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Electronic Theses, Treatises and Dissertations The Graduate School

2004

The Risk and Safety Practices in YouthBaseball and SoftballChristopher Francis Lachapelle

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THE FLORIDA STATE UNIVERSITY

COLLEGE OF EDUCATION

THE RISK AND SAFETY PRACTICES IN YOUTH BASEBALL AND SOFTBALL

BY

Christopher Francis Lachapelle

A Dissertation submitted to the

Department of Sport Management, Recreation Management, and Physical Education in partial fulfillment of the

requirements for the degree of Doctor of Philosophy

Degree Awarded:

Summer Semester, 2004

Copyright ©2004 Christopher Francis Lachapelle

All Rights Reserved

ii

The members of the Committee approve the dissertation of Christopher Francis

Lachapelle defended on Thursday, April 22, 2004. ______________________________ Aubrey Kent Professor Directing Dissertation ______________________________ Sande Milton Outside Committee Member ______________________________ Annie Clement Committee Member ______________________________ Charles Imwold Committee Member Approved:

Charles Imwold, Chairperson, Sport Management, Recreation Management, and Physical Education The Office of Graduate Studies has verified and approved the above named committee members.

iii

ACKNOWLEDGEMENTS

There are so many people I want to thank for guiding me to this ultimate dream.

Dr. Aubrey Kent my directing professor has been a great mentor. I would have never

imagined that a friend from the University of Windsor would later become so important

to me in my doctoral journey. Who would ever have thought that a Redwings fan and a

Leafs fan could be such good friends? Well, it can happen. I am so thankful to Dr. Kent

for his time, especially while he was experiencing fatherhood for the very first time.

I cannot thank Dr. Annie Clement enough for educating me in risk management

and encouraging me to investigate areas that were so unknown. She is an incredible

teacher, friend, and her knowledge is truly astonishing. I will always be grateful to her for

what she has done for me.

I want to thank Dr. Charles Imwold for not only being a member on my

committee but also being a great mentor during my years at Florida State. Every time he

had a chance to educate, direct, and support me, during our lunches, our many jogs

together or when he was in his office, he never hesitated to help me no matter how busy

he was. Finally, I give thanks to my final committee member Dr. Sande Milton. He has

inspired me as a teacher, and his direction during smoking breaks will always be

remembered. His style of teaching is something I try to implement in my teaching today.

Thanks for being such an inspiration to me.

I am grateful to many other professional colleagues for their assistance in

enabling me to fulfill my dream. I would like to thank Dr. Janet Wigglesworth and Dr.

Terry Pettijohn for directing me in my statistical analyses. I could not have been

successful without their time and direction. I want to thank Dr. Steve and Dr. Joy Mosher

iv

for supporting me during some tough times in this process. Both of them gave me so

much love, encouragement and support to make sure I did not fall off track.

I want to thank my professors at the University of Windsor for guiding me to my

passion for Sport Management. Dr. James Weese and Dr. Bob Boucher need to be

thanked for their unique teaching styles and direction. Special thanks to Dr. Marge

Holman, Dr. Dick Moriarty and Dr. Gordan Olafson for taking the time to push and make

me realize my potential in the field of Sport Management.

Western Illinois University was a truly a special learning experience for me. I was

able to make mistakes and learn about myself as a person. Dr. Charles Spencer, Dr.

James Karabetsos and Dr. Darlene Young are the three individuals that nurtured and

encouraged me during this time of my life. I need to thank Coach Dick Pawlow and his

amazing wife Fran for giving me so much love and direction during my years at WIU. As

well, I want to thank my best friends Oscar and Franciska Gomez for always being there

for me from the first day at WIU and they have continued give me tremendous support

and love no matter where they traveling. I am truly blessed to have them in my life.

I want to thank my colleagues at Mercyhurst College. During the final stages of

this journey they were always giving me support. Dean Michael Victor, Mike, Randy,

Penny, Helga, John, Bob, Will and Trish, thank you for all you have done for me. And

special thanks to Lee for all her help in editing and the tremendous support she has given

to me during the last six months.

This is the toughest part of my dissertation. How do I put into words what my

family has meant to me during my long and challenging journey? First of all, I need to

dedicate this dissertation to a few people. These two individuals are not here to celebrate

this moment physically but I knew they were there during my toughest times and will

always be a part of my life until I meet up with them again. My aunt Sharron and my

great friend Mathew Sylva encouraged me during the tough times and I know they are

celebrating in heaven and I bet Mat cannot believe I did it.

I have many friends to thank but I could not have accomplished this goal if it was

not for Keith Hamilton, Kevin Campbell, Kimberly Schlussel, Jessica Basham, Oscar

Gomez, Jill Taylor, Nancy Wenzel, Gina Capobianco and the Mary Amen (Gator Lady).

v

Their friendship was so valuable to me that I would not be where I am today without

them. You guys are simply the best. I want to thank the Hill, Fitzpatrick and Sylva

families. They have been a part of my life from day one, and there have not been three

families that have supported me more than these families. Finally, Dustin and Bonnie

Basham for loving me and making me feel closer to my native country of Canada.

I have to give a lot of my success at Florida State to Mary Seals-Evans and her

family. She not only taught me so much about life, she taught me about how a home

should feel and how people should be cared for. It was an honor to live with her for 3

years, and I can say coming home to your home every night was the best time in my life

while I was at Florida State.

During every journey, you need the financial support to keep going and I would

not have been able to even start this process (Masters) if it was not for my Aunt Mike and

Uncle Ren. These two people, are so important to me, words cannot be used. I thank them

everyday for loving me and helping me in so many ways. My brothers Wayne, Jared and

my sister-in-law Kimberley have played an extremely unique role in my journey. They

always made me laugh in how they viewed my educational life. Their support was

incredible in their own special way. I am proud to have you as my brothers and my sister.

I want to thank Anne (Jaws) and Steve DeLude for not only introducing me to my

wife (their daughter) but always being there to review my work, make suggestions, keep

my feet on the ground and supporting me every step of the way. I have been lucky to call

these people my friends but more importantly, my mother and father in law.

My mom and dad have been there since day one, never giving up on me when

times were tough, sacrificing so much of their lives for me, always there to give support

and encouragement and most of all, teaching me the values and beliefs to be a good

person, husband, and teacher. No one will ever know what this accomplishment means to

me and my parents. We have overcome so many things and I am who I am today because

of them.

Finally, I need to thank the person who entered my life at the beginning of my

doctoral journey and has been more than anything I could have ever imagined, my wife

Jennifer. She has been my strength, energy, and foundation. She has been my biggest

vi

teacher and I learn so much from her each and every day. Her brilliance, compassion, and

understanding has given me the needed energy to complete this incredible task. I owe her

so much, and I thank God everyday for Him leading me to her. I am honored to have her

as my wife and to share this moment and my future journey with her. For all those I did

not mention, you are all in my heart and you know how important you are to me.

vii

TABLE OF CONTENTS

List of Tables...................................................................................................................x

List of Figures ............................................................................................................. xiii

Abstract .......................................................................................................................xvii

CHAPTER 1: INTRODUCTION ....................................................................................1

Statement of Purpose ...........................................................................................3 Significance of the Study .....................................................................................4 Theoretical Proposition ........................................................................................5 Research Questions ..............................................................................................5 Limitations of the Study.......................................................................................6 Delimitations of the Study....................................................................................6

CHAPTER 2: REVIEW OF LITERATURE ....................................................................8

Baseball/Softball Participation and Injuries ..........................................................8 Court Cases........................................................................................................13

Byrne v. Fords-Clara Barton Boys Baseball Legion, Inc. (1989).............13 Lassegne v. American Legion, Nicholson Post #38 (1990) .....................14 Primrose v. Amelia Little League (1998) ................................................14 Taylor v. Massapequa Intern. Little League (1999).................................15 Zmitrowitz v. Roman Catholic Diocese (2000) .......................................15 West v. Sundown Little League of Stockton, Inc. (2002) ........................16

Risk Management Models..................................................................................16 The Kaiser Model (1986)........................................................................17 The Clement Model (1988, 1998) ...........................................................19 The van der Smissen Model (1990) ........................................................21 The Berlonghi Model (1990) ..................................................................24 The Head and Horn Model (1991) ..........................................................25 The Mulroney Model (1995)...................................................................30 The Tummala and Leung Model (1996)..................................................32 The Kavaler and Spiegel Model (1997)...................................................34 The Fried Model (1999)..........................................................................37 The Bandyopadhyay, Mykytyn, and Mykytyn Model (1999) ..................38 The Miccolis and Shah Model (2000) .....................................................41

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Summary of Models...........................................................................................44 Governance of Sport ..........................................................................................46

Sport Organizations ................................................................................46 Volunteerism..........................................................................................47

Summary ...........................................................................................................51

CHAPTER 3: METHODS.............................................................................................54

Overview ...........................................................................................................54 Research Design ................................................................................................54 Study Sample .....................................................................................................55 Pilot Study .........................................................................................................56 Instrumentation ..................................................................................................57 Data Collection Procedures ................................................................................58 Data Analysis Procedures...................................................................................59 Analysis of Research Questions .........................................................................60

CHAPTER 4: RESULTS...............................................................................................63

Introduction .......................................................................................................63 Results ...............................................................................................................63 Descriptive Statistics..........................................................................................64

Research Question 1 ...............................................................................65 Research Question 2 ...............................................................................65 Research Question 3 ...............................................................................71 Research Question 4 ...............................................................................73 Research Question 5 ...............................................................................74 Research Question 6 ...............................................................................82 Research Question 7 .............................................................................103 Research Question 8 .............................................................................116 Research Question 9 .............................................................................123

CHAPTER 5 : DISCUSSION & CONCLUSIONS ......................................................124

Introduction .....................................................................................................124 Discussion........................................................................................................124

Research Question 1 .............................................................................125 Research Question 2 .............................................................................126 Research Question 3 .............................................................................127 Research Question 4 .............................................................................131 Research Question 5 .............................................................................134

ix

Research Question 6 .............................................................................136 Research Question 7 .............................................................................138 Research Question 8 .............................................................................139 Research Question 9 .............................................................................141

Conclusions .....................................................................................................141 Research Question 1 .............................................................................142 Research Question 2 .............................................................................142 Research Question 3 .............................................................................143 Research Question 4 .............................................................................143 Research Question 5 .............................................................................144 Research Question 6 .............................................................................144 Research Question 7 .............................................................................145 Research Question 8 .............................................................................146 Research Question 9 .............................................................................146

Implications .....................................................................................................146 Future Recommendations.................................................................................147

APPENDIX A: SURVEY............................................................................................149

APPENDIX B: LETTER TO COACHES ....................................................................155

APPENDIX C: SURVEY RESULTS ..........................................................................157

REFERENCES............................................................................................................190

BIOGRAPHICAL SKETCH .......................................................................................197

x

LIST OF TABLES

Table 1. The van der Smissen Risk Management Implementation Model.......................23

Table 2. Risk Management Matrix.................................................................................29

Table 3. The Risk Matrix ...............................................................................................31

Table 4. The Risk Matrix with Treatments of Risk.........................................................31

Table 5. The Eight Constructs for Survey Analysis ........................................................58

Table 6. Answers to Survey Question 1 Organized by Location .....................................66




Table 10. Answers to Survey Question 5 Organized by Location ...................................68





Table 15. Linear Regression Results for Years Coaching and Safety Practices.............123

Table 16. Survey Responses for Warm-up & Cooldown ..............................................158

Table 17. Survey Responses for Safety & Field ...........................................................159

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Table 18. Survey Responses for Water & Injury ..........................................................160

Table 19. Survey Responses for Equipment .................................................................161

Table 20. Survey Responses for Preseason...................................................................162

Table 21. Question 3 – Location Comparison Results ..................................................163

Table 22. Question 3 – Country Comparison Results ...................................................164

Table 23. Question 4 – Location Comparison Results ..................................................164

Table 24. Question 4 – Country Comparison Results ...................................................164

Table 25. Question 5 – Warm-up & Preseason Results for Various Player Age Groups165

Table 26. Question 5 – Injury & Water Results for Various Player Age Groups...........166

Table 27. Question 5 – Safety & Cooldown Results for Various Player Age Groups....167

Table 28. Question 5 – Equipment & Field Results for Various Player Age Groups.....168

Table 29. Question 6 (Child) – Warm-up & Preseason Results ....................................169

Table 30. Question 6 (Child) – Injury & Water Results................................................170

Table 31. Question 6 (Child) – Safety & Cooldown Results.........................................171

Table 32. Question 6 (Child) – Equipment & Field Results..........................................172

Table 33. Question 6 (Enjoy) – Warm-up & Preseason Results....................................173

Table 34. Question 6 (Enjoy) – Injury & Water Results ...............................................174

Table 35. Question 6 (Enjoy) – Safety & Cooldown Results ........................................175

Table 36. Question 6 (Enjoy) – Equipment & Field Results .........................................176

Table 37. Question 6 (Community) – Warm-up & Preseason Results...........................177

Table 38. Question 6 (Community) – Injury & Water Results ......................................178

Table 39. Question 6 (Community) – Safety & Cooldown Results...............................179

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Table 40. Question 6 (Community) – Equipment & Field Results ................................180

Table 41. Question 7 (First Aid) – Warm-up & Preseason Results ...............................181

Table 42. Question 7 (First Aid) – Injury & Water Results...........................................182

Table 43. Question 7 (First Aid) – Safety & Cooldown Results ...................................183

Table 44. Question 7 (First Aid) – Equipment & Field Results.....................................184

Table 45. Question 7 (CPR) – Warm-up & Preseason Results......................................185

Table 46. Question 7 (CPR) – Injury & Water Results .................................................186

Table 47. Question 7 (CPR) – Safety & Cooldown Results ..........................................187

Table 48. Question 7 (CPR) – Equipment & Field Results ...........................................188

Table 49. Question 8 – Results for Various Coach Age Groups ...................................189

xiii

LIST OF FIGURES

Figure 1. The Kaiser Risk Management Model ..............................................................17 Figure 2. Risk Measures Matrix .....................................................................................19 Figure 3. The Clement Evaluation Model ......................................................................21 Figure 4: Steps in the Risk Management Process ...........................................................27 Figure 6. The Kavaler and Spiegel Risk Management Model.........................................36 Figure 7. The Bandyopadhyay, Mykytyn and Mykytyn Risk Management Model .........40 Figure 8. Summary of Models .......................................................................................45 Figure 9. Average Warm-up Survey Scores for Various Player Age Groups ..................78 Figure 10. Average Equipment Survey Scores for Various Player Age Groups ..............78 Figure 11. Average Preseason Survey Scores for Various Player Age Groups................79 Figure 12. Average Field Survey Scores for Various Player Age Groups .......................79 Figure 13. Average Injury Survey Scores for Various Player Age Groups......................80 Figure 14. Average Water Survey Scores for Various Player Age Groups......................80 Figure 15. Average Safety Survey Scores for Various Player Age Groups .....................81 Figure 16. Average Cooldown Survey Scores for Various Player Age Groups ...............81 Figure 17. Average Warm-up Survey Scores for Coaches Who Have and Do Not Have a Child/Relative Participating on Their Team...................................................................85

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Figure 18. Average Equipment Survey Scores for Coaches Who Have and Do Not Have a Child/Relative Participating on Their Team...................................................................85 Figure 19. Average Preseason Survey Scores for Coaches Who Have and Do Not Have a Child/Relative Participating on Their Team...................................................................86 Figure 20. Average Field Survey Scores for Coaches Who Have and Do Not Have a Child/Relative Participating on Their Team...................................................................86 Figure 21. Average Injury Survey Scores for Coaches Who Have and Do Not Have a Child/Relative Participating on Their Team...................................................................87 Figure 22. Average Water Survey Scores for Coaches Who Have and Do Not Have a Child/Relative Participating on Their Team...................................................................87 Figure 23. Average Safety Survey Scores for Coaches Who Have and Do Not Have a Child/Relative Participating on Their Team...................................................................88 Figure 24. Average Cooldown Survey Scores for Coaches Who Have and Do Not Have a Child/Relative Participating on Their Team...................................................................88 Figure 25. Average Warm-up Survey Scores for Coaches Who Were and Were Not Motivated to Volunteer Because They Enjoyed Coaching..............................................92 Figure 26. Average Equipment Survey Scores for Coaches Who Were and Were Not Motivated to Volunteer Because They Enjoyed Coaching..............................................92 Figure 27. Average Preseason Survey Scores for Coaches Who Were and Were Not Motivated to Volunteer Because They Enjoyed Coaching..............................................93 Figure 28. Average Field Survey Scores for Coaches Who Were and Were Not Motivated to Volunteer Because They Enjoyed Coaching ..............................................................93 Figure 29. Average Injury Survey Scores for Coaches Who Were and Were Not Motivated to Volunteer Because They Enjoyed Coaching..............................................94 Figure 30. Average Water Survey Scores for Coaches Who Were and Were Not Motivated to Volunteer Because They Enjoyed Coaching..............................................94 Figure 31. Average Safety Survey Scores for Coaches Who Were and Were Not Motivated to Volunteer Because They Enjoyed Coaching..............................................95 Figure 32. Average Cooldown Survey Scores for Coaches Who Were and Were Not Motivated to Volunteer Because They Enjoyed Coaching..............................................95

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Figure 33. Average Warm-up Survey Scores for Coaches Who Were and Were Not Motivated to Volunteer Because They Wanted to Give Back to the Community ............99 Figure 34. Average Equipment Survey Scores for Coaches Who Were and Were Not Motivated to Volunteer Because They Wanted to Give Back to the Community ............99 Figure 35. Average Preseason Survey Scores for Coaches Who Were and Were Not Motivated to Volunteer Because They Wanted to Give Back to the Community ..........100 Figure 36. Average Field Survey Scores for Coaches Who Were and Were Not Motivated to Volunteer Because They Wanted to Give Back to the Community...........................100 Figure 37. Average Injury Survey Scores for Coaches Who Were and Were Not Motivated to Volunteer Because They Wanted to Give Back to the Community ..........101 Figure 38. Average Water Survey Scores for Coaches Who Were and Were Not Motivated to Volunteer Because They Wanted to Give Back to the Community ..........101 Figure 39. Average Safety Survey Scores for Coaches Who Were and Were Not Motivated to Volunteer Because They Wanted to Give Back to the Community ..........102 Figure 40. Average Cooldown Survey Scores for Coaches Who Were and Were Not Motivated to Volunteer Because They Wanted to Give Back to the Community ..........102 Figure 41. Average Warm-up Survey Scores for Coaches Who Have and Do Not Have Current First Aid Certification .....................................................................................106 Figure 42. Average Equipment Survey Scores for Coaches Who Have and Do Not Have Current First Aid Certification .....................................................................................106 Figure 43. Average Preseason Survey Scores for Coaches Who Have and Do Not Have Current First Aid Certification .....................................................................................107 Figure 44. Average Field Survey Scores for Coaches Who Have and Do Not Have Current First Aid Certification .....................................................................................107 Figure 45. Average Injury Survey Scores for Coaches Who Have and Do Not Have Current First Aid Certification .....................................................................................108 Figure 46. Average Water Survey Scores for Coaches Who Have and Do Not Have Current First Aid Certification .....................................................................................108 Figure 47. Average Safety Survey Scores for Coaches Who Have and Do Not Have Current First Aid Certification .....................................................................................109

xvi

Figure 48. Average Cooldown Survey Scores for Coaches Who Have and Do Not Have Current First Aid Certification .....................................................................................109 Figure 49. Average Warm-up Survey Scores for Coaches Who Have and Do Not Have Current CPR Certification............................................................................................112 Figure 50. Average Equipment Survey Scores for Coaches Who Have and Do Not Have Current CPR Certification............................................................................................113 Figure 51. Average Preseason Survey Scores for Coaches Who Have and Do Not Have Current CPR Certification............................................................................................113 Figure 52. Average Field Survey Scores for Coaches Who Have and Do Not Have Current CPR Certification............................................................................................114 Figure 53. Average Injury Survey Scores for Coaches Who Have and Do Not Have Current CPR Certification............................................................................................114 Figure 54. Average Water Survey Scores for Coaches Who Have and Do Not Have Current CPR Certification............................................................................................115 Figure 55. Average Equipment Survey Scores for Coaches Who Have and Do Not Have Current CPR Certification............................................................................................115 Figure 56. Average Cooldown Survey Scores for Coaches Who Have and Do Not Have Current CPR Certification............................................................................................116 Figure 57. Average Warm-up Survey Scores for Various Coach Age Groups ..............119 Figure 58. Average Equipment Survey Scores for Various Coach Age Groups ............119 Figure 59. Average Preseason Survey Scores for Various Coach Age Groups..............120 Figure 60. Average Field Survey Scores for Various Coach Age Groups .....................120 Figure 61. Average Injury Survey Scores for Various Coach Age Groups....................121 Figure 62. Average Water Survey Scores for Various Coach Age Groups....................121 Figure 63. Average Safety Survey Scores for Various Coach Age Groups ...................122 Figure 64. Average Cooldown Survey Scores for Various Coach Age Groups .............122

xvii

ABSTRACT

Risk is the inevitable consequence of being human. We cannot entirely eliminate

or avoid all risk, as it is an inherent part of our nature. However, we are far from being

helpless victims wandering in a world of negative outcomes. We have developed

assessment tools and strategies for mitigating risks or counteracting potentially disastrous

outcomes. Risk management is a term used by experts to encompass all the strategies that

may be employed to deal with risk. From a bottom line financial point of view, the

objective of risk management is to efficiently conserve the assets and financial resources

of an organization and to maintain financial stability by reducing the potential for

financial loss. However, within a sport organization, risk management does not solely

focus on the financial aspects but also must include concern for the physical safety of the

participants and those who instruct them.

This study investigated risk and safety practices and methods utilized by youth

baseball and softball organizations and their coaches from four different regions (New

York & Florida, United States and Ontario & Alberta, Canada). Research included a

literature review examining the differences and similarities of the leading risk

management models, risk related legal liability cases and results, injury statistics from

youth baseball and softball (ages 5-17) participants, and the different actions and

motivating factors for risk and safety management for both sport organizations and

individual volunteers.

A survey was used to collect the data on safety and risk management practices

with close to a 50 % response. The survey was designed to answer eight research

questions. The research questions focused on the willingness to improve safety, the level

of the organization’s involvement in risk and safety, coaches’ actions to ensure safety,

xviii

measures of implementing safety, the relationship between coaches’ motivation to

volunteer and their safety practices and whether the age of the coach and/or players play

a role in risk and safety practices and actions. ANOVA techniques such as MANOVA,

one- and two-way ANOVA and post hoc testing were used to analyze the data.

In summary, coaches were willing to improve their level of risk and safety

knowledge if it was required as a prerequisite to coaching. Second, organizations were

not providing adequate risk and safety material or programs for their coaches and the

implementation of risk and safety procedures varied between regions. Third, as player

age increased, less risk and safety practices were conducted. Fourth, coaches who were

under thirty years of age conducted the most risk and safety practices. Fifth, coaches’

motivation to volunteer significantly influenced their risk and safety practices. Finally,

being certified in general safety techniques (First Aid and CPR) should be accompanied

with specific baseball and softball risk and safety education to improve overall safety.

1

CHAPTER 1

INTRODUCTION

Risk is an inherent part of life. Without accepting the risk of falling, an infant

would never learn to walk. Our species gained the knowledge of how to control fire only

through taking the risk of being burned. We drive and fly across the landscape with the

realization that we risk accidental injury. Businesses grow by taking calculated gambles

that their products will be competitive in the marketplace without causing unanticipated

injuries that will bring subsequent lawsuits and financial ruin. According to Berstein

(1996), the innovative idea that draws the boundary between modern times and the past is

the mastery of risk: the notion that the future is more than a whim of the gods, and that

men and women are not passive before nature. The word “risk” derives from the early

Italian word risicare, which means “to dare” (Berstein, 1996). Risk exists when people

are in the state of the world in which outcomes may differ from expectations. A “risk” is

an element of danger due to uncertainty, whereas a “hazard” is a given danger in its

particulars (Appenzeller, 1998). Managing risk is interpreted in many different ways

depending on the industry.

Risk management is a term created by experts for encompassing all the strategies

that may be required for dealing with such risk (Appenzeller, 1998). Risk management

has been a part of private and corporate environments for decades (van der Smissen,

1990). The objective of risk management is to efficiently conserve the assets and

financial resources of the organization and to achieve financial stability by reducing the

potential for financial loss (Kaiser, 1986). According to Clement (1988, 1998), risk

management is the identification, evaluation, and control of loss to property, clients,

2

employees, and the public. Risk management can also be defined as the attempt to reduce

losses and exposures and increase the desire to make sport safer (Appenzeller, 1998).

As participation rates of children in organized and informal sports and recreation

activities have increased over the years, substantial increases in sport and recreation

related injuries have been noted. Due in part to the rapid growth of sports programs, an

increase in the number of participants, and the proliferation of personal injury lawsuits,

safety has become one of the most important concerns for today’s sport manager

(Appenzeller & Lewis, 2000). An estimated 3.2 million children ages 5 to 14 suffer sport

and recreation related injuries each year (Ingersoll, Sitler, Mickalide, & Taft, 2001).

The United States (USA) Consumer Product Safety Commission’s (CPSC)

National Electronic Injury Surveillance System (NEISS) surveys USA hospital

emergency departments across the country and compiles yearly data on injuries

associated with 15,000 categories of consumer products (Consumer Product Safety

Review, 2001). This product-related injury data consists of a national probability sample

of hospital emergency departments of differing sizes and locations and provides national

estimates of the number and types of consumer product-related injuries. The Consumer

Product Safety Fall Reviews for 1999 through 2002 reported the following injury

statistics among children up to 15 years of age who participated in baseball/softball:

125,019 (1999), 138,666 (2000), 125,018 (2001), and 116,558 (2002).

Baseball is one of the most popular sports in North America and has the highest

fatality rate among sports for children aged 5 to 14, with three to four children dying

from baseball injuries each year between 1998 and 2000 (Consumer Product Safety

Review, Fall, 1999; National Safe Kids Campaign, 2001). Similar findings were reported

by Mueller, Marshall, and Kirby (2001) in their study of the years 1987 to 1996. Kyle

(1996) noted that one-third of these injuries could have been prevented or at least reduced

in nature if equipment such as reduced-impact balls, safety bases, and face guards were

universally used. Kyle goes on to report that proper use and maintenance of safer

equipment and the active promotion of a safety conscious attitude can only be gained

through the involvement of the coaches and administrators. In order to achieve this,

3

coaches and administrators must understand the foundations of coaching and risk

management (Appenzeller & Lewis, 2000).

In many cases, coaches and administrators in community based sports

organizations are parent volunteers. Certainly baseball is typical in this regard. Today,

volunteers fill vital roles as coaches, administrators, and instructors. The game of

baseball is often viewed as being very simple to teach and in which to participate. The

ball is caught, thrown, and batted, and players run around a diamond-shaped layout to see

who can score the most runs in a given time frame. Because of this misperception, many

individuals have been chosen to coach baseball teams without being given the proper

education, direction, and instruction by the organization, placing both coaches and

organizations at risk of litigation.

The majority of youth organizations rely heavily on volunteer involvement. These

volunteers have various talents and levels of expertise that often do not relate to coaching

or administering youth sport. The research conducted will investigate whether the

characteristics of volunteers such as motivation to coach, experience, safety certification,

age of players and the age of the coach impact the overall safety practices that are

implemented by coaches. Research indicates that organizations fail to implement added

safety qualifications of their coaches in fear of losing them (Clarke, 1999; Drucker, 1990;

Mackin, 1998). Further, organizations believe that avoidance in safety implementation is

the most efficient approach to decrease the potential lost during litigation.

Statement of Purpose

The purpose of this research was to identify what practices youth baseball and

softball coaches and sport organizations were conducting to ensure safety. The research

investigated factors such as the level of risk and safety practices being conducted by

youth baseball and softball coaches; their attitudes towards the topic; possible increase in

risk and safety standards in order to coach; how sports organizations have dealt with the

4

issue; whether a certain motivation to volunteer affected safety practices; and if the age of

the coach or players impacted risk and safety performance.

Significance of the Study

Due in part to the rapid growth of sports programs, an increase in the number of

participants, and the proliferation of personal injury lawsuits, safety has become one of

the most important concerns for today’s sport manager (Appenzeller & Lewis, 2000).

According to Altman and Kelly (1997) and Clement (1998), little research has been done

to investigate the level of risk management knowledge of volunteers in general, let alone

those involved in baseball/softball. There is a need for volunteers in youth sports because

of the rapid increase of the number of youth participants. It is critical to identify the level

of volunteers’ risk and safety knowledge and to educate those who lack these particular

skills.

In 1999, youth athletes between the ages of 5 and 14 accounted for 40 % of the

sports-related injuries for all sports (Consumer Product Safety, Fall, 2000), and 20 % of

these were considered serious (Washington et al., 2001). The fatality rate in baseball is

higher than that of any other sport for this age range (Cantu & Mueller, 1999). According

to Kyle (1996), one-third of the injuries could have been prevented with the proper safety

practices.

This investigation will look at volunteers actively coaching youth ages 5 to 17 in

baseball/softball. It is known that the number of injuries steadily increases with age,

peaking at 12 years (Kyle, 1996). With this in mind and the unknown status of volunteer

risk management practices, research will be conducted to determine whether the age of

the players, age of the coach, experience in coaching, and emergency care certification

play a part in the overall safety practices of the players. The significance of this research

is to determine whether or not effective risk and safety practices for baseball/softball are

being implemented through the coach via the sports organization and how consistent the

levels of risk and safety practices are in different regions.

5

Theoretical Proposition

The effectiveness of a risk management program is based on four critical aspects;

identification, evaluation, implementation, and control of the various potential risks that

surround the activity. Models such as Clement (1988), Berlonghi (1990), Enterprise Risk

Management (ERM), Fried Model (1999), van der Smissen (1990), Miccolis and Shah

(2000), Mulroney (1995), and Kavaler and Speigel (1997), will provide the framework

for this investigation.

The research is expected to find that certain aspects of risk and safety

management are being administered at a very low level such as identification of the

problems but in regards to the other three aspects it is not expected to see the actions of

the coaches or organizations reach the levels needed to provide a safe environment for all

participants.

Research Questions

The researcher proposes to answer the following eight research questions:

1. To what extent are baseball/softball coaches willing to improve safety practices

required by the organization in order to coach?

2. To what extent does the organization provide safety information for its coaches?

3. To what extent are coaches’ preparations to ensure the overall safety of their

players?

4. To what extent are coaches implementing safety measures?

5. What is the relationship between age groups and coaches’ safety practices?

6. Will a particular motivation to coach baseball/softball influence coaches’ safety

practices?

7. Will holding a current first aid and/or CPR certification influence coaches’ safety

practices?

6

8. What is the relationship between the age of coaches and their safety practices?

9. What is the relationship between the number of years coaching baseball/softball

and a coach’s safety practices?

Limitations of the Study

The researcher acknowledges the following seven limitations:

1. North American coaches are different than coaches in other parts of the world and

may not be representative of all areas.

2. Each coach may not be interested and motivated to thoughtfully complete the

study.

3. Coaches may be biased towards providing information about themselves.

4. Due to the large number of the sample, no prenotification to the sample or follow

up letter to the non respondents was conducted.

5. The questionnaire may not be filled out completely.

6. There could be a non-response error with the sample population.

7. The questionnaire could result in some level of sampling and or measurement

error.

Delimitations of the Study

The researcher proposes to delimit the scope of this study in the following ways:

1. Select baseball/softball coaches from the USA and Canada will be asked to

participate.

2. The test group chosen, youth baseball/softball coaches, may not be consistent

with outcomes for other sports or organizations, but only representative of itself.

3. Only youth baseball/softball coaches will be asked to participate.

7

4. Each person filling out the survey will be presently coaching youth between 5 and

17 years of age.

8

CHAPTER 2

REVIEW OF LITERATURE

Approximately 20 million children and youth take part in recreational or

competitive sports outside the schools (Washington, Bernharnt, Gomez, Johnson, Martin,

& Rowland, 2001). In 1999, youth athletes between the ages of 5 and 14 sustained 40 %

of sports-related injuries for all sports (Consumer Product Safety, Fall, 2000). According

to Washington et al. (2001), 20 % of those injuries were considered serious. Baseball had

the highest fatality rate among sports for children from 5 to 14, with three to four children

dying from baseball injuries each year (National Safe Kids Campaign, 2001).

Youth baseball organizations, like most sports programs, rely on volunteers, many

of whom are untrained and unskilled in the particular sport. Youth baseball organizations

claim not to have the expertise and financial resources to formally educate their

volunteers on proper safety techniques. The following are the results of research on

baseball/softball participation and injuries, court cases, risk management models, and

governance of sport.

Baseball/Softball Participation and Injuries

Hergenroeder (1998) found that there were 30 million children and adolescents

participating in some form of organized sports in the USA. According to the National

Sporting Goods Association (2001), 32 million children and adolescents participated in

some form of organized sports in the USA in the year 2000. Approximately 3 million

9

injuries occurred annually during sports participation by children and adolescents in the

USA, with injury being defined as “a physical ailment resulting from sports activity that

causes time lost from sports participation” (Hergenroeder, 1998, p. 1057). Baseball’s

popularity in the USA and the numerous injuries that young players have incurred has

been the subject of inquiry by a number of organizations (Pasternack, Veenema, &

Callahan, 1996). In a report by the Baseball and Softball Council (1998), baseball was

second only to basketball in team sport participation. Basketball had an estimated 8.6

million players from 6 to 17 years of age. The National Sporting Goods Association

statistics indicated that participation in baseball/softball among youths age 7 and older

was 29.6 million in 1999 (2000), and 28.1 million in 2000 (2001).

In the Eighteenth Annual Report for the National Center for Catastrophic Sport

Injury, Mueller and Cantu (2000) defined three categories of catastrophic injury:

1. Fatality - death.

2. Non-fatal - permanent severe functional disability.

3. Serious - no permanent functional disability but severe injury. (Example:

fractured facial bone)

They characterized sport injuries as direct or indirect. Direct injuries occurred to

participants who were taking part in the skills of a particular sport. Indirect injuries were

caused by a systemic failure of the body as a result of exertion from participating in a

sport (after participation). Both direct and indirect injuries could result in a fatality.

Mueller and Cantu (2000) identified four baseball/softball deaths and one nonfatal

permanent severe functional disability injury in athletes between the summer of 1999 and

the spring of 2000.

Cantu and Mueller (1999) studied baseball injuries at the high school level from

1983 to 1997. They found that high school baseball caused 28 direct fatalities or

catastrophic injuries. Most occurred during headfirst sliding or when a player was struck

by a thrown or batted ball. Mueller et al. (2001) concluded that the greatest number of

injuries associated with baseball occurred during base running, with infielders having the

most frequent casualties.

