduling and onsite childcare can reduce the stress associated with work-family conflict, in both corporate and university settings there is evidence that indicates such policies are not utilized (Allen, 2001; Clark, 2001; Hollenshead et al., 2005; Thompson, Beauvis, and Lyness, 1999; Williams, 2004). Similarly, research has shown that employees perceive the use of such policies as potentially harmful to their career advancement (Norton, 1994; Schneer and Reitman, 1990). Nonetheless, the best approach to remedy the problem of work life conflict is the initiation of programs and policies to support work life balance (Ferber and O’Farrell, 1991; Galensky, Bond and Friedman, 1993; Hollenshead, et al, 2005). Clearly, the impact of the organizational culture is crucial to the viability of work life balance policies (Allen, 2001; Clark, 2001; Hollenshead et al., 2005; Williams, 2004). Due to the significant influence of both the availability of policies and the knowledge of such policies among direct supervisors in athletic departments, there is a need to assess the perceptions of athletic administrators. Because the SWA is female, while most ADs are male, both perspectives were considered beneficial to understanding work-life policies and cultures in athletics. Similarly, parental status may influence knowledge and /or use of related policies. Thus, parental status was included as a separate variable in the analysis. Lastly, the commonalities and differences inherent in the three competitive divisions of the NCAA provide a need for analysis of the issue to develop an understanding among all levels.

METHOD Subjects The population for the study consisted of athletic directors and senior woman administrators from the 1018 NCAA active Division I, II, and III schools during the 20052006 academic year. After deleting duplicate or non-entry data entries, the sample for the study consisted of 442 senior woman administrators (SWA) and 456 athletic directors (AD) for a respective response rate of 43% and 45%. Eight individuals in division II and 21 individuals in division III identified themselves as both the AD and SWA. The responses of these individuals were included in the AD data.

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Instrument The instrument utilized for the study was a partial replication of an instrument used in previous studies endorsed by the NCAA Division II Management Council and Division I and III Governance Staffs (Tiell, 2004). The initial instrument used to research the perceptions of ADs and SWAs on the roles, tasks and career paths of the Senior Woman Administrator was modified with the addition of a series of questions adapted from the work-family conflict literature of Anderson, et al., (2002) and Allen (2001). The content validity of the final instrument was determined by a panel of experts representative of all three divisions, both genders, and who were either employed in the field of athletic administration or who had published scholarly research on related subject matter (Ary et al., 1996). Revisions to the instrument were based on the recommendations of the expert panel consisting of academic professors, members of the NCAA headquarters staff, a DI conference administrator, a DI university president, athletic coaches, SWAs, and athletic directors.

Data Collection Procedure Data collection procedures were identical despite occurring in two separate time periods approximately six months apart. Senior woman administrators and athletic directors from the 317 active NCAA Division I institutions were initially invited to complete the instrument followed by a separate data collection period involving the senior woman administrators and athletic directors from the 701 active NCAA Division II and III institutions. The deliberate lag in collecting data from the division II and III administrators was to create a significant time lapse between the current study and a previous study administered to the same population by one of the primary researchers. The two versions of the instrument administered over the six month period included identical sets of questions related to worklife interface. The web-based survey was created using Perseus Survey Solutions XP Standard Edition software and was converted into an HTML electronic document. The NCAA was instrumental in supplying electronic mail addresses of the SWAs and ADs at a majority of the institutions; however, verification for personnel changes was made using the reference of institutional athletics department website directories. The subjects were e-mailed the link for accessing the survey in addition to a brief explanation of the purpose of the study, a statement about the voluntary consent for participation, a confidentiality clause, a deadline for submission, and a statement regarding the support of NCAA President Myles Brand and endorsement from the NCAA Project Team on Life and Work Balance. Approximately two weeks after the initial electronic message was sent to a sample group, a reminder email was sent. In order for the survey to properly be submitted, the subject was required to check “yes” to a statement verifying their knowledge of the purpose of the research and their voluntary consent to participate. The statement also indicated that the subject had not waived any legal or human rights and that they could at any time contact the primary researcher or decline participation.

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Data Analysis Perseus Survey Solutions allowed for data to be easily transported into a database package then analyzed using SPSS. Frequencies and measures of central tendency were utilized to examine descriptive variables. An Analysis of Variance (ANOVA) was used as the statistical tool to describe the ordinal data indicating whether the subject groups generally agreed or disagreed with each statement describing the work-life climate of his or her department. Further post hoc (Scheffe’s) tests of statistical significance were applied when the significance level was at .05 or less. Chi square analyses with an alpha level of .05 was used to determine whether sample groups agreed or disagreed on the perception of whether the institution offered workplace benefits to potentially address work-life conflict.

RESULTS Demographic Characteristics Athletic Directors: A majority of the 456 athletic directors in the sample were male (77.6%). Of the female ADs (22.1%) in the sample, the greatest percentage was reported in Division III (36.1%) followed by Division II (19.4%) and Division I (8.9%). A cumulative 90.5% of the ADs were White and 9.5% identified themselves as either Black, non-Hispanic; American Indian; Alaskan Native; Asian/Pacific Islander; Hispanic; or other. Seventy-seven percent of the AD sample was age 45 or over. Two individuals in Division II and one in Division III reported they were 29 years of age or younger. Most ADs (68%) reported their highest academic degree was at the Masters degree level. A Bachelors degree only was reported by 15.5% of ADs in Division I, 9.3% in Division II, and 7.8% in Division III. A majority of ADs (82%) reported having children and 45.3% reported having at least one dependent child residing at home. Twenty-five percent of the Division III sample did not have children, followed by 18.5% of Division II, and 10.1% of Division I. Senior Women Administrators. There were 442 valid responses from SWAs. The respondents were female (99.1%), with the exception of one designated SWA in Division III who reported he was male. Eighty-nine percent of the respondents were White with Division III having the greatest percentage (95%) of white SWAs followed by Division II (89.8%) and Division I (82.9%). Compared to ADs, the SWAs were a much more diverse group in respect to age. Only 20.2% of SWAs were age 45 or older. SWAs between the ages of 30-39 were reported most frequently in Division II (42%), followed by Division III (36.8%), and Division I (only 25.7%). Eight individuals in Division I (4%), two in division II (1.9%), and one in Division III (.6%) were age 29 or younger. Most SWAs (70.7%) reported their highest academic degree was at the Masters level. Two SWAs in Division II (both females) reported having earned only a high school degree. Most likely this finding is representative of an administrative assistant being granted the SWA title, because she is the only female on the staff. Less than half of the SWAs (40.1%) reported having children and only 28.3% reported having at last one dependent child residing at home.

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Benefits Available Table 1 displays the reported availability of work-life benefits as indicated by both ADs and SWAs in all three divisions. Nearly all schools in Division I offered the majority of benefits. The opposite was true for division II and III where less than half of the institutional representatives reported the availability of work-life benefits. In comparing the responses of ADs and SWAs across all three divisions, there were no statistically significant differences in the responses of ADs and SWAs regarding any of the 17 benefit categories offered at the institution (p=0.00, p<.01). Table 1 shows that for all 17 categories, a greater percentage of the sample of ADs and SWAs in Division I reported the benefit was offered at his or her institution than in either of the other two divisions. In division I, the most frequently reported benefits available were Family Emergency Care Leave (AD = 89.9%, SWA = 94%), Tuition Reimbursement (AD = 83.9%, SWA = 88.9%), and Government Mandated Time off for dependent care (AD = 80.4%, SWA = 87.9%), In both division II and III, the most frequently reported benefits available were Phased or Partial Retirement Plans (DII: AD = 37.0%, SWA = 50.0% / DIII: AD = 41.4%, SWA = 45.8%), and Programs for Family Problems - EAPs (DII: AD = 37.0%, SWA = 42.0% / DIII: AD = 41.1%, SWA = 45.8%). Paid paternity leave was regarded as the benefit with the greatest discrepancy between Division I and the other two divisions. In division I, the benefit was reported by 82.1% of ADs and 79.9% of SWAs, but was reported by only 4.6% and 10% of ADs in division II and III and by 3.4% and 6.5% of SWAs in division II and III. The second greatest discrepancy was reported for the benefit of Emergency Family Care Leave (AD: I = 89.9%, II = 11.1%, III = 7.5% / SWA: I = 94.0%, II = 10.2%, III = 7.7%). When combining the data from all three divisions and comparing the responses of administrators with children and administrators without children, a Chi square test reported statistically significant differences for all 17 work-life benefits (p < .05). Table 1. Descriptive Results of ADs and SWAs for Availability of Work-Life Benefits DI

D II

D III

AD

SWA

AD

SWA

AD

SWA

Compensatory time off for required overtime

63.7%

62.8%

26.9%

30.7%

27.8%

23.9%

Flexible work time arrangements - job sharing

62.5%

54.3%

16.7%

14.8%

17.8%

24.5%

Compressed work week options

51.2%

47.7%

38.0%

39.8%

37.8%

33.5%

Tele-commuting options

50.0%

50.8%

15.7%

17.0%

22.2%

20.6%

Child care, resource finder / referral service

57.1%

50.3%

15.7%

12.5%

21.7%

19.4%

Family travel options for athletic events/activities

70.8%

66.8%

35.2%

37.5%

34.4%

38.7%

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Nancy Lough, Bonnie Tiell and Barbara Osborne Table 1. Continued DI

Wellness programs for employees

D II

D III

AD

SWA

AD

SWA

AD

SWA

83.9%

75.9%

25.0%

30.7%

27.8%

29.7%

Family access to fitness and exercise opportunities Referrals for resource provider for family-related problems

84.5%

76.4%

9.3%

14.8%

7.2%

9.0%

85.1%

78.4%

13.0%

13.6%

11.7%

9.0%

Programs for family problems (EAP)

79.8%

76.9%

37.0%

42.0%

40.0%

47.1%

Government mandated time off for dependent care

80.4%

87.9%

25.0%

29.5%

31.1%

29.7%

Paid paternity leave

82.1%

79,9%

4.6%

3.4%

10.0%

6.5%

Family Emergency care leave

89.9%

94.0%

11.1%

10.2%

7.5%

7.7%

Phased or partial retirement plans

81.0%

78.9%

37.0%

50.0%

41.1%

45.8%

Tuition reimbursement

83.9%

88.9%

25.0%

21.6%

31.1%

27.7%

Sabbaticals

47.0%

47.7%

3.7%

5.7%

4.4%

6.5%

Work-Life Task Force or Committee

56.0%

47.7%

13.0%

18.2%

19.4%

16.8%

Work-Life Climate Table 2 displays the ANOVA table for the six statements relating to the perceived climate of the athletic department based on divisions. When analyzing the three divisions combined, there were no statistically significant differences reported between the sample of ADs and SWAs (p< 0.01) or between the sample of administrators with children and the administrators without children (p < 0.05) for any of the six statements referencing the perceived institutional and department climate for work-life balance.

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Table 2. ANOVA Table for Work-Life Climate Statements based on Division

Family/Personal Needs Accommodated

Employees Encouraged to strike life-work balance

Employees can easily balance worklife conflict

Sum of Squares

df

Mean Square

F

Sig.

Between Groups

6.633

2

3.316

3.914

.020

Within Groups

758.366

895

.847

Total

764.999

897

34.514

2

17.257

15.150

.000

1019.464 1053.978

895 897

1.139

11.034

2

5.517

4.254

.014

Sum of Squares 1160.721 1171.755

df

Mean Square 1.297

F

Sig.

38.151

2

19.075

15.679

.000

Within Groups

1088.874

895

1.217

Total

1127.024

897

30.956

2

15.478

14.342

.000

Within Groups

965.908

895

1.079

Total

996.864

897

7.674

2

3.837

3.704

.025

Within Groups

927.183

895

1.036

Total

934.856

897

Between Groups

Within Groups Total Between Groups

Within Groups Work-life benefits are communicated to employees

Commitment to work-life balance publicized

There is interest in programs to reduce work-life conflict

Total Between Groups

895 897

Between Groups

Between Groups

In division I, there were no significant differences reported between the sample of ADs and SWAs (p<.01) for the six statements referencing the climate of the institution and department for work-life balance (p=0.00, P<0.01). In division II, a statistically significant difference was reported between the sample of ADs and SWAs (p=.920, p<0.05) on only one of the six statements, suggesting that the family and personal needs of employees are accommodated. In division III, a statistically significant difference was reported between the sample of ADs and SWAs for two of the six statements. The difference was reported for the statement that the family and personal needs of employees are accommodated (p=0.157, p<0.05) and the statement that employees can easily balance their personal/family life and work obligations (p=.839, p<0.05).

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DISCUSSION AND IMPLICATIONS A total of seventeen benefits were listed based on the previous research. Most noticeable was the high percentage of benefits available or offered according to both Division I administrators. The range for reported benefits available in Division I extended from a low of 47% to a high of 94% (see Table 1). In contrast, both DII and DIII administrators reported far fewer benefits available. The range in DII was between 3.4% and 50% while for DIII a low of 4.4% was reported along with a high of 47.1% for any single benefit. In essence, DI schools appear to provide the benefits that most effectively address work life balance. Given the budgets and high profile nature of these programs, this finding comes as no surprise. In contrast, DII and DIII either are not aware that many of the benefits are available at their institution, or they truly are not offered by their institution. In some cases, the lack of knowledge or awareness seems to be most likely, given the legal requirements all places of employment are held to. ADs and SWAs provided similar responses, when examined by division. This was viewed as a positive in DI where both groups appear to have an established awareness of policies. However, agreement or similarity of responses in DII and DIII suggests reason for concern. If the administrators are unaware of benefits available at the institution, then the likelihood that coaches and other employees are aware or are encouraged to utilize the benefits that could in fact assist with work life balance appears limited. Additionally, some reports of fewer benefits offered may be reflective of the different environment DII and DIII athletic programs operate in. Many of these schools have far fewer or more restricted resources than those of many DI schools. Further concern is generated when the shared responsibility, or extended work load is considered in DII and DIII. When coaches and athletic administrators are required to fulfill multiple roles, there may be an even more pronounced need for work life balance policies. This result points to one of the key findings of our study, which is the evidence that DI athletic programs differ significantly from DII and DIII programs, and therefore merit research focusing specifically on DII and DIII issues and needs. The rationale for an awareness of phased or partial retirement plans most likely is linked to the tenure of the administrators, and specifically the age of the Athletic Directors. The data supported the notion that knowledge of benefits was linked to the individual respondent’s status. For example, the majority of ADs (77%) were over 45, when age categories were combined. Potentially, the closer the representative is to a career stage such as retirement, the more likely they are to have knowledge of that benefit. However, following the same line of thinking may be concerning for the next most offered benefit. Extended logic would indicate that knowledge of Employee Assistance Programs (EAP) was recognized due to the need for this benefit. Whether this need has arisen due to staff or personal needs, the fact that it stands out as one benefit these administrators are aware of, may also point to difficulty for those employees who are negotiating the work-life interface. Perhaps if the other benefits listed were available and utilized, the need for employee assistance programs would decrease. Finally, the discrepancy around paid paternity leave in DII and DIII indicates support for the social expectation of gender roles in which mothers are granted leave, yet new fathers are not always supported in this work environment.

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When examining the perceived work life climate, six statements were utilized to measure agreement. No significant differences were found when the responses were analyzed based on parental status. Perhaps the explanation for this rests in the high percentage (82%) of ADs (men) who had children, and significant number (45%) of them who still had children living at home. Given this parental status, the male administrators may be more prone to creating a family friendly climate, which resembles a work-life balanced culture for all employees. Specifically at the DI level, there were no significant differences between responses by ADs and those from the SWAs on this item. The most interesting aspect of this lack of difference, rests in the fact that far fewer SWAs had children (40%) and even fewer had children living at home (28%). Yet previous researchers have suggested that women tend to be more aware and concerned with developing a family friendly climate (Bruening and Dixon, 2007). This statement appears to support the notion that even when women are not parents, they may still be as concerned with creating a family friendly climate as the men who actually are parents. Thus, the contribution that women make in regards to supporting work-life balance in an athletic environment should be recognized as positive.

CONCLUSION A statistically significant difference between the perceptions of the athletic directors and senior woman administrators in division I, II and III programs regarding the existence of workplace benefits was not found. However, the congruence of responses between DII and DIII administrators reflected a shared lack of awareness or lack of policies. In contrast, the congruence among DI administrators reflected a shared knowledge and/or use of policies. The potential influence that this awareness or lack of awareness has on the work-life conflict or climate at the institution merits further study. In reference to the difference between the perceptions of these high ranking administrators in division I, II, and III programs regarding the work-life climate within the athletic department, all reported a climate conducive to work-life balance. Division III administrators responded differently to two of the six measures, yet their overall impression remained that the climate was acceptable. Perhaps the next strategy to assess work life climate needs to delve qualitatively into the experiences of a variety of athletic department employees to compare their perceptions with the impressions of the administrators responsible for the perceived climate. Lastly, the difference in the perceptions of work-life climate among ADs and SWAs based upon parental / non-parental status remains an area that merits a deeper understanding. The relationship between motherhood and work family conflict has been established, specifically for women coaches. However, fatherhood and work life conflict, or the direct influence of fathers as athletic administrators impacting the climate for other departmental employees requires additional inquiry. Similarly, the contribution that women make to a culture dominated by men warrants further study.

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FUTURE RESEARCH For future research examining work life balance in intercollegiate athletics, a focus on generational issues and/or values appears to be warranted. As younger generations fill the higher level positions, including coaches, a greater emphasis on work life balance is likely to be needed. Gen X, Gen Y and the millennial generation have all been described as unique from previous generations, with a greater interest in balancing their life with their work. To prevent further decline of women in intercollegiate coaching and administration, the promotion of a work-life balanced climate or culture should be undertaken. When recruiting young coaches and administrators, this approach may allow one athletic program to secure a top talent, while a competitor struggles to understand how they failed to secure the employee. Increasingly this may be true for men as well as women, given that the generational attitudes are attributed to both genders. Future research is also needed that focuses specifically on issues confronting DII and DIII administrators. To date, most studies that have included the lower divisions have done so as a comparison to DI. Given the philosophical differences and growing distinctions between the divisions, further study would be of value.

REFERENCES Acosta, V. and Carpenter, L. (2008). Women in intercollegiate sport. A longitudinal study – thirty year update – 1977-2008. Unpublished Manuscript, Brooklyn College, Brooklyn, New York. Allen, T. (2001). Family-supportive work environments: The role of organizational perceptions. Journal of Vocational Behavior, 58, 414–435. American Council on Education. (2005). An agenda for excellence: Creating flexibility in tenure track careers. Washington DC: A.C.E. Office of Woman in Higher Education. Anderson, D., Morgan, B., and Wilson, J. (2002). Perceptions of family-friendly policies: University versus corporate employees. Journal of Family and Economic Issues, 23, 7392. Ary, D., Jacobs, C. J., and Razavieh, A. (1996). Introduction to research in education (5th ed.). Fort Worth: Holt, Rinehart, and Winston. Boles, J., Howard, W.G., Donofrio, H., (2001). An investigation into the inter-relationships of work-family conflict, family-work conflict, and work satisfaction. Journal of Managerial Issues, 13, 376-391. Bruening, J. and Dixon, M. (2007). Work-family Conflict II: Managing Role Conflict. Journal of Sport Management, 21(4), 471-496. Bruening, J., Dixon, M., and Pastore, D. (2005, February 2). Title IX moms: Gender, work and parenting in college athletics. Presentation at Bowling Green State University Symposium for Women and Sport: Before, During, and After Title IX. Bruening, J., Dixon, M., Tiell, B., Osborne, B., Lough, N. and Sweeney, K. (2008). The role of the Supervisor in the Work-Life Culture of Collegiate Athletics. International Journal of Sport Management, 9(3), 250-272.

