Order 1690689: Chapter Two: Literature Review of Impact of Beliefs

adelphiandcorelationstudy.pdf

Home >Literature homework help >Order 1690689: Chapter Two: Literature Review of Impact of Beliefs

University of South Florida Scholar Commons

Graduate Theses and Dissertations Graduate School

January 2013

The Relationship between High School Coaches' Beliefs about Sports Injury and Prevention Practice Readiness Siwon Jang University of South Florida, [email protected]

Follow this and additional works at: http://scholarcommons.usf.edu/etd

Part of the Public Health Commons

This Dissertation is brought to you for free and open access by the Graduate School at Scholar Commons. It has been accepted for inclusion in Graduate Theses and Dissertations by an authorized administrator of Scholar Commons. For more information, please contact [email protected].

Scholar Commons Citation Jang, Siwon, "The Relationship between High School Coaches' Beliefs about Sports Injury and Prevention Practice Readiness" (2013). Graduate Theses and Dissertations. http://scholarcommons.usf.edu/etd/4694

http://scholarcommons.usf.edu/?utm_source=scholarcommons.usf.edu%2Fetd%2F4694&utm_medium=PDF&utm_campaign=PDFCoverPages

http://scholarcommons.usf.edu?utm_source=scholarcommons.usf.edu%2Fetd%2F4694&utm_medium=PDF&utm_campaign=PDFCoverPages

http://scholarcommons.usf.edu/etd?utm_source=scholarcommons.usf.edu%2Fetd%2F4694&utm_medium=PDF&utm_campaign=PDFCoverPages

http://scholarcommons.usf.edu/grad?utm_source=scholarcommons.usf.edu%2Fetd%2F4694&utm_medium=PDF&utm_campaign=PDFCoverPages

http://scholarcommons.usf.edu/etd?utm_source=scholarcommons.usf.edu%2Fetd%2F4694&utm_medium=PDF&utm_campaign=PDFCoverPages

http://network.bepress.com/hgg/discipline/738?utm_source=scholarcommons.usf.edu%2Fetd%2F4694&utm_medium=PDF&utm_campaign=PDFCoverPages

mailto:[email protected]

The Relationship between High School Coaches’ Beliefs about Sports Injury and

Prevention Practice Readiness

Si-Won Jang

A dissertation submitted in partial fulfillment

of the requirements of the degree of

Doctor of Philosophy

Department of Community & Family Health

College of Public Health

University of South Florida

Major Professor: Karen D. Liller, Ph.D.

Julie Baldwin, Ph.D.

Jeff Konin, Ph.D.

Carla Vandeweerd, Ph.D.

Yiliang Zhu, Ph.D.

Date of Approval:

July 19, 2013

Keywords: sports, adolescents, injury training and development, high school coaches,

injury prevention, Certified Athletic Trainers (ATCs)

Dedication

I dedicate this doctoral dissertation to God, who gave me life and led me to this

invaluable journey. I love you, O LORD, my strength (Psalms 18:1).

Acknowledgments

First of all, I would like to thank my entire family for believing in my potential as

a scholar and providing all the support that I needed to finish this big challenge. I

especially thank my husband Jin and my fabulous boys, Daniel and David for their

patience, encouragement, and love. I would like to extend my sincere appreciation and

gratitude to my major professor, Dr.Karen Liller for providing academic and financial

support for me to continue my doctoral program. I would not have completed this long

journey without her teaching, mentoring, and encouragement. I am also sincerely

grateful to Dr.Baldwin for providing prompt and consistent support and feedback since

we met in the first semester of my doctoral program. My deep gratitude goes to Dr.

Konin for supporting my dissertation research and sharing his Sports Medicine expertise

with me. I would like to thank Dr.VandeWeerd for providing great support and insightful

guidance during my doctoral program. My deep appreciation goes to Dr.Zhu for his

expertise regarding Biostatistics throughout my dissertation process and for sharing his

wisdom that is needed for my academic career. My cohort including Euna, Cara, and

Lianne: thank you so much for your tangible and emotional help and encouragement. My

deep gratitude goes to the members in Tampa New Light Church for their continuous

prayer and unconditional love for me and my family. Lastly, I would like to thank Drs.

Coulter and Perrin for my research/teaching assistant positions at USF. I learned many

valuable things from them that are needed to be a true researcher/professor.

Table of Contents

List of Tables ..................................................................................................................... v

List of Figures .................................................................................................................. vi

Abstract ........................................................................................................................... vii

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

Statement of the Problem ........................................................................................1

High School Sports Injury ......................................................................................2

Purpose of the Study ...............................................................................................3

Research Questions .................................................................................................4

Assumptions ............................................................................................................4

Significance of the Study ........................................................................................4

Definition of Key Terms .........................................................................................5

CHAPTER TWO: LITERATURE REVIEW .....................................................................7

Sports Injuries among Adolescents .........................................................................7

Overall prevalence ......................................................................................7

Injury characteristics of high risk sports .....................................................9

Football ...........................................................................................9

Soccer ...........................................................................................11

Wrestling .......................................................................................12

Basketball ......................................................................................13

High School vs Collegiate Sports .........................................................................14

General Risk Factors for Sports Injuries ...............................................................16

Personal factors .........................................................................................16

Gender ...........................................................................................16

Body size, age/grade/experience, performance measures .............17

Previous injury history ..................................................................18

Psychological factors ................................................................................18

Environmental factors ...............................................................................19

Session types (competition vs. practice settings) ..........................19

Surface condition ..........................................................................20

Prevention Efforts .................................................................................................20

Need for better surveillance systems ........................................................21

Protective equipment ................................................................................23

Rule change and related strategies ............................................................24

Other efforts ..............................................................................................26

Coaches and Sports Injuries ..................................................................................30

Coaches’ influence on athletes ..................................................................30

Injury prevention provided by coaches .....................................................32

Coaching education & certification ..........................................................35

Instruments to measure coach factors .......................................................39

Coaches vs ATCs ......................................................................................41

Theories and Models in Sports Injury Research ...................................................43

Health Belief Model ..................................................................................44

Theory of Planned Behavior / Theory of Reasoned Action ......................46

Social Cognitive Theory ...........................................................................49

Other theories ............................................................................................51

Theoretical Framework of the Study ....................................................................52

CHAPTER THREE: METHODOLOGY .........................................................................54

Overview of the Study Design ..............................................................................54

Part I: Survey Instrument Validation Utilizing Delphi Technique .......................56

Subjects and setting ...................................................................................57

Instrumentation .........................................................................................58

Data collection ..........................................................................................59

Data analysis .............................................................................................61

Part II: High School Coach Survey .......................................................................61

Subjects and setting ...................................................................................61

Instrumentation .........................................................................................62

Data collection ..........................................................................................63

Data analysis .............................................................................................64

iii

CHAPTER FOUR: RESULTS .........................................................................................66

Descriptive Analysis .............................................................................................66

Coaches’ Experiences Regarding Injury Prevention ............................................67

The Results of Delphi Process ..............................................................................69

Instrumentation Results ........................................................................................71

Reliability test ...........................................................................................71

Factor analysis ...........................................................................................72

Research Question 1 .............................................................................................74

Coaches’ beliefs and knowledge regarding sports injury .........................74

Coaches’ readiness for sports injury prevention practice .........................76

Research Question 2 .............................................................................................77

Research Question 3 .............................................................................................82

Demographic characteristics .....................................................................82

HBM variables ...........................................................................................83

Coaches’ readiness for injury prevention practice ....................................84

CHAPTER FIVE: DISCUSSION AND CONCLUSIONS ..............................................86

Summary and Discussion ......................................................................................86

Coaches’ Beliefs and Knowledge Pertaining to Sports Injury ..............................88

Coaches’ Injury Prevention Practice .....................................................................91

Relationship between Coaches’ Beliefs and Injury Prevention Practice ..............93

Differences in Beliefs and Practices between Coaches Who Have Medical

Staff and Those Who Do Not ...........................................................................95

Implications for Public Health ..............................................................................96

Strengths and Limitations .....................................................................................98

Recommendations for Future Research ..............................................................100

Conclusion ..........................................................................................................101

References .......................................................................................................................102

Appendices ......................................................................................................................118

Appendix A: IRB Documents .............................................................................119

Appendix B: Delphi Questionnaire .....................................................................125

Appendix C: Coach Survey Questionnaire .........................................................140

Appendix D: Coaches’ Experiences Regarding Injury Prevention .....................147

Appendix E: Example Frequency Tables for Coach Survey ..............................151

List of Tables

Table 1: Haddon Matrix Applied to the Problem of Athletic Injuries ..............................27

Table 2: Eight Domains of Coaching Competencies Developed by the National

Association for Sport and Physical Education (NASPE) .................................. 35

Table 3: Sub-categories of the Coaching Behavior Assessment System ..........................40

Table 4: Sub-categories of Coaching Efficacy Scale II ....................................................41

Table 5: Research Design and Objectives ........................................................................56

Table 6: Warm-up and Cool-down Time ..........................................................................68

Table 7: Results of the Delphi Process .............................................................................69

Table 8: Internal Consistency and Descriptive Statistics for Stages of Change and

Health Belief Model Subscales ...........................................................................72

Table 9: Factor Analysis Result ........................................................................................73

Table 10: Descriptive Statistics for Health Belief Model (HBM) Components ...............75

Table 11: Coaches’ Readiness of Sports Injury Prevention Behavior ..............................77

Table 12: Pearson Correlation between HBM Factors and Injury Prevention

Behaviors ..........................................................................................................79

Table 13: Logistic Regression Models of Factors Associated with Coaches’ Injury

Prevention Behaviors ........................................................................................81

Table 14: Demographic Characteristic for Each Group ...................................................83

Table 15: HBM Variables for Each Group .......................................................................84

Table 16: Coaches’ Readiness of Sports Injury Prevention Practices by Group ..............85

List of Figures

Figure 1: Theoretical Framework .....................................................................................55

vii

Abstract

Although sports and other forms of physical activities are associated with

numerous health benefits, adolescent sports injury has emerged as an important public

health problem. As the most immediate caregivers for athletes, coaches are expected to

play an important role in preventing and reducing injuries, -considering that sports

medical staff, such as athletic trainers are not always available to care for athletes.

However, research on coaches’ beliefs and practices related to injury prevention has

been limited to coaching competency issues, in which injury prevention is considered

only one component. Therefore, the purpose of the study was to describe the coaches’

beliefs and knowledge pertaining to sports injury and their readiness for injury prevention

practice to be incorporated into high school settings. The research questions are: (1)

What are the coaches’ beliefs and knowledge related to sports injury and their readiness

for injury prevention practice?; (2) What are the relationships between coaches’ beliefs

and knowledge pertaining to sports injury and readiness for injury prevention practice?;

and (3) What are the differences in coach-related factors between the coaches who have

medical staff and those who do not? The participants in the study had average to low

perceptions regarding injuries on their team. The knowledge score related to sports injury

was not high. However, a majority of the coaches showed strong beliefs in favor of

implementing injury prevention interventions as an effective way to prevent and reduce

sports injuries. Supporting previous studies, the present study revealed strong

viii

associations between self-efficacy and the injury prevention behaviors assessed. It was

also found that coaches who employed medical staff were approximately four times more

likely to provide injury prevention programs to their athletes and have emergency plans.

Findings from this study will provide a broader understanding of coaches’ perceptions

regarding sports injury, injury prevention interventions conducted by coaches, and the

implications for developing quality coaching programs and policies to prevent and reduce

sports injuries.

CHAPTER ONE: INTRODUCTION

Statement of the Problem

Injury is a very significant public health issue threatening the health of children,

adolescents, and young adults in the United States who have the potential to contribute to

our society in the future or are already actively functioning within society. In 2006,

unintentional injury was ranked the leading cause of death among those aged 10 to 34

years, resulting in 30,021 deaths (Center for Disease Control and Prevention [CDC],

2009). According to Christoffel and Gallagher (2006), approximately 142 million injury-

related visits to physician offices, hospital emergency, and outpatient department are

made every year. The authors also estimate that the social costs resulting from injury are

almost equal to the costs due to heart disease and cancer combined.

As obesity among children and adolescents continues to be a public health

concern in the United States, sports and other forms of physical activities have been

strongly encouraged to resolve the problem. However, these also entail a risk of injury.

In the United States, the estimated cost of sports injury hospitalizations among 5-18 year

olds was $485 million during 2000-2003 with a steady increase each year (Yang et al.,

2007). According to a recent survey, 1,442,533 injuries occurred among high school

athletes in the U.S. during the 2005-2006 school year (CDC, 2006). The economic costs

of sports injuries among high school athletes in North Carolina were estimated to be $9.9

million in medical costs, $44.7 million in human capital costs (medical costs plus loss of

future earnings), and $144.6 million in comprehensive costs (human capital costs plus

lost quality of life).

Coaches play an important role in influencing the performance, motivation, and

self-esteem of youth athletes and preventing and reducing injuries (Hergenroeder, 1998).

Their role for injury prevention is particularly critical given that sports medical staff, such

as athletic trainers, are not always available to care for athletes. One study reports that

three-fourths of the coaches perceived they had a major role in injury prevention

education, implicating that injury prevention programs provided by coaches may be an

effective approach to decrease the risk of athletes’ injury (Otago, Swan, & Ramage,

2005). However, only a few studies on coaches’ beliefs and practices related to sports

injury as well as the relationship between the coach factors and injury outcomes have

been conducted. Most coach and injury-related research has been limited to coaching

competency issues, in which injury prevention is considered one component (National

Association for Sport and Physical Education [NASPE], 2009). The paucity of research

on the coaches’ perception related to sports injury and their readiness for injury

prevention practice may be a fundamental barrier for effective prevention interventions

provided by coaches.

High School Sports Injury

One recent national study shows that approximately 60% of high school students

had played on at least one sports team during 2011 in the United States (Eaton et al.,

2012). According to another national study conducted by the Centers for Disease Control

and Prevention (2006), approximately 4.2 million U.S. high school students participated

in nine sports (baseball, football, and wrestling for boys, softball and volleyball for girls,

and basketball and soccer for boys and girls), and 1,442,533 injuries occurred during the

2005-06 school year. A study conducted using a nationally representative sampling

reported that football had the highest injury rate (4.36 injuries per 1,000 high school

athletes) followed by wrestling (2.50) and soccer (2.43 for boys and 2.36 for girls)

compared to the overall injury rate of 2.44 per 1,000 high school athletes (CDC, 2006).

According to Fernandez and colleagues’ study (2007) that targeted a nationally

representative sample of 100 high schools and investigated the epidemiology of lower

extremity injuries among high school athletes, sprains/strains, contusions, and fractures

were the most common among nine sports (baseball, football, and wrestling for boys;

softball and volleyball for girls; and basketball and soccer for boys and girls). In that

study, the most common body parts injured were the ankle, knee, and thigh (Fernandez,

Yard, & Comstock, 2007).

Although high school sports injuries need to be regarded as a significant public

health problem and should be approached from a prevention perspective, most previous

studies have focused on assessing injuries through simple injury reporting systems or

clinical aspects of specific sport injuries. In addition, very few studies have addressed

sports injury prevention for high school athletes; those that have focused on limited

issues, such as the development of safety rules and the importance of sports equipment

(Francisco, Nightingale, Guilak, Glisson, & Garrett, 2000; Theye & Mueller, 2004; Yang

et al., 2005).

Purpose of the Study

The purpose of the study was to describe the coaches’ beliefs pertaining to sports

injury and their readiness for injury prevention practice related to high school athletes.

Also, the study explored the relationships between coach-related factors, such as coaches’

beliefs and knowledge related to sports injury and their prevention practice readiness.

Findings from this study will provide a broader understanding of coaches’ perception of

sports injury, injury prevention interventions conducted by coaches, and the implications

for developing quality coaching programs and policies to prevent and reduce sports

injuries.

Research Questions

The research questions of the study were: (1) What are the coaches’ beliefs and

knowledge related to sports injury and their readiness for injury prevention practice?; (2)

What are the relationships between coaches’ beliefs and knowledge pertaining to sports

injury and readiness for injury prevention practice?; and (3) What are the differences in

coach-related factors between the coaches who have medical staff and those who do not?

Assumptions

It was assumed that the Delphi process and the coach survey are appropriate

methods of addressing the research questions of the study. It was also assumed that all

participants would truthfully respond to the survey questions.

Significance of the Study

Sedentary life style is known as a risk factor for non-communicable diseases such

as cardiovascular disease, diabetes, and obesity. The need for physical activity has been

strongly emphasized by experts. In particular, obesity among children and adolescents

continues to be a public health concern in the United States. For the adolescent

population, sports and other forms of physical activities contribute to physical

development and mental health promotion, providing learning about important values

such as fair play, team spirit, and tolerance (EuroSafe, 2009). However, sports and other

physical activities also entail a risk of injury which is a leading cause of morbidity in

children and adolescents. For example, sports are the leading causes of adolescent injury

requiring medical attention and emergency department admissions in the United States.

In fact, sports injuries, like other injuries, are often predictable and preventable

utilizing behavioral and environmental control of risk factors (Christoffel & Gallagher,

2006). In particular, coaches may be significant because they are mostly available during

practices and games for each sport and can play multiple roles to prevent and reduce

injuries, influencing athletes’ behaviors and the environment surrounding the athletes.

Therefore, it is anticipated that the findings of the study will provide a broader

understanding of coaches’ perception of sports injury, injury prevention interventions

conducted by coaches at high school settings, and the implications for developing quality

coaching programs and policies to prevent and reduce sports injuries.

Definition of Key Terms

ATCs (Certified Athletic Trainers): Health care providers who specialize in the

prevention, assessment, treatment and rehabilitation of injuries and illnesses (National

Athletic Trainers’ Association [NATA], 2010a)

Athlete: A person who is trained or skilled in exercises, sports, or games requiring

physical strength, agility, or stamina (Merriam-Webster Online Dictionary, 2010)

Coach: One who instructs players in the fundamentals of a competitive sport and

directs team strategy (Merriam-Webster Online Dictionary, 2010)

Coach-related factors: Coach factors that are assumed to influence sports injury

outcomes. In the study, the coach factors include coaches’ beliefs and knowledge

pertaining to sports injury and their readiness for injury prevention.

Injury knowledge: The knowledge of coaches related to sports injury including

injury mechanism, risk factors, injury assessment, emergency plan, and prevention

methods

Injury prevention practice: Activities to eliminate or reduce the likelihood of

injury (Hemenway, Aglipay, Helsing, & Raskob, 2006)

Medical staff: Health care professionals licensed, certified, or registered to

provide health care services to high school athletes. Appropriate health care

professionals could be: certified athletic trainers, team physicians, consulting physicians,

school nurses, physical therapists, emergency medical services (EMS) personnel, dentists

and other allied health care professionals (NATA, 2010b)

Readiness for prevention practice: Coach’s willingness to implement activities needed to

prevent and reduce injuries

Sports injury: 1)An injury that occurs as a result of participation in an organized

high school competition or practice; 2)Requires medical attention by a licensed medical

professional; and 3) Results in restriction and/or modification of the high school athlete’s

participation for one or more days beyond the day of injury (Liller et al., 2009)

CHAPTER TWO: LITERATURE REVIEW

This chapter provides a review of the literature on sports injuries among

adolescents which includes overall prevalence, injury characteristics of high-risk sports,

comparisons between high school and collegiate sports, general risk factors, and

prevention efforts. In addition, this chapter contains information on coaches and sports

injuries, focusing on coaches’ influence on athletes, injury prevention provided by

coaches, coaching education and certification, instruments to measure coach factors, and

injury prevention-related literature on certified athletic trainers (ATCs). This chapter also

provides a section on theories and models in sports injury research. This section describes

information on previous sports injury research that utilized the Health Belief Model,

Theory of Planned Behavior, Theory of Reasoned Action, Social Cognitive Theory, and

other well-known public health theories, along with the theoretical framework for this

study.

Sports Injuries among Adolescents

Overall prevalence

Emery (2003) reported that sports are the leading causes of adolescent injury

requiring medical attention and emergency department admissions, indicating that

hospital emergency departments report rates range from 7.03 to 8.55 injuries/100

adolescents/year. Burt and Overpeck (2001) also estimated that approximately 2.6

million persons between the ages of 5 and 24 years visited the emergency room due to

sports-related injuries from 1997 to 1998.

Powell and Barber-Foss (1999) reported that approximately two million high

school sports injuries occur annually, leading to 500,000 doctor visits and 30,000

hospitalizations. According to the Centers for Disease Control and Prevention (CDC)

(2006), approximately 4.2 million U.S. high school students participated in nine sports

(baseball, football, and wrestling for boys, softball and volleyball for girls, and basketball

and soccer for boys and girls) and 1,442,533 injuries occurred during the 2005-06 school

year.

Overall, the definition of injury used in the prevalence studies does not seem to be

consistent. Inclusion criteria such as medical requirement and time loss due to injury

vary. Many studies define injury as a condition that requires medical attention and

causes a player to be removed from the practices/games, however some studies do not

include the medical requirement. For example, in the Junge and colleagues’ study on

prevention of soccer injuries (2002), the injury was defined as “any physical complaint

caused by soccer that lasted for more than 2 weeks or resulted in absence from a

subsequent match or training session” (p. 654), showing that medical attention is not

necessarily required (Junge, Rosch, Peterson, Graf-Baumann, & Dvorak, 2002).

Designating the time loss to define injury also differs widely ranging from one day

(Emery, 2007) to two week loss (Junge et al., 2002). The variability in defining injury is

linked to the variability in measurement, which hinders the comprehensive comparison of

injury prevalence across the studies. Many sports injury researchers recognize this

problem (Emery, 2003; Junge et al., 2008), but a universal definition has not been

developed except in football (soccer) (Fuller et al., 2006) and rugby (Fuller et al., 2007)

A consistent definition is essential to understand the magnitude of sports injury and

ensure the validity of research.

Injury characteristics of high risk sports

In most of the previous sports injury prevalence studies, football has been found

to account for the highest injury rate (CDC, 2006; Powell & Barber-Foss, 1999). Beachy

and colleagues (1997) reported that football had the highest injury rate for male athletes,

and soccer resulted in the highest injury rate for female athletes. Researchers estimated

that, in an average year, “41-61% of football players, 40-46% of wrestlers and gymnasts,

and 31-37 % of basketball players sustain an injury while participating

in organized high

school sports” (Yang et al., 2005, p.511). In terms of types of injures, lower extremity

injuries appear to be most common. The current review presents injury characteristics of

football, soccer, wrestling, and basketball which are high risk sports played commonly in

educational settings.

Football

Due to the fact that it requires a high degree of contact between players, football

has been recorded as the sport with the highest rate of injury (Beachy, Akau, Martinson,

& Olderr, 1997; CDC, 2006; Fernandez et al, 2007; Powell & Barber-Foss, 1999;

Ramirez, Schaffer, Shen, Kashani, & Kraus, 2006). Dick and colleagues (2007b)

reported from the National Collegiate Athletic Association (NCAA) 16-year injury

surveillance study that approximately 36 per 1000 athlete-exposures occurred every year

to collegiate men’s football players. The authors found that lower extremity injuries

accounted for more than 50% of injuries, and at least more than 57% of football injuries

resulted from player contact. In terms of the most common injured body part and injury

type, knee internal derangements, ankle ligament sprains, upper leg muscle tendon

strains, and concussions accounted for the majority of injuries for games and practices

(Dick et al., 2007b). According to a study conducted by the Center for Injury Research

and Policy at Columbus Children’s Hospital in Columbus, Ohio (CDC, 2006), football

had the highest injury rate (4.36 injuries per 1,000 athlete exposures) among nine high

school sports including soccer and basketball for boys and girls; football, baseball,

wrestling for boys; and softball and volleyball for girls.