10

Since the beginning of the 20th century, interest and fascination with the game of

baseball has grown steadily, but not until 1965 did the issue of “Little League elbow”

raise concerns about the overall safety of youth baseball (Risser, Anderson, Bolduc,

Harris, Landry, Orenstein, & Smith, 1994). Over the years, highly publicized catastrophic

impact injuries from contact with a ball or bat have raised new safety concerns. These

injuries, as well as the ongoing concern for shoulder and elbow injuries, have motivated

the medical and sports communities to investigate the game and identify the potential for

serious injury. Little League Baseball, Inc. conducted the original study on baseball

safety in 1961 (Hale, 1961). Investigations of the safety of children who participated in

baseball have continued through groups such as the Consumer Product Safety

Commission (Rutherford & McGheel, 1984), and the Academy of Pediatrics (Risser et

al., 1994).

The USA Consumer Product Safety Commission (Fall, 1986) found that from

1973 to 1980, there were 40 baseball/softball-related deaths reported for children between

the ages of 5 and 14. Of these deaths, 21 resulted from head and neck injuries, 17 from

non-penetrating impact to the chest, and 2 from other undisclosed causes - an average of

5 per year. According to Cantu and Mueller (1999), the number of deaths in baseball was

more than that of any other sport. This average has stayed consistent since 1973. Of these

deaths, 43 % were from direct-ball impact to the chest, 24 % were from direct-ball

contact with the head; 15 % were from impacts from bats; 10 % were from direct contact

with a ball impacting the neck, ears, or throat; and in 8 % the instrument that led to death

was not identified. Recently, Mueller et al. (2001) reported 13 deaths among 5- to 12-

year-old Little League baseball and softball players identified in a study conducted for

the years between 1987 and 1996. Kyle (1996), using CPSC data, found that between

1973 and 1995 there were 88 baseball related deaths in children of 5 to14 years, an

average of 4 per year.

According to Hergenroeder (1998), 25 % to 30 % of sports injuries in 1997

occurred to youth who were involved in organized sports and another 40 % to youth

playing unorganized sports. Approximately 3 million injuries occurred annually during

sports participation by children and adolescents in the USA, with injury being defined as

11

“a physical ailment resulting from sports activity that causes time lost from sports

participation” (Hergenroeder, 1998, p. 1057). The overall incidence of injury in baseball

ranges between 2 % and 8 % of participants every year (Washington et al., 2001). Among

children from 5 to 14, an estimated 162,000 baseball/softball and tee-ball injuries were

treated in emergency rooms in 1995. There were similar findings for the two previous

years (Pasternack et al., 1996).

Kyle (1996) found that the number of injuries steadily increased with age,

peaking at 12 years. The injuries were fractures (26 %), contusions and abrasions (37 %),

and strains, sprains, concussions, internal injuries, and dental injuries (37 %). Mueller et

al. (2001) expanded on Kyle’s (1996) findings to show that fractures and dislocations

(severe injuries) accounted for nearly half of all injuries to hands, arms, and elbows and

for 30 % of the injuries to the knees, legs, and ankles. The potential for life-threatening

injury resulted from a direct strike with a bat, baseball, or softball. Incidences resulting in

death have been from impact to the head that resulted in intracranial bleeding and from

blunt chest impact. Children 5 to 15 years of age may be more susceptible to blunt chest

injuries because their thorax is not adequately developed to sustain a contact of that

intensity (Link, Wang, Pandian, et al., 1998).

The most frequent cause of death and serious injury comes from direct contact

with the ball (Mueller et al., 2001). Over the years, preventive measures have been

implemented to protect young players from direct ball contact. Batting helmets, face

protectors, bases, and special equipment for the catcher are some of the advances that

have been developed to decrease the chance of injury. Janda, Maguire, and Mackesy

(1993) concluded that there was an 80 % reduction in sliding injuries when safety bases

were used.

Recently, concern has been raised about eye injuries in baseball. More eye

injuries to children occur in baseball than in any other sport, and the highest incidence

occurs in children 5 to 14 years of age (Yen & Metzel, 2000). Grin, Nelson, and Jeffers

(1987) first noticed the high incidence of eye injuries in baseball, and later studies

conducted by Nowjack-Raymer and Gift (1996) concluded that 41 % of baseball injuries

occur to the head, face, mouth, or eyes. Headgear and faceguards have been developed

12

for baseball and softball players, but not all leagues or teams are required to use this

safety equipment. In many cases, only selected positions such as catchers and hitters are

covered by the rules of safety. Nowjack-Raymer and Gift (1996) found that only 7 % of

the baseball/softball players wore mouth guards all or most of the time and only 35 % of

them wore the proper protective headgear. Kyle (1996) concluded that one-third of all the

injuries could have been prevented or at least reduced in nature if equipment such as

reduced-impact balls, safety bases, and face guards had been universally used. Risser et

al. (1994) highlighted the recommendations made by the American Academy of

Pediatrics (p. 693). They are as follows:

1. Pediatricians may be supportive of the desire of 5- to14-year-old children to participate in baseball and softball. Catastrophic and chronically disabling injuries are rare and do not seem to have been increasing in frequency in the past decade.

2. All preventive measures should be employed to protect young baseball pitchers from disabling throwing injuries. These measures include a restriction on the amount of pitching, in both organized and informal settings, instruction of proper biomechanics, and education of parents, coaches, and children to permit early diagnosis and treatment of overuse pitching injuries. All preventive measures that can reduce serious and catastrophic injuries should be employed in both baseball and softball. These include approved batting helmets; catcher’s helmet, neck and throat protectors; and rubber spikes. Elimination of the on deck circle, the protective fencing of dugouts and benches, and the use of breakaway bases is recommended.

3. Protective equipment should always be sized and maintained. It should be employed in games and practices and in formal and organized participation.

4. Rules should be modified for pitching and alternative pitching techniques and the avoidance of headfirst sliding for players less than 10 years of age should be introduced.

5. Players are encouraged to wear safety polycarbonate protectors on their helmets and goggles in the field.

6. Low impact baseballs and softballs should be used to reduce injury risk. 7. Surveillance of baseball and softball injuries should be continued. Research

should be continued to develop other new, improved, and efficacious safety equipment.

These same recommendations were stated in Washington et al. (2001) when they

investigated baseball injuries to children from 5 to 14 years old. They further brought

emphasis to the coaches’ role in decreasing the chance of injuries for athletes. Coaches

need to be able to teach the fundamental skills of the sport and they should not be

13

appointed if they do not have the training and experience needed to teach the skills of the

sport and properly train athletes (Risser et al., 1994).

Court Cases

The increase in lawsuits has caused nonprofit youth baseball organizations to

spend countless sums each year to defend themselves against claims (Altman & Kelly,

1997). According to Holman (2002), “the increase in litigation can be partially attributed

to the fact that people are more aware of their rights and seek remedy through the courts”

(p. 149). Most lawsuits against youth baseball organizations relate to negligence of a

volunteer and/or the organization. Some of the most significant cases in baseball are

described below.

Byrne v. Fords-Clara Barton Boys Baseball Legion, Inc. (1989)

Byrne (1989), an 11-year-old, was instructed by coach Bonk to warm up the

pitcher. Byrne went out to the field without wearing a mask, was struck in the eye with

the ball, and sustained serious eye injury. The plaintiff charged Bonk with ordinary

negligence and with “willful, wanton, reckless and gross” negligence. The defendant lost

and appealed. Bonk’s motion for dismissal was based on the League’s failure to have

established a safety program for volunteers. “The trial court judge did not rule on the

wanton and gross negligence claims and declined to read the statute as requiring the

establishment of a safety and training program for volunteers, concluding therefore that a

volunteer who did not have training in safety because there was no program was fully

entitled to statutory immunity” (p. 1224). A partial summary judgment dismissing

ordinary negligence was awarded to the defendant.

14

Lassegne v. American Legion, Nicholson Post #38 (1990)

In the Lassegne case (1990), the baseball team was practicing on wet grass, not an

official field, because of inclement weather. The child was hit in the head when a fellow

player slipped as he was throwing the ball. The coaches checked the injured player and

determined that he was fit to continue play. That night, Lassegne told his parents about

the incident. Later that night he developed severe symptoms from the injury to his head;

he was taken to a hospital and required surgery. In the suit, Lassegne’s parents accused

the coaches of inadequate supervision and failure to render aid and assistance as would be

expected from ordinary prudent coaches. Cassels and Johnson, the coaches, did not report

Jason's injury to the parents, thereby increasing the severity of the injury. The trial court

granted the defendants' motion for summary judgment, dismissing the plaintiffs' claim.

The Court of Appeals affirmed the lower court’s decision that the coaches did not breach

their duty.

Primrose v. Amelia Little League (1998)

Primrose resulted from an altercation following a Little League baseball game

between the towns of Amelia and Lumberton. The Amelia players attacked the

Lumberton players in the parking lot with bats and other objects; as a result, Larry

Primrose II received an injury to his knee and Chad Hampshire sustained a concussion

from a blow to the head. Larry Primrose and his wife, Lona Primrose, individually and as

next friend for Larry Primrose II, a minor, brought a personal injury suit against the

Amelia Little League. A suit against the league was also brought by Bobby Hampshire

and his wife, Winnie Hampshire, individually and as next friend for Chad Hampshire, a

minor. The Primroses sued Amelia Little League for negligence, gross negligence,

malice, and fraud. The Hampshires sued the league on the grounds of tortuous conduct,

negligence, gross negligence, and malice. Amelia Little League filed a motion for

15

summary judgment. The court ruled in favor of the defendant. The Primroses appealed,

claiming that the coaches of Amelia should have known that the game could have

resulted in violent behavior because of the threats and language used during the game.

The Texas Court of Appeals, Ninth District, Beaumont, ruled that the summary judgment

was well established on the grounds that foreseeability alone was not sufficient to justify

the imposition of a duty.

Taylor v. Massapequa Intern. Little League (1999)

Taylor (1999), a 10-year-old plaintiff, participated in a so-called minor league

level game after two years of playing at a lower level. The plaintiff’s coach instructed the

team’s members that they had to slide into the base or they would be called out. Nobody,

including the coach, had ever taught Taylor the proper way to slide. The plaintiff slid into

third base at his coach’s direction and injured his left knee. Taylor sued on the grounds

that the defendants were negligent in “failing to provide adequate training and/or

coaching for the activities required during baseball games” (p. 397). The defendants

moved for a summary judgment on the grounds that the plaintiff had assumed the risk of

the injuries incurred. The Supreme Court of New York denied the motion and found in

favor of the plaintiff.

Zmitrowitz v. Roman Catholic Diocese (2000)

Zmitrowitz (2000), a catcher, was injured when, after signaling the pitcher to

deliver a fast ball, the pitcher decided to throw a curve ball that deflected off her glove,

striking her in the nose. She suffered a concussion and a broken nose that required

surgery. The jury apportioned fault between the parties, attributing 60 % of the blame to

the defendants and 40 % to Zmitrowitz. The defendants appealed the verdict. The New

York Supreme Court, Appellate Division, found no reason to disturb the jury’s verdict,

16

holding that the failure to provide a catcher during a tryout session was inconsistent with

the standard athletic custom in the state.

West v. Sundown Little League of Stockton, Inc. (2002)

West (2002) filed suit against Sundown Little League of Stockton, Inc., for

injuries sustained from losing a baseball in the sun and getting hit in the left eye. The

complaint alleged that the defendants had negligently increased the risk of harm to West

by throwing balls into the sun on purpose. The court ruled in favor of the defendants

because the situation was viewed as a condition of inherent risks of the sport of baseball.

Risk Management Models

In discussions with colleague Tom Aaron there were six models of risk

management (Kaiser, 1986; van der Smissen, 1990; Clement, 1988, 1998; Head & Horn,

1991; Berlonghi, 1990; Mulroney, 1995) that were planned jointly (T. Aaron, personal

communication, April, 2002). The rest of the models are unique to this document. A

variety of professionals have devised plans to reduce risk in specific areas. The

profession of sport management is no different. Scholars in the field have also developed

guidelines to reduce the risk in the areas such as recreation (Kaiser, 1986; van der

Smissen, 1990), sport and physical activity (Clement, 1988, 1998; Head and Horn, 1991),

event management (Berlonghi, 1990; Fried, 1999), and sport facilities (Mulroney, 1995).

Other models helpful to the discussion are Tummala and Leung (1996), Kavaler and

Spiegal (1997), Bandyopadhyay, Mykytyn, and Mykytyn (1999), and Miccolis and Shah

(2000).

17

The Kaiser Model (1986)

The objective of risk management is to efficiently safeguard the assets and

financial resources of the organization and to achieve financial stability by reducing the

potential financial deficit (Kaiser, 1986). As shown in Figure 1, the Kaiser (1986) model

identifies risk management as having four components: identification, evaluation,

selection, and implementation.

Risk Identification

- Tort

- Contract

- Fidelity

- Property Loss

Risk Treatment

- Avoidance

- Reduction

- Retention

- Transference

Risk Evaluation

- Probability of Loss

- Severity of loss

Risk Implementation

- Policy

- Procedures Manual

Figure 1. The Kaiser Risk Management Model Note: From Liability and Law in Recreation, Parks, and Sports by R. A. Kaiser, 1986, Englewood Cliffs, NJ: Prentice Hall.

18

Risk identification is a critical aspect of risk management. This model first

requires the ability to identify all risks prior to their occurrence and dictates whether an

organization can effectively treat each risk. Although sport administrators are faced with

a variety of financial and legal risks, such as property loss and contractual liability, the

Kaiser model focuses only on tort liability risks.

According to Kaiser (1986), only two possible options are available to identify

tort liability risks confronting an agency and its personnel. Administrators may retain

outside professional services such as those of an insurance consultant to aid in identifying

risk, or they may undertake the enormous task with existing staff. Questionnaires often

used to identify risk must be developed to meet the individual needs of the agency. The

evaluation procedures for each risk situation can vary from simple implications to

complex statistical analysis. Regardless of what instrument is used, all involve the

determination of the probability of loss occurring, maximum and minimum severity of

such loss, predictability of a loss during a given period of time, and financial resources to

deal with such losses (Kaiser, 1986).

Identifying risks is only one part of successful risk management. An agency or

organization must decide on the options available to protect against losses. Some of the

options available to organizations to handle risks are risk avoidance, risk reduction, risk

retention, and risk transference (Kaiser, 1986) (Figure 2). No single method will assure

effective results. Subjective evaluations must be applied in the process. According to

Kaiser (1986), however, it is possible to develop a set of steps for selecting the best risk

treatment process for a situation. For any policy or procedure to reach its expectations,

commitment is needed from the agency or organizational governing board, and proper

training must be provided to all the parties involved. If the employees are not fully

engaged in the risk management plan and solid procedures are not developed and

maintained, the goal of reducing tort liability will not be achieved.

19

Hig

h 5Avoidance

4

3Retention

2Reduction Transfer

1

Low

0 1 2 3 4 5

Low HighMagnitude of Loss in Dollars

Freq

uen

cy o

f A

ccid

en

ts

Figure 2. Risk Measures Matrix Note: From Liability and Law in Recreation, Parks, and Sports by R. A. Kaiser, 1986, Englewood Cliffs, NJ: Prentice Hall.

The Clement Model (1988, 1998)

“The purpose of risk management is to make the sport and exercise environment

as safe as possible for participants and spectators, and the business efficient using

accepted business practices” (Clement, 1998, p. 219). According to Clement (1988, 1997,

1998), a risk management program requires a systematic examination of the environment,

with identification of potential for loss and legal liability. Clement agreed with the

20

findings of Kaiser (1986), that risk management encompasses the identification,

evaluation, and control of risks to property, clients, employees, and the public.

The first step of the Clement Model (1988, 1998) is the creation of a risk

management program that will be able to discover all of the areas of risk. The

identification of all possible incidences that could affect the safety of participants or

spectators must be determined. Identifying all the possible risks is crucial for developing

a high-quality risk management plan. Particular importance should be assigned to those

instances that could subject the agency or organization to public criticism or potential

litigation. This requires an understanding of local, state, and federal regulations;

professional organizations’ and industries’ standards; policies and procedures; facility

requirements; equipment; personnel; supervision; participant education; and contracts.

Once each risk is identified, it must be evaluated (Figure 3) to determine the

degree of liability it represents. Risks are assessed in terms of probability, severity, and

magnitude. Clement used a Likert scale to determine the level of risk (Clement, 1988,

1998). The evaluation process in the Clement model then uses the three factors to rate

identified risks from low to high. For example, a situation rated as a low risk may have a

high probability of occurring but when it does occur, the few who were directly involved

will suffer only minor discomfort. On the other hand, a situation rated as a high risk may

be low in probability but would result in multiple fatalities. Any activity scoring high on

the Clement evaluation model should be given serious consideration. A single death or

even minor discomfort for a large population could have a tremendous impact on the

organization (Clement, 1988, 1998).

The third and final step in the Clement model is to implement control within a

risk management plan. The author highlighted ways that liability could be controlled:

1. Accepting the risk and assuming the responsibility.

2. Retaining the activity and transferring the risk through contract or insurance.

3. Altering the activity to reduce the risk.

4. Eliminating the activity.

21

PROBABILITY A……………………………………………………………………..B

Low probability of injury or harm High probability of injury or harm

SEVERITY A……………………………………………………………………..B

Minor discomfort Serious injury or death

MAGNITUDE A……………………………………………………………………..B

Few people injured Many people injured

Figure 3. The Clement Evaluation Model Note: From Law in Sport and Physical Activity by A. Clement, 1998 (2nd ed). Tallahassee, FL: Sport and Law Press.

The van der Smissen Model (1990)

The model created by van der Smissen in 1990 was best described when she

stated: “A plan need not be sophisticated or complex, but can be simple for small

operations; but it must be prepared carefully . . . the plan is not static, needing preparation

only once…It is dynamic and needs to be regularly reviewed for updating . . . changing

approaches to controlling losses in keeping with changing needs and capabilities of the

organization which become available within the insurance industry, as well as within the

organization, itself, for loss control” (van der Smissen, 1990, p. 3-4).

The van der Smissen (1990) evaluation process is similar to the Clement model

regarding probability and the ranking of potential levels of severity as high or low. The

22

van der Smissen (1990) model encompasses statements of policy, risk analysis,

determination of control approaches, and implementing processes (Table 1).

According to van der Smissen, statements of policy should receive the support of

the board or policy-making body of the corporation, whether governmental or

nongovernmental. Statements should be created to delineate the importance of risk

management to the organization and where it fits within the organizational structure.

These statements should indicate the extent and nature of approaches to managing risk

and the policies by which the approaches are enforced and maintained. Risk analysis and

determination of control approaches is a continuously developing process. The severity

and extent of risk is often very difficult to identify; therefore, a plan must be created to

recognize and implement the most effective approach to deal with a variety of risks. This

plan consists of three parts: identification of risks, estimation of the extent of the risks,

and determination of available alternative approaches to control the identified risk as well

as the expected impact each risk could create. Identification of risks in the van der

Smissen model is continuous; it is initially prepared at the beginning of the risk

management plan and should be formally addressed periodically. Plans must be creative

and adaptable to changing times. There is no one specific way to identify risks; the

process involves interaction with employees, administrators, and external experts. An

effective procedure can then be developed to serve the needs of the operation.

Estimation of risks is the second step of the plan. There are four dimensions to the

measurement process: severity, frequency, predictability, and probability of the loss.

Severity is often related to risk management through the financial perspective, with an

assessment of the impact on the corporation’s ability to function. There are three degrees

of severity: vital, significant, and insignificant. Vital would be losses that result in

bankruptcy. Significant would require a cutback or financial reallocation of funds to deal

with the problem. Insignificant severity is a loss that can be handled through operating

revenues. In regard to personal injury, degree of severity might be high, medium, or low.

High severity could result in a fatality or permanent disability, medium in permanent

injury, and low in temporary disability or minor permanent injury. The frequency with

23

which an incident occurs must be differentiated into three levels: high or often, medium

or infrequent, and low or seldom.

The third step of risk analysis is assessing the potential approaches to risk control,

that is, how to decrease the severity of losses. There are four approaches to risk control:

elimination, transfer, retention, and reduction. Elimination can be by avoidance or

discontinuance. When a risk is deemed unacceptable, the activity is discontinued.

Avoidance is used when the organization determines to avoid the risks involved or to

manage the risks while allowing the activity to continue. Avoidance is an effective

alternative when the organization is unable to fully meet all the standards of care for the

activity. Transfer is the assignment of financial risk to another by contract or affiliation

agreement. The third alternative is retention. It is best described as self-insuring; the best

example would be that of deductibles. Finally, reduction is the management of situations

Table 1. The van der Smissen Risk Management Implementation Model Note: From Legal Liability and Risk Management for Public and Private Entities by B. van der Smissen, 1990, Cincinnati, OH: Anderson.

High or Often Medium or Infrequent Low or Seldom

High or Vital Avoid or transfer Transfer Transfer

Medium or Significant Transfer Transfer or retain Transfer or retain

Low or Insignificant Retain Retain Retain

24

that lead to claims and lawsuits by creating programs that decrease the severity and

frequency of the risks. The final step of van der Smissen’s plan is implementing the

process. Selecting the right approach for the organization’s financial structure is critical

for success. For any program to be effective, the procedures and policies set forth must be

used properly and monitored regularly.

The Berlonghi Model (1990)

Berlonghi (1990) has developed an efficient, manageable, and cost-effective

model for event managers. He defines risk management as a process of creating and

successfully implementing policies that minimize the adverse effects of potential losses

in staging an event. Effective risk management programs should identify the problems

and then create alternative solutions within the organization’s financial capabilities. The

Berlonghi (1990) model identifies five processes that lead to effective risk management:

risk analysis, examining risk management techniques, planning effective and appropriate

actions and systems, implementing recommendations to ensure safety, and evaluating and

improving the risk management program.

Before an event takes place, risk factors should be identified and separated into

those that are unrealistic, potential, probable, and realistic. There are four parts to this

process:

1. What is exposed to loss?

2. What specifically could cause a loss?

3. Who would suffer the loss?

4. What are the financial consequences?

There are many ways to handle risk, and a risk manager must decide on the most

feasible alternatives for dealing with potential losses once they have been identified. This

can be accomplished through risk control and/or risk financing. Some situations can be

dealt with by implementing rules and procedures to decrease the chance of risk. Other

25

situations, not so easily prevented, may require protective steps such as obtaining

insurance (Berlonghi, 1990). Depending on the event, risk managers must decide on the

most effective and appropriate actions to serve the goals and objectives of the event. The

severity and frequency of expected losses needs to be determined, the outcomes of

decisions considered, and the cost to implement those decisions calculated.

According to Berlonghi (1990), all recommendations must be workable - that is, a

risk manager or other personnel must be able to implement them. There is no point in

encouraging actions that could not or would not be implemented or successfully carried

out. Finally, an evaluation should be completed after the event that objectively analyzes

the success and effectiveness of the risk management program and the program’s

feasibility. This evaluation should include all cost-related functions such as insurance

premiums and administrative costs necessary to execute the risk management plan

(Berlonghi, 1990).

The Head and Horn Model (1991)

The focus of the Head and Horn Model (1991) is to identify loss exposures that

confront an organization and determine the most efficient and effective practices for

handling such exposures. Their objectives of risk management are classified as either

preloss or postloss objectives. Important objectives before a loss occurs include economy,

reduction of anxiety, and meeting legal obligations. Important objectives after a loss

occurs include survival, stability of earnings, continued growth, and social responsibility.

The Head and Horn (1991) model of risk management involves four steps:

identify potential loss, evaluate potential loss, select the appropriate technique for treating

loss exposures, and implement and administer the program (Figure 4).

The first step is to identify all the significant and insignificant loss exposures.

Many different sources of information can be used to aid in the identification of such

potential losses including risk analysis questionnaires, physical inspection, flowcharts,

and financial statements (Head & Horn, 1991).

26

After the identification process is completed, the next phase is to evaluate and

measure the potential impact of losses on the organization. Loss frequency is defined as

the probable number of losses that may occur during some given time period. Loss

severity is defined as the probable size of the losses that may occur (Head & Horn, 1991).

Once the relative frequency and severity of loss is estimated, the risk manager can choose

the appropriate technique for handling each exposure (Head & Horn, 1991). According to

Head and Horn (1991), the techniques that are chosen to deal with the exposures can be

classified as either risk control or risk financing. Risk control refers to techniques that

decrease the frequency and severity of accidental losses. These actions either prevent

losses from occurring or reduce the severity of a loss after it occurs. The techniques most

often used in risk control are avoidance and loss control.

Avoidance means a certain loss exposure is never accepted, or an existing loss

exposure is eliminated. If the loss exposure is not permitted, the chance of loss is reduced

to zero. The disadvantage is that avoiding an exposure may not always be feasible or

practical (Head & Horn, 1991). Loss control has two important components: loss

prevention and loss reduction. Loss prevention refers to measures that reduce the

frequency of a particular loss. Loss reduction refers to measures that reduce the severity

of a loss after it has occurred. Risk financing consists of methods for funding losses after

they occur. Those techniques are retention, noninsurance transfers, and commercial

insurance.

When losses do occur, the agency must cover part or all of the costs that result.

Retention can be either active or passive. Active risk retention occurs when an

organization is aware of the loss exposure and plans to absorb all or part of the potential

loss. Passive risk retention is the opposite of loss exposure because the organization fails

to identify the loss exposure, and thus does not take the necessary actions to handle it.

According to Head and Horn (1991), retention can be used in a risk management program

when no other methods of treatment are available, the worst possible loss is not serious,

and losses are highly predictable. The importance of risk retention is that it allows the

organization to save money, increase cash flow, and encourage loss prevention. Risk

27

retention also has its faults, however, such as the possibility of higher losses, higher

expenses, and higher taxes (Head & Horn, 1991).

Identify potential losses

Evaluate potential issues

Select the appropriate technique for

treating loss exposures.

1. Risk control

- Avoidance

- Loss control

2. Risk financing

- Retention

- Noninsurance transfer

- Commercial insurance

Implement and administer the

program.

Figure 4: Steps in the Risk Management Process Note: From Essentials of Risk Management by G. I. Head and S. Horn, 1991, Malvern, PA: Insurance Institute of America.

28

Noninsurance transfers are methods other than insurance by which pure risk and

its potential financial consequences are transferred to another party. Contracts, leases, and

hold-harmless agreements are some examples of noninsurance transfers. Among the

advantages are these: potential losses that are commercially insurable can be transferred,

noninsurance transfers are less expensive than typical insurance, and potential losses may

be shifted to another party who can exercise loss control. There can also be

disadvantages: the transfer may be disallowed because of flaws in the contract agreement,

the party to whom the potential loss is to be transferred may not be able to cover the loss,

and not all noninsurance transfers are recognized by insurance companies (Head & Horn,

1991).

Commercial insurance is also used in a risk management program. If the loss

exposures have a low probability of loss and the severity of loss is high, purchasing the

proper insurance is appropriate (Table 2). Commercial insurance also has advantages and

drawbacks. As advantages, the organization can continue to operate after a loss has

occurred; managers’ worries and fears are reduced, allowing them to perform better;

insurers can provide additional risk management services; and insurance premiums are

tax deductible. Among the drawbacks of using commercial insurance are these: premium

rates are often expensive and must be paid in advance, the investigation and negotiation

of insurance coverage is time-consuming, and purchasing insurance can lead to a false

sense of security for the organization (Head & Horn, 1991).

Head and Horn (1991) developed a matrix to aid in identifying the appropriate

method or methods for handling losses. The matrix is designed to classify the various loss

exposures according to frequency and severity. The first type of loss exposure is

characterized by both low frequency and low severity of loss. Retention is the best way to

deal with this type of loss because the loss is infrequent and does not cause financial

harm to the organization. Retention should also be used when the losses are predictable

and occur regularly. The second type of loss is more serious because of its frequency.

Loss control should be used to reduce the frequency of the loss. The third type of

exposure is best handled through the purchase of insurance because even though the

frequency is low, severity of loss, such as a fatality, is very high. According to Head and

29

Horn (1991), the most serious type of exposure has both high frequency and high

severity. This exposure should be avoided at all costs. As required in the models of van

der Smissen (1990), Kavaler and Spiegel (1997), and Clement (1988), potential

frequency and severity of loss need to be carefully estimated.

The first step in implementing a risk management program is the development of

a policy statement (Head & Horn, 1991). This is important because it identifies the

objectives of the organization and the policy that will govern the treatment of loss

exposures. According to Head and Horn (1991), a risk management manual should be

created to train new employees and guide the whole organization. The Head and Horn

(1991) model has been commended by other risk management scholars. Notably,

Appenzeller (1998) used it as the model to follow when creating an effective risk

management program.

Table 2. Risk Management Matrix Note: From Essentials of Risk Management by G. L. Head and S. Horn, 1991, Malvern, PA: Insurance Institute of America.

Type

of loss

Loss

frequency

Loss

severity

Appropriate risk

management technique

1 Low Low Retention

2 High Low Loss control and retention

3 Low High Insurance

4 High High Avoidance

30

The Mulroney Model (1995)

According to Mulroney (1995), the goal of the risk management plan is to

decrease possible monetary losses while operating a facility. A successful risk manager

needs to recognize the foreseeable risks, and then assess, handle, and create an

operational program to deal with them.

A facility manager must be able to identify the various risks that may result in

losses during an event or activity. Mulroney (1995) believes that a well-trained staff plays

an important role in identifying risk. In the Mulroney model, the assessment of risk is

based on two criteria: frequency and amount of loss. There are 25 potential categories

into which a risk manager can classify any identified risk and this matrix provides a

consistent format for assessing problems (Table 3).

Once the risk has been identified, a facility manager must determine how to treat

each risk. Depending on the level of frequency and amount of loss of each risk, a

treatment could be to avoid the risk altogether, shift risk to a third party such as an

insurance company, or even handle the risk internally. The matrix designed by Mulroney

(1995) allows the risk manager to determine the severity of a possible risk and what

should be accomplished to handle it.

The final step in the Mulroney model is the development of standard operating

procedures (SOPs). These are detailed operating directions for personnel to carry out

under certain specified situations. Mulroney claims that by completing comprehensive

operating directions and implementing them thoroughly, facility managers would be

conducting themselves appropriately to ensure the safety of their patrons to the best of

their abilities (Table 4).

31

Table 3. The Risk Matrix Note: From Liability in Public Assembly Facilities by A. Mulrooney, 1995, Irving, TX: International Assembly of Auditorium Managers Resource Library.

Ver

y f

requen

t

Fre

qu

ent

Moder

ate

Infr

equen

t

Ver

y i

nfr

equen

t

Very high loss

High loss

Moderate loss

Low loss

Very low loss

Table 4. The Risk Matrix with Treatments of Risk Note: From Liability in Public Assembly Facilities by A. Mulroney, 1995, Irving, TX: International Assembly of Auditorium Managers Resource Library.

Ver

y f

requen

t

Fre

qu

ent

Moder

ate

Infr

equen

t

Ver

y i

nfr

equen

t

Very high loss Avoid Avoid Shift Shift Shift

High loss Avoid Avoid Shift Shift Shift

Moderate loss Shift Shift Shift Shift Keep and decrease

Low loss Keep and decrease

Keep and decrease

Keep and decrease

Keep and decrease

Keep and decrease

Very low Keep and decrease

Keep and decrease

Keep and decrease

Keep and decrease

Keep and decrease

32

The Tummala and Leung Model (1996)

According to Tummala and Leung (1996), “successful achievement of goals and

objectives depends on how risks and uncertainties involved with them are assessed and

optimal decisions are taken in containing and managing risk” (p. 53). The goals and

objectives are centered around the “safety, health, reliability, on time and within budget,

and the environmental issues as they impact the customers, employees, shareholders, and

the people at-large, as well as the business’s internal operations performance” (p. 54).

This model was created for public utility corporations including transportation and

electric power generation and distribution companies. Disasters such as severe rains,

tornados, and typhoons often result in not only the interruption of services to customers

but also safety and health concerns for people. Tummala and Leung (1996) have

proposed a comprehensive and systematic approach consisting of five core elements: risk

or hazard identification, system hazard analysis, ranking of hazards, development of

action plans, and risk control and monitoring.

As shown in Figure 5, the Tummala and Leung (1996) risk management approach

begins with the identification of all potential risk factors associated with a given project

and specification of the corresponding consequences and their severity. Risk or hazard

identification specifies all the potential accidents that may occur; this allows managers to

implement proactive maintenance in order to reduce the number of accidents that might

happen (Tummala & Leung, 1996).

The second step in the process is system hazard analysis. All possible

consequences of all identified hazards are considered based on the severity of each

hazard. The severity is assessed in terms of four categories:

1. Catastrophic: Incidents that result in death, system loss, or severe environmental

damage.

2. Critical: Severe injury, severe occupational illness, or major system or

environmental damage.

33

3. Marginal: Minor injury, minor occupational illness, minor system damage, or

environmental damage.

4. Negligible: Less than minor injury, occupational illness, or less than minor system

or environmental damage (Tummala & Leung, 1996).

Ranking hazards is the third step in the process. Hazards are ranked based on a

matrix with two dimensions: qualitative and quantitative. The matrix has the following

five categories:

1. Frequency: (Level A) likely to occur

2. Probable: (Level B) will occur sometimes

3. Occasionally: (Level C) likely to occur sometime in the lifetime

4. Remote: (Level D) unlikely but possible

5. Improbable: (Level E) so unlikely it can be assumed that occurrence will not be

experienced.

Hazards with a priority of “A” need immediate attention, followed by priority

“B,” as both seriously affect the safety and consistency of the organization’s objectives.

To handle these situations a proper course of action must be implemented. Some of the

action plans may only deal with design proposals that will improve safety of situation.

The fourth phase is to evaluate all the action plans created (Tummala & Leung, 1996).

The evaluation process is important because resources are limited in many organizations

and being able to prioritize based on the matrix of ranking hazards will allow managers to

allocate the necessary resources efficiently to deal with potential situations. The final

phase in the Tummala and Leung model is risk control and monitoring. This is a very

important step because continuously reviewing the process will lead to corrective actions

and accomplishment of the organization’s goals and objectives.

34

Corporate

Business

Plan

Project

Mission,

Aim and

Objectives

DRIVER Risk

Identification

Risk

Measurement

Risk

Assessment

Risk

Evaluation

Risk

Control and

Monitoring

Risk

Management

Process

Figure 5. Tummala and Leung Risk Management Model Note: From “A Risk Management Model to Assess Safety and Reliability Risks” by V. M. Tummala and Y. H. Leung, 1996, Journal of International Quality, 13(8), 6.