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Clark, S.C. (2001). Work cultures and work/family balance. Journal of Vocational Behavior, 58, 348-365. Claussen, C. and Lehr, C. (2002). Decision making authority of senior woman administrators. International Journal of Sport Management, 3, 215-228. Dixon, M., and Bruening, J. (2005). Perspectives on work-family conflict: A review and integrative approach. Sport Management Review, 8, 227-254. Dixon, M. and Bruening, J. (2007). Work-Family Conflict in Coaching I: A Top-Down Perspective. Journal of Sport Management, 21 (3), 377-406. Dixon, M. and Sagas, M. (in press). The relationship between organizational support, workfamily conflict, the culture of intercollegiate athletics and the job-life satisfaction of university coaches. Research Quarterly for Exercise and Sport. Dixon, M., Tiell, B., Lough, N., Osborne, B., Sweeney, K. and Bruening, J. (in press). Exploration of Life and Work Interface in Intercollegiate Athletics: Perceptions of Division I Administrators Towards Policies, Programs, and Institutional Climate. Journal for the Study of Sport and Athletes in Education. Drago, R.; Hennighausen, L; Rogers, J; Vescio, T. and Stauffer, K. (2005, August 19). Final Report for CAGE: The Coaching and Gender Equity Project. Eby, L., Casper, W., Lockwood, A., Bordeaux, C. and Brinley, A. (2005). Work and family research in IO/OB: Content analysis and review of the literature (1980-2000). Journal of Vocational Behavior, 66, 124-197. Galinsky, E. and Stein, P. (1990). The impact of human resource policies on employees. Journal of Family Issues, 11, 368-377. Ferber M. and O’Farrell, B. (1991). Work and family: Policies for a changing work force. Washington, DC: National Academy Press. Greenhaus, J.H. and Powell, G.N. (2003). When work and family collide: Deciding between competing role demands. Organizational Behavior and Human Decision Processes, 90, 291-303. Guest, D. (2002). Human resource management, corporate performance, and employee wellbeing: Building the worker into HRM, The Journal of Industrial Relations, 44, 335-358. Hollenshead, C. (2005). Work/family policies in higher education: Survey data and case studies of policy implementation. New Directions for Higher Education, 2005(130), 4165. Kaufman-Rosen, L., and Kalb, C. (1995, March 27). Holes in the glass ceiling theory. Newsweek, 24-25. Kingston, P. (1990). Illusions and ignorance about the family responsible workplace. Journal of Family Issues, 11, 438-454. Kossek, E.E., Colquitt, J.A., and Noe, R.A. (2001). Caregiving decisions, well being, and performance: The effects of place and provider as a function of dependent type and workfamily climates. Academy of Management Journal, 44, 29-44. Litan, R., Orszag, J., and Orszag, P. (2003, August). The empirical effects of collegiate athletics: An interim report. Sebago Associates. Lough, N. and Grappendorf, H. (2007). Senior Woman Administrator’s Perspectives on Professional Advancement. International Journal of Sport Management, 8(2), 193-209. *NCAA. (2005). What's the difference between Divisions I, II and III? NCAA On-line Resource Center. Retrieved December 26, 2006 at http://www.ncaa.org/wps/portal/ !ut/p/kcxml/04_Sj9SPykssy0xPLMnMz0vM0Y_QjzKLN4j3CQXJgFjGpvqRqCKOcAFfj_z

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cVH1v_QD9gtzQiHJHRUUAc0tpTA!!/delta/base64xml/L3dJdyEvUUd3QndNQSEvNElV RS82XzBfTFU!?CONTENT_URL=http://www.ncaa.org/about/div_criteria.html NCAA Bylaws (2006, July). Division II Manual 2006-2007: Constitution, Operating Bylaws, Administrative Bylaws. Published by NCAA Educational Services, Indianapolis, Indiana. NCAA Digest. (2006, August 28). Life-work balance. Task force’s first meeting focuses on recent research. NCAA News. Retrieved November 22, 2006 at http://www.ncaa.org/wps/portal/newsdetail?WCM_GLOBAL_CONTEXT=/wps/wcm/con nect/NCAA/NCAA+News/NCAA+News+Online/2006/News+Digest/NCAA+Digest+-+828-06+NCAA+News. Norton, S. (1994). Pregnancy, the family, and work: An historical review and update of legal regulations and organizational policies and practices in the United States. Gender, Work and Organizations, 1, 217-225. Sagas, M., and Cunningham, G. (2005). Work-family conflict among college assistant coaches. International Journal of Sport Management, 6, 183-197. Schneer, J.A. and Rutman, F. (1990). Effects of employment gaps on the careers of MBAs: More damaging for women than for men? Academy of Management Journal, 33, 391406. Shulman, J.L. and Bowen, W.G. (2001). The Game of Life: College Sports and Educational Values. Princeton University Press, Princeton, New Jersey. Solomon, C.M. (1996). Flexibility comes out of flux. Personnel Journal, 75, 34-43. Sweeney, K. and Lough, N. (2005, August). Work-Life balance among college coaches of women’s sport. International Association of Physical Education and Sport for Girls and Women. Edmonton, Alberta, Canada. Thomas, L.T., and Ganster, D.C. (1995). Impact of family-supportive work variables on work-family conflict and strain: A Control perspective. Journal of Applied Psychology, 80, 6-15. Thompson, C., Beauvais, L.., and Lyness, K. (1999). When work–family benefits are not enough: The influence of work–family culture on benefit utilization, organizational attachment, and work–family conflict. Journal of Vocational Behavior, 54, 392–415. Tiell, B. (2006, January 7). Clarification of the designation of the senior woman administrator in intercollegiate athletics. Paper presented at the 2006 NCAA Convention. Indianapolis, Indiana. Tiell, B., Dixon, M., Sweeney, K., Lough, N., Osborne, B., and Bruening, J. (2006). Progressive programs: Stopping the pull. Athletic Management, 18, 63-67. Tiell, B. (2004). Roles, tasks, and career path of senior woman administrators in intercollegiate athletics. Unpublished dissertation. Williams, J. (2004). Hitting the maternal wall. Academe, 90 (6), 16-20.

Contemporary Athletics Compendium, Volume 3 Editor: James H. Humphrey

ISBN: 978-1-60741-561-9 © 2009 Nova Science Publishers, Inc.

Chapter 23

THE IMPACT OF PLAYING POSITION ON PERCEPTIONS OF HORIZONTAL INTERPERSONAL POWER IN SPORT Daniel L. Wann∗ Murray State University, Murray, Kentucky, USA

ABSTRACT Interpersonal power involves the extent to which an individual has the ability to influence or change the attitudes and behaviors of others (Baron and Greenberg, 1990; Keys and Case, 1990). French and Raven (1959) suggested that there were five common forms of interpersonal power: reward, coercive, referent, legitimate, and expert. The current investigation examined the extent to which teammates possess differential levels of these five power bases. Based on the theoretical framework offered by Whetten and Cameron (1984), it was hypothesized that players occupying positions that were central, critical, flexible, visible, and relevant would be perceived as possessing greater levels of power than teammates playing positions that lacked these characteristics. To test this prediction, college intramural flag football players were asked to rate the power possessed by their team's best quarterback (a highly central, critical, flexible, visible, and relevant position) and best offensive lineman. The data indicated that the quarterbacks were viewed as possessing greater amounts of reward, expert, and legitimate power. Quarterbacks and offensive linemen were not perceived as possessing differential levels of coercive and referent power.

∗

This project was partially supported by a grant from the Murray State University Committee on Institutional Studies and Research (#2-12886). Portions of this paper were presented at the meeting of the Association for the Advancement of Applied Sport Psychology, Orlando, FL, October, 2001. The author thanks Al R. Rochelle for his assistance with the data collection. Address correspondence to Daniel L. Wann, Department of Psychology, Box 9, Murray State University, Murray, KY 42071 or to [email protected] via Internet (fax #270-809-2991).

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Keywords: power, centrality, leadership, athlete leadership. Interpersonal power involves the extent to which an individual has the ability to influence or change the attitudes and behaviors of others (Baron and Greenberg, 1990; Keys and Case, 1990). Although research on interpersonal power is quite common in some areas of psychology (e.g., industrial and organizational, educational), sport psychologists have tended to neglect the important implications of power for sport organizations. Indeed, only a handful of sport scientists have written on this topic (e.g., Knoppers, Meyer, Ewing, and Forrest, 1990; Slack, 1997; Wann, 1997). This research and theoretical void is unfortunate because many persons in sport possess interpersonal power themselves and/or are influenced by the power of others. Such persons include coaches, players, owners, athletic directors, and even spectators. In an attempt to initiate empirical research on interpersonal power in sport, Wann, Metcalf, Brewer, and Whiteside (2000) recently developed the Power in Sport Questionnaire (PQS). Based on the widely validated theoretical model of organization power presented by French and Raven (1959; see Podsakoff and Schriesheim, 1985), the PSQ was designed to assess five forms of interpersonal power: reward, coercive, referent, legitimate, and expert. Reward power involves the ability to change another individual's attitude or behavior because one controls access to desired rewards. Coercive power concerns the ability to change another individual's attitude or behavior because one controls access to one or more punishments. Referent power is the ability to change another person's attitude or behavior because one is liked and respected by the group members. Legitimate power involves the ability to change another individual's attitude or behavior because of one's position within the organization or group. And finally, expert power concerns the ability to change another individual's attitude or behavior because one is believed to be knowledgeable, skillful, or talented in a specific domain. Wann and his colleagues validated two forms of the PSQ, the PSQ-O (i.e., other), which concerns an individual's perceptions of the power possessed by others, and the PSQ-S (i.e., self), which involves beliefs about one's own sources of power. Examinations of the reliability and validity of the PSQ were conducted on intercollegiate varsity and intramural coaches, athletes, and officials. This work supported the strong psychometric qualities of both versions of the PSQ. Thus, Wann et al. were able to draw several conclusions with respect to the influence of interpersonal power on sport participants. For instance, officials were viewed as having significantly lower levels of referent power than coaches, while head coaches were perceived of as having greater amounts of total power than assistant coaches. Further, intramural officials were viewed as having lower levels of power than varsity officials, with the exception of referent power for which the pattern was reversed. The Wann et al. (2000) research laid important groundwork for both understanding and accurately assessing perceptions of interpersonal power in sport systems. However, Wann et al. limited their research to vertical power, that is, interpersonal power in which individuals occupy different levels in the organization’s hierarchy (e.g., perceptions players have of the power of coaches and officials). A second and often equally important form of interpersonal power involves horizontal power (Whetten and Cameron, 1984; Yukl, 1994). Horizontal power concerns the influence of power among persons on the same hierarchical plane within an organization. Although previous research had examined factors leading to player leadership (e.g., Grusky, 1963; Kozub and Pease, 1991; Tropp and Landers, 1979), research

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on the horizontal power possessed by teammates had yet to be undertaken. In sport settings, horizontal power is most evident in the relationships among teammates. With respect to the sources of power described by French and Raven, teammates may possess horizontal power to the extent that they can influence the attitudes and behaviors of other players because they are viewed as an expert, possess access to certain rewards, and the like. The current investigation was designed to extend the Wann et al. research on vertical power in sport by investigating perceptions of horizontal power among teammates. The theoretical model proposed by Whetten and Cameron (1984) was used to guide the predictions developed for the current study. Drawing on research in industrial/organizational psychology, Whetten and Cameron theorized that five characteristics of positions within an organizational system lead to increases in power among those occupying the positions. The five characteristics are centrality, criticality, flexibility, visibility, and relevance. Positions that are central within an organization or group are expected to possess more power than peripheral positions because persons occupying central positions have greater access to important information (Boje and Whetten, 1981; Hinings, Hickson, Pennings, and Schneck, 1974). Individuals in central positions can use this information to influence others in the system. Research on athletes confirms the importance of central positions in the development of leadership (Glenn and Horn, 1993; Grusky, 1963; Kozub and Pease, 1991; Loy, Curtis, and Sage, 1979; Melnick and Loy, 1996). Similar to centrality, critically concerns the extent to which positions within the organization or group are responsible for the most critical tasks. According to Whetten and Cameron, a position is critical to the extent that its function is "unique" and because of "its location in the work flow" (p. 251). Thus, individuals occupying positions that a) are not redundant with other positions and b) control the flow of work (i.e., assignments) have the potential to greatly influence others. The importance of criticality has also been demonstrated in sport settings. For instance, in their work with field hockey teams, Tropp and Landers (1979) found that the independent tasks executed by goalies (e.g., blocking shots, clearing) led to the high level of leadership ascribed to these players (see also Chelladurai and Carron, 1977; Loy et al., 1979). The third characteristic in Whetten and Cameron's (1984) theoretical model, flexibility, involves an individual's ability "to improvise, to innovate, to demonstrate initiative" (p. 254). Flexibility is most often associated with positions that involve variety and novelty, as well as the use of one's own judgement (Hickson, Hinings, Lee, Schneck, and Pennings, 1971). Persons will have the potential for greater power when they occupy positions that often allow them to make decisions without first gaining the approval of others. Such latitude and authority allow these individuals to exert considerable horizontal influence over their coworkers and associates. Visibility is the fourth important position characteristic described by Whetten and Cameron (1984). The relationship between visibility and horizontal power is relatively straightforward. Simply put, persons occupying positions that render their task performance more visible (i.e., their actions are viewed by larger numbers of individuals) will have the potential for greater levels of power than those occupying positions in which their efforts are "unseen" by others in the organization (Korda, 1975; Mechanic, 1962). In sport settings, Chelladurai and Carron’s (1977) model of player leadership suggests that visibility (i.e., propinquity) will be an important determinant of leadership potential (see also Lee, Coburn, and Partridge, 1983).

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The fifth and final position characteristic, relevance, concerns the extent to which persons occupy positions that "are generally associated with activities that are directly related to central objectives and issues" (Whetten and Cameron, 1984, p. 258; see also Perrow, 1970; Salancik and Pfeffer, 1977). Positions within an organizational hierarchy that most impact the organization's goals will be perceived as most relevant (Hellriegel, Slocom, and Woodman, 1992). Consequently, persons occupying such positions will likely have greater levels of horizontal power than individuals in positions that are perceived as less relevant. Thus, according to Whetten and Cameron's (1984) theoretical framework, persons occupying positions that are central, critical, flexible, visible, and relevant should have greater amounts of horizontal power than associates in positions that are peripheral, redundant, routine, unseen, and irrelevant. As noted, this conceptualization was used to guide predictions of horizontal power in sport teams. It was hypothesized that persons occupying central, critical, flexible, visible, and relevant positions on a sport team would be perceived by teammates as being more powerful than players occupying positions that lacked these qualities. This prediction was tested using collegiate intramural flag football teams. It was expected that players would perceive their team’s best quarterback as possessing greater amounts of power than their team’s best offensive lineman. This prediction is consistent with Whetten and Cameron’s theory because, relative to offensive linemen, the position of quarterback is more central and critical (information typically flows through the quarterback, e.g., plays are sent in to the quarterback who then relays this information and the corresponding work assignment to teammates). Further, the position of quarterback is more flexible. For instance, quarterbacks typically have the authority to change the play at the line of scrimmage and are able to be innovative during a play (e.g., scrambling). In addition, because research indicates that individuals tend to focus on the player in possession of the ball (Steele and Wann, 1999; Wann, Brewer, and Carlson, 1998; Wann, and Steele, 1998), offensive linemen should be less visible than quarterbacks. And finally, quarterbacks may be more relevant than offensive lineman. Although, each position in football is vital to the success of a team, quarterbacks may be especially important because they handle the ball on almost every offensive play and a poor performance by these persons seriously damages the team’s chances for success. Anecdotally, it is often believed by coaches that it is extremely difficult to win without a quality quarterback, a perception that also suggests the heightened relevance of this position. Two additional points warrant mention about the positions selected for study. First, perceptions of the team’s best quarterback and offensive lineman were examined so as not to confound the relative talent required to play each position. In addition, this eliminated the possibility that some participants may have targeted their team’s best quarterback but worst offensive lineman and vice versa. Second, both quarterbacks and offensive linemen play on offense, thus eliminating the potential confound that could result from comparing offensive and defensive positions. Because the position of quarterback is more central, critical, flexible, visible, and relevant than the position of offensive lineman, a team’s best quarterback was expected to be viewed as possessing greater amounts of power than the team’s best offensive lineman. However, the aforementioned research by Wann et al. (2000) indicates that there is often an interaction between sport target and the various forms of interpersonal power. It was believed that a similar interaction would occur here. It was hypothesized that, although quarterbacks would be viewed as possessing greater amounts of power than offensive linemen, this finding would

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be limited to certain forms of interpersonal power. Specifically, quarterbacks would be viewed as possessing greater amounts of legitimate and expert power but that players occupying the two positions would be viewed as possessing equal amounts of referent power. With respect to legitimate power, one's position of authority within an organizational system is a strong determinant of this power base. Because flexibility is predicted to lead to increased perceptions of authority (Whetten and Cameron, 1984), it was expected that quarterbacks (a highly flexible position) would have greater legitimate power potential. As for expert power, the position of quarterback is high in criticality. Consequently, those occupying this position should be viewed as an expert, both because they are playing a highly specialized position (e.g., it is not redundant with other positions as there is only one player in this position on the field at a time), and because they possess special talents that let them control the flow of work assignments. Quarterbacks and offensive linemen were not expected to possess differential levels of referent power because research indicates that possession of a leadership position in sport does not guarantee increased perceptions of referent power. For instance, Wann et al. (2000) found that although players report that their head coaches possess greater amounts of coercive, legitimate, and expert power than assistant coaches, the two levels of coaches were not viewed as possessing differential levels of referent power. In summary, persons occupying the position of quarterback were expected to possess greater amounts of legitimate and expert power than those playing offensive lineman. Perceptions of the referent power of persons in the two positions were not expected to differ. Predictions about perceptions of the reward and coercive power of the players were less obvious. Neither theory (e.g., French and Raven, 1959; Whetten and Cameron, 1984) nor research (e.g., Wann et al., 2000) led to suggestions with respect to the relationship between player position and perceptions of reward and coercive power. Consequently, potential differences with respect to these forms of power were investigated with the framework of a research question and no hypotheses were tested.

METHOD Participants Participants were 99 college students participating on one of 12 different intramural flag football teams. The respondents received $5.00 in exchange for their participation. Twentythree of the subjects were removed from the sample for various reasons (see below), resulting in a final sample of 76 persons (35 males, 41 females). The participants had a mean age of 20.03 years (SD = 1.81, range = 18 to 27). They reported playing flag football for an average of 2.17 years (SD = 1.68, range = 0 to 10) and for their current team for an average of 1.51 years (SD = 0.84, range = 0 to 4). Their class standings were: 18 percent freshmen, 41 percent sophomore, 16 junior, 24 percent senior, and 1 percent graduate.