Based on the data from the National Center for Catastrophic Sports Injury

Research, Boden and colleagues (2006) reported that football had the highest number of

direct catastrophic injuries. These catastrophic injuries include cervical spine region

injuries, such as spinal column disruption (fractures, subluxation, or dislocation), cervical

nerve root avulsion, or a cervical injury resulting in permanent neurologic deficits or

transient neurologic symptoms in at least two extremities. The authors found that the

annual incidence of direct catastrophic football injuries was 1.34 per 100,000 high school

and college players (Boden et al., 2006). Further, approximately six injuries per year

were linked to quadriplegic events among high school and collegiate football players,

which corresponds to an incidence rate of 0.52 per 100,000 participants. The authors also

indicate that spear tackling is a leading cause of quadriplegia, suggesting the need for

coaches’ education to prevent these catastrophic injuries (Boden et al., 2006).

Catastrophic head injury is also a significant health issue among football players

(Boden, Tacchetti, Cantu, Knowles, & Mueller, 2007). Researchers indicate that second-

impact syndrome (SIS) which occurs when an individual suffers a second head injury

before the brain recovers from the first head injury is particularly problematic because it

can lead to rapid and catastrophic brain swelling, permanent brain damage, and even

death (CDC, 1997). A study of American high school and college football players

reported that 71% of high school players suffering catastrophic head injuries had a

previous concussion in the same season (Boden, et al., 2007). Experts strongly suggest

that coaches and officials must not allow the injured athlete to return to play until

approved by a health care professional skilled in evaluating concussion (CDC, 1997).

Given that experts have urged the change of the exiting concussion rule, the National

Federation of State High School Associations (NFHS) (2010) has revised their rule so

any head-injured athletes showing the signs and symptoms of concussion can be removed

from play. The previous rule allowed removing an athlete from play only if he or she is

unconscious or apparently unconscious, and a written authorization from a medical

doctor was required for the player to return to play. The new rule, however, states that a

concussed athlete cannot return to play until cleared by an appropriate health-care

professional (NFHS, 2010). These changes may contribute to detecting more concussed

athletes and preventing them from returning to play before completely recovered from a

concussion.

Soccer

The injury rate of collegiate men’s soccer was four times higher in games

compared with practices (18.75 vs. 4.34 injuries per 1000 athlete-exposures) according to

a study of the NCAA (Agel, Evans, Dick, Putukian, & Marshall, 2007a). Dick and

colleagues (2007c) reported that the rate of injury in women’s soccer was three times

greater during games than practices (16.44 vs. 5.23 injuries per 1000 athlete-exposures).

More than two-thirds of soccer injuries occurred to the lower extremities, and ankle

ligament injuries which account for a substantial portion of game injuries, appear to

require further research for both males and females (Dick, Putukian, Agel, Evans, &

Marshall, 2007c). In soccer, player to player contact during games seems to be a primary

cause of injuries (Agel et al., 2007a; Dick et al., 2007c). A recent CDC report on sports

related injuries among high school athletes (CDC, 2006) indicated that boys’ soccer had

2.43 injuries per 1000 athlete exposures, while girls’ soccer showed a slightly lower

injury rate than boys: 2.36 injuries per 1,000 athlete exposures. According to Powell and

Barber-Foss (2000), girls’ soccer in high school had a 14% higher injury rate than boys’

soccer; the injury rate per 100 players for boys ranged from 22.6 to 24.8 while the injury

rate for girls ranged from 26.0-28.5. The authors also reported that the most frequently

injured body part in soccer was the ankle and foot and the most common type of injury

was a sprain (Powell & Barber-Foss, 2000).

Wrestling

In a review of 16 years of NCAA injury surveillance data, Agel and colleagues

(2007b) found that the injury rate of collegiate men’s wrestling was more than four times

higher in matches than in practices (26.4 vs. 5.7 injuries per 1000 athlete-exposure),

suggesting that “it may reflect poorly planned attempts to quickly reduce total body

weight for an upcoming season” (p. 307). In terms of injury mechanisms, most injuries

in matches occurred from player contact (55.0%) and the injuries from other contact

primarily resulted from the mat (Agel, Ransone, Dick, Oppliger, & Marshall, 2007b).

Player contact was also a main reason for the majority of practice injuries. The most

commonly injured body areas included the shoulder, knee, ankle, and head (Agel et al.,

2007b; Pasque & Hewett, 2000). In addition to the musculoskeletal system and head

injuries, skin infections of collegiate wrestlers were reported as a serious health issue by

the authors. Skin infections such as herpes simplex and ringworm accounted for

approximately 20% of all practice injuries as previous studies on wrestling injury have

reported (Agel et al., 2007b). The largest percentage of wrestling positions resulting in

injury was takedown (Agel et al., 2007b). According to a recent CDC report (2006),

wrestling had the second highest injury rate of nine high school sports surveyed (2.5

injuries per 1,000 athlete exposures). Pasque and Hewett (2000) reported a higher injury

rate of 6.0 injuries per 1000 exposures in a prospective study monitoring 458 male

wrestlers from 14 high schools. The results showed that the injury rate was higher during

competition than in practice and the most commonly injured parts were the shoulder and

knee (Pasque & Hewett, 2000).

Basketball

Dick and colleagues (2007a) reported that, during basketball games,

approximately 9.9 injuries per 1000 athlete-exposures and 7.68 injuries per 1000 athlete-

exposure occurred every year to collegiate men and women players respectively. The

authors found that lower extremity injuries accounted for approximately 60% of the

injuries and the majority of injuries occurring in games resulted from player contact. In

terms of the most commonly injured body part and injury type, knee internal

derangements, ankle ligament sprains, upper leg muscle tendon strains, and concussions

accounted for the majority of injuries for basketball games and practices (Dick et al.,

2007a). According to the CDC (2006), the overall injury rate (practice and competition)

of high school basketball was 2.01 injuries per 1,000 athlete exposures for girls and 1.89

for boys during the 2005-2006 school year. Powell and Barber-Foss (2000) reported that

the injury rate for girls’ basketball in high school was slightly higher than for boys’ teams

(28.3-31.7 vs 27.8-30.3). The most often injured body part was the ankle/foot, and the

most common type of injury was a sprain (Powell & Barber-Foss, 2000). These results

show that the injured body area and type of injury showed the same pattern as soccer.

In the previous studies cited, injury data for high risk sports have been collected

based on various definitions of injury, depending on whether a study requires medical

attention in defining the injury and how much time is allowed to be evaluated as an

“injury.” In addition, reporting source varied including the athletes injured, parents,

coaches, athletic trainers, physicians, and emergency departments. Considering that high

risk sports may lead to catastrophic injuries, the data collection should be done by

medical personnel such as athletic trainers, physicians, and nurses for accurate screening

and diagnoses of injury (Mensch, Crews, & Mitchell, 2005). Having medical personnel

also will assist in 1) decreased injury rates, 2) decreased loss of playing time due to

accurate diagnosis and treatment, and 3) decreased rate of re-injury due to proper

rehabilitation (Aukerman, Aukerman, & Browning, 2006, p.132)

High School vs Collegiate Sports

Studies have reported that the injury rate of high school athletes is lower than that

of their college counterparts. However, it should be noted that high school players seem

to be more susceptible to injury due to their immature bodies and less experience.

According to Shankar and colleagues (2007), the football related injury rate was greater

in the National Collegiate Athletic Association (NCAA) football players (8.61) than in

high school football players (4.36). However, the study also showed that the high school

athletes sustained a greater portion of fractures and concussions (Shankar, Fields, Collins,

Dick, & Comstock, 2007). The authors explained the difference in that high school

athletes may be more prone to fractures due to their open growth plates. Another

assumption was that athletes who were exposed to the risk of concussion in high school

may not continue to play football in college, leading to the lower rate of concussions

among the college population. Boden and colleagues (2006) reported that the incidence

of direct catastrophic cervical spine injuries per 100,000 football players was more than

4-fold higher in college athletes (4.72) compared to high school athletes (1.10). The

authors discussed the higher incidence of injuries among collegiate athletes could be

interpreted by faster, bigger, and stronger athletes who have higher collision forces

(Boden et al., 2006). In a national study comparing US high school and college wrestling

injuries (Yard, Collins, Dick, & Comstock, 2008), the injury rate was three times higher

in the college population than in their high school counterparts, especially during matches.

The authors believed that it may be due to increased exposure time in collegiate matches

(college wrestling match is one minute longer than a high school match) and a higher

level of competition in college. The study results also showed that the high school

wrestlers sustained larger proportions of fractures compared to the college players (Yard,

et al., 2008). The authors hypothesized that the high school athletes may have less

experience in using proper falling skills, and they might be more skeletally immature than

college wrestlers.

Reel and Gill (1996) conducted a survey to investigate psychosocial factors

related to eating disorders among high school and college female cheerleaders. The

authors found that high school cheerleaders reported greater body dissatisfaction and

eating disorder patterns than that of their college counterparts although the high school

cheerleaders exhibited fewer sport pressures (Reel & Gill, 1996). Similar results were

found in a previous study on eating disorders among athletes, indicating that high school

athletes had more eating pathology compared to (college) varsity athletes (Hausenblas &

Carron, 1999). Researchers suggest further research is needed to more fully understand

the differences between high school athletes and collegiate players.

General Risk Factors for Sports Injuries

General risk factors for sports injuries are divided into two categories: personal

factors and environmental factors. Personal factors include gender, body size,

age/grade/experience, previous injury history, performance measures, and psychological

variables. Environmental factors include session type (competition/practice) and playing

surface condition.

Personal factors

Gender

According to previous studies, each sport shows a different gender effect, leading

to controversial results among researchers. Among sports with male and female teams

(e.g., soccer and basketball), the female injury rate per player tends to be higher than the

male injury rate (Powell & Barber-Foss, 2000; Rauh, Margherita, Rice, Koepsell, &

Rivara, 2000; Rauh, Koepsell, Rivara, Margherita, & Rice, 2006). According to Rauh

and colleagues (2006), girls were exposed to a significantly higher risk of injury. The

incidence rate for girls is 19.6/1,000 athletic exposures (AEs), and boys is 15.0/1,000

AEs for high school cross-country runners, resulting in ≥15 days of disability (Rauh et al.,

2006). In a systematic review of the sports injury literature on children and adolescents,

Emery (2005) identified that boys experience the highest rates of injury in hockey,

basketball, and football, whereas participating in gymnastics, basketball, and soccer

caused the highest injury rates for girls. In addition, males were identified as having

greater risk for injury (OR = 1.16-2.4) and re-injury (rates ranged from 13.1% to 38%),

showing that previous injury clearly increases the risk of injury in sports (Emery, 2005).

Similarly, the anterior cruciate ligament injury rates of women were significantly higher

than the rates for men in collegiate basketball and soccer (Agel, Arendt, & Bershadsky,

2005). Arendt and Dick (1995) reported the same results that female showed higher rates

of anterior cruciate ligament injury in basketball and soccer compared to male athletes.

According to a literature review on pediatric gymnastics injuries, young females’

commonly injured body parts in the upper extremity were the wrist, elbow, and

hand/finger, whereas young male gymnasts were most often injured at the shoulder,

followed by the wrist (Caine & Nassar, 2005). Greater body size (height and weight),

age, body fat, periods of rapid growth, and increased life stress were associated with an

increased injury risk among young female gymnasts (Caine & Nassar, 2005). Conversely

and surprisingly, however, a national report showed that there was no statistically

significant difference by gender for high school basketball and soccer (CDC, 2006).

Although many efforts have been made to address the gender difference between men

and women players (Arendt & Dick, 1995; Agel et al, 2005; Powell & Barber- Foss, 2000;

Rauh et al., 2000), better designed research studies need to be conducted to understand

why this difference exists.

Body size, age/grade/experience, performance measures

Older and more experienced athletes tend to be at higher risk than younger

athletes, and high school athletes who have increased size and weight are more

susceptible to sports injury. Pasque and Hewett (2000) report that high school wrestlers

who had a 32% greater experience level and were five months older had more injuries.

Conversely, Boden and colleagues (2003) suggested that limiting complex skills to

experienced cheerleaders can be a strategy to prevent severe injuries. This is derived

from their research finding that lack of experience, such as a small number of and limited

training of cheerleading spotters, was a risk factor for catastrophic cheerleading injuries

(Boden, Tacchetti, & Mueller, 2003).

Specific performance measures utilized to predict injury risk, such as the vertical

jump test, a test to measure “the difference between a person’s standing reach and the

height to which he or she can jump and touch” have been used (Klavora, 2000, p.70).

Most of the researchers who have conducted the performance measure studies, report no

relationship between risk of injury in athletes and performance testing (McGuine, 2006).

Previous injury history

Previous injury history has been regarded as a risk factor for future injury in many

studies (CDC, 2006; McGuine, 2006). For example, the recurrence of ankle sprains in

basketball ranges from 26% to 75% (Dick et al., 2007a; Leanderson, Nemeth, &

Eriksson, 1993; Yeung, Chan, So, & Yuan, 1994). Dick and colleagues (2007a) suggest

that previous sprain experience is the most common predisposing factor for an ankle

sprain in college basketball players.

Psychological factors

Regarding psychosocial factors, Junge (2000) reported that life events can

influence the risk of athletic injuries. Summarizing the findings of related studies, the

author indicated that only competitive anxiety has been identified to be associated with

injury occurrence although many other psychological factors such as personality traits

have been investigated by researchers (Junge, 2000). In a prospective cohort study to

measure the influence of psychological factors on injuries, Steffen and colleagues (2009)

found that a high level of life stress was a significant predictor for new injuries among

young female football players. In high school athletes, higher levels of preseason total

and negative life changes, low vigor, and high fatigue affect increased risk of injury

(Mcguine, 2006).

Environmental factors

Research findings have suggested that providing a safe environment for physical

activities needs to be prioritized to prevent sports injuries (Janssen, Dostaler, Boyce, &

Pickett, 2007).

Session types (competition vs. practice settings)

The majority of studies show that athletes are exposed to greater risk during

competition than practice (Agel et al., 2007c; CDC, 2006; Dick et al., 2007a, 2007b,

2007c; Mcguine, 2006). In a report that covered 16 years of NCAA injury surveillance

data, Hootman and colleagues (2007) found that injury rates were significantly higher in

games than practices for 15 sports studied. For example, Agel and colleagues (2007c)

reported that the injury rate of collegiate women’s basketball in a game setting was

almost two times higher than in a practice (7.68 vs. 3.99 injuries per 1,000 athlete

exposures). The authors attributed this finding to the fact that the competition allows

player to player contact, increased intensity, and an uncontrolled game situation (Agel et

al., 2007c).

Surface condition

Surface condition can influence injury patterns. Natural grass uniquely causes

non-contact epidermal and muscle-related trauma, whereas head and ligaments injuries

are more common on field turf (McGuine, 2006). In a systematic review of risk factors

in child and adolescent sports, the author reported that the type and/or condition of

playing surface was identified as a potentially modifiable risk factor that influences child

and adolescent sport players (Emery, 2003). According to Bahr and Krosshaug (2005),

training on a hard surface is a risk factor of injury, influencing an athlete’s performance

through increasing a bio-mechanical load. Boden and colleagues (2003) indicated that

complex stunts without floor mats or with wet mats were risk factors for catastrophic

injuries in cheerleading.

Some risk factors such as age, injury history, and session types have been

continuously supported by scientific evidence, but there are still controversial risk factors

that require more research. For example, a national study found that there was no

difference between girls and boys in terms of injury rate while many other studies

reported the higher injury rate of female players than that of male players (CDC, 2006).

In addition, sufficient research on psychological factors for adolescent sports injury needs

to be conducted since only a few studies have focused on this issue.

Prevention Efforts

Although a few studies have focused on sports injury prevention efforts (Junge,

et al., 2002; Marshall et al., 2005; Yang et al., 2005), studies about effective sports injury

prevention strategies for adolescents have not been conducted in a rigorous manner.

Need for better surveillance systems

Based on the success of prevention efforts through systematic monitoring of

infectious diseases, public health experts have imposed the need for strong surveillance

systems in the injury field. However, much of the work in developing injury surveillance

systems has been too expensive, thus requiring a need for more sustainable systems

development (Christoffel & Gallagher, 2006). Large-scale injury surveillance systems in

the U.S. include the National Electronic Injury surveillance System (NEISS), National

Hospital Ambulatory Medical Care Survey (CDC), and pertaining to college sports, only

the National Collegiate Athletic Association Injury Surveillance System (NCAA- ISS).

NCAA-ISS was developed to provide injury trends data in intercollegiate athletics.

Athletic injury and exposure data are collected yearly from a sample of NCAA member

institutions (National Collegiate Athletic Association [NCAA], 2010).

Although the need for national sports injury surveillance systems has been

advocated by researchers (Caine & Nassar 2005; Fernandez et al., 2007), few studies on

sports injury assessment have been conducted. In the studies that have been done, data

were collected at the micro level, confined to a school or a sport, and the methods were

not described in sufficient detail. In addition, very little information is delivered from

existing surveillance systems utilizing a computerized database. The Athletic Injury

Monitoring System (AIMS) is a computer database for injury surveillance for a variety of

sports, capturing general injury rates, concussion rates, prophylactic knee braces, and

football helmets (Zemper, 2003). One study on the relative risk of a second cerebral

concussion conducted using AIMS indicates that the risk of sustaining a cerebral

concussion is approximately six times higher for football players who have had a

concussion history than for those who do not (Zemper, 2003). AIMS was managed by

Exercise Research Associates (ERA), and certified athletic trainers at each participating

school submitted a form indicating how many players had a concussion history during the

last five years as a baseline based on the medical history of each player. In addition, the

trainers provided weekly reports throughout each season for two years containing data on

exposure to the injury possibility in practices and games and on any injury that impeded

players’ participation for one day or more (Zemper, 2003).

Recently, an online injury surveillance tool was developed by the Center for

Injury Research and Policy at Columbus Children’s Hospital in Columbus, Ohio to

collect athletic injury exposure and outcome data (e.g., number of injuries and detailed

information about each injury) (Center for Injury Research and Policy, 2010). The

surveillance system, Reporting Information Online (RIO) allows 24/7 access to report,

revise, and update injury data on the internet, utilizing the RIO software which was

designed for prospective surveillance studies targeting large, geographically disperse

study populations (Center for Injury Research and Policy, 2010). In a study utilizing

RIO, Comstock and colleagues (CDC, 2006) investigated injury incidence and athletic

injury exposure data for 100 nationally representative high schools. The data were

collected by certified athletic trainers for nine high school sports, including baseball,

football, wrestling for boys; softball and volleyball for girls; and basketball and soccer for

both boys and girls. The authors reported that approximately 1, 442,533 sports injuries

occurred among US high school athletes during practices or competitions in the 2005-06

school year (CDC, 2006).

A sports injury surveillance registry for high school athletes was developed by

the Sports Medicine and Athletic Related Trauma (SMART) Institute of the University of

South Florida College of Medicine (Liller et al., 2009). The SMART injury registry was

designed to provide data on incidence, prevalence, risk factor, and exposure for high

school athletes in West Central Florida. Beginning in August, 2007, 10certified athletic

trainers (ATCs) were hired and trained for placement in 10 public high schools to serve

the athletes’ medical needs and to collect the injury data. According to SMART’s annual

report for the 2009-2010 academic year, data were collected on athletes participating in

football, baseball, volleyball, swimming, track, cross-country, flag football, soccer,

basketball, golf, wresting, softball, tennis, and cheerleading. A total of 365 injuries were

reported by six ATCs who worked at six public high schools, utilizing professional sports

injury surveillance software created by Simtrak TM

. The injury rage per 1000 athlete-

exposures for competitions was greatest for football at 15.2, followed by flag football at

6.69 and women’s basketball at 6.41. Sprains and strains were the leading physiologic

injuries, and the leading body sites injured were the ankles, knees, and head.

Protective equipment

Emery (2005) conducted a systematic review of the sports injury related

literature to examine risk factors and prevention strategies in child and adolescent sports

injury. The author summarized that previous studies promote neuromuscular training

programs (i.e. balance training programs) and the use of sports-specific protective

equipment (i.e. helmets). This supposes that the use of protective equipment in many

sports such as full face masks and mouth guards in hockey, face shields and safety balls

in baseball, shin pads in soccer, and helmets in cycling, skiing and snowboarding, exert

protective effects (Emery, 2005). The author also found that educational strategies in

combination with legislation of facility/sport association requirements may be the best

approach to increase the use of protective equipment among athletes (Emery, 2005).

Marshall and colleagues (2005) reported that their study research findings support the

effectiveness of protective equipment used in rugby unions such as mouth guards, padded

headgear, and support sleeves in preventing orofacial injuries, scalp injuries, and

sprains/strains, respectively. According to a literature review on sports injuries

conducted by McGuine (2006), effects of protective equipment, such as braces, protective

padding, protective eyewear, and knee pads are prevalent overall, whereas the use of

ankle braces is associated with an increased risk of football injury. Collins and

colleagues (2006) examined the prevention effects of a new helmet technology by

comparing concussion rates and recovery times between traditional helmets and newer

helmets among high school football players. The new football helmet was developed to

reduce the risk of concussion among athletes and had improved features in the exterior

shell, interior liner construction, and offset from the interior surface of the shell to the

wearer’s head (Collins, Lovell, Iverson, Ide, & Maroon, 2006). The three-year protective

cohort study shows that wearing the new helmet decreased approximately 31% of relative

risk and 2.3% of absolute risk for sustaining cerebral concussions (Collins et al., 2006).

Rule change and related strategies

Hootman and colleagues (2007) emphasized that implementing and enforcing

existing rules and policies developed for competitions needs to be considered. This is

important since many game and practice injuries are associated with player contact. Dick

and colleagues (2007b) requested consistent efforts to change or modify existing rules in

football based on appropriate injury surveillance data with the prevention measures

emphasizing position-specific activities. Experts also recommend that football rules that

prohibit illegal blocking or tackling must be strictly enforced by coaches and officials

(Lawrence, Stewart, Christy, Gibbs, & Ouellette, 1997). To prevent and reduce wrestling

injuries, researchers suggested the need for intensive efforts by referees to be vigilant to

potentially dangerous holds and trainers’ efforts to improve wrestler and mat hygiene

(Agel et al., 2007b). Recently, the National Federation of State High School

Associations (NFHS) released a revised concussion rule which reflects the experts’

recommendations (NFHS, 2010). According to the revised rule, any player who shows

signs, symptoms, or behaviors associated with a concussion must be removed from the

game and shall not return to play until cleared by an appropriate health-care professional.

In the previous rule, the loss of consciousness was used to be a standard of judgment to

remove a concussed player. However, with the revised rule, officials now can also

remove any player with concussion symptoms as headache, dizziness, confusion, or

balance problems (NFHS, 2010).