The Kavaler and Spiegel Model (1997)

According to Kavaler and Spiegel (1997), risk identification involves collecting

information about current and past occurrences and other events that could bring potential

loss to the organization (Figure 6). The next step is to identify exposures to accidental

losses (e.g., no protective screening behind home plate) that could interfere with an

organization’s basic objectives. The areas of risk that need to be considered may range

from antitrust violations to general liability for slips and falls. It is crucial that risk

identification is not a once-a-year static analysis. Continuous identification of possible

liability risks is needed to ensure that the organization is taking the necessary steps to

protect its assets. An information system needs to be established, both formal and

35

informal, to gather needed information. There must be active interaction between

employees at all levels and administrators/supervisors. External professionals should be

consulted as appropriate; these could include legal counsel, insurance brokers,

physicians, and emergency care services. It is important that the systematic procedure be

established to assure total assessment in order to avoid unexpected losses.

Risk analysis entails the evaluation of past occurrences and current exposure to

eliminate or reduce the impact of risk on the organization or facility. Measuring or

evaluating the extent of the risk or loss exposure is divided into four dimensions:

severity, frequency, predictability, and probability of the loss potential. The dimensions

of severity and frequency can be estimated quite easily by all entities, large and small,

private and public, and are important when personnel are looking realistically at risk

potentials. The degrees of severity are as follows: vital, significant, and insignificant.

Losses that would be catastrophic in nature, such as bankruptcy, would be considered

vital. Significant losses occur when services must be decreased or when finances must be

relocated from one area to another to deal with a particular event. Severity also might be

thought of as seriousness of an injury, which then translates into potential dollar liability.

A high degree of injury is a fatal accident such as a spectator falling out of the stands and

perishing or sustaining severe brain damage. The other two descriptions - medium and

low severity - can result in a disabling injury (loss of body function) or temporary

disability (broken leg) from participating in a sporting activity.

Frequency is very basic but significant in risk analysis. How often does a

particular situation occur? Injuries in football and hockey are frequent based on history

and thus necessary actions are needed to handle the many different situations. Frequency

may be low in a certain sport but have the potential for serious injury. The next

dimensions are predictability and probability.

An effective risk manager/organization must be able to recognize potentially

dangerous situations relevant to that particular sporting activity. Nearly every sport has a

history of incidents that have resulted in lawsuits, injury, and/or some loss to the

organization. Risk managers must research incidents that have occurred so they can avoid

similar situations in the future. Liability and responsibility increase when the risk

36

manager or organization fails to remedy a known hazard. Actions such as the

development of an emergency plan to handle safety incidents can play an important role

in establishing reasonable care and reducing potential damages. This analysis provides

the risk manager with the information necessary to create the proper alternative risk

management techniques for dealing with these exposures.

Risk control and/or treatment are the organization’s responses to the critical areas

of risk (unacceptable risks) that have been discovered through identification and analysis.

This is the most common function associated with risk management. For critical risks, the

only option is elimination by either discontinuance or avoidance. Discontinuance is used

when the function/service/activity is deemed to be “too great a risk” even after the

application of all practical means of risk mitigation, and the activity is terminated.

Risk Stratification

Risk Analysis

Risk Control/Treatment

Risk Financing

Risk Management Process

Figure 6. The Kavaler and Spiegel Risk Management Model Note: From Risk Management in Health Care Institutions: A Strategic Approach by F. Kavaler and A. D. Spiegel, 1997, Sudbury, MA: Jones and Bartlett.

37

Avoidance, on the other hand, involves identifying the risk before the situation occurs,

with the risk manager taking the appropriate actions to make the risk acceptable. This risk

mitigation may be achieved by influencing the frequency, probability, or severity

(potential loss) dimension of a critical risk. It is vital to protect the organization from

major losses, and management decisions will dictate the severity of future losses. After

these programs are implemented, they have to be evaluated regularly to ensure that the

risk management program is truly creating a safe environment.

The Fried Model (1999)

Another risk management model, created by Fried (1999), advocates a

combination of ethics and risk management practices. His model is composed of the

“front headlines test” and “ECT” approach.

The “front headlines test” is a process by which an individual can identify

potential legal concerns and create effective procedures or strategies to reduce or

eliminate risks that otherwise could result in the sensational headlines that sell

newspapers. This test is similar to an older ethical maxim called “The TV Test.”

According to Parkhouse (1996), “The TV Test” is whether a person “acts in such a way

that the actions could be defended comfortably in front of a national audience.” Fried

(1996) believes that everyone should examine his or her actions prior to undertaking any

activity to determine whether a news reporter would view it as front-page material. The

important factor is to protect the organization’s image (Fried, 1999).

Fried (1999) sees the ECT approach as a risk management tool that allows one to

conceptualize the entire risk management process. It uses these steps:

1. Deflect liability from others. Liability should be transferred from risk managers to someone else through contracts, waivers, releases, and indemnity clauses.

2. Reflect on your risk management objectives. Risk management objectives should be reviewed after the liability has been deflected. This step involves creating risk management manuals, educational material, and safety conferences.

3. Inspect your program and facilities. The inspection process should be created and implemented so potential dangers can be detected.

38

4. Reflect on what has been seen. Once the area or event has been evaluated and all potential areas or situations have been seen, one must reflect and write down observations. Details such as the time date and what was done should be part of information included.

5. Correct the hazard. Make sure that suitable action is taken to remove the hazard or provide protection from the hazard.

6. Re-inspect the hazards. It is important after the problem has been corrected that a follow-up is conducted to make sure that the problem is corrected and not worsened.

7. Photograph the facility. The last step is photographing the facility before and after the event. The photograph can provide important information if and when there is a claim by the plaintiff that you did or failed to do something to the facility (Fried, 1999).

The Bandyopadhyay, Mykytyn, and Mykytyn Model (1999)

Business organizations annually invest hundreds of billions of dollars in

information technology (Baura, Kribel, & Mukhopadhyay, 1995). The spending in

information technology accounts for one-third of all expenditures and is the largest single

item in the capital-spending budget of USA corporations (Schnitt, 1993). Therefore,

information technology risk management is one of the most important issues facing

executives of information technology systems today (Bandyopadhyay et al., 1999).

The object of risk management is to protect information technology assets such as

data, hardware, software, personnel, and facilities from all external hazards (e.g., natural

disasters) and internal threats (e.g., sabotage) so costs of losses can be reduced

(Bandyopadhyay et al., 1999). The risk management framework these authors created

includes risk identification, risk analysis, risk-reducing measures, and risk monitoring.

Risk management for information technologies begins with the risk identification

process, which allows organizations to recognize and determine the potential impact of

internal and external threats to the information technology environment. According to

Bandyopadhyay et al. (1999), the first step in identifying risks is to define the information

39

technology environment of the organization. As shown in Figure 7, the authors identified

three possible levels: application, organizational, and interorganizational.

1. Application level: Concentrates on the risks of technical or implementation failure of applications. Such risks may arise from internal or external forces. Some of these threats range from natural disasters and computer viruses to hackers. It is believed that natural disasters and employee accidental actions represent the greatest level of risk (p. 439).

2. Organizational level: The focus is on the impact of information technology throughout all functional areas of the organization rather than on any isolated area. Businesses are increasingly deploying information technologies at the organization level to gain competitive advantage over their competitors. If the organization cannot commit itself to continually invest in upgrading rapidly changing technology, it may become vulnerable to competitors with greater resources (p. 439).

3. Inter-organizational level: One of the most striking and powerful uses of information technology involves networks that surpass organizational boundaries. These are automated information systems that are shared by two or more organizations. This joint linkage has contributed to increase productivity, flexibility and competitiveness. When organizations come together, the risks often compound (p. 440).

After the information technology environment has been identified with its

associated risks, the related vulnerabilities of information technology assets need to be

determined. This provides the foundation on which risk management decisions are made.

Risk analysis can be carried out through a variety of methodologies. These

methodologies are categorized as quantitative, qualitative, or a combination of both. The

authors assert that the combination method is more effective and useful because of its

flexibility in considering the wide variety of assets, all possible threats, and

vulnerabilities (Bandyopadhyay et al., 1999, p. 441). Once risks are identified, the next

process is to reduce the risks. Risk reducing measures constitute the third phase of the

proposed framework. After the assets and different threats to which they are exposed are

identified, necessary steps need to be taken to protect these assets against all sources of

threats to the greatest extent possible. Some suggestions for reducing risks such as natural

disasters, data security, computer viruses, legal risks, and strategic risks for organizations

include these: password control, disaster recovery plan (written plan to operate during a

crisis), access codes, fingerprinting, palm printing, voice recognition, call back modems,

40

employee education, patent protection, hiring of expert consultants, and stringent audit

procedures.

The final process in the framework is to ensure that the components added to

handle the risks are maintained. Risk monitoring is an additional safeguard to protect the

information technology environment. It is important that active risk monitoring is

conducted and maintained to make certain that effective counter measures to control risks

are appropriately implemented. This process is used to determine whether the risk

management process that was implemented by the organization is actually reducing the

exposure to risks. Risk monitoring not only serves the purpose of evaluating performance

of risk reducing measures but as well serves as a constant audit function for the

organization (Bandyopadhyay et al., 1999).

Risk Identification Risk Analysis

Risk Monitoring Risk Reducing Measures

IT Risk Management Process

Application Level

Organizational Level

Interorganizational Level

Figure 7. The Bandyopadhyay, Mykytyn and Mykytyn Risk Management Model Note: From “A Framework for Integrated Risk Management in Information Technology,” by K. Bandyopadhyay., P. P. Mykytyn, and K. Mykytyn, 1999, Management Decision, 37(50), 444.

41

The Miccolis and Shah Model (2000)

The management of risk is undergoing crucial change within leading

organizations (Miccolis & Shah, 2000). Worldwide, organizations are moving away from

the “silo-by-silo” approach to manage risk more comprehensively and coherently

(Miccolis & Shah, 2000). In just the last few years, industry and government regulatory

bodies, as well as institutional investors, have turned to scrutinizing companies’ risk

management policies and procedures. Boards of directors are now being forced to review

and report on the efficiency and quality of the risk management processes of their

organization. Pressure to adopt Enterprise Risk Management (ERM) has increased due to

both internal forces (increasing executive personal liability) and external forces

(governance bodies and investors). ERM is considered the new and leading process to

reduce risk within an organization (Miccolis & Shah, 2000). There are three kinds of risk

environment that must be identified for an organization to “know themselves” before they

are able to handle the risks effectively and efficiently (Miccolis & Shah, 2000).

The three types of risk environment are as follows: unprotected, transitional, and

“Go Ahead.” Unprotected risk occurs within an organization when systems are not in

place, cultural attitudes are not supported, basic competencies are not strong, there is a

lack of capability and resources to start programs, and there is an overall lack of

preparation throughout the organization. Unprotected risks occur in an environment

where risk procedures and practices have simply been ignored. The next type of risk

environment is called transitional. This environment has issues such as historical

problems regarding accidents, moderate financial control, rapid change in the industry,

high pressure to produce, constrained resources, personnel stretched to their limits, and a

lot of “fire fighting” in how they handle situations. It is obvious in this environment that

risk has been identified but with all the changes taking place and the environment being

unstable, risk control is recognized but not thought of as a priority. Finally, “Go Ahead”

is the third type of risk environment in this model. The organization in this environment

has well-established systems, common processes, pockets of slackness, basic

42

competencies well established, and many areas of implementation. The challenge is the

operational, strategic, unconscious complacency with the feeling that the organization has

a solid handle on risks. It is vital that an organization identify which one of these

environments they are in before using ERM. Identifying the environment is recognized as

being the starting point of Enterprise Risk Management (Miccolis & Shah, 2000).

Enterprise Risk Management (ERM) is a straightforward process. An effective

ERM process is based on sound analytics (Miccolis & Shah, 2000). If organizations have

valid measurements, managing risk is effective and efficient and not only by chance. The

role of ERM is to help managers control the factors that influence risk so that they can

pursue strategic advantage. The key to this model is to identify and manage these factors

and know yourself. The objective of ERM is to enhance shareholder value and this is

achieved through these steps:

1. Improving capital efficiency

2. Providing an objective basis for allocating resources

3. Reducing expenditures on immaterial risks

4. Exploiting natural hedges and portfolio effects

5. Supporting informed decision-making

6. Identifying and exploiting areas of “risk-based advantage”

The framework for Enterprise Risk Management consists of four elements:

assessing risk, shaping risk, exploiting risk, and keeping ahead. Assessing risk focuses on

risk as a threat as well as an opportunity. The assessment of risk in this process includes

identification of the risks, prioritization, and classification of risk factors for the proper

“defensive response.” Viewing risk as an opportunity includes profiling risk-based

opportunities for the proper “offensive” treatment.

The second step is shaping risk. Shaping risk is the “defensive track” of the ERM

process, which includes risk quantification/modeling, mitigation, and financing. The

approach to risk shaping depends heavily on operations research methods such as applied

probability statistics, stochastic simulation, and portfolio optimization. Many

organizations have failed to implement this approach in its entirety (Miccolis & Shah,

43

2000). The risks are modeled as a probability distribution, and the correlation among the

risk sources is determined. These probability distributions are typically expressed by

different operational and financial measures. The second step links these disparate

distributions to a common financial measure (i.e. free cash flow) through a stochastic

financial model (Miccolis & Shah, 2000). The third step involves developing risk

remediation strategies to be evaluated using the stochastic financial model. The model

focuses on risk aversion and risk neutrality. When all assets are risky or when there is one

riskless asset the organization has to decide how they will handle the situation to ensure

their financial prosperity and limited losses. The different types of strategies create a

portfolio of risk management investment choices for the organization to choose from. In

the final step, the ERM budget is allocated optimally across these strategies using

portfolio optimization methods.

Exploiting risk and keeping ahead is considered the “offensive track” and

includes analysis, development, and execution of plans to exploit certain risks for

competitive advantage (Miccolis & Shah, 2000). As mentioned earlier, risk has two

faces: threat and opportunity. Often risk is viewed as a threat, but in fact, organizations

routinely pursue risk for the chance of increased reward. Companies create a competitive

advantage by identifying which risks the organization can pursue better than its peers

(Miccolis & Shah, 2000). There are two ways that this advantage can arise. The first

relates to the nature of the risk itself. Certain risks provide more of a risk to your

competition than to your own company because of their predictability and effect on

company financials. The second way is the organization’s ability to understand the risks

and to deal with them effectively. The nature of risk, the environment in which it

operates, and the organization itself change with time; maintaining an effective risk

management program is critical for success against dangerous and costly occurrences.

The situation requires continual monitoring and course corrections. ERM enhances the

drivers of share value: growth, return on capital, consistency of earnings, and quality of

management (Miccolis & Shah, 2000). ERM can identify and manage serious threats to

growth and return while identifying risks that represent opportunities to exploit for better

growth and return. The central goal of ERM is to achieve a consistency in earnings, and

44

investors are now defining management quality to include enterprise risk management

(Miccolis & Shah, 2000).

Summary of Models

The one common factor among all the models reviewed is to reduce financial

losses and to ensure safety for the organization itself, the people who are directly

involved, and those who may be affected by a specific incident. There is recognition that

the models must cover the future as well as the present.

The 11 models discussed were from many different parts of the business

environment; they had many similar themes as well as some unique applications or

approaches. All the models acknowledged the necessity for identifying the risk,

evaluating each risk and its potential resolution, and implementing control of the risk.

Some models ranked the risks and potential changes based on a level of severity or

probability, such as Clement (1988), van der Smissen (1990), Berlonghi (1990),

Mulroney (1995), Kavaler and Speigel (1997), Enterprise Risk Management (ERM),

Miccolis and Shah (2000), and the Fried Model (1999). Others such as Tummala and

Leung (1996), Miccolis and Shah (2000), and Bandyopadhyay et al. (1999), had different

perspectives on risks, how it is understood, and how it should be minimized. Figure 8

highlights all the models examined and their similarities and differences.

The models and the works of the mentioned authors are the theoretical foundation

for sport risk management. They are to sport risk management what Freud, Pascal, and

Piaget are to psychology. In light of the fact that this dissertation will be one of the first

in sport risk management a foundation was essential. Also, youth sports organizations can

learn from the processes of the many different risk management models the importance

of being proactive in the quest to assess, reduce and control risk for their participants,

volunteers and the organization as a whole.

45

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el

BM

M M

odel

ER

M M

odel

Identification √ √ √ √ √ √ √ √ √ √ √

Evaluation √ √ √ √ √ √ √ √ √ √ √

Selection √ √

Implementation √ √ √ √ √

Control √

Estimation √

Risk analysis √ √ √ √

Rank hazards √

Exploit risks √

Shaping risk √

Risk monitor √ √ √

Figure 8. Summary of Models A summary of the stages of each of the risk management models as discussed is shown.

46

Governance of Sport

Sport Organizations

Nonprofit sports organizations play a fundamental role in the personal and social

development of all those who participate. As Peter F. Drucker, author of Managing the

Nonprofit Organization explains, nonprofits do something very different from either

business or government: “Business supplies, either goods or services . . . a ‘nonprofit’

institution neither supplies goods or services nor controls” (Drucker, 1990, p. 79). Its

product is a changed human being. “The nonprofit institutions are human change agents”

(Mackin, 1998, p. 11).

A generation ago, nonprofit “charitable” organizations were considered secondary

to North American society. Today, many of those institutions are some of the most

important distinguishing features of North American democracy and capitalism.

According to Mackin (1998), half of society volunteers in the nonprofit sector - in

hospitals, crisis centers, parent-teacher associations, religious groups, and most of all in

sport associations.

Nonprofits have changed and grown more complex in response to an increasingly

complicated marketplace. Nonprofit organizations are beginning to behave like “for

profit” organizations, competing for limited resources whether these be funding,

volunteers, or participants. Today’s nonprofits share some of the goals of “for profits”

such as accountability and credibility, however, nonprofits have suffered a serious

disadvantage: a lack of educational programs and management designed specifically for

their marketplace (Mackin, 1998). A baseball organization in a small town cannot run its

organization like Ford Motor Company or the New York Yankees. Recreational baseball

organizations may not be able to manage their organization like “for profit”

organizations; however, they must face the challenge of prioritizing their activities for the

benefit of their participants. Unfortunately, it appears that a concerted effort to find the

47

funding, manpower, and the expertise to actively develop, implement, and maintain a

safety program for coaches and volunteers has not been a priority. This failure has led to

some of the liability issues that exist today. Effective safety training and education of

volunteers and employees, coupled with association liability insurance, can be an

excellent form of legal protection against a lawsuit. Organizations cannot eliminate

litigation but they can reduce their chances of losing. If organizations create an

environment for their volunteers that ensures proper safety instruction and

implementation, they will gain a better chance of obtaining and recruiting new volunteers

(Mueller et al., 2001).

Volunteerism

Volunteers today come from all economic groups, races, and communities. People

volunteer for many reasons. For some individuals, satisfying the need to “give something

back” is a key motivator (Clarke, 1999). Giving something back acknowledges that no

individual develops solely by his or her own efforts. A person develops and progresses

because others contributed in some way to enhancing that person’s development.

According to Clarke (1999), people who understand the value of others’ contributions to

their development feel an obligation to return the favor by assisting society through

volunteer activities. They feel that by volunteering their time and talents they can give

something back to society in a meaningful way. They benefit personally while

contributing to the welfare of a larger community or cause. Recruitment of volunteers in

sports organizations has always been informal. Often it is an nonsystematic process of

enticing parents to move from watching their children participate in a sport, to becoming

actively involved with the coaching or supervision of the activity. Clarke (1999)

mentioned a study by the Gallup organization that found 1 in 10 nonprofit organizations

had experienced the resignation of a volunteer because of liability concerns, and 1 in 6

volunteers reported withholding his or her services because of the fear of being exposed

to legal liability. This problem was believed to have a negative effect on the recruitment

48

of high-quality volunteers in nonprofit organizations. The liability concerns of volunteers

brought a coalition to advocate federal legislation to deal with this “crisis.”

The National Coalition for Volunteer Protection was organized in 1987 to

encourage legislation to protect volunteers from liability. Supporters for volunteer

protection have always been careful to emphasize that the perceptions of would-be

volunteers concerning their exposure to liability were as critical as the reality of the

situation. Most states handled this dilemma by passing volunteer protection statutes.

These statutes varied from one state to another and as a result nonprofit organizations

were unable to reassure individuals that they would not be exposed to liability if they

decided to volunteer. A federal statute was needed.

Representative John Porter (Republican - Illinois) first introduced the Volunteer

Protection Act in Congress in early 1987. The bill was assigned the number H.R. 911, a

number that evoked a sense of urgency. More than 10 years later, Congress finally

responded by passing, with an overwhelming majority of 390 to 35, the Volunteer

Protection Act. The Senate passed the bill by unanimous voice vote that same evening.

On June 18, 1997, President Bill Clinton signed the Volunteer Protection Act into law.

The signing of the bill ended a decade-long battle to protect from liability those

individuals who donate their time to nonprofit organizations. The overall purpose of the

act was to limit lawsuits against volunteers serving nonprofit public and private

organizations and governmental agencies.

In retrospect, the act may have created serious outcomes for both the volunteer

and the nonprofit organization. Volunteers and organizations did not fully understand the

Volunteer Protection Act, and today many have false perceptions of the act’s protection

(Runquist & Zyback, 1997). The Volunteer Protection Act alone cannot be the sole

safeguard for volunteers of sport organizations. Passage of the act created a false

assumption among coaches that they were totally immune from liability. Immunity for

volunteers under the Volunteer Protection Act, like most other immunity laws, exists only

in negligence and not in gross negligence or willful, wanton, and reckless misconduct

(Appenzeller, 1998; Clement 1998; Head & Horn, 1991).

49

Clement (1998) defined negligence as “doing something that a reasonable person

would not be expected to do or failing to do something that a reasonable person would be

expected to do” (p. 27). It is behavior that falls below the standards established by law.

Negligence by a volunteer is best described as carelessness. Negligence is identified by

different level of degrees: negligence; gross negligence; and willful, wanton, and reckless

misconduct (Appenzeller, 1998; Clement, 1998). According to Keeton, Dobbs, Keeton,

and Owen (2001), general negligence is “absence of that degree of care and vigilance

[when] persons . . . [fail] to exercise great care” (p. 211). Keeton et al. (1984) defined

gross negligence as “very great negligence . . . failure to exercise even that care that a

careless person would use” (p. 211-212). Under the Volunteer Protection Act (1997), a

volunteer must meet the following criteria to have a complete defense to an action for

liability. A volunteer is not liable for harm if all the following are met:

1. The volunteer was “acting within the scope of the volunteer’s responsibilities” in

the organization at the time of the act or omission.

2. The volunteer is properly licensed, certified, or authorized by the appropriate

authorities of the State for the activities taken, if such is “appropriate or required.”

3. The volunteer is not guilty of willful or criminal misconduct, gross negligence,

reckless misconduct, or “a conscious, flagrant indifference” to the rights or safety

of the individual harmed.

4. The harm was not caused by the operation of a vehicle, vessel, or aircraft for

which the state requires an operator’s license and insurance.

5. Exceptions. The action does not apply to an action brought by the organization

against the volunteer, nor does it limit the liability of the organization itself, to the

extent it would otherwise be responsible for the act of the volunteer (Runquist &

Zyback, 1997).

The act also allowed states to set criteria that in that state would not be protected

under the act. Runquist and Zyback (1997) defined a volunteer under the act as anyone

who:

50

1. Performs services (including officers, directors, trustees, and direct service

volunteers).

2. Works for a nonprofit organization or governmental entity.

3. Either: (a) receives no compensation (reasonable reimbursement is allowed), or

(b) does not receive anything of value in lieu of compensation, in excess of $500

per year.

Even when volunteers do not fully meet the criteria set out by the act, they may

still have some protection against awards such as noneconomic or punitive damages, as

long as they did not engage in specific types of prohibited conduct.

There are five specific situations in which the act does not protect the volunteer:

1. When the defendant has been convicted of a crime of violence or terrorism.

2. When a hate crime has been committed.

3. When the defendant has been convicted of a sexual offense.

4. When the defendant has violated a federal or state civil rights law.

5. When the defendant was under the influence of drugs or alcohol at the time of the

misconduct.

The act does not prohibit lawsuits against volunteers; at best it provides a credible

defense for the volunteer if he or she is sued (Runquist & Zyback, 1997). When an act is

passed by Congress it generally preempts the laws of any state. However, some states

have additional laws that provide further protection from liability or may remove the

protection of the act if the parties involved are citizens of that particular state. In other

words, the act applies to volunteers unless the state provides greater protection or if the

state nullifies the act for its citizens. The only way that volunteers would be totally

protected against lawsuits would be if all of the liability for the volunteer’s conduct

would be transferred to the organization. Most statutes are unclear in the language that

defines how much of a volunteer’s conduct is protected (Runquist & Zyback, 1997).

Many volunteers believe erroneously that they are protected under the Volunteer

Protection Act because society in general has told them they are, sport organizations tell

51

them they are, or because they are providing a service to the community. Biedzynski

(1999) agreed with Runquist and Zyback’s (1997) stance that the Volunteer Protection

Act is “defective” and does not provide sufficient protection for volunteers. The major

flaw is that the legislation does not protect volunteers from the time, expense, and

aggravation of defending themselves in a lawsuit, even if the act would ultimately be

found to bar judgment.

Summary

Baseball is the second most popular team sport after basketball in North America,

with roughly 30 million children and adolescents participating in “America’s National

Pastime.” Based on statistics from various medical and sports information sources,

baseball participants incur an estimated 3 million injuries each year. Over the last three

years (1998-2000), approximately 130,000 injuries have been reported among young (up

to 17 years of age) baseball participants. One-third of these injuries could possibly have

been prevented with the proper safety mechanisms in place.

In 1999, youth athletes between the ages of 5 and 14 sustained 40 % of sports-

related injuries for all sports (Consumer Product Safety, Fall 2000, 3). According to

Washington et al. (2001), 20 % of those injuries were considered serious. Baseball had

the highest fatality rate among sports for children from 5 to 14, with three to four children

dying from baseball injuries each year (National Safe Kids Campaign, 2001). Baseball

was one of the most popular athletic activities in the USA, with an estimated 4.8 million

children 5 to 14 years of age participating annually in organized and recreational baseball

and softball (Washington et al., 2001). Baseball’s popularity in the USA and the

numerous injuries that young players have incurred has been the subject of inquiry by a

number of organizations (Pasternack, Veenema, & Callahan, 1996). In a report by the

Baseball and Softball Council (1998), baseball was second only to basketball in team

sport participation.

52

Cantu and Mueller (1999) studied baseball injuries at the high school level from

1983 to 1997. They found that high school baseball caused 28 direct fatalities or

catastrophic injuries. Most occurred during headfirst sliding or when a player was struck

by a thrown or batted ball. Mueller et al. (2001) concluded that the greatest number of

injuries associated with baseball occurred during base running, with infielders having the

most frequent casualties.

The USA Consumer Product Safety Commission (Fall, 1986, 3) found that from

1973 to1980, there were 40 baseball/softball-related deaths reported for children between

the ages of 5 and 14. Of these deaths, 21 resulted from head and neck injuries, 17 from

non-penetrating impact to the chest, and 2 from other undisclosed causes - an average of

5 per year. From 1986 to 1990, 16 baseball/softball-related deaths were recorded

(Mueller et al., 2001). Kyle (1996), using CPSC data, found that between 1973 and 1995

there were 88 baseball related deaths in children of 5 to14 years, an average of 4 per year.

According to Cantu and Mueller (1999), the number of deaths in baseball was more than

that of any other sport.

Risser et al. (1994) highlighted the recommendations made by the American

Academy of Pediatrics and the same recommendations were stated in Washington et al.

(2001) when they investigated baseball injuries to children from 5 to 14 years old. They

further brought emphasis to the coaches’ role in decreasing the chance of injuries for

athletes. Coaches need to be able to teach the fundamental skills of the sport and they

should not be appointed if they do not have the training and experience needed to teach

the skills of the sport and to properly train athletes (Risser et al., 1994).

Risk management is one tool that a sport organization can use to identify critical

safety concerns and develop proactive approaches to mitigate unacceptable risks. The use

of this process provides a means to allocate funds and resources to avoid preventable

catastrophic injuries and/or losses. Through the use of risk management, the organization

reduces its potential liability and that of its volunteers by establishing a documented

reasonable standard of care for its participants and volunteers.

Organizations often claim that the cost, time, and effort to implement a risk

management system are not available. They claim that trying to implement such a system

53

will demand too much time from their volunteers and will lead to a drastic reduction in

those willing to provide their assistance to the sports organization. Effective safety

training and education of volunteers and employees, coupled with association liability

insurance, can be an excellent combination of legal protection against a lawsuit.

Organizations cannot eliminate litigation but they can reduce their chances of losing. If

organizations create an environment for their volunteers that would ensure proper safety

instruction and implementation, they would gain a better chance of obtaining and

recruiting new volunteers (Mueller et al., 2001).

In summary, the proper application of risk management will allow the volunteers

to focus on the more important concerns while at the same time reducing the time lost

handling injuries and making the sports experience more beneficial to all participants. It

may allow the organization to regain the confidence of hesitant volunteers by eliminating

their fear of personal financial loss. Finally, once established, the risk management

process is not difficult to administer and update with the latest information.

54

CHAPTER 3

METHODS

Overview

This chapter outlines the procedures that the researcher used to analyze the risk

management practices of youth baseball/softball coaches. The methodology is presented

in the following five sections: (a) Research Design; (b) Study Sample; (c) Pilot Study (d)

Instrumentation; (e) Data Collection Procedures; and (f) Data Analysis Procedures.

Research Design

Surveys have been used in sports to investigate a wide variety of topics in the

areas of marketing, finance, gender issues, behaviors, and attitudes (Hunt, Bristol, &

Bashaw, 1999; Lazarus & Shanahan, 1995; Mason, 1999; Nicholls, Roslow & Dublish,

1999; Bristow & Sebastian, 2001; Kelinske, Mayer, & Chen, 2001; Theodorakis,

Kambitisis & Laios, 2001). Mail surveys were chosen because they were the best method

to reach the population that was investigated.

According to Salant and Dillman (1994), using mail surveys minimizes the

sampling error at an affordable cost. Also, mail surveys provide a sense of privacy for the

survey taker compared to other methods, such as face-to-face interviews. The final

advantage of mail surveys is that they decrease the chance of bias from the survey taker.

A mail survey has some challenges as well. When surveys are mailed, some of the

55

address information received may be incomplete and some people may choose not to

respond (Salant & Dillman, 1994). The assistance from the national and local

organizations in the distribution and collection of the surveys should decrease the chance

of these problems occurring. According to Salant and Dillman (1994) and Dillman

(2000), the biggest problem with a survey is the way it is structured. Each question must

avoid confusing the reader, violating private personal information, leading the participant

or being discriminatory. According to Groves, Cialdini and Couper (1992) and

Yammarino, Skinner and Childers (1991), factors need to be considered such as the mood

of the participant, the value of the study, deference and the person handing the survey out

to avoid faulty results. All these could lead to a survey not being completed objectively.

Non response bias is another challenge when a survey is used to conduct research.

Non response bias is the potential differences between those who completed and those

who failed to return the survey (King, Pealer & Bernard, 2001). The final area that

researchers must be tentative to is the sample population. The sample population must be

large enough, everyone attending must have an equal chance of being selected, and the

characteristics of the people selected must be similar to those who are not chosen for the

study (Salant & Dillman, 1994).

Study Sample

The study sample consisted of youth baseball/softball coaches located in four

geographic locations in two countries. Two geographic locations from each country,

Southern and Northeastern USA, and Central and Western Canada were used. There were

200 surveys (Appendix A) distributed in Southern (Tallahassee, Florida) and

Northeastern (Ithaca, New York) USA, 400 in Central (province of Ontario) and 225

Western (province of Alberta) Canada. The expected response rate for this study was 30

% (Salant & Dillman, 1994). The researcher collaborated with presidents of local, state,

provincial, and national organizations in each location in distributing the questionnaire to

youth baseball/softball coaches. The organizations selected were registered and governed

56

by Little League Baseball or Baseball Canada. Coaches selected for the study were

actively coaching baseball/softball players ages 5 to 17 under the chosen organizations.

The four locations were chosen based on the researcher’s professional

relationships within each area. The researcher was an active member in youth baseball

and softball organizations as an official and administrator in the four regions. The

researcher received tremendous support from the subjects in each of the regions. Another

reason these four regions were chosen were their demographic and geographic

differences. Each region had many youth baseball and softball organizations, league

schedules differed in length, climate was very different, both rural and urban leagues

were prevalent and the organizational structures of each region varied.

Pilot Study

Although surveys have been used to investigate a wide variety of topics in Sport

Management, few have been used to explore sport risk management; therefore, a

potential survey was created to be used in this study. The survey was created to measure

Little League and Baseball Canada coaches’ safety and risk management practices

pertaining to injuries that occur during participation. The survey was also intended to

assess the coaches’ perception of governing organizations’ provisions for safety and

education. It incorporated questions from a variety of baseball websites and journal

articles that shed light on the “risks” and “dangers” of participating in youth baseball as a

player and coach. Content validity or the degree to which the survey was consistent with

the practices it was suppose to measure (Popham, 1993) was tested through a detailed

questionnaire. They were: (1) coaches’ attitudes towards added safety procedures and

certification; (2) personal safety procedures/actions taken by the coach; (3) safety

concerns regarding playing conditions of the baseball field; (4) sensitivity of the coaches

and organization to safety issues related to condition and wearing of proper sports

equipment; and (5) demographic information about the coaches. Only minor changes

were made in the above survey.

57

The experts selected for the validation of the survey were from the areas of risk

management, survey development, law, and baseball. Selection of the experts was based

on their expertise in the subject areas (Rea & Parker, 1997). Three of the experts held

PhDs in the related fields, two had extensive coaching experience, and two had been

baseball instructors and administrators for over 20 years. A mail-back survey and

questionnaire was sent to the six experts. They were asked to fill out the survey and to

rate each sentence using a 5-point Likert scale (1-Very Good, 2-Good, 3-Neutral, 4-Poor,

5-Very Poor). The respondents were asked to give additional suggestions on the quality

of each question, comments for improvement, and comments regarding the survey

overall. After 14 days, a phone call was made and an email sent to all non-respondents.

All six experts responded to the survey.

Four of the reviewers rated the overall survey as “1” or very good, and the other

two reviewers rated the survey as “2” or good. The majority of the reviewers rated the

survey as 1 (Very Good) on a 1-5 point Likert scale.

After the survey recommendations by the experts were integrated into the revised

survey, it was electronically mailed back to the six experts for further review using the

original 5-point Likert scale. All six experts returned the electronic survey. All six

reviewers rated the overall survey as “1” or very good. The survey that was used in this

study can be seen in Appendix A.

Instrumentation

The survey was broken down into eight constructs for analysis. The eight

constructs collectively formed the overall safety component of the research. Each

construct was developed using the following questions from the survey (see Table 5).

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Table 5. The Eight Constructs for Survey Analysis Each construct was composed of two or more survey questions as shown.