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Procedure and Materials Intramural flag football coaches were contacted prior to a scheduled contest involving their team. The coaches were told that a researcher in the Department of Psychology was conducting research on athletes' perceptions of their teammates. The coaches were further informed that, prior to their team's next game, a research assistant would be stationed at the flag football field. The coaches were informed that all participants who completed the 15minute survey would receive $5.00. Coaches were asked to relay this information to their players. At the field, the research assistant was located under a pavilion with a large sign reading "Psychology Study on Perceptions of Teammates -- Earn $5.00 for Your Participation". When players arrived at the pavilion, they were handed a clipboard containing a questionnaire packet and a pencil. The players were instructed to have a seat under the pavilion to complete the packet. The questionnaire packet contained four sections. The first section contained general demographic items assessing age, gender, and year in school. The second section contained items assessing the participant's experience with flag football and his or her team. The first two items in this section asked subjects to indicate the number of years that they had played flag football in general and, specifically, with their current team. Next, the respondents indicated how much they expected to play "this season" by circling one of the following responses "I expect to play only about 1 of the team’s games," "I expect to play about half of the team's games," “I expect to play most of the team's games," or "I expect to play all of the team's games." The players then indicated if they were usually a starter or substitute on offense and a starter or substitute on defense. They then reported the offensive and defensive positions they expected to play most frequently. Finally, they were to indicate if they were the coach for their flag football team. The third and fourth sections of the packet contained two versions of the Power in Sport Questionnaire - Other (PSQ-O; Wann et al., 2000). As noted earlier, the 15-item PSQ-O is a reliable and valid instrument for assessing perceptions of the power possessed by others. Five sources of power are included in the PSQ-O: reward, coercion, referent, legitimate, and expert. Each of the five subscales contains three Likert-scale items. Response options to each item range from 1 (this is very untrue) to 9 (this is very true). Thus, higher numbers on the PSQ-O indicate beliefs that the target person possesses greater levels of power. In the first version of the PSQ-O, the respondents were asked to name their team's best quarterback and to indicate if this person was the head coach for the team. Subjects then completed the PSQ-O for the individual they perceived to be the team's best quarterback. The second version asked subjects to repeat the process for the individual they believed to be their team's best offensive lineman. Subjects read that if they believed they were their team's best quarterback or offensive lineman, they were to leave the items on the corresponding PSQ-O blank. After completing the questionnaire packet (approximately 15 minutes), the participants were asked to return the clipboard, questionnaire packet, and pencil. They then signed a receipt and were given $5.00. They were then handed a debriefing statement explaining the hypotheses of the research. The statement also contained contact information if they wished to receive a copy of the final research report. The participants were then excused from the testing session.

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RESULTS As noted above, 23 of the original 99 participants had to be removed from the sample. Four of the questionnaire packets were incomplete. Nine of the participants reported that they were their team's best quarterback while four individuals indicated that they were their team's best offensive lineman. Consequently, these 13 participants were not included in the analysis (for these persons perceptions of the best quarterback or offensive lineman would have been self-perceptions, not perceptions of the power held by a teammate). One person believed that her team's best quarterback and best offensive lineman was the same individual. This person was not included in the analyses because it would not have been possible to compare perceptions of the team's best quarterback and offensive lineman. Finally, four subjects listed a best quarterback who was also the team's head coach while one participant's best offensive lineman was also the coach. Because the position (i.e., quarterback or offensive lineman) was confounded with coaching status for these five targets, these subjects were also removed from the sample. The result was a final sample of 76 persons who had complete packets, did not view themselves as either their team's best quarterback or offensive lineman, felt that their team's best quarterback and offensive lineman were separate individuals, and did not list a team's head coach as its best quarterback or offensive lineman. Cronbach's reliability analyses of the final sample indicated that the PSQ-O subscales and total scale were reliable (subscale alphas ranged from .62 to .86; total scale alphas = .87 and .89 for perceptions of the power of the best quarterback and offensive lineman, respectively).

Relationship between Perceptions of Power and Subject Variables To insure that PSQ-O scores were not confounded by the participants' gender, level of involvement with the team (i.e., amount they expected to play), starting/substituting status, primary offensive and defensive position, or involvement as a coach, correlations or ANOVAs were computed involving these subject variables and PSQ-O subscale and total scale scores. Because of the large number of correlations computed (i.e., 12 per subject variable), the alpha level was set at a more conservative .01. With respect to gender, no significant relationships emerged involving this variable and the PSQ-O subscales and total scales (rs ranged from -.26 to .17). Indeed, 75 percent of the coefficients ranged from -.15 to .15. Thus, consistent with past research (Wann et al., 2000), gender was not related to perceptions of power in sport and, consequently, subsequent analyses were conducted across this variable. With respect to involvement level, 1 percent of the sample expected to play only about 1 game, 7 percent expected to play about half the games, 24 percent expected to play most of the games, and 68 percent expected to play all of the games. A correlation analysis failed to reveal any significant relations between playing expectations and PSQ-O scores (rs ranged from -.16 to .18, 83 percent ranged from -.15 to .15). Thus, future analyses were conducted across this variable. As for starting/substituting status, 63 percent of the participants expected to start on offense (37 percent expected to substitute) and 58 percent expected to start of defense (42 percent expected to substitute). Correlational analyses with PSQ-O scores failed to yield

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significant relationships for both offensive starting status (rs ranged from -.18 to .13, 83 percent ranged from -.15 to .15) and defensive starting status (rs ranged from -.07 to .22, 83 percent ranged from -.15 to .15). With respect to the subjects' primary playing positions, on offense, 47 percent of the participants listed wide receiver, 33 percent listed offensive lineman, 4 percent quarterback, and 15 percent running back (1 percent did not list an offensive position). On defense, 14 percent listed linebacker, 43 percent defensive back, and 40 percent defensive lineman (3 percent failed to list a defensive position). The relationships between playing position and perceptions of power were analyzed using a pair of within-subjects ANOVAs. The 2 (Target: best quarterback and best offensive lineman) x 5 (PSQ-O Subscale) by 4 (Primary Offensive Position: wide receiver, offensive lineman, quarterback, or running back) offensive position ANOVA failed to indicate any significant main or interaction effects involving offensive playing position. Similarly, the 2 (Target) x 5 (PSQ-O Subscale) x 3 (Primary Defensive Position: linebacker, defensive back, or defensive lineman) defensive position ANOVA failed to indicate any significant main or interaction effects involving defensive playing position. Consequently, all subsequent analyses were conducted across this variable. Finally, the impact of the participants' involvement as their team's coach was examined by correlating responses to this item with the PSQ-O scores. Eight percent of the sample indicated that they were their team's coach (92 percent were not their team's coach). Correlational analyses failed to indicate any significant relationships between coaching status and perceptions of power (rs ranged from -.13 to .09). Therefore, all analyses were conducted across coaching status.

Perceptions of Power as a Function of Playing Position The hypothesis that persons occupying a central, critical, flexible, visible, and relevant position on a sport team would be perceived by teammates as possessing greater amounts of power than persons occupying a position lacking these characteristics was tested through a 2 (Target: best quarterback and best offensive lineman) x 5 (PSQ-O Subscale) within-subjects ANOVA. Means and standard deviations for this analysis appear in Table 1. The analysis yielded a significant main effect for target, F(1, 75) = 19.61, p < .001. As expected, the team’s best quarterback was perceived of as possessing greater amounts of power than the team’s best offensive lineman. The PSQ-O subscale main effect was also significant, F(4, 300) = 65.51, p < .001, indicating that the targets were viewed as possessing differential levels of the five forms of power. The main effects were qualified by a significant two-way interaction, F(4, 300) = 7.10, p < .001. As revealed in Table 1, consistent with expectations, the team’s best quarterback was viewed as possessing greater levels of legitimate and expert power than the team’s best offensive lineman while persons occupying the two position types were not perceived as possessing differential levels of referent power. Quarterbacks were also viewed as possessing greater levels of reward power. Quarterbacks and offensive linemen were not viewed as possessing differential levels of coercive power.

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Table 1. Means and Standard Deviations for Perceptions of Power for the Team's Best Quarterback and Offensive Lineman Quarterback

Offensive Lineman

Power

M

SD

M

SD

Reward*

16.30

6.83

13.86

7.13

Coercive

10.61

6.56

9.80

6.60

Referent

19.29

5.65

19.18

6.41

Legitimate*

17.42

5.97

13.20

6.61

Expert*

19.91

5.49

17.45

7.25

Total power

83.68

23.32

73.49

26.06

DISCUSSION The results presented above extend past research on player leadership in sport (e.g., Chelladurai and Carron, 1977; Grusky, 1963; Kozub and Pease, 1991; Tropp and Landers, 1979) by providing strong support for the hypothesized pattern of effects. The data also indicate that Whetten and Cameron’s (1984) theoretical model of horizontal power is a useful framework for understanding player-to-player influence on sport teams. As expected, players occupying central, critical, flexible, visible, and relevant positions were viewed as possessing greater levels of power than players not occupying such a position. However, also as expected, the power attributed to these persons was limited to specific forms of power, namely, expert and legitimate. Also as predicted, players occupying the two position types were not viewed as possessing differential levels of referent power. The data also revealed that persons occupying the “key” position were viewed as possessing greater amounts of reward power than persons playing a less key position. This finding suggests that individuals view persons in key positions as having more direct access to and control of desired rewards. This does seem logical, particularly if one considers the sport targeted in the current investigation (North American football). Because a quarterback tends to function as a team’s on-field decision maker (they are often referred to as “field generals”), other players may perceive of the quarterback as possessing the ability to make decisions that are favorable to them. For instance, a wide receiver may view the quarterback as a powerful figure because he/she could throw often to the receiver. Because the quarterback controls access to this desired reward (i.e., play selection and pass execution), he or she is able to change the attitude and/or behavior of the receiver. With respect to coercion, no differences in perceptions of this form of power were found between central, critical, flexible, visible, and relevant positions and positions lacking these

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qualities. At first glance, this finding may seem puzzling, particularly in light of the fact that persons occupying key positions were perceived of as possessing greater levels of reward power. For instance, to return to the example above, one may be tempted to argue that the receiver should also be concerned that the quarterback will not throw to him or her. Consequently, he or she will view the quarterback as an individual possessing large amounts of referent power. However, such logic is invalid and reflects the common confusion between punishments (i.e., coercion) and response cost (see Wann, 1997, for an in-depth discussion of the sport implications of these two strategies for changing behavior). Coercion and punishment involve the application of a negative stimulus to decrease unwanted behavior. An obvious sport example would be a football coach requiring her receivers to run laps each time they dropped a pass. Conversely, response cost involves the removal or withholding of a positive stimulus to decrease behavior. Thus, response cost, rather than punishment or coercion, is being employed when a quarterback refuses to throw to a particular receiver or call a play for a specific player. Rather than applying a negative stimulus, the quarterback is withholding a positive consequence. In all likelihood, punishment and coercion are only initiated by the head coach of a team. Other members of the coaching staff and even prominent players such as team captains are more likely to utilize response cost as a method of reducing unwanted behaviors. The work by Wann and his colleagues (2000) substantiates this line of reasoning as they found that head coaches were perceived as possessing significantly greater amounts of coercive power than assistant coaches. There are a number of important implications to the findings detailed above, for both coaches and sport psychologists alike. With respect to coaches, it would be in a coach’s best interest to locate players who are viewed by teammates as most powerful. Most likely, these will be the players who are able to most effectively exert influence on other players, including the desires of the coaches. Coaches are often better able to encourage compliance with team rules and regulations when powerful players exert force toward the same end. Players would seemingly be less likely to challenge a coach’s directives if powerful players push for the same directives. Thus, coaches are wise to get key players to adopt their position and help in influencing the remainder of the team (in fact, this is often viewed as one of the responsibilities of a team captain). The data presented above, coupled with the theoretical framework offered by Whetten and Cameron (1984), provide coaches with valuable information on whom these powerful players will be. That is, coaches should look to align themselves with players occupying central, critical, flexible, visible, and relevant positions. Alliances between coaches and players occupying powerful positions may be particularly valuable during certain times. For instance, the initial days of training camp are an important time in teaching team norms to new players. A unified front involving powerful players and coaches would be highly effective in facilitating the socialization process for new players. Similarly, coaches could use the support of powerful players during crises, such as during a long losing streak or when there is desention among teammates. With respect to sport psychologists, these applied professionals could also benefit from aligning themselves with powerful players. One of the most difficult tasks facing performance enhancement professionals is getting all players on a team to commit to a psychological skills program. In many instances, although some teammates readily endorse such programs, other players are quite hesitant and skeptical. By gaining the endorsement of key players, that is, those players viewed as powerful, the sport psychologist may get a larger proportion of the team to accept the program. Again, the

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current study and the model it tested offers concrete and (now) empirically supported predictions of who these players will be. Finally, because this was the first sport-specific test of Whetten and Cameron’s (1984) model, additional research is warranted. Such research should focus on different sports and positions within those sports (e.g., pitchers in baseball and point guards in basketball) and with other levels of competition (e.g., scholastic, recreational, professional/elite). Another important step in this research would involve testing the self-perceptions of players occupying the key positions. Wann et al. (2000) found a great deal of similarity between self-perceptions of power and how one is viewed by others. For instance, head coaches felt that they possessed high levels of legitimate power and players did in fact view these individuals as possessing high levels of this form of power. Based on Wann’s findings, one would expect that players occupying central, critical, flexible, visible, and relevant positions to view themselves as possessing greater amounts of power (particularly expert, legitimate, and, perhaps, reward power) than persons playing other positions.

REFERENCES Baron, R. A., and Greenberg, J. (1990). Behavior in organizations: Understanding and managing the human side of work (3rd ed.). Needham Heights, MA: Allyn and Bacon. Boje, D. M., and Whetten, D. A. (1981). Effects of organizational strategies and contextual constraints on centrality and attributions of influence in interorganizational networks. Administrative Science Quarterly, 26, 378-395. Celladurai, P., and Carron, A. V. (1977). A reanalysis of formal structure in sport. Canadian Journal of Applied Sport Sciences, 2, 9-14. French, J. R. P., and Raven, B. (1959). The bases of social power. In D. Cartwright (Ed.), Studies in social power (pp. 150-167). Ann Arbor, MI: Institute for Social Research. Glenn, S. D., and Horn, T. S. (1993). Psychological and personal predictors of leadership behavior in female soccer athletes. Journal of Applied Sport Psychology, 5, 17-34. Grusky, O. (1963). The effects of formal structure on managerial recruitment: A study of baseball organization. Sociometry, 26, 345-353. Hellriegel, D., Slocum, J. W. Jr., and Woodman, R. W. (1992). Organizational behavior (6th ed.). West: New York. Hickson, D. J., Hinings, C. R., Lee, C. A., Schneck, R. E., and Pennings, J. M. (1971). Strategic contingencies theory of intraorganizational power. Administrative Science Quarterly, 16, 216-229. Hinings, C. R., Hickson, D. J., Pennings, J. M., and Schneck, R. E. (1974). Structural conditions of intraorganizational power. Administrative Science Quarterly, 21, 22-44. Keys, B., and Case, T. (1990). How to become an influential manager. Academy of Management Executive, 4, 38-51. Knoppers, A., Meyer, B. B., Ewing, M., and Forrest, L. (1990). Dimensions of power: A question of sport or gender? Sociology of Sport Journal, 7, 369-377. Korda, M. (1975). Power: How to get it, how to use it. New York: Ballantine. Kozub, S. A., and Pease, D. G. (2001). Coach and player leadership in high school basketball. Journal of Sport Pedagogy, 7, 1-15.

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Lee, M. J., Partridge, R., and Coburn, T. (1983). The influence of team structure in determining leadership function in Association Football. Journal of Sport Behavior, 4, 170-183. Loy, J. W., Curtis, J. E., and Sage, J. N. (1979). Relative centrality of playing position and leadership recruitment in team sports. In R. S. Hutton (Ed.), Exercise and sport science reviews (Vol. 6). Santa Barbara: Journal Publishing Affiliates. Mechanic, D. (1962). Sources of power of lower participants in complex organizations. Administrative Science Quarterly, 7, 349-364. Melnick, M. J., and Loy, J. W. (1996). The effects of formal structure on leadership recruitment: An analysis of team captaincy among New Zealand Provincial rugby teams. International Review of the Sociology of Sport, 31, 91-105. Perrow, C. (1970). Departmental power and perspectives in industrial firms. In M. N. Zold (Ed.), Power in organizations. Nashville: Vanderbilt University Press. Podsakoff, P. M., and Schriesheim, C. A. (1985). Field studies of French and Raven's bases of power: Critique, reanalysis, and suggestions for future research. Psychological Bulletin, 97, 387-411. Salancik, G. R., and Pfeffer, J. (1977). Who gets power—and how they hold on to it: A strategic-contingency model of power. Organizational Dynamics, 5, 3-21. Slack, T. (1997). Understanding sport organizations: The application of organization theory. Champaign, IL: Human Kinetics. Steele, N. L., and Wann, D. L. (1999). Type of play, temporal position, salience, and attentional focus of sport spectators. Psi Chi Journal of Undergraduate Research, 4, 113118. Stodgill, R. M. (1963). Manual for the Leader Behavior Description Questionnaire--Form XII. Columbus, OH: Ohio State University Bureau of Business Research. Tropp, K. J., and Landers, D. M. (1979). Team interaction and the emergence of leadership and interpersonal attraction in field hockey. Journal of Sport Psychology, 1, 228-240. Wann, D. L. (1997). Sport psychology. Upper Saddle River, NJ: Prentice Hall. Wann, D. L., Brewer, K. R., and Carlson, J. D. (1998). Focus of attention and sport spectators: Beliefs about causation. Perceptual and Motor Skills, 87, 35-41. Wann, D. L., Metcalf, L. A., Brewer, K. R., and Whiteside, H. D. (2000). Development of the Power in Sport Questionnaire. Journal of Sport Behavior, 4, 423-443. Wann, D. L., and Steele, N. L. (1998). Attentional focus of sport spectators. Perceptual and Motor Skills, 86, 1163-1167. Whetten, D. A., and Cameron, K. S. (1984). Developing managerial skills. Glenview, IL: Scott Foresman. Yukl, G. (1994). Leadership in organizations (3rd ed.). Upper Saddle River, NJ: Prentice Hall.

Contemporary Athletics Compendium, Volume 3 Editor: James H. Humphrey

ISBN: 978-1-60741-561-9 © 2009 Nova Science Publishers, Inc.

Chapter 24

STRESS FACTORS IN THE PROFESSION OF COACHING: ASSESSING THEIR NATURE, SCOPE AND IMPACT Deborah A. Yow1, James H. Humphrey1 and William W. Bowden2 1

2

University of Maryland, College Park, Maryland, USA Strategic Management Associates, Athens, Georgia, USA

ABSTRACT The coaching profession is most appropriately characterized by the profound uniqueness of its nature. A coach is at once a teacher, a psychologist, a father/mother figure and other roles which he or she finds it expedient or necessary to assume at a given time. Clearly, the college athletic coach labors in a distinctly stressful environment. It is a volatile and often unpredictable profession involving numerous and concurrent pressures. These include the need to continuously interact personally and effectively with his or her student athletes regarding myriads of training, competitive, academic and personal issues. There is also the continuous pressure to recruit and develop a winning team and the need for the coach and players to handle defeat. Add to this relational element with student athletes the human relations which must be maintained with his or her sports supervisor (athletic director, assistant athletic director or associate athletic director), the parents of student athletes, individuals in the media, high school coaches, boosters/fans, assistant coaches, athletic department support staff, and myriads of others, then we see the compelling matrix of human relations which must be attended to by the coach (not to mention the personal and family relations which are often challenging to maintain because of the considerable demands and pressure of the profession).