In a cluster randomized controlled trial, Emery and colleagues (2007) identified

that a basketball-specific balance training program for high school basketball players was

effective in decreasing acute-onset injuries. A standardized warm-up program was

provided both to the control (n = 426) and the training group (n = 494), and the training

group had an additional warm-up component and a home-based balance training program

(Emery, Cassidy, Klassen, Rosychuk, & Rowe, 2007). However, there is no information

on how often the home training was implemented nor how it contributed to the

effectiveness of the intervention. The lack of this information may hinder an accurate

evaluation of the program although the study utilized clustered randomization. Wang and

colleagues (2006) also suggested the need for balance training to prevent ankle injuries in

basketball, recommending the one-leg standing test as “a screening tool to recommend

balance training before the basketball season” (Wang, Chen, Shiang, Jan, & Lin, 2006, p.

824). Dick and colleagues (2007a) reported that prophylactic taping, bracing, and

balance training were effective in preventing basketball ankle sprain injury, especially

among college basketball players who had previous sprains. Kaut and colleagues (2003)

insisted on the need for educational interventions for head injury prevention. They

presented a study result that 56% of all athletes did not have knowledge of possible

consequences following a head injury although approximately 32% of all athletes have

head blow experiences causing dizziness (Kaut, DePompei, Kerr, & Congeni, 2003).

Researchers, including the authors of this study, suggested future education as a tool to

prevent and reduce injuries based on their descriptive study findings only. However, for

successful injury prevention in high school athletes, more specific strategies and

recommendations from scientific evidence should be provided. To evaluate prevention

programs, prospective research with randomized controlled trials is needed. For the

strategy impact assessment, long term studies are also needed.

Other efforts

As an effort to develop sports injury prevention strategies, the use of the Haddon

Matrix was suggested by a group of researchers from the National Athletic Trainers

Association (NATA, 2004). The Haddon Matrix has significantly contributed to a greater

understanding of injuries based on the epidemiology model (Lett, Kobusingye, & Sethi,

2002). The first axis of the Matrix consists of the core elements of the epidemiological

triad - host, (agent)/vector, and environment, and the second axis includes three time

phases ( pre-injury phase, injury phase, and post-injury phase), indicating that prevention

efforts can be done at one or at all of the three times (Lett et al., 2002). The NATA

researchers indicated that the matrix can be used in brainstorming to design interventions

according to a specific time phase and a specific risk factor (NATA, 2004). They also

presented an example of the Haddon Matrix applied to sports injury (p. 68) (Table 1).

Table 1

Haddon Matrix Applied to the Problem of Athletic Injuries (NATA, 2004, p.68)

Phases

Host Agent/Vector Physical

Environment

Social

Environment

Before

injury

Determine the

individual’s

readiness to

participate

Advise on

the selection,

fit, function,

and

maintenance

of athletic

equipment

Promote safe and

appropriate

practice,

competition, and

treatment

facilities

Provide

scientifically sound

nutritional

counseling and

education.

Develop and

implement a

comprehensive

athletic health care

administrative

system

Injury Protective

Responses

Player size and

speed

Establish protocols

regarding

environmental

conditions

Rules enforcement

After

injury

Facilitate

rehabilitation

and

reconditioning

Exposure to

repeat trauma

Develop and

implement a

comprehensive

emergency action

plan.

Provide for on-site

recognition,

evaluation, and

immediate

treatment of injury

and illness, with

appropriate

referrals.

Provide for

psychosocial

consultation and

referral.

Hootman and colleagues (2007) presented a few injury prevention strategies to

decrease preseason injury rates. These included “phased-in, multiple-day practices;

modifying practice times to accommodate environmental conditions; mandating

appropriate recovery time; and pre-participation medical examinations” (Hootman et al.,

2007, p. 313). In preventing and reducing sport-related concussions, the researchers

emphasized that certified athletic trainers and team physicians should utilize objective

data in evaluating athletes who have concussions (Oliaro, Anderson, & Hooker, 2001;

Osborne, 2001). These included appropriate grading scales, a symptom checklist, the

Balance Error Scoring System, and the Standardized Assessment of Concussion, rather

than using subjective judgment (Oliaro et al., 2001; Osborne, 2001). Training coaches

are critical to preventing injuries. A study showed that coaches’ medium level of

education, qualification, and training (EQT) is related to approximately a 40% reduction

in cheerleading injury risk (Schulz et al., 2004).

Bundy and Feudtner (2004) suggest improvement of the current Participation

Physical Evaluation (PPE) system for high school athletes. According to the authors,

current PPEs deliver a false sense of safety. They propose a research agenda to improve

current PPEs as follows:

(1) Improve the Evidence Base Regarding Effectiveness.

More studies on effectiveness of PPE that target various venues and practitioners and

examine its contents need to be conducted.

(2) Enhance Systems-Level Approaches.

System-wide changes proven by previous research such as enforcing safety-related

regulations and improving field conditions should be implemented more actively.

(3) Develop and Evaluate New Delivery Methods.

New delivery methods for PPE including computer or web-based options should be

developed.

(4) Evaluate Additional or Alternative Objectives.

Other preventive services need to be developed and tested for adolescent health and

safety (p.261).

Overall, very few studies have addressed sports injury prevention for high school

athletes. These studies have largely focused on limited issues such as safety equipment

use and the development of safety rules (Francisco et al., 2000; Theye & Mueller, 2004;

Yang et al., 2005). Among the prevention studies reviewed, team sports such as football

and basketball have had greater focus than individual sports. More prevention research

for high school athletes and their individual sports should be conducted. Additional

evaluative studies to examine direct relationships between the prevention strategies and

injury outcomes are also needed. In terms of study design, many prevention studies

utilized a cluster randomized control trial which is understandable considering the

makeup of team sports. To ensure effectiveness of prevention programs and to generalize

the results, researchers should continue to make efforts to use randomization wherever

possible. In addition, researchers suggest the importance of multifaceted prevention

approaches to reduce injuries (Agel et al., 2007c; Dvorak et al., 2000). However, there

has been very little specific information provided as to how the multifaceted approach

can be effectively applied to sports injury prevention research and practice. Only one

study reviewed presented a table utilizing the Haddon Matrix which includes

multifaceted factors to design prevention interventions (NATA, 2004). Therefore, more

active research on multifaceted approaches for sports injury prevention needs to be

conducted.

Coaches and Sports Injuries

Coaches’ influence on athletes

There is sufficient evidence that coaches influence not only the physical

performance of athletes but their psychological factors, which in turn affect the athletes’

achievements in sports. According to Ommundsen and colleagues (2006), a supportive,

mastery-oriented coaching style was related to athletes’ constructive psychosocial

outcomes such as high-quality friendship and positive competency perceptions whereas

joint pressuring behavior of parents and coaches was associated with maladaptive

achievement. This includes over-concern for mistakes and doubt about one’s actions

(Ommundsen, Roberts, Lemyre, & Miller, 2006). In a literature review on the risk of

injury to gymnasts, Daly and colleagues (2001) also put a great emphasis on coaches’

influence on athletes’ self-esteem, stating “there is some suggestion that a gymnast’s self-

esteem can be significantly affected by the coach’s feeling, attitudes, and behavior toward

team- mates” (Daly, Bass, & Finch, 2001, p. 12).

In addition, research has shown that coaches are perceived as one of the most

influential social supporters by their athletes. According to Rosenfeld and colleagues

(1989), athletes perceived that coaches provided task challenge, task appreciation, and

emotional challenge support whereas reality confirmation support, listening support, and

emotional support were not provided (Rosenfeld et al., 1989). In a study on high school

athletes’ perceptions about coaches’ social support before and after injury (Malinauskas,

2008), athletes felt that there was no difference in coaches’ support between pre-injury

and post-injury with two exceptions: more listening support and emotional support at post

injury. The author concluded that coaches’ listening and emotional support for injured

high school athletes may have positive effects on their rehabilitation (Malinauskas,

2008).

As the most immediate caregivers for injured athletes, coaches are expected to

play an important role in preventing and reducing injuries. Utilizing a web-based survey,

Cross and colleagues (2010) conducted a study to examine the need for education of high

school coaches in the prevention, assessment and management of sports-related injuries.

The results indicated that the majority of the respondents reported they were responsible

for the immediate medical care of athletes at practices (89.07%) and competitions

(74.90%) (Cross et al, 2010). In addition, 79.96% of the coaches surveyed agreed or

strongly agreed they needed more education on sports injury management. The role of

coaches in injury prevention was discussed in Hergenroeder’s literature review (1998)

that addressed sports injury prevention among children, adolescents, and young adults.

Even though the article primarily emphasized a pediatrician’s role in injury prevention,

the coaches’ role to prevent and reduce sports injuries is also well-described based on

empirical studies (Hergenroeder, 1998). The author indicated that the role of coaches

was critical in injury prevention and reduction in that it influenced players’ motivation,

self-esteem and fun experience in sports. Regarding coaching factors, the author

suggested that adequate technical training for coaches is important in injury prevention

since performing skills are associated with sports injury rates (Hergenroeder, 1998).

Daly and colleagues’ literature review on gymnastic injuries (2001) also showed that

poor coaching techniques may increase the risk of injury.

Injury prevention provided by coaches

Otago and colleagues (2005) assessed the risk management knowledge of

basketball coaches and the coaches’ influence on the injury prevention strategies for the

players using a face to face interview. The results showed that 70% of the coaches who

had completed a coach accreditation course believed that they had good or better

knowledge of injury prevention measures, and three-fourths of the coaches perceived that

they played a major role in injury prevention education (Otago et al., 2005). The

implications from this study are that injury prevention information should be included in

coach accreditation courses, and the injury prevention programs provided by coaches

may be an effective approach to decrease the risk of injury. As an evaluation of

effectiveness of injury prevention programs delivered through coach education, a survey

was conducted for netball and football/soccer coaches in New Zealand (Gianotti, Hume,

& Tunstall, 2008). The injury prevention courses for the two sports, NetballSmart and

SoccerSmart, are based on SportSmart which was developed by the Accident

Compensation Corporation for sports injury prevention (Gianotti et al, 2008).

SportSmart consists of a 10-point plan: (1) screening; (2) warm-up, cool-down and

stretch; (3) physical conditioning; (4) technique; (5) fair play; (6) protective equipment;

(7) hydration and nutrition; (8) injury reporting; (9) environment; and (10) injury

management (Gianotti et al, 2008). The results showed that 89% of netball coaches

changed their way of training after attending a NetballSmart course as an effort to

incorporate injury prevention behaviors into player practices, and at least 70% of those

coaches reported that their athletes had changed their landing and stopping, dodging

ability, and cool-down/recovery procedures which are known to contribute to reducing

risks of injury. Also, 96% of football/soccer coaches indicated that they changed the way

to teach warm-up/cool-down and stretching after attending the injury prevention course

for coaches (Gianotti et al, 2008).

Berg and colleagues (1998) surveyed 508 coaches’ perceptions about oral-facial

injuries and mouth-guard use among high school athletes. Although the American Dental

Association recommends the use of oral-facial protection for those who are at significant

risk of experiencing sports injury (Berg, Berkey, Tang, Altman, & Londeree, 1998), the

results showed that only 11% of girls’ volleyball coaches who reported oral-facial-

injuries had provided their athletes with education on the topic. Indicating that coaches

who are aware of oral-facial-injuries are more likely to be in favor of mouth-guard use,

the authors asserted a great need for coach education to encourage mouth-guard use as an

injury prevention strategy. Sawyer and colleagues (2010) also indicated that only 7.2% of

coaches surveyed replied that they had distributed the Fact Sheet for Athletes as an

educational source for concussion prevention. This study was conducted to evaluate

school coaches’ perceptions, assessments, and use of a toolkit developed by CDC to

prevent and manage concussions among high school athletes.

Yang and colleagues (2005) investigated the patterns and determinants of

discretionary (non-mandatory) protective equipment use through an analysis of three-

years of data of 19,278 athletes from 100 high schools in North Carolina. Head coaches’

education, qualifications, and training (coach EQT) was measured to assess the schools’

social environment and the coaches’ influence on the use of lower extremity discretionary

protective equipment (LEDPE) such as kneepads, shin guards, knee braces, and ankle

braces (Yang, et al., 2005). The coach EQT section includes five binary questions that

assessed if the coach (1) coached the particular sport more than one year at a high school

level or higher; (2) played the sport more than one year at a high school level or higher;

(3) had a graduate level of education; (4) was currently certified in a safety-related area;

and (5) had taken a coaching class. The findings from the EQT variables showed that a

low player/coach ratio was associated with increased use of LEDPE although there was

no relationship between coach EQT and LEDPE use (Yang, et al., 2005). However, Daly

and colleagues (2001) indicated several studies reported the student/instructor ratio was

not related to injury rate.

Studies have shown that coaches need to be provided with injury prevention

education based on scientific evidence. Shehab and colleagues (2006) investigated how

high school coaches actually recognize and practice pre-exercise stretching (PES). The

results showed that approximately 95% of the coaches recognized stretching was helpful

to decrease injury risk, and almost 73% believed that there were no disadvantages in

stretching (Shehab, Mirabelli, Gorenflo, & Fetters, 2006). However, recent studies

showed disadvantages of pre-exercise such as stretching which does not help reduce

sports injury rates. For example, ballistic stretching involving bobbing, bouncing,

rebounding, and rhythmic types of movement can cause muscle soreness and injury due

to its potentially impairing effect on muscle performance (Human Kinetics, 2009). The

coaches also replied that personal experience and scientific evidence would most likely

influence their future recommendations on PES. However, not all studies support the

positive association between coach-related factors and sports injury outcomes. For

example, Weiker (1985) found no relationship between injury rate and coach-related

factors such as the number of instructors with or without safety certification.

Coaching education & certification

Researchers have suggested that injury prevention programs within coaching

education may be an effective strategy to help reduce the risk of injury, and injury

prevention should be considered as one principle of all the competencies required to be a

coach (Cross et al., 2010; NASPE, 2009; Otago et al, 2005). For example, the National

Standards for Sport Coaches suggested by NASPE (2009) include Safety and Injury

Prevention as one of the eight standards (Table 2).

Table 2

Eight Domains of Coaching Competencies Developed by the National Association for

Sport and Physical Education (NASPE)

Domain Contents

1. Philosophy and Ethics

athlete-centered coaching philosophy and professional

accountability for fair play

2. Safety and Injury Prevention

coach responsibility for providing safe conditions and

appropriate actions when emergencies arise

3. Physical Conditioning

behavioral description of coaching responsibilities in the

areas of physiological training, nutrition education, and

maintaining a drug-free environment

4. Growth and Development

developmental considerations in designing practice and

competition to enhance the physical, social, and emotional

growth of athletes

5. Teaching and Communication

individualizing instruction, empowering communication

skills, and using good management techniques in

designing practices

6. Sport Skills and Tactics

the need for coaches to have basic sport knowledge and be

able to apply it to the competitive environment

7. Organization and Administration

risk management responsibilities as well as effective use of

human and financial resources

8. Evaluation

ongoing evaluation responsibilities of the coach in areas

such as personnel selection, on-time reflection of practice

effectiveness, progress toward individual athlete goals,

game management, and program evaluation

Gianotti and colleagues (2008) specifically recommended coaches have a

responsibility to maintain up-to-date knowledge of athletes’ health issues and injury

prevention programs to minimize the potential risk of sports injuries. Although experts

suggest that quality coaching education and a standardized certification system need to be

provided for coaches to be prepared for their responsibilities (NASPE, 2009), it seems

there are problems both in injury prevention education itself and society’s attitude

towards coaching education and certification (Burgeson, Wechsler, Brener, Young, &

Spain, 2001; DeRenne, Morgan, Hetzler, & Taura, 2007).

Based on the findings of the School Health Policies and Programs Study (SHPPS)

conducted by CDC in 2000, Burgeson and colleagues (2001) reported that only 34% of

states in the US require coaches to complete a training course, 40% require them to be

certified in first aid, and 40% require cardiopulmonary resuscitation (CPR) certification.

Almost all the junior/middle and senior high schools examined (99.2%) provided

interscholastic sports, but only 51.7% of the schools required their head coaches to

complete a coaches’ training course, 51.3% required first aid certification, and 45.6%

required CPR certification (Burgeson et al., 2001). DeRenne and colleagues (2007) also

reported that a majority of Hawaii High School Athletic Association (HHSAA) athletic

directors (88.14%) did not require any formal coaching certification for their baseball

head coaches, and 67.8% did not require CPR nor first aid certification. Recent studies

show that many coaches do not have current certification in CPR and first aid. According

to a study investigating medical coverage of high school athletics in North Carolina

(Aukerman et al., 2006), most of the high school coaches at the surveyed schools did not

have certifications in CPR nor first aid. Cross and colleagues (2010) also reported that

less than 50% of the coaches surveyed in South Dakota had current CPR or first aid

certification in a study to assess the need for sports injury-related education of high

school coaches.

Sands (2000) pointed out there is no license for gymnastics coaches in the US

although they typically have a college degree. The author also indicated that there is no

formal training in injury prevention and rehabilitation in gymnastics coaching, and the

only test a gymnastics coach may ever take is a test for safety certification on basic

aspects of gymnastics environmental safety. The author requested the development of

schools of coaching, certification, and licensure, indicating that the coaches with first aid

certification were more likely to answer rest/ice/compression/elevation as a soft tissue

injury treatment (Sands, 2000).

According to a survey of basketball injury, warm-up was answered as a major

injury prevention measure by the coaches (Otago et al., 2005). The players also reported

that their coaches encouraged warm up the most. Interestingly, 50% of 27 coaches

indicated that they acquired their knowledge of prevention from playing experience

whereas only 18.5% believed that their injury prevention knowledge came from coach

accreditation courses. The authors recommended that injury prevention should be

included in coach accreditation courses, emphasizing the importance of coaches’ role in

injury prevention (Otago et al., 2005).

Dils and Ziatz (2000) developed a list of desired student athlete learning outcomes

needed for coaches to pursue quality coaching standards, such as the National Coaching

Standards developed by the National Association for Sport and Physical Education. The

learning outcomes include: self-confidence (A student athlete will be able to develop a

positive and accurate perception of one’s ability to fulfill one’s own intentions.); self-

respect(A student athlete will be able to feel that one has self-worth and has an equal

right to fair treatment and available rewards.); self-discipline (A student athlete will be

able to control aggression and control one’s own on-task and off-task actions through

self-regulation.); circulo-respiratory efficiency (A student athlete will be able to develop

and maintain optimal circulatory and respiratory functioning.); and the courage to act (A

student athlete will be able to take action that reflects one’s best evaluation of a just

balance among autonomy, altruism, and responsibility.) (Dils & Ziatz, 2000). The

authors suggested that the student athlete learning outcomes could contribute to defining

the educational role of the interscholastic athletics coaches and stimulating further

research on coaching education curriculum (Dils & Ziatz, 2000).

In Australia, a study assessed injury knowledge and technical needs of junior

Rugby Union coaches (Carter & Muller, 2008). There was a significant positive

relationship between the total number of seasons coached and the injury knowledge

score. The coaches surveyed replied that education on the mechanisms of injury and

early management of minor and soft tissue needs to be included in Rugby Union

coaching programs (Carter & Muller, 2008).

Coaching education as an injury prevention strategy seems cost effective. The

Accident Compensation Corporation (ACC) in New Zealand published an article on cost

effectiveness of sports injury prevention programs (Gianotti & Hume, 2007). They

assessed the cost of sports injury and compared it with the cost of intervention programs

at a national level. A total of nine injury prevention programs have been conducted with

ACC’s financial support and three of them included coach education (Gianotti & Hume,

2007). The pre-implementation cost-outcome results show that most injury prevention

initiatives, including the coach education programs, were cost-effective, and the post-

implementation cost-outcome results indicate that injury prevention programs for Rugby

Union and snowboarding/skiing respectively are expected to be cost-saving, generating a

positive return on investment (Gianotti & Hume, 2007). In this study, one criteria of the

definition of injury includes “there must be a link between the two (injury and accident)”

(p. 438), but not only the extent of “injury” is ambiguous but also identifying the

causation between accident and injury is not easy. The formulas used have the power to

control external variables that can interfere with the correct interpretation of the

effectiveness of the nine initiatives. Used is the concept of “unadjusted claims” that

involves 28 confounding variables based on the ACC’s claim database. This study may

be valuable in that it could provide a foundation for cost outcome studies for injury

prevention interventions such as coach education.

Instruments to measure coach factors

There are very few instruments to assess those coaching factors influencing

sports injuries although accurate accounting can contribute to the development of

effective prevention programs. Among existing measures, the Coaching Behavior

Assessment System (CBAS), which was developed to measure coaches’ behaviors in

athletic settings, has provided a basis in developing coach-related instruments (Smith,

Smoll, & Christensen, 1996). The social learning theory was used as a theoretical

foundation, and 12 categories were determined through a content analysis of coaches’

behaviors observed during practices and games. The CBAS consists of 12 categories

under two major classes, reactive behaviors (responses to desirable performances) and

spontaneous behaviors (game-related spontaneous behaviors), as shown in Table 3

(Smith et al., 1996). In addition, the authors introduced a training program including a

training manual, instructions for scoring, a written test, the scoring of videotaped

sequences, and extensive practice in actual field settings (Smith et al., 1996). The authors

indicated that, in the several studies on the reliability of the CBAS coding system, the

results showed good consistency of scoring over time and high inter-rater reliability in

coding.

To examine the effectiveness of coaches’ self-efficacy on sports-related

outcomes, a conceptual model was suggested by researchers using the instrument, the

Coaching Efficacy Scale (CES) (Feltz, Chase, Moritz, & Sullivan, 1999). Coaching

efficacy was defined as “the extent to which coaches believe they have the capacity to

affect the learning and performance of their athletes” (p. 765). The model hypothesizes

that various sources of coaching efficacy influence coaching efficacy dimensions. These

Table 3

Sub-categories of the Coaching Behavior Assessment System

Reactive

behaviors

A. Desirable

Performance

1.Positive reinforcement or reward

2.Nonreinforcement

B. Mistakes/Errors 3.Mistake-contingent encouragement

4.Mistake-contingent technical instruction

5.Punishment

6.Punitive mistake-contingent technical

instruction

7.Ignoring mistakes

C. Misbehaviors 8.Keeping control

Spontaneous

behaviors

A. Game related 9.General technical instruction

10.General encouragement

11.Organization

B. Game irrelevant 12.General communication

efficacy categories consist of four components: Game Strategy, Motivation, Technique,

and Character Building, and the dimensions then affect the sports-related outcomes such

as coaching behavior and athletes’ learning and performance (Feltz, et al., 1999). In

preliminary work targeting high school coaches, a coach’s past success, coaching

experience, perceived player talent, and social support predicted coaching efficacy.

Coaching efficacy, in turn, predicted coaching behavior, player satisfaction, and current

success (Feltz, et al., 1999). The CES II was introduced in 2008 with several revisions

including one additional dimension, physical conditioning (Myers, Feltz, & Wolfe, 2008)

(Table 4).