CATEGORY SURVEY QUESTIONS

Warmup 17, 18, 19, 37

Cooldown 20, 21

Safety 33, 35

Water 22, 23, 24

Injury 12, 13, 14, 15

Field 25, 26, 27, 29

Preseason 10, 11

Equipment 16, 28, 30, 31, 32, 34, 36

Data Collection Procedures

According to Dillman (2000) and Salant and Dillman (1994) there are four basic

procedures that involve personalized correspondence that that will result in very high

response rates. The procedures are as follows:

1. Prenotification letter: A personalized, advance notice letter is distributed

explaining to the participants that they have been selected for a survey and that

they will be receiving a questionnaire. According to Kent and Turner (2002), this

method is the most effective process by which to encourage coaches to respond to

a survey.

2. About one week later, a personalized cover letter with slightly more detail on the

survey, a questionnaire, and a stamped return envelope are sent to the test taker

59

(Appendix B). These findings are similar to the findings of Kent and Turner

(2002).

3. Four to eight days after the questionnaire is mailed, a follow-up postcard is sent,

thanking those who have responded and requesting a reply from those who have

not yet responded.

4. Three weeks after the original questionnaire is sent, a new questionnaire and

stamped return envelope are mailed to all the subjects that have not replied.

A modified version of the above was used by the researcher in collecting the data

for this study. Due to financial constraints; an advance notice letter was not sent to all

subjects. Each organization used their own logo envelope containing the survey to bring

notice to the subject that it was important and needed to be completed.

Data Analysis Procedures

Data for this study was analyzed using SPSS version 11.0. The data was analyzed

in two ways: (1) Frequencies and percentages of all variables were calculated; and (2) the

differences between previously identified quantitative sets of scores were computed using

ANOVA. According to Cohen (1977), Fraenkel and Wallen (1996), and Hair, Anderson,

Tatham and Black (1995), effect sizes between 0 and 0.3, 0.3 and 0.6, and 0.6 and greater

are termed small, moderate, and large respectively. Therefore, the effect size between the

comparison group’s scores should be 0.5 or higher, which is half of the standard

deviation of the comparison groups, to be considered meaningful. There were six

independent variables: (1) Willingness to increase safety practices (Questions 1-5); (2)

Safety information (Questions 6-9); (3) Age groups (Question D2); (4) Motivation

(Question D3); (5) Health Safety Certification (Question D4); and (6) The age of the

coach (Question D6). The three dependent variables used were: (1) Safety Preparation

(Questions 10-24); (2) Safety Measures (Questions 25-37); and (3) Safety Practices

(Questions 10-37).

60

Analysis of Research Questions

The researcher proposes to answer the following eight research questions in this

manner:

1. To what extent are baseball/softball coaches willing to improve safety

practices required by the organization in order to coach?

The first question was analyzed by grouping the data of the first five questions of

the survey, and obtaining the percentages and frequencies.

2. To what extent does the organization provide safety information for its

coaches?

The second question was analyzed by grouping questions 6 thru 9 of the survey

and obtaining the percentages and frequencies.

3. To what extent are coaches prepared to ensure the overall safety of their

players amongst the four regions?

The third question was analyzed by using the data collected from questions 10-24

of the survey. ANOVA will be used to identify the differences between the coaches of the

different regions regarding their preparation in providing safety to their players.

4. What safety measures are coaches implementing?

The fourth question was analyzed by using the data collected from questions 25-

37 of the survey. ANOVA will be used to identify the differences between coaches in the

different regions and their individual safety measures.

5. What is the relationship between player age groups and coaches’ safety

practices?

The fifth research question was analyzed by using data collected form

demographic question 2 (Age Groups) in the survey and questions 10-37 of the survey.

A MANOVA was conducted to determine whether the player age group influenced coach

safety practices when all dependent variables were combined. As well, two-way ANOVA

techniques were used to detect significant differences between player age groups, the

country in which the team is located, and the interaction between these two factors. Post

61

hoc tests were then conducted to identify the age groups and/or countries that were

significantly different from each other.

6. Will a particular motivation to coach baseball/softball influence a coach’s

safety practices?

The sixth question was analyzed by using the data collected from demographic

question 3 (Motivation) in the survey and questions (10-37) of the survey. A MANOVA

was conducted to determine whether the motivational factor influenced coach safety

practices when all dependent variables were combined. As well, two-way ANOVA

techniques were used to detect significant differences between coaches who selected and

did not select a particular motivational factor, the location of the team, and the interaction

between these two factors. Post hoc tests were then conducted to identify the motivational

factor and/or locations that were significantly different from each other. The following

eight dependent variables were examined independently for the ANOVA and post hoc

analyses; warm-up, equipment, preseason, field, injury, water, safety, and cooldown.

7. Will holding a current first aid and/or CPR certification influence a coach’s

safety practices?

The seventh question was analyzed by using the data collected from demographic

question 4 (Certification) in the survey and questions 10-37 of the survey. A MANOVA

was conducted to determine whether the safety certification influenced coach safety

practices when all dependent variables were combined. As well, two-way ANOVA

techniques were used to detect significant differences between coaches who held and did

not hold the particular safety certification, the location of the team, and the interaction

between these two factors. Post hoc tests were then conducted to identify the safety

certification and/or locations that were significantly different from each other. The

following eight dependent variables were examined independently for the ANOVA and

post hoc analyses; warm-up, equipment, preseason, field, injury, water, safety, and

cooldown.

62

8. What is the relationship between the ages of coaches and their safety

practices?

The eighth question was analyzed by using the data collected from demographic

question 6 in the survey and questions 10-37. A MANOVA was conducted to determine

whether a coach’s age influenced his/her safety practices when all dependent variables

were combined. As well, one-way ANOVA techniques were used to detect significant

differences between the four different coach age groups (less than 30 years, 30-39 years,

49-49 years, and 50 years and greater). Post hoc tests were then conducted to identify

which coach age groups were significantly different from each other. The following eight

dependent variables were examined independently for ANOVA and post hoc analyses;

warm-up, equipment, preseason, field, injury, water, safety, and cooldown.

9. What is the relationship between the number of years coaching

baseball/softball and a coach’s safety practices?

The final question was analyzed by using Linear Regression from demographic

question 1 in the survey and the 8 constructs (warm-up, preseason, field, injury

prevention, water safety, equipment and cooldown) created for the study.

63

CHAPTER 4

RESULTS

Introduction

In this chapter an attempt was made to determine whether various factors (the age

of the players, age of the coach, motivation to coach, willingness of the coach to improve

safety practices, organization’s dissemination of safety information, obtaining safety

certification and actions to prevent injury), that apply to youth baseball and softball

coaches affect the overall risk and safety of the players. This chapter details how each

question was measured through the use of descriptive and ANOVA techniques.

Results

The results of this investigation are presented as follows in addressing each of the

eight research questions.

1. The first section examines the use of descriptive statistics (percentages) in

explaining both overall data and the first two research questions (Question 1 and

Question 2).

2. The second section is an investigation into coaches’ preparation (Question 3) and

measures (Question 4) to ensure overall safety for their players using one-way

ANOVA techniques.

64

3. ANOVA techniques such as MANOVA and two-way ANOVA and post hoc

testing were utilized to determine the relationship between the age of the players

and the coaches’ safety practices (Question 5).

4. ANOVA techniques such as MANOVA and two-way ANOVA were used to

determine whether or not motivation (Question 6) or holding a current first aid or

CPR certification (Question 7) influenced the coaches’ safety practices.

5. The last inquiry (Question 8), utilizes one-way ANOVA to determine the

relationship between the coach’s age and his/her safety practices.

Descriptive Statistics

Northeastern (Ithaca, NY) and Southern (Tallahassee, FL) USA, and Central

(Ontario) and Western (Alberta) Canada were the geographic regions selected for the

study. The survey instrument was sent through posted mail. Two hundred surveys were

mailed to both regions in the United States and the response was 105 (52.5 %) from New

York and 114 (57 %) from Florida. Four hundred surveys were mailed to Ontario and 202

(50.5 %) were returned. Alberta had 110 (49 %) respondents out of the 225 surveys that

were mailed. Overall, there were 531 (51.8%) respondents out of the 1025 surveys that

were distributed. The number of respondents exceeded the 30 % expected rate for a

survey study (Salant & Dillman, 1994). There were a total of 43 questions on the survey

and less than 1.3 % of the questions were not answered. The success of the return rate can

be attributed to the direct support of baseball league executive leaders and their interest in

gaining a better understanding of risk and safety on their playing fields and within their

organizations.

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Research Question 1

The first research question dealt with the willingness of youth baseball/softball

coaches to improve their safety practices if required by the organization. The question

was devised by using the first five questions of the survey (see Tables 6-10). In question

one, 90.2 % of the coaches surveyed indicated that they would still coach if the

organization required them to improve their safety practices. The results of question two

revealed that 75.8 % of the coaches would continue to coach if they had to obtain first

aid/CPR certification by using their own personal funds. Out of the four locations,

Florida was the only location that had less than 70 % of coaches willing to coach if they

had to pay for first aid/CPR on their own (67.3 %). In question three, 81.4 % of the

coaches indicated that they would be willing to participate in an annual coaching and

safety awareness clinic between 8-16 hours in duration. The province of Ontario was the

only location that had less than 80 % of its coaches in agreement (78.6 %). The results of

question four indicated that three out of the four locations had less than 60 % of coaches

willing to use their personal funds to purchase a medical/first aid kit from the

organization. The coaches from the province of Alberta were the most willing to use

personal funds for this expense (63.8 %). For question five, in three of the four locations,

less than 50 % of the coaches were willing to use personal funds to replace used medical

supplies. Again, the Alberta coaches were the most willing to use personal funds for

purchasing replacement medical supplies (50.5 %) compared to the other three locations.

Research Question 2

The second research question was used to determine the extent of the safety

information that baseball/softball organizations provide to their coaches. The question

was devised by using questions 6-9 from the survey (see Tables 11-14). In question six,

only 33.5 % of the coaches surveyed indicated that they received a safety manual from

66

their organization at the beginning of the year. Florida baseball/softball organizations

distributed the most safety manuals of the four locations (47.3 %). The results in question

seven indicated that only 26.2 % of the coaches were provided with a written emergency

action plan (EAP). Alberta baseball/softball organizations provided EAPs the most often

(37.8 %), and New York baseball/softball organizations provided EAPs the least often

(17.5 %). The results for question eight indicated that only 19.0 % of coaches had

participated in a safety-training workshop that was provided by their organization, with

Florida having the highest percentage (27.4 %) compared to all other locations. The

results from question nine indicated that only 26.1 % of coaches were notified by their

organizations about other sources for obtaining additional safety material. Among the

four locations, Florida coaches were provided the most support in this area (38.1 %).

Table 6. Answers to Survey Question 1 Organized by Location Question 1: I would continue to coach if I had to obtain first aid/CPR certification (Personal Cost $30-$60).

Location Yes No Total

Count [#] 96 8 104

Percent [%] 92.3% 7.7% 100.0%

Count [#] 98 16 114

Percent [%] 86.0% 14.0% 100.0%

Count [#] 179 23 202

Percent [%] 88.6% 11.4% 100.0%

Count [#] 105 5 110

Percent [%] 95.5% 4.5% 100.0%

Count [#] 478 52 530

Percent [%] 90.2% 9.8% 100.0%

New York

Florida

Ontario

Alberta

Total

67

Table 7. Answers to Survey Question 2 Organized by Location Question 2: I would be willing to pay for the first aid/CPR certification out of my own personal funds (Personal Cost $30-$60).


Count [#] 83 22 105

Percent [%] 79.0% 21.0% 100.0%

Count [#] 76 37 113

Percent [%] 67.3% 32.7% 100.0%

Count [#] 148 54 202

Percent [%] 73.3% 26.7% 100.0%

Count [#] 94 15 109

Percent [%] 86.2% 13.8% 100.0%

Count [#] 401 128 529

Percent [%] 75.8% 24.2% 100.0%

Ontario

New York

Florida

Alberta

Total

Table 8. Answers to Survey Question 3 Organized by Location Question 3: I am willing to participate in an annual coaching and safety awareness clinic (8-16 hours in length).


Count [#] 83 19 102

Percent [%] 81.4% 18.6% 100.0%

Count [#] 92 21 113

Percent [%] 81.4% 18.6% 100.0%

Count [#] 158 43 201

Percent [%] 78.6% 21.4% 100.0%

Count [#] 95 15 110

Percent [%] 86.4% 13.6% 100.0%

Count [#] 428 98 526

Percent [%] 81.4% 18.6% 100.0%

New York

Florida

Ontario

Alberta

Total

68

Table 9. Answers to Survey Question 4 Organized by Location Question 4: I would continue to coach if I had to replace used medical supplies out of my own personal funds (Personal Cost $30-$50).


Count [#] 59 46 105

Percent [%] 56.2% 43.8% 100.0%

Count [#] 63 50 113

Percent [%] 55.8% 44.2% 100.0%

Count [#] 112 90 202

Percent [%] 55.4% 44.6% 100.0%

Count [#] 70 40 110

Percent [%] 63.6% 36.4% 100.0%

Count [#] 304 226 530

Percent [%] 57.4% 42.6% 100.0%

New York

Florida

Ontario

Alberta

Total

Table 10. Answers to Survey Question 5 Organized by Location Question 5: I would continue to coach if I had to replace used medical supplies out of my own personal funds (Personal Cost $20-$40).


Count [#] 49 56 105

Percent [%] 46.7% 53.3% 100.0%

Count [#] 49 64 113

Percent [%] 43.4% 56.6% 100.0%

Count [#] 90 112 202

Percent [%] 44.6% 55.4% 100.0%

Count [#] 55 54 109

Percent [%] 50.5% 49.5% 100.0%

Count [#] 243 286 529

Percent [%] 45.9% 54.1% 100.0%

New York

Florida

Ontario

Alberta

Total

69

Table 11. Answers to Survey Question 6 Organized by Location Question 6: I am provided with a safety manual from my youth baseball/softball organization at the start of every season.


Count [#] 30 67 97

Percent [%] 30.9% 69.1% 100.0%

Count [#] 53 59 112

Percent [%] 47.3% 52.7% 100.0%

Count [#] 60 139 199

Percent [%] 30.2% 69.8% 100.0%

Count [#] 30 79 109

Percent [%] 27.5% 72.5% 100.0%

Count [#] 173 344 517

Percent [%] 33.5% 66.5% 100.0%

New York

Florida

Ontario

Alberta

Total

Table 12. Answers to Survey Question 7 Organized by Location Question 7: I am provided with a written Emergency Action Plan to follow in case of serious injury from my youth baseball/softball organization.


Count [#] 17 80 97

Percent [%] 17.5% 82.5% 100.0%

Count [#] 42 69 111

Percent [%] 37.8% 62.2% 100.0%

Count [#] 51 149 200

Percent [%] 25.5% 74.5% 100.0%

Count [#] 25 83 108

Percent [%] 23.1% 76.9% 100.0%

Count [#] 135 381 516

Percent [%] 26.2% 73.8% 100.0%

New York

Florida

Ontario

Alberta

Total

70

Table 13. Answers to Survey Question 8 Organized by Location Question 8: I have participated in a safety training workshop provided by my youth baseball/softball organization.


Count [#] 16 86 102

Percent [%] 15.7% 84.3% 100.0%

Count [#] 31 82 113

Percent [%] 27.4% 72.6% 100.0%

Count [#] 36 165 201

Percent [%] 17.9% 82.1% 100.0%

Count [#] 17 92 109

Percent [%] 15.6% 84.4% 100.0%

Count [#] 100 425 525

Percent [%] 19.0% 81.0% 100.0%

New York

Florida

Ontario

Alberta

Total

Table 14. Answers to Survey Question 9 Organized by Location Question 9: I have been notified by my organization about official correspondence, websites or other internet communications where I can obtain additional safety material.


Count [#] 14 87 101

Percent [%] 13.9% 86.1% 100.0%

Count [#] 43 70 113

Percent [%] 38.1% 61.9% 100.0%

Count [#] 49 152 201

Percent [%] 24.4% 75.6% 100.0%

Count [#] 31 78 109

Percent [%] 28.4% 71.6% 100.0%

Count [#] 137 387 524

Percent [%] 26.1% 73.9% 100.0%Total

New York

Florida

Ontario

Alberta

71

Research Question 3

The results obtained from questions 10 through 24 of the survey were used to

determine the extent of coaches’ preparations to ensure the overall safety of their players

amongst the four regions. Differences between groups were analyzed using frequencies,

ANOVA techniques and t-tests. A one-way ANOVA was used to determine whether or

not geographic locations were significantly different from one another for the following 6

categories; warm-up, preseason, injury, water, safety, and cooldown. Post hoc tests were

then conducted to identify the locations that were significantly different from each other

(see Appendix C, Table 21). T-tests were also conducted to detect differences between

countries (Canada and USA) for each category (see Appendix C, Table 22). In order to

compare between countries, the data from Ontario and Alberta were combined to

represent Canada and the data from New York and Florida were combined to represent

the USA. Significance was determined at an alpha level of 0.05. The overall survey

results for each category can be found in Appendix C, Tables 16-20.

In the area of warm-up, 75.4 % of the coaches conducted a 15-minute warm-up

session before each game and practice (all of the time). As well, 60.9 % of the coaches

supervised these warm-up sessions (all of the time) and 63.4 % of the coaches organized

the exercises performed (all of the time). Finally, only 32.7 % of the coaches insisted that

experienced catchers warm up pitchers before a game or practice (all of the time). There

was a significant difference in warm-up between the locations, F (3, 527) = 2.947, p =

0.032. No significant differences between the individual locations were detected using

post hoc independent sample t-tests.

In the area of preseason preparation, the survey revealed that 27.8 % of the

coaches never asked their players to fill out a medical report form and 66.5 % admitted

that they had never asked their fellow coaches to fill one out. There were no significant

differences between the locations for preseason, F (3, 513) = 2.229, p = 0.084.

The survey revealed that coaches are not well prepared for dealing with injury.

Fully 43.3 % of coaches indicated that they never brought a medical book to the games or

72

practices. Furthermore, 34.5 % of coaches indicated that they never recorded injuries

when they occurred. Close to half of the coaches who traveled out of town with their

team (47.4 %), did not collect information relating to safety such as hospital location. The

survey also indicated that 75.1 % of coaches made sure the equipment was away from the

playing area (all of the time). Finally, only 53.8 % of coaches brought a first aid kit to a

game or practice (all of the time) and only 18.3 % most of the time.

In the area of injury, significant differences were detected between locations, F

(3, 518) = 3.777, p = 0.011. New York engaged in less activities to prevent injury

compared to both Florida (p = 0.008), and Alberta (p = 0.048). The effect size was

moderate between both New York and Florida (0.580), and New York and Alberta

(0.475).

For water, 59.4 % of coaches admitted that they provided water for each game

and practice (all of the time), and 22.5 % of coaches indicated that they brought water

most of the time. When it came to giving water breaks for the players, 70.6 % of coaches

gave breaks (all of the time), and 92.9 % of coaches never had used withholding water

breaks as a form of punishment. For the questions related to water, there was a significant

difference between the locations, F (3, 524) = 2.960, p = 0.032. Using post hoc testing,

Alberta was found to be doing more water practices compared to New York (p = 0.045).

Despite this, the effect size between the locations was small (0.239).

In the area of safety, 58.4 % of coaches indicated that they did not allow their

players to slide head-first (all of the time), and 16.5 % of coaches instructed sliding feet

first most of the time. Close to 12.0 % of coaches also revealed that they had not

instructed their players to slide feet first. The researcher found no difference pertaining to

safety among the four locations, F (3, 517) = 1.799, p = 0.146.

Survey questions associated with cooldown revealed that only 15.2 % of coaches

supervised cooldown activities after a game or practice (all of the time), and 13.2 % of

coaches conducted cooldown practices for 15 minutes (all of the time). There was a

significant difference between the locations for cooldown, F (3, 520) = 3.407, p = 0.017.

As determined from post hoc testing, Alberta implements significantly more cooldown

73

than Ontario (p = 0.012). The effect size was moderate between Alberta and Ontario

(0.492).

When the countries were compared, the only significant difference between them

was in the area of warm-up, t (529) = 2.819, p = 0.005, Ms for USA = 4.176 and Canada

= 4.363. Therefore, Canada was conducting significantly more warm-up procedures than

the USA (see Appendix C, Table 22).

Research Question 4

The purpose of question 4 was to investigate the safety measures being used by

coaches. The two dependant variables were equipment and field. As in the previous

question, differences between groups were analyzed using frequencies, ANOVA

techniques and t-tests. A one-way ANOVA was used to identify whether geographic

locations were significantly different from one another for the categories of equipment

and field. Post hoc tests were then conducted to identify the locations that were

significantly different from each other (see Appendix C, Table 23). T-tests were also

conducted to detect differences between countries (Canada and USA) for each category

(see Appendix C, Table 24). In order to compare between countries, the data from

Ontario and Alberta were combined to represent Canada and the data from New York and

Florida were combined to represent the USA. Significance was determined at an alpha

level of 0.05. The overall survey results for the areas of field and equipment can be found

in Appendix C, Tables 16-20.

The survey focused on equipment that catchers are required to wear such as shin

pads, chest protector and a mask. It was found that 61.7 % of coaches made sure that

equipment fit properly (all of the time), and 24.6 % some of the time. Other equipment

areas such as wearing a protective support and not wearing jewelry during participation

were being followed as well. Despite this, 75.2 % of coaches indicated that they never

required their players to wear mouth guards, and 44.2 % of coaches admitted that they

never encouraged or required their players who wear glasses to wear safety glasses

74

during participation. There was a significant difference between the locations for

equipment, F (3, 527) = 4.496, p = 0.004 (see Table 22). The results of post hoc testing

indicated that Florida was more effective in the area of equipment when compared to

New York (p = 0.005). The effect size was moderate between Florida and New York

(0.356).

In the area of field condition, 33.6 % of coaches indicated that they inspected the

field before every game or practice. As well, 43.8 % of coaches revealed that they

checked the weather before all games and practices, and 75.1 % of coaches made sure

that all equipment was away from the playing area at all times. With regard to field

conditions, there were no significant differences between the locations, F (3, 517) =

1.597, p = 0.189.

There were also no differences between Canada and the USA for both equipment,

t (529) = 0.123, p = 0.902, Ms for USA = 3.472 and Canada = 3.464, and field condition,

t (519) = 0.036, p = 0.972, Ms for USA = 4.173 and Canada = 4.171 (see Appendix C,

Table 24).

Research Question 5

For the fifth research question, a MANOVA was conducted to determine whether

the player age group influenced coach safety practices when all dependent variables were

combined. As well, two-way ANOVA techniques were used to detect significant

differences between player age groups, the country in which the team is located, and the

interaction between these two factors. Post hoc tests were then conducted to identify the

age groups and/or countries that were significantly different from each other. In order to

compare between countries, the data from Ontario and Alberta were combined to

represent Canada and the data from New York and Florida were combined to represent

the USA. The following eight dependent variables were examined independently in the

ANOVA and post hoc analyses; warm-up, equipment, preseason, field, injury, water

75

safety, safety, and cooldown. Significance was determined at an alpha level of 0.05. The

overall survey results for each category can be found in Appendix C, Tables 25-28.

The majority of the coaches surveyed were coaching the 9-11.5 player age group

(31.6 %). The rest of the coaches were coaching age groups 5-6.5 years (13.6 %), 7-8.5

years (19.1 %), 12-13.5 years (13.6 %), 14-15.5 years (13.4%) and 16-17.5 years (8.7%).

The Wilks’ Lambda indicated a statistically significant MANOVA for the locations, F

(24, 1367) = 2.373, p < 0.001, and the player age groups, F (40, 2056) = 2.461, p < 0.001.

Despite this, the Wilks’ Lambda indicated no significant MANOVA for the interaction

between player age group and location, F (120, 3366) = 1.093, p = 0.233.

In the area of warm-up, a significant difference was detected between different

player age groups, F (5, 524) = 2.988, p = 0.011. Post hoc analysis revealed that the 9-

11.5 year player age group was performing significantly more warm-up then the 5-6.5

year player age group (p = 0.004). The effect size was moderate between the 9-11.5 year

player age group and the 5-6.5 year player age groups (.364). Canada was found to

implement more warm-up than the USA, F (1, 528) = 8.967, p = 0.003, but the effect size

was small (0.184). In addition, the interaction between player age group and country was

not significant, F (5, 524) = 0.804, p = 0.547 (see Figure 9).

In the area of equipment, a significant difference was detected between different

player age groups, F (5, 524) = 4.152, p = 0.001. Post hoc analysis indicated significantly

less equipment checking was taking place for the 16-17.5 year player age group when

compared to the 7-8.5 year player age group (p = 0.035), the 9-11.5 year player age group

(p < 0.001), and the 12-13.5 year player age group (p = 0.016). The effect size was

substantial between the 16-17.5 year player age group and the 7-8.5 year player age

group (0.419), the 16-17.5 year player age group and the 9-11.5 year player age group

(0.551), and the 16-17.5 year player age group and the 12-13.5 year player age group

(0.483). No significant difference was detected between countries, F (1, 528) < 0.001, p =

0.983, nor with regards to the interaction between player age group and country, F (5,

524) = 1.084, p = 0.368 (see Figure 10).

Relating to preseason, no significant difference was detected between player age

groups, F (5, 510) = 1.498, p = 0.189, nor between countries, F (1, 514) = 2.411, p =

76

0.121. There was also no significant interaction between player age group and country, F

(5, 510) = 1.989, p = 0.079. However, as shown in Figure 11, there is a large difference

between countries for the 5-6.5 year player age group.

For field, no significant difference was detected between player age groups, F (5,

514) = 1.266, p = 0.277, nor between countries, F (1, 518) = 0.386, p = 0.535. There was,

however, a significant interaction between player age group and country, F (5, 514) =

2.451, p = 0.033. This difference was seen between the coaches living in USA coaching

the 12-13.5 year player age group and the coaches living in the USA coaching the 14-

15.5 player age group (see Figure 12).

In the area of injury, no significant difference was detected between different

player age groups, F (5, 515) = 0.716, p = 0.612, nor between countries, F (1, 519) =

0.854, p = 0.356. As well, no significant interaction was detected between player age

group and country, F (5, 515) = 0.314, p = 0.905. Despite these results, it was interesting

to observe that the 12-13.5 year player age group had the highest average injury survey

score (see Figure 13).

In the area of water safety, no significant difference was detected between

different player age groups, F (5, 521) = 0.987, p = 0.425, nor between countries, F (1,

525) = 0.036, p = 0.850. As well, no significant interaction was detected between player

age group and country, F (5, 521) = 0.580, p = 0.716 (see Figure 14).

Regarding safety, a significant difference was detected between player age

groups, F (5, 514) = 6.784, p < 0.001. Post hoc testing indicated that the 9-11.5 year

player age group performed significantly more safety than the 5-6.5 year player age

group (p < 0.001), the 14-15.5 year player age group (p = 0.008), and the 16-17.5 year

player age group (p < 0.001). The effect size was substantial between the 9-11.5 year

player age group and the 5-6.5 year player age group (0.491), the 9-11.5 year player age

group and the 14-15.5 year player age group (0.385), and the 9-11.5 year player age

group and the 16-17.5 year player age group (0.624). In addition, the 7-8.5 year player

age group performed significantly more safety than the 16-17.5 year player age group (p

= 0.013). The effect size was moderate between these two groups (0.466). On the other

hand, no significant difference was detected between countries, F (1, 518) = 0.511, p =

77

0.475; however, a significant interaction was detected between player age group and

country, F (5, 514) = 2.828, p = 0.016. This difference was seen between the coaches

living in USA coaching the 7-8.5 year player age group and the coaches living in the

Canada coaching the 16-17.5 player age group (see Figure 15).

In the area of cooldown, a significant difference was detected between player age

groups, F (5, 517) = 2.401, p = 0.036. Post hoc analysis revealed that the 5-6.5 year

player age group performed significantly less cooldown activities than the 9-11.5 year

player age group (p = 0.025), the 14-15.5 year player age group (p = 0.001), and the 16-

17.5 year player age group (p = 0.040). The effect size was substantial between the 5-6.5

year player age group and the 9-11.5 year player age group (0.596), the 5-6.5 year player

age group and the 14-15.5 year player age group (0.898), and the 5-6.5 year player age

group and the 16-17.5 year player age group (0.753). No significant difference was

detected between countries, F (1, 521) = 0.680, p = 0.410, nor with regard to the

interaction between player age group and country, F (5, 517) = 1.149, p = 0.333. There

was an overall trend towards increased cooldown activities and increasing player age (see

Figure 16).

78

Warm-up and Player Age

0.0000

1.0000

2.0000

3.0000

4.0000

5.0000

5-6.5 7-8.5 9-11.5 12-13.5 14-15.5 16-17.5

Player Age in Years

Esti

mate

d M

arg

inal

Mean

s

USA

CANADA

Figure 9. Average Warm-up Survey Scores for Various Player Age Groups The bold line represents Canada, and the thin line represents the USA.

Equipment and Player Age

0.0000

0.5000

1.0000

1.5000

2.0000

2.5000

3.0000

3.5000

4.0000

5-6.5 7-8.5 9-11.5 12-13.5 14-15.5 16-17.5

Player Age in Years

Esti

mate

d M

arg

inal

Mean

s

USA

CANADA

Figure 10. Average Equipment Survey Scores for Various Player Age Groups The bold line represents Canada, and the thin line represents the USA.

79

Preseason and Player Age

0.0000

0.5000

1.0000

1.5000

2.0000

2.5000

3.0000

3.5000

5-6.5 7-8.5 9-11.5 12-13.5 14-15.5 16-17.5

Player Age in Years

Esti

mate

d M

arg

inal

Mean

s

USA

CANADA

Figure 11. Average Preseason Survey Scores for Various Player Age Groups The bold line represents Canada, and the thin line represents the USA.

Field and Player Age

0.00000.50001.0000

1.50002.00002.50003.00003.5000

4.00004.50005.0000

5-6.5 7-8.5 9-11.5 12-13.5 14-15.5 16-17.5

Player Age in Years

Esti

mate

d M

arg

inal

Mean

s

USA

CANADA

Figure 12. Average Field Survey Scores for Various Player Age Groups The bold line represents Canada, and the thin line represents the USA.

80

Injury and Player Age

0.0000

0.5000

1.0000

1.5000

2.0000

2.5000

3.0000

3.5000

5-6.5 7-8.5 9-11.5 12-13.5 14-15.5 16-17.5

Player Age in Years

Esti

mate

d M

arg

inal

Mean

s

USA

CANADA

Figure 13. Average Injury Survey Scores for Various Player Age Groups The bold line represents Canada, and the thin line represents the USA.

Water and Player Age

0.0000

0.5000

1.0000

1.5000

2.0000

2.5000

3.0000

3.5000

4.0000

5-6.5 7-8.5 9-11.5 12-13.5 14-15.5 16-17.5

Player Age in Years

Esti

mate

d M

arg

inal

Mean

s

USA

CANADA

Figure 14. Average Water Survey Scores for Various Player Age Groups The bold line represents Canada, and the thin line represents the USA.

81

Safety and Player Age

0.0000

1.0000

2.0000

3.0000

4.0000

5.0000

5-6.5 7-8.5 9-11.5 12-13.5 14-15.5 16-17.5

Player Age in Years

Esti

mate

d M

arg

inal

Mean

s

USA

CANADA

Figure 15. Average Safety Survey Scores for Various Player Age Groups The bold line represents Canada, and the thin line represents the USA.

Cooldown and Player Age

0.0000

0.5000

1.0000

1.5000

2.0000

2.5000

3.0000

3.5000

5-6.5 7-8.5 9-11.5 12-13.5 14-15.5 16-17.5

Player Age in Years

Esti

mate

d M

arg

inal

Mean

s

USA

CANADA

Figure 16. Average Cooldown Survey Scores for Various Player Age Groups The bold line represents Canada, and the thin line represents the USA.

82

Research Question 6

The researcher investigated whether or not there were motivational factors that

influenced coaches’ safety practices. The following motivational factors were examined:

whether or not the coach was motivated to volunteer because a sibling or family member

participated on the team, whether or not the coach was motivated to volunteer because

he/she enjoyed coaching, and whether or not the coach was motivated to volunteer

because he/she wanted to give back to the community. A MANOVA was conducted to

determine whether the motivational factor influenced coach safety practices when all

dependent variables were combined. As well, two-way ANOVA techniques were used to

detect significant differences between coaches who selected and did not select the

particular motivational factor, the location of the team, and the interaction between these

two factors. Post hoc tests were then conducted to identify the motivational factor and/or

locations that were significantly different from each other. The following eight dependent

variables were examined independently for the ANOVA and post hoc analyses; warm-up,

equipment, preseason, field, injury, water safety, safety, and cooldown. Significance was

determined at an alpha level of 0.05. The overall survey results for each category can be

found in Appendix C, Tables 29-40.

Motivational Factor – Child/Relative

The first motivational factor was whether or not a sibling or family member

participated on the team for which the coach was volunteering. The Wilks’ Lambda

indicated a statistically significant MANOVA for the locations, F (24, 1410) = 2.686, p <

0.001, and the child/relative motivational factor, F (8, 486) = 7.241, p < 0.001. Despite

this, the Wilks’ Lambda indicated no significant MANOVA for the interaction between

player age group and the motivational factor, F (24, 1410) = 1.472, p = 0.066. The

overall survey results for each category can be found in Appendix C, Tables 29-32.

83

In the area of warm-up, a significant difference was detected between the

locations, F (3, 524) = 2.740, p = 0.043. Post hoc analysis was unable to identify which

locations were significantly different from each other. Despite this, no significant

difference was detected between having and not having a family member participating on

the team, F (1, 526) = 3.249, p = 0.072, nor with regard to the interaction between this

motivational factor and the location of the team, F (3, 524) = 1.248, p = 0.292. As shown

in Figure 17, New York and Alberta baseball/softball coaches performed more warm-up

when they were not motivated to volunteer because they had a family member

participating on the team.

In the area of equipment, a significant difference was detected between the

locations, F (3, 524) = 2.886, p = 0.035. Post hoc analysis revealed that Florida

performed more equipment checks than New York (p = 0.008). The effect size was

moderate between the two groups (0.345). Despite this, no significant difference was

detected between having and not having a family member participating on the team, F (1,

526) = 0.048, p = 0.826, nor with regard to the interaction between this motivational

factor and the location of the team, F (3, 524) = 0.934, p = 0.424 (see Figure 18).

In the area of preseason, no significant difference was detected between the

locations, F (3, 511) = 1.792, p = 0.148. A significant increase in preseason preparation

was detected for those coaches who did not have a family member participating on the

team, F (1, 513) = 13.429, p < 0.001. The effect size was moderate between the two

groups (0.446). This increase was most apparent for Florida and Alberta (see Figure 19).

No significant interaction was detected between this motivational factor and the location

of the team, F (3, 511) = 1.249, p = 0.291.