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THE ESSENCE OF COACHING The essence of coaching is the balance between being caring, motivational, supportive, and approachable, while maintaining the firm discipline, strategic drive and uncompormising determination to require of student athletes the academic and competitive excellence which also characterize the work of outstanding college coaches. Again, effective human relations are as important to a coach’s long term success and respect as his or her command of the game itself. Clearly, coaching intercollegiate sports demands many more competencies than just being able to teach a specific skill. It is possible that some coaches might be unable to physically and psychologically cope with the stress resulting from the human demands on their energy, emotions and time. At the same time, however, it is clear that coaching as a profession can be as enjoyable and fulfilling as it can be frustrating and difficult. Successful coaches accept the rigors of their profession while they also recognize their own strengths and weaknesses. Although they are constantly striving for improvement and development, they maintain a healthy level of self-affirmation. As a result, they remain psychologically well adjusted and successful a majority of the period of their coaching careers, while also experiencing the inevitable sense of vulnerability from time to time. Indeed, most coaches admit to the fact that their jobs can be fraught with a variety of mild to quite serious stress inducing factors. In order to assess the scope and impact of these and other stress inducing factors, the authors conducted a comprehensive survey of stress among collegiate coaches and in the college athletic environment. The results are discussed extensively in the book by the authors entitled, Stress In College Athletics: Causes, Consequences and Coping (along with a thorough examination of stress among athletic administrators and student athletes, published by Haworth Press). Here, we will examine the causes and consequences of stress among collegiate coaches and then discuss a variety of their attempts to cope with this stress.

CAUSES OF STRESS We obtained firsthand from coaches themselves those factors which induced the most stress, their consequences and how they attempt to cope with them. This was accomplished by simply requesting that they identify those factors connected with their jobs that were most stressful for them, how this stress affected them, and how they attempted to cope with this stress. Obviously, this resulted in a large mass of data. It was helpful to sort out the stressors and place them into a number of kinds or classifications. The difficulty encountered in attempting to devise a seamless system for classification of the coaches’ stressors was the fact that it is sometimes not possible to fit an identified stressor in one exclusive classification because it may touch upon or overlap another kind of stressor. However, an attempt was made to do so and the results indicate that the classifications are representative of the kinds of responses received from collegiate coaches. The following predominant classifications of coaches’ stressors were identified: Players; Performance/Results; Outside Influences; Time; Associates; Public Relations; Finance.

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Student Athletes/Players There is no question that those who participate on an athletic team are its most important asset. Anyone knows that without the proper material (adequate player personnel) coaches would not be able to consistently produce competitively successful teams. But many coaches are in the profession because of the personal satisfaction they derive from dealing with the young men and women with whom they are associated, whatever their skill level. It is not uncommon for coaches to refer to team members and others closely associated with them as a “family.” And, even though in most families the members love and respect each other, at the same time they can be stressful to one another. So it is not surprising that players are frequently a significant stress-inducing factor for coaches. Indeed, in this stress classification (players), 85 percent of the coaches reported sources of stress. These stressors are identified in the following list of subclassifications, with the descriptors of this and each of the other areas stated in the words of the coaches. 1. Player Behavior and Attitude. This was a serious stressor for coaches as evidenced by the fact that 38 percent of the player stressors were in this category. The things that stressed coaches the most in regard to player behavior and attitude were the following: • • • • • • • • • •

Apathy and indifference of players. Social problems such as the need for drug testing. Players behaving improperly or unlawfully on campus and in the local community. Insubordination of players. Dissensions among players. Selfishness of players. Any kind of team conflict. Players not accepting responsibility for their own actions. Lack of maturity of players. Players who do not have the best interest of the team.

2. Recruiting. It is not surprising that 22 percent of player stressors are found in this category. Coaches were not only stressed by the general aspect of recruiting, but specific aspects were stated as follows: • • • •

Failing to sign the top athletes. Not getting your quota of recruits. The last two days of recruiting are especially stressful. Rejecting people who expect to be recruited.

3. Academic Performance of Players. Seventeen percent of the player stressors were in this category. It is well known that numerous troubling and even scandalous incidents in college athletics have been related to academic issues. Among the stressors for coaches were: • • • •

Players not interested in graduating. The stress of keeping players eligible to participate. Players failing to progress academically. Cheating on examinations or otherwise receiving fraudulent grades.

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4. Player Performance. Coaches are concerned about how their players perform and 15 percent of the stressors were in this category. Among the most important were: • • • • •

Players not performing to their potential. Not getting the best effort or attitude from players. Difficulty in motivating players to perform. Excuses of players for not performing well. Lack of dedication and commitment of players.

5. Injuries. Coaches worry about injuries to players–both in regard to the success of the team and their feelings and concern for their players. Eight percent of the stressors were in this category and as might be expected the majority of concerns regarding injury were among football coaches. Finally, it should be mentioned that the player-coach stress factor is a natural phenomenon. This is to say that in most instances the same sort of relationship prevails among most caretakers or custodians with persons who are in their charge. Studies show that physicians and nurses are stressed by patients, teachers are stressed by students, prison guards are stressed by inmates, and further that conditions precipitating long-term stress are essentially the same for all of these groups.

Performance/Results This category of stressors pertains to the performance of the coach himself or herself. In this classification a notable 74 percent of the coaches reported sources of stress. This classification overlaps to some extent with performance of players, but for the most part involved the coach’s own feeling about his or her ability and performance. No attempt was made to make subclassification because of the difficulty in doing so. Coaches stated these examples of performance-related stressors: • • • • • • • • •

Inability to produce consistently winning teams. The frustration of not having practices which get us ready for what must be done in games. Game day performance. Losing games that should have been won. Not winning the big game. Losing games on chance factors or circumstances that were perceived as beyond the control of the coach. Waiting for the kickoff before a game. High expectations not met. Game day participation/performance of coach.

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Outside Influences Included here is any individual who is outside the immediate group of team members, coaches and others who have a close working relationship with the team such as trainers, managers, chaplains, and team physicians. A remarkable 56 percent of the coaches reported stressors in this classification. Included among such stressors stated were: • • • • • • • • • •

Reactions of alumni and other fans. Not being able to please administrators. Officiating. Hate mail. NCAA rules and policies. Dealing with unqualified people trying to run my job. Things that are controlled by others. Criticism that is unwarranted. Outside influences on athletes such as drugs, alcohol and agents. Faculty members who do not accept the value of athletics in the total university program.

Time In most studies of occupational stress well over one-fourth of the respondents cite factors related to time as serious causes of stress. One half of this number say there is insufficient time for planning and about one-third of them say there is not enough time in the day to do the job expected of them. Notably, 38 percent of the coaches reported stressors in this classification. Such stressors included in their statements were: • • • • • •

Not having enough time for family. Not enough time to get everything done. Time and priority allocations. Abundance of time-consuming travel required. Meeting deadlines. Not enough time for players’ needs.

Associates Success in any endeavor, coaching included, depends upon the cooperation of group members. In the present context associates are identified as the assistants to the head coach. It was surprising to find that 32 percent of the coaches reported this classification as a cause of stress. Most coaches maintain firm control and good relationships in dealing with staff members, but according to our findings this is clearly not always the case. In fact, one coach made this statement: “Much stress is created by groups within the staff itself. Selfishness is a

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key to stressful situations. The less selfishness within the staff, the less stressful situations are seen.” The following were stated most stressful in this category: • • • • • • • •

Getting personalties of the program to work together. Unpleasant interpersonal relationships with staff. Treating conflicts among staff members. Lack of communication with staff. Staff placing their recruits ahead of needs of the team. Motives of associates. Motivating staff. Hiring and maintaining a stable staff.

Public Relations Twenty-one percent of the coaches reported some aspect of public relations as being stressful. The stressors were related to the areas identified by these coaches in their following statements: • • • • • • •

Misunderstanding by the media and public. Lack of media understanding and printing the truth. Media innuendo. Dealing with time demands of the media. Dealing with time demands of the public. Being in public after losing a game. Boosters, alumni and fans who don’t have a clue.

Finances A majority of coaches feel that the financing of athletic programs is mainly the responsibility of others and only 12 percent of them reported this classification as a source of stress. A few coaches indicated that they felt stress due to the lack of money for their programs and others said they were under stress to win in order to finance other sports. The preceding discussion of the data on stress-inducing factors was presented as an aggregate to include all coaches who provided responses. At this point it seems appropriate to cite these comparative data for female coaches and male coaches. The information in Table I is provided for this purpose. It would be speculative at best to offer reasons for the differences between female and male coaches. Each reader will interpret the results individually. However, we would comment on the significant difference in the stressor classification of Public Relations. We have discussed this with selected female coaches who feel that they generally do not have enough media attention nor sufficiently pervasive or vigorous public interest for these sources to create significant stress. (It is possible that indeed this lack of attention for their sport could be a potential stressor for a number of females. Again, however, this would be speculation since the study did not focus on this issue.)

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Table I. Comparison of Stressors for Female and Male Coaches Stress Classification

Percent for Females

Percent for Males

Players

90

83

Performance

90

67

Outside Influences

50

58

Time

50

33

Associates

20

38

Public Relations

6

29

Finances

10

13

CONSEQUENCES OF STRESS The effect that stress has on coaches can be classified into the following two broad areas: (a) impact on physical health, and (b) impact on mental/emotional health. Forty seven percent of the coaches perceived an impact on their physical health while more than half of them said that stress impacted their mental/emotional health. The following statements by coaches indicate how it affected them physically. • • •

It affects me physically with loss of sleep. Stress will have an influence on my eating habits and sleeping. Very often stress causes me to have an upset stomach.

Regarding its effect on mental/emotional health a number of coaches commented as follows. • • •

Sometimes I have an emotional outburst against the team and I hate myself for it after it is over. I get terribly frustrated when I lose and it takes me too long to get over it. It causes me to get angry with no really good reason for it.

Only about 10 percent of the coaches said that stress did not bother them. They made such comments as the following. • • •

Stress in coaching can be handled with a systematic daily routine of spiritual nourishment; therefore it does not bother me. Stress is greatly overrated. If you are organized and have a plan you should not be stressed. I never feel any stress in coaching; however, maybe I experience it but don’t know that I’m experiencing it.

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COPING WITH STRESS We learned that the coping techniques of coaches fell into what can be called coping behaviors and coping techniques.

Coping Behaviors Regarding the coping behaviors inherent in the basic principles of living, the following results of the study were apparent.

Principle #1: Practicing Good Personal Health Habits The imposing work load of a coach may cause him or her to neglect the basic requirements that are essential for the human being to maintain an adequate functional health level. (Recall how stress had an effect on the physical health of some coaches.) Fifty-six percent of the coaches said they abided by this principle in attempting to cope with the stress of their profession. This leaves almost half of them who are neglectful of some aspect of their personal health. Principle #2: Learnt to Recognize and Value Your Own Accomplishments Sometimes coaches do not accept or assume enough credit for their own performance and achievements. (See previous comment under performance as a cause of stress for coaches.) Twenty-six percent of the coaches said that they practiced this principle of valuing their own achievements as a means of coping with stress. Principle #3: Learn to Take One Thing at a Time Some coaches are likely to put things off, especially unpleasant things, and as a consequence frustrations can build as tasks pile up. An important solution to this for coaches is the practice of taking one task or problem at a time. We are all familiar with coaches who also talk about “taking one game at a time.” Budgeting of time can also help eliminate serious worries related to time urgency and the feeling of “too much to do in too short a time.” Sixtyone percent of the coaches indicated that they practiced this principle in order to diminish the stress under which they were functioning. Principle #4: Learn to Take Things Less Seriously Often a coach will take the loss of a game too seriously. It is important to remember this single truism: A game that has been lost can never be won no matter how much a coach may fret or agonize over it. Those coaches who are able to keep the challenges of their profession and specific losses in perspective and to see the humorous side of various situations tend to look at a potentially stressful situation more objectively. Clearly, this can assist in keeping stress levels lower. Forty-seven percent of the coaches said they attempt to abide by this principle. Principle #5: Do Things for Others It can be stated unequivocally that most coaches try to do a considerable amount on behalf of their players. That in itself, as well as other acts of assisting individuals in some

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way, can help to relieve coaches from stress. Generally, this is a principle of human nature. Fifty-three percent of the coaches said that they practiced this principle in order to relieve stress.

Principle #6: Talk Things Over with Others One coach commented that it could be a good idea for coaches to get together in order to have a dialogue about the stressful conditions of the profession. It is important to keep in mind that such discussion should best be positive and objective lest it degenerate into idle gossip. Of course there is value sometimes in simply venting frustrations or fears regarding challenges, problems, and issues. Three-fourths of the coaches said they practiced this principle and in most instances they talked issues over with family members or close friends. These were the prevailing six life principles practiced by coaches in coping with stress.

Coping Techniques Coaches were asked to identify those techniques they used in attempting to deal with stress. These techniques involved the following methods. Three techniques which are specifically used for inducing a relaxation response–muscle relaxation, meditation, and biofeedback; they also used the techniques of physical exercise, recreational activities, resorting to divine guidance, and consumption of alcoholic beverages. The three techniques for inducing a relaxation response were as follows: 17 percent used muscle relaxation, 3 percent used meditation, and less than 1 percent used biofeedback. Eighty-six percent of the coaches engaged in physical exercise as a means of reducing stress. However, the majority said that this was done more or less sporadically. Half of the respondents said they engaged in recreational activities, including such activities as reading, card games and listening to music. Slightly more than half of the coaches resorted to divine guidance and the following are representative statements in this regard. • • •

In dealing with stress, I put my faith in God. A personal commitment to Christ is my central theme, and the only way I have been able to lessen stress. When I feel stressed I personally draw peace and strength from my relationship with the Lord.

Ten percent of the coaches said they used alcohol with some regularity in order to cope with the stress of their work. Simply stated, individuals dealing with the problems of stress differ, techniques for dealing with stress differ, and what might be successful for one person might not be necessarily so for another. Finally, the information presented in Tables II and III is intended to make comparisons of female and male coaches in terms of the procedures they use to cope with stress. Table II reflects a comparison of the “application of principles of living,” and Table III presents “specific coping techniques.”

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Again, the reader is left to his or her own judgment regarding the reasons for the differences. It is not entirely clear which of the genders in the coaching profession is more sensitive to or susceptible to stress reactivity, or which of the interventions are most useful. In the absence of completely objective evaluative criteria, such questions will remain difficult to answer. Table II. Comparison of Female and Male Coaches in the Application of Principles of Living to Avoid Stress Principle

Percent for Female

Percent fo Male

Observation of Personal Health Practices

45

60

Recognizing Your Own Accomplishments

27

40

Taking One Thing at a Time

67

60

Taking Things Less Seriously

45

48

Doing Things for Others

45

36

Talk Things Over With Others

78

72

Table III. Comparison of Female and Male Coaches for Specific Stress-Reducing Techniques TechniquePhysical Exercise Recreational Activities

Percent for Female

Percent fo Male

Physical Exercise

91

84

Recreational Activities

36

56

Muscle Relaxation

18

16

Meditation

0

4

Biofeedback

0.2

0.4

Divine Guidance

55

56

Use of Alcohol

8

12

What is very clear is that coaches function under considerable stress and that among a significant percentage of college coaches this stress is pervasive and almost unrelenting. In February 1999 the Iowa State Legislature presented the University of Iowa’s retiring head football coach, Hayden Fry, with a ceremony and Resolution of Appreciation for his 18 years of service to the institution and the state. Coach Fry’s final season had ended several weeks before, but one of his compelling statements at the ceremony was, “I’m trying to learn how to relax." Coaches across the profession would understand his statement–after his 18 excellent

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years at Iowa, following his successful years at Southern Methodist University and previous experiences. Clearly, it was only after he was out from under the unrelenting stress of the coaching profession that he was at last finding an opportunity “...to relax.” Coaches, in general, will understand the full dimension of that statement.

ACCOUNTABILITY FOR STUDENT ATHLETE WELFARE One notable current movement in the NCAA is the viable and pervasive emphasis on student athlete welfare. Among the several emphases of this movement are the physical, academic and personal welfare of the college athlete. This trend represents an important recognition of the accountability that the athletic department, the institution and the coaching staff must accept to assure that in every way possible each athlete will be viewed as a person of value and importance beyond the court and playing field–that they are worthy of everyone’s best effort to see that they develop and succeed as an individual and as a student. But authentically great coaches have for decades accepted this role and this accountability. In July 1954 coach Brutus Hamilton, respected track coach at the University of California at Berkeley, wrote a recruiting letter to an outstanding high school runner named Don Bowden. It reflected his commitment to the welfare and total development of the student athlete and his commitment to “coaching the whole person.” “There is not much I can add to what I told you when you last visited the campus. You know pretty well what kind of a coach I am, since we have visited together and since you heard me speak at your meeting there in San Jose. You know our facilities, our schedule, and you know the prestige of the university as an educational institution. There can be no degree more coveted than one earned here. I think you know, too, that we have a healthy attitude toward sports here at Berkeley. We want our boys to win; we want them to maximize their potentialities in sports, but we don’t want them doing so at the expense of the more serious phases of college life [italics added]. Your principal purpose in going to college, of course, is to get an education in your field of study which will probably be medicine. If you can break the world’s record in the half-mile, which seems quite likely to me, while doing this, well and good. The main thing, however, is to be graduated a capable, self-reliant young man which your parents and friends want you to be. I can assure you that we here in the Athletic Department will do everything possible to see that your goals are achieved.”

Don Bowden enrolled at the University of California at Berkeley, was a successful student and became the first American to run the mile in under 4 minutes (on June 1, 1957). Likewise, in 1999 the highly conscientious head football coach at the University of Maryland expressed his commitment to the welfare of his student athletes when he said, “I measure my success not solely by our wins on the field, but also by our young men winning in the classroom and in life. That is our firm and uncompromising goal and we will not settle for less.” (Coach Ron Vanderlinden, College Park, Maryland, February 1999.) The kind of accountability embraced by these and many other college coaches clearly adds to the scope of responsibility and the stress of the profession, but they indicate that it also presents an opportunity for the job of coaching to take on a more meaningful and personal dimension.

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Deborah A. Yow, James. H. Humphrey and William W. Bowden

We have discussed in some depth the stressors which challenge college coaches, the results or consequences of these stressing factors, and the ways in which coaches attempt to cope with stress in their professional experience. The findings are interesting and compelling – and indicate the prevalence of mild to very serious stress among collegiate coaches. The results of this study will also be quite helpful to athletics administrators who interface with coaches and, of course, to coaches themselves.

ABOUT THE AUTHORS Deborah A. Yow, Director of Athletics at the University of Maryland, has authored numerous articles and books and is a nationally respected leader and athletics administrator. Dr. Yow has served as a member of the NCAA Management Council and other prestigious athletics and educational agencies and commissions. She has served as President of the National Association of Collegiate Directors of Athletics and currently serves as President of the Division IA Athletic Directors Association. James H. Humphrey, Professor Emeritus at the University of Maryland has authored or coauthored more than a dozen books about stress, including Stress in Coaching. His articles and research reports have appeared in more than 20 national and international journals and magazines. Considered a pioneer in stress education, he is the founder and editor of Human Stress: Current Selected Research and editor of the 16-book series on Stress in Modern Society. William W. Bowden is President of Strategic Management Associates, an education and business consulting firm which has worked with dozens of colleges, universities, corporations and the NCAA in their athletics interests and their management challenges. He served previously as a university administrator and is the author of more than 40 research reports, articles and books.