Table 4

Sub-categories of Coaching Efficacy Scale II

Coaches vs ATCs

According to an article that reviewed case law about the standard of care for

athletic trainers (West & Ciccolella, 2004), athletic trainers and coaches have a general

duty to protect the health and safety of their athletes. However, the athletic trainers have

a distinguished role for an injured athlete compared to coaches in the aspect that they

treat injuries or make judgments about the severity of a physical condition. The court

Motivation efficacy the confidence coaches have in their ability to affect the

psychological mood and psychological skills of their athletes

Game strategy efficacy the confidence coaches have in their abilities to lead during

competition

Technique efficacy the confidence coaches have in their instructional and

diagnostic skills

Character building

efficacy

the confidence coaches have in their abilities to influence the

personal development and positive attitude toward sport in

their athletes

Physical conditioning

efficacy

the confidence a coach has in his or her ability to prepare his

or her athletes physically for participation in their sport

considered coaches as the prudent person holding educational backgrounds which include

courses in first aid and the prevention/treatment of athletic injuries, but the specialized

skills and knowledge of athletic trainers are beyond that possessed by coaches (West &

Ciccolella, 2004). Ransone and Dunn-Bennett (1999) conducted a study to assess high

school coaches’ first-aid knowledge and decision-making on athletic injuries in various

hypothetical injury situations. Interestingly, the coaches who passed the First Aid

Assessment decided to return injured players to the game compared to the coaches who

failed the assessment but chose to keep the player out of the game (Ransone & Dunn-

Bennett, 1999). The authors suggested that certified athletic trainers should provide all

medical care for high school athletes, reporting that the athletic coaches did not

adequately meet the first-aid standards which were generated in accordance with the

American Red Cross.

Even though there is no study to examine the difference in injury prevention

efforts and efficiency between the coaches who have medical staff and those who do not,

a study reported that certified athletic trainers (ATCs) are more accurate in reporting

injuries than coaches (Yard, Collins, & Comstock, 2009). The study was conducted to

compare quantity and quality of exposure and injury reports between high school coaches

and ATCs. The findings showed that the ATCs submitted almost all of the expected

exposure reports with accuracy whereas the coaches reported only one-third of the

expected reports, and one-third of these reports submitted were inaccurate (Yard, Collins,

& Comstock, 2009).

Mensch and colleagues (2005) conducted a qualitative study utilizing semi-

structured interviews to explore the perspectives of coaches and ATCs pertaining to the

role of the ATCs in high school settings. The study results indicated that the coaches

were weak at describing their need for ATCs whereas ATCs explicitly described their

duties differentiated by phases of the sport season (Mensch, Crews, & Mitchell, 2005).

The authors emphasized the importance of coaches’ knowledge on the ATCs’ various

roles that can lead to the health care success of a team.

In terms of research on coaches and sports injuries, there is sufficient evidence

that coaches influence not only the physical performance of athletes but their

psychological factors, which in turn affects the athletes’ achievements in sports.

However, their role, perceptions, and behaviors related to controlling sports injury have

not been well addressed. There are only a few studies describing injury prevention

programs provided by coaches, and the research on the effectiveness of the programs is

limited. The causal relationship between coach factors and injury outcomes has not been

clearly researched nor demonstrated. In addition to the existing studies about coaches

and ATCs, more research needs to be conducted to compare injury-related perception and

practice of coaches who have medical staff and those who do not. If scientific evidence

supports superiority of either group in preventing and reducing injuries, available efforts

should be focused on the superior group’s effective injury prevention activities.

Theories and Models in Sports Injury Research

Theories and models provide a systematic view for researchers to explain and

predict human behavior, guiding why people behave in a specific way, what we should

know, and what should be done to change a specific behavior (Glanz, Rimer, &

Viswanath, 2008). Considerable research has been conducted to validate health behavior

theories and models for injury issues (Clement, 2008; Deroche, Yannik, Brewer, &

LeScanff, 2007; Finch, Donohue, & Garnham, 2002; Gielen, Sleet, & DiClemente, 2006;

Levy, Polman, & Marchant, 2008; Yang et al., 2005). However, there still is a lack of

behavioral and social science theories and models applied in sports injury research.

A systematic review to identify what social science theories and models have

been utilized for sports injury prevention shows that the Health Belief Model, Theory of

Planned Behavior, and Social Cognitive Theory were most frequently cited in 50 sports

injury related articles (McGlashan, Finch, Aucote, & Twomey, 2009).

Health Belief Model

The Health Belief Model (HBM) was developed in the 1950’s by social

psychologists in the U.S. as a theoretical framework to explain people’s participation in

health programs which aim to prevent and detect diseases (Glanz, et al., 2008). The

HBM is classified as one of the value-expectancy theories that emphasize the importance

of individual value and expectations in explaining health behavior (Glanz, et al., 2008).

In the HBM, the value represents individual desire to avoid illness conditions due to

disease or injury, and the expectation is elaborated as the beliefs that a specific health

behavior will prevent the illness outcomes. The HBM constructs consist of several

concepts that predict peoples’ action to prevent or to control illness conditions; these

include susceptibility (feeling about the chances of experiencing a risk), severity (belief

about how serious a condition is and what its consequences are), benefits (belief about

benefits of the advised action) and barriers (belief about the negative aspects of the

advised action) to a behavior, cues to action (strategies to activate “readiness”), and most

recently, self-efficacy (confidence in one’s ability to take action) (Glanz, et al., 2008).

A study to examine determinants of “perceived susceptibility” to sport related

injury was conducted based on the assumption “once people perceive themselves as being

susceptible to health risks, they form intentions to take preventive actions, or to give up

risky health behavior” (Deroche et al., 2007) (p. 2219). In the study, previous experience

with injury and personality factors were identified as predictors of perceived

susceptibility to injury among French rugby players. Personality factors consisting of

neuroticism (anxiety, anger-hostility, depression, social shy, impulsiveness, and

vulnerability) and global self-esteem were also positively related to perceived

susceptibility (Deroche et al., 2007).

The Victorian Health Promotion Foundation (2006) conducted a survey to

investigate parental perception of sports injury risk. The survey included all the

constructs of the Health Belief Model to assess parental perception of sports injury risk–

perceived susceptibility, perceived severity, perceived benefits, perceived barriers, cues

to action, and self-efficacy. Eight-hundred-forty-five parents of children who

participated in 46 sports in Australia responded to the survey, and 55 phone interviews

were conducted for further analysis (Victorian Health Promotion Foundation, 2006). The

majority of parents surveyed believed that their child would not experience a serious

injury when participating in sports although they thought their child was susceptible to

sports injury. The parents of children involved in contact and incidental collision sports

reported greater perceived susceptibility and severity to injury. The results also showed

that the parents generally felt “happy” for their child to participate in a sport if there was

no risk of injury although their child will have “fun” regardless of the safety of the sport

(perceived benefits) (Victorian Health Promotion Foundation, 2006). Not following safe

practice was considered as a barrier by the parents whereas cost of protective equipment

and loss of spontaneity by protective equipment use were not perceived as barriers. In

terms of perceived ability to take action, the parents were confident of taking preventive

action to ensure their child’s safe participation in a sport. As cues to take action,

officials, use of protective equipment, and trained coaches were perceived as important

factors in reducing the risk of sports injury (Victorian Health Promotion Foundation,

2006).

Theory of Planned Behavior / Theory of Reasoned Action

The Theory of Planned Behavior (TPB) was developed by Ajzen (1991) through

adding perceived behavioral control to the Theory of Reasoned Action (TRA). The TRA

was created to predict human behavior based on the assumption that behavioral intention

is the most important determinant of human behavior. The perceived behavioral control

was added based on the concept that environmental factors outside individual control

could affect intentions to perform a specific behavior (Ajzen, 1991). The main constructs

of the TPB include attitude (behavioral beliefs and evaluations of behavioral outcomes),

subjective norm (normative beliefs and motivation to comply), and perceived control

(control beliefs and perceived power). According to the TPB, each main construct

(attitude, subjective norm, and perceived control) influences “intention” to perform a

specific behavior and the behavioral intention leads to performing the behavior.

However, a direct relationship could exist between perceived control and behavior when

a person has high confidence about his/her perceived control. In this case, perceived

control is not used to create behavioral intention; it directly influences the target behavior

(Ajzen, 1991).

Applying the Theory of Planned Behavior (TPB), Sagas and colleagues (2006)

developed a questionnaire to identify male and female assistant coaches’ intentions to

become head coaches. The authors’ main hypothesis was that there would be a gender

difference in head coaching intention between men and women such that women assistant

coaches would have less intention than men to become a head coach in the next three

years (Sagas et al., 2006). Previous studies utilizing the TPB as a theoretical framework

of research had a tendency to use the direct measures of the theory consisting of attitude

toward the behavior, subjective norms, and the perceived behavioral control (Finch,

Donohue, & Garnham, 2002). However, this study comprehensively assessed “belief-

based indicators” of the three main constructs as indirect measures, assuming that these

belief based indicators provide the cognitive and affective foundations for the three main

constructs (Sagas et al., 2006). The indirect measures include the evaluation of the

outcomes of the belief for the “attitude” construct, the normative expectation of others

and the motivation to comply with these expectations for “subjective norms” construct,

and the aggregate of facilitating or impeding factors toward the behavior for “perceived

behavioral control” construct of the TPB. Through applying the TPB to the head

coaching intention analysis, the authors found that gender differences existed in head

coaching intentions between male and female assistant coaches; male coaches had higher

scores than women on intentions, attitudes, and subjective norms (Sagas et al., 2006).

The study results also supported the TPB’s predictability of head coaching intentions in

both men and women.

An integrated psycho-social approach to predict sport injury rehabilitation

adherence was developed (Levy et al., 2008) based on the TPB. The model, called the

Adapted Planned Behavior Model (APBM), has two phases: an initiation phase and a

maintenance phase. The initiation phase is a decision making phase for the formation of

rehabilitation intentions consisting of several primary psycho-social factors including

attitude, goal orientation, and threat appraisals (perceived severity and susceptibility).

The second phase, the maintenance phase, involves secondary factors related to initiating

(action) rehabilitation behavior. The maintenance phase includes coping, ability,

treatment efficacy, and social support which are needed to measure adherence to sports

injury rehabilitation programs. In addition to the primary and secondary psycho-social

factors, the APBM has self-efficacy/self-motivation and habit (cues to action) constructs

which are regarded as influencing sports injury rehabilitation adherence behavior (Levy

et al., 2008). Levy, Polman, and Marchant (2008) conducted a study to test the predictive

validity of the APBM to injured athletes’ rehabilitation adherence. According to the

study results, attitudes and perceived severity were predictors regarding rehabilitation

intention in the initial phase, and coping ability and social support were found to predict

rehabilitation adherence. Self-efficacy/self-motivation predicted clinic rehabilitation and

attendance but not home rehabilitation (Levy et al., 2008).

The Theory of Reasoned Action (TRA) was used to develop a questionnaire to

understand the attitudes and beliefs towards football safety of junior (aged 16-18)

Australian players (Finch, et al., 2002). The questionnaire included the main constructs

of the theory: attitudes and perceived outcomes towards safety behaviors and subjective

norms regarding the level of support received or expected support, if the player had been

injured or was to be injured. The authors reported that they used the TRA as the

framework for the study (Finch, et al., 2002), but the perceived behavioral control, which

is a main construct of the Theory of Planned Behavior (TPB), was also utilized. This

should have been explained since the only difference between the TRA and the TPB is

the use of perceived behavioral control. The results showed that 58% of the junior

football players responded that they were willing to risk playing football with an injury

although the majority of the survey respondents believed that football was not safe to

play (Finch, et al., 2002). It is also interesting that 80% of players were willing to take

the risk of injury due to playing football if they thought that not playing would affect the

chances of being selected in the Australian Football League (AFL) draft. Among three

contexts in which the respondents played (Victorian Football Leagues Under 18 (VFL U

18) club, local club, and school), players perceived the VFL U18 clubs as providing good

support for injured players, putting high priority on safety issues. The authors suggested

that negative beliefs and perceptions towards injury risk that were identified in the study

need to be considered in any comprehensive injury prevention strategy (Finch, et al.,

2002).

Social Cognitive Theory

The Social Cognitive Theory (SCT) evolved from Social Learning Theory

developed by Miller and Dollard (1941) and Rotter (1954) that posits an individual learns

a particular behavior through observations and rewards within the human social context.

With further development led by Bandura, SCT has added concepts of integrations of

organizational and individual behavior change from sociology and political science

(Glanz et al., 2008). SCT emphasizes that human behavior is the product of the dynamic

interplay of personal, behavioral, and environmental influences. Key concepts include

Reciprocal determinism (The dynamic interaction of the person, behavior, and the

environment in which the behavior is performed), Behavioral capability (a person must

know what to do and how to do to perform a specific behavior), Psychological

determinants of behavior (outcome expectations, self-evaluative outcome expectations,

self-efficacy, and collective efficacy), Observational learning (attention, retention,

production, and motivation), Environmental determinants of behavior (incentive

motivation and facilitation), Self-regulation (controlling oneself through self-monitoring,

goal-setting, feedback, self-reward, enlistment of social support ), and Moral

disengagement (euphemistic labeling, dehumanization and attribution of blame,

displacement of responsibility, and perceived moral justification) (Glanz et al., 2008).

Yang and colleagues (2005) utilized Social Cognitive Theory (SCT) as a guide to

develop a conceptual model explaining the factors influencing discretionary protective

equipment use, considering “the decisions of high school athletes to use discretionary

protective equipment are influenced not only by individual determinants but also by the

physical and social environment” (p. 1996). The conceptual model includes physical

environment (school size), social environment (coaches’ EQT, player/coach ratio),

observational learning (teammates’ equipment usage), and behavioral capability (history

of previous injury). The study analyzed three years of data of 100 North Carolina high

school athletes engaged in 12 organized sports (Yang et al., 2005). The results indicate

that approximately 30% of the athletes were using Lower Extremity Discretionary

Protective Equipment (LEDPE), and girls, seniors, players who were involved in limited-

contact sports, and multiple sports players showed higher usage of LEDPE. The authors

also reported that small school size, low player/coach ratio, high proportion of team

usage, and experience of previous lower extremity injury were found as important

predictors of LEDPE usage. They recommended that not only individual factors but also

school-level factors should be considered to promote use of discretionary protective

equipment (Yang et al., 2005).

Other theories

In addition to the three theories described, the Transtheoretical Model (TTM) has

been utilized in injured athletes’ rehabilitation research (Clement, 2008). The TTM was

developed based on a comparative analysis of major theories of psychotherapy and

behavior change to integrate process and principles of change across leading theories

(Glanz, et al., 2008). TTM aims to assess a person’s readiness to change and to identify

the processes and principles of human behavior change. TTM posits behavior change is a

process- not a discrete event- that unfolds over time through a series of six stages: pre-

contemplation, contemplation, preparation, action, maintenance, and termination of an

action. In addition to the construct “Stages of Change,” TTM has three main constructs:

Processes of Change (consciousness raising, dramatic relief, self-reevaluation,

environmental reevaluation, self-liberation, helping relationships, counter-conditioning,

reinforcement management, stimulus control, and social liberation), Decisional Balance

(pros and cons of changing), and Self-Efficacy (confidence and temptation). The TTM

has been applied to various behavior change programs in public health as it allows for a

practical guide for health professionals to develop tailored intervention programs

matched for each stage (Glanz, et al., 2008).

Clement (2008) applied the Transtheoretical Model (TTM) to assess injured

athletes’ readiness for rehabilitation and the relationships between the impact of Stages of

Change and athletes’ adherence and compliance rates with respect to their rehabilitation

programs. Although most previous studies utilized some part of the four main constructs

of the model (Stages of Change, Processes of Change, Decisional Balance, and Self-

Efficacy), Clement’s study included all the constructs of TTM (Clement, 2008). Even

though the results showed no statistically significant relationship between Stages of

Change and adherence and compliance, the study should be regarded as a good trial that

included the whole structure of TTM to understand sports injury rehabilitation.

Another recent study on sports injury rehabilitation presented a review of three

theoretical models which have been used to understand injured athletes’ compliance to

the recovery process (Christakou & Lavallee, 2009). These models included the

Protection Motivation Theory, the Personal Investment Theory, and Models of Cognitive

Appraisal. The authors provided practical guidelines and strategies for sport injury

rehabilitation personnel to assist athletes’ adherence to injury rehabilitation based on the

findings of the studies (Christakou & Lavallee, 2009). According to the review,

educating athletes about their injuries and rehabilitation, increasing effective

communication and active listening, providing social support,

and encouraging positive beliefs of injured athletes can increase athletes’ compliance to

sports injury rehabilitation programs (Christakou & Lavallee, 2009).

Theoretical Framework of the Study

Considering the lack of intensive research related to coaches’ perception of sports

injury, the study will utilize the HBM to assess the coaches’ perceived susceptibility and

severity of having injured athletes within the team, barriers and benefits of injury

prevention practice, self-efficacy in implementing injury prevention activities, and cues

to activate injury prevention practice. To measure the coaches’ readiness for injury

prevention practice, the Stages of Change construct of TTM will be used, assuming that

the coaches who are in a specific stage have unique characteristics regarding HBM

constructs. For example, the coaches in the action stage could have stronger perceived

self-efficacy than the coaches in contemplation stage. In that case, a tailored intervention

that can improve coaches’ self-efficacy needs to be conducted to lead the coaches in the

contemplation stage into the action stage. Among the six stages, the ‘termination’ stage

will not be assessed for this study because the purpose of the study is to identify current

practice regarding sports injury prevention.

CHAPTER THREE: METHODOLOGY

This chapter provides the research methods that were used in this study. It is

divided into two parts: Part I- survey instrument validation utilizing the Delphi technique,

and Part II- high school coach survey. This chapter presents the purpose of the study, the

research questions, and the overview of the study design. In addition, subjects and

settings of the study, instrumentation, data collection, and data analysis are described.

The purpose of the study was to describe the coaches’ beliefs and knowledge

pertaining to sports injury and their readiness for injury prevention practice in high

school settings.

The research questions are : (1) What are the coaches’ beliefs and knowledge

related to sports injury and their readiness for injury prevention practice?; (2) What are

the relationships between coaches’ beliefs, knowledge, and readiness for injury

prevention practice?; and (3) What are the differences in coach-related factors between

the coaches who have medical staff and those who do not?

Overview of the Study Design

To address the research questions, this study utilized a two part mixed-method

approach guided by a combination of the theoretical constructs of the Health Belief

Model and Transtheoretical Model (See Figure 1). Part I, the qualitative portion, utilized

the Delphi method to evaluate the survey instrument that measures coaches’ beliefs and

knowledge pertaining to sports injury and their readiness for injury prevention practice.

Part II, the quantitative portion, utilized the instrument confirmed in Part I to identify (1)

high school coaches’ beliefs and knowledge related to sports injury and their readiness

for injury prevention practice; (2) the relationships between coaches’ beliefs, knowledge,

and prevention practice readiness; and (3) the difference in coach-related factors

regarding sports injury between coaches who have medical staff for their team and those

who do not (See Table 5). Approvals for this study were acquired from the University of

South Florida Institutional Review Board and the Review Boards of the participating

School Systems (See Appendix A).

Figure 1. Theoretical Framework

Sports Injury Knowledge

Individual Beliefs

Perceived Susceptibility

Perceived Severity

Perceived Benefits

Perceived Barriers

Perceived Self-efficacy

Cues to action

Pre-contemplation

Contemplation

Preparation

Action

Maintenance

Injury prevention

practice readiness

Coach-related factors regarding high school sports injury

Table 5

Research Design and Objectives

Study

Part

Research

Design Objectives

Research

method Sampling

Part I QUAL To validate the survey instrument

that measures coaches’ beliefs

and knowledge pertaining to

sports injury and their readiness

for injury prevention practice.

Delphi

Technique

Snowball

sampling of

experienced

high school

coaches who

have current

first aid

certification.

Part II QUAN To assess (1) high school

coaches’ beliefs and knowledge

related to sports injury and their

readiness for injury prevention

practice; (2) the relationships

between coaches’ beliefs,

knowledge, and prevention

practice readiness; and (3) the

difference in coach-related factors

regarding sports injury between

coaches who have medical staff

for their team and those who do

not

Self-

reported

Survey

111 head

coaches

employed

during the

2010-11 school

years

- Group A: 5

SMART high

school coaches

- Group B: 5

high school

coaches

without medical

staff

Part I: Survey Instrument Validation Utilizing Delphi Technique

The Delphi technique uses “a structured process for collecting and distilling

knowledge from a group of experts by means of a series of questionnaires interspersed

with controlled opinion feedback” (Adler & Ziglio, 1996, p.3). Part I of the study

utilized the Delphi method to validate the survey instrument which was developed for

this study to measure coaches’ beliefs and knowledge pertaining to sports injury and their

readiness for injury prevention practice. Before the Delphi process began, a draft of the

survey questionnaire was developed from a review of the sports injury literatures and

reviewed by nationally known sports injury researchers, health educators, ATCs, and

high school coaches.

Subjects and setting

At the beginning of the first round of the Delphi process, seven experienced high

school coaches were selected as panelists to evaluate if the questions developed were

appropriate to ask to coaches, the wording used was understandable, and if there were

additional ideas/subjects that should be asked. The participant selection was achieved

through a snowball sampling of experienced high school coaches. At the beginning of the

participant selection, a few coaches were either referred by high school athletic personnel

or found on websites related to Florida high school sports, such as the Florida High

School Athletic Association (FHSAA). The coaches selected first referred other coaches

who were qualified as experienced coaches for the study. The experienced coaches were

defined as head coaches who had served high school athletes for more than 10 years, had

sports educational and training backgrounds in injury prevention, and held current first

aid certifications. The selected coaches had similar characteristics to the sample coaches

of the study, but they did not belong to any of the sample high schools to prevent

contamination issues.

At the beginning of the first round of the Delphi process, two panelists withdrew

without notice after sending their informed consents so the five remaining coaches

performed the first round review. Unfortunately, another two of the five panelists

dropped out at the end of the second round so two new panelists were invited so that the

Delphi group had at least five members as recommended in the literature. One of the

coaches who withdrew reported that she was too busy to participate in the Delphi

process. However, the other missing coaches have never responded despite continuous

efforts of research staff to reach them. The two newly invited panelists were informed

about the Delphi process plan and the results of the previous round. They also had

individual question and answer sessions with the researcher regarding the Delphi process

which were conducted via phone calls and emails.

Instrumentation

The initial draft of the questionnaire was developed to measure coaches’ beliefs

and knowledge pertaining to sports injury and their readiness for injury prevention

practice guided by the Health Belief Model (HBM) and Transtheoretical Model (TTM).

Based on a review of the sports injury literature, the questionnaire included information

on coaches’ perceived susceptibility and severity of having injured athletes on the team,

barriers and benefits of injury prevention practice, self-efficacy in implementing injury

prevention activities, and cues to activate injury prevention practice. It also included

questions on coaches’ readiness for injury prevention practice based on the Stages of

Change model of TTM. The questions involved themes on implementing injury

prevention programs, checking protective equipment, checking safety of playing fields

and facilities, having emergency care procedures, and checking up-to-date injury

prevention information. The knowledge questions were developed based on the literature

on general sports injuries that coaches could encounter and prevent during practices and

competitions. The literature includes previous studies conducted on coaches’ sports

injury knowledge and a sports injury curriculum which was developed to provide an

online course for coaches to receive a sports safety certificate. Demographic questions,

including coaches’ educational backgrounds, training experiences in injury prevention,

and first aid certifications were also used.