With regards to field, no significant difference was detected between the

locations, F (3, 514) = 0.551, p = 0.648, nor between having and not having a family

member participating on the team, F (1, 516) = 1.856, p = 0.174. In addition, no

significant interaction was detected between this motivational factor and the location of

the team, F (3, 514) = 0.998, p = 0.393 (see Figure 20).

For injury, a significant difference was detected between the locations, F (3, 515)

= 3.012, p = 0.030. Post hoc analysis identified that Florida performed significantly more

84

injury prevention than New York (p = 0.007). The effect size was substantial between the

two groups (0.589). A significant increase in the prevention of injuries was detected for

those coaches who did not have a family member participating on the team, F (1, 517) =

12.072, p = 0.001. The effect size was moderate between the two groups (0.463) and the

increase was evident for all locations (see Figure 21). However, no significant interaction

was detected between this motivational factor and the location of the team, F (3, 515) =

0.080, p = 0.971.

In the area of water safety, no significant difference was detected between the

locations, F (3, 521) = 1.949, p = 0.121, nor between having and not having a family

member participating on the team, F (1, 523) = 2.214, p = 0.137. As well, no significant

interaction was detected between this motivational factor and the location of the team, F

(3, 521) = 2.073, p = 0.103 (see Figure 22).

In the area of safety, no significant difference was detected between the locations,

F (3, 514) = 1.681, p = 0.170. Despite this, a significant increase in safety practices was

detected for those coaches who had a family member participating on the team, F (1,

516) = 12.686, p < 0.001, but the effect size was small (0.247). No significant interaction

was detected between this motivational factor and the location of the team, F (3, 514) =

1.895, p = 0.129 (see Figure 23).

With regard to cooldown, a significant difference was detected between the

locations, F (3, 512) = 6.814, p < 0.001. Post hoc analysis identified that those in Alberta

preformed significantly more cooldown activities than those in Ontario (p = 0.013). The

effect size was moderate between the two groups (0.483). As well, a significant increase

in cooldown practices was detected for those coaches who did not have a family member

participating on the team, F (1, 512) = 18.059, p < 0.001. The effect size was moderate

between the two groups (0.426), and the most substantial increase was found in Alberta

(see Figure 24). No significant interaction was detected between this motivational factor

and the location of the team, F (3, 512) = 2.567, p = 0.054.

85

Warm-up and Child/Relative

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5.0000

NEW YORK FLORIDA ONTARIO ALBERTA

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Figure 17. Average Warm-up Survey Scores for Coaches Who Have and Do Not Have a Child/Relative Participating on Their Team The grey bars represent those coaches who do not have a child/relative participating on their team. The black bars represent those coaches who have a child/relative participating on their team.

Equipment and Child/Relative

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Figure 18. Average Equipment Survey Scores for Coaches Who Have and Do Not Have a Child/Relative Participating on Their Team The grey bars represent those coaches who do not have a child/relative participating on their team. The black bars represent those coaches who have a child/relative participating on their team.

86

Preseason and Child/Relative

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YES

Figure 19. Average Preseason Survey Scores for Coaches Who Have and Do Not Have a Child/Relative Participating on Their Team The grey bars represent those coaches who do not have a child/relative participating on their team. The black bars represent those coaches who have a child/relative participating on their team.

Field and Child/Relative

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Location

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Figure 20. Average Field Survey Scores for Coaches Who Have and Do Not Have a Child/Relative Participating on Their Team The grey bars represent those coaches who do not have a child/relative participating on their team. The black bars represent those coaches who have a child/relative participating on their team.

87

Injury and Child/Relative

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Figure 21. Average Injury Survey Scores for Coaches Who Have and Do Not Have a Child/Relative Participating on Their Team The grey bars represent those coaches who do not have a child/relative participating on their team. The black bars represent those coaches who have a child/relative participating on their team.

Water and Child/Relative

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4.0000


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YES

Figure 22. Average Water Survey Scores for Coaches Who Have and Do Not Have a Child/Relative Participating on Their Team The grey bars represent those coaches who do not have a child/relative participating on their team. The black bars represent those coaches who have a child/relative participating on their team.

88

Safety and Child/Relative

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4.0000

5.0000


Location

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Figure 23. Average Safety Survey Scores for Coaches Who Have and Do Not Have a Child/Relative Participating on Their Team The grey bars represent those coaches who do not have a child/relative participating on their team. The black bars represent those coaches who have a child/relative participating on their team.

Cooldown and Child/Relative

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3.0000

3.5000

4.0000

4.5000


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Figure 24. Average Cooldown Survey Scores for Coaches Who Have and Do Not Have a Child/Relative Participating on Their Team The grey bars represent those coaches who do not have a child/relative participating on their team. The black bars represent those coaches who have a child/relative participating on their team.

89

Motivational Factor – Enjoyment

The second motivational factor was whether or not the coach was motivated to

volunteer because he/she enjoys coaching. The Wilks’ Lambda indicated a statistically

significant MANOVA for the locations, F (24, 1419) = 2.737, p < 0.001, the enjoyment

motivational factor, F (8, 489) = 3.085, p = 0.002, and the interaction between locations

and the motivational factor, F (24, 1419) = 1.628, p = 0.028. The overall survey results

for each category can be found in Appendix C, Tables 33-36.


locations, F (3, 528) = 3.260, p = 0.021. Post hoc testing was unable to identify the

locations that were significantly different from each other. A significant increase in

warm-up was detected for those coaches who were motivated to volunteer because he/she

enjoyed coaching, F (1, 530) = 17.309, p < 0.001; however, the effect size was small

(0.283). In addition, no significant interaction was detected between this motivational

factor and the location of the team, F (3, 528) = 0.628, p = 0.597 (see Figure 25).


locations, F (3, 528) = 5.883, p = 0.001. Post hoc analysis revealed that New York was

performing significantly less equipment checking than both Florida (p = 0.005), and

Alberta (p = 0.004). The effect size was moderate between New York and Florida

(0.356), but small between New York and Alberta (0.276). A significant increase in

checking equipment was also detected for those coaches who were motivated to volunteer

because he/she enjoyed coaching, F (1, 530) = 8.541, p = 0.004; however, the effect size

was small (0.272). As well, a significant interaction was detected between this

motivational factor and the location of the team, F (3, 528) = 3.424, p = 0.017. Florida

baseball/softball coaches who volunteered because they enjoyed coaching were different

from Ontario coaches who did not volunteer because they enjoyed coaching (see Figure

26).


locations, F (3, 514) = 2.505, p = 0.058, nor between being and not being motivated to

volunteer because he/she enjoyed coaching, F (1, 516) = 0.372, p = 0.542. In addition, no

90




locations, F (3, 518) = 1.844, p = 0.138. Despite this, a significant increase in checking

the field was detected for those coaches who were motivated to volunteer because he/she

enjoyed coaching, F (1, 520) = 7.813, p = 0.005; however, the effect size was small

(0.207). In addition, a significant interaction was detected between this motivational

factor and the location of the team, F (3, 518) = 2.797, p = 0.040. Florida

baseball/softball coaches who volunteered because they enjoyed coaching were different

from New York coaches who did not volunteer because they enjoyed coaching (see

Figure 28).


= 4.784, p = 0.003. Post hoc analysis revealed that coaches in New York were performing

significantly less injury prevention than those in both Florida (p = 0.008), and Alberta (p

= 0.045). The effect size was large between both New York and Florida (0.580), and New

York and Alberta (0.474). A significant increase in the prevention of injuries was

detected for those coaches who were motivated to volunteer because he/she enjoyed

coaching, F (1, 521) = 5.938, p = 0.015. The effect size was moderate between the two

groups (0.358). This increase was particularly evident for those in New York and Ontario

(see Figure 29). However, no significant interaction was detected between this

motivational factor and the location of the team, F (3, 519) = 2.494, p = 0.059.

In the area of water, a significant difference was detected between the locations, F

(3, 525) = 2.922, p = 0.034. Post hoc analysis revealed that those in New York showed

significantly less concern for water safety than those in Alberta (p = 0.042); however, the

effect size was small (0.239). A significant increase concerning water safety was detected

for those coaches who were motivated to volunteer because he/she enjoyed coaching, F

(1, 527) = 18.908, p < 0.001; however, the effect size was small (0.257). As well, no



91

In the area of safety, a significant difference was detected between the locations,

F (3, 518) = 2.711, p = 0.044. Post hoc testing was unable to identify the locations that

were significantly different from each other. No significant difference was detected

between being and not being motivated to volunteer because he/she enjoyed coaching, F

(1, 520) = 1.766, p = 0.182. However, a significant interaction was detected between this

motivational factor and the location of the team, F (3, 518) = 4.150, p = 0.006. Alberta

baseball/softball coaches who did not volunteer because they enjoyed coaching were

different from New York coaches who did not volunteer because they enjoyed coaching

(see Figure 31).


locations, F (3, 521) = 4.651, p = 0.003. Post hoc analysis revealed that coaches in

Ontario were performing significantly less cooldown than those in Alberta (p = 0.011).

The effect size was moderate between the two groups (0.492). A significant increase in

cooldown was detected for those coaches who were motivated to volunteer because

he/she enjoyed coaching, F (1, 523) = 4.526, p = 0.034. The effect size was moderate

between the two groups (0.342), and the difference was particularly true for coaches in

New York and Ontario. As well, a significant interaction was detected between this

motivational factor and the location of the team, F (3, 521) = 3.383, p = 0.018. Alberta

baseball/softball coaches who did not volunteer because they enjoyed coaching were

different from New York coaches who did not volunteer because they enjoyed coaching

(see Figure 32).

92

Warm-up and Enjoyment

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Figure 25. Average Warm-up Survey Scores for Coaches Who Were and Were Not Motivated to Volunteer Because They Enjoyed Coaching The grey bars represent those coaches who were not motivated to volunteer because they enjoyed coaching. The black bars represent those coaches who were motivated to volunteer because they enjoyed coaching.

Equipment and Enjoyment

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YES

Figure 26. Average Equipment Survey Scores for Coaches Who Were and Were Not Motivated to Volunteer Because They Enjoyed Coaching The grey bars represent those coaches who were not motivated to volunteer because they enjoyed coaching. The black bars represent those coaches who were motivated to volunteer because they enjoyed coaching.

93

Preseason and Enjoyment

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YES

Figure 27. Average Preseason Survey Scores for Coaches Who Were and Were Not Motivated to Volunteer Because They Enjoyed Coaching The grey bars represent those coaches who were not motivated to volunteer because they enjoyed coaching. The black bars represent those coaches who were motivated to volunteer because they enjoyed coaching.

Field and Enjoyment

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YES

Figure 28. Average Field Survey Scores for Coaches Who Were and Were Not Motivated to Volunteer Because They Enjoyed Coaching The grey bars represent those coaches who were not motivated to volunteer because they enjoyed coaching. The black bars represent those coaches who were motivated to volunteer because they enjoyed coaching.

94

Injury and Enjoyment

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YES

Figure 29. Average Injury Survey Scores for Coaches Who Were and Were Not Motivated to Volunteer Because They Enjoyed Coaching The grey bars represent those coaches who were not motivated to volunteer because they enjoyed coaching. The black bars represent those coaches who were motivated to volunteer because they enjoyed coaching.

Water and Enjoyment

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4.0000


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YES

Figure 30. Average Water Survey Scores for Coaches Who Were and Were Not Motivated to Volunteer Because They Enjoyed Coaching The grey bars represent those coaches who were not motivated to volunteer because they enjoyed coaching. The black bars represent those coaches who were motivated to volunteer because they enjoyed coaching.

95

Safety and Enjoyment

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YES

Figure 31. Average Safety Survey Scores for Coaches Who Were and Were Not Motivated to Volunteer Because They Enjoyed Coaching The grey bars represent those coaches who were not motivated to volunteer because they enjoyed coaching. The black bars represent those coaches who were motivated to volunteer because they enjoyed coaching.

Cooldown and Enjoyment

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Figure 32. Average Cooldown Survey Scores for Coaches Who Were and Were Not Motivated to Volunteer Because They Enjoyed Coaching The grey bars represent those coaches who were not motivated to volunteer because they enjoyed coaching. The black bars represent those coaches who were motivated to volunteer because they enjoyed coaching.

96

Motivational Factor – Community Giving

The third motivational factor was whether or not the coach was motivated to

volunteer because he/she wanted to give back to the community. The Wilks’ Lambda


0.001, and the community motivational factor, F (8, 488) = 3.494, p = 0.001. Despite

this, the Wilks’ Lambda indicated no significant MANOVA for the interaction between

motivational factor and location, F (24, 1416) = 1.338, p = 0.127. The overall survey





warm-up was detected for those coaches who were motivated to volunteer because he/she

wanted to give back to the community, F (1, 529) = 12.264, p = 0.001; however, the

effect size was small (0.208). No significant interaction was detected between this

motivational factor and the location of the team, F (3, 527) = 0.353, p = 0.787 (see Figure

33).


locations, F (3, 527) = 2.990, p = 0.031. Post hoc analysis revealed that those in New

York were performing significantly less equipment checking than those in Florida (p =

0.005). The effect size was moderate between the two groups (0.356). A significant

increase in equipment checking was detected for those coaches who were motivated to

volunteer because he/she wanted to give back to the community, F (1, 529) = 13.497, p <

0.001. The effect size was small between the two groups (0.301). No significant

interaction was detected between the motivational factor and the location of the team, F

(3, 527) = 2.005, p = 0.112 (see Figure 34).

In the area of preseason preparation, no significant difference was detected

between the locations, F (3, 513) = 2.273, p = 0.079. A significant increase in preseason

preparation was detected for those coaches who were motivated to volunteer because

he/she wanted to give back to the community, F (1, 515) = 9.794, p = 0.002. The effect

97

size was moderate between the two groups (0.417) and the increase was largest for the

Ontario respondents (see Figure 35). No significant interaction was detected between this



locations, F (3, 517) = 1.411, p = 0.239. A significant increase in field checking was

detected for those coaches who were motivated to volunteer because he/she wanted to

give back to the community, F (1, 519) = 12.789, p < 0.001; however, the effect size was

small (0.248). In addition, no significant interaction was detected between this


36.




= 0.048). The effect size was large between both New York and Florida (0.580), and

moderate between New York and Alberta (0.474). A significant increase in the

prevention of injuries was also detected for those coaches who were motivated to

volunteer because he/she wanted to give back to the community, F (1, 520) = 7.961, p =

0.005. The effect size was moderate between the two groups (0.348) and the increase was

most evident for the New York respondents and the Florida respondents (see Figure 37).

In addition, no significant interaction was detected between this motivational factor and

the location of the team, F (3, 518) = 0.325, p = 0.807.


locations, F (3, 524) = 2.505, p = 0.058. A significant increase in water safety was

detected for those coaches who were motivated to volunteer because he/she wanted to

give back to the community, F (1, 526) = 7.499, p = 0.006; however, the effect size was

small (0.151). In addition, no significant interaction was detected between this


38).


F (3, 517) = 0.995, p = 0.395, nor between being and not being motivated to volunteer

98

because he/she wanted to give back to the community, F (1, 519) = 2.259, p = 0.133.

Despite this, Ontario coaches’ survey scores for safety were notably higher when they

were motivated to volunteer because they wanted to give back to the community (Figure

39). As well, no significant interaction was detected between this motivational factor and

the location of the team, F (3, 517) = 1.922, p = 0.125.





cooldown activities was detected for coaches who were motivated to volunteer because

they wanted to give back to the community, F (1, 522) = 10.376, p = 0.001. The effect

size was moderate between the two groups (0.464), and was largest for those coaches in

Ontario and Alberta (see Figure 40). No significant interaction was detected between this


99

Warm-up and Community Giving

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Figure 33. Average Warm-up Survey Scores for Coaches Who Were and Were Not Motivated to Volunteer Because They Wanted to Give Back to the Community The grey bars represent those coaches who were not motivated to volunteer because they wanted to give back to the community. The black bars represent those coaches who were motivated to volunteer because they wanted to give back to the community.

Equipment and Community Giving

0.00000.50001.0000

1.50002.00002.50003.0000

3.50004.00004.5000


Location

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YES

Figure 34. Average Equipment Survey Scores for Coaches Who Were and Were Not Motivated to Volunteer Because They Wanted to Give Back to the Community The grey bars represent those coaches who were not motivated to volunteer because they wanted to give back to the community. The black bars represent those coaches who were motivated to volunteer because they wanted to give back to the community.

100

Preseason and Community Giving

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YES

Figure 35. Average Preseason Survey Scores for Coaches Who Were and Were Not Motivated to Volunteer Because They Wanted to Give Back to the Community The grey bars represent those coaches who were not motivated to volunteer because they wanted to give back to the community. The black bars represent those coaches who were motivated to volunteer because they wanted to give back to the community.

Field and Community Giving

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Figure 36. Average Field Survey Scores for Coaches Who Were and Were Not Motivated to Volunteer Because They Wanted to Give Back to the Community The grey bars represent those coaches who were not motivated to volunteer because they wanted to give back to the community. The black bars represent those coaches who were motivated to volunteer because they wanted to give back to the community.

101

Injury and Community Giving

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YES

Figure 37. Average Injury Survey Scores for Coaches Who Were and Were Not Motivated to Volunteer Because They Wanted to Give Back to the Community The grey bars represent those coaches who were not motivated to volunteer because they wanted to give back to the community. The black bars represent those coaches who were motivated to volunteer because they wanted to give back to the community.

Water and Community Giving

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4.0000


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YES

Figure 38. Average Water Survey Scores for Coaches Who Were and Were Not Motivated to Volunteer Because They Wanted to Give Back to the Community The grey bars represent those coaches who were not motivated to volunteer because they wanted to give back to the community. The black bars represent those coaches who were motivated to volunteer because they wanted to give back to the community.

102

Safety and Community Giving

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YES

Figure 39. Average Safety Survey Scores for Coaches Who Were and Were Not Motivated to Volunteer Because They Wanted to Give Back to the Community The grey bars represent those coaches who were not motivated to volunteer because they wanted to give back to the community. The black bars represent those coaches who were motivated to volunteer because they wanted to give back to the community.

Cooldown and Community Giving

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Location

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Figure 40. Average Cooldown Survey Scores for Coaches Who Were and Were Not Motivated to Volunteer Because They Wanted to Give Back to the Community The grey bars represent those coaches who were not motivated to volunteer because they wanted to give back to the community. The black bars represent those coaches who were motivated to volunteer because they wanted to give back to the community.

103

Research Question 7

The researcher investigated whether or not holding specific safety certifications

influenced coaches’ safety practices. First aid and CPR certifications were the specific

practices examined. A MANOVA was conducted to determine whether the safety

certification influenced coaches’ safety practices when all dependent variables were

combined. As well, two-way ANOVA techniques were used to detect significant

differences between coaches who held and did not hold the particular safety certification,

the location of the team, and the interaction between these two factors. Post hoc tests

were then conducted to identify the safety certification and/or locations that were

significantly different from each other. The following eight dependent variables were

examined independently for the ANOVA and post hoc analyses; warm-up, equipment,

preseason, field, injury, water safety, safety, and cooldown. Significance was determined

at an alpha level of 0.05. The overall survey results for each category can be found in

Appendix C, Tables 41-48.

Safety Factor – First Aid Certification

The first part of this research question examined whether or not coaches who held

a current first aid certification implemented more safety practices. The Wilks’ Lambda


0.001, first aid certification, F (8, 489) = 1.994, p = 0.045, and the interaction between

first aid certification and location, F (24, 1419) = 1.544, p = 0.045. The overall survey





warm-up was detected for those coaches who held a current first aid certification, F (1,

530) = 8.671, p = 0.003; however, the effect size was small (0.212). No significant

104

interaction was detected between holding first aid certification and the location of the

team, F (3, 528) = 1.176, p = 0.318 (see Figure 39).


locations, F (3, 528) = 4.439, p = 0.004. Post hoc analysis revealed that coaches in New

York were performing significantly less equipment checking than those in Florida (p =

0.005). The effect size was moderate between the two groups (0.356). No significant

difference was detected between coaches who were holding or not holding current first

aid certification, F (1, 530) = 1.624, p = 0.203. However, as shown in Figure 42, there

was a large difference between those coaches who held and did not hold current first aid

certification in Ontario. No significant interaction was detected between holding first aid

certification and the location of the team, F (3, 528) = 2.388, p = 0.068.


locations, F (3, 514) = 1.856, p = 0.136. A significant increase in preseason preparation

was detected for those coaches who held current first aid certification, F (1, 516) = 4.534,

p = 0.034. The effect size was small between the two groups (0.330) and was most

evident for Ontario (see Figure 43). No significant interaction was detected between

those holding first aid certification and the location of the team, F (3, 514) = 1.227, p =

0.299.


locations, F (3, 518) = 1.625, p = 0.182, nor between holding and not holding current first

aid certification, F (1, 520) = 2.231, p = 0.136. In addition, no significant interaction was

detected between those holding first aid certification and the location of the team, F (3,

518) = 1.097, p = 0.350 (see Figure 44).




= 0.046). The effect size was large between New York and Florida (0.580), and New

York and Alberta (0.474). A significant increase in the prevention of injuries was also

detected for those coaches who held current first aid certification, F (1, 521) = 9.457, p =

0.002; however the effect size was small (0.205). In addition, no significant interaction

105

was detected between the possession of first aid certification and the location of the team,

F (3, 519) = 0.991, p = 0.397 (see Figure 45).

In the area of water, a significant difference was detected between the locations, F

(3, 525) = 3.062, p = 0.028. Post hoc analysis revealed that coaches in New York were

significantly less concerned with water safety than those in Alberta (p = 0.041); however,

the effect size was small (0.239). A significant increase in water safety was detected for

those coaches who held current first aid certification, F (1, 527) = 7.104, p = 0.008;

however, the effect size was small (0.214). As well, a significant interaction was detected

between holding first aid certification and the location of the team, F (3, 525) = 3.036, p

= 0.029. Ontario baseball/softball coaches who held first aid certification were different

from New York coaches who held first aid certification (see Figure 46).


F (3, 518) = 1.829, p = 0.141, nor between holding and not holding current first aid

certification, F (1, 520) = 0.050, p = 0.823. As well, no significant interaction was

detected between holding first aid certification and the location of the team, F (3, 518) =

1.965, p = 0.118 (see Figure 47).

With regards to cooldown, a significant difference was detected between the

locations, F (3, 521) = 3.412, p = 0.017. Post hoc analysis revealed that Ontario

respondents were performing significantly less cooldown than those in Alberta (p =

0.012). The effect size was moderate between the two groups (0.492). A significant

increase in cooldown activities was detected for those coaches who held current first aid

certification, F (1, 523) = 8.160, p = 0.004. The effect size was small between the two

groups (0.388), and was most evident for Florida and Ontario (see Figure 48). No

significant interaction was detected between holding first aid certification and the

location of the team, F (3, 521) = 0.809, p = 0.489.

106

Warm-up and First Aid

0.0000

1.0000

2.0000

3.0000

4.0000

5.0000


Location

Es

tim

ate

d M

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ina

l M

ea

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NO

YES

Figure 41. Average Warm-up Survey Scores for Coaches Who Have and Do Not Have Current First Aid Certification The grey bars represent those coaches who do not have current first aid certification. The black bars represent those coaches who have current first aid certification.

Equipment and First Aid

0.0000

0.5000

1.0000

1.5000

2.0000

2.5000

3.0000

3.5000

4.0000


Location

Esti

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d M

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inal

Mean

s

NO

YES

Figure 42. Average Equipment Survey Scores for Coaches Who Have and Do Not Have Current First Aid Certification The grey bars represent those coaches who do not have current first aid certification. The black bars represent those coaches who have current first aid certification.

107

Preseason and First Aid

0.0000

0.5000

1.0000

1.5000

2.0000

2.5000

3.0000

3.5000


Location

Esti

mate

d M

arg

inal

Mean

sNO

YES

Figure 43. Average Preseason Survey Scores for Coaches Who Have and Do Not Have Current First Aid Certification The grey bars represent those coaches who do not have current first aid certification. The black bars represent those coaches who have current first aid certification.

Field and First Aid

0.0000

1.0000

2.0000

3.0000

4.0000

5.0000


Location

Es

tim

ate

d M

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ina

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ea

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NO

YES

Figure 44. Average Field Survey Scores for Coaches Who Have and Do Not Have Current First Aid Certification The grey bars represent those coaches who do not have current first aid certification. The black bars represent those coaches who have current first aid certification.

108

Injury and First Aid

0.0000

0.5000

1.0000

1.5000

2.0000

2.5000

3.0000

3.5000


Location

Es

tim

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d M

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ina

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NO

YES

Figure 45. Average Injury Survey Scores for Coaches Who Have and Do Not Have Current First Aid Certification The grey bars represent those coaches who do not have current first aid certification. The black bars represent those coaches who have current first aid certification.

Water and First Aid

0.0000

0.5000

1.0000

1.5000

2.0000

2.5000

3.0000

3.5000

4.0000


Location

Es

tim

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d M

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NO

YES

Figure 46. Average Water Survey Scores for Coaches Who Have and Do Not Have Current First Aid Certification The grey bars represent those coaches who do not have current first aid certification. The black bars represent those coaches who have current first aid certification.

109

Safety and First Aid

0.0000

1.0000

2.0000

3.0000

4.0000

5.0000


Location

Es

tim

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d M

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l M

ea

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NO

YES

Figure 47. Average Safety Survey Scores for Coaches Who Have and Do Not Have Current First Aid Certification The grey bars represent those coaches who do not have current first aid certification. The black bars represent those coaches who have current first aid certification.

Cooldown and First Aid

0.0000

0.5000

1.0000

1.5000

2.0000

2.5000

3.0000

3.5000


Location

Esti

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d M

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inal

Mean

s

NO

YES

Figure 48. Average Cooldown Survey Scores for Coaches Who Have and Do Not Have Current First Aid Certification The grey bars represent those coaches who do not have current first aid certification. The black bars represent those coaches who have current first aid certification.

110

Safety Factor – CPR Certification

The second part of this research question examined whether or not coaches who

held current CPR certification implemented more safety practices. The Wilks’ Lambda


0.001. Despite this, the Wilks’ Lambda indicated no significant MANOVA for CPR

certification, F (8, 489) = 1.906, p = 0.057, nor the interaction between CPR certification

and location, F (24, 1419) = 1.395, p = 0.097. The overall survey results for each

category can be found in Appendix C, Tables 45-48.




warm-up was detected for those coaches who held current CPR certification, F (1, 530) =

11.837, p = 0.001; however, the effect size was small (0.232). No significant interaction

was detected between holding CPR certification and the location of the team, F (3, 528) =

0.584, p = 0.626 (see Figure 49).


locations, F (3, 528) = 3.892, p = 0.009. Post hoc analysis revealed that New York

respondents were performing significantly less equipment checking than those in Florida

(p = 0.005). The effect size was small between the two groups (0.356). A significant

increase in equipment checking was detected for coaches who held current CPR

certification, F (1, 530) = 4.525, p = 0.034; however, the effect size was small (0.214).

No significant interaction was detected between holding CPR certification and the

location of the team, F (3, 528) = 2.022, p = 0.110 (see Figure 50).


locations, F (3, 514) = 2.428, p = 0.065, nor between coaches who were holding and not

holding current CPR certification, F (1, 516) = 1.294, p = 0.256. Despite this, Ontario

coaches performed substantially more preseason preparation when they held current CPR

certification (see Figure 51). As well, no significant interaction was detected between

holding CPR certification and the location of the team, F (3, 514) = 1.336, p = 0.262.

111

With regard to field, no significant difference was detected between the locations,

F (3, 518) = 1.277, p = 0.282. A significant increase in field checking was detected for

coaches who held current CPR certification, F (1, 520) = 10.623, p = 0.001; however, the

effect size was small (0.246). In addition, no significant interaction was detected between

holding CPR certification and the location of the team, F (3, 518) = 0.947, p = 0.418 (see

Figure 52).




= 0.045). The effect size was large between both New York and Florida (0.580), and New

York and Alberta (0.474). A significant increase in the prevention of injuries was also

detected for those coaches who held current CPR certification, F (1, 521) = 8.356, p =

0.004. The effect size was moderate between the two groups (0.433), and was particularly

large for Ontario coaches (see Figure 53). In addition, no significant interaction was

detected between holding CPR certification and the location of the team, F (3, 519) =

1.456, p = 0.226.

In the area of water safety, a significant difference was detected between the

locations, F (3, 525) = 2.754, p = 0.042. Post hoc analysis revealed that those in New

York were significantly less concerned with water safety than were coaches in Alberta (p

= 0.042); however, the effect size was small (0.239). A significant increase in water

safety was detected for those coaches who held current CPR certification, F (1, 527) =

6.014, p = 0.015; however, the effect size was small (0.199). As well, no significant

interaction was detected between holding CPR certification and the location of the team,

F (3, 525) = 2.548, p = 0.055 (see Figure 54).


F (3, 518) = 1.384, p = 0.247. A significant increase in safety was detected for coaches

who held current CPR certification, F (1, 520) = 4.567, p = 0.033; however, the effect

size was small (0.192). No significant interaction was detected between holding CPR

certification and the location of the team, F (3, 518) = 1.283, p = 0.280 (see Figure 55).

112





cooldown activities was detected for those coaches who held current CPR certification, F

(1, 523) = 8.291, p = 0.004. The effect size was moderate between the two groups

(0.419), and was particularly evident for respondents in Ontario (see Figure 56). No

significant interaction was detected between holding CPR certification and the location of

the team, F (3, 521) = 1.472, p = 0.221.

Warm-up and CPR

0.0000

1.0000

2.0000

3.0000

4.0000

5.0000


Location

Es

tim

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d M

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ina

l M

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NO

YES

Figure 49. Average Warm-up Survey Scores for Coaches Who Have and Do Not Have Current CPR Certification The grey bars represent those coaches who do not have current CPR certification. The black bars represent those coaches who have current CPR certification.

113

Equipment and CPR

0.0000

0.5000

1.0000

1.5000

2.0000

2.5000

3.0000

3.5000

4.0000


Location

Es

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d M

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inal M

ean

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NO

YES

Figure 50. Average Equipment Survey Scores for Coaches Who Have and Do Not Have Current CPR Certification The grey bars represent those coaches who do not have current CPR certification. The black bars represent those coaches who have current CPR certification.

Preseason and CPR

0.0000

0.5000

1.0000

1.5000

2.0000

2.5000

3.0000

3.5000


Location

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NO

YES

Figure 51. Average Preseason Survey Scores for Coaches Who Have and Do Not Have Current CPR Certification The grey bars represent those coaches who do not have current CPR certification. The black bars represent those coaches who have current CPR certification.

114

Field and CPR

0.0000

1.0000

2.0000

3.0000

4.0000

5.0000


Location

Es

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d M

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l M

ea

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NO

YES

Figure 52. Average Field Survey Scores for Coaches Who Have and Do Not Have Current CPR Certification The grey bars represent those coaches who do not have current CPR certification. The black bars represent those coaches who have current CPR certification.

Injury and CPR

0.0000

0.5000

1.0000

1.5000

2.0000

2.5000

3.0000

3.5000


Location

Es

tim

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d M

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NO

YES

Figure 53. Average Injury Survey Scores for Coaches Who Have and Do Not Have Current CPR Certification The grey bars represent those coaches who do not have current CPR certification. The black bars represent those coaches who have current CPR certification.

115

Water and CPR

0.0000

0.5000

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1.5000

2.0000

2.5000

3.0000

3.5000

4.0000


Location

Es

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NO

YES

Figure 54. Average Water Survey Scores for Coaches Who Have and Do Not Have Current CPR Certification The grey bars represent those coaches who do not have current CPR certification. The black bars represent those coaches who have current CPR certification.

Safety and CPR

0.0000

1.0000

2.0000

3.0000

4.0000

5.0000


Location

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l M

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NO

YES

Figure 55. Average Equipment Survey Scores for Coaches Who Have and Do Not Have Current CPR Certification The grey bars represent those coaches who do not have current CPR certification. The black bars represent those coaches who have current CPR certification.

116

Cooldown and CPR

0.0000

0.5000

1.0000

1.5000

2.0000

2.5000

3.0000

3.5000


Location

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NO

YES

Figure 56. Average Cooldown Survey Scores for Coaches Who Have and Do Not Have Current CPR Certification The grey bars represent those coaches who do not have current CPR certification. The black bars represent those coaches who have current CPR certification.

Research Question 8

The eighth research question examined the relationship between the age of the

coach and his/her safety practices. A MANOVA was conducted to determine whether a

coach’s age influenced coach safety practices when all dependent variables were

combined. As well, one-way ANOVA techniques were used to detect significant

differences between the four different coach age groups (less than 30 years, 30-39 years,

49-49 years, and 50 years and greater). Post hoc tests were then conducted to identify

which coach groups were significantly different from each other. The following eight

dependent variables were examined independently for ANOVA and post hoc analyses;

warm-up, equipment, preseason, field, injury, water safety, safety, and cooldown.

117

Significance was determined at an alpha level of 0.05. The overall survey results for each

category can be found in Appendix C, Table 49.

The majority of the coaches were between 30-39 years of age (34.7 %) and 40-49

years of age (40.7 %). Only 13.7% of coaches were less than 30 years of age and 10.8 %

of coaches were greater than 50 years of age. The Wilks’ Lambda indicated a statistically

significant MANOVA for the locations, F (24, 1364) = 2.305, p < 0.001, and the coach

age group, F (24, 1364) = 3.479, p < 0.001. Despite this, the Wilks’ Lambda indicated no

significant MANOVA for the interaction between coach age group and location, F (72,

2866) = 1.150, p = 0.184.

In the area of warm-up, a significant difference was detected between the coach

age groups, F (3, 515) = 2.893, p = 0.035. Post hoc testing revealed that the 30-39 year

coach age group performed significantly less warm-up than the 40-49 year coach age

group (p = 0.020) (see Figure 57). Despite this, the effect size between the two age

groups was small (0.212).

In the area of equipment, no significant difference was detected between the

coach age groups, F (3, 515) = 1.670, p = 0.173 (see Figure 58).

In the area of preseason, a significant difference was detected between the coach

age groups, F (3, 502) = 3.122, p = 0.026. Post hoc analysis revealed that the less than 30

year coach age group performed significantly more preseason preparation than the 30-39

year coach age group (p = 0.014) (see Figure 59). The effect size between the two age

groups was moderate (0.583).

With regard to field, a significant difference was detected between the coach age

groups, F (3, 506) = 4.042, p = 0.007. Post hoc analysis revealed that the less than 30

year coach age group performed significantly less field checking than the 40-49 year

coach age group (p = 0.009) (see Figure 60). The effect size between to the two age

groups was small (0.310).