Contemporary Athletics Compendium, Volume 3 Editor: James H. Humphrey

ISBN: 978-1-60741-561-9 © 2009 Nova Science Publishers, Inc.

Expert Commentary

NEW TECHNOLOGY HOLDS PROMISE FOR THE FUTURE APPLICATION OF PSYCHOPHYSIOLOGICAL METHODS FOR THE ENHANCEMENT OF PERFORMANCE DURING SPORT AND EXERCISE David L. Neumann∗ School of Psychology, Griffith University, Southport, QLD, Australia and Centre of Excellence for Applied Sport Science Research, Queensland Academy of Sport, Queensland, Australia

COMMENTARY Psychophysiology is the study of psychological processes through the measurement and interpretation of physiological responses (Cacioppo, Tassinary, Berntson, 2007). The realisation of the relationship between the so-called “mind” and “body” has encouraged the application of psychophysiology in various areas of psychology, including sport psychology (see Hatfield and Hillman, 2000). Unfortunately, methodological problems have limited the application of psychophysiological techniques to the study of sport. The gross body movements in most sports cause considerable degradation in the quality of the physiological recordings. The obtrusiveness of the electrode attachments and the wiring of the electrodes to a data acquisition system can also severely impede the athlete’s mobility and performance. It is perhaps not surprising that most psychophysiological research has been concerned with sports that involve minimal movements, such as pistol shooting (e.g., Mets, Konttinen, and Lyytinen, 2007). However, a range of new technological advances are giving encouragement for future applications of psychophysiological methodology in sport. ∗

Address for correspondence: David Neumann, School of Psychology, Griffith University (Gold Coast Campus), Mail: GRIFFITH UNIVERSITY QLD, Queensland, 4222, Australia, E-mail [email protected], Facsimile +61(0)7 5552 8291, Telephone +61(0)7 5552 8052

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New data filtering and processing techniques have been developed to greatly improve signal quality. A case in point is the recording of heart rate, which has shown to be sensitive to both physical and psychological states in exercising individuals (e.g., Szabo, Peronnet, Gauvin, and Furedy, 1994). Commercially available equipment can record heart rate averaged across several seconds or more using non-invasive and robust devises that can be worn on the wrist like a watch or as a strap around the chest. Such techniques are useful, but can be limited when more precise measurement of heart rate is required. In many cases, heart rate needs to be time locked to certain behaviours (e.g., the onset of a baseball pitch) or indices derived from the biosignal that underlies heart rate (e.g., T-wave amplitude) are required. In such cases, the electrocardiogram (ECG) itself must be acquired. Although the ECG is a relatively large biosignal, it can still be difficult to obtain clear recordings in active athletes due to the noise created by muscle activity and artefacts created by movement. Improvements in the quality of the recording electrodes to allow for a firmer attachment and improved conductive gels can reduce artefacts caused by moderate movements at the source. New data processing techniques are providing additional solutions. Noise may be removed in many cases using digital signal processing techniques such as wavelets (Celka and Gysels, 2006), nonlinear methods (Schreiber and Kaplan, 1996), adaptive filtering (Thakor and Zhu, 1991), and principal components analysis (Moody and Mark, 1989). Motion artefacts that persist in the signal may also be removed with some success using these modern digital signal processing techniques (e.g., Renevey, Vetter, Krauss, Celka, and Depeursinge, 2001). Significant challenges still remain for smaller biosignals, such as the electroencephalogram, although future technologies hold promise for improvements in the quality of even these biosignals. The use of an electromyographic signal to cancel out muscle and motion artefacts from the ECG was recently demonstrated during a rowing task (Celka and Kilner, 2006). Rowing is a continuous and energetic task that greatly impacts on the recording of ECGs from the chest. For such recordings, the biosignals generated by the pectoral and surrounding muscles and movement artefacts are a problem. To recover the ECG during rowing, the electromyogram recording of the distal pectoral muscle was used to provide a reference signal for motion and muscle activity cancellation. This additional reference information, in combination with bandpass and adaptive filters, allowed the ECG to be recovered even during highly vigorous rowing by trained rowers. I have applied the same technique during a cricket batting task. Although cricket batting represents a different task to rowing (e.g., it is a discrete task of relatively clear ECG recordings punctuated by sudden and rapid movements), the ECG during the entire task could be recovered successfully using the relatively low-complexity technique of Celka and Kilner (2006). It should also be noted that such techniques could be used the other way around, that is, by using concurrent recordings of ECG and cancellation techniques to improve the quality of electromyographic recordings. Another technological advancement that encourages further psychophysiological study in sport is the increased simplicity of the data acquisition equipment. In addition to becoming less expensive, the recording equipment has become easier to set up. Interfacing with a computer no longer necessitates the use of input/output cards and complicated calibration settings. There are now several commercially available systems that interface with a computer by using plug-and-play universal serial bus (USB) connections. Such technology also allows the standard laptop computer to be used for data acquisition. Finally, the recording equipment

New Technology Holds Promise for the Future Application…

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is becoming smaller in size, thus increasing the portability of the system when used during on-field studies of a sport. Perhaps one of the most significant technological advances for sport application has been the development of new wireless portable or telemetry systems. Such systems allow the athlete to be physically separated from the data acquisition equipment. As such, the athlete is afforded greater freedom of movement and can be less conscious of avoiding the wires and damaging the equipment. This can be particularly important for psychological research because researchers want to avoid a situation in which the measurement technique changes the behaviours they were designed to observe. Also from a researchers perspective, wireless systems can allow psychophysiological measurements to be taken in many sports that have been unable to be studied in the past. Portable wireless systems can be used stand-alone in that the same unit can acquire the biosignal, do some signal processing, and store the information for later retrieval. Improved technology has increased the storage capacity of portable systems, thus allowing for recordings to be made for longer periods or at higher sampling rates. Telemetry systems can be used to acquire the biosignal and send this information via a wireless protocol to a receiving station for signal processing and storage. Such telemetry systems can allow for more sophisticated data processing techniques to be used and for on-line monitoring of the athletes psychophysiological responses. The adoption of new technological advancements in the psychophysiological study of sport has the potential to increase our understanding of performance-related psychological factors. Psychophysiological methods can provide unique information about psychological factors in sport that can be difficult to measure using self-report or behavioural observation. Moreover, psychophysiological techniques provide an excellent interface between the psychological and physical demands of many sports. Biofeedback, the process in which an individual’s biological state is played back to an athlete to help them gain control over a mental state or motor actions (Blumenstein, Bar-Eli, and Tenenhaum, 2002), is particularly well positioned to produce improvements in sports performance through the application of new technology. By using information obtained from biofeedback during the actual sport performance, rather than during simulated or post-session periods, a greater correspondence between performance and psychological state can be achieved. Moreover, by using new technological advancements in psychophysiological recording techniques, biofeedback information can be more accurate and applied in a wider variety of sports.

REFERENCES Blumenstein, B., Bar-Eli, M., and Tenenbaum, G. (Eds.) (2002). Brain and body in sport and exercise: Biofeedback applications in performance enhancement. New York: John Wiley and Sons. Cacioppo, J. T., Tassinary, L. G., and Berntson, G. G. (2007). Handbook of psychophysiology (3rd ed). New York: Cambridge University Press. Celka, P., and Gysels, E. (2006). Smoothly adjustable denoising using a priori knowledge. Signal Processing, 86, 2233-2242. Celka, P., and Kilner, B. (2006). Carmeli’s S index assesses motion and muscle artefact reduction in rowers’ electrocardiograms. Physiological Measurement, 27, 737-755.

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Hatfield, B. D., and Hillman, C. H. (2001). The psychophysiology of sport: A mechanistic understanding of the psychology of superior performance. In R. N. Singer, H. A. Hausenblas, and C. M. Janelle (Eds.), Handbook of Sport Psychology (pp. 363-386). New York, NY: John Wiley and Sons Inc. Mets, T., Konttinen, N., and Lyytinen, H. (2007). Shot placement within cardiac cycle in junior elite rifle shooters. Psychology of Sport and Exercise, 8, 169-177. Moody, G., and Mark, R. (1989). QRS morphology representation and noise estimation using the Karhunen-Loève transform. Computers in Cardiology, 16, 269-272. Renevey, P., Vetter, R., Krauss, J., Celka, P., and Depeursinge, Y. (2001). Wrist-located pulse detection using IR signals, activity and nonlinear artefact cancellation. Proceedings of the 23rd Annual International Conference of the IEEE, 3, 3030-3033. Schreiber, T., and Kaplan, D. (1996). Nonlinear noise reduction for electrocardiogram. Chaos, 6, 87-92. Szabo, A., Peronnet, F., Gauvin, L., and Furedy, J. J. (1994). Mental challenge elicits "additional" increases in heart rate during low and moderate intensity cycling. International Journal of Psychophysiology, 18, 197-204. Thakor, N., and Zhu, V. (1991). Application of adaptive filtering to ECG analysis: noise cancellation and arrhythmia detection. IEEE Transactions on Biomedical Engineering, 38, 785-794.

INDEX

9 9/11, 58, 59, 63

A AAA, 192, 194 Abundance, 285 academic, ix, xii, xiii, xvi, 40, 103, 104, 105, 106, 107, 108, 110, 137, 138, 141, 149, 150, 151, 152, 153, 154, 155, 156, 159, 181, 182, 183, 184, 187, 190, 197, 212, 232, 236, 237, 240, 241, 254, 256, 258, 259, 260, 281, 282, 283, 291 academic performance, 153, 187 academic success, 152, 153, 190, 256 academics, 109, 153, 154, 155, 161, 181, 183, 184, 185, 187, 188, 254 access, xi, 53, 86, 150, 153, 210 accessibility, 23 accidental, 62 accidents, 76 accountability, 34, 244, 291 accounting, 116, 230 accuracy, 23 achievement, 133, 152, 164, 189, 208, 232, 240 achievement test, 189 activity level, xii, 111, 114, 115, 119, 121, 122, 123, 126 ADA, 199, 205 adjudication, 196 adjustment, 49, 50, 232, 242 administration, ix, xii, 15, 26, 83, 84, 95, 103, 104, 105, 106, 107, 108, 110, 189, 196, 259, 266 administrative, 33, 34, 117, 156, 244, 256, 260 administrators, xiv, xv, 97, 98, 106, 155, 156, 159, 184, 185, 207, 208, 209, 217, 229, 239, 253, 254,

255, 256, 257, 258, 259, 261, 262, 264, 265, 266, 267, 268, 282, 285, 292 adolescence, 114, 124 adolescents, 90, 113, 114, 123, 124, 125 adult, xii, xiii, 111, 112, 113, 115, 116, 117, 119, 121, 122, 163 adult obesity, 112 adult population, 112, 113 adulthood, 98, 121 adults, 112, 113, 114, 116, 121, 122, 123, 124, 125, 126, 134, 138, 211 advertisement, 105, 132 advertisements, xii, 17, 18, 103, 106, 108, 110 advertising, 23, 129, 132, 138 aesthetics, 164 affective reactions, 49, 76 Africa, 235, 238, 239, 241 African American, 36, 115, 166, 212, 216, 221 African-American, 126, 141 afternoon, xiii, 127 age, xvii, xviii, 3, 13, 19, 35, 36, 49, 57, 67, 80, 81, 92, 115, 116, 122, 141, 166, 167, 173, 221, 231, 233, 234, 245, 260, 264, 273, 274 agent, 201 agents, 101, 112, 122, 140, 285 aggression, ix, 72, 95, 96, 101, 134, 164 aid, x, xv, 33, 39, 56, 92, 107, 156, 158, 229, 242, 256, 287, 289 AIM, 10, 17, 23 air, 139, 210 Alabama, 103, 210 Alaskan Native, 115, 260 Alberta, 268 alcohol, 128, 130, 131, 285, 289 alcohol consumption, 128, 130 alienation, 66, 71, 210, 220 alpha, 45, 50, 116, 211, 222, 223, 260, 275 alternative, 84, 128, 178, 192, 195, 203 alternatives, 4, 125

298

Index

ambiguity, 34, 77 American Council on Education, 266 American culture, 232 American Indian, 115, 221, 260 amplitude, 294 anabolic, 89, 91, 96, 99, 100 anabolic steroid, 89, 91, 96, 100 anabolic steroids, 89, 96, 100 anger, 63, 220 ANOVA, 169, 170, 171, 260, 262, 263, 276 antecedents, 88 anti-terrorism, 64 anxiety, 44, 50, 51, 211 apathy, 185 appellate courts, 156 application, xvi, 12, 60, 64, 109, 129, 132, 197, 278, 280, 289, 293, 295 arbitration, xiv, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205 argument, 21, 98, 152, 154, 156, 157, 193 Arizona, 89, 90, 160 arrest, 196 arrhythmia, 296 Asia, 87, 235, 239 Asian, 36, 115, 141, 221, 260 Asian American, 221 assault, x, 53, 54, 55 assessment, xiii, 24, 55, 60, 61, 63, 116, 125, 126, 153, 177, 179, 181, 187, 188, 189 assessment procedures, 60, 61 assets, 55, 60 assignment, 34, 272 associations, 68, 83 assumptions, 46, 207, 209 athleticism, 189, 210 Atlantic, 159, 178 atmosphere, 128, 158, 192, 210, 215 attachment, 14, 268, 294 attacks, 54, 55, 58, 59, 63 attention, 43, 44, 58, 60, 178, 185 attitudes, xv, 30, 85, 126, 208, 214, 231, 257, 266, 269, 270, 271 attractiveness, xv, 139, 229, 236, 237, 238, 239, 240, 241 Australia, 106, 199, 293 authenticity, 49, 51 authority, 62, 184, 197, 199, 254, 267, 271, 272, 273 autonomous, 61 autonomy, 77, 79, 84 availability, xv, 106, 253, 255, 258, 261 awareness, 61, 96, 139, 217, 242, 264, 265

B bargaining, 156, 157, 196, 197, 200 basketball, xiii, 26, 30, 45, 66, 139, 140, 142, 145, 152, 153, 154, 155, 157, 158, 160, 164, 177, 178, 179, 183, 184, 185, 188, 209, 210, 224, 256, 279 beer, 130, 131, 134 behavior, ix, xii, 11, 23, 24, 48, 76, 77, 88, 96, 99, 100, 111, 112, 113, 114, 116, 119, 121, 122, 123, 126, 127, 129, 132, 144, 178, 184, 202, 210, 227, 270, 277, 278, 279, 283 Behavioral Risk Factor Surveillance System, 124 behavioral sciences, 242 behaviours, 294, 295 beliefs, 99, 113, 114, 123, 208, 210, 214, 215, 270, 274 benchmark, 131 benefits, xiv, xv, 71, 72, 123, 157, 160, 165, 175, 189, 191, 192, 193, 197, 200, 219, 220, 224, 225, 226, 227, 253, 254, 255, 258, 260, 261, 263, 264, 265, 268 beverages, 131, 132, 289 bias, 46, 80 Bible, 210 binding, 193, 194, 195, 198, 200 biofeedback, 289, 295 black, 152 blood, 130, 146 body size, xii, 111, 115, 117, 119, 121, 122 bomb, xi, 54, 60 bonds, 78 Boston, xvii, 30, 66, 126, 201, 217, 218, 242 bounds, 89 boys, 26, 91, 291 brand loyalty, 145, 225 breaches, 98 breakdown, 95 Britain, 232, 240 British, 63 broadcasters, 152 Brooklyn, 85, 266 Brutus, 291 buffer, 44, 49, 50 buildings, 60 burnout, 41 business, xi, 75, 156, 158, 160, 181, 193, 195, 200, 202, 203

C calibration, 294 California, 157

Index campaigns, xii, 127, 128, 129 Canada, 43, 106, 268 candidates, 108, 254 capacity, 18, 114, 179, 295 capital, 71, 188, 190 caps, 108 career development, 76 CAS, 198, 199, 205 case law, 130, 192 case study, ix, 1, 2, 3, 5, 63 category a, 284 category d, 180 Catholic, 212 Caucasian, x, xv, 33, 36, 166, 212, 216, 221, 243 Caucasians, 141 causal relationship, 10, 11, 72 causality, 113 causation, 114, 280 CBS, 138, 140 cell, 19, 207 Census, 112, 126 Census Bureau, 112, 126 Centers for Disease Control (CDC), 90, 99, 112, 113, 124, 126 certification, xiv, 154, 155, 207, 216, 217, 218 CFA, 46 Chad, vi, 137 cheating, 151 chemotherapy, 7 Chi square, 260, 261 Chicago, 86, 152, 189, 204 childcare, 258 childhood, xii, 111, 112 children, xi, xii, xv, xvii, 54, 111, 112, 113, 114, 115, 116, 117, 118, 121, 122, 123, 124, 125, 126, 128, 165, 175, 183, 214, 253, 255, 260, 261, 262, 265 China, 100 Christians, 212 chronic, 68 Cincinnati, 147 citizens, 183 citizenship, 88, 183 classes, 13, 19, 46, 108, 117, 159 classical, 63 classification, xiii, 149, 159, 225, 234, 282, 283, 284, 285, 286 classified, 48, 68, 69, 166 classroom, 66, 73, 156, 181, 184, 291 classroom settings, 73 cleanup, 100 clients, 150 clinical, 6

299

clinical assessment, 126 clinician, 6 clinicians, 30 clinics, 247 close relationships, 13 Co, 127, 196, 204 coaching staff, 183, 232, 249, 278, 291 codes, 124 coding, x, 25, 26, 54 coercion, 274, 277 cognition, 23 cognitive, xii, 10, 12, 16, 17, 18, 19, 20, 21, 22, 23, 43, 50, 111, 112, 113, 116, 117, 118, 122, 124, 125, 220, 224 cognitive activity, 116, 117 cognitive dissonance, 125 cohesion, 87, 208 collaboration, 150 collective bargaining, 156, 157, 196, 197, 200 college campuses, 184 college students, xiii, 13, 67, 137, 140, 141, 143, 164, 175, 211, 224, 226, 273 colleges, 37, 61, 90, 104, 106, 107, 108, 141, 151, 152, 156, 178, 230, 232, 242, 292 collegiate level, 198 collisions, 5 Colorado, xvii, 157, 178 colors, 54, 132 combined effect, 69, 70 commercial, 152 commercialization, ix, 152, 155, 159 commercials, 128 communication, 59, 99, 105, 133, 139, 140, 145, 146, 193, 256, 286 communication systems, 99, 133 communities, 98, 198, 216 community, xiv, 54, 58, 60, 61, 64, 66, 134, 150, 155, 191, 192, 216, 218, 283 Comparative Fit Index (CFI), xii, 46, 112, 119 compensation, xiii, 135, 147, 149, 152, 153, 154, 155, 156, 159, 160 competence, 50, 51 competency, 180 competition, ix, x, xiii, 2, 4, 5, 25, 26, 27, 28, 29, 30, 33, 45, 50, 91, 92, 97, 98, 99, 137, 141, 144, 151, 153, 164, 183, 185, 198, 221, 226, 231, 232, 236, 240, 242, 244, 279 competitive anxiety, 50, 51 competitive sport, 7, 44 competitiveness, 181, 230 competitor, 3, 192, 266 complement, 214 complexity, x, 43, 44, 45, 50, 51, 179, 294