Data collection

The three-round Delphi procedure began in May, 2011. Email communication

was used as the data gathering channel. All informed consents were acquired from the

participants. The questionnaires for the Delphi process were designed to enable the

panelists to elicit individual responses and refine their views as the group work proceeded

through each round. The panelists scored each question anonymously to reach a possible

consensus at the end of each round. Prioritization of questions was accomplished by

scoring each item on a 5-point Likert Scale (1 = strongly inappropriate question to 5 =

strongly appropriate question). A separate document describing the purpose and tasks for

each round was provided. Ten days were given to the expert panel for review of the draft

instrument for each round. The researcher compiled the responses of the panelists to

construct a questionnaire for each subsequent round.

In the first round, the panelists were informed about the purpose of the study and

the plan for the Delphi process. The questionnaire was emailed and the panelists were

required to evaluate the questionnaire, focusing on the appropriateness of contents as a

tool to measure coaches’ beliefs and knowledge pertaining to sports injury and their

readiness for injury prevention practice. Throughout the first round, the areas of

agreement and disagreement among panelists were identified for each item, and issues

requiring further clarification were discussed based on the mean score calculated for each

question. All questions scoring an average of 3 or above were retained for revalidation

procedure in the second round.

The second round questionnaire was developed based on the results of the first

round. Panelists were able to review their original responses and compare these to those

of the whole group. During this interactive process, agreement and disagreement were

identified based on the mean score of each question, issues were clarified, and new ideas

were added. All questions scoring an average of 3 or above were considered for

revalidation for the third round. The panelists also had an opportunity to revise the scores

they gave to the questions in an earlier round. The facilitator edited the questionnaire

based on the comments where necessary.

In the third round, the panelists received a draft of the instrument including the

results of the second round. Follow up discussions took place through email

communication before the final scoring was performed. Edits were made by the

facilitator and the final scoring of the edited questionnaire ended the round. The final

version of the questionnaire included all of the questions that received an average of 4 or

above in the third round of the Delphi process excluding the “other questions” section

that contained demographic information, coaching experience, injury prevention, and

athletic injuries the coaches had in the past. The panelists were informed that the

questions had to receive 4 or above to be included in the final version of the coach

questionnaire because the third round is the final stage of the Delphi process. Incentives

were offered to the panelists.

Data analysis

The results of scoring were analyzed using SPSS 20 with numerical values

allocated to each item (1=“strongly inappropriate question” to 5=“strongly appropriate

question”). Descriptive statistics including mean scores were calculated to decide if an

item was included or eliminated. All questions scoring an average of 3 or above were

retained to be considered for revalidation procedure for the first and second round. For

the third round, questions scoring an average of 4 or above were included in the final

questionnaire.

Part II: High School Coach Survey

Utilizing the instrument developed in Part I, Part II of the study aimed to identify

(1) high school coaches’ beliefs and knowledge related to sports injury and their

readiness for injury prevention practice; (2) the relationships between coaches’ beliefs,

knowledge, and prevention practice readiness; and (3) the difference in coach-related

factors regarding sports injury between coaches who have medical staff for their team

and those who do not.

Subjects and setting

A total of 185 coaches employed during the 2010-2011 school year were

purposively selected from 10 public high schools in West-Central Florida, including the

five SMART schools. Showing a response rate of 60%, 112 surveys were submitted. Of

those submitted, 111 surveys were used for analysis. To control possible difference that

could exist between the five SMART injury surveillance high schools and the five non-

SMART high schools which do not have any full-time medical staff such as ATCs,

school nurses, and/or team physicians, the five non-SMART high schools were selected

as a control group to match the SMART schools according to school size, geographic

region, ethnic composition of students, and the proportion of economically disadvantaged

students in the school. The fundamental hypothesis was that there could be a major

difference in coaches’ beliefs and practices about sports injury between the coaches who

have medical staff at school and those who do not.

Instrumentation

The survey instrument developed based on the results of Part I was used for the

coach survey in Part 2. The instrument included the questions to assess coaches’

perceptions of sports injury using the HBM constructs: perceived susceptibility,

perceived severity, perceived barriers, perceived benefits, cues to action, and self-efficacy.

In terms of coaches’ readiness for sports injury prevention, participants were asked to

answer the five questions about their prevention practice readiness scoring from 1 (pre-

contemplation) to 5 (maintenance). The prevention readiness questions were generated

from injury prevention literature that contains suggestions about prevention practices to

reduce and prevent sports injuries and the results of Part I. The questions included

providing an injury prevention program to athletes, checking protective equipment,

maintaining safe playing fields and facilities, preparing emergency care procedures, and

dedicating time to review up-to-date information about injury prevention. Sports injury

knowledge questions were developed based on the sports injury literature with a review

by an expert panel consisting of nationally known sports injury researchers, health

educators, ATCs, and high school coaches. This review was conducted to secure content

validity of the instrument. Considering the study sample involved coaches from 15

sports, the knowledge questions were general in nature and not specific to any one sport.

Data collection

Data collection for the coach survey began in August, 2011. A total of 12 public

high schools were contacted based on the selection criteria including school size,

geographic region, ethnic composition of students, and the proportion of economically

disadvantaged students in the school. In addition to the 6 SMART high schools (Group

A) that participated in the SMART injury surveillance project during the 2010-2011

academic year, another 6 high schools (Group B) were contacted utilizing the selection

criteria. The selection pool was developed to recruit the control group high schools

(Group B) that have similar characteristics with Group A schools based on the Florida

High School Database provided by the Education Information and Accountability

service, Florida department of Education. A total of 12 target schools were finally

selected for the control group selection pool. Two public high schools were listed as

matching schools for each SMART high school in case the first school did not participate

in the study. The school principal and the athletic director were contacted to participate

in the survey. One school of Group A declined participation in the study so a total of 10

schools (five Group A schools and five Group B schools) were included in the final

survey.

Athletic coaches of the 10 participating high schools were contacted through the

athletic director and/or the ATC of each school during May to July 2011. As on-site

administrators, the SMART ATCs of each school conducted the survey for Group A

schools. For Group B schools that do not have medical staff for athletic teams, the

researcher administered the survey in cooperation with athletic directors. The survey

administrators (ATCs and athletic directors) were informed about the overview of the

study and survey procedure including a specific time-line. The survey packets, which

include a brief guide for survey administrators, survey questionnaires, informed consent

forms, and the incentive option sheet were distributed and collected by the survey

administrators of each school. The survey was conducted from August to October 2011

following the coaches’ group meeting schedule of each school. As an incentive, a $10

gift card was offered to each participant, and a $30 gift card was provided to each of the

survey administrators.

Data analysis

A unique identifier was assigned for each survey, and collected data were coded

and entered into SPSS 20. Descriptive statistics, including frequency distributions,

central tendency (i.e., mean, median, mode), and variability (i.e., standard deviation,

variance) were reviewed to explore the data collected. The five TTM prevention practice

questions were coded from 1 (pre-contemplation) to 5 (maintenance) and the last option

(having an assigned person to do the task) was coded as 0. For the HBM questions,

responses were indicated on a 5-point Likert-type scale ranging from 1=“very unlikely”

to 5=“very likely”, excluding one question which asked the percentage of chances of an

injury occurring to any athlete on the team. For each of the HBM constructs, the mean

score of questions under a construct were calculated as the factor analysis results strongly

support (Table 9). For example, the scores of the three questions of the perceived

susceptibility section were added to generate a mean score to represent the perceived

susceptibility construct. In addition, logistic regression was conducted to examine the

effect of HBM variables and demographic measures on coaches’ injury prevention

behaviors. Mean scores were calculated to determine significant differences between

Group A and Group B school in terms of the HBM constructs. Finally, Chi-squared

statistics were utilized to assess differences between Groups A and B in terms of the

significance of having or not having medical personnel available in the school.

CHAPTER FOUR: RESULTS

This chapter presents the results of the data analysis. The chapter is organized into

four sections: the research questions, descriptive analysis, the results of the Delphi

process, instrumentation results, and the results related to the research questions.

Research questions

This study addresses the following research questions:

1. What are the coaches’ beliefs and knowledge related to sports injury and their

readiness for injury prevention practice?

2. What are the relationships between coaches’ beliefs and knowledge pertaining to

sports injury and readiness for injury prevention practice?

3. What are the differences in coach-related factors between the coaches who have

medical staff and those who do not?

Descriptive Analysis

There were 112 surveys submitted by high school coaches. Of those that were

submitted, 111 surveys were completed. The age of the coaches ranged from 23 - 63

years, with a mean age of 37.29 and a median age of 33. Because of the partial

completion of some surveys, the total N reported for individual survey items may vary.

There were 73 male coaches (65.8%) and 37 female coaches (33.3%). The ethnicity of

the participants included 15 (13.5%) Black or African American, 4 (3.6%) Hispanic or

Latino, and 90 (81.1%) White. The length of coaching position held by the respondents

ranged from one year to 38 years. In terms of education, the majority of respondents

completed college/university or post-graduate study.

Coaches’ Experiences Regarding Injury Prevention

As the Delphi panelists suggested, several questions regarding coaches’ injury-

related experiences were included in the coach survey. Approximately half of the

responding coaches (52.1%) held a certificate in a national, state, or county- level sports

organization, and 20.5% of the respondents reported that they took some courses

regarding the sport to be qualified as a coach. There were 16 high school coaches

(21.9%) who regarded playing the sport for years or receiving a coaching award as a

coaching credential, despite a lack of any formal certification or coaching

training/education.

In terms of the coaches’ training/education experiences related to sports injury

prevention, about one-half of the survey participants (50 coaches) answered that they had

training in CPR, and about one-fourth of the participants (32 coaches) stated that they had

training related to concussions. Only 25 out of 111 coaches reported that they had first

aid training.

In response to the question “In what aspects of injury prevention programs do you

feel you need more training?”, 22 (26%) coaches reported that they need more training in

general injury prevention. The other needs of the coaches included trainings on cool-

down/warming-up, wrapping and taping, and prevention techniques regarding a specific

area of body such as the back, shoulder, and lower body. A summary of the responses is

presented in Appendix D.

When asked to list steps that the coaches take to prevent injuries, 38 (17.5%)

coaches provided “stretching” related responses, and 25 (11.5%) coaches listed

conditioning drills. Equipment check and warm-up/cool down were also listed by more

than 20 coaches.

Approximately half of the survey participants (49 coaches) listed conditioning

drills as an effective injury prevention program. Stretching, athletic education, and warm-

up/cool-down were included in the coaches’ other responses.

About one-half of the participants (63 coaches) believed that coaches are most

effective in leading injury prevention efforts followed by athletic directors (48 coaches).

In terms of the importance of conditioning drills in preventing athletic injuries, a majority

of the coaches (81 coaches) reported that these are very important. The results of the

amount of time for warm-up and cool-down showed that the coaches spend more time in

warm-ups than cool-downs in both practices and competitions (Table 6).

Table 6

Warm-up and Cool-down Time

Warm-up (Mean ± SD) Cool-down (Mean ± SD)

Practices 21.06 ± 9.68 11.72 ± 8.34

Games 23.99 ± 11.82 8.24 ± 9.26

When asked to estimate the numbers of injuries the teams experience during the

2010-2011 academic year, coaches reported, on average, 3.65 injuries in fall 2010, 1.41

injuries in spring 2011, and 0.38 injuries in fall 2011. There were many missing values

for this question, and more than one-third of the coaches who responded to the question

also reported there was no injury in spring (38 coaches) and fall (51 coaches) seasons in

2011. One half of the coaches had full-time medical staff for the team as expected. In

terms of performing CPR while coaching, three coaches reported that they conducted

CPR at one time. Similarly, five coaches reported that they used an AED while coaching.

More detailed data on the coaches’ experiences regarding injury prevention are

presented in Appendix D.

The Results of the Delphi Process

Table 7 presents the results of the Delphi process. A total of 50 questions were

finally selected for the coach survey questionnaire for Part II of the study.

The coach questionnaire consists of four main parts:

1. Coaches’ readiness for injury prevention practice guided by Stages of Change

model of TTM (Section A, 5 items)

2. Coaches’ beliefs of sports injury (Section B – Section F, 17 items)

3. Knowledge regarding sports injury and prevention (Section G, 9 items)

4. Other questions including general information, coaching experience, injury

prevention, and athletic injuries they had in the past (Section H, 19 items).

Table 7

Results of the Delphi Process

Theoretical

Framework Survey Question Themes

Final

question

number

Stages of

Change

(TTM*)

1. Implementing injury prevention program 1

2. Checking protective equipment 2

3. Checking safety of playing fields and facilities 3

4. Having emergency care procedures 4

New Q- Checking up-to-date injury prevention information*** 5

Perceived susceptibility (HBM**)

5. What do you believe is the chance that a sport injury will occur during

practices and/or games? Deleted

6. What do you believe is the chance that a sport injury will occur during

practices and/or games in terms of percentages

(0-100%)? 8

7. How susceptible do you feel that your athletes will receive an injury

during practices and/or games? 6

Table 7 (Continued) 8. What do you believe are your chances of having athletes injured

during the sport season as compared to other sports teams? 7

Perceived

severity

(HBM**)

9. The injury will interrupt my plan for practice/competition on the day

the injury occurs. Deleted

10. The injury will affect my long-term plan for my team. Deleted

11. The injury will cause problems related to my legal responsibility as a

coach. 9

12. The injury will threaten my evaluation as a coach. 10

13. The injury will interfere with my athlete’s

practice/competition involvement. Deleted

14. The injury will discourage other athletes’ participation in

practices/competitions. Deleted

Perceived

benefits

(HBM**)

15. Your efforts for injury prevention will decrease chances of injury

occurrence within your team. 11

16. Implementing an injury prevention program is the best way to

prevent and reduce injuries. 12

17. Preventing injury through various methods is more cost-effective

than treating after injury. Deleted

Perceived

Barriers

(HBM**)

18. Lack of training for injury prevention activities. 14

19. No resources available for sports injury prevention. Deleted

20. Lack of knowledge and skills to implement existing injury

prevention programs. Deleted

21. Too much additional time and efforts to implement injury prevention

programs. 15

22. Other issues more important than injury prevention. Deleted

23. No administrative support for me to work on injury prevention

activities. 16

New Q- Parents’ low awareness of the importance of injury

prevention***

Deleted

Self-efficacy

(HBM**)

24. I am confident in my ability to provide my athletes with appropriate

injury prevention programs. 17

25. I am confident in my ability to check and maintain playing fields and

facilities for safety. 18

26. I am confident in my ability to check if athletes’ protective

equipment is in good condition. 19

27. I am confident in my ability to prepare an appropriate emergency

care plan. 20

28. I am confident in my ability to undertake regular re-accreditation

and education to ensure your injury prevention knowledge is kept up-to-

date.

29. I am confident in my ability to conduct correct cardio-pulmonary

resuscitation (CPR) when needed. 22

Cues to

Action

(HBM**)

30. Parents’ request for injury prevention programs 13

31. Exposure to educational resources such as injury prevention

campaign Deleted

Sports

Injury

Knowledge

(HBM**)

1. Which of the following is true about an Automated External

Defibrillator (AED)? 23

2. CPR begins with an evaluation of the injured athlete’s ABC. What

does “ABC” stand for? 24

http://en.wikipedia.org/wiki/Automated_external_defibrillator

Instrumentation Results

Reliability test

A Cronbach’s alpha test was conducted to measure the consistency of the survey

items. The Cronbach’s alpha coefficients were computed for all items of the TTM and

each of the five HBM constructs excluding the cues to action construct which included

only one question. The coefficients of Stages of Change, perceived susceptibility,

perceived severity, perceived benefits, and self-efficacy were all above 0.70, and the

perceived barriers and knowledge constructs showed .641 and .390 respectively (Table

8). Including the knowledge questions in the Cronbach’s alpha test might not be helpful

to check the questions’ internal consistency because the knowledge questions consisted

of generic issues regarding sports injury prevention and not specifics.

Table 7 (Continued) 3. Which of the following statements is true about the use of ice and

heat for injured athletes? 25

4. Which of the following statements is NOT true about paralysis? 26

5. The risk factors for heat illness do NOT include 27

6. Which of the following statements is true about dehydration 28

7. Which of the following statements is Not correct about common

special medical conditions that can result in life threatening situations

for athletes

8. Which of the following statements is NOT true about Asthma 30

9. Which of the following statements is NOT true about safety

equipment Deleted

10. Which of the following statements is NOT true about Concussion 31

*Transtheoretical Model (TTM) **Health Belief Model (HBM) *** Newly added questions through the Delphi

process

Table 8

Internal Consistency and Descriptive Statistics for Stages of Change and Health Belief

Model Subscales

Subscale No. of items Cronbach’s alpha

Stages of change 5 .775

Perceived susceptibility 3 .709

Perceived severity 2 .897

Perceived benefits 2 .873

Perceived barriers 3 .641

Self-efficacy 6 .799

Knowledge 9 .390

Factor analysis

Exploratory factor analysis was utilized to determine the construct validity for the

coach survey questions. Factor analysis with “varimax” rotation was performed to

create factors for the Stages of Change construct of the TTM and each of the five HBM

constructs. The only exception to this analysis was the cues to action. Utilizing the

survey data collected, the extraction of the initial factors was first conducted based on a

review of the relevant covariance matrix. The Varimax rotation was finally selected as a

result of performing several rotations.

The results of the factor analysis yielded five factors, as the survey questionnaire

initially was designed with the exception of the knowledge construct of HBM. The five

factors include injury prevention readiness (Stages of Changes of TTM), self-efficacy,

perceived severity, perceived susceptibility, and perceived barriers as shown on Table 9.

The knowledge questions did not yield a factor. Including the knowledge questions in the

factor analysis might not be helpful since the knowledge questions are binary (correct/

incorrect).

Table 9

Factor Analysis Result

Self-Efficacy Perceived

Severity

Perceived

Susceptibility

Stages of

Changes

Perceived

Barriers

Program (Q1) .144 -.085 -.043 .691 .227

Equipment (Q2) .376 .011 .302 .601 -.034

Facility (Q3) .059 -.059 -.047 .644 .087

Emplan (Q4) .452 .174 .088 .283 -.064

Newinfo (Q5) .542 -.150 .001 .401 .113

suscept1 (Q6) -.116 -.141 .823 .118 .034

suscept2 (Q7) -.089 -.129 .854 -.022 -.226

suscept3 (Q8) .034 .012 .803 -.112 -.005

outcome1 (Q9) .145 .848 -.073 .005 .101

outcome2 (Q10) .074 .815 -.072 .029 .114

benefit1 (Q11) .080 -.512 .100 -.523 .066

benefit2 (Q12) .010 -.459 .129 -.539 .066

barriers1 (Q14) .180 .122 -.002 -.003 .799

barriers2 (Q15) .227 -.017 -.190 .163 .709

barriers3 (Q16) -.085 .133 -.086 .171 .624

self efficacy1 (Q17) .783 .109 -.110 .140 .147

self efficacy2 (Q18) .228 .123 -.172 .125 .058

self efficacy3 (Q19) .312 .237 .052 .029 .011

self efficacy4 (Q20) .654 .058 .057 .155 .104

self efficacy5 (Q21) .682 .050 -.005 -.116 .218

self efficacy6 (Q22) .735 .073 -.215 -.008 -.014

Knowled1 (Q23) .132 .097 .065 -.038 .130

Knowled2 (Q24) .023 -.011 .078 .031 .048

Knowled3 (Q25) -.028 .071 -.005 .147 -.094

Knowled4 (Q26) -.061 .193 -.031 .016 .161

Knowled5 (Q27) -.082 .086 .134 -.120 .160

Knowled6 (Q28) -.088 -.099 .247 -.218 .426

Knowled7 (Q29) .009 -.532 .114 .200 -.005

Knowled8 (Q30) .044 -.264 -.237 -.123 -.091

Knowled9 (Q31) -.033 .127 -.006 .045 -.106

( ): Survey question number

Research Question 1

What are the coaches’ beliefs and knowledge related to sports injury and their

readiness for injury prevention practice?

Coaches’ beliefs and knowledge regarding sports injury

Six constructs of Health Belief Model (HBM) were assessed to explore coaches’

beliefs and knowledge pertaining to sports injury (Table 10). Higher scores included 75%

or above of the possible score. This percentage was based on a previous study that

utilized the HBM to assess dental hygienists’ beliefs on oral health care (DeBate, Plichta,

Tedesco, & Kerschbaum, 2006).

Perceived susceptibility scores ranged from 2 to 15, with higher scores indicating

greater perception of susceptibility to injury. The mean score for perceived susceptibility

was 8.61 ± 2.98 with only 22% of coaches indicating a high level of susceptibility to

sports injury. Scores of 11 or higher were classified as the high level of susceptibility.

Perceived Severity scores ranged from 4 to 10, with higher scores reflecting

greater perception of severity of sports injury. The mean score was 7.91 ± 2.47, and over

half of the participants (58.6%) recorded a high level of perceived severity that includes

scores of 8 or higher.

The range of perceived benefits scores was from 2 to 10. The results showed that

a majority of the coaches (71.1%) recorded a high level of perceived benefits indicating

implementing prevention programs was an effective way to prevent and reduce sports

injuries. Scores of 8 or higher were defined as a higher score and the mean score for

perceived benefits was 8.06 ± 1.780.

Perceived barriers scores ranged from 3 to 13 indicating higher scores reflect

greater perception of barriers which may interrupt the implementation of injury

prevention programs. The mean score for perceived barriers was 7.79 ± 2.516 with only

12.7% of participants indicating a high level of perceived barriers due to sports injury.

Scores of 11 or higher were classified as the high level of perceived barriers.

The range for cues to action was from 1 to 5, and the mean score was 3.19 ±

1.202. Higher scores indicate more perceived pressure from parents who request

implementing injury prevention programs. Scores of 4 or higher were defined as the high

level of perception of cues to action, and 36% of coaches fell into this high level.

In terms of self-efficacy scores ranged from 17 to 30, approximately 80% of the

coaches scored 23 or more, classified as having a higher level of self-efficacy. The mean

score was 25.45±3.545.

The knowledge score ranged from 2 to 9 with a mean score of 6.40±1.498 with

25.2% of the participants correctly identifying at least eight out of nine sports injury-

related questions. A frequency table for the knowledge questions is presented in

Appendix E.

Table 10

Descriptive Statistics for Health Belief Model (HBM) Components

Subscale No. of items Mean SD % with higher scores

Perceived susceptibility 3 8.61 2.978 22.0

Perceived severity 2 7.91 2.474 58.6

Perceived benefits 2 8.06 1.780 71.1

Perceived barriers 3 7.79 2.516 12.7

Cues to action 1 3.19 1.202 36.0

Self-efficacy 6 25.45 3.545 78.5

Knowledge 9 6.40 1.498 25.2

Coaches’ readiness for sports injury prevention practice

Stages of Change of the Transtheoretical Model (TTM) was utilized to assess

coaches’ readiness for sports injury prevention practice. Coaches were asked to indicate

in which stage they are currently engaged for each of the following five injury prevention

behaviors:

- Implementing injury prevention program for athletes - Checking protective equipment - Checking safety of playing fields and facilities - Having emergency care procedure - Checking up-to-date injury prevention information

With regard to the Stages of Change constructs of TTM, pre-contemplation stage

was defined as having no intention to start the behavior in the next 6 months.

