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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
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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).
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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
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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.
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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
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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
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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 7. Answers to Survey Question 2 Organized by Location .....................................67
Table 8. Answers to Survey Question 3 Organized by Location .....................................67
Table 9. Answers to Survey Question 4 Organized by Location .....................................68
Table 10. Answers to Survey Question 5 Organized by Location ...................................68
Table 11. Answers to Survey Question 6 Organized by Location ...................................69
Table 12. Answers to Survey Question 7 Organized by Location ...................................69
Table 13. Answers to Survey Question 8 Organized by Location ...................................70
Table 14. Answers to Survey Question 9 Organized by Location ...................................70
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
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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
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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
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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
Stages Kai
ser
Mo
del
Cle
men
t M
odel
van
der
Sm
isse
n M
od
el
Ber
lon
Mo
del
Horn
Hea
d M
odel
Mulr
on
ey M
od
el
TL
Model
Kav
ler
Spei
gal
Model
Fri
ed M
od
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.
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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).
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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.
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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).
Location Yes No Total
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).
Location Yes No Total
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).
Location Yes No Total
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).
Location Yes No Total
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.
Location Yes No Total
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.
Location Yes No Total
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.
Location Yes No Total
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.
Location Yes No Total
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
0.0000
1.0000
2.0000
3.0000
4.0000
5.0000
NEW YORK FLORIDA ONTARIO ALBERTA
Location
Es
tim
ate
d M
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ina
l M
ea
ns
NO
YES
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
0.0000
0.5000
1.0000
1.5000
2.0000
2.5000
3.0000
3.5000
4.0000
NEW YORK FLORIDA ONTARIO ALBERTA
Location
Es
tim
ate
d M
arg
ina
l M
ea
ns
NO
YES
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
0.0000
0.5000
1.0000
1.5000
2.0000
2.5000
3.0000
3.5000
4.0000
NEW YORK FLORIDA ONTARIO ALBERTA
Location
Es
tim
ate
d M
arg
ina
l M
ea
ns
NO
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
0.0000
1.0000
2.0000
3.0000
4.0000
5.0000
NEW YORK FLORIDA ONTARIO ALBERTA
Location
Es
tim
ate
d M
arg
ina
l M
ea
ns
NO
YES
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
0.0000
0.5000
1.0000
1.5000
2.0000
2.5000
3.0000
3.5000
NEW YORK FLORIDA ONTARIO ALBERTA
Location
Es
tim
ate
d M
arg
ina
l M
ea
ns
NO
YES
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
0.0000
0.5000
1.0000
1.5000
2.0000
2.5000
3.0000
3.5000
4.0000
NEW YORK FLORIDA ONTARIO ALBERTA
Location
Es
tim
ate
d M
arg
ina
l M
ea
ns
NO
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
0.0000
1.0000
2.0000
3.0000
4.0000
5.0000
NEW YORK FLORIDA ONTARIO ALBERTA
Location
Es
tim
ate
d M
arg
ina
l M
ea
ns
NO
YES
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
0.0000
0.5000
1.0000
1.5000
2.0000
2.5000
3.0000
3.5000
4.0000
4.5000
NEW YORK FLORIDA ONTARIO ALBERTA
Location
Es
tim
ate
d M
arg
ina
l M
ea
ns
NO
YES
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.
In the area of warm-up, a significant difference was detected between the
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).
In the area of equipment, a significant difference was detected between the
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).
In the area of preseason, no significant difference was detected between the
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
significant interaction was detected between this motivational factor and the location of
the team, F (3, 514) = 0.857, p = 0.463 (see Figure 27).
With regards to field, no significant difference was detected between the
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).
For injury, a significant difference was detected between the locations, F (3, 519)
= 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
significant interaction was detected between this motivational factor and the location of
the team, F (3, 525) = 0.379, p = 0.768 (see Figure 30).
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).