300

Index

compliance, 100, 256, 278 components, 3, 68, 76, 116, 294 composite, 15, 16, 20 composition, 36 computation, 45 computers, 87 conceptualization, 51, 78, 85, 272 conceptualizations, 43 concrete, 279 conditioning, 4 conductive, 294 confidence, 46, 78, 88 confidence interval, 46, 88 confidence intervals, 88 confidentiality, 94, 259 confirmatory factor analysis, 46 conflict, xv, 24, 41, 77, 210, 253, 254, 255, 257, 258, 260, 263, 265, 266, 283 conformity, 46 confusion, 56, 59, 220, 278 congruence, 265 conjunctivitis, 2 Connecticut, 151 conscientiousness, 220 consensus, 155 consent, 67, 91, 100, 117, 151, 167, 212, 222, 259 Constitution, 268 constraints, 198, 279 construction, 7, 83, 191, 203 consulting, 218, 292 consumer loyalty, 225 consumer satisfaction, 22 consumers, xii, 10, 12, 17, 18, 127, 128, 129, 133, 164, 173, 226, 227 consumption, xii, 17, 23, 24, 127, 128, 129, 130, 225, 226, 289 consumption patterns, 225, 226 content analysis, 105, 106, 108, 110, 180 contingency, 280 contracts, 156, 194, 195 control, 7, 10, 11, 14, 15, 16, 17, 19, 20, 22, 44, 83, 84, 123, 130, 131, 151, 152, 153, 154, 155, 158, 159, 193, 211, 246, 251, 271, 273, 277, 284, 285, 295 control group, 11, 14, 15, 16, 17, 19, 20, 22 controlled, 153 coping, 282, 288, 289 coping strategies, 66 coping strategy, 224 coronary heart disease, 112 corporate performance, 267 corporations, 140, 292

correlation, 13, 15, 57, 70, 94, 95, 116, 118, 159, 183, 211, 237, 275 correlation analysis, 275 correlation coefficient, 15, 57, 94, 237 correlations, xi, 17, 45, 46, 47, 48, 75, 81, 116, 119, 237, 275 corruption, 195 cost effectiveness, 192 costs, xv, 26, 90, 113, 143, 158, 199, 203, 243, 251 counterbalance, 44 country of origin, 198 Court of Appeals, 131, 197 courts, 93, 96, 98, 156, 196, 197, 204 covariate, 13, 15, 17, 19 coverage, 96, 157, 159 covering, 158 cracking, 100 credibility, 55 credit, 67, 288 crime, 92 criminal acts, 128 criminal behavior, 178 criticism, 97, 144 cross-cultural, 72, 227 cross-sectional, 49, 50, 84 cultivation, 241 cultural, 30, 77, 88, 214, 216, 218 cultural influence, 30 cultural perspective, 88 culture, x, 25, 28, 29, 30, 53, 84, 87, 128, 131, 150, 154, 227, 254, 265, 266, 267, 268 curiosity, 96 curriculum, 109 customers, 10, 11, 22, 129, 150 cycling, 296

D Dallas, 146 danger, 3, 54, 60, 131 data analysis, 16, 23, 26, 180, 181 data collection, 46, 80, 123, 179, 180, 186, 259, 269 data distribution, 16 data processing, 294, 295 database, 180, 204, 260 death, xvii, 100, 130, 135 deaths, 131, 151 decision makers, 41, 251 decision making, 149 decision support tool, 55 decisions, 109, 114, 145, 187, 193, 195, 198, 199, 202, 267, 271, 277 defendants, 131, 201

Index defense, 274, 275, 276 deficit, 87, 249 definition, 157, 159, 164 degenerate, 289 degradation, xvi, 293 degree, x, xiii, 4, 29, 33, 36, 44, 49, 72, 78, 79, 149, 159, 175, 177, 179, 184 Delphi, 109 Delphi study, 109 demand, 192, 199 democracy, 54 demographic, x, 25, 26, 34, 36, 46, 49, 57, 67, 87, 166, 174, 209, 212 demographic characteristics, 166, 174 demographics, xi, 35, 37, 65, 85, 166, 167, 245 demography, 78, 85 denoising, 295 Department of Education, 91 Department of Health and Human Services, 124, 125, 126 Department of Homeland Security (DHS), 54, 59, 60 dependant, 17, 151, 215 dependent variable, 15, 16, 17, 20, 68, 69, 70, 81, 169, 234 depressed, 123 depression, 50, 51, 165, 220 desire, xi, 27, 28, 54, 159, 174 desires, 79 detection, 97, 296 detonation, 60 deviation, 251 diabetes, 112 differential rates, 225 differentiation, 44 dimensionality, 44 directives, 278 discipline, 92, 104, 108, 184, 189, 282 discomfort, 114, 215 discourse, 63 discrimination, 84, 85, 208, 210, 216, 217 diseases, 3, 4, 7 disputes, xiv, 145, 191, 192, 193, 197, 198, 199, 200, 202, 203 dissatisfaction, 84 distraction, 144 distribution, 16, 35, 46, 122, 208, 245 diversity, xi, 75, 87, 158, 208, 216, 217 diving, 91, 234, 235, 241 division, xv, 41, 80, 199, 211, 251, 253, 254, 255, 256, 258, 259, 260, 261, 263, 264, 265 dominance, 214 doping, 203 draft, 139, 146

301

drinking, 128, 134 drug use, ix, 93, 97, 100 drugs, 26, 30, 89, 90, 91, 93, 95, 96, 97, 98, 99, 100, 183, 196, 285 dry, 5 duplication, 57 DuPont, 97 duration, 11 duties, x, 33, 34, 38, 39, 40, 104, 105, 155, 243, 251 dykes, 218 dysfunctional, 44, 50

E earnings, 197 ears, 156 eating, 287 echoing, 80 economic, x, 53, 55, 63, 164, 166, 168, 169, 172, 174, 189 economic incentives, 225 economics, 105, 145, 146 economy, 189 education, xvii, 5, 9, 30, 35, 36, 43, 81, 83, 91, 93, 98, 99, 105, 141, 146, 150, 152, 153, 155, 158, 159, 161, 166, 187, 217, 218, 242, 266, 267, 268 educational process, 98 educational programs, xiv, 207, 216 educational system, 232, 240 efficacy, 86 eggs, 50 elaboration, 10, 12, 16, 17, 18, 19, 20, 21, 22, 24 elbows, 132 electrocardiogram (ECG), 294, 296 electrodes, xvi, 293, 294 electroencephalogram, 294 electromyogram, 294 elementary school, 122 eligibility standards, 187 email, 94, 259 emotion, 63, 220 emotional, 208, 220, 232, 287 emotional health, 287 emotional reactions, 220 emotions, 17, 18, 23, 77, 165, 207, 282 empathy, 164 employees, 55, 76, 77, 79, 86, 156, 159, 160, 197, 254, 255, 256, 257, 258, 262, 263, 264, 265, 266, 267 employers, 144 employment, 76, 80, 104, 105, 107, 122, 150, 156, 159, 196, 264, 268 empowerment, 41, 79, 251

302

Index

encapsulation, 216 encouragement, xvi, 115, 121, 122, 123, 293 energy, xv, 41, 116, 118, 253, 282 engagement, 116, 121, 124 England, 6, 41, 151 English, 29, 30, 151 enrollment, 37, 108, 141, 180, 186, 187, 189 enterprise, 155, 160 entertainment, 64, 145, 164, 165, 166, 168, 169, 172, 174, 175 entrepreneurs, 144 envelope, 35 environment, x, xii, xiv, xvi, 11, 13, 18, 25, 26, 62, 71, 76, 78, 79, 84, 113, 123, 127, 128, 129, 130, 133, 182, 193, 207, 208, 210, 211, 215, 216, 257, 264, 265, 281, 282 environmental, 212 environmental factors, 76, 212, 232, 241 Environmental Protection Agency, 62 Epi, 6 epidemic, xii, 111, 112 epidemiology, 6 epistemology, 218 equality, 15, 166, 168, 169, 174, 217, 238 erosion, 129 ESC, 168, 170, 174 ESP, 62 estimating, 87 ethics, ix, 46 ethnic background, 35, 36, 221, 245 ethnicity, 36, 49, 115, 166, 211, 212, 221 Europe, 151, 235, 239, 241 European, 72, 199 eustress, 164, 166, 168, 170, 174 evidence, 11, 12, 29, 46, 72, 73, 192, 195, 197, 201 evolution, 100, 109, 138, 158, 242 examinations, 66, 104, 168, 283 excitement, 55, 163, 175 execution, 277 Executive Order, 91 exercise, 23, 50, 131, 150, 208, 262, 295 expenditures, 154, 158 expert, xv, 138, 232, 259, 269, 270, 271, 273, 274, 276, 277, 279 expertise, 179, 194 explosive, xi, 53 exposure, x, 53, 113 external validity, 15, 83 extraction, 235 extroversion, 66, 220 eyes, 242

F FAA, 195, 196, 198 face validity, 34, 244 facilitators, 123 factor analysis, xv, 46, 116, 229, 234, 235 factorial, 211 faculty positions, 34, 105, 109 failure, 114, 128, 133, 220, 227 fairness, 194 faith, 289 false, 56 family, xvi, 1, 80, 132, 164, 165, 166, 168, 170, 173, 174, 175, 181, 182, 184, 185, 186, 188, 189, 253, 255, 257, 258, 259, 262, 263, 265, 266, 267, 268, 281, 283, 285, 289 family conflict, 253, 255, 257, 258, 259, 265, 266, 267, 268 family life, 257, 263 family members, 258, 289 family structure, 185 family support, 181, 185 fat, 126 fatalities, 128 fatherhood, 265 fatigue, 2, 48, 220 fax, 111, 207, 269 fear, 55, 63, 189, 217 fears, 210, 289 federal government, 151 fee, 138, 144, 248 feedback, 44, 76, 133, 233 feelings, 23, 54, 63, 77, 79, 165, 179, 284 fees, 122, 138, 140, 143, 154, 158 females, 57, 68, 69, 141, 143, 216, 234, 260, 273, 286 femininity, 210 feminist, 218 filters, 294 finance, 105, 286 financial aid, x, 33, 39, 158 financial resources, 143 financial support, 233 financing, 286 fire, 196 firearms, 129 firms, 280 fishing, 138 fitness, xviii, 50, 105, 262 five-factor model, 73, 227, 236 flavor, 230, 242 flexibility, 266, 271, 273 flight, 139

Index flow, 271, 273 focusing, 178, 215, 264 food, 247 foreclosure, x, 43, 51 Fort Worth, 146, 266 Fourth Amendment, 93 France, 77, 85 franchise, 226 fraud, 195, 197 freedom, 151, 295 friendship, 145 frustration, 146, 210, 284 funding, ix, 160, 231, 244 fundraising, xv, 35, 189, 243, 244, 245 funds, xv, 151, 243, 247, 251

G gambling, ix, xiii, 137, 138, 140, 141, 144 games, x, xiii, 13, 14, 21, 33, 53, 56, 57, 58, 59, 61, 62, 64, 91, 117, 118, 131, 137, 140, 142, 144, 151, 160, 163, 164, 165, 166, 170, 171, 172, 173, 174, 175, 178, 186, 201, 202, 231, 243, 274, 275, 284, 289 GAO, 62 gay men, 208, 214, 216, 218 gels, 294 gender, ix, xiv, 26, 27, 29, 30, 45, 50, 57, 67, 68, 69, 70, 77, 78, 80, 81, 83, 84, 92, 95, 117, 141, 166, 207, 218, 221, 229, 233, 234, 238, 255, 264, 274, 275, 279 gender differences, 26, 27, 29, 30, 68, 69, 83 gender effects, 68 gender role, 264 General Motors, 140 generalizability, 19 generation, 144, 225, 266 geography, 71 Georgia, 62 Germany, 88 gift, 14 gifted, 90 girls, 26, 90, 91, 114, 125, 217 glass, 132, 267 goal setting, 149 goals, 27, 62, 90, 123, 154, 157, 179, 181, 231, 256, 272, 291 God, 289 goodness of fit, xii, 112, 119 gossip, 289 governance, 105, 149, 154, 155, 203, 204 government, 93, 98, 139, 144, 151, 196 GPA, 141

303

grades, 91, 100, 178, 182, 283 graduate students, 57 grandparents, 126 grants, 156, 159 Great Britain, 106 Great Lakes, xvii, xviii group membership, 46, 68 group variance, 17 grouping, 168 groups, 4, 11, 14, 15, 16, 17, 20, 22, 40, 45, 46, 67, 78, 128, 160, 201, 232, 238, 251, 254, 260, 264, 284, 285 growth, 64, 104, 139, 140, 150, 151 guardian, 91, 92, 152 guidance, 123, 289 guidelines, ix, xiii, xiv, 1, 5, 48, 119, 177, 184, 207, 217 guilt, 258 guilty, 131, 132, 195 gymnastics, 117, 164

H hands, 10, 83 harm, x, 2, 53, 54, 55, 56, 93, 96, 129, 130, 158, 210, 216 harmful, 3, 54, 59, 60, 62 harmony, 158 Harvard, 64, 139, 150, 151 hate, 287 Hawaii, xvii hazardous materials, 64 hazards, 60, 63 head, x, 33, 34, 35, 36, 80, 81, 83, 85, 155, 179, 180, 210, 214 health, xi, xvii, 26, 30, 50, 65, 67, 68, 72, 73, 92, 98, 112, 122, 123, 124, 125, 157, 159, 165, 173, 288 Health and Human Services, 124, 125, 126 health care, 112 health care costs, 112 health care system, 112 healthcare, 112 hearing, 186, 193, 194, 195, 197, 199, 200, 201, 202, 203 heart, 101, 112, 152, 294, 296 heart rate, 294, 296 helping behavior, 77 helplessness, 29 heme, 185 herpes, ix, 1, 2, 3, 4, 5, 6, 7 herpes labialis, 4 herpes simplex, 1, 3, 6, 7 herpes simplex virus type 1, 6, 7

304

Index

heterogeneity, 44 heterosexuality, 207, 209, 210 heuristic, 12, 23 HHS, 125 high school, ix, xii, xiii, xvi, 1, 2, 3, 5, 68, 84, 90, 91, 92, 93, 94, 96, 97, 98, 99, 101, 111, 114, 115, 122, 123, 137, 141, 145, 158, 169, 173, 175, 178, 181, 182, 184, 186, 187, 230, 231, 260, 279, 281, 291 high school degree, 260 higher education, xii, xiii, 41, 103, 149, 150, 154, 178, 189, 254, 267 hips, 76 hiring, 104, 106, 107, 110, 152 Hispanic, 36, 115, 166, 212, 221, 260 Hispanics, 141 hockey, 145, 160, 164, 165, 271, 280 holistic, 41, 178, 221, 251 Holland, 2 Homeland Security, 54, 59, 60, 63 homogeneity, 141 homosexuality, 209, 210, 214, 215 homosexuals, 214, 216 hospital, 86, 88, 113 hospitalization, 2 host, 130, 160, 198 hostility, 208 House, 92, 102, 151 household, 144, 182 household income, 144 households, 125 HRM, 267 human, xvi, 88, 150, 164, 188, 189, 190, 208, 259, 267, 279, 281, 282, 288, 289 human capital, 189 human kinetics, 31, 41, 50, 217, 227, 280 human nature, 289 human rights, 259 humorous, 288 husband, xiii, 127 hybrid, xiv, 191, 192, 202 hypertension, 112 hypocrisy, 159 hypothesis, x, xi, xiv, 12, 16, 18, 19, 20, 21, 29, 43, 65, 72, 79, 80, 81, 82, 171, 172, 219, 221, 222, 223, 224, 227, 276

I ice, 164 id, 101, 122, 164, 173, 186, 197, 203, 204, 242, 287 identification, ix, xi, xiii, xiv, 9, 10, 13, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 55, 59, 65, 66, 67, 68,

69, 70, 71, 72, 73, 129, 163, 165, 167, 171, 172, 173, 174, 175, 176, 219, 220, 221, 222, 223, 224, 225, 226, 227 identity, x, 43, 45, 50, 51, 66, 72, 79, 84, 208, 212, 215, 216, 226, 227 identity foreclosure, x, 43 Illinois, xvii, 219, 242 images, 128, 132 implementation, ix, 1, 56, 62, 98, 256, 267 incentive, 10, 11, 22, 151 incentives, 18, 108, 154, 156, 158 incidence, 58 incidents, 130 inclusion, 57, 94 income, 144 independence, 27, 236, 237, 240 independent variable, 15, 19, 20, 81, 234 Indian, 115 Indiana, 131, 135, 155, 201, 268 indices, xii, 44, 71, 112, 119, 167, 294 indirect effect, 87, 88 individual development, 241 industrial, 86, 270, 271, 280 industrialized countries, 56 industry, xiv, xv, 88, 100, 104, 129, 139, 191, 203, 253 infection, 1, 2, 3, 4, 6, 7 infections, 6 infectious disease, 2, 3, 4, 5 infectious diseases, 3, 4 infinite, 224 inflation, 14 information processing, ix, 9, 10, 11, 12, 16, 17, 18, 23 information processing theory, 18 information system, 63, 86 information systems, 86 information technology, 84, 87, 236, 237, 240 informed consent, 212, 222 infrastructure, 55, 157 infusion model, 10, 17, 18, 23 inherited, 189 initiation, 258 injection, 95 injuries, 4, 5, 25, 26, 59, 125, 134, 135, 140, 145, 284 injury, x, 2, 5, 25, 26, 28, 29, 30, 31, 49, 55, 130, 131, 284 inmates, 284 insight, 4, 49, 83, 115, 240 inspection, 3 inspections, 5

Index institutions, xii, xiv, xv, 33, 34, 35, 37, 85, 103, 104, 106, 108, 151, 153, 154, 155, 156, 160, 179, 207, 216, 230, 231, 234, 241, 242, 243, 244, 245, 253, 254, 255, 256, 259 instruction, 217 instructors, 105, 107, 109 instruments, 68 intangible, 182 integration, 44, 256 integrity, 92, 152, 154, 156, 178 intellectual skills, 150 intelligence, 85 intensity, 296 intentions, 76, 86, 87, 212 interaction, ix, 9, 18, 20, 21, 22, 78, 140, 164, 272, 276, 280 interaction effect, 21, 276 interaction effects, 276 interactions, 23, 113, 215 intercollegiate athletics, xiv, 3, 77, 83, 85, 93, 149, 151, 154, 155, 178, 182, 197, 217, 218, 229, 230, 231, 233, 235, 236, 237, 238, 239, 240, 241, 254, 256, 257, 266, 267, 268 interface, 259, 264, 292, 294, 295 interference, 93, 192 internal consistency, 14, 45, 46, 167 internal validity, 15 internalization, 225, 226 international, xiv, 191, 192, 198, 199 international law, xiv, 191 International Olympic Committee, 198 international students, 231 internationalization, 63 internet, 117, 146, 242 Internet, 9, 65, 105, 118, 139, 144, 234, 269 interpersonal relations, 29, 286 interpersonal relationships, 29, 286 interpretation, xvi, 57, 94, 130, 293 interval, 46 intervention, 60, 87 interview, 180, 181, 182 interviews, xiv, 177, 179, 180, 182, 185, 187, 233 intimidating, 192 intimidation, 185 intoxication, 131 intrinsic, 225 intrinsic rewards, 225 investigative, 57 investment, 142, 179, 186, 189 IOC, 198 Ireland, 113, 125 irrationality, 56, 61 Islam, 116, 126