Contemplation stage was defined as considering starting the behavior in the next 6

months on a regular basis. Preparation stage was defined as performing the behavior not

regularly but occasionally. Action stage was defined as having done the behavior within

the past 6 months on a regular basis. Maintenance stage was defined as having done the

behavior for six months or more in a regular manner. Lastly, there was an option “Other”

for coaches who already have an assigned person so do not need to perform the behavior

Results presented in Table 11 indicate that less than half of coaches are engaged

in injury prevention related behaviors for their athletes. Only 45% of coaches in the

sample were engaged in implementing injury prevention program on a regular basis, and

37.8% of the participants identified themselves in the action/maintenance stages with

regard to checking up-to-date injury prevention information in a regular manner. Just

44% of coaches identified that they prepared a written emergency action plan for injured

athletes and have applied it when needed. For checking safety of playing fields and

facilities, a majority of the coaches (78.4%) reported they are in action/maintenance

stages, indicating they have been doing the behavior on a regular basis. Approximately

two third of the coaches (64.9%) identified themselves in the action/maintenance stages

with regard to checking protective equipment in a regular manner.

Table 11

Coaches’ Readiness of Sports Injury Prevention Behavior

Sports Injury prevention

behavior

Stage of current behavior Pre-

contemplation

n (%)

Contemplation n (%)

Preparation n (%)

Action n (%)

Maintenance n (%)

Other n (%)

Implementing injury

prevention program

(2.7)

(10.8)

(27.0) 16

(14.4)

(30.6)

(12.6)

Checking protective

equipment 5

(4.5)

(3.6)

(18.0)

(10.8)

(54.1)

(4.5)

Checking safety of playing

fields and facilities 0 4

(3.6)

(13.5)

(12.6)

(65.8)

(1.8)

Having emergency care

procedure 5

(4.5)

(16.2)

(10.8)

(8.1)

(36.0)

(23.4)

Checking up-to-date injury

prevention information 3

(2.7)

(16.2)

(34.2)

(9.9)

(27.9)

(7.2)

Research Question 2

What are the relationships between coaches’ beliefs and knowledge pertaining to

sports injury and readiness for injury prevention practice?

Bivariate analyses were conducted to assess the relationship between each of the

HBM variables and injury prevention behaviors which were measured utilizing the

Stages of Change of TTM. The survey responses of the five injury prevention behaviors

were converted to a dichotomous version consisting of “action” and “no-action” for

analysis. The “action” included action and maintenance stages and the “no-action”

included the stages of pre-contemplation, contemplation, and preparation.

Regarding the association among the HBM variables including sports injury

knowledge, self-efficacy was positively correlated with perceived severity (r = .35, p <

.00) and perceived benefits (r = .20, p < .03). Self-efficacy was negatively correlated

with perceived barriers (r = -.33, p < .00) (See Table 12). In addition, the findings

indicated that perceived severity was positively associated with the perceived benefits

construct (r = .21, p <.03). The perceived benefits construct was also negatively

correlated with cues to action (r = -.36, p < .00), indicating there is a negative relationship

between the perceived benefits of conducting injury prevention interventions and the cues

to activate injury prevention behaviors.

In terms of the relationship between HBM variables and the TTM variables, self-

efficacy demonstrated statistically significant correlations with having emergency care

procedures (r = .27, p < .00) and checking up-to-date injury prevention information (r =

.24, p < .01). The results also showed a strong relationship between checking protective

equipment and checking safety of playing fields and facilities (r=.531, p=>.00),

Implementing injury prevention programs was also associated with checking up-to-date

injury prevention information (r=.29, p<.00).

Table 12

Pearson Correlation between HBM Factors and Injury Prevention Behaviors

1 2 3 4 5 6 7 8 9 10 11 12

Pearson Correlation 1 -.053 -.106 .163 -.038 -.115 -.040 -.124 .159 .024 .019 -.045

Sig. (2-tailed) .590 .279 .095 .704 .236 .686 .209 .109 .808 .847 .649

N 107 107 107 106 104 107 104 105 103 105 106 105

Pearson Correlation 1 .212 * -.111 .350

** .006 .104 .094 .014 -.069 .179 .062

Sig. (2-tailed) .026 .248 .000 .946 .286 .334 .890 .481 .062 .524

N 111 111 110 107 111 108 109 106 108 110 109

Pearson Correlation 1 -.094 .202 *

-.364 ** .133 .154 -.060 .046 .113 .124

Sig. (2-tailed) .328 .037 .000 .169 .111 .544 .635 .238 .198

N 111 110 107 111 108 109 106 108 110 109

Pearson Correlation 1 -.334 ** .111 -.145 -.170 .076 .009 -.013 -.077

Sig. (2-tailed) .000 .250 .135 .078 .438 .925 .894 .426

N 110 107 110 107 108 105 107 109 108

Pearson Correlation 1 -.139 .008 .177 -.052 -.034 .270 **

.240 *

Sig. (2-tailed) .154 .932 .071 .601 .727 .005 .014

N 108 107 104 105 104 105 106 105

Pearson Correlation 1 .018 -.036 .042 -.113 -.175 -.067

Sig. (2-tailed) .851 .712 .667 .244 .068 .492

N 111 108 109 106 108 110 109

Pearson Correlation 1 .004 .017 .020 .005 .035

Sig. (2-tailed) .968 .868 .838 .957 .723

N 108 106 103 105 107 106

Pearson Correlation 1 .109 .168 .111 .287 **

Sig. (2-tailed) .267 .084 .249 .003

N 109 105 107 109 108

Pearson Correlation 1 .531 ** -.054 -.113

Sig. (2-tailed) .000 .581 .249

N 106 106 106 105

Pearson Correlation 1 -.116 -.097

Sig. (2-tailed) .231 .319

N 108 108 107

Pearson Correlation 1 .117

Sig. (2-tailed) .226

N 110 109

Pearson Correlation 1

Sig. (2-tailed)

N 109

**. Correlation is significant at the 0.01 level (2-tailed).

*. Correlation is significant at the 0.05 level (2-tailed).

9.Equipmnt-

Dichotomized

Correlations

SUSceptibility

2.SEVerity

Score

3. BENefits

Score

10.Facility-

Dichotomized

11.EMplan-

Dichotomized

12.Newinfo-

Dichotomized

4.BARriers

Score

5.SELf efficacy

Score

6.Cues to

action Score

7.Knowledge

Score

8.Program-

Dichotomized

Logistic regression utilizing backward-stepwise selection was used to examine the

effect of HBM variables on coaches’ behaviors regarding injury prevention practice (the

TTM variables) when considered together. A separate logistic regression analysis was

conducted for each of the five injury prevention behaviors, generating five separate

models as below.

Model A: factors associated with implementing injury prevention programs

Model B: factors associated with checking protective equipment

Model C: factors associated with checking safety of playing fields and facilities

Model D: factors associated with having emergency care procedure

Model E: factors associated with checking up-to-date injury prevention information

Overall, self-efficacy was associated with increased odds of conducting all of the

injury prevention behaviors (OR = 1.148-1.638) with exception of checking safety of

playing fields and facilities (Model C) (Table 13). Most noteworthy findings were that

coaches belonging to Group A were about four times more likely to provide injury

prevention programs for the athletes in Model A than those in Group B. This was also

exhibited in Model D which shows that the coaches belonging to Group A were about

four times more likely to have a self-prepared emergency plan compared to the coaches

in Group B.

Model A revealed that having higher perceived benefits was associated with an

increased odd of providing injury prevention programs to athletes (OR = 1.435). The

results also showed that coaches in Group A were four times more likely to provide

injury prevention programs to athletes (OR = 4.247). For model B, self-efficacy was

found to be associated with checking protective equipment in a regular manner,

indicating coaches with higher self-efficacy are more likely to check athletes’ protective

equipment. Model C revealed that coaches with higher score for cues to action were two

times more likely to check the safety of playing fields and facilities (OR = 2.271). For

Model D, higher perceived severity, higher score on cues to action, higher self-efficacy,

and being in Group A were associated with increased odds of having an emergency plan

for the team (OR= 1.326, 1.335, 1.211, and 3.712 respectively). Lastly, Model E showed

that coaches with higher score on cues to action and higher self-efficacy were one and

half times more likely to check up-to-date injury prevention information on a regular

basis. Certain coach factors including gender, perceived barriers, and knowledge did not

increase the odds of doing any of these injury prevention behaviors.

Table 13

Logistic Regression Models of Factors Associated with Coaches’ Injury Prevention

Behaviors

Independent variables

Model A

(Injury

prevention

program)

Model B

(Checking

protective

equipment)

Model C

(Checking

safety of

environment)

Model D

(Having

emergency

procedure)

Model E

(up-to-date

injury

information)

Odds Ratio

(95% CI)

Odds Ratio

(95% CI)

Odds Ratio

(95% CI)

Odds Ratio

(95% CI)

Odds Ratio

(95% CI)

HBM constructs

Perceived

susceptibility

.982*

(.961-1.003)

.939*

(.876-1.007)

Perceived severity 1.326*

(1.031-1.031)

.865

(.663-1.128)

Perceived benefits 1.435*

(1.003-2.001)

Perceived barriers

Cues to action 2.271

(.780-6.614)

1.335

(.764-2.331)

1.485

(.887-2.485)

Self-efficacy 1.148

(.960-1.374)

1.638*

(1.150-2.333)

1.211*

(.985-1.490)

1.460*

(1.180-1.807)

Knowledge

Table 13 (Continued)

Other variables

Group A vs B 4.247*

(.857-21.043)

.404

(.053-3.100)

3.712*

(.954-14.449)

.424

(.115-1.569)

Gender

(Male vs Female)

.242*

(.044-1.338)

.360

(.077-1.691)

.463

(.113-1.898)

Age .936*

(.871-1.005)

.845*

(.760-.938)

.784*

(.629-.977)

.959

(.902-1.021)

Coaching years 1.011*

(1.000-1.022)

1.009

(.977-1.023)

Model Chi-square

(p value)

19.942

(.003)

23.710

(.000)

12.961

(.011)

22.075

(.001)

21.128

(.001)

R 2 .203 .221 .123 .246 .205

*P<0.1

Research Question 3

What are the differences in coach-related factors between the coaches have

medical staff and those who do not?

Demographic characteristics

To address this research question, the coaches from the SMART injury

surveillance high schools which have ATCs were classified as Group A. Group B, the

control group for Group A, included the coaches without any full-time medical staff such

as certified athletic trainers (ATCs), school nurses, and/or team physicians. The

participating high school coaches were selected according to school size, geographic

region, ethnic composition of students, and the proportion of economically disadvantaged

students in the school.

Table 14 presents the demographic characteristics of each group. There were 47

coaches (61.7% male, 38.3% female) in Group A and 63 coaches (68.8% male, 29.7%

female) in Group B. The majority of each group reported themselves as White (Group A:

80.9%, Group B: 81.2%) followed by Black or African American (Group A: 17.0%,

Group B: 10.9%). The majority of the coaches completed college/university or post-

graduate study for both Groups A (95.7%) and B (82.8%). The mean age of the Group A

coaches was 36 years, and the mean age of the Group B was 38 years.

Table 14

Demographic Characteristic for Each Group

Variables

Group A

with ATCs Group B

Total

Demographic variables

Gender

- Male 29 (61.7%) 44 (68.8%) 73 (65.8%)

- Female 18 (38.3%) 19 (29.7%) 37 (33.3%)

Ethnicity

- White 38 (80.9%) 52 (81.2%) 90 (81.1%)

- Black or African American 8 (17.0%) 7 (10.9%) 15 (13.5%)

- Other 1 (2.1%) 3 (7.8%) 4 (5.4%)

Education

- High school graduate 0 (0.0%) 2 (3.1%) 2 (1.8%)

- Some college 1 (2.1%) 6 (9.4%) 7 (6.3%)

- College/University graduate 29 (61.7%) 37 (57.8%) 66 (59.5%)

- Post-graduate study 16 (34.0%) 16 (25.0%) 32 (28.8%)

Variables Mean ± SD Mean ± SD Mean ± SD

Coaching months 94.11± 86.00 103.89 ± 94.06 99.75 ± 90.47

Age 36.19 ±10.36 38.09 ± 14.75 37.29 ± 13.05

HBM variables

The mean scores of each of the seven constructs of Health Belief Model (HBM)

were assessed among the coaches of Group A and B (Table 14). A two-sided t-test was

used to compare the differences in the HBM constructs between Group A and Group B

(Table 15).

The results showed that the Group B coaches recorded higher mean scores for

most of the HBM constructs including perceived susceptibility, perceived severity,

perceived benefits, perceived barriers and cues to action. However, only the higher mean

score of perceived barriers for Group B was statistically significant (t=-3.65, p < .00).

The mean scores for self-efficacy and knowledge were a little higher among the Group A

coaches but were not statistically significant.

Table 15

HBM Variables for Each Group

Variables

Group A with

ATC Group B T-test

Mean ± SD Mean ± SD t p <

Perceived susceptibility 47.23 ± 29.329 52.05 ± 32.166 .689 .492

Perceived severity 7.87 ± 2.576 7.94 ± 2.416 .137 .892

Perceived benefits 7.83 ± 1.736 8.23 ± 1.806 -1.185 .238

Perceived barriers 6.83 ± 2.287 8.51 ± 2.455 -3.650 .000

Cues to action 3.15 ± 1.142 3.22 ± 1.253 -.301 .764

Self-efficacy 25.83 ± 3.335 25.16 ± 3.698 .956 .341

Knowledge 6.49 ± 1.349 6.38 ± 1.601 .375 .708

Coaches’ readiness for injury prevention practice

Chi-squared statistics were used to identify the differences pertaining to injury

prevention practices between the coaches who had medical staff (Group A) and those

who did not (Group B) (Table 16). The results showed that a greater percentage of

Group A coaches were in action/maintenance stage for three injury prevention behaviors:

implementing injury prevention programs, checking protective equipment, and having

emergency care procedures. Group B coaches exhibited higher percentages of

action/maintenance status for the rest of the prevention behaviors including checking

safety of playing fields and facilities and checking up-to-date injury prevention

information. However, only “having emergency care procedure” for Group A coaches

was statistically significant.

Table 16

Coaches’ Readiness of Sports Injury Prevention Practices by Group*

Sports injury

prevention

behavior

Group

Stage of current behavior

Pre-

contemp

lation

n (%)

Contemplation

n (%)

Preparation

n (%)

Action

n (%)

Maintenance

n (%)

Value

implementing

injury

prevention

program

A 0 (0.0) 3 (7.9) 13 (34.2) 7 (18.4) 15 (39.5)

.463 B 3 (5.3) 9 (15.8) 17 (29.8) 9 (15.8) 19 (33.3)

checking

protective

equipment

A 3 (7.5) 1 (2.5) 7 (17.5) 3 (7.5) 26 (65.0) .588

B 2 (3.3) 3 (4.9) 13 (21.3) 9 (14.8) 34 (55.7)

checking

safety of

playing fields

and facilities

A 0 (0.0) 2 (4.5) 8 (18.2) 2 (4.5) 32 (72.7)

.144 B 0 (0.0) 2 (3.2) 7 (11.3) 12(19.4) 41 (66.1)

having

emergency

care

procedure

A 1 (2.6) 5 (13.2) 4 (10.5) 3 (7.9) 25 (65.8)

.049 B 4 (8.7) 13 (28.3) 8 (17.4) 6 (13.0) 15 (32.6)

checking up-

to-date injury

prevention

information

A 0 (0.0) 10 (25.6) 14 (35.9) 3 (7.7) 12 (30.8)

.318 B 3 (4.8) 8 (12.9) 24 (38.7) 8 (12.9) 19 (30.6)

*The coaches who had another school staff in charge of each behavior were excluded in this analysis.

CHAPTER FIVE: DISCUSSION AND CONCLUSIONS

This chapter provides discussion of the study results. Conclusions are provided,

along with limitations and strengths of the study. Contribution of this research to public

health and recommendations for future research are discussed.

Summary and Discussion

As the most immediate initial caregivers for athletes during practices and games,

coaches are expected to play an important role in preventing and reducing sports injuries.

The role would be more critical if sports medical staff, such as athletic trainers are not

available to care for athletes. The current study sought to explore the coaches’ beliefs

and knowledge pertaining to sports injury, their readiness for injury prevention practice

in high school settings, and the relationship between the beliefs and knowledge factors

and the practice readiness factors. This study was designed to address the following

research questions:

1. What are the coaches’ beliefs and knowledge related to sports injury and their

readiness for injury prevention practice?

2. What are the relationships between coaches’ beliefs and knowledge pertaining to

sports injury and readiness for injury prevention practice?

3. What are the differences in coach-related factors between the coaches who have

medical staff and those who do not?

A two parts mixed-method approach guided by the Health Belief Model (HBM)

and Transtheoretical Model (TTM) was utilized to address the research questions. In Part

I of the study, a three- round Delphi method was used to validate the survey instrument

which was developed to assess coaches’ beliefs and knowledge pertaining to sports injury

and their readiness for injury prevention practice. Email communication was used as the

data gathering channel, and an average of five experienced coaches were involved in the

Delphi process as panelists for each round. The panelists were requested to evaluate the

coach questionnaire by focusing on the appropriateness of the questions as tools to

measure the coach factors. A total of 50 questions were finally selected for the coach

questionnaire that contained four main parts:

- Coaches’ readiness for injury prevention practice guided by the Stages of Change

model of TTM (Section A, 5 items)

- Coaches’ beliefs about sports injury (Section B – Section F, 17 items)

- Knowledge regarding sports injury and prevention (Section G, 9 items)

- Other questions including general information, coaching experience, injury

prevention, and athletic injuries they had in the past (Section H, 19 items).

In Part II of the study, a survey was conducted among 111 high school coaches,

and the completed questionnaires formed the data basis for analysis. The participants

were purposively selected from 10 public high schools in West-Central Florida identified

for this study. These 10 schools include the five SMART schools which necessarily have

ATCs (Group A), and five non-SMART schools which do not have any full-time medical

staff as the control group (Group B). The fundamental hypothesis was that there could be

a difference in coaches’ beliefs and practices pertaining to sports injury between the

coaches who have medical staff for the team and those who do not.

Coaches’ Beliefs and Knowledge Pertaining to Sports Injury

Coaches’ contributions to injury prevention and reduction are expected given that

they are the closest caregiver to athletes during practices and games. Coaches themselves

also recognize that coaches are responsible for the immediate medical care of athletes at

practices and competitions (Cross et al, 2010).

In the current study, more than half of the coaches (63 coaches) reported that

coaches are the most effective in leading injury prevention efforts (Appendix D).

However, coaches seem to believe that the risk of injuries occurring to any athlete of their

team during practices and/or games is not high. Only 22% of respondents exhibited a

higher level of susceptibility regarding injury occurrence, implying that coaches may

underestimate the possibility of injury occurrence. In terms of perceived severity of

having injured athletes in the team, more than half of the respondents (58.6%) reported a

higher level of perceived severity, indicating that having injured athletes can negatively

influence coaching evaluations and cause problems related to the legal responsibility as a

coach.

It is interesting that a majority (72.1%) of the coaches believe implementing

injury prevention interventions is the most effective way to prevent and reduce sports

injuries although only 45% of respondents reported that they provide injury prevention

programs on a regular basis (See Appendix E). This discrepancy may exist because the

coaches believe injury would not likely occur within their team so they are not strongly

interested in providing injury prevention programs to their athletes. Or, they may believe

that injury is not preventable so injury prevention activities would not work. There is a

need to disseminate scientific evidence that sports injury is a significant public health

issue, threatening the health of adolescents. At the same time, it is very important to

educate on the effectiveness of injury prevention activities. Even though very limited

research is available, existing evidence needs to be disseminated, and more empirical

studies should be conducted.

A majority of the coaches surveyed in the current study indicated that lack of

training on injury prevention activities and additional time and efforts for these activities

are not serious barriers in implementing injury prevention programs; only about 10% of

respondents indicated a higher level of perceptions of those barriers. Considering the

barriers given were generated through the Delphi process and a literature review, there

might be a possibility that coaches’ low susceptibility of injury occurrence is itself a main

barrier, not lack of training, additional time needed to conduct the prevention programs,

and/or no administrative support.

Many examples of the cues to action construct of HBM were discussed during the

Delphi process including social campaigns, existing educational resources, and parents’

request for injury prevention programs. However, the panelists were not positive about

the given “cues to action” examples which would prompt their injury prevention

activities. For example, most of them replied that they had never seen campaigns on

sports injury prevention. Furthermore, the existing educational resources of injury

prevention were not appealing to motivate their action to initiate a sports injury

prevention intervention. The Delphi panelists finally agreed to leave the “parents’

request for injury prevention programs” variable for the cues to action construct. There

might be some relationship between the low chance of being exposed to the cues to

action and low practice readiness.

Self-efficacy is defined as confidence in one’s ability to take action (Glanz, et al.,

2008). The study in Glanz et al. (2008) measured coaches’ self-efficacy in implementing

six injury prevention activities:

- Provide my athletes with appropriate injury prevention programs

- Check and maintain playing fields and facilities for safety

- Check if athletes’ protective equipment is in good condition

- Prepare an appropriate emergency care plan

- Undertake regular re-accreditation and education to ensure my injury prevention

knowledge is kept up-to-date

- Conduct correct cardio-pulmonary resuscitation (CPR) when needed

More than two-thirds of the respondents (78.5%) reported a higher level of self-

efficacy, indicating they are confident or very confident in the six injury prevention

activities, including CPR. However, only 25.2% of the coaches surveyed acquired a high

score (8 or 9 out of 9) for the knowledge of sports injury section, implying the possibility

of a discrepancy between the perceived self-efficacy and knowledge the coaches have

regarding sports injury prevention. This concern was brought out by Adams’ study (2012)

as well. This study reported “(the secondary school football coaches) hold a higher self-

confidence in management abilities than indicated by their knowledge level (p. vi).”

Coaches’ may need more knowledge regarding sports injury as research shows. The

results of the current study are consistent with Ransone and Dunn-Bennett’s study on

high school coaches’ knowledge and attitudes regarding oral facial injuries (Ransone &

Dunn-Bennett, 1993). They reported that 36% of coach participants exhibited scores of

29/34 which was classified as a higher score in the study.

Coaches’ Injury Prevention Practice

Given the influence of coaches on athletes, coaches’ efforts to prevent injuries

play an important role (Hergenroeder, 1998). However, research shows that a very small

number of coaches are actively engaged in injury prevention practice. For example, one

study indicated that only 13.2% of coaches surveyed reported that they had offered

educational programs on mouth guard use and oral-facial injury prevention to their

athletes even though about 72% of the respondents said their athletes had sustained oral-

facial injuries (Berg et al., 1998). Sawyer and colleagues (2010) also indicated that only

7.2% of coaches surveyed replied they had distributed a fact-sheet for their high school

athletes, which is a free concussion prevention resource developed and distributed by the

Centers for Disease Control and prevention (CDC). In the current study, coaches’ injury

prevention practice was assessed utilizing Stages of Change of TTM. Coaches were

requested to answer in which stage they are currently engaged for each of the following

five injury prevention behaviors:

- Implementing injury prevention program for athletes

- Checking protective equipment

- Checking safety of playing fields and facilities

- Having emergency care procedure

- Checking up-to-date injury prevention information

When the answers were divided into a dichotomous version consisting of “action”

(action and maintenance) and “no-action” (pre-contemplation, contemplation, and

preparation), less than half of the respondents were engaged in three out of five injury

prevention practices, consistent with previous research. The three behaviors include

implementing injury prevention programs (45%), having emergency care procedures

(44%), and checking up-to-date injury prevention information (37.8%) (Table 15).