For injury, a significant difference was detected between the coach age groups, F

(3, 507) = 5.511, p = 0.001. Post hoc analysis revealed that the less than 30 year coach

age group performed significantly more injury prevention than the 30-39 year coach age

group (p = 0.005), the 40-49 year coach age group (p = 0.001), and the 50 years and older

118

coach age group (p = 0.010) (see Figure 61). The effect size was large between the less

than 30 year coach age group and the 30-39 coach age group (0.623), the less than 30

year coach age group and the 40-49 year coach age group (0.708), and the less than 30

year coach age group and the 50 years and older coach age group (0.742).


coach age groups, F (3, 512) = 2.310, p = 0.076 (see Figure 62).

In the area of safety, a significant difference was detected between the coach age

groups, F (3, 506) = 5.973, p = 0.001. Post hoc analysis revealed that the less than 30

year coach age group was performing significantly fewer safety practices than the 40-49

year coach age group (p < 0.001) (see Figure 63). The effect size between the two age

groups was moderate (0.452).

With regard to cooldown, a significant difference was detected between the coach

age groups, F (3, 508) = 7.182, p < 0.001. Post hoc analysis revealed that the 30-39 year

coach age group performed significantly less cooldown than both the less than 30 year

coach age group (p < 0.001), and the 40-49 year coach age group (p = 0.002) (see Figure

64). The effect size between the 30-39 year coach age group was large when compared to

the less than 30 year coach age group (0.781), and the 40-49 year coach age group

(0.486).

119

Warm-up and Coach Age

0.0000

1.0000

2.0000

3.0000

4.0000

5.0000

<30 30-39 40-49 50+

Coach Age in Years

Es

tim

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d M

arg

inal M

ean

s

Figure 57. Average Warm-up Survey Scores for Various Coach Age Groups The following four coach age groups were created: less than 30 years, 30-39 years, 40-40 years, and 50 years and older.

Equipment and Coach Age

0.0000

0.5000

1.0000

1.5000

2.0000

2.5000

3.0000

3.5000

4.0000

<30 30-39 40-49 50+

Coach Age in Years

Es

tim

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d M

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ina

l M

ea

ns

Figure 58. Average Equipment Survey Scores for Various Coach Age Groups The following four coach age groups were created: less than 30 years, 30-39 years, 40-40 years, and 50 years and older.

120

Preseason and Coach Age

0.0000

0.5000

1.0000

1.5000

2.0000

2.5000

3.0000

3.5000

<30 30-39 40-49 50+

Coach Age in Years

Es

tim

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d M

arg

ina

l M

ea

ns

Figure 59. Average Preseason Survey Scores for Various Coach Age Groups The following four coach age groups were created: less than 30 years, 30-39 years, 40-40 years, and 50 years and older.

Field and Coach Age

0.0000

0.5000

1.0000

1.5000

2.0000

2.5000

3.0000

3.5000

4.0000

4.5000

<30 30-39 40-49 50+

Coach Age in Years

Es

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d M

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ina

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ea

ns

Figure 60. Average Field Survey Scores for Various Coach Age Groups The following four coach age groups were created: less than 30 years, 30-39 years, 40-40 years, and 50 years and older.

121

Injury and Coach Age

0.0000

0.5000

1.0000

1.5000

2.0000

2.5000

3.0000

3.5000

<30 30-39 40-49 50+

Coach Age in Years

Es

tim

ate

d M

arg

ina

l M

ea

ns

Figure 61. Average Injury Survey Scores for Various Coach Age Groups The following four coach age groups were created: less than 30 years, 30-39 years, 40-40 years, and 50 years and older.

Water and Coach Age

0.0000

0.5000

1.0000

1.5000

2.0000

2.5000

3.0000

3.5000

4.0000

<30 30-39 40-49 50+

Coach Age in Years

Es

tim

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d M

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ina

l M

ea

ns

Figure 62. Average Water Survey Scores for Various Coach Age Groups The following four coach age groups were created: less than 30 years, 30-39 years, 40-40 years, and 50 years and older.

122

Safety and Coach Age

0.0000

1.0000

2.0000

3.0000

4.0000

5.0000

<30 30-39 40-49 50+

Coach Age in Years

Es

tim

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d M

arg

ina

l M

ea

ns

Figure 63. Average Safety Survey Scores for Various Coach Age Groups The following four coach age groups were created: less than 30 years, 30-39 years, 40-40 years, and 50 years and older.

Cooldown and Coach Age

0.0000

0.5000

1.0000

1.5000

2.0000

2.5000

3.0000

3.5000

<30 30-39 40-49 50+

Coach Age in Years

Esti

mate

d M

arg

inal

Mean

s

Figure 64. Average Cooldown Survey Scores for Various Coach Age Groups The following four coach age groups were created: less than 30 years, 30-39 years, 40-40 years, and 50 years and older.

123

Research Question 9

The final research question was whether or not the number of years coaching

baseball/softball had an affect on overall safety practices. Linear regression analyses were

used to determine the relationship between number of years coaching and each of the

following independent variables; warm-up, equipment, preseason, field, injury, water,

safety, and cooldown. The results indicated that warm-up activities improved as the

number of years coaching baseball/softball increased (See Table 15).

Table 15. Linear Regression Results for Years Coaching and Safety Practices This chart shows the relationship between the number of years of baseball/softball coaching experience and a coach’s safety practices.

Standardized

Coefficients

B STD. ERROR BETA

Water

Safety

Cooldown

Equipment

Preseason

Field

Injury

CATEGORY T VALUE P VALUE

Warm-up

Unstandardized Coefficients

1.263 0.520 0.139 2.428 0.016

-0.056 0.555 -0.006 -0.101 0.919

0.023 0.223 0.005 0.104 0.918

0.3690.9000.0540.5390.485

-2.420 0.208 -0.005 -0.116 0.908

0.034 0.519 0.003 0.065 0.949

0.209

-0.039 0.241 -0.008 -0.160 0.873

-0.524 0.417 -0.068 -1.258

124

CHAPTER 5

DISCUSSION & CONCLUSIONS

Introduction

Society has a great emotional attachment to children and their overall health and

well being. Sport organizations, coaches and volunteers are no different. Participation in

sports such as baseball and softball provides great opportunities for youth. Unfortunately,

children can and do get hurt while playing baseball/softball. For some, these injuries can

even cause death or a life long physical impairment. The investigation attempted to

determine if coaches and baseball/softball organizations are identifying potential risks

and safety concerns and implementing systems to ensure the safety of youth baseball and

softball players. The findings of the study will be discussed in this chapter.

Discussion

Limited research has been performed to investigate the level of risk management

knowledge of youth sport volunteers in general and even less focusing on specific sports

such as baseball and/or softball. The research problem of interest was to discover the risk

management safety practices of youth baseball/softball coaches. Included in the study

was an attempt to identify whether certain factors significantly influenced risk

management and safety practices. These factors included the coaches’ willingness to

improve safety, organization involvement, the coaches’ preparation concerning safety

125

issues, the implementation of safety techniques for the players, the age of the players, the

motivation for coaching/volunteering, the influence of holding safety certifications, and

the age of the coach.

Some of the survey results were not consistent with previously reported research.

In the discussion, some possible explanations for the observations are addressed.

Research Question 1

To what extent are baseball/softball coaches willing to improve safety


The results affirmed the findings of Mueller et al. (2001) that if organizations

create an environment for their volunteers that encourages and supports proper safety

instruction and implementation, they gain a better chance of retaining and recruiting new

volunteers. Just over ninety percent (90.2 %) of the 530 coaches polled agreed that they

would continue coaching if first aid/CPR certification were a requirement.

According to Mueller et al. (2001), organizations often claim that the cost, time,

and effort required to implement a risk management system are prohibitive.

Organizational leaders claim that trying to implement such a system will demand too

much time from their volunteers and will lead to a drastic reduction in those willing to

provide their assistance to the sports organization. The findings of this research showed

that 75.8 % of coaches would be willing to pay part or all costs required for obtaining

proper safety certification. As well, 81.4 % of coaches surveyed indicated that they would

be willing to participate in an annual 8-16 hour coaching and safety awareness clinic.

According to Clarke (1999), many people feel that by volunteering their time and talents

they can give something back to society in a meaningful way. If organizations would

invest the time to properly create a risk management program and instruct the volunteers

on the importance of safety, it appears that volunteers would be willing to learn and

implement a program that would increase overall safety.

126

Only 57.4 % of coaches were willing to purchase a medical/first aid kit from the

organization and only 45.9 % of coaches said that they would replenish supplies on their

own. Volunteers believe that ‘time is money’ and when they give up so much of their

personal time, many feel that spending personal funds is inappropriate (Clarke, 1999;

Mackin, 1998; Mueller et al., 2000). One solution to this problem would be for the

organization to raise funds for all or a portion of these expenses. This could be

accomplished via sponsorships and/or fundraisers.

Research Question 2

To what extent does the organization provide safety information for its

coaches?

The findings were similar to the findings of Mackin (1998) and Mueller et al.

(2001). Youth baseball organizations are not providing their coaches with proper risk

management and safety mechanisms. Of the 517 coaches who responded, 66.5 % of them

indicated that they did not receive a safety manual before the start of each season. In

Alberta alone, 72.5 % of coaches did not receive this important material from the

organization. More Florida coaches (47.5 %) were provided with a safety manual at the

beginning of the season. Because of Florida’s warm climate, baseball/softball is played

all year. As a result, the level of competitiveness is higher and the organizations may be

better established and more aware of risk and safety than the other locations. Despite this,

it is apparent, regardless of area that organizations fail to provide adequate risk

management and safety instructions to their coaches.

The incidence of emergency action planning was similar to the results of the

previous section. Emergency Action Plans (EAPs) are a critical component of a

comprehensive safety manual. Overall, 73.8 % of coaches did not receive a written EAP

which outlined steps to follow in case of a serious injury. As with other findings, Alberta

had the worst average (76.9 %) and Florida was the most prepared (37.5 %).

127

Furthermore, 81.0 % of coaches indicated that they had not attended a safety-

training workshop. These findings suggest that coaches are not provided with the

opportunity to benefit from safety training and/or the organization fails to make it

mandatory for their coaches to attend. Since 90.2 % of coaches indicated that they would

continue to coach even if forced to obtain first aid/CPR certification, it is likely that they

would also be willing to participate in a safety-training workshop.

It is evident that organizations are neglecting the key components of risk

management. According to a number of risk management models (Kaiser, 1986; Clement

1988 & 1998; van der Smissen, 1990; Head & Horn, 1991; Mulroney, 1995; Tummala &

Leung, 1996; Fried 1999; Bandyopadhyay et al., 1999; Miccilis & Shah, 2000), the

necessity for identifying the risk, evaluating each risk and its potential resolution, and

implementing control of the risk are the key factors for building a successful risk

management program. Safety manuals, safety training workshops, additional safety

learning opportunities and emergency action plans are not made available to coaches

even though they are effective ways to combat tragedy and liability. Mackin (1998) and

Mueller et al. (2001) concluded that the challenges of creating and maintaining a risk

management program (lack of financial resources and knowledgeable volunteers) were

too difficult to overcome. However, the findings indicated that the majority of coaches

were willing to attend a safety training workshop, obtain first aid/CPR certification and

purchase a team medical kit. Since coaches are willing to abide by new rules and a risk

management framework has been established, an efficient and successful risk

management program can be created and applied to ensure safety.

Research Question 3

To what extent are coaches prepared to ensure the overall safety of their

players?

The authors of the risk management models (Bandyopadhyay et al., 1999;

Clement, 1988, 1998; Fried 1999; Head & Horn, 1991; Kaiser, 1986; Miccilis & Shah,

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2000; Mulroney, 1995; Tummala & Leung, 1996; van der Smissen, 1990) all outlined the

importance of identifying the risk and being prepared to handle an occurrence.

Preparation has been identified by the authors in three stages; beginning, during, and at

the end of the event or program. This question specifically dealt with these stages. The

responses of each coach, region and country are discussed.

The coaches’ overall responses revealed that in the area of warm-up, 75.4 %

conducted a 15-minute warm-up session before each game and practice (all of the time)

and 60.9 % had these warm-up sessions supervised (all of the time). Warm-up exercises

were organized by 63.4 % of coaches (all the time). These statistics can be associated

with the time constraints that coaches have in preparing for the game or practice. The

coach has many responsibilities that may distract him/her from effectively supervising a

player warm-up. These include ensuring that the field is properly prepared, setting the

batting lineup, having discussions with other coaches and organizing/communicating

each player’s game and/or fundraising commitments. In addition to these duties, the

volunteer coach has personal work and home obligations that may cause him to arrive

late for a practice or game. These factors can result in the players leading their own

warm-up activities, especially as the players become older. The most revealing statistic

related to warm-up was that only 32.7 % of experienced catchers were warming up the

pitchers before the game or practice (all of the time). Injuries to inexperienced catchers

can result from having poorly fitted equipment, neglecting to wear proper equipment and

a lack of the correct mechanics required to protect themselves. The player turning his/her

head away from a pitch in the dirt with the result of getting hit in the ear, ribs, back, knee

or elbow can easily occur when a player has not been trained to catch for a pitcher.

Coaches must ensure that players are shown proper catching techniques and are

supervised until they can demonstrate acceptable proficiency. Players should not be

allowed to catch just because they think it will be enjoyable.

The questions associated with cooldown in the survey revealed that 15.2 % of

coaches had cooldown activities after the game or practice with coaches’ supervision (all

of the time) and 30.4 % of coaches indicated that cooldown activities were never

supervised. In addition, 15.2 % of coaches conducted cooldown practices for 15 minutes

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(all of the time) and 36.5 % of coaches admitted that they did not hold any cooldown

activities. This was not surprising because the coaches and players are often tired after a

game or practice and want to go home. This is especially true for volunteer coaches who

have come straight from work, have not had dinner, and have not seen their families yet

that day. Unfortunately, without a proper cooldown, injuries can result later in the

evening or on the following day because muscles are stiff, leading to a spasm, pull, tear

or strain of the muscle.

In the area of safety, 58.4 % of coaches indicated that they had taught their

players not to slide head-first (all of the time) and 16.5 % of the coaches surveyed

instructed their players to slide feet-first most of the time. Close to 12 % of coaches

revealed that they have not instructed their players to slide feet-first. The reason for these

results can be attributed to coaches who have experience in the game of baseball/ softball.

Experienced coaches understand the dangers of the head-first slide through personal

experience as a player or having observed the frequency of injuries to others who

attempted this maneuver. Those coaches who have limited playing or coaching

experience may have seen head-first slides on television, thus thinking that it is exciting

and allowing their players to slide in any manner. Many of these inexperienced coaches

do not know how to instruct the players in how to slide and thus it is often neglected.

For water safety, 59.4 % of coaches demonstrated that they provided water for

each game and practice (all of the time). Another 22.5 % of coaches indicated that they

brought water most of the time. Furthermore, 70.6 % of coaches revealed that they gave

water breaks all the time and 92.9 % of coaches indicated that they never had used

withholding water breaks as a form of punishment. Despite this, no matter the level of

coaching experience, the importance of hydration is well known. Fortunately, when a

coach forgets to bring water, there are often other coaches or parents who bring water to

games and practices.

The survey revealed that coaches are not well prepared for dealing with injury.

Fully 43.3 % of coaches indicated that they never brought a medical book to the games or

practices. Furthermore, 34.5 % of coaches indicated that they never recorded injuries

when they occurred. Finally, close to half of the coaches who had traveled out of town

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with their team (47.4 %) did not collect information relating to safety such as hospital

location. This area is often neglected because youth coaches do not consider serious

injuries likely to occur. Coaches fail to keep records of injuries because many of them do

not realize that they could be liable months or even years later. Organizations should

enforce the recording of all injuries, but they have also failed to recognize the legal

ramifications that can result if this information is not available. In a proper

baseball/softball safety clinic, these areas would be taught and coaches would learn the

importance of recording and collecting safety information. It is imperative that sport

organizations create a process whereby all injuries and safety information is collected and

maintained to protect against future liability.

The quality of the field conditions for youth baseball and softball players is often

poor and even dangerous. Many of the diamonds are located in public parks where the

field maintenance is lacking. As a result, coaches need to inspect the field before each

game and practice. In the survey 33.6 % of coaches indicated that they inspect the field

before every game and practice. In other areas related to field, 43.8 % of coaches

revealed that they checked the weather before all games and practices and 75.1 % of

coaches indicated that they made sure the equipment was away from the playing area at

all times. The most interesting finding was that only 53.8 % of coaches brought a first aid

kit to the game or practice (all of the time) and 18.3 % most of the time. This can be

attributed to a lack of safety knowledge regarding the importance of having a medical kit

in case of injury. Many players receive minor cuts and scrapes throughout the game and

medical supplies are required to treat even these minor injuries.

Another of area of concern identified by this investigation was of preseason

preparation. The survey revealed that 27.8 % of coaches had never asked their players to

fill out a medical report form and 66.5 % also admitted that they had never asked their

fellow coaches to fill one out. This is critical to the safety of the players and coaches.

Medical report forms allow coaches to learn about any allergies their players or coaches

may have and it provides the coach with important insurance and family information that

may be required prior to treatment if a player is seriously injured when their guardians

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are not present. Not having this important medical information may risk permanent injury

to the player or coach and possibly lead to a liability suit.

The results indicated that Canada performs more warm-up activities than the

USA. Warm-up activities included: having a coach present, lasting at least 15 minutes, a

properly designed program is implemented and an experienced catcher always warms up

the pitcher before each game. A number of injuries can be caused by not sufficiently

warming the body before taking part in a particular sporting activity.

Coaches in both Florida and Alberta were found to perform more injury

prevention activities than those in New York. Also, water safety was practiced less often

in New York than in Alberta. Perhaps the survey area for New York can explain these

significant differences. New York coaches were predominately from rural areas where

there may be a lack of individuals to implement a risk management plan and to

adequately educate volunteer coaches.

Alberta coaches moderately perform more cooldown activities than Ontario

coaches. The colder weather in Alberta during the baseball season may be responsible for

this difference. Stretching before, during and after games is important and even more

critical when playing in colder temperatures. A proper cooldown can reduce the

occurrence of pulled muscles and help manage post-game muscle stiffness and soreness.

It was apparent that all of the four regions were lacking critical aspects of risk

management and safety practices. Further research needs to be conducted on the

demographics of coaches to further identify the factors that lead to how risk management

and safety practices are implemented.

Research Question 4

What safety measures are coaches implementing?

The investigation focused on two aspects that are very critical to the game of

baseball; field conditions and equipment. Baseball and softball are unlike other outdoor

sports such as football, soccer, rugby, and field hockey when it comes to the condition of

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the field. For youth baseball in particular, the fields are often located in areas where

upkeep of the facility is not at the highest level. They are usually located in public parks

where debris and other unsafe material can be left in areas that cannot be seen easily.

Baseball requires a large area to play on and baseball equipment being left in the playing

area has led to injuries. It is important that all items, including equipment such as

helmets, bats and catcher’s apparel, be removed from the playing surface. The law case

Lassegne (1990), is a perfect example of what can happen when playing on a field that is

not ideal for baseball and softball. Field conditions must be playable and without debris

so that the chance of injury is decreased.

The National Sporting Goods Association indicated that participation in

baseball/softball among youths age 7 and older was 29.6 million in 1999 (2000) and 28.1

million in 2000 (2001). It can then be assumed that thousands of injuries such as cuts,

sprains and strains occur due to poor field conditions each year and are not reported.

Injury data for baseball and softball is collected based on those players that actually go to

the hospital for medical assistance. As previously defined, an injury is “a physical

ailment resulting from sports activity that causes time lost from sports participation”

(Hergenroeder, 1998, p. 1057).

Another field-related concern pertains to the types of bats that the players are

using. Aluminum bats are being used and are similar to golf clubs in the sense that they

have the same attractiveness to lightning. Obtaining the proper weather report is critical

to the safety of the players (Appenzeller, 1998).

The last field related issue was whether or not a medical kit is present at each

game and practice. The research showed that there was no difference between the

locations or the countries in this area. Further analysis found that 53.8 % of the 531

coaches brought a medical kit to all the games and practices and only 33.6 % of them

checked the field for debris all the time. It is clear that if coaches had a proper safety

checklist (present in a safety manual) the chances of field safety being neglected would

decrease (Appenzeller, 1998 & Appenzeller & Lewis, 2000).

The other area that was researched for this question was equipment. In the game

of baseball, protective equipment includes a helmet, a protective support for a

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reproductive organ and a mask, chest protector and leg guards for the catcher. The survey

focused on equipment that catchers are required to wear such as shin pads, chest protector

and a mask. Survey results indicated that 61.7 % of coaches made sure that equipment fit

the player properly all of the time and 24.6 % most of the time. Other equipment areas

such as wearing a protective support and not wearing jewelry during participation were

being managed properly as well. The final area where equipment was being investigated

was related to the protection of the player’s head. Surprisingly, 75.2 % of coaches

indicated that they never required their players to wear mouth guards and 44.2 % of

coaches admitted that they never encouraged or required their players who wore glasses

to use safety glasses during playing time. These two findings clearly highlight the fact

that coaches do not recognize the high frequency of injuries to the mouth and eyes. The

use of these two items of personal protective equipment is prevalent in other sports such

as basketball, football and field hockey. Mouth guards and proper eye protection can

substantially reduce the risk of injury to the player. Injuries to the face are very expensive

financially and socially and with the implementation of proper mouth and eye protection

coaches can reduce the severity of these injuries. Over the last decade, there has been an

increase in males wearing jewelry (ear rings and large chains) and rules have been

created to ensure their removal before participation. No literature exists on injuries

caused by jewelry, but, gruesome stories have been told about injuries.

Prevention is the most important method for avoiding serious or potentially fatal

injury. There are many safety appliances available for baseball/softball players and

coaches need to more often encourage or even require their use. If coaches are instructed

in the type of injuries that can occur in baseball/softball it may result in more coaches

ensuring that the necessary areas regarding risk and safety are implemented.

The research indicated that coaches’ in Florida was more effective in the areas of

equipment than those in New York. New York coaches were from rural areas and may

not have been as knowledgeable about equipment safety compared to coaches from

Florida. In Florida, coaches were predominantly from larger cities and league resources

may have been more substantial and leagues were thus able to provide the necessary

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equipment for each team. Further research needs to be conducted on the demographics of

coaches to further identify whether or not it has an affect on risk and safety practices.

Nowjack-Raymer and Gift (1996) concluded that 41.0 % of baseball injuries

occur to the head, face, mouth, or eyes. Headgear and faceguards have been developed

for baseball and softball players, but not all leagues or teams are required to use this

safety equipment. In the research conducted, 98.0 % of coaches did not recommend or

suggest that their players wear mouth guards. Nowjack-Raymer and Gift (1996) found

that a mere 7.0 % of baseball/softball players wore mouth guards all or most of the time.

The cost for a mouth guard is less than $60 and with dental costs being extremely high,

the value of wearing one is priceless. On another level, having all baseball/softball

players at a young age wear mouth guards will provide an opportunity for players to learn

about safety, thus leading to a lifetime of safety awareness and practice. Other than the

obvious protective benefits, safety gear often provides a sense of confidence for most

athletes.

Research Question 5

What is the relationship between age groups and coaches’ safety practices?

The study found that the 9-11.5 year player age group was performing more

warm-up and cooldown than the 5-6.5 year player age group. The 14-15.5 and the 16-

17.5 year player age groups were also performing more cooldown than the 5-6.5 year

player age group. As athletes become older, competition increases and more games are

being played. All-Star teams are being formed and coaches are becoming more serious,

competitive, and knowledgeable. As the players become older, some coaches begin to

realize the importance of warm-up and cooldown practices.

The results revealed that the 16-17.5 year player age group performed less

equipment checking than the 7-8.5, the 9-11.5 and the 12-13.5 year player age groups. As

players become older, putting on equipment and taking care of equipment becomes the

individual responsibility of the athlete. The younger players, on the other hand, require

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more assistance from the coaches because they may not know how to put on catcher’s

equipment and where to place equipment. Many youngsters have a hard time putting on

their gloves and shoes and keeping track of where they put their hats and gloves.

Data analysis showed that the 9-11.5 year player age group performed more

safety practices than 5-6.5, the 14-15.5 and the 16-17.5 year player age groups. In

addition, the 7-8.5 year player age group performed moderately more safety practices

than the 16-17.5 year player age group. The two areas of safety studied included whether

or not players were being taught to slide feet first and if horseplay was being prevented.

Research has shown that sliding headfirst results in a high number of chest, neck, facial,

arm, wrist, and finger injuries (Gowjack-Raymer & Gift, 1996).

The results disclosed that there were major differences in the risk and safety

practices depending on the player age groups. It was apparent that as the age of the player

increased so did the focus of certain safety practices of the coaches. This occurrence

could be related to coaches assuming that players are aware of risk and safety to the level

that they do not need direction, and that they also know how to prepare their own bodies

for competition. The organizational structure for younger athletes is viewed as more

important compared to older athletes and thus warm-up activities was seen as a process to

educate players on becoming prepared to compete. As players become older, areas such

as cooldown are often ignored by the players and coaches must recognize the importance

of cooling the body down after competition no matter how old the players. The 5-6.5 year

player age group was doing the least amount of cooldown when compared to all other

groups. It was obvious that depending on the age of the players, certain areas of risk and

safety practices of the coaches were influenced.

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Research Question 6

Will a particular motivation to coach baseball/softball influence coaches’

safety practices?

This question was based on three motivational factors that were considered as

potentially affecting coaches’ risk management and safety practices.

Motivational Factor – Child/Relative

Coaches who were not motivated to volunteer because they had a family member

participating on the team performed more preseason preparation, injury prevention and

cooldown. These coaches were motivated by other factors such as enjoyment of coaching

or giving back to the community, and they were not likely forced into this role due to

obligation. For this reason they may be more knowledgeable and competent in the area of

baseball/softball and have more experience than some of the new parent coaches.

Coaches who do not have this type of personal connection with the player(s) may look

beyond their individual welfare and focus instead on such goals as the success of the

team. Coaches who do not have a sibling or family member on the team may not be

rushed to leave, have to worry about or deal with their family member(s), or be

emotionally attached to the accomplishments or failures of their family member(s). When

there are no siblings or family members on the team, coaches have a reduced chance of

being sidetracked. Their focus can be on the game and the program they have created.

Coaches who were motivated to coach because they had a family member

participating on the team performed less overall safety practices. Among the coaches

surveyed 73.1% were motivated to volunteer because they had a child or family on the

team. Organizations cannot assume that these volunteers because they have a family

member participating will provide effective risk and safety practices. Most parents want

their children to have fun participating and many do not think that their child or family

member playing a fun sport will ever hurt seriously. The attachment between the coach

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and the family member does not lead to an enhanced awareness and focus on their safety

and well-being.

Motivational Factor – Enjoyment

The second motivational factor was enjoyment. Coaches who were motivated to

volunteer because they enjoy coaching (63.7%) performed moderately more injury

prevention, safety and cooldown activities. When a person enjoys what they are doing,

they will often take the time to improve themselves. These coaches will read about

coaching and baseball/softball, attend various instructional clinics and seek out as much

information as possible to improve their overall coaching. On the contrary, those who do

not like what they are doing may become lackadaisical and overlook important aspects of

their role. Those individuals who do not like to coach are often those who spend little

time preparing for the season and before games or practices. Baseball/softball

organizations must educate all coaches on the importance of coaching and risk

management and safety practices. This can be done by providing resources and

encouragement so that they may fully realize their important contribution to the league.

Motivational Factor - Community

The last motivational factor was community involvement. Coaches who were

motivated to volunteer because they wanted to give back to the community (38.3%)

performed moderately more equipment, preseason safety, injury prevention, and

cooldown activities. These coaches may be former athletes who were fortunate to have

great coaching, enjoyed playing the sport, and have many fond memories of being an

athlete. They believe that such experiences were beneficial to their lives and they want to

provide similar experiences to children. These feelings motivate coaches to be the best

they can by attending training workshops so they can learn important aspects of the game

as well as safety practices. When individuals are motivated to coach, they are willing to

learn, follow procedures and implement programs that are beneficial to the players.

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Individuals who volunteer because of necessity, coercion or guilt are reluctant to take

responsibility for a team and cannot be expected to implement risk and safety programs

on their own. Organizations have to create the environment and process whereby coaches

are selected who want to coach, and are motivated to provide a safe experience for the

players.

The researcher believes that coaches are not receiving the direction and support

that inspires them to maintain and gather information and record injuries. A volunteer’s

motivation to coach could be very positive, but if they are not trained in proper risk and

safety techniques by the organization and rules are not enforced, the players’ safety will

be jeopardized. According to Miccolis & Shah (2000) and Tummala and Leung (1996) if

a risk management program is created, implemented and maintained the results indicated

that the severity of injuries, time lost due to injury, and the number of injuries are reduced

substantially with the implementation of an effective risk management program.

Research Question 7

Will holding a current first aid and/or CPR certification influence coaches’

safety practices?

Safety Factor – First Aid Certification

Just over 49 % of coaches surveyed held current first aid certification. They

performed moderately more preseason preparation, and cooldown activities. Those who

held First aid certification conducted substantially more injury prevention. These

components of risk and safety management are taught in all first aid courses. Gathering

player health information is critical in the prevention and management of injuries.

Knowing the medical history of those one is coaching allows the person providing first

aid treatment to react more efficiently in the event of a medical emergency. Those who

have first aid training, learn that maintaining medical records and recording injuries is a

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preventive measure that could protect them later on against a lawsuit. The survey results

show that coaches with first aid certification are applying what they have learned and that

the course itself is valuable in improving particular safety categories. However, there was

no difference between coaches who did and did not have first aid certification in the areas

of warm-up, equipment, field, water safety, and safety. Therefore, first aid certification

alone is not sufficient and there is a need for baseball/softball specific risk and safety

training.

Safety Factor – CPR Certification

Coaches who held current CPR certification performed more injury prevention

and cooldown activities. Those coaches who held first aid certification conducted more

preseason than those coaches who held CPR certification. Further analysis revealed that

44.0 % of coaches held CPR certification and 38.5 % of the 531 coaches surveyed held

both first aid and CPR certification. CPR and First certification alone are not sufficient

and there is a need for baseball/softball specific risk and safety training.

Research Question 8

What is the relationship between age of coaches and their safety practices?

Kaiser (1986), Clement (1988, 1998) and Berlonghi (1990) acknowledged the

importance of education and training as key contributors to successful identification,

evaluation and controlling of risk. The results showed that coaches less than 30 years old

conducted more injury prevention than all other age groups and performed more

preseason preparation and cooldown activities than the 30-39 year coach age group.

These coaches could be past or present experienced players, students taking post

secondary education in the field of coaching and physical education, and/or volunteers

with aspirations of making coaching a career at a professional, national, or college level.

This being the case, the majority of these individuals would have significant knowledge

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of baseball/softball, especially in all sport specific areas. It is also likely that a higher

proportion of these coaches hold first aid and/or CPR certification because it is required

for a coaching career.

Survey results revealed that the 30-39 year coach age group had the lowest survey

score for preseason and cooldown when compared to the other age groups. The

researcher speculates that this could be related to changes in lifestyle. During this time,

individuals are establishing their professional careers, moving, getting married and

having children. Consequently, many individuals will decide to stop coaching. Even for

the dedicated coach who chooses to continue his/her involvement, time commitments and

priorities change and under these pressures, compromises may be made to reduce time

spent on activities relating to risk management and safety. Another potential explanation

is that inexperienced individuals are now beginning to coach because of their children.

According to Clarke (1999), a key motivator for becoming involved with volunteer

activities is the need to ‘give something back.’ As much as they want to give their time

and enjoy being with their children, they do not have the experience, knowledge or

training to recognize and mitigate the many risk and safety challenges that surround

them.

Coaches between 40-49 years of age conducted more warm-up than the 30-39

coach age group, more field checking than the less than 30 year coach age group, more

safety than the less than 30 year coach age group and more cooldown activities than the

30-39 year coach age group. According to Kavler and Spiegel (1997), the ability to

identify risk involves collecting information about past and current events that could

result in potential loss to the organization. The majority of coaches in this age group and

in the 50 years and older coach age group likely have additional baseball/softball

experience. The majority of these coaches have probably seen and experienced injuries

because of debris on the field, equipment being located in unsafe areas, weather problems

and the consequences of failing to possess required first aid materials to assist an injured

athlete, umpire, coach or parent. Personal liability may also influence the coaches’

adherence to safety procedures. This age group may have significant personal assets and

these would be at risk if they were faced with a lawsuit claiming willful negligence. Due

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to personal and professional experience, these coaches are able to recognize a potential

legal liability, which provides a strong incentive for them to implement safety practices.

Research Question 9

What is the relationship between the numbers of years coaching


The results indicated that only warm-up activities improved as the number of

years coaching the game of baseball/softball increased. It is surprising that experience in

coaching baseball/softball does not lead to an improved risk and safety environment.

Improved safety practices are more likely related to a coach’s initiative rather than the

number of years they have been in the program. It is apparent that all coaches, no matter

how long they have been coaching the game of baseball/softball, need risk and safety

training.

Conclusions

The research has revealed that there are many misperceptions and challenges for

youth sports organizations and their coaches. The main misperception is that

organizations will demand safety certification of their coaches and that coaches will be

unwilling to comply. The results refuted this claim and organizations should not be

concerned with a decline in volunteering as a result of demanding more certification in

order to coach. The coaches need direction and support in this area because their

knowledge varies greatly amongst them.

Organizations need to create opportunities for their coaches and volunteers to be

educated in the field of risk and safety as well as a program that direct, support, maintain

and evaluates risk and safety practices. Such a program must be implemented despite the

age of the coach or the age of the player so that a consistent risk and safety activities are

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followed throughout the organization. It is important that baseball and softball organizers

understand that general safety education is beneficial but for effective safety practices to

occur, risk and safety pertaining to the game of baseball and softball must be taught. A

detailed conclusion for each research question is stated below.

Research Question 1

To what extent are baseball/softball coaches willing to improve safety


If organizations create an environment for their volunteers that ensures proper

safety instruction and implementation, they will gain a better chance of retaining and

recruiting new volunteers. Just over 90 % of the 530 coaches polled agreed that they

would continue coaching if first aid/CPR certification were required to coach.

The findings showed that 75.8 % of coaches would assist in subsidizing the costs

of obtaining the proper safety certification. Furthermore, 81.4 % of coaches surveyed

indicated that they would be willing to participate in an annual 8-16 hour coaching and

safety awareness clinic.

Research Question 2

To what extent does the organization provide safety information for its

coaches?

Over half of the respondents (66.5 %) indicated that they had not received a safety

manual from their organizations prior to the start of the season. The province of Alberta

had the highest rate of coaches not receiving any material (72.5 %). As well, 73.8 % of

coaches did not receive written Emergency Action Plans to be used in case of serious

injury. Once again, Alberta had the worst average (76.9 %) and Florida the best (37.5 %)

amongst all coaches. In addition, 81.0 % of coaches indicated that they had not attended a

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safety training workshop. Evidently, the coaches surveyed were not given an opportunity

to improve their safety practices and/or their organizations were failing to make these

information sessions mandatory.