305

isolation, 49 ISS, 25 ITA, 230

J Japan, 227 Japanese, 85, 88 job performance, 86, 87 job position, 105 job satisfaction, xi, 75, 76, 77, 79, 80, 81, 82, 83, 84, 85, 87, 88, 257 jobs, 77, 104, 105, 108, 181, 182, 186, 254, 257, 282 judge, 192, 194 judgment, 12, 18, 23, 63, 93, 194, 197, 290 jurisdiction, 194, 198, 201 jury, 130, 134, 153, 194 justice, 87

K K-12, 100 Kentucky, 163, 219 killing, xi, 53 kindergarten, xii, 111, 115, 117

L L2, 43 labor, 123, 199, 200, 202 labor force, 200, 202 land, 151 language, 119, 156 laptop, 294 Latino, 115 law, 4, 62, 92, 93, 128, 130, 134, 135, 159, 192, 195, 198 laws, xiv, 144, 156, 159, 191, 198 lawsuits, 130 lawyers, 192 layoffs, 85 lead, x, 2, 43, 59, 71, 84, 154, 155, 193 leadership, xiii, 77, 78, 79, 85, 86, 87, 88, 105, 149, 152, 160, 181, 182, 189, 270, 271, 273, 277, 279, 280 leadership abilities, 181 learning, xvii, 144, 149, 182 learning process, 182 legal aspects, 105, 132 legal issues, ix legal protection, 217 legality, 93, 96, 138

306

Index

legislation, 91, 97, 157, 178, 198 legislative, 62, 198 leisure, xii, 111, 113, 116, 118, 119 leisure time, xii, 111, 118, 119 Lesbian, 217, 218 lesions, 5 liberal, 214 licenses, 196 life satisfaction, 66, 165, 267 lifestyle, 113, 232 lifestyles, 121 likelihood, ix, 1, 2, 3, 5, 10, 17, 18, 24, 59, 60, 90, 119, 129, 131, 132, 264, 278 Likert scale, 14, 57, 67, 94 limitation, xi, 17, 22, 89, 94, 129 limitations, 16, 17, 29, 49, 61, 99, 123, 194, 233 linear, 81, 226, 237 linear regression, 81 linkage, 78, 85, 86 listening, 289 literature, xi, 10, 11, 12, 14, 17, 18, 30, 44, 48, 50, 75, 76, 77, 78, 80, 83, 84, 210, 215 litigation, xiv, 4, 132, 133, 191, 192, 193, 195, 196, 197, 202, 203 living environment, 237 local community, 283 location, 37, 116, 117, 123, 134, 165, 236, 237, 240, 241, 271 London, 64, 151, 242 loneliness, 66, 68, 71, 165, 220 long distance, 143, 231 long period, 155 longitudinal study, 85, 87, 113, 266 Los Angeles, 64, 101, 156 losses, 220, 288 Louisiana, 90, 197 love, 80, 283 loyalty, 78, 145, 225, 226, 227

M magazines, xvii, 140, 143, 292 magistrates, 150 Maine, 2, 6 mainstream, 138 maintenance, 11, 22, 23 Maintenance, 11, 62 Major League Baseball, 138, 142, 147, 165, 173, 199, 204, 225, 229 males, xiii, 57, 68, 69, 80, 90, 123, 137, 143, 209, 210, 216, 273 management, ix, xii, xiii, 1, 2, 3, 4, 6, 7, 10, 13, 16, 34, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 77, 84,

88, 103, 104, 105, 106, 107, 108, 109, 110, 128, 129, 133, 200, 202, 203, 230, 254, 256, 267, 292 management practices, 58, 59 Manhattan, 189 manipulation, ix, 9, 10, 11, 16, 17, 18, 19, 21, 22 manners, xv, 243, 249 MANOVA, 17, 19, 20, 168, 169, 171 manufacturer, 77, 140 manufacturing, 129 marginalization, 207 marijuana, 98, 196 marital status, 81 market, 105, 108, 109, 128, 132, 143, 144, 145, 157, 159 market segment, 128, 132 marketability, 134 marketing, xii, 10, 11, 18, 22, 105, 127, 128, 129, 132, 133, 134, 143, 144, 146, 152, 225, 226, 227, 256 markets, 60, 63, 175 Maryland, xvii, xviii, 254, 281, 291, 292 masculinity, 208 mask, 97 Massachusetts, 150, 242 mastery, 164 maternal, 268 matrix, xvi, 47, 118, 131, 132, 179, 237, 281 meanings, 181 measurement, xvi, 44, 46, 48, 51, 123, 124, 218, 222, 293, 294, 295 measures, xii, xiii, xiv, 13, 15, 16, 20, 21, 54, 56, 68, 79, 80, 92, 111, 124, 128, 131, 163, 167, 168, 207, 260, 265 media, x, xvi, 53, 89, 96, 122, 138, 139, 140, 152, 190, 193, 201, 226, 248, 254, 255, 256, 281, 286 median, 15, 116 mediation, xiv, 81, 87, 191, 192, 193, 197, 202 medicine, ix, 5, 6, 30, 31, 101, 291 meditation, 289 membership, 30, 46, 143, 153, 203, 218, 256 memory, 12, 23, 24 men, xiii, 26, 28, 29, 30, 66, 80, 99, 101, 125, 131, 151, 154, 158, 164, 173, 177, 179, 183, 184, 185, 188, 208, 209, 210, 212, 213, 214, 215, 216, 218, 221, 231, 254, 256, 257, 258, 265, 266, 268, 283, 291 mental health, 72 mental state, 295 merchandise, 10, 11, 145 MET, 116, 120, 124 meta-analysis, 85 metabolic rate, 116, 120 metropolitan area, 60

Index Mexican, 140 Miami, 127, 178 microscope, 183 migration, 84 Minnesota, 202 minorities, xii, 111 minority, 98, 216 minors, 130 misleading, 128 Mississippi, 53 Missouri, 23, 63, 134 mobility, xvi, 293 modeling, 10, 113, 114, 122, 123 models, 83, 87, 88, 112, 114, 123, 179, 185, 215 moderators, 85 modus operandi, 158 momentum, 159 money, xv, 22, 33, 34, 98, 122, 138, 140, 142, 151, 157, 158, 160, 191, 192, 200, 203, 243, 246, 247, 249, 250, 251, 286 mood, ix, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 101 mood change, 23 mood states, 11, 12, 18 morphology, 296 motherhood, 265 mothers, 115, 122, 257, 264 motion, 294, 295 motivation, xiii, xv, 17, 23, 28, 50, 88, 163, 164, 165, 167, 168, 169, 171, 172, 173, 175, 179, 181, 182, 229, 233, 234, 235, 237, 238 motives, xiii, xiv, 23, 29, 30, 128, 158, 163, 164, 166, 170, 171, 172, 173, 174, 175, 229, 232, 233, 235, 237, 238, 239, 240, 241, 242 motor actions, 295 motor activity, xvii movement, xvii, 149, 157, 215, 291, 294, 295 multicultural, 217 multidimensional, 46 multiples, 116 multivariate, 21, 126, 169 multivariate statistics, 126 murder, 131 muscle, 91, 99, 289, 294, 295 muscle mass, 91 muscle relaxation, 289 muscles, 294 music, 128, 289

N naming, 130 narcotics, 196

307

nation, 112, 198 national, ix, 1, 63, 83, 152, 198, 199, 210 National Academy of Sciences (NAS), 45, 46, 47, 48, 63 National Basketball Association (NBA), xiii, 137, 138, 142, 143, 145, 182, 199, 201, 202, 204, 220, 230, 242 National Collegiate Athletic Association (NCAA), vi, x, xiii, xiv, xv, 3, 5, 6, 25, 30, 33, 34, 35, 41, 45, 56, 61, 64, 80, 84, 85, 87, 92, 138, 149, 151, 160, 161, 177, 178, 182, 184, 186, 188, 189, 190, 197, 204, 207, 211, 216, 217, 218, 230, 231, 232, 233, 234, 236, 237, 241, 242, 243, 244, 245, 251, 253, 254, 255, 256, 257, 258, 259, 267, 268, 285, 291, 292 National Football League (NFL), xiii, 130, 135, 137, 138, 140, 142, 143, 145, 187, 199, 201, 202, 204, 220, 225 Native American, 141, 166 natural, 90, 214, 284 Navy, xvii neck, 1, 130 negative attitudes, 209, 214 negative consequences, 210 negative emotions, 165 negative mood, 11, 12, 13, 16, 19, 22 negative relation, 76 negative stimulus, 278 neglect, 154, 270, 288 negligence, 129 negotiating, 193, 264 negotiation, 30 Netherlands, 232, 240 network, 139 neurotic, 144 Nevada, 207, 253, 254 New England, 6, 99 New Jersey, 91, 92, 93, 97, 98, 101, 102, 134, 151, 268 New York, xi, 23, 24, 50, 51, 53, 62, 63, 64, 66, 72, 73, 85, 88, 107, 109, 125, 130, 139, 146, 147, 161, 199, 202, 218, 225, 228, 242, 266, 279, 295, 296 New York Times, 63, 139 New Zealand, 50, 106, 280 NHL, 142, 143, 146, 199, 200, 204, 229 Nixon, 25, 28, 30 noise, 294, 296 non-binding, 194 nongovernmental, 194 nongovernmental organization, 194 non-invasive, 294 nonlinear, 294, 296

308

Index

non-profit, 139 normal, 16, 90, 93, 99, 101, 187, 194, 203 norms, x, 25, 29, 216, 278 North America, 51, 73, 87, 88, 104, 109, 134, 228, 230, 277 North Carolina, 131, 242, 253 Northeast, xii, 103, 107 Notre Dame, xiii, 127, 131, 134 novelty, 271 nurses, 284 nutrition, ix

O obese, 112, 117 obesity, xii, 111, 112, 113, 115, 124, 125, 126 objectivity, 56 obligation, 78 obligations, 198, 257, 263 observational learning, 112, 114 observations, 234 observed behavior, 113 occupational, 83, 285 Oceania, 235, 239, 241 offenders, 97 Office of National Drug Control Policy, 98, 102 Ohio, xvii, 137, 205, 280 Oklahoma, xi, 54, 59, 126 Olympic Games, 198, 199 online, 94, 95, 99, 144, 178, 190, 234 on-line, 295 openness, 215, 220 operator, 59, 196 opposition, 210 oppression, 216 ordinal data, 260 Oregon, 242 organization, 4, 50, 55, 56, 59, 60, 76, 77, 79, 80, 128, 130, 132, 133, 137, 139, 153, 157, 179, 188, 191, 192, 194, 202, 225, 226, 270, 271, 272, 279, 280 organizational citizenship behaviors, 88 organizational culture, 258 organizational tenure, 83 organizations, xii, 4, 5, 22, 40, 55, 60, 85, 86, 127, 128, 129, 130, 140, 151, 160, 193, 198, 199, 203, 210, 257, 258, 270, 279, 280 orientation, xiv, 77, 79, 114, 207, 208, 209, 211, 212, 215, 216, 217 orientation discrimination, 217 oversight, 153, 154, 155 overtime, 261 overweight, 112, 124, 126

overweight adults, 112

P Pacific, 87, 221, 260 Pacific Islander, 221, 260 packets, 275 pain, x, 25, 26, 27, 28, 29, 30, 93, 98 parameter, 121, 235 parameter estimates, 121 parental influence, 122, 126, 236, 237, 240 parental support, 114 parenting, 114, 125, 266 parents, xii, xvi, 27, 29, 111, 112, 113, 114, 115, 116, 117, 118, 119, 121, 122, 123, 124, 126, 150, 182, 257, 265, 281, 291 paternal, 126 paternity, 261, 262, 264 path analysis, 118, 119 path model, 113, 115, 119, 121 pathology, 144 patients, 284 pattern recognition, 180 payroll, 201 PCT, 227 Pearson correlations, 81 pedometer, 124 peer, 124 peer influence, 124 peers, 114, 122, 143, 182, 215 penalties, 153 penalty, 91, 153 Pennsylvania, 107 perception, xv, 29, 30, 56, 58, 60, 61, 64, 76, 90, 93, 214, 216, 241, 253, 255, 260, 272 perceptions, xv, 23, 29, 56, 57, 61, 62, 79, 81, 85, 99, 100, 114, 179, 208, 209, 210, 211, 216, 253, 255, 258, 259, 265, 266, 270, 272, 273, 274, 275, 276, 277, 279 performance, xvi, 10, 11, 24, 44, 48, 49, 50, 66, 76, 77, 85, 86, 87, 89, 90, 91, 95, 96, 97, 98, 99, 138, 142, 153, 155, 158, 159, 176, 178, 179, 187, 188, 189, 190, 191, 200, 208, 220, 224, 225, 230, 231, 267, 271, 272, 278, 284, 288, 293, 295, 296 performance-enhancing substances, 90, 97, 99 periodic, 155 permit, 98 personal, ix, xvi, xviii, 5, 9, 10, 17, 18, 19, 20, 45, 50, 68, 78, 80, 90, 112, 130, 145, 164, 184, 208, 210, 236, 237, 240, 254, 257, 263, 264, 279, 281, 283, 288, 289, 291 personal benefit, 164 personal life, 184

Index personal relevance, ix, 9, 10, 17, 18, 19, 20 personal welfare, 291 personality, xvii, 45, 73, 87, 88, 188, 227 personality dimensions, 45 personality test, 188 personality traits, 87, 88 persuasion, 24 Philadelphia, 100, 160, 202, 203, 204 philosophical, 64, 266 philosophy, ix, 144, 178 phone, xii, 11, 103, 105, 106, 107, 108, 111, 143, 167, 180, 186, 187 physical activity, xii, 111, 113, 114, 115, 116, 117, 119, 121, 122, 123, 124, 125, 126, 208, 217 physical appearance, 46, 47 physical education, xvii, 105, 217 physical exercise, 289 physical health, 287, 288 physicians, 5, 284, 285 physiological, xvi, 220, 293 pilot study, 34, 179, 211, 233, 244 pitch, 294 planning, 55, 64, 133, 155, 285 play, x, xi, xv, 25, 26, 27, 28, 29, 30, 65, 71, 77, 78, 96, 122, 123, 138, 145, 146, 147, 151, 152, 153, 154, 157, 158, 159, 164, 165, 181, 182, 185, 200, 202, 229, 231, 241, 256, 272, 274, 275, 277, 278, 280, 294 point like, 211 police, 196 policymakers, 256 policy-makers, 56 politeness, 183 poor, 13, 34, 66, 122, 159, 183, 184, 220, 232, 240, 244, 272 poor performance, 66, 159, 220, 272 population, xiii, xiv, 1, 61, 80, 84, 94, 95, 99, 112, 113, 124, 137, 138, 141, 142, 143, 177, 208, 211, 212, 215, 216, 225, 241, 258, 259 portability, 295 portfolio, 140 ports, 64, 172, 175, 230 positive correlation, 13 positive interactions, 215 positive mood, 10, 11, 12, 13, 15, 16, 19, 22, 24 positive relation, xi, 14, 65, 66, 67, 73, 76, 79, 165, 224, 228 positive relationship, xi, 14, 65, 66, 67, 73, 76, 79, 165, 224, 228 positive stimulus, 278 post-game, ix, 9, 10, 12, 15, 16, 18, 20, 21, 22, 131

309

power, xiv, xv, 16, 20, 49, 86, 88, 93, 98, 155, 160, 191, 192, 200, 208, 256, 269, 270, 271, 272, 273, 274, 275, 276, 277, 279, 280 powers, 195, 198, 254 predictability, xi, 75, 81 prediction, xv, 114, 115, 121, 122, 178, 227, 269, 272 predictor variables, 69, 70 predictors, 47, 69, 179, 180, 184, 189, 279 preference, xii, 17, 111, 113, 115, 118, 121, 122 pre-game, ix, 9, 10, 12, 13, 16, 18, 19, 20, 21, 22, 131, 134 prejudice, 208, 217 preparation, 4, 34, 180 preparatory schools, 157 preparedness, 62 prescription drug, 134 president, 96, 97, 152, 155, 189, 259 pressure, xiii, xvi, 29, 154, 159, 177, 178, 187, 188, 281 prestige, 291 prevention, 98 preventive, 54 priming, 11 printing, 286 prior knowledge, 97 priorities, 55, 62 privacy, 92, 93, 98, 192, 193 private, 37, 106, 113 proactive, 62, 216 probability, x, 49, 53, 59, 60 procedural justice, 87 procedural rule, 195 procedures, 4, 19, 46, 48, 54, 56, 58, 59, 60, 61, 87, 192, 197 product design, 129 productivity, 144, 257 profession, 76, 77, 78, 79, 83, 84 professionalism, 159 professions, 83 Profile of Mood States, 73, 227 profit, 139, 140, 157, 160 profits, 146 program, xi, xv, 13, 15, 19, 33, 40, 41, 55, 62, 89, 91, 92, 93, 94, 98, 100, 106, 107, 109, 140, 157, 179, 182, 183, 186, 187, 189, 232, 234, 244, 245, 251, 253, 254, 256, 266, 278, 285, 286 programming, xiv, 119, 207, 208, 215, 217 promote, xii, 62, 127, 133, 139, 217, 225 property, 147, 196 proportionality, 141 proposition, 145 protection, 2, 60, 98, 198

310

Index

protocol, 57, 60, 92, 94, 102, 295 PSQ, 45, 270, 274, 275, 276 psychological, xi, 14, 43, 44, 49, 50, 55, 65, 66, 67, 68, 69, 70, 71, 72, 73, 85, 165, 173, 175 psychological health, xi, 65, 67, 68, 73, 165, 173, 220, 224, 227 psychological processes, xvi, 293 psychological states, 294 psychological well-being, 66, 69, 70, 71, 72, 73, 227, 228 psychologist, xvi, 278, 281 psychology, ix, xvi, 72, 73, 86, 218, 228, 270, 271, 280, 293, 296 psychometric properties, 222 psychophysiology, xvi, 293, 295, 296 public, 37, 54, 56, 59, 61, 64, 93, 96, 100, 106, 107, 112, 113, 132, 151, 157, 193, 194, 196, 197, 256, 286 public education, 151 public interest, 197, 286 public policy, 197 public relations, 286 public service, 151 pulse, 296 punishment, 92, 199, 202, 278 punitive, 130

Q qualifications, 109 Qualitative evaluation, 146 quarterback, xvi, 269, 272, 273, 274, 275, 276, 277, 278 queer theory, 218 questioning, 215 questionnaire, x, xi, 14, 15, 19, 25, 26, 34, 35, 45, 57, 65, 67, 68, 80, 84, 94, 104, 117, 167, 175, 181, 183, 186, 222, 233, 244, 245, 274, 275 questionnaires, 26, 57, 117, 141