Interestingly, the coaches exhibited higher levels of engagement in the other two

prevention behaviors, checking safety of playing fields and facilities and checking

protective equipment. Coaches may be more interested in checking physical factors such

as playing fields and protective equipment rather than providing informational resources

for sports injury prevention. This could be related to the fact that a significant number of

previous injury prevention studies have been conducted on protective equipment use.

Based on the results of the current study, information on evidence based injury

prevention programs should be provided for coaches, along with practical strategies to

deliver the information to high school athletes. The findings from existing descriptive

studies examining the relationship between coaching factors and injury outcomes have

generated mixed results. Most of the results supporting the effectiveness of injury

prevention programs were presented by uncontrolled studies with fundamental limitations

in explaining cause-effect relationships. Therefore, further studies should be conducted

to investigate coaching factors and injury outcomes. Internet search training would also

be helpful for the coaches to acquire up-to-date injury prevention information. It is

noticeable that more than half of the respondents of the study are in contemplation

(16.2%) or preparation (34.2%) stages, indicating that they are considering checking

recent injury prevention information on a regular basis or occasionally. Tailored

interventions should be developed and implemented for the coaches in these two stages

so they move to the action/maintenance stage. Experts insist that coaches have a

responsibility to maintain up-to-date knowledge of athletes’ health issues and injury

prevention programs to minimize the potential risk of sports injuries (Gianotti et al.,

2008). Finally, having emergency care procedures should be mandated in every county

or state, due to its strong influence on coaches. Many coaches in the current study had

certification/training experiences that were offered by county and state level

organizations (See Appendix D).

Relationship between Coaches’ Beliefs and Injury Prevention Practice

Research on the relationships between coaches’ perceptions of sports injury and

their behaviors to control sports injuries is very limited. In the current study, it was

assumed that coaches’ higher levels of perception and knowledge regarding sports injury

would have a positive relationship with their injury prevention practices. Berg and

colleagues (1998) reported that coaches who are more aware of oral-facial-injuries are

more likely to be in favor of mouth-guard use. A study also showed that 89% of coaches

changed their training methods to prevent injuries as they learned from an injury

prevention course for coaches (Gianotti et al, 2008).

Many public health studies which utilized HBM support the role of self-efficacy

as a strong factor/predictor influencing specific behaviors. The current study also

supports these results, demonstrating self-efficacy’s strong relationship with the HBM

factors and the prevention behaviors. In the current study, the results showed that self-

efficacy was positively related to perceived severity and perceived benefits. It is

interesting that self-efficacy was negatively associated with perceived barriers, indicating

coaches with higher self-efficacy exhibited lower levels of perception to the barriers.

This could be interpreted that coaches who are confident with their abilities to conduct

injury prevention activities perceive less barriers.

The findings of this study also showed that perceived severity was positively

associated with the perceived benefits construct. However, the perceived benefits

construct was negatively correlated with cues to action, indicating that there is a negative

relationship between the perceived benefits of conducting injury prevention interventions

and the cues to activate injury prevention behaviors. One study reported a significant

positive relationship between the total number of seasons coached and the injury

knowledge score of coaches (Carter & Muller, 2008). However, no relationship was

found between the knowledge score and the other HBM and TTM variables in the current

study.

In the current study, the analyses between the HBM variables and the TTM

variables indicated that self-efficacy had statistically significant relationships with having

emergency care procedures and checking up-to-date injury prevention information. The

findings also showed a positive relationship between checking protective equipment and

checking safety of playing fields and facilities. Implementing injury prevention programs

also showed statistically significant relationships with having emergency care procedures

and checking up-to-date injury prevention information respectively.

The logistic regression results supported the strong impact of self-efficacy on

implementing injury prevention behaviors. Self-efficacy was associated with increased

odds of conducting all of the injury prevention behaviors (OR = 1.148 - 1.638) with the

exception of checking the safety of playing fields and facilities. In addition, coaches in

Group A were more likely to implement injury prevention practices. These coaches were

about four times more likely to provide injury prevention programs to the athletes and

four times more likely to have prepared emergency plans. Given that Group A coaches

necessarily have certified athletic trainers (ATCs), it may be that the ATCs influenced the

coaches’ injury prevention practices given that injury prevention is a major job duty of

ATCs. Also, the ATCs may provide resources for coaches to use to help their athletes

prevent injuries. Or, the ATCs could have directly been involved in their coaches’ injury

prevention interventions. Research to identify direct relationships between having ATCs

and coaches’ injury prevention practices should be conducted.

Differences in Beliefs and Practices between Coaches Who Have Medical

Staff and Those Who Do Not

A few studies have been conducted that identify the differences between coaches

and athletic trainers in terms of handling sports injuries (Ransone & Dunn-Bennett, 1999;

Mensch, Crews, & Mitchell, 2005). Previous studies reported that both coaches and

athletic trainers have a general duty to maintain the health and safety of their athletes.

However, the studies indicated that athletic trainers were stronger in accurately reporting

injuries, making judgments about the severity of a physical condition, and providing

medical care for athletes (Yard et al., 2009; Mensch et al., 2005). These results are not

surprising given that injury/illness prevention is one of the main focus areas of accredited

athletic training programs (NATA, 2013). The problem is that most high schools cannot

have a full-time on-site athletic trainer due to financial difficulty. Therefore, this study

sought to examine the differences between the coaches who had medical staff for the

team and those who do not under the assumption that there could be differences in

coaches’ beliefs and practices pertaining to sports injury between these two groups of

coaches.

The results of the current study showed that only perceived barriers construct for

Group B was statistically significantly higher than Group A although Group B coaches

recorded higher mean scores for most of the HBM constructs. It can be interpreted that

Group B coaches possess a higher level of perception about the barriers in conducting

injury prevention programs compared to the Group A coaches. The results of the chi-

squared analysis of the five injury prevention behaviors support the results of the HBM

construct analysis. The higher scoring Group A coaches were engaged in three injury

prevention behaviors: implementing injury prevention program, checking protective

equipment, and having emergency care procedures. A statistically significant difference

was observed for having emergency care procedures; more Group A coaches had

prepared for the emergency care procedure and have been using them for their teams.

The Group A coaches could have been encouraged to have emergency care procedures by

the ATCs. Or, ATCs could be actively involved in preparing and applying the

emergency care procedures.

Implications for Public Health

Injury is a very significant public health issue threatening the health of children,

adolescents, and young adults in the United States (CDC, 2009), and sports are the

leading cause of adolescent injury requiring medical attention and emergency department

admissions (Emery, 2003). This research is significant because minimal empirical

research has been conducted to explore coach-related factors which can be crucial in

preventing and reducing sports injuries in high school settings. The results of this study

may increase the understanding of high school coaches’ beliefs, knowledge, and

prevention practices regarding sports injury. As obesity among children and adolescents

continues to be a public health concern in the United States, sports and other forms of

physical activities have been strongly encouraged to resolve the issue. This study has the

potential to contribute to increasing adolescents’ sports participation by decreasing the

chances of injuries through coaches’ effective prevention practices.

Although several social science theories and models have been applied to sports

injury research, there still is a paucity of information on coaches’ perceptions and

behaviors related to injury. Considering that theory-based research on coaches should

provide fundamental information needed for coaches to plan, implement, and evaluate

injury prevention programs for athletes, this study has contributed to adding theory-based

research to the current sports injury prevention literature by utilizing the two well-

researched public health theories, HBM and TTM. In particular, the use of Stages of

Changes of TTM enables health professionals to develop tailored interventions matched

for each stage. For example, in this study, more than half of the coaches surveyed are in

contemplation (16.2%) or preparation (34.2%) stages, indicating that they are considering

checking recent injury prevention information on a regular basis or occasionally. Based

on the result, tailored interventions could be designed and implemented for the coaches in

these two stages so that they can move to the action/maintenance stage.

In addition, this study promotes the inclusion of a formal injury prevention course

as part of the current coaching education curriculum. The findings of the study could be

used to provide specific guidelines on what should be addressed to meet coaches’ needs

on conducting injury prevention programs. It would be worthwhile to mandate that

coaches’ training for injury prevention includes CPR/first aid certification. Based on the

results of Group A coaches’ higher levels of implementing injury prevention programs,

school administrators should strongly consider employing trained medical staff such as

certified athletic trainers (ATCs). These individuals can serve as on-site medical

professionals and effective health educators for coaches and athletes.

Strengths and Limitations

Although the role of coaches is critical in preventing and reducing sports injuries

and coaches perceive themselves responsible for injury prevention practices for their

athletes, little research has been conducted on coach factors regarding sports injury

prevention. Given that the paucity of research on coach factors may be a fundamental

barrier for effective prevention interventions provided by coaches, the primary strength of

the current study is to provide extensive information related to coaches’ perceptions,

knowledge, and practices pertaining to sports injury prevention in high school settings.

Additionally, this study used a mixed method approach to confirm the utility of the coach

questionnaire.

Because there was a lack of existing instruments to measure coach related injury

prevention factors, the Delphi process was useful in refining the initial questionnaire. As

a result, the questionnaire became more practical for the coaches. In addition, the use of

public health theories in planning the research and in interpretation of the results adds

greatly to the current literature on sports injury prevention. In particular, simultaneous

application of the HBM and TTM enabled an in-depth exploration of the coach factors.

This also has a potential for developing tailored interventions to promote coaches’ injury

prevention practices. According to a systematic literature review on the use of behavioral

and social science theories and models (McGlashan, A., Finch, C., Aucote, H., &

Twomey, D., 2009) only 11% of published sports injury prevention research studies

explicitly used behavioral and social science theories and models, applying the

theory/model to design or conduct the study. The authors assert the need for increased

attention to theory guided research as an effort to fully understand the behavioral

determinants of safety actions.

Finally, this study highlighted the role of certified athletic trainers in preventing

sports injuries. The results of the current study show that the coaches who had full time

ATCs at schools were about four times more likely to provide injury prevention programs

to the athletes and have emergency plans for the team compared to the coaches who do

not have full time ATCs. Even though the current study did not investigate the direct

causation between the relationships of how the ATC influence their coaches, ATCs could

be a great asset for the development and implementation of injury prevention

interventions.

Despite its strengths, there are several limitations of this study. The study sample

was limited to the coaches of 10 high school coaches and convenient sampling was used

to recruit the study participants. The small sample size and lack of random selection limit

the ability to generalize the findings to other high schools. Also, data for this study were

collected through self-report which could have systematic errors from recall bias, social

desirability bias, and non-response. Lastly, the survey data were cross-sectional and thus

cannot predict information about coaches’ perceptions and behaviors over time or the

causation of the associations.

100

Recommendations for Future Research

After reviewing the results of this study, the following recommendations are

presented for future research:

1. The efforts to accumulate knowledge of coach factors regarding sports injury

and the development of effective prevention strategies for high school coaches

should be continued through randomized trials using rigorous research

designs. In particular, design and implementation of randomized control trials

of coaches with and without ATCs or other medical supports should be

conducted at state or national levels so that the findings can be applied to all

high school coaches in the United States.

2. A longitudinal study should be conducted to allow for the determination of the

true role of ATCs in injury prevention practices and athletes’ morbidity in

high schools. The longitudinal study should include environmental factors

surrounding high school coaches such as school system, parents, and athletes

themselves. Triangulation of data from these environmental factors will add

strength to the results of the longitudinal study.

3. Further research based on behavioral and social science theories and models

need to be conducted as a first step to better understand adolescent sports

injury and coach factors. Theory-based research on coaches will provide

fundamental information needed to plan, implement, and evaluate injury

prevention programs for athletes.

4. Educational materials and sports injury prevention campaigns should be

developed and include the potential role for self-efficacy.

101

Conclusion

This study explored high school coaches’ beliefs, knowledge, and practice

readiness regarding sports injury as well as the relationships among the coach-related

variables guided by the HBM and TTM models. The participants of the study exhibited

low to average perceptions of having an injured athlete on their team, meaning that the

coaches believe that the chance of injury occurrence within their team is not high. The

knowledge score on sports injury was not high. However, a majority of the coaches

showed strong beliefs in implementing injury prevention interventions as an effective

way to prevent and reduce sports injuries. In terms of the coaches’ injury prevention

practice readiness, less than half of the respondents were engaged in implementing injury

prevention programs, had emergency care procedures, and checked up-to-date injury

prevention information on a regular basis. On the other hand, a majority of the coaches

were engaged in the two prevention behaviors, checking safety of playing fields and

facilities and checking protective equipment. Supporting previous studies, the present

results revealed the strong associations between self-efficacy and HBM constructs and

the injury prevention behaviors assessed. It was also found that coaches who had

medical staff were about four times more likely to provide injury prevention programs to

their athletes and have emergency care plans. The results of this study should help lay the

groundwork for enhancing the roles of coaches and ATCs in the prevention of sports

injuries among high school athletes.

102

References

Adler, M., & Ziglio, E. (1996). Gazing into the oracle. Bristol, PA: Jessica Kingsley

Publishers.

Agel, J., Arendt, E. A., & Bershadsky, B. (2005). Anterior cruciate ligament injury in

national collegiate athletic association basketball and soccer: A 13-year review.

The American Journal of Sports Medicine, 33(4), 524-530.

Agel, J., Evans, T. A., Dick, R., Putukian, M., & Marshall, S. W. (2007a). Descriptive

epidemiology of collegiate men’s soccer injuries: National collegiate athletic

association injury surveillance system, 1988-1989 through 2002-2003. Journal of

Athletic Training, 42(2), 270-277.

Agel, J., Ransone, J., Dick, R., Oppliger, R., & Marshall, S. W. (2007b). Descriptive

epidemiology of collegiate men’s wrestling injuries: 1988-1989 through 2003-

2004. Journal of Athletic Training, 42(2), 303-310.

Agel, J., Olson, D. E., Dick, R., Arendt, E. A., Marshall, S. W., & Sikka, R. S. (2007c).

Descriptive epidemiology of collegiate women’s basketball injuries: National

collegiate athletic association injury surveillance system, 1988-1989 through

2003-2004. Journal of Athletic Training, 42(2), 202-210.

Ajzen, I.(1991). The theory of planned behavior. Organizational behavior and human

decision processes, 50, 179-211.

103

Arendt, E., & Dick, R. (1995). Knee injury patterns among men and women in collegiate

basketball and soccer. NCAA data and review of literature. The American Journal

of Sports Medicine, 23(6), 694-701.

Athlete. (2010). In Merriam-Webster online dictionary. Retrieved March 26, 2010, from

http://www.merriam-webster.com/dictionary/athletes

Aukerman, D. F., Aukerman, M. M., & Browning, D. (2006). Medical coverage of high

school athletics in North Carolina. Southern Medical Journal, 99(2), 132-136.

Bahr, R., & Krosshaug, T. (2005). Understanding injury mechanisms: A key component

of preventing injuries in sport. British Journal of Sports Medicine, 39, 324-329.

Beachy, G., Akau, C. K., Martinson, M., & Olderr, T. F. (1997). High school sports

injuries. A longitudinal study at Punahou School: 1988 to 1996. The American

Journal of Sports Medicine, 25(5), 675-681.

Berg, R., Berkey, D. B., Tang, M. W., Altman, D. S., & Londeree, K. A. (1998).

Knowledge and attitudes of Arizona high school coaches regarding oral-facial

injuries and mouth guard use among athletes. Journal of American Dental

Association. 129, 1425-1432.

Boden, B. P., Tacchetti, R., & Mueller, F. O. (2003). Catastrophic cheerleading injuries.

The American Journal of Sports Medicine, 31(6), 881-888.

Boden, B. P., Tacchetti, R. L., Cantu, R. C., Knowles, S. B., & Mueller, F. O. (2006).

Catastrophic cervical spine injuries in high school and college football players.

The American Journal of Sports Medicine, 34(8), 1223-1232.

http://www.merriam-webster.com/dictionary/athletes

104

Boden, B. P., Tacchetti, R. L., Cantu, R. C., Knowles, S. B., & Mueller, F. O. (2007).

Catastrophic head injuries in high school and college football players. The

American Journal of Sports Medicine, 35(7): 1075-1081.

Bundy, D. G. & Feudtner, C. (2004). Preparticipation physical evaluations for high

school athletes: Time for a new game plan. Ambulatory Pediatrics, 4(3), 260-263.

Burgeson, C. R., Wechsler, H., Brener, N. D., Young, J. C., & Spain, C. G. (2001).

Physical education and activity: Results from the school health policies and

programs study 2000. The Journal of School Health, 71(7), 279-293.

Burt, C. W. & Overpeck, M. D. (2001). Emergency visits for sports-related injuries.

Annals of Emergency Medicine, 37(3), 301-308.

Caine, D. J. & Nassar, L. (2005). Gymnastics injuries. Medicine and Sport Science, 48,

18-58.

Carter, A. F., & Muller, R. (2008). A survey of injury knowledge and technical needs of

junior rugby union coaches in Townsville (North Queensland). Journal of Science

and Medicine in Sport, 11(2), 167-173.

Centers for Disease Control and Prevention. (1997). Sports-related recurrent brain

injuries—United States. Morbidity and Mortality Weekly Report, 46(10), 224–227.

Centers for Disease Control and Prevention. (2006). Sports-related injuries among high

school athletes-United States, 2005-06 school year. Morbidity and Mortality

Weekly Report, 55(38), 1037-1040.

Centers for Disease Control and Prevention. (2009). National biostatistics reports.

Retrieved July 1, 2009, from

http://www.cdc.gov/nchs/data/nvsr/nvsr57/nvsr57_14.pdf

105

Center for Injury Research and Policy. (2010). RIO™: Reporting information online.

Retrieved from http://injuryresearch.net/rio.aspx

Christakou, A., & Lavallee, D. (2009). Rehabilitation from sports injuries: From theory to

practice. Perspectives in Public Health, 129(3), 120-126.

Christoffel, T., & Gallagher, S. S. (2006). Injury prevention and public health: Practical

knowledge, skills and strategies (2nd ed.). Sudbury, MA: Jones & Bartlett

Publishers.

Clement, D. (2008). The Transtheoretical Model: An exploratory look at its applicability

to injury rehabilitation. Journal of Sport Rehabilitation, 17, 269-282.

Coach. (2010). In Merriam-Webster Online Dictionary. Retrieved March 16, 2010, from

http://www.merriam-webster.com/dictionary/coach

Collins, M., Lovell, M. R., Iverson, G. L., Ide, T., & Maroon, J. (2006). Examining

concussion rates and return to play in high school football players wearing newer

helmet technology: A three-year prospective cohort study. Neurosurgery, 58(2),

275-286.

Cross, P. S., Karges, J. R., Adamson, A. J., Arnold, M. R., Meier, C. M., & Hood, J. E.

(2010). Assessing the need for knowledge on injury management among high

school athletic coaches in South Dakota. South Dakota Medicine, 63(7), 241-245.

Daly, R. M., Bass, S. L., & Finch, C. F. (2001). Balancing the risk of injury to gymnasts:

How effective are the counter measures? British Journal of Sports Medicine, 35,

8-20.

http://injuryresearch.net/rio.aspx

http://www.merriam-webster.com/dictionary/coach

106

DeBate, R. D., Plichta, S. B., Tedesco, L. A., & Kerschbaum, W. E. (2006). Integration

of oral health care and mental health services: Dental hygienists’ readiness and

capacity for secondary prevention of eating disorders. Journal of Behavioral

Health Services and Research, 33(1), 113-125.

DeRenne, C., Morgan, C. F., Hetzler, R. K., & Taura, B. T. (2007). A state analysis of

high school coaching certification requirements for head baseball coaches. The

Sport Journal, 10(3). Retrieved October 15, 2008, from

http://www.thesportjournal.org/article/state-analysis-high-school-coaching-

certification-requirements-head-baseball-coaches.

Deroche, T., Yannik, S., Brewer, B., & LeScanff, C. (2007). Predictors of perceived

susceptibility to sport‐related injury. Personality & Individual Differences, 34(8),

2218‐2228.

Dick, R., Hertel, J., Agel, J., Grossman, J., & Marshall, S. W. (2007a). Descriptive

epidemiology of collegiate men’s basketball injuries: National collegiate athletic

association injury surveillance system, 1988-1989 through 2003-2004. Journal of

Athletic Training, 42(2), 194-201.

Dick, R., Ferrara, M, Agel, J., Courson, R., Marshall, S., Hanley, M., & Reifsteck, F.

(2007b). Descriptive epidemiology of collegiate men’s football injuries: National

collegiate athletic association injury surveillance system, 1988-1989 through

2003-2004. Journal of Athletic Training, 42(2), 221-233.

107

Dick, R., Putukian, M., Agel, J., Evans, T. A., & Marshall, S. W. (2007c). Descriptive

epidemiology of collegiate women’s soccer injuries: National collegiate athletic

association injury surveillance system, 1988-1989 through 2002-2003. Journal of

Athletic Training, 42(2), 278-285.

Dils, A. K., & Ziatz, D. H. (2000). The application of teacher education curriculum

theory to interscholastic coaching education: Learning outcomes associated with a

quality interscholastic athletic program. The Physical Educator, 57(2), 88-98.

Dvorak, J., Junge, A., Chomiak, J., Graf-Baumann, T., Peterson, L., Rösch, D., &

Hodgson, R. (2000). Risk factor analysis for injuries in football players

possibilities for a prevention program. American Journal of Sports Medicine, 28,

suppl 5 S69-S74.

Eaton, D. K., Kann, L., Kinchen, S., Shanklin, S., Flint, K. H., Hawkins, J., ... Wechsler,

H. (2012). Youth risk behavior surveillance — United States, 2011. MMWR

Surveillance Summaries, 61(4), 1-162.

Emery, C. A. (2003). Risk factors for injury in child and adolescent sport: A systematic

review of the literature. Clinical Journal of Sport Medicine, 13, 256–268.

Emery, C. A. (2005). Injury prevention and future research. Medicine and Sport Science,

49, 170-191.

Emery, C. A., Cassidy, J. D., Klassen, T. P., Rosychuk, R. J., & Rowe, B. H. (2007).

Effectiveness of a home-based balance-training program in reducing sports-

related injuries among healthy adolescents: A cluster randomized controlled trial.

Canadian Medical Association Journal, 172(6), 749-754.

108

EuroSafe. (2009). Safety in Sports. EurpSafe Alert, November. Retrieved from

http://www.childsafetyeurope.org/csi/eurosafe2006.nsf/wwwAssets/5E205E34C1

80AB9BC12576C800290C8C/$file/Alert%20special%20issue%20Sport,%20Nov

ember%202009.pdf

Feltz, D. L., Chase, M. A., Moritz, S. E., & Sullivan, P. J. (1999). A conceptual model of

coaching efficacy: Preliminary investigation and instrument development. Journal

of Educational Psychology, 91(4), 765-776.

Fernandez, W. G., Yard, E. E., & Comstock, R. D. (2007). Epidemiology of lower

extremity injuries among U.S. high school athletes. Academic Emergency, 14(7),

641-645.