With regard to cooldown, a significant difference was detected between the
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
0.0000
0.5000
1.0000
1.5000
2.0000
2.5000
3.0000
3.5000
4.0000
4.5000
5.0000
NEW YORK FLORIDA ONTARIO ALBERTA
Location
Esti
mate
d M
arg
inal
Mean
s
NO
YES
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
0.0000
0.5000
1.0000
1.5000
2.0000
2.5000
3.0000
3.5000
4.0000
NEW YORK FLORIDA ONTARIO ALBERTA
Location
Esti
mate
d M
arg
inal
Mean
s
NO
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
0.0000
0.5000
1.0000
1.5000
2.0000
2.5000
3.0000
3.5000
NEW YORK FLORIDA ONTARIO ALBERTA
Location
Esti
mate
d M
arg
inal
Mean
s
NO
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
0.0000
0.5000
1.0000
1.5000
2.0000
2.5000
3.0000
3.5000
4.0000
4.5000
5.0000
NEW YORK FLORIDA ONTARIO ALBERTA
Location
Esti
mate
d M
arg
inal
Mean
s
NO
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
0.0000
0.5000
1.0000
1.5000
2.0000
2.5000
3.0000
3.5000
NEW YORK FLORIDA ONTARIO ALBERTA
Location
Esti
mate
d M
arg
inal
Mean
s
NO
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
0.0000
0.5000
1.0000
1.5000
2.0000
2.5000
3.0000
3.5000
4.0000
NEW YORK FLORIDA ONTARIO ALBERTA
Location
Esti
mate
d M
arg
inal
Mean
s
NO
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
0.0000
0.5000
1.0000
1.5000
2.0000
2.5000
3.0000
3.5000
4.0000
4.5000
5.0000
NEW YORK FLORIDA ONTARIO ALBERTA
Location
Esti
mate
d M
arg
inal
Mean
s
NO
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
0.0000
0.5000
1.0000
1.5000
2.0000
2.5000
3.0000
3.5000
NEW YORK FLORIDA ONTARIO ALBERTA
Location
Esti
mate
d M
arg
inal
Mean
s
NO
YES
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
indicated a statistically significant MANOVA for the locations, F (24, 1416) = 2.321, p <
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
results for each category can be found in Appendix C, Tables 37-40.
In the area of warm-up, a significant difference was detected between the
locations, F (3, 527) = 3.447, p = 0.017. 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
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).
In the area of equipment, a significant difference was detected between the
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
motivational factor and the location of the team, F (3, 513) = 0.565, p = 0.638.
With regards to field, no significant difference was detected between the
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
motivational factor and the location of the team, F (3, 517) = 0.584, p = 0.626 (see Figure
36.
For injury, a significant difference was detected between the locations, F (3, 518)
= 2.941, p = 0.033. 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
= 0.048). 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.
In the area of water safety, no significant difference was detected between the
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
motivational factor and the location of the team, F (3, 524) = 1.891, p = 0.130 (see Figure
38).
In the area of safety, no significant difference was detected between the locations,
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.
With regard to cooldown, a significant difference was detected between the
locations, F (3, 520) = 2.721, p = 0.044. Post hoc analysis revealed that coaches in
Ontario were performing significantly less cooldown than those in Alberta (p = 0.013).
The effect size was moderate between the two groups (0.485). A significant increase in
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
motivational factor and the location of the team, F (3, 520) = 0.917, p = 0.432.
99
Warm-up and Community Giving
0.0000
1.0000
2.0000
3.0000
4.0000
5.0000
NEW YORK FLORIDA ONTARIO ALBERTA
Location
Es
tim
ate
d M
arg
ina
l M
ea
ns
NO
YES
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
NEW YORK FLORIDA ONTARIO ALBERTA
Location
Esti
mate
d M
arg
inal
Mean
s
NO
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
0.0000
0.5000
1.0000
1.5000
2.0000
2.5000
3.0000
3.5000
NEW YORK FLORIDA ONTARIO ALBERTA
Location
Es
tim
ate
d M
arg
ina
l M
ea
ns
NO
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
0.0000
1.0000
2.0000
3.0000
4.0000
5.0000
NEW YORK FLORIDA ONTARIO ALBERTA
Location
Es
tim
ate
d M
arg
ina
l M
ea
ns
NO
YES
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
0.0000
0.5000
1.0000
1.5000
2.0000
2.5000
3.0000
3.5000
NEW YORK FLORIDA ONTARIO ALBERTA
Location
Es
tim
ate
d M
arg
ina
l M
ea
ns
NO
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
0.0000
0.5000
1.0000
1.5000
2.0000
2.5000
3.0000
3.5000
4.0000
NEW YORK FLORIDA ONTARIO ALBERTA
Location
Es
tim
ate
d M
arg
ina
l M
ea
ns
NO
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
0.0000
1.0000
2.0000
3.0000
4.0000
5.0000
NEW YORK FLORIDA ONTARIO ALBERTA
Location
Es
tim
ate
d M
arg
ina
l M
ea
ns
NO
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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NEW YORK FLORIDA ONTARIO ALBERTA
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YES
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
indicated a statistically significant MANOVA for the locations, F (24, 1419) = 2.455, p <
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
results for each category can be found in Appendix C, Tables 41-44.
In the area of warm-up, a significant difference was detected between the
locations, F (3, 528) = 2.734, p = 0.043. 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 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).
In the area of equipment, a significant difference was detected between the
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.
In the area of preseason, no significant difference was detected between the
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.
With regards to field, no significant difference was detected between the
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).