Research Question 3

To what extent are coaches prepared to ensure the overall safety of their

players?

There were differences in many aspects of risk and safety management between

the locations. In the areas of warm-up activities, injury prevention, water safety and

cooldown activities, different locations were doing more than others. The results showed

that there were no clear systematic processes that were being implemented to cover all

the aspects of risk and safety by the locations. The only difference between the countries

was that Canadian coaches conducted more warm-up practices than the American

coaches.

Research Question 4

What safety measures are coaches implementing?

The majority of coaches surveyed were not implementing safety measures. The

two areas that were used in determining safety measures were field conditions and

equipment. The results showed that 94.0 % of the 531 coaches did not bring a medical kit

to all the games and practices and 88.0 % of them indicated that they only checked the

field for debris some of the time. The second area investigated was equipment. It must be

noted that not all safety equipment is being used to protect baseball/softball players.

Nowjack-Raymer and Gift (1996) concluded that 41.0 % of baseball injuries occur to the

head, face, mouth, or eyes. Nowjack-Raymer and Gift (1996) found that only 7.0 % of

the baseball/softball players wore mouth guards all or most of the time. This was similar

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to the current study in that only 2.0 % of coaches surveyed recommended that their

players wear mouth guards and/or safety glasses.

Research Question 5

What is the relationship between player age groups and coaches’ safety

practices?

There were differences between the different player age groups with respect to

safety practices. The younger age groups were conducting more warm-up and safety

practices than the older age groups. As the players became older in age, less equipment

safety was being conducted and more cooldown activities were being completed.

Research Question 6

Will a particular motivation to coach baseball/softball influence coaches’

safety practices?

All three motivational factors affected coaches’ overall safety practices. Those

coaches who were not motivated to volunteer because they had a family member

participating on the team performed moderately more risk and safety practices in the

areas of preseason preparation, and cooldown. Those who did not have a family member

on the team conducted more injury prevention activities. Those coaches who were

motivated to volunteer because they have a family member on the team need further risk

and safety training.

The second motivational factor was enjoyment. Coaches who were motivated to

volunteer because they enjoyed coaching performed moderately more injury prevention,

and cooldown activities. It is likely that those coaches who do not enjoy coaching are

often forced into the role. Since youth baseball/softball organizations depend on

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volunteers to maintain a high standard regardless of coach motivation, the league must

teach and enforce strict risk and safety rules and regulations.

The last motivational factor was community involvement. Coaches who were

motivated to volunteer because they wanted to give back to the community performed

more equipment checking, preseason preparation, and cooldown activities. Those coaches

who were motivated to volunteer because they wanted to give something back to the

community are true assets for youth organizations because they are knowledgeable and

competent in the areas of risk and safety.

Research Question 7

Will holding a current first aid and/or CPR certification influence coaches’

safety practices?

Coaches who held current first aid certification performed moderately more

preseason preparation, and cooldown activities. On the other hand, coaches who held

current CPR certification performed more injury prevention, and cooldown activities.

There is a need for baseball/softball specific risk and safety training even for coaches

with first aid and/or CPR certification. Youth baseball/softball organizations cannot

solely rely on first aid and/or CPR certification for dealing with risk and safety.

Organizations need to further educate their coaches with safety training workshops, by

providing safety manuals to follow, and by implementing and enforcing risk and safety

practices.

146

Research Question 8

What is the relationship between the age of coaches, and their safety

practices?

There were differences between the four coach age groups with regard to risk and

safety practices. These differences can be attributed to baseball/softball and life

experience of the coach. Youth baseball/softball organizations need to understand the

challenges of volunteer coaches, and create and implement a program that can achieve all

of their risk and safety objectives.

Research Question 9

What is the relationship between the numbers of years coaching


Organizations cannot assume that because a coach has been coaching the game of

baseball/softball for a number of years that they do not need a baseball/softball safety

training workshop. Experience playing or coaching the game of baseball/softball does not

lead to the implementation of effective risk and safety practices.

Implications

Sport managers in baseball/softball should be striving to create risk management

and safety programs that can be implemented, controlled and maintained by the coaches

and administrators in the organization (Appenzeller, 1998; Appenzeller & Lewis, 2000;

Clement 1997 & 1998; Fried 1999). The study investigated some of the possible factors

that cause organizations and coaches to fail in providing a safe environment for their

players and coaches, thus increasing liability for themselves and the organization. Based

147

on these findings and conclusions, successful risk and safety programs can be developed

and successfully maintained within a youth baseball/softball organization based on the

following research:

1. Evidence was found that indicated that coaches would be willing to continue

coaching if additional risk and safety qualifications were required.

2. Coaches were willing to subsidize the cost of additional risk and safety

qualifications (first aid/CPR) in the financial range of $30-$60.

3. Coaches were willing to use personal funds to purchase a medical supply kid but

were unwilling to maintain materials from personal funds.

4. Organizations were failing to provide coaches with a safety manual, a written

emergency action plan, safety-training workshops, and sport specific instructional

programs. Such implementation can decrease the chance of serious and tragic

injuries and liability.

5. Evidence indicated variations in risk and safety practices between player age

groups. Consistent risk and safety practices must be administered for all age

groups.

6. Coaches who do not have a child/family member on the team conducted more

likely risk and safety practices. Organizations must create a risk and safety

awareness program that ensures all players the opportunity to receive the same

level of safety.

7. Age of the coach played a role in risk and safety actions. Risk and safety

programs need to be created so all coaches, no matter their age and experience,

can learn and implement a risk and safety program.

Future Recommendations

1. An attempt should be made to analyze other youth sports such as football, soccer,

basketball, and hockey to see if these organizations and coaches implement risk

148

management and safety programs more effectively than do baseball/softball

coaches and organizations.

2. Data should be collected on the risk management and safety practices of the

parents of youth sports participants to find out what types of risk management and

safety activities they conduct and whether or not they transfer that knowledge to

their children.

3. Future research could examine the attitudes and actions of youth sports players

relating to risk and safety. As players increase in age, a study could be done on

their awareness of risk and safety issues in their sport and whether or not this

relates to an increase in their risk management and safety activities.

4. Investigations on the process of how national youth sports organizations are

conveying information about risk and safety to their contingents could be

beneficial.

5. A more focused investigation into the attitudes and actions toward risk and safety

of organizations could be conducted to further understand why risk and safety

practices are or are not being implemented in a proper manner.

6. An investigation on whether or not the demographics have an affect on risk

management and safety practices of the coaches.

149

APPENDIX A

Survey

150

Florida State UNIVERSITY

Office of the Vice President For Research Tallahassee, Florida 32306-2763 (850) 644-8673 FAX (850) 644-4392

APPROVAL MEMORANDUM Human Subjects Committee Date: 2/4/2003 Christopher Lachapelle 2782 N Triphammer Rd Ithaca, NY 14850 Dept.: Sport Administration From: David Quadagno Re: Use of Human Subjects in Research Youth baseball and Risk The forms that you submitted to this office in regard to the use of human subjects in the proposal referenced above have been reviewed by the Secretary, the Chair, and two members of the Human Subjects Committee. Your project is determined to be exempt per 45 CFR § 46.101(by 2 and has been approved by an accelerated review process. The Human Subjects Committee has not evaluated your proposal for scientific merit, except to weigh the risk to the human participants and the aspects of the proposal related to potential risk and benefit. This approval does not replace any departmental or other approvals, which may be required. If the project has not been completed by 2/3/2004 you must request renewed approval for continuation of the project. You are advised that any change in protocol in this project must be approved by resubmission of the project to the Committee for approval. Also, the principal investigator must promptly report, in writing, any unexpected problems causing risks to research subjects or others. By copy of this memorandum, the chairman of your department and/or your major professor is reminded that he/she is responsible for being informed concerning research projects involving human subjects in the department, and should review protocols of such investigations as often as needed to insure that the project is being conducted in compliance with our institution and with DHHS regulations. This institution has an Assurance on file with the Office for Protection from Research Risks. The Assurance Number is IRB00000446. Cc: Dr. Annie Clement HSC No. 2003.044

151

Youth Baseball and Softball Coaches Risk Management and Safety Survey

Please take a few minutes to answer these 30 questions. All your responses will be kept in confidence. Please answer each question by filling in the circles.

Part I: The following questions deal with coaches’ safety practices and to identify what youth baseball and softball organizations have provided to ensure safety for the players.

1 I would continue to coach if I had to obtain first aid/CPR certification (Personal Cost $30-$60).

o o

2 I would be willing to pay for the first aid/CPR certification out of my personal funds (Personal Cost $30-$60).

o o

3 I am willing to participate in an annual coaching and safety awareness clinic (Attending 8-16 Hour Clinic).

o o

4 I would continue to coach if I had to purchase a medical/first aid kit from the organization (Personal Cost $30-$50)

o o

5 I would continue to coach if I had to replace used medical supplies out of my own personal funds (Personal Cost $20-$40).

o o

6 I am provided with a safety manual from my youth baseball/softball organization at the start of every season.

o o

7 I am provided with a written Emergency Action Plan to follow in case of serious injury from my youth baseball/softball organization.

o o

8 I have participated in a safety-training workshop provided by my youth baseball/softball organization.

o o

9 I have been notified by my organization about official correspondence, websites or other Internet communications where I can obtain additional safety material.

o o

152

Please rate each statement below using the following scale.

10 I require my players to fill out a medical report form at the beginning of every season. o o o o o

11 I require my coaches to fill out a medical report form at the beginning of every season. o o o o o

12 I bring the medical report book to all practices and games. o o o o o

13 I record injuries that occur during games/practices. o o o o o

14 I record injuries that occur in my presence before or after games/practices. o o o o o

15 When I take my team out of town, I gather phone numbers for the local police and hospital, and directions to the closest emergency medical facility.

o o o o o

16 I require my players to wear mouth guards when playing and practicing. o o o o o

17 I require my players to warm up for at least 15 minutes before each game and practice. o o o o o

18 I require my players to warm up under coach’s supervision before each game and practice. o o o o o

19 A proper warm-up regimen before every game or practice has been designed. o o o o o

20 I make my players complete a cooldown regimen under a coach’s supervision after each game and practice.

o o o o o

21 I require my players to complete a cool-down regimen for 15 minutes after each game and practice. o o o o o

22 I require that water is provided at every game and practice. o o o o o

23 I require that I give my players breaks during practice to drink fluids. o o o o o

24 I have denied my players water breaks as a form of punishment. o o o o o

153

Please rate each statement below using the following scale

25 I inspect the field for glass, stones, debris, and other foreign objects. o o o o o

26 I check weather reports for possible dangerous weather conditions (lightning, heavy rains, etc.) o o o o o

27 I ensure that a first aid kit is present and accessible before each game/practice. o o o o o

28 I encourage parents of players who wear glasses to provide safety glasses. o o o o o

29 I make sure that bats and other loose equipment are off the field prior to and during baseball games.

o o o o o

30 I inspect my players’ equipment for condition and fit. o o o o o

31 I check my catchers to make sure that they are wearing properly fitted and safe helmets, mask, and throat protectors.

o o o o o

32 I check my catchers to make sure that they are wearing properly fitted and safe shin guards and long model chest protectors.

o o o o o

33 I encourage and teach my players to slide into bases feet-first rather than head-first. o o o o o

34 I check all players to ensure they are wearing a protective hard cup with athletic supporter. o o o o o

35 I discourage and stop horseplay among players when it occurs. o o o o o

36 I make sure players are not wearing watches, jewelry, rings, pins, or other metallic items during games and practice.

o o o o o

37 I make sure that an experienced catcher warms up the pitcher. o o o o o

154

Please check the box next to the answers that describe you best.

1. How many years have you been coaching youth baseball/softball?

______________________

2. What age group are you currently coaching?

______________________

3. What is your motivation to coach baseball?

4. Please indicate which health/safety certification you currently hold. (Check all that apply).

5. What is your present occupation/profession?

__________________________________________________

6. How old are you?

___________________

My child/relative plays baseball

I enjoy the game

I am giving back to the community

First Aid

CPR

Other (Please specify): ________________________

155

APPENDIX B

Letter to Coaches

156

Chris Lachapelle 2782 N. Triphammer Rd. Ithaca, NY, 14850 (607) 257-3586 (607) 227-9401 Date **** Person’s Address Dear Baseball/Softball Coach:

My name is Chris Lachapelle and I am a doctoral student at Florida State

University. I am conducting a survey study for my doctoral dissertation. The study is

investigating the risk management practices of youth baseball/softball coaches.

You will be asked to respond to a series of questions regarding your risk

management views and procedures when you coach baseball/softball players. The

questionnaire will take approximately 20 minutes to complete. Every response will be

treated confidentially to the extent allowed by law and no person or organization will be

identified except by means of a code number. Please understand that your participation is

totally voluntary and there is no penalty for nonparticipation in the study.

In order for this study to be a success, a high rate of return is critically needed;

therefore your response is appreciated. A postage-paid envelope is provided for your

convenience. I look forward to your early response. Each subject will have an

opportunity to find out the results by contacting me at (607) 257-3586 or emailing me at

[email protected]. You may also contact my major professor, Dr. Annie Clement,

at (850) 644-9214 or email her at: [email protected], prior to July 1, 2003.

Finally, if you have any questions on your rights as a subject/participant in this

research, or if you feel you have been placed at risk, please contact the Chair of the

Human Subjects Committee, Institutional Review Board, through the Vice President for

the Office of Research at (850) 644-8633.

Sincerely,

Chris Lachapelle Doctoral Student Florida State University

157

APPENDIX C

Survey Results

158

Table 16. Survey Responses for Warm-up & Cooldown

A

ll o

f th

e ti

me

M

ost

of

the

tim

e

S

om

etim

es

R

arel

y

N

ever

A

ll o

f th

e ti

me

M

ost

of

the

tim

e

S

om

etim

es

R

arel

y

N

ever

New York 70 21 8 1 1 69.3 20.8 7.9 1.0 1.0

Florida 69 26 8 4 6 61.1 23.0 7.1 3.5 5.3

Ontario 172 20 6 2 1 85.6 10.0 3.0 1.0 0.5

Alberta 85 17 4 2 2 77.3 15.5 3.6 1.8 1.8

T otal 396 84 26 9 10 75.4 16.0 5.0 1.7 1.9

New York 47 26 15 9 1 48.0 26.5 15.3 9.2 1.0

Florida 64 28 12 5 3 57.1 25.0 10.7 4.5 2.7

Ontario 132 44 24 2 0 65.3 21.8 11.9 1.0 0.0

Alberta 75 26 8 1 0 68.2 23.6 7.3 0.9 0.0

T otal 318 124 59 17 4 60.9 23.8 11.3 3.3 0.8

New York 57 22 7 12 1 57.6 22.2 7.1 12.1 1.0

Florida 69 19 10 8 7 61.1 16.8 8.8 7.1 6.2

Ontario 133 38 12 6 11 66.5 19.0 6.0 3.0 5.5

Alberta 72 24 9 4 1 65.5 21.8 8.2 3.6 0.9

T otal 331 103 38 30 20 63.4 19.7 7.3 5.7 3.8

New York 22 39 27 2 4 23.4 41.5 28.7 2.1 4.3

Florida 47 30 20 2 12 42.3 27.0 18.0 1.8 10.8

Ontario 71 50 42 6 23 37.0 26.0 21.9 3.1 12.0

Alberta 25 43 32 5 3 23.1 39.8 29.6 4.6 2.8

T otal 165 162 121 15 42 32.7 32.1 24.0 3.0 8.3

New York 10 13 21 23 32 10.1 13.1 21.2 23.2 32.3

Florida 16 14 27 26 27 14.5 12.7 24.5 23.6 24.5

Ontario 27 24 39 35 77 13.4 11.9 19.3 17.3 38.1

Alberta 26 14 22 24 22 24.1 13.0 20.4 22.2 20.4

T otal 79 65 109 108 158 15.2 12.5 21.0 20.8 30.4

New York 11 10 19 21 39 11.0 10.0 19.0 21.0 39.0

Florida 10 12 28 25 36 9.0 10.8 25.2 22.5 32.4

Ontario 23 26 28 39 85 11.4 12.9 13.9 19.4 42.3

Alberta 25 12 17 25 30 22.9 11.0 15.6 22.9 27.5

T otal 69 60 92 110 190 13.2 11.5 17.7 21.1 36.5

20

Cooldown

Warm-up

17

18

19

37

SURVEY ANSWER (%)SURVEY ANSWER (Frequency)

CAT EGORY LOCATIONQUESTION (#)

21

159

Table 17. Survey Responses for Safety & Field

A

ll o

f th

e ti

me

M

ost

of

the

tim

e

S

om

etim

es

R

arel

y

N

ever

A

ll o

f th

e ti

me

M

ost

of

the

tim

e

S

om

etim

es

R

arel

y

N

ever

New York 57 13 8 0 17 60.0 13.7 8.4 0.0 17.9

Florida 74 25 6 0 8 65.5 22.1 5.3 0.0 7.1

Ontario 106 28 26 14 24 53.5 14.1 13.1 7.1 12.1

Alberta 63 19 9 5 12 58.3 17.6 8.3 4.6 11.1

Total 300 85 49 19 61 58.4 16.5 9.5 3.7 11.9

New York 42 45 7 0 0 44.7 47.9 7.4 0.0 0.0

Florida 65 32 13 0 3 57.5 28.3 11.5 0.0 2.7

Ontario 119 60 16 3 2 59.5 30.0 8.0 1.5 1.0

Alberta 66 29 14 0 0 60.6 26.6 12.8 0.0 0.0

Total 292 166 50 3 5 56.6 32.2 9.7 0.6 1.0

New York 28 35 15 13 4 29.5 36.8 15.8 13.7 4.2

Florida 44 40 20 5 5 38.6 35.1 17.5 4.4 4.4

Ontario 63 76 43 13 6 31.3 37.8 21.4 6.5 3.0

Alberta 39 35 26 7 1 36.1 32.4 24.1 6.5 0.9

Total 174 186 104 38 16 33.6 35.9 20.1 7.3 3.1

New York 37 26 25 4 3 38.9 27.4 26.3 4.2 3.2

Florida 52 37 21 1 3 45.6 32.5 18.4 0.9 2.6

Ontario 95 63 33 6 3 47.5 31.5 16.5 3.0 1.5

Alberta 43 31 24 9 2 39.4 28.4 22.0 8.3 1.8

Total 227 157 103 20 11 43.8 30.3 19.9 3.9 2.1

New York 40 24 7 15 6 43.5 26.1 7.6 16.3 6.5

Florida 69 24 12 0 7 61.6 21.4 10.7 0.0 6.3

Ontario 109 32 25 22 11 54.8 16.1 12.6 11.1 5.5

Alberta 57 15 12 17 7 52.8 13.9 11.1 15.7 6.5

Total 275 95 56 54 31 53.8 18.6 11.0 10.6 6.1

New York 69 23 4 1 0 71.1 23.7 4.1 1.0 0.0

Florida 88 15 6 1 3 77.9 13.3 5.3 0.9 2.7

Ontario 144 39 10 6 1 72.0 19.5 5.0 3.0 0.5

Alberta 89 18 2 0 0 81.7 16.5 1.8 0.0 0.0

Total 390 95 22 8 4 75.1 18.3 4.2 1.5 0.8

Field

25

26

27

29


CATEGORY LOCATIONQUESTION (#)

Safety

33

35

160

Table 18. Survey Responses for Water & Injury

A

ll o

f th

e ti

me

M

ost

of

the

tim

e

S

om

etim

es

R

arel

y

N

ever

A

ll o

f th

e ti

me

M

ost

of

the

tim

e

S

om

etim

es

R

arel

y

N

ever

New York 46 27 12 4 12 45.5 26.7 11.9 4.0 11.9

Florida 81 15 4 4 9 71.7 13.3 3.5 3.5 8.0

Ontario 119 45 17 7 12 59.5 22.5 8.5 3.5 6.0

Alberta 65 31 13 0 1 59.1 28.2 11.8 0.0 0.9

Total 311 118 46 15 34 59.4 22.5 8.8 2.9 6.5

New York 60 24 11 0 5 60.0 24.0 11.0 0.0 5.0

Florida 86 14 5 1 6 76.8 12.5 4.5 0.9 5.4

Ontario 139 39 8 6 10 68.8 19.3 4.0 3.0 5.0

Alberta 85 18 5 1 1 77.3 16.4 4.5 0.9 0.9

Total 370 95 29 8 22 70.6 18.1 5.5 1.5 4.2

New York 0 1 3 3 92 0.0 1.0 3.0 3.0 92.9

Florida 5 1 1 3 103 4.4 0.9 0.9 2.7 91.2

Ontario 4 1 3 6 188 2.0 0.5 1.5 3.0 93.1

Alberta 1 0 1 4 104 0.9 0.0 0.9 3.6 94.5

Total 10 3 8 16 487 1.9 0.6 1.5 3.1 92.9

New York 17 9 13 5 53 17.5 9.3 13.4 5.2 54.6

Florida 41 7 11 8 43 37.3 6.4 10.0 7.3 39.1

Ontario 52 16 36 15 79 26.3 8.1 18.2 7.6 39.9

Alberta 41 6 8 6 47 38.0 5.6 7.4 5.6 43.5

Total 151 38 68 34 222 29.4 7.4 13.3 6.6 43.3

New York 15 8 11 19 44 15.5 8.2 11.3 19.6 45.4

Florida 31 15 15 16 33 28.2 13.6 13.6 14.5 30.0

Ontario 53 20 34 32 60 26.6 10.1 17.1 16.1 30.2

Alberta 34 11 13 9 40 31.8 10.3 12.1 8.4 37.4

Total 133 54 73 76 177 25.9 10.5 14.2 14.8 34.5

New York 17 6 15 17 43 17.3 6.1 15.3 17.3 43.9

Florida 32 14 17 13 34 29.1 12.7 15.5 11.8 30.9

Ontario 57 15 31 31 65 28.6 7.5 15.6 15.6 32.7

Alberta 36 11 12 10 39 33.3 10.2 11.1 9.3 36.1

Total 142 46 75 71 181 27.6 8.9 14.6 13.8 35.1

New York 15 3 8 9 45 18.8 3.8 10.0 11.3 56.3

Florida 22 15 13 12 39 21.8 14.9 12.9 11.9 38.6

Ontario 34 22 18 28 92 17.5 11.3 9.3 14.4 47.4

Alberta 17 11 9 17 52 16.0 10.4 8.5 16.0 49.1

Total 88 51 48 66 228 18.3 10.6 10.0 13.7 47.4

12

13

Injury

14

15

SURVEY ANSWER (%)

Water

SURVEY ANSWER (Frequency)


24

22

23

161

Table 19. Survey Responses for Equipment

A

ll o

f th

e ti

me

M

ost

of

the

tim

e

S

om

etim

es

R

arel

y

N

ever

A

ll o

f th

e ti

me

M

ost

of

the

tim

e

S

om

etim

es

R

arel

y

N

ever

New York 1 4 6 7 80 1.0 4.1 6.1 7.1 81.6

Florida 11 6 13 18 63 9.9 5.4 11.7 16.2 56.8

Ontario 6 7 12 18 158 3.0 3.5 6.0 9.0 78.6

Alberta 0 4 5 10 88 0.0 3.7 4.7 9.3 82.2

Total 18 21 36 53 389 3.5 4.1 7.0 10.3 75.2

New York 17 8 8 16 43 18.5 8.7 8.7 17.4 46.7

Florida 18 15 21 22 35 16.2 13.5 18.9 19.8 31.5

Ontario 36 26 24 17 95 18.2 13.1 12.1 8.6 48.0

Alberta 16 9 12 19 52 14.8 8.3 11.1 17.6 48.1

Total 87 58 65 74 225 17.1 11.4 12.8 14.5 44.2

New York 28 31 19 11 5 29.8 33.0 20.2 11.7 5.3

Florida 36 29 29 9 8 32.4 26.1 26.1 8.1 7.2

Ontario 58 68 49 13 12 29.0 34.0 24.5 6.5 6.0

Alberta 39 37 24 5 3 36.1 34.3 22.2 4.6 2.8

Total 161 165 121 38 28 31.4 32.2 23.6 7.4 5.5

New York 50 27 14 2 1 53.2 28.7 14.9 2.1 1.1

Florida 75 21 9 2 6 66.4 18.6 8.0 1.8 5.3

Ontario 118 52 11 12 8 58.7 25.9 5.5 6.0 4.0

Alberta 76 27 5 1 0 69.7 24.8 4.6 0.9 0.0

Total 319 127 39 17 15 61.7 24.6 7.5 3.3 2.9

New York 44 31 15 2 1 47.3 33.3 16.1 2.2 1.1

Florida 74 21 9 2 7 65.5 18.6 8.0 1.8 6.2

Ontario 107 52 10 7 20 54.6 26.5 5.1 3.6 10.2

Alberta 73 27 6 1 2 67.0 24.8 5.5 0.9 1.8

Total 298 131 40 12 30 58.3 25.6 7.8 2.3 5.9

New York 1 26 21 25 9 1.2 31.7 25.6 30.5 11.0

Florida 0 57 23 13 6 0.0 57.6 23.2 13.1 6.1

Ontario 0 85 25 36 24 0.0 50.0 14.7 21.2 14.1

Alberta 0 52 17 20 12 0.0 51.5 16.8 19.8 11.9

Total 1 220 86 94 51 0.2 48.7 19.0 20.8 11.3

New York 44 36 12 1 4 45.4 37.1 12.4 1.0 4.1

Florida 75 24 8 2 5 65.8 21.1 7.0 1.8 4.4

Ontario 130 38 17 3 11 65.3 19.1 8.5 1.5 5.5

Alberta 71 20 12 4 2 65.1 18.3 11.0 3.7 1.8

Total 320 118 49 10 22 61.7 22.7 9.4 1.9 4.2

31

32

16

28

30



Equipment

34

36

162

Table 20. Survey Responses for Preseason

A

ll o

f th

e ti

me

M

ost

of

the

tim

e

S

om

etim

es

R

arel

y

N

ever

A

ll o

f th

e ti

me

M

ost

of

the

tim

e

S

om

etim

es

R

arel

y

N

ever

New York 41 14 6 1 36 41.8 14.3 6.1 1.0 36.7

Florida 55 8 9 8 29 50.5 7.3 8.3 7.3 26.6

Ontario 123 16 11 7 44 61.2 8.0 5.5 3.5 21.9

Alberta 63 3 4 3 34 58.9 2.8 3.7 2.8 31.8

Total 282 41 30 19 143 54.8 8.0 5.8 3.7 27.8

New York 7 5 6 6 73 7.2 5.2 6.2 6.2 75.3

Florida 22 6 10 13 58 20.2 5.5 9.2 11.9 53.2

Ontario 29 6 7 18 138 14.6 3.0 3.5 9.1 69.7

Alberta 17 5 6 8 71 15.9 4.7 5.6 7.5 66.4

Total 75 22 29 45 340 14.7 4.3 5.7 8.8 66.5

Preseason

11



10

163

Table 21. Question 3 – Location Comparison Results CAT EGORY LOCATION N MEAN ST D. DEV. F VALUE P VALUE

New York 104 4.186 0.723

Florida 114 4.166 0.928

Ontario 203 4.361 0.631

Alberta 110 4.366 0.592

Total 531 4.286 0.719

New York 98 2.449 1.289

Florida 110 2.868 1.457

Ontario 201 2.846 1.276

Alberta 108 2.759 1.436

Total 517 2.757 1.358

New York 98 2.303 1.323

Florida 112 2.883 1.373

Ontario 202 2.713 1.255

Alberta 110 2.777 1.387

Total 522 2.686 1.333

New York 102 3.167 0.740

Florida 114 3.386 0.771

Ontario 202 3.278 0.670

Alberta 110 3.406 0.443

Total 528 3.307 0.672

New York 97 4.186 0.830

Florida 114 4.386 0.784

Ontario 201 4.179 0.837

Alberta 109 4.280 0.806

Total 521 4.247 0.820

New York 101 2.411 1.307

Florida 112 2.545 1.228

Ontario 202 2.384 1.380

Alberta 109 2.876 1.483

Total 524 2.526 1.367

0.146

0.017

0.032

0.084

0.011

0.032

1.799

3.407

2.947

2.229

3.777

2.960

Safety

Cooldown

Warm-up

Preseason

Injury

Water

164

Table 22. Question 3 – Country Comparison Results CAT EGORY COUNTRY N MEAN STD. DEV. T VALUE P VALUE

USA 218 4.176 0.835

Canada 313 4.363 0.617

USA 208 2.671 1.393

Canada 309 2.816 1.333

USA 210 2.612 1.378

Canada 312 2.736 1.301

USA 216 3.282 0.763

Canada 312 3.323 0.602

USA 211 4.294 0.810

Canada 310 4.215 0.826

USA 213 2.481 1.264

Canada 311 2.556 1.434

2.819

1.036

1.190

0.657

1.084

0.632

0.279

0.528

0.005

0.235

0.301

0.512

Safety

Cooldown

Warm-up

Preseason

Injury

Water

Table 23. Question 4 – Location Comparison Results

CATEGORY LOCATION N MEAN STD. DEV. F VALUE P VALUE

New York 104 3.286 0.924

Florida 114 3.642 0.806

Ontario 203 3.410 0.810

Alberta 110 3.562 0.607

Total 531 3.467 0.804

New York 97 4.057 0.736

Florida 114 4.272 0.796

Ontario 201 4.177 0.705

Alberta 109 4.159 0.622

Total 521 4.172 0.717

0.004

0.189

4.496

1.597

Equipment

Field

Table 24. Question 4 – Country Comparison Results

CATEGORY COUNTRY N MEAN STD. DEV. T VALUE P VALUE

USA 218 3.472 0.880

Canada 313 3.464 0.747

USA 211 4.173 0.774

Canada 310 4.171 0.676

Equipment

Field

0.902

0.9720.036

0.123

165

Table 25. Question 5 – Warm-up & Preseason Results for Various Player Age Groups CAT EGORY PLAYER AGE COUNT RY N MEAN STD. DEV. DIFFERENCE F VALUE P VALUE

USA 23 3.873 1.083

Canada 49 4.068 0.692

Total 72 4.006 0.834

USA 36 4.238 0.758

Canada 65 4.324 0.687

Total 101 4.294 0.711

USA 86 4.266 0.692

Canada 81 4.481 0.503

Total 167 4.370 0.616

USA 27 4.176 0.717

Canada 45 4.398 0.562

Total 72 4.315 0.629

USA 28 4.027 1.072

Canada 43 4.517 0.591

Total 71 4.324 0.843

USA 16 4.297 1.030

Canada 30 4.333 0.588

Total 46 4.321 0.760

USA 216 4.179 0.837

Canada 313 4.363 0.617

Total 529 4.288 0.720

USA 21 1.929 1.228

Canada 48 3.042 1.263

Total 69 2.703 1.346

USA 36 2.639 1.524

Canada 65 2.677 1.464

Total 101 2.663 1.478

USA 81 2.698 1.378

Canada 79 2.551 1.285

Total 160 2.625 1.331

USA 26 2.942 1.203

Canada 45 2.867 1.424

Total 71 2.894 1.339

USA 26 2.865 1.432

Canada 42 3.060 1.196

Total 68 2.985 1.284

USA 16 2.906 1.474

Canada 30 3.033 1.245

Total 46 2.989 1.314

USA 206 2.677 1.395

Canada 309 2.816 1.333

Total 515 2.760 1.358

0.189

0.121

0.079

0.011

0.003

0.547

1.989

2.988

8.967

0.804

PLAYER AGE

COUNTRY

INTERACTION

PLAYER AGE

COUNTRY

INTERACTION

5-6.5 years

1.498

2.411Preseason 12-13.5 years

14-15.5 years

16-17.5 years

Total

7-8.5 years

9-11.5 years

Warm-up

5-6.5 years

7-8.5 years

9-11.5 years

12-13.5 years

14-15.5 years

16-17.5 years

Total

166

Table 26. Question 5 – Injury & Water Results for Various Player Age Groups

CATEGORY PLAYER AGE COUNTRY N MEAN STD. DEV. DIFFERENCE F VALUE P VALUE

USA 20 2.442 1.330

Canada 49 2.697 1.281

Total 69 2.623 1.290

USA 35 2.681 1.486

Canada 65 2.549 1.302

Total 100 2.595 1.363

USA 83 2.576 1.470

Canada 81 2.799 1.360

Total 164 2.687 1.417

USA 27 2.911 1.276

Canada 45 2.882 1.348

Total 72 2.892 1.312

USA 27 2.725 1.171

Canada 42 2.857 1.273

Total 69 2.806 1.227

USA 16 2.354 1.261

Canada 30 2.642 1.185

Total 46 2.542 1.206

USA 208 2.627 1.377

Canada 312 2.736 1.301

Total 520 2.692 1.332

USA 22 3.273 0.808

Canada 49 3.238 0.808

Total 71 3.249 0.802

USA 36 3.324 0.826

Canada 65 3.221 0.649

Total 101 3.257 0.715

USA 85 3.243 0.706

Canada 81 3.397 0.461

Total 166 3.318 0.602

USA 27 3.469 0.636

Canada 45 3.474 0.359

Total 72 3.472 0.477

USA 28 3.214 0.876

Canada 42 3.325 0.685

Total 70 3.281 0.763

USA 16 3.313 0.839

Canada 30 3.256 0.585

Total 46 3.275 0.675

USA 214 3.290 0.758

Canada 312 3.323 0.602

Total 526 3.310 0.670

7-8.5 years

9-11.5 years

0.987

Injury 12-13.5 years

14-15.5 years

16-17.5 years

Total

5-6.5 years

PLAYER AGE

COUNTRY

INTERACTION

5-6.5 years

7-8.5 years

Water

9-11.5 years

12-13.5 years

14-15.5 years

16-17.5 years

Total

PLAYER AGE

COUNTRY

INTERACTION

0.716 0.612

0.854

0.314

0.356

0.905

0.425

0.850

0.716

0.036

0.580

167

Table 27. Question 5 – Safety & Cooldown Results for Various Player Age Groups


USA 23 4.152 0.897

Canada 49 3.929 0.823

Total 72 4.000 0.848

USA 35 4.614 0.654

Canada 64 4.180 0.828

Total 99 4.333 0.795

USA 81 4.451 0.696

Canada 80 4.531 0.628

Total 161 4.491 0.663

USA 27 4.167 0.707

Canada 44 4.250 0.852

Total 71 4.218 0.796

USA 28 3.857 1.044

Canada 43 4.267 0.804

Total 71 4.106 0.922

USA 15 4.033 0.743

Canada 30 3.783 0.980

Total 45 3.867 0.907

USA 209 4.299 0.803

Canada 310 4.215 0.826

Total 519 4.249 0.817

USA 21 2.214 1.261

Canada 49 1.888 1.347

Total 70 1.986 1.321

USA 36 2.653 1.281

Canada 65 2.377 1.364

Total 101 2.475 1.335

USA 84 2.494 1.352

Canada 80 2.675 1.380

Total 164 2.582 1.365

USA 27 2.222 1.121

Canada 45 2.711 1.528

Total 72 2.528 1.401

USA 27 2.630 1.229

Canada 42 3.048 1.378

Total 69 2.884 1.329

USA 16 2.625 1.103

Canada 30 2.800 1.460

Total 46 2.739 1.336

USA 211 2.486 1.266

Canada 311 2.556 1.434

Total 522 2.528 1.368

12-13.5 years

12-13.5 years

14-15.5 years

PLAYER AGE

COUNTRY

INTERACTION

14-15.5 years

Cooldown

16-17.5 years

Total

5-6.5 years

7-8.5 years

Safety

5-6.5 years

7-8.5 years

9-11.5 years

9-11.5 years

16-17.5 years

Total

0.000

0.475

0.016

0.680

1.149

6.784

0.511

2.828

0.036

0.410

0.333

PLAYER AGE

COUNTRY

INTERACTION

2.401

168

Table 28. Question 5 – Equipment & Field Results for Various Player Age Groups


USA 23 3.475 0.896

Canada 49 3.305 0.680

Total 72 3.359 0.753

USA 36 3.564 0.790

Canada 65 3.437 0.748

Total 101 3.482 0.762

USA 86 3.509 0.908

Canada 81 3.725 0.683

Total 167 3.614 0.811

USA 27 3.583 0.531

Canada 45 3.524 0.745

Total 72 3.546 0.669

USA 28 3.443 0.997

Canada 43 3.354 0.824

Total 71 3.389 0.890

USA 16 2.920 1.029

Canada 30 3.139 0.728

Total 46 3.063 0.840

USA 216 3.472 0.877

Canada 313 3.464 0.747

Total 529 3.467 0.802

USA 22 4.341 0.650

Canada 49 4.117 0.666

Total 71 4.187 0.664

USA 35 4.195 0.630

Canada 64 4.190 0.666

Total 99 4.192 0.650

USA 82 4.184 0.779

Canada 80 4.294 0.611

Total 162 4.238 0.701

USA 27 4.389 0.582

Canada 44 4.089 0.694

Total 71 4.203 0.665

USA 28 3.851 1.001

Canada 43 4.258 0.721

Total 71 4.097 0.859

USA 15 4.133 0.915

Canada 30 3.883 0.730

Total 45 3.967 0.795

USA 209 4.181 0.772

Canada 310 4.171 0.676

Total 519 4.175 0.715

0.277

0.535

0.033

1.266

0.386

2.451

16-17.5 years

Total

Field

5-6.5 years

7-8.5 years

9-11.5 years

12-13.5 years

14-15.5 years

PLAYER AGE

COUNTRY

INTERACTION

0.000

1.084

0.983

0.368

Equipment

5-6.5 years

COUNTRY

INTERACTION

7-8.5 years

9-11.5 years

12-13.5 years

14-15.5 years

16-17.5 years

Total

PLAYER AGE 4.152 0.001

169

Table 29. Question 6 (Child) – Warm-up & Preseason Results CAT EGORY LOCATION CHILD N MEAN ST D. DEV. DIFFERENCE F VALUE P VALUE