Finch, C., Donohue, S., & Garnham, A. (2002). Safety attitudes and beliefs of junior

Australian football players. Injury Prevention, 8(2), 151-154.

Francisco, A. C., Nightingale, R. W., Guilak, F., Glisson, R. R., & Garrett, W. E., Jr.

(2000). Comparison of soccer shin guards in preventing tibia fracture. American

Journal of Sports Medicine, 28, 227-233.

Fuller, C. W., Ekstrand, J., Junge, A., Andersen, T. E., Bahr, R.,..., Meeuwisse, W. H.

(2006). Consensus statement on injury definitions and data collection procedures

in studies of football (soccer) injuries. Clinical Journal of Sport Medicine,

16(2), 97-106.

Fuller, C. W., Molloy, M. G., Bagate, C., Bahr, R., Brooks, J. H., Donson, H.,…, Wiley,

P.(2007). Consensus statement on injury definitions and data collection

procedures for studies of injuries in rugby union. British Journal of Sports

Medicine, 42(5), 328-331.

http://www.ncbi.nlm.nih.gov/pubmed/17452684

109

Gianotti, S., & Hume, P. A. (2007). A cost-outcome approach to pre and post-

implementation of national sports injury prevention programs. Journal of Science

and Medicine in Sport,10, 436-446.

Gianotti, S., Hume, P. A., & Tunstall, H. (2008). Efficacy of injury prevention related

coach education within netball and soccer. Journal of Science and Medicine in

Sport, 13(1), 32-35.

Gielen, A.C., Sleet, D., & DiClemente, R. (Eds). (2006). Injury and violence prevention:

Behavioral science theories, methods, and applications. San Francisco: Jossey-

Bass Publishers.

Glanz, K., Rimer, B. K., & Viswanath, K. (Eds.). (2008). Health Behavior and Health

Education: Theory, Research, and Practice (4th ed.). San Francisco: Wiley, John

& Sons, Incorporated.

Hausenblas, H. A., & Carron, A. V. (1999). Eating disorder indices and athletes: An

integration. Journal of Sport & Exercise Psychology, 21(3), 230-258.

Hemenway, D., Aglipay, G. S., Helsing, K. L., & Raskob, G. E. (2006). Injury prevention

and control research and training in accredited schools of public health: A

CDC/ASPH assessment. Public Health Reports, 121(3), 349-351.

Hergenroeder, A. C. (1998). Prevention of sports injuries. Pediatrics, 101(6), 1057-1063.

Hootman, J. M., Dick, R., & Agel, J. (2007). Epidemiology of collegiate injuries for 15

sports: Summary and recommendations for injury prevention initiatives. Journal

of Athletic Training, 42(2), 311-319.

Human Kinetics (2009). Stretching Techniques. Retrieved July 1, 2009, from

http://hk.humankinetics.com/products/showexcerpt.cfm?excerpt_id=2929

110

Janssen, I., Dostaler, S., Boyce, W. F., & Pickett, W. (2007). Influence of multiple risk

behaviors on physical activity-related injuries in adolescents. Pediatrics, 119(3),

e672-e680.

Junge, A.(2000). The influence of psychological factors on sports injuries: Review of the

literature. American Journal of Sports Medicine, 28, S-10.

Junge, A., Rosch, D., Peterson, L., Graf-Baumann, T., & Dvorak, J. (2002). Prevention of

soccer injuries: A prospective intervention study in youth amateur players. The

American Journal of Sports Medicine, 30(5), 652-659.

Junge, A., Engebretsen, L., Alonso, J., Renström, P., Mountjoy, M., Aubry, M., &

Dvorak, J.(2008). Injury surveillance in multi-sport events: The international

Olympic committee approach. British Journal of Sports Medicine, 42, 413-421.

Kaut, K. P., DePompei, R., Kerr, J., & Congeni, J. (2003). Reports of head injury and

symptom knowledge among college athletes: Implications for assessment and

educational intervention. Clinical Journal of Sport Medicine, 13(4), 213-221.

Klavora, P. (2000). Vertical-jump tests: A critical review. Strength & Conditioning

Journal, 22(5), 70-75.

Lawrence, D. W., Stewart, G. W., Christy, D. M., Gibbs, L. I., & Ouellette, M. (1997).

High school- related cervical spinal cord injuries in Louisiana: The athlete’s

perspective. Journal of the Louisiana State Medical Society, 149(1), 27-31.

Leanderson, J., Nemeth, G., & Eriksson, E. (1993). Ankle injuries in basketball players.

Knee Surgery, Sports Traumatology, Arthroscopy, 1(3-4), 200-202.

http://bjsm.bmj.com/search?author1=P+Renstr%C3%B6m&sortspec=date&submit=Submit

111

Lett, R., Kobusingye, O., & Sethi, D. (2002). A unified framework for injury control: The

public health approach and Haddon’s Matrix combined. Injury Control and Safety

Promotion, 9(3), 199–205.

Levy, A., Polman, R., & Marchant, D. (2008). Examining the revised theory of planned

behavior for predicting exercise adherence: A preliminary prospective study.

Athletic Insight, 10(3). Retrieved from

http://www.athleticinsight.com/Vol10Iss3/ExercisePlanned.htm

Liller, K. D., Jang, S., Kadel, R., Morris, B., Konin, J., & Thorson, S. (2009). Results of

the SMART injury surveillance registry for high school athletes in west-central

Florida, USA: A pilot study. The Journal of Korean Society for School Health

Education, 10(2), 29-42.

Malinauskas, R. (2008). College athletes’ perceptions of social support provided by their

coach before injury and after it. Journal of Sports Medicine and Physical Fitness,

48(1), 107-112.

Marshall, S. W., Loomis, D. P., Waller, A. E., Chalmers, D. J., Bird, Y. N., Quarrie, K.

L., & Feehan, M. (2005). Evaluation of protective equipment for prevention of

injuries in rugby union. International Journal of Epidemiology, 34(1), 113-118.

McGlashan, A., Finch, C., Aucote, H., & Twomey, D. (2009). Ensuring uptake of sport

injury interventions: Are we using behavioural and social sciences theories and

models? A systematic review. Journal of Science and Medicine in Sport, 12, S54.

McGuine, T. (2006). Sports injuries in high school athletes: A review of injury risk and

injury prevention research. Clinical Journal of Sport Medicine, 16(6), 488-499.

http://www.athleticinsight.com/Vol10Iss3/ExercisePlanned.htm

112

Mensch, J., Crews, C., & Mitchell, M. (2005). Competing perspectives during

organizational socialization on the role of certified athletic trainers in high school

settings. Journal of Athletic Training, 40(4), 333-340.

Miller, N., & Dollard, J. (1941). Social Learning and Imitation. New Haven, Conn: Yale

University Press.

Morgan, D. L. (1998). Practical strategies for combining qualitative and quantitative

methods: Applications to health research. Qualitative Health Research, 8, 362–

376.

Myers, N. D., Feltz, D. L., & Wolfe, E. W. (2008). A confirmatory study of rating scale

category effectiveness for the Coaching Efficacy Scale. Research Quarterly for

Exercise and Sport, 79(3), 300-311.

National Association for Sport and Physical Education. (2009). National standards for

sport coaches, 2nd Edition. Retrieved July 1, 2009, from

http://www.aahperd.org/naspe/template.cfm?template=domainsStandards.html.

National Athletic Trainers’ Association. (2004). Appropriate medical care for the

secondary school-age athlete communication. Retrieved January 20, 2010, from

http://www.nata.org/statements/support/secondary_school_medcarecommunicatio

n.pdf

National Athletic Trainers’ Association. (2010a). Athletic training terminology.

Retrieved February 10, 2010, from

http://www.nata.org/about_AT/terminology.htm

http://www.aahperd.org/naspe/template.cfm?template=domainsStandards.html

http://www.nata.org/statements/support/secondary_school_medcarecommunication.pdf

http://www.nata.org/about_AT/terminology.htm

113

National Athletic Trainers’ Association. (2010b). Appropriate medical care for secondary

school-age athletes: Consensus statement. Retrieved September 25, 2010, from

http://www.nata.org/sites/default/files/AppropriateMedicalCare4SecondarySchool

AgeAthletes.pdf

National Athletic Trainers’ Association. (2013). Athletic training. Retrieved January 15,

2013, from http://www.nata.org/Athletic-Training

National Collegiate Athletic Association. (2010). National collegiate athletic association

Injury Surveillance System (ISS). Retrieved from

http://www.ncaa.org/wps/portal/ncaahome?WCM_GLOBAL_CONTEXT=/ncaa/

ncaa/academics+and+athletes/personal+welfare/iss/index.html

National Federation of State High school Associations. (2010). Concussion Rule Revised,

Strengthened in High School Football. Retrieved from

http://www.nfhs.org/content.aspx?id=3853

Oliaro, S., Anderson, S., & Hooker, D. (2001). Management of cerebral concussion in

sports: The athletic trainer’s perspective. Journal of Athletic Training, 36(3), 257-

262.

Ommundsen, Y., Roberts, G. C., Lemyre, P. N., & Miller, B. W. (2006). Parental and

coach support or pressure on psychosocial outcomes of pediatric athletes in

soccer. Clinical Journal of Sport Medicine, 16(6), 522-526.

Osborne, B. (2001). Principles of liability for athletic trainers: Managing sport-related

concussion. Journal of Athletic Training, 36(3), 316-321.

http://www.nata.org/sites/default/files/AppropriateMedicalCare4SecondarySchoolAgeAthletes.pdf

http://www.nata.org/Athletic-Training

http://www.ncaa.org/wps/portal/ncaahome?WCM_GLOBAL_CONTEXT=/ncaa/ncaa/academics+and+athletes/personal+welfare/iss/index.html

114

Otago, L., Swan, J., & Ramage, S. (2005). The risk management knowledge of basketball

coaches and their influence on the injury prevention strategies of their players.

Journal of Science and Medicine in Sport, 8(4), suppl. 206.

Pasque, C. B., & Hewett, T. E. (2000). A prospective study of high school wrestling

injuries. The American Journal of Sports Medicine, 28(4), 509-515.

Powell, J. W., & Barber-Foss, K. D. (1999). Injury patterns in selected high school

sports: A review of the 1995-1997 seasons. Journal of Athletic Training, 34(3),

277-284.

Powell, J. W., & Barber- Foss, K. D. (2000). Sex-related injury patterns among selected

high school sports. The American Journal of Sports Medicine, 28(3), 385-391.

Ramirez, M., Schaffer, K. B., Shen, H., Kashani, S., & Kraus, J. F. (2006). Injuries to

high school football athletes in California. The American Journal of Sports

Medicine, 34(7), 1147-1158.

Ransone, J. & Dunn-Bennett, L. (1999). Assessment of first-aid knowledge and decision

making of high school athletic coaches. Journal of Athletic Training, 34(3), 267-

271.

Rauh, M. J., Koepsell, T. D., Rivara, F. P., Margherita, A. J., & Rice, S. G. (2006).

Epidemiology of musculoskeletal injuries among high school cross-country

runners. American Journal of Epidemiology, 163(2), 151-159.

Rauh, M. J., Margherita, A. J., Rice, S. G., Koepsell, T. D. & Rivara, F. P. (2000). High

school cross country running injuries: A longitudinal study. Clinical Journal of

Sport Medicine, 10, 110-116.

115

Reel, J. J. & Gill, D. L. (1996). Psychosocial factors related to eating disorders among

high school and college female cheerleaders. The Sport Psychologist, 10, 195-

206.

Rosenfeld, L. B., Richman, J. M., & Hardy, C. J. (1989). Examining social support

networks among athletes: Description and relationship to stress. The Sport

Psychologist, 3(1), 23-33.

Rotter, J. B. (1954). Social Learning and Clinical Psychology. Englewood Cliffs, N.J:

Prentice-Hall.

Sagas, M., Cunningham, G. B., & Pastore, D. (2006). Predicting head coaching intentions

of male and female assistant coaches: An application of the theory of planned

behavior. Sex Roles, 54, 695-705.

Sands, W. A. (2000). Injury prevention in women’s gymnastics. Sports Medicine, 30(5),

359-373.

Sawyer, R. J., Hamdallah, M., White, D., Pruzan, M., Mitchko, J., & Huitric, M. (2010).

High school coaches’ assessments, intentions to use, and use of a concussion

prevention toolkit: Centers for Disease Control and Prevention’s Heads Up:

Concussion in high school sports. Health Promotion Practice. 11(1), 34–43.

Schulz, M. R., Marshall, S. W., Yang, J., Mueller, F. O., Weaver, N. L., & Bowling, J.

M. (2004). A prospective cohort study of injury incidence and risk factors in

North Carolina high school competitive cheerleaders. The American Journal of

Sports Medicine, 32(2), 396-405.

116

Shankar, P. R., Fields, S. K., Collins, C. L., Dick, R. W. & Comstock, R. D. (2007).

Epidemiology of high school and collegiate football injuries in the United States,

2005-2006. The American Journal of Sports Medicine, 35(8), 1295-1303.

Shehab, R., Mirabelli, M., Gorenflo, D., & Fetters, M. D. (2006). Pre-exercise stretching

and sports related injuries: Knowledge, attitudes and practices. Clinical Journal of

Sport Medicine, 16(3), 228-231.

Smith, R. E., Smoll, F. L., & Christensen, D. S. (1996). Behavioral assessment and

interventions in youth sports. Behavior Modification, 20(1), 3-44.

Steffen, K., Pensgaard, A. M., & Bahr, R. (2009). Self-reported psychological

characteristics as risk factors for injuries in female youth football. Scandinavian

Journal of Medicine & Science in Sports, 19(3), 442-451.

Theye, F., & Mueller, K. A. (2004). “Heads up”: Concussions in high school sports.

Clinical Medicine and Research, 2(3), 165-171.

Victorian Health Promotion Foundation. (2006). Parental perceptions of sports injury

risk project. Australia: Otago, L., Spittle, M., Garnham, J., Reynolds, M., &

Finch, C.

Wang, H. K., Chen, C. H., Shiang, T. Y., Jan, M. H., & Lin, K. H. (2006). Risk-factor

analysis of high school basketball-player ankle injuries: A prospective controlled

cohort study evaluating postural sway, ankle strength, and flexibility. Archives of

Physical Medicine and Rehabilitation, 87(6), 821-825.

Weiker, G. G. (1985). Club gymnastics. Clinics in Sports Medicine, 4(1), 39-43.

West, S. A. & Ciccolella, M. E. (2004). Issues in the standard care for certified athletic

trainers. Journal of Legal Aspects of Sport, 63, 1-8.

117

Yang, J., Bowling, J. M., Lewis, M. A., Marshall, S. W., Runyan, C. W., & Mueller, F.

O. (2005). Use of discretionary protective equipment in high school athletes:

Prevalence and determinants. American Journal of Public Health, 161(6), 511-

519.

Yang, J., Peek-Asa, C., Allareddy, V., Phillips, G., Zhang, Y., & Cheng, G. (2007).

Patient and hospital characteristics associated with length of stay and hospital

charges for pediatric sports-related injury hospitalizations in the United States,

2000–2003. Pediatrics, 119(4), e813-e820.

Yard, E. E., Collins, C. L., Dick, R. W., & Comstock, R. D. (2008). An epidemiologic

comparison of high school and college wrestling injuries. American Journal of

Sports Medicine.36(1), 57-64.

Yard, E. E., Collins, C. L., & Comstock, R. D. (2009). A comparison of high school

sports injury surveillance data reporting by certified athletic trainers and coaches.

Journal of athletic training, 44(6), 645-652.

Yeung, M. S., Chan, K. M., So, C. H., & Yuan, W. Y. (1994). An epidemiological survey

on ankle sprain. British Journal of Sports Medicine, 28(2), 112-116.

Zemper, E. D. (2003). Two-year prospective study of relative risk of a second cerebral

concussion. American Journal of Physical Medicine & Rehabilitation, 82(9), 653-

659.

118

Appendices

119

Appendix A: IRB Documents

120

121

122

123

124

125

Appendix B: Delphi Questionnaire

126

127

128

129

130

131

132

133

134

135

136

137

138

139

140

Appendix C: Coach Survey Questionnaire

141

142

143

144

145

146

147

Appendix D: Coaches’ Experiences Regarding Injury Prevention

Question 8: What coaching qualifications do you have for this sport?

Frequency Valid

Percent

Cumulative

Percent

Cert. in coaching at State level organization 9 12.3 39.7

Cert. in coaching at county level organization 3 4.1 43.8

Cert. in other organization 6 8.2 52.1

PE, fitness, or Athletic training degree 4 5.5 57.5

Took Courses regarding the sport 15 20.5 78.1

Played(coached) the sport for years 13 17.8 95.9

Received coaching award 3 4.1 100.0

Total 73 100.0

Missing values 38

Total 111

Question 9: What trainings and/or education have you had related to injury prevention?

Frequency Valid

Percent

Cumulative

Percent

Concussion 32 20.3 27.2

County program 5 3.2 30.4

CPR 50 31.6 62.0

Degree in Athletic training/PE 5 3.2 65.2

First aid 25 15.8 81.0

Other injury prevention training/session 24 15.2 96.2

College course on injury prevention 6 3.8 100.0

Total* 158 100.0

*Multiple-choice question

148

Question 10: In what aspects of injury prevention programs do you feel you need more

training?

Injury prevention program Frequency Valid

Percent

Cumulative

Percent

1 Action plan 3 3.5 8.2

2 AED 2 2.4 10.6

4 All interventions 3 3.5 14.1

6 Asthma 3 3.5 17.6

7 Conditioning 2 2.4 20.0

8 Cool down/warm up 1 1.2 21.2

9 Diabetes 2 2.4 23.5

10 Eating habits 1 1.2 24.7

12 First Aid 2 2.4 27.1

13 Fractures 1 1.2 28.2

14 Heat illnesses 4 4.7 32.9

15 heart related illness including CPR 3 3.5 36.5

16Hydration 1 1.2 37.6

18 Injury prevention (General) 22 25.9 63.5

19 Knee health Response procedures when not

around trainer or other medical staff

1 1.2 64.7

23 Spinal injuries 1 1.2 65.9

24 Sport specific training exercises 1 1.2 67.1

25 Sprains 2 2.4 69.4

26 Stretching 4 4.7 74.1

27 Wrapping and Taping 7 8.2 82.4

28 Specific body part related prevention (back,

shoulder knee, lower body

7 8.2 90.6

29 Etc (rehab, allergy,stress ) 8 9.4 100.0

Total* 85 100.0

*Multiple-choice question

149

*Multiple-choice question

Question 11: What steps do you usually take to prevent sports injuries?

Frequency

Valid

Percent

Cumulative

Percent

1 Athletic education 2 .9 .9

3 Safety of environment including checking fields 9 4.1 5.1

4 Concussions 1 .5 5.5

5 Conditioning drills 25 11.5 17.1

6 Consulting trainer 4 1.8 18.9

7 Athletic education 17 7.8 26.7

8 Equipment check 20 9.2 35.9

9 Exercise 1 .5 36.4

12 Hydration 16 7.4 43.8

13 Nutrition plan 6 2.8 46.5

14 PEP 2 .9 47.5

17 Stretching 38 17.5 65.0

18 Proper techniques for safe play 13 6.0 71.0

20 Ice 8 3.7 74.7

21 Strength building 1 .5 75.1

22 Warm-up/cool downs 24 11.1 86.2

23 Wrapping/Taping 4 1.8 88.0

24 Etc (fundamental training, weight training, safe

habits, rest)

25 11.5 99.5

25 Missing value 1 .5 100.0

Total* 217 100.0

150

Question 12: Which injury prevention programs (i.e. conditioning drills, safety education

for athletes, etc) do you feel work well?

Frequency

Valid

Percent

Cumulative

Percent

4 Concussions 1 .6 1.3

5 Conditioning drills 49 31.0 32.3

7 Athletic education 24 15.2 47.5

8 Equipment check 4 2.5 50.0

11 Ice 1 .6 50.6

12 Hydration 4 2.5 53.2

13 Nutrition plan 2 1.3 54.4

14 PEP 1 .6 55.1

17 Stretching 28 17.7 72.8

18 Proper techniques for safe play 4 2.5 75.3

20 Ice 1 .6 75.9

21 Strength building 1 .6 76.6

22 Warm-up/cool downs 13 8.2 84.8

24 Etc 24 15.2 100.0

Total* 158 100.0

*Multiple-choice question

Question 13: From your perspective as a coach, who is most effective in leading injury

prevention efforts?

Frequency

Valid

Percent

Cumulative

Percent

1 Coach 63 48.1 48.1

2 Athletic trainer 48 36.6 84.7

3 Other medical staff 5 3.8 88.5

4 Parents 3 2.3 90.8

5 Other 6 4.6 95.4

99 Missing value 6 4.6 100.0

Total 131 100.0

Question 14: How important do you believe conditioning drills are in preventing injuries?

5-point Likert Scale

(1= Not important, 5=Very important) Frequency

Valid

Percent

Cumulative

Percent

3 3 2.7 3.6

4 20 18.2 21.8

5 81 73.6 95.5

Missing values 5 4.5 100.0

Total 110 100.0

151

Appendix E: Example Frequency Tables for Coach Survey

Question 1: Implementing Injury prevention program

Frequency Valid

Percent

Cumulative

Percent

no in the next 6 months 3 2.7 2.7

yes in the next 6 months 12 10.8 13.5

Occasionally 30 27.0 40.5

for less than 6 months 16 14.4 55.0

for 6 months or more 34 30.6 85.6

other person 14 12.6 98.2

99 2 1.8 100.0

Total 111 100.0

Question 12: Implementing an injury prevention program is the best way to prevent and reduce

injuries

5-point Likert Scale

(1= Very likely, 5=Very unlikely)

Frequency Valid

Percent

Cumulative

Percent

1 41 36.9 36.9

2 39 35.1 72.1

3 24 21.6 93.7

4 5 4.5 98.2

5 2 1.8 100.0

Total 111 100.0

152

Frequency of Knowledge Questions (Question 23-31)

Question number

(key word) 1 2 3 4 Total n

23 (AED use) 6 (5.5) 2 (1.8) 97 (88.2) 5 (4.5) 110

24 (CPR) 1 ( .9) 0 32 (29.1) 77 (70.0) 110

25 (ice and heat use) 5 (4.6) 5 (4.6) 69 (63.9) 29 (26.9) 108

26 (paralysis) 8 (7.3) 19 (17.4) 76 (69.7) 6 (5.5) 109

27 (heat illness) 1 ( .9) 88 (81.5) 10 (9.3) 9 (8.3) 108

28 (dehydration) 2 (1.8) 10 (9.1) 94 (85.5) 4 (3.6) 110

29 (medical conditions) 20 (19.0) 5 (4.8) 26 (24.8) 54 (51.4) 105

30 (Asthma) 5 (4.6) 85 (78.7) 9 (8.3) 9 (8.3) 108

31 (Concussion) 1 ( .9) 92 (86.0) 10 (9.3) 4 (3.7) 107

* Correct answer highlighted

University of South Florida
Scholar Commons

January 2013

The Relationship between High School Coaches' Beliefs about Sports Injury and Prevention Practice Readiness

Siwon Jang

Scholar Commons Citation