For injury, a significant difference was detected between the locations, F (3, 519)
= 3.160, p = 0.024. 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
= 0.046). 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).
In the area of safety, no significant difference was detected between the locations,
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
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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
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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
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Esti
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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
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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
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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
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NEW YORK FLORIDA ONTARIO ALBERTA
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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
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NEW YORK FLORIDA ONTARIO ALBERTA
Location
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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
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NEW YORK FLORIDA ONTARIO ALBERTA
Location
Esti
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Mean
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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
indicated a statistically significant MANOVA for the locations, F (24, 1419) = 2.377, p <
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.
In the area of warm-up, a significant difference was detected between the
locations, F (3, 528) = 3.367, p = 0.018. 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 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).
In the area of equipment, a significant difference was detected between the
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).
In the area of preseason, no significant difference was detected between the
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).
For injury, a significant difference was detected between the locations, F (3, 519)
= 3.203, p = 0.023. 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 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).
In the area of safety, no significant difference was detected between the locations,
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
With regard to cooldown, a significant difference was detected between the
locations, F (3, 521) = 2.857, p = 0.037. 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 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
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NEW YORK FLORIDA ONTARIO ALBERTA
Location
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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
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NEW YORK FLORIDA ONTARIO ALBERTA
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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
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NEW YORK FLORIDA ONTARIO ALBERTA
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
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NEW YORK FLORIDA ONTARIO ALBERTA
Location
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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
NEW YORK FLORIDA ONTARIO ALBERTA
Location
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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
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4.0000
NEW YORK FLORIDA ONTARIO ALBERTA
Location
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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
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NEW YORK FLORIDA ONTARIO ALBERTA
Location
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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
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NEW YORK FLORIDA ONTARIO ALBERTA
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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).
In the area of water safety, no significant difference was detected between the
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
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4.0000
5.0000
<30 30-39 40-49 50+
Coach Age in Years
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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
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4.0000
<30 30-39 40-49 50+
Coach Age in Years
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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
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1.0000
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3.5000
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Coach Age in Years
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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
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1.0000
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3.5000
4.0000
4.5000
<30 30-39 40-49 50+
Coach Age in Years
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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
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1.0000
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2.0000
2.5000
3.0000
3.5000
<30 30-39 40-49 50+
Coach Age in Years
Es
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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
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3.0000
3.5000
4.0000
<30 30-39 40-49 50+
Coach Age in Years
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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
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2.0000
3.0000
4.0000
5.0000
<30 30-39 40-49 50+
Coach Age in Years
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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
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Mean
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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
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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
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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
practices required by the organization in order to coach?
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.
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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 %).
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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
141
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
baseball/softball and a coach’s safety practices?
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
142
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
practices required by the organization in order to coach?
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
143
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
144
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
145
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
baseball/softball and a coach’s safety practices?
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
SURVEY ANSWER (%)SURVEY ANSWER (Frequency)
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)
CATEGORY LOCATIONQUESTION (#)
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
SURVEY ANSWER (%)SURVEY ANSWER (Frequency)
CATEGORY LOCATIONQUESTION (#)
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
SURVEY ANSWER (%)SURVEY ANSWER (Frequency)
CATEGORY LOCATIONQUESTION (#)
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
CATEGORY PLAYER AGE COUNTRY N MEAN STD. DEV. DIFFERENCE F VALUE P VALUE
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
CATEGORY PLAYER AGE COUNTRY N MEAN STD. DEV. DIFFERENCE F VALUE P VALUE
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
CATEGORY LOCATION CHILD N MEAN STD. DEV. DIFFERENCE F VALUE P VALUE
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
CATEGORY LOCATION CHILD N MEAN STD. DEV. DIFFERENCE F VALUE P VALUE
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
CATEGORY LOCATION ENJOY N MEAN STD. DEV. DIFFERENCE F VALUE P VALUE
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
CATEGORY LOCATION ENJOY N MEAN STD. DEV. DIFFERENCE F VALUE P VALUE
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
CATEGORY LOCATION COMMUNITY N MEAN STD. DEV. DIFFERENCE F VALUE P VALUE
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
CATEGORY LOCATION COMMUNITY N MEAN STD. DEV. DIFFERENCE F VALUE P VALUE
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
CATEGORY LOCATION FIRST AID N MEAN STD. DEV. DIFFERENCE F VALUE P VALUE
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
CATEGORY LOCATION FIRST AID N MEAN STD. DEV. DIFFERENCE F VALUE P VALUE
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
CATEGORY LOCATION CPR N MEAN STD. DEV. DIFFERENCE F VALUE P VALUE
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
CATEGORY LOCATION CPR N MEAN STD. DEV. DIFFERENCE F VALUE P VALUE
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).