No 26 4.394 0.549

Yes 77 4.108 0.765

Total 103 4.180 0.725

No 31 4.129 0.970

Yes 82 4.203 0.897

Total 113 4.183 0.914

No 67 4.403 0.584

Yes 134 4.341 0.653

Total 201 4.362 0.630

No 18 4.597 0.404

Yes 92 4.321 0.613

Total 110 4.366 0.592

No 142 4.366 0.673

Yes 385 4.260 0.728

Total 527 4.289 0.715

No 23 2.826 1.362

Yes 74 2.324 1.259

Total 97 2.443 1.295

No 30 3.300 1.579

Yes 80 2.706 1.384

Total 110 2.868 1.457

No 66 2.962 1.188

Yes 133 2.790 1.325

Total 199 2.847 1.280

No 18 3.500 1.465

Yes 90 2.611 1.392

Total 108 2.759 1.436

No 137 3.084 1.351

Yes 377 2.638 1.347

Total 514 2.757 1.361

Total

Warm-up

New York

Florida

Ontario

Alberta

Preseason

New York

Florida

Ontario CHILD

INTERACTION

Alberta

Total

LOCATION

CHILD

INTERACTION

LOCATION 1.792

13.429

1.249

0.148

0.000

0.291

1.248

0.043

0.072

0.292

2.740

3.249

170

Table 30. Question 6 (Child) – Injury & Water Results

CATEGORY LOCATION CHILD N MEAN STD. DEV. DIFFERENCE F VALUE P VALUE

No 24 2.684 1.348

Yes 73 2.188 1.307

Total 97 2.311 1.328

No 30 3.283 1.288

Yes 81 2.758 1.377

Total 111 2.900 1.368

No 66 2.984 1.207

Yes 134 2.581 1.271

Total 200 2.714 1.262

No 18 3.250 1.197

Yes 92 2.685 1.408

Total 110 2.777 1.387

No 138 3.031 1.252

Yes 380 2.568 1.344

Total 518 2.692 1.335

No 25 3.427 0.523

Yes 76 3.079 0.787

Total 101 3.165 0.743

No 31 3.323 0.905

Yes 82 3.423 0.714

Total 113 3.395 0.768

No 66 3.253 0.654

Yes 134 3.275 0.667

Total 200 3.268 0.661

No 18 3.574 0.251

Yes 92 3.373 0.466

Total 110 3.406 0.443

No 140 3.341 0.666

Yes 384 3.291 0.671

Total 524 3.304 0.669

0.971

3.012

12.072

0.080

1.949

2.214

2.073

0.121

0.137

0.103

Water

New York

Florida

Ontario

Alberta

Total

New York

Florida

INTERACTION

Injury

LOCATION

CHILD

0.030

0.001

Ontario

Alberta

Total

LOCATION

CHILD

INTERACTION

171

Table 31. Question 6 (Child) – Safety & Cooldown Results


No 25 4.020 0.872

Yes 71 4.254 0.815

Total 96 4.193 0.832

No 31 4.210 0.920

Yes 82 4.463 0.719

Total 113 4.394 0.783

No 67 4.119 0.862

Yes 132 4.212 0.822

Total 199 4.181 0.835

No 18 3.722 0.878

Yes 91 4.390 0.748

Total 109 4.280 0.806

No 141 4.071 0.882

Yes 376 4.318 0.785

Total 517 4.251 0.819

No 25 2.660 1.367

Yes 75 2.313 1.286

Total 100 2.400 1.309

No 30 3.017 1.185

Yes 81 2.383 1.208

Total 111 2.554 1.229

No 66 2.530 1.406

Yes 134 2.325 1.371

Total 200 2.393 1.383

No 18 3.944 1.423

Yes 91 2.665 1.408

Total 109 2.876 1.483

No 139 2.842 1.421

Yes 381 2.416 1.333

Total 520 2.530 1.369

Safety

New York

1.681

12.686

1.895

LOCATION

CHILD

INTERACTION

0.170

0.000

0.129

Florida

Ontario

Alberta

Total

Cooldown

New York

LOCATION

CHILD

INTERACTION

6.814

18.059

2.567

Florida

Ontario

Alberta

Total

0.000

0.000

0.054

172

Table 32. Question 6 (Child) – Equipment & Field Results


No 26 3.397 0.922

Yes 77 3.263 0.924

Total 103 3.297 0.921

No 31 3.568 1.084

Yes 82 3.669 0.684

Total 113 3.642 0.809

No 67 3.295 0.787

Yes 134 3.482 0.815

Total 201 3.419 0.808

No 18 3.627 0.582

Yes 92 3.549 0.614

Total 110 3.562 0.607

No 142 3.415 0.865

Yes 385 3.494 0.778

Total 527 3.473 0.802

No 24 4.115 0.737

Yes 72 4.042 0.744

Total 96 4.060 0.739

No 31 4.062 1.070

Yes 82 4.371 0.633

Total 113 4.286 0.785

No 67 4.119 0.701

Yes 132 4.218 0.697

Total 199 4.185 0.698

No 18 4.088 0.551

Yes 91 4.173 0.637

Total 109 4.159 0.622

No 140 4.102 0.780

Yes 377 4.207 0.685

Total 517 4.178 0.712

Equipment

New York

LOCATION

CHILD

INTERACTION

2.886

0.048

0.934

Florida

Ontario

Alberta

Total

0.035

0.826

0.424

Field

New York

LOCATION

CHILD

INTERACTION

0.551

1.856

Florida

Ontario

Alberta

Total

0.648

0.174

0.3930.998

173

Table 33. Question 6 (Enjoy) – Warm-up & Preseason Results CAT EGORY LOCATION ENJOY N MEAN STD. DEV. DIFFERENCE F VALUE P VALUE

No 38 3.963 0.825

Yes 66 4.314 0.629

Total 104 4.186 0.723

No 42 3.958 1.046

Yes 72 4.287 0.835

Total 114 4.166 0.928

No 76 4.168 0.668

Yes 127 4.476 0.581

Total 203 4.361 0.631

No 37 4.293 0.638

Yes 73 4.403 0.568

Total 110 4.366 0.592

No 193 4.106 0.795

Yes 338 4.389 0.652

Total 531 4.286 0.719

No 36 2.222 1.355

Yes 62 2.581 1.242

Total 98 2.449 1.289

No 40 2.763 1.502

Yes 70 2.929 1.438

Total 110 2.868 1.457

No 76 2.816 1.283

Yes 125 2.864 1.277

Total 201 2.846 1.276

No 36 2.931 1.522

Yes 72 2.674 1.395

Total 108 2.759 1.436

No 188 2.713 1.403

Yes 329 2.783 1.333

Total 517 2.757 1.358

Total

Warm-up

New York

Florida

Ontario

Alberta

Preseason

New York

Florida

Ontario ENJOY

INTERACTION

Alberta

Total

LOCATION

ENJOY

INTERACTION

LOCATION 2.505

0.372

0.857

0.058

0.542

0.463

0.628

0.021

0.000

0.597

3.260

17.309

174

Table 34. Question 6 (Enjoy) – Injury & Water Results

CATEGORY LOCATION ENJOY N MEAN STD. DEV. DIFFERENCE F VALUE P VALUE

No 35 1.910 1.212

Yes 63 2.521 1.341

Total 98 2.303 1.323

No 41 2.896 1.367

Yes 71 2.876 1.387

Total 112 2.883 1.373

No 76 2.309 1.159

Yes 126 2.956 1.253

Total 202 2.713 1.255

No 37 2.795 1.382

Yes 73 2.768 1.399

Total 110 2.777 1.387

No 189 2.458 1.301

Yes 333 2.816 1.335

Total 522 2.686 1.333

No 37 2.937 0.842

Yes 65 3.297 0.646

Total 102 3.167 0.740

No 42 3.206 0.874

Yes 72 3.491 0.690

Total 114 3.386 0.771

No 76 3.160 0.771

Yes 126 3.349 0.593

Total 202 3.278 0.670

No 37 3.243 0.507

Yes 73 3.489 0.385

Total 110 3.406 0.443

No 192 3.143 0.768

Yes 336 3.400 0.592

Total 528 3.307 0.672

0.059

4.784

5.938

2.494

2.922

18.908

0.379

0.034

0.000

0.768

Water

New York

Florida

Ontario

Alberta

Total

New York

Florida

INTERACTION

Injury

LOCATION

ENJOY

0.003

0.015

Ontario

Alberta

Total

LOCATION

ENJOY

INTERACTION

175

Table 35. Question 6 (Enjoy) – Safety & Cooldown Results


No 36 3.972 0.971

Yes 61 4.312 0.714

Total 97 4.186 0.830

No 42 4.286 0.970

Yes 72 4.444 0.653

Total 114 4.386 0.784

No 74 4.000 0.958

Yes 127 4.284 0.742

Total 201 4.179 0.837

No 36 4.528 0.676

Yes 73 4.158 0.841

Total 109 4.280 0.806

No 188 4.160 0.934

Yes 333 4.296 0.745

Total 521 4.247 0.820

No 37 1.973 1.099

Yes 64 2.664 1.357

Total 101 2.411 1.307

No 40 2.675 1.444

Yes 72 2.472 1.094

Total 112 2.545 1.228

No 76 1.987 1.317

Yes 126 2.623 1.366

Total 202 2.384 1.380

No 37 2.905 1.518

Yes 72 2.861 1.476

Total 109 2.876 1.483

No 190 2.308 1.396

Yes 334 2.650 1.336

Total 524 2.526 1.367

Safety

New York

2.711

1.786

4.150

LOCATION

ENJOY

INTERACTION

0.044

0.182

0.006

Florida

Ontario

Alberta

Total

Cooldown

New York

LOCATION

ENJOY

INTERACTION

4.651

4.526

3.383

Florida

Ontario

Alberta

Total

0.003

0.034

0.018

176

Table 36. Question 6 (Enjoy) – Equipment & Field Results


No 38 3.103 0.824

Yes 66 3.391 0.967

Total 104 3.286 0.924

No 42 3.588 0.939

Yes 72 3.674 0.722

Total 114 3.642 0.806

No 76 3.084 0.859

Yes 127 3.606 0.714

Total 203 3.410 0.810

No 37 3.587 0.719

Yes 73 3.549 0.547

Total 110 3.562 0.607

No 193 3.294 0.874

Yes 338 3.566 0.744

Total 531 3.467 0.804

No 35 3.833 0.855

Yes 62 4.183 0.632

Total 97 4.057 0.736

No 42 4.105 0.945

Yes 72 4.369 0.683

Total 114 4.272 0.796

No 74 3.989 0.734

Yes 127 4.287 0.666

Total 201 4.177 0.705

No 36 4.266 0.570

Yes 73 4.106 0.643

Total 109 4.159 0.622

No 187 4.039 0.789

Yes 334 4.246 0.662

Total 521 4.172 0.717

Equipment

New York

LOCATION

ENJOY

INTERACTION

5.883

8.541

3.424

Florida

Ontario

Alberta

Total

0.001

0.004

0.017

Field

New York

LOCATION

ENJOY

INTERACTION

1.844

7.813

Florida

Ontario

Alberta

Total

0.138

0.005

0.0402.797

177

Table 37. Question 6 (Community) – Warm-up & Preseason Results

CATEGORY LOCAT ION COMMUNITY N MEAN STD. DEV. DIFFERENCE F VALUE P VALUE

No 66 4.080 0.800

Yes 38 4.371 0.525

Total 104 4.186 0.723

No 59 4.030 1.036

Yes 55 4.312 0.778

Total 114 4.166 0.928

No 137 4.297 0.623

Yes 65 4.523 0.586

Total 202 4.370 0.619

No 65 4.319 0.632

Yes 45 4.433 0.527

Total 110 4.366 0.592

No 327 4.210 0.758

Yes 203 4.418 0.623

Total 530 4.289 0.716

No 62 2.274 1.190

Yes 36 2.750 1.412

Total 98 2.449 1.289

No 57 2.711 1.467

Yes 53 3.038 1.441

Total 110 2.868 1.457

No 136 2.658 1.250

Yes 64 3.250 1.257

Total 200 2.848 1.279

No 63 2.683 1.429

Yes 45 2.867 1.455

Total 108 2.759 1.436

No 318 2.598 1.320

Yes 198 3.015 1.384

Total 516 2.758 1.359

Alberta

Total

Ontario

0.079

0.002

0.638

2.273

9.794

0.565

LOCATION

COMMUNITY

Preseason

New York

Florida

Total

Warm-up

New York

Florida

Ontario

Alberta

INT ERACTION

LOCATION

COMMUNITY

INT ERACTION

3.447

12.264

0.353

0.017

0.001

0.787

178

Table 38. Question 6 (Community) – Injury & Water Results

CATEGORY LOCATION COMMUNITY N MEAN STD. DEV. DIFFERENCE F VALUE P VALUE

No 63 2.138 1.309

Yes 35 2.600 1.316

Total 98 2.303 1.323

No 58 2.655 1.295

Yes 54 3.128 1.425

Total 112 2.883 1.373

No 136 2.645 1.246

Yes 65 2.873 1.271

Total 201 2.719 1.256

No 65 2.683 1.394

Yes 45 2.910 1.381

Total 110 2.777 1.387

No 322 2.555 1.309

Yes 199 2.903 1.348

Total 521 2.688 1.333

No 65 3.067 0.767

Yes 37 3.342 0.664

Total 102 3.167 0.740

No 59 3.243 0.877

Yes 55 3.539 0.610

Total 114 3.386 0.771

No 136 3.288 0.646

Yes 65 3.251 0.724

Total 201 3.276 0.671

No 65 3.349 0.462

Yes 45 3.489 0.406

Total 110 3.406 0.443

No 325 3.248 0.692

Yes 202 3.399 0.630

Total 527 3.306 0.673

0.033

0.005

2.941

0.058

0.006

0.130

2.505

7.499

1.891INTERACTION

New York

Florida

Ontario

Alberta

Total

LOCATION

COMMUNITY

Injury

LOCATION

COMMUNITY

INTERACTION

Total

7.961

0.325 0.807

Water

New York

Florida

Ontario

Alberta

179

Table 39. Question 6 (Community) – Safety & Cooldown Results


No 61 4.131 0.926

Yes 36 4.278 0.638

Total 97 4.186 0.830

No 59 4.398 0.803

Yes 55 4.373 0.771

Total 114 4.386 0.784

No 135 4.063 0.830

Yes 65 4.431 0.805

Total 200 4.183 0.838

No 65 4.292 0.814

Yes 44 4.261 0.803

Total 109 4.280 0.806

No 320 4.184 0.848

Yes 200 4.350 0.765

Total 520 4.248 0.820

No 65 2.323 1.350

Yes 36 2.569 1.226

Total 101 2.411 1.307

No 58 2.448 1.220

Yes 54 2.648 1.239

Total 112 2.545 1.228

No 136 2.173 1.324

Yes 65 2.846 1.392

Total 201 2.391 1.380

No 64 2.672 1.510

Yes 45 3.167 1.410

Total 109 2.876 1.483

No 323 2.351 1.358

Yes 200 2.815 1.335

Total 523 2.529 1.366

LOCATION

COMMUNITY

INTERACTION

Total

0.001

Florida

Ontario

Alberta

Cooldown

New York

0.432

2.721

10.376

0.917

LOCATION

COMMUNITY

INTERACTION

0.044

Florida

Ontario

Alberta

Total

0.995

2.259

1.922

0.395

0.133Safety

New York

0.125

180

Table 40. Question 6 (Community) – Equipment & Field Results


No 66 3.147 0.975

Yes 38 3.528 0.780

Total 104 3.286 0.924

No 59 3.463 0.850

Yes 55 3.835 0.714

Total 114 3.642 0.806

No 137 3.294 0.788

Yes 65 3.657 0.812

Total 202 3.411 0.812

No 65 3.582 0.533

Yes 45 3.532 0.705

Total 110 3.562 0.607

No 327 3.352 0.810

Yes 203 3.653 0.762

Total 530 3.467 0.804

No 60 3.943 0.798

Yes 37 4.241 0.585

Total 97 4.057 0.736

No 59 4.153 0.843

Yes 55 4.400 0.727

Total 114 4.272 0.796

No 135 4.086 0.700

Yes 65 4.392 0.647

Total 200 4.185 0.697

No 65 4.123 0.656

Yes 44 4.212 0.571

Total 109 4.159 0.622

No 319 4.079 0.739

Yes 201 4.327 0.644

Total 520 4.175 0.714

Total

12.789

Florida

Ontario

Alberta

Field

New York

0.584

0.239

0.000

0.626

LOCATION

COMMUNITY

INTERACTION

1.411

0.031

0.000

0.112

LOCATION

COMMUNITY

INTERACTION

2.990

13.497Equipment

New York

2.005

Florida

Ontario

Alberta

Total

181

Table 41. Question 7 (First Aid) – Warm-up & Preseason Results CAT EGORY LOCATION FIRST AID N MEAN STD. DEV. DIFFERENCE F VALUE P VALUE

No 60 4.143 0.767

Yes 44 4.244 0.664

Total 104 4.186 0.723

No 58 3.993 1.044

Yes 56 4.345 0.757

Total 114 4.166 0.928

No 98 4.227 0.663

Yes 105 4.486 0.576

Total 203 4.361 0.631

No 53 4.344 0.631

Yes 57 4.386 0.557

Total 110 4.366 0.592

No 269 4.181 0.782

Yes 262 4.393 0.632

Total 531 4.286 0.719

No 57 2.307 1.284

Yes 41 2.646 1.286

Total 98 2.449 1.289

No 54 2.732 1.472

Yes 56 3.000 1.443

Total 110 2.868 1.457

No 97 2.572 1.301

Yes 104 3.101 1.204

Total 201 2.846 1.276

No 53 2.802 1.570

Yes 55 2.718 1.308

Total 108 2.759 1.436

No 261 2.594 1.395

Yes 256 2.924 1.300

Total 517 2.757 1.358

1.176

0.043

0.003

0.318

2.734

0.867

1.856

4.534

1.227

0.136

0.034

0.299

LOCATION

FIRST AID

INTERACTION

LOCATION

Alberta

Total

Florida

Ontario FIRST AID

INTERACTION

Preseason

New York

Total

Warm-up

New York

Florida

Ontario

Alberta

182

Table 42. Question 7 (First Aid) – Injury & Water Results

CATEGORY LOCATION FIRST AID N MEAN STD. DEV. DIFFERENCE F VALUE P VALUE

No 56 2.034 1.184

Yes 42 2.661 1.425

Total 98 2.303 1.323

No 56 2.821 1.445

Yes 56 2.945 1.308

Total 112 2.883 1.373

No 98 2.446 1.200

Yes 104 2.964 1.260

Total 202 2.713 1.255

No 53 2.671 1.469

Yes 57 2.876 1.311

Total 110 2.777 1.387

No 263 2.484 1.330

Yes 259 2.891 1.306

Total 522 2.686 1.333

No 59 3.170 0.779

Yes 43 3.163 0.691

Total 102 3.167 0.740

No 58 3.345 0.930

Yes 56 3.429 0.568

Total 114 3.386 0.771

No 98 3.063 0.799

Yes 104 3.481 0.435

Total 202 3.278 0.670

No 53 3.333 0.489

Yes 57 3.474 0.388

Total 110 3.406 0.443

No 268 3.201 0.781

Yes 260 3.415 0.517

Total 528 3.307 0.672

Ontario

Alberta

Total

LOCATION

FIRST AID

INTERACTION

0.024

0.002

INTERACTION

Injury

LOCATION

FIRST AID

Water

New York

Florida

Ontario

Alberta

Total

New York

Florida

3.062

7.104

3.036

0.028

0.008

0.029

0.397

3.160

9.457

0.991

183

Table 43. Question 7 (First Aid) – Safety & Cooldown Results


No 56 4.143 0.862

Yes 41 4.244 0.792

Total 97 4.186 0.830

No 58 4.405 0.901

Yes 56 4.366 0.650

Total 114 4.386 0.784

No 96 4.094 0.936

Yes 105 4.257 0.731

Total 201 4.179 0.837

No 52 4.433 0.721

Yes 57 4.140 0.860

Total 109 4.280 0.806

No 262 4.241 0.882

Yes 259 4.253 0.754

Total 521 4.247 0.820

No 59 2.263 1.334

Yes 42 2.619 1.253

Total 101 2.411 1.307

No 56 2.295 1.190

Yes 56 2.795 1.224

Total 112 2.545 1.228

No 98 2.122 1.294

Yes 104 2.630 1.418

Total 202 2.384 1.380

No 52 2.856 1.496

Yes 57 2.895 1.484

Total 109 2.876 1.483

No 265 2.334 1.344

Yes 259 2.722 1.365

Total 524 2.526 1.367

0.017

0.004

0.489

3.412

8.160

0.809

Florida

Ontario

Alberta

Total

Cooldown

New York

LOCATION

FIRST AID

INTERACTION

0.141

0.823

0.118

Florida

Ontario

Alberta

Total

Safety

New York

1.829

0.050

1.965

LOCATION

FIRST AID

INTERACTION

184

Table 44. Question 7 (First Aid) – Equipment & Field Results


No 60 3.234 0.927

Yes 44 3.357 0.925

Total 104 3.286 0.924

No 58 3.628 0.797

Yes 56 3.657 0.822

Total 114 3.642 0.806

No 98 3.232 0.828

Yes 105 3.576 0.759

Total 203 3.410 0.810

No 53 3.629 0.696

Yes 57 3.499 0.509

Total 110 3.562 0.607

No 269 3.396 0.839

Yes 262 3.540 0.760

Total 531 3.467 0.804

No 56 4.066 0.730

Yes 41 4.045 0.752

Total 97 4.057 0.736

No 58 4.198 0.889

Yes 56 4.348 0.685

Total 114 4.272 0.796

No 96 4.046 0.742

Yes 105 4.297 0.649

Total 201 4.177 0.705

No 52 4.154 0.634

Yes 57 4.164 0.615

Total 109 4.159 0.622

No 262 4.105 0.754

Yes 259 4.239 0.672

Total 521 4.172 0.717

0.182

0.136

0.3501.097

Florida

Ontario

Alberta

Total

0.004

0.203

0.068

Field

New York

LOCATION

FIRST AID

INTERACTION

1.625

2.231

2.388

Florida

Ontario

Alberta

Total

Equipment

New York

LOCATION

FIRST AID

INTERACTION

4.439

1.624

185

Table 45. Question 7 (CPR) – Warm-up & Preseason Results CAT EGORY LOCATION CPR N MEAN STD. DEV. DIFFERENCE F VALUE P VALUE

No 64 4.145 0.739

Yes 40 4.252 0.700

T otal 104 4.186 0.723

No 56 4.005 1.061

Yes 58 4.322 0.754

T otal 114 4.166 0.928

No 114 4.233 0.654

Yes 89 4.525 0.563

T otal 203 4.361 0.631

No 63 4.294 0.638

Yes 47 4.463 0.513

T otal 110 4.366 0.592

No 297 4.184 0.764

Yes 234 4.416 0.636

T otal 531 4.286 0.719

No 62 2.476 1.288

Yes 36 2.403 1.308

T otal 98 2.449 1.289

No 52 2.817 1.498

Yes 58 2.914 1.430

T otal 110 2.868 1.457

No 113 2.624 1.291

Yes 88 3.131 1.205

T otal 201 2.846 1.276

No 62 2.742 1.544

Yes 46 2.783 1.294

T otal 108 2.759 1.436

No 289 2.652 1.384

Yes 228 2.890 1.315

T otal 517 2.757 1.358

0.584

0.018

0.001

0.626

3.367

11.837

2.428

1.294

1.336

0.065

0.256

0.262

LOCAT ION

CPR

INT ERACTION

LOCAT ION

Alberta

Total

Florida

Ontario CPR

INT ERACTION

Preseason

New York

Total

Warm-up

New York

Florida

Ontario

Alberta

186

Table 46. Question 7 (CPR) – Injury & Water Results

CATEGORY LOCATION CPR N MEAN STD. DEV. DIFFERENCE F VALUE P VALUE

No 61 2.157 1.224

Yes 37 2.543 1.458

Total 98 2.303 1.323

No 54 2.836 1.448

Yes 58 2.927 1.312

Total 112 2.883 1.373

No 114 2.415 1.166

Yes 88 3.099 1.268

Total 202 2.713 1.255

No 63 2.677 1.413

Yes 47 2.911 1.355

Total 110 2.777 1.387

No 292 2.495 1.304

Yes 230 2.928 1.333

Total 522 2.686 1.333

No 63 3.143 0.703

Yes 39 3.205 0.804

Total 102 3.167 0.740

No 56 3.381 0.913

Yes 58 3.391 0.612

Total 114 3.386 0.714

No 114 3.110 0.762

Yes 88 3.496 0.443

Total 202 3.278 0.670

No 63 3.349 0.517

Yes 47 3.482 0.309

Total 110 3.406 0.443

No 296 3.219 0.743

Yes 232 3.418 0.550

Total 528 3.307 0.672

Ontario

Alberta

Total

LOCATION

CPR

INTERACTION

0.023

0.004

INTERACTION

Injury

LOCATION

CPR

Water

New York

Florida

Ontario

Alberta

Total

New York

Florida

2.754

6.014

2.548

0.042

0.015

0.055

0.226

3.203

8.356

1.456

187

Table 47. Question 7 (CPR) – Safety & Cooldown Results


No 61 4.082 0.900

Yes 36 4.361 0.672

Total 97 4.186 0.830

No 56 4.348 0.948

Yes 58 4.422 0.591

Total 114 4.386 0.784

No 112 4.040 0.896

Yes 89 4.354 0.724

Total 201 4.179 0.837

No 62 4.290 0.797

Yes 47 4.266 0.827

Total 109 4.280 0.806

No 291 4.162 0.892

Yes 230 4.354 0.705

Total 521 4.247 0.820

No 63 2.278 1.253

Yes 38 2.632 1.379

Total 101 2.411 1.307

No 54 2.380 1.228

Yes 58 2.698 1.217

Total 112 2.545 1.228

No 114 2.079 1.253

Yes 88 2.778 1.442

Total 202 2.384 1.380

No 62 2.855 1.469

Yes 47 2.904 1.517

Total 109 2.876 1.483

No 293 2.341 1.323

Yes 231 2.760 1.388

Total 524 2.526 1.367

0.037

0.004

0.221

2.857

8.291

1.472

Florida

Ontario

Alberta

Total

Cooldown

New York

LOCATION

CPR

INTERACTION

0.247

0.033

0.280

Florida

Ontario

Alberta

Total

Safety

New York

1.384

4.567

1.283

LOCATION

CPR

INTERACTION

188

Table 48. Question 7 (CPR) – Equipment & Field Results


No 64 3.237 0.885

Yes 40 3.364 0.988

Total 104 3.286 0.924

No 56 3.601 0.877

Yes 58 3.682 0.736

Total 114 3.642 0.806

No 114 3.232 0.800

Yes 89 3.639 0.767

Total 203 3.410 0.810

No 63 3.563 0.663

Yes 47 3.560 0.530

Total 110 3.562 0.607

No 297 3.373 0.822

Yes 234 3.587 0.765

Total 531 3.467 0.804

No 61 3.995 0.737

Yes 36 4.162 0.732

Total 97 4.057 0.736

No 56 4.118 0.999

Yes 58 4.421 0.497

Total 114 4.272 0.796

No 112 4.035 0.730

Yes 89 4.356 0.632

Total 201 4.177 0.705

No 62 4.133 0.662

Yes 47 4.193 0.569

Total 109 4.159 0.622

No 291 4.063 0.775

Yes 230 4.309 0.610

Total 521 4.172 0.717

0.282

0.001

0.4180.947

Florida

Ontario

Alberta

Total

0.009

0.034

0.110

Field

New York

LOCATION

CPR

INTERACTION

1.277

10.623

2.022

Florida

Ontario

Alberta

Total

Equipment

New York

LOCATION

CPR

INTERACTION

3.892

4.525

189

Table 49. Question 8 – Results for Various Coach Age Groups CAT EGORY COACH'S AGE N MEAN STD. DEV. F VALUE P VALUE

<30 years 71 4.299 0.684

30-39 years 180 4.163 0.772

40-49 years 211 4.375 0.629

50+ years 56 4.240 0.890

Total 518 4.276 0.723

<30 years 69 3.203 1.389

30-39 years 175 2.620 1.344

40-49 years 207 2.730 1.322

50+ years 54 2.759 1.456

Total 505 2.759 1.362

<30 years 70 3.268 1.193

30-39 years 178 2.645 1.409

40-49 years 207 2.560 1.299

50+ years 55 2.526 1.230

Total 510 2.683 1.335

<30 years 71 3.409 0.583

30-39 years 178 3.202 0.774

40-49 years 210 3.350 0.580

50+ years 56 3.321 0.699

Total 515 3.304 0.669

<30 years 71 3.944 0.881

30-39 years 177 4.186 0.856

40-49 years 206 4.396 0.767

50+ years 55 4.264 0.713

Total 509 4.246 0.822

<30 years 69 2.978 1.501

30-39 years 178 2.197 1.284

40-49 years 208 2.683 1.311

50+ years 56 2.429 1.469

Total 511 2.525 1.371

<30 years 71 3.449 0.737

30-39 years 180 3.367 0.799

40-49 years 211 3.543 0.772

50+ years 56 3.509 0.905

Total 518 3.465 0.794

<30 years 71 3.971 0.784

30-39 years 176 4.114 0.718

40-49 years 207 4.281 0.621

50+ years 55 4.100 0.907

Total 509 4.160 0.720

0.001

0.000

0.173

0.007

0.035

0.026

0.001

0.076

5.973

7.182

1.670

4.042

2.893

3.122

5.511

2.310

Safety

Cooldown

Equipment

Field

Warm-up

Preseason

Injury

Water

190

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BIOGRAPHICAL SKETCH

Christopher Francis Lachapelle was born on September 07, 1972 in Windsor,

Ontario, Canada. His enthusiasm in the field of sports throughout his life brought him to

the University of Windsor, Ontario, Canada for his Undergraduate study of Sport

Management. Lachapelle graduated from the University of Windsor with a Bachelor of

Human Kinetics degree with Honors in Sport Management in 1996. With his interest in

Sport Management still extremely high, he decided to attend the University of Western

Illinois and received his Master of Science degree in Sport Management in 1998. In order

to further his education, Lachapelle attended Florida State University where he received

his Doctorate of Philosophy in Sport Management.

Along with his doctorate, Lachapelle has been part of many committees in the

sport community. He was the Senior Staff Manager of Skiing during the Olympic Winter

games in 2002 and directed race day tours, social events and the sport promotion program

for the NASCAR Pepsi 400 in 2000-01. Among these major accomplishments, he has

also been: the Recreation Director of St. Mary’s college (Calgary, Alberta, Canada), the

Director of Business Operations of the Canadian Luge Association (Calgary, Alberta,

Canada), the Facilities Manager of the Tecumseh Baseball Complex (Tecumseh, Ontario,

Canada), Manager of the University of Windsor Concession Facilities (Windsor, Ontario,

Canada), the General Manager of the Windsor Bulldogs Junior B Hockey Club (Windsor,

Ontario, Canada), and the Fund Raising and Promotions Coordinator of the Teen Health

Lachapelle comes from a hard working family of five. He has two brothers

Wayne (older) and Jared (younger). On August 2, 2003 he married Jennifer DeLude in

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Calgary, Alberta. Jennifer has her Masters in Mechanical Engineering and has younger

sister Kimberly.

Presently, Lachapelle is acting as the Director of the Sport Business Program in

the Walker School of Business at Mercyhurst College (Erie, Pennsylvania).

diginole.lib.fsu.edu181645/datastream/... · ii the members of the committee approve the...

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