R race, 30, 77, 83, 84, 85, 86, 95, 141, 158, 211, 212, 221 racial differences, 84, 175 racism, 216 rail, 11, 190 random, 80, 91, 92, 97, 98, 100, 101, 102, 180, 186 range, xvi, 36, 57, 59, 94, 118, 123, 155, 167, 168, 172, 211, 222, 233, 247, 264, 273, 274, 293 rash, 1 reaction time, 93

reactivity, 290 reading, xvii, 12, 274, 289 real time, 138, 153 reality, 146, 152 real-time, 187 reasoning, 24, 144, 278 recall, 18, 113, 126, 173 recognition, xviii, 28, 123, 132, 180, 291 reconcile, 197, 257, 258 recreation, 39, 105 recreational, 30, 141, 279, 289 recruiting, xiv, xv, 153, 167, 177, 178, 179, 182, 183, 184, 187, 188, 189, 229, 230, 231, 241, 242, 243, 250, 254, 266, 283, 291 reduction, 84, 181, 295, 296 reflection, 187 reforms, 153, 155 regional, 150, 152 regression, xi, 68, 69, 70, 75, 81, 227 regression analysis, xi, 69, 75, 81 regression equation, 70 regular, 144, 181, 186 regulation, 123, 124 regulations, 98, 129, 139, 151, 160, 268, 278 regulatory bodies, 62 reimbursement, 262 reinforcement, 225 relationship, x, xi, xvi, 10, 11, 23, 26, 27, 29, 43, 44, 48, 49, 50, 51, 65, 66, 67, 72, 73, 75, 76, 77, 78, 79, 80, 81, 83, 88, 95, 113, 114, 123, 124, 125, 128, 130, 140, 156, 165, 188, 193, 200, 210, 216, 224, 228, 256, 257, 265, 267, 271, 273, 284, 285, 289, 293 relationships, x, xii, 13, 14, 29, 43, 44, 46, 48, 66, 71, 72, 76, 77, 78, 81, 83, 86, 87, 95, 111, 113, 114, 115, 119, 266, 271, 275, 276, 285, 286 relaxation, 289 relevance, ix, 9, 10, 17, 18, 19, 20, 271, 272 reliability, 26, 46, 47, 57, 67, 68, 69, 81, 82, 94, 116, 124, 125, 167, 211, 222, 237, 270, 275 religion, ix, 211, 212 religious, 151, 210, 211, 212, 216 replication, 73, 259 reproduction, 78, 88, 112, 113 reputation, 133, 232 research and development, xiv, 177, 179 research design, 17 researchers, x, xiv, 11, 17, 25, 26, 49, 55, 66, 68, 105, 106, 108, 112, 113, 117, 122, 123, 140, 142, 144, 173, 216, 219, 232, 233, 259, 265, 295 residential, 154 residuals, 46 resilience, 51, 63

Index resolution, xiv, 191, 192, 193, 194, 196, 197, 198, 199, 200, 202 resource allocation, 55 resource management, 267 resource policies, 267 resources, 18, 55, 78, 80, 122, 139, 143, 224, 236, 237, 240, 256, 264 responsibilities, x, xv, 33, 34, 38, 39, 41, 105, 150, 154, 155, 243, 244, 255, 278 restoration, 155 retention, 257 retirement, xviii, 262, 264 revenue, 138, 146, 147, 152, 155, 157, 158, 159, 160, 225, 254, 255 rewards, x, 28, 53, 80, 112, 138, 270, 271, 277 Reynolds, 178, 218 Rho, 116 Rhode Island, 151 rings, 140, 146 risk, ix, x, xii, 1, 2, 3, 4, 5, 7, 23, 25, 28, 29, 30, 54, 55, 56, 58, 59, 60, 61, 62, 63, 64, 93, 98, 99, 100, 127, 129, 130, 133, 153, 164, 182 risk assessment, 61 risk management, ix, 1, 2, 3, 4, 5, 7, 55, 56, 58, 59, 60, 61, 62, 63, 64 risk perception, 56 risks, 2, 3, 4, 5, 28, 30, 55, 56, 59, 60, 61, 62, 63, 93, 98, 123, 132, 133, 144 role conflict, 77 royalty, 157 rugby, 3, 7, 280 rumination, 29 rural, xii, 111, 115, 123, 126 Russian, 96

S safeguards, 61 safety, x, 2, 30, 53, 56, 58, 64, 92, 93, 98, 131, 133 salaries, 155, 156, 158, 200, 203, 249 salary, 155, 159, 193, 199, 200, 201 sales, 11, 145, 157, 247 sample, x, xi, xiii, 11, 13, 19, 22, 34, 43, 45, 46, 47, 48, 49, 71, 75, 80, 83, 84, 114, 115, 116, 122, 123, 137, 141, 142, 143, 144, 166, 173, 180, 194, 199, 208, 209, 212, 214, 215, 216, 221, 223, 224, 226, 234, 244, 257, 258, 259, 260, 261, 262, 263, 273, 275, 276 sample survey, 34, 244 sampling, 44, 80, 84, 141, 211, 295 SAS, 87 satellite, 140

311

satisfaction, xi, 10, 11, 22, 23, 24, 66, 72, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 90, 145, 165, 241, 257, 266, 267, 283 scandalous, 178, 283 scarcity, 108, 175 scheduling, ix, 258 schema, 51 schizophrenia, 125 scholarship, xiv, 4, 90, 98, 153, 156, 158, 159, 187, 197, 229, 232, 233, 234, 235, 238, 256 scholarships, 153, 156, 158, 159, 231, 232, 249, 250, 254, 256 school, ix, xii, xiii, xv, xvi, 1, 2, 3, 4, 5, 14, 60, 68, 84, 90, 91, 92, 93, 94, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 111, 113, 114, 115, 116, 117, 122, 123, 126, 128, 132, 137, 138, 141, 145, 150, 151, 152, 153, 154, 157, 158, 159, 160, 169, 173, 175, 178, 181, 182, 183, 184, 186, 187, 188, 189, 229, 230, 231, 236, 237, 238, 239, 240, 241, 254, 256, 258, 260, 261, 264, 274, 279, 281, 291 school activities, 116 science, 19, 23, 56, 72, 150, 187, 208 science department, 19 scientific, 54 scientists, 270 scores, x, 15, 43, 45, 46, 47, 48, 57, 68, 69, 94, 116, 118, 119, 167, 168, 169, 170, 171, 178, 211, 213, 214, 222, 275, 276 SCT, 122 search, 92, 93, 108, 109, 158, 190 searches, xii, 93, 102, 103, 108 searching, 55, 93, 96, 203 seasonal factors, 226 secret, 146 secular, 151 security, xiii, 54, 55, 57, 58, 60, 62, 63, 79, 128, 129, 131 sedentary, 113, 116, 117, 118, 121, 122, 124 sedentary behavior, 116, 117, 124 sedentary lifestyle, 113, 121 seizure, 93 seizures, 93, 98 selecting, 57, 130, 194 self, v, x, 28, 43, 44, 45, 47, 48, 50, 51, 68, 72, 87, 143, 168, 170, 173, 181 self esteem, 164, 169 self worth, 165 self-concept, 44, 49, 50, 72 self-definition, 164 self-efficacy, 114, 123 self-esteem, 43, 50, 66, 68, 69, 72, 164, 165, 166, 168, 174, 176, 220, 224, 227

312

Index

self-management, 77 self-monitoring, 49 self-organization, 50 self-perceptions, 275, 279 self-presentation, x, 25, 43, 44, 45, 48, 49, 50, 51 self-regulation, 123, 124 self-report, 45, 113, 122, 123, 222, 295 self-study, 218 Senate, 92 sensitivity, 225 separation, 161 September 11, xi, 53, 57, 58, 59, 63 series, xvii, 68, 69, 80, 101, 169, 222, 223, 259, 292 service provider, xii, 127, 129 services, 22, 128, 138, 140, 157, 159, 237 SES, 69 severity, 132, 134 sex, xiv, 88, 207, 213, 215 sex role, 88 sexism, 216, 217, 218 sexual identity, 208, 215 sexual orientation, xiv, 207, 208, 209, 210, 211, 212, 215, 216, 217 SFQ, 67, 69, 167, 171, 172 shame, 210 shape, 76, 78, 226 shaping, 63, 78, 83, 93 sharing, 41, 210, 261 Sherman Act, 197 shoot, 132 short period, 188 shortage, 104, 108 shoulder, 1 sign, 91, 155, 157, 184, 187, 199, 274, 283 signal quality, 294 signals, 119, 296 significance level, 212, 260 signs, 98, 131, 144, 156 similarity, 49, 78, 166, 168, 169, 174, 211, 264, 279 simulation, 144, 146 Singapore, 106 sites, 140, 234 skills, 4, 123, 144, 150, 159, 211, 231, 232, 240, 278, 280 skin, 1, 3, 4, 5, 6 sleep, 287 smoke, 196 soccer, 138, 146, 163, 175, 199, 230, 231, 279 social, xi, 7, 23, 49, 51, 56, 65, 66, 67, 68, 69, 70, 71, 72, 73, 85, 88, 152, 163, 164, 165, 173, 175, 181, 183, 211, 212, 214, 217 social adjustment, 232 social behavior, 23

social capital, 67, 71 social cognitive theory, 112, 122, 124 social comparison, 49 social competence, 51 social construct, 7 social exchange, 88 social fabric, 256 social identity, 66, 226, 227 social life, 66, 152, 181 social relations, 211 social sciences, 105, 212 social support, 145, 220 socialization, 125, 278 society, 4, 29, 30, 150, 189 socioeconomic, 122, 123 socioeconomic status, 122, 123 sociological, 50 sociology, ix, 105 software, 63, 140, 259 solidarity, 216 solutions, 62, 193 sorting, x, 43, 45 South Africa, 232, 241 South America, 235 South Korea, 106 specialization, 106 species, 64 spectrum, 214 speculation, 18, 286 speed, 95, 96, 97, 192 speed limit, 97 spiritual, 287 sponsor, 35, 61, 91, 92, 140, 210, 245, 256 sport psychologists, 270, 278 sport spectators, 14, 22, 176, 225, 280 sprains, 5 SPSS, 20, 27, 87, 212, 234, 242, 260 St. Louis, 23, 140 St. Petersburg, 178, 189 stability, 182 staffing, 254, 255 stakeholders, 150, 160 standard deviation, 20, 68, 118, 169, 225, 237, 251, 276 standards, 5, 119, 153, 187 stars, 99, 188 state laws, 156 state office, 93 Statistical Package for the Social Sciences, 27 statistics, 17, 20, 46, 47, 48, 81, 109, 126, 138, 139, 140, 142, 145, 146, 147, 152, 177, 200, 211, 217, 233, 234, 242 statutes, xiv, 100, 191, 192, 194, 195, 197, 203

Index stereotype, 29, 209 stereotypes, 29, 88, 208, 209 stereotypical, 145 steroid, xi, 89, 90, 91, 92, 94, 95, 96, 97, 98, 99, 100, 101, 102 steroids, xi, 89, 90, 91, 92, 94, 95, 96, 97, 98, 99, 100 stimulus, 278 stock, 45, 144 stomach, 287 storage, 295 strain, 3, 156, 268 strains, 5 strategic, 66, 85 strategies, xii, 12, 13, 14, 56, 63, 64, 66, 77, 87, 114, 127, 128, 129, 217, 225, 278, 279 streams, 254, 255 strength, 17, 95, 96, 99, 289 stress, ix, x, xvii, 34, 43, 44, 48, 49, 50, 164, 254, 258, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292 stress level, 288 stressful events, 44, 51 stressors, 49, 88, 232, 282, 283, 284, 285, 286, 292 stress-related, 50 strikes, 59, 159 stroke, 112 structural equation model, 10, 88, 125 structuring, 76 student enrollment, 37 student group, 40 students, xi, xii, xiii, 2, 13, 16, 19, 34, 37, 40, 57, 65, 67, 72, 90, 91, 93, 96, 97, 98, 101, 104, 105, 108, 109, 111, 114, 115, 137, 138, 140, 141, 142, 143, 144, 150, 154, 156, 157, 164, 175, 181, 182, 183, 186, 189, 208, 211, 212, 215, 216, 218, 224, 226, 230, 231, 232, 241, 256, 273, 284 subgroups, 49, 192 substance abuse, 183 substance use, 102 substances, 90, 91, 96, 97, 99 substitution, 47 success rate, 138, 141 suicide, 90 summer, 3, 153, 197 Super Bowl, xi, 54 superiority, 214 supervision, 129, 131 supervisor, xi, xvi, 75, 76, 77, 78, 79, 80, 81, 82, 84, 85, 86, 87, 88, 254, 281 supervisors, 78, 79, 258 supplements, 90, 99 supply, 104, 195 support staff, xvi, 254, 281

313

Supreme Court, 93, 96, 98, 196 surfing, 117, 118 surprise, xi, 54, 264 surveillance, 100 susceptibility, 55 suspensions, 178, 201 Sweden, 232, 240 swimmers, 232, 240 switching, xiv, 219, 224 Switzerland, 199 symbolic, 58, 61 symbols, 128, 159 symptom, 210 symptoms, ix, 1, 2, 5, 95, 96, 98 synthesis, 51 systematic, 12, 16, 21, 23, 47 systematic processing, 12 systems, 58, 60, 86, 149, 152, 179, 190, 198, 231, 270, 294, 295

T tactics, 86, 192, 225, 226 talent, 48, 90, 183, 230, 266, 272 tangible, 97 targets, x, xi, 53, 55, 56, 58, 60, 61, 128, 275, 276 task performance, 271 taxonomic, 179 taxonomic model, 179 teachers, 84, 108, 284 teaching, x, xvii, 33, 34, 38, 104, 105, 156, 214, 243, 278 team members, 76, 283, 285 team sports, 164, 216, 238, 240, 241, 280 technological, 63 technological advancement, 294, 295 technology, 84, 87, 139, 140, 145, 157, 294, 295 technology transfer, 157 teens, 99, 100 teeth, 96 telephone, 104 television, 66, 116, 117, 118, 123, 140, 152, 154, 254, 255 temporal, 129, 280 Tennessee, 90, 160, 220, 229 tension, 220 tenure, 34, 80, 83, 106, 107, 264, 266 terrorism, 54, 56, 60, 63, 64, 135 terrorist, x, xi, 53, 54, 55, 56, 59, 61, 63, 64 terrorist attack, xi, 53, 54, 55, 59, 61, 63, 64 terrorists, xi, 53 test scores, 178 testosterone, 99, 101, 226

314

Index

test-retest reliability, 116, 167, 222 Texas, xvii, 1, 89, 90, 91, 92, 97, 111, 139, 149, 177, 187 theoretical, 10, 17, 65 theory, xii, 18, 56, 59, 64, 72, 77, 78, 79, 86, 87, 88, 111, 112, 113, 119, 121, 122, 124, 125, 189, 190, 208, 210, 215, 218, 227, 256, 267, 272, 273, 279, 280 therapy, 4, 51, 236, 237, 240 thinking, 11, 210, 264 third party, 128, 135 threat, 15, 54, 55, 56, 58, 59, 60, 62, 66, 131, 132, 226 threatened, 154, 178 threatening, 159 threats, 54, 55, 56, 59, 60, 62, 227 threshold, 59, 237 TID, 15, 16 time commitment, 145 time constraints, 198 time consuming, 180 time periods, 259 timetable, 192 timing, 4 title, 106, 260 tolerance, 218 tort, 4, 128, 129, 135 toughness, 29 tracking, 188 trade, 139, 145 tradition, 257 traffic, xiii, 127 training, xvi, 29, 55, 90, 97, 109, 152, 217, 220, 232, 240, 254, 278, 281 trait anxiety, 44, 50 traits, 45, 46, 85, 87, 88 transactions, 23 transcript, 2, 7, 100, 195 transcripts, 100, 180, 195 transfer, 157 transformation, 118 transition, 109, 208 transmission, 3, 4, 126 transportation, 122, 195 trauma, 3 travel, xv, 33, 159, 243, 249, 250, 261, 285 trend, 95, 140, 178, 202, 291 trial, 10, 12, 17, 18, 101, 192, 194, 197 truism, 288 trust, 66, 78, 79, 86, 183, 184 trustworthiness, 73, 183 tuition, 158 Turkey, 106

turnover, 76, 77, 83, 84, 85, 86, 87, 88, 257 two-way, ix, 9, 21, 276 Type I error, 222, 223

U U.S. economy, x, 53 ubiquitous, 79 UK, 226 uncertainty, 55, 64 undergraduate, xii, xvii, 48, 103, 106, 107, 108, 109, 110, 150 undergraduate education, 150 unions, 156 United States, x, xi, xii, xiv, 13, 19, 53, 61, 63, 89, 90, 94, 96, 100, 103, 104, 105, 106, 115, 124, 125, 126, 130, 151, 174, 195, 196, 197, 198, 199, 211, 218, 221, 229, 230, 231, 232, 233, 235, 236, 239, 240, 241, 242, 268 univariate, 16, 20, 21, 47, 169, 170, 171 universities, xii, xiv, 37, 56, 60, 61, 103, 104, 105, 106, 107, 108, 109, 150, 151, 152, 153, 154, 156, 157, 158, 159, 177, 178, 179, 182, 189, 197, 221, 230, 242, 292 university students, 72 unreasonable searches, 93, 98 unstructured interviews, 179 upload, 218 urban, 37, 64, 211 urinalysis, 93 urine, 93

V vacancies, 107, 109 valence, 23, 63 validation, 72, 124, 126, 175 validity, 14, 15, 16, 34, 46, 57, 67, 72, 83, 94, 116, 122, 125, 211, 222, 227, 233, 237, 244, 259, 270 values, 25, 29, 79, 116, 119, 254, 266 variability, 44, 48 variable, 13, 15, 16, 17, 19, 47, 49, 69, 70, 81, 85, 88, 118, 169, 179, 238, 239, 258, 275, 276 variables, xii, 11, 14, 15, 20, 45, 46, 47, 49, 68, 69, 70, 80, 87, 88, 112, 114, 118, 119, 121, 167, 168, 179, 183, 190, 226, 234, 235, 260, 268, 275 variance, xii, 17, 19, 45, 69, 70, 84, 112, 116, 121, 122, 164, 235, 236 vehicles, 60 vein, 83 venue, 54, 59, 61, 64, 202 video, 15, 19, 22, 201

Index video clips, 22 video games, 117, 118, 140 vignette, 220 violence, 54 violent, 126, 128 violent behavior, 126 Virginia, 33, 64, 151 virus, 1, 3, 6, 7 virus infection, 6 viruses, 1, 7 visible, xv, 178, 225, 269, 271, 272, 276, 277, 278, 279 vision, 149 visual, 2 voice, 95, 96, 139, 183 voting, 153 vulnerability, 55, 58, 60, 63, 282

W wages, 122 walking, 116, 118, 121, 186 Wall Street Journal, 63 warrants, 67, 265 Washington, 64, 88, 216, 218 wavelets, 294 weakness, 60 web, 76, 138, 259 web service, 138 web-based, 259 websites, 140 weight loss, 2 welfare, 189, 291 well-being, xi, 44, 49, 50, 51, 65, 66, 67, 68, 69, 70, 71, 72, 73, 112, 165, 220, 224, 227, 228, 267 White House, 97, 98, 102, 151 White House Office, 98, 102

315

wide receiver, 202, 276, 277 wildfire, 139 windows, 242 winning, xvi, xvii, 4, 13, 27, 36, 138, 158, 220, 226, 281, 284, 291 wireless, 237, 295 wireless systems, 295 wires, 295 Wisconsin, 63, 160 withdrawal, 5 witnesses, 194 women, 26, 28, 29, 30, 80, 87, 88, 146, 160, 164, 207, 209, 210, 212, 213, 214, 215, 217, 221, 255, 256, 257, 265, 266, 268, 283 work climate, 254, 255 work environment, 76, 77, 84, 254, 264, 266 work ethic, 182, 188 workers, 84, 185, 195, 271 workforce, 150, 156 working population, 84 workload, 41 workplace, xv, 76, 196, 253, 254, 255, 257, 260, 265, 267 World Anti-Doping Agency, 199, 205 World Health Organization, 1, 7 World Trade Center, xi, 53, 59 World War II, 230 World Wide Web, 190 worry, 45, 90, 183, 284 writing, xviii

Y yield, 116, 173, 179, 225, 275 young adults, 134 young men, 283, 291 younger children, 114