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AN ASSESSMENT OF THE FACTORS PREDICTING
COACHING EFFICACY AND COACHING
SATISFACTION IN YOUTH SPORTS

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Craig A. Paiement

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AN ASSESSMENT OF THE FACTORS PREDICTING COACHING EFFICACY
AND COACHING SATISFACTION IN YOUTH SPORTS

By

Craig A. Paiement

A DISSERTATION

Submitted to
Michigan State University
in partial fulﬁllment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY

Department of Kinesiology

2006

ABSTRACT

AN ASSESSMENT OF THE FACTORS PREDICT ING COACHING EFFICACY
AND COACHING SATISFACTION IN YOUTH SPORTS

By

Craig A. Paiement

The main purpose of this study was to investigate the relationships among sources
of efficacy information, coaching efﬁcacy and coaching satisfaction of youth hockey
coaches. Previous research has shown that coaching education, experience, playing
experience, perceived ability of the team, and social support signiﬁcantly predicted
coaching efﬁcacy. This dissertation added perceived skill improvement of the team and
age of the coach as predictors of coaching efficacy. The study also added coaching
satisfaction as an outcome of efficacy information sources and coaching efﬁcacy.

Participants for this study were 512 amateur ice hockey coaches attending USA
Hockey coaching certiﬁcation clinics in the Northeastern and Midwestern United States.
The ﬁndings suggest that coaching efﬁcacy and satisfaction of volunteer youth coaches is
predicted by previous coaching experience, social support and playing experience.
Perceived team improvement was also a signiﬁcant predictor of coaching efﬁcacy, but
did not provide a large contribution to the regression equation. Age of the coach was
significant and provided a small contribution to coaching efﬁcacy but was negatively
correlated with it, indicating that younger coaches perceived higher levels of efficacy.
Coaching education level and perceived team ability did not provide a signiﬁcant

contribution to coaching efficacy in this study. These ﬁndings add to the coaching

efﬁcacy literature, not only are social support and coaching experience strong predictors
of coaching efﬁcacy, but along with coaching efﬁcacy they also predict coaching
satisfaction.

Practically, coaching education programs may need to focus on instilling the skills
necessary to garner social support from parents, athletes and the organization.
Additionally, coaching education may need to include an internship or mentored
coaching experience prior to a coaching assignment to provide opportunities for coaches

to develop a sense of coaching efficacy.

ACKNOWLEDGEIVIENTS

This project would not have happened without the support of many people. I am
blessed to have had this opportunity and to have so many great people willing to help me
become a better person.

First and foremost, to my parents, Lloyd and Claudette, the love and support you
have given me in all of my activities can never be measured. Simply, I owe you everything.

Next, I want to extend my sincerest appreciation and gratitude to my doctoral
committee chair and advisor, Dr. Deborah Feltz for her support and positive inﬂuence
throughout my doctoral studies. I am forever indebted to you.

I would also like to extend my utmost appreciation for the contributions of time,
effort, patience, and understanding of the additional members of my committee - Dr. Marty
Ewing, Dr. Dan Gould, and Dr. Jere Brophy. Your guidance was invaluable.

I would be remiss to not acknowledge the love and support of my wife Christy, who
provided data collecting and entry, editorial, emotional and motivational support.

Ryan Hedstrom, thank you for your friendship, support, critical analysis, the much
needed reality checks, and just being in the trenches with me for four years.

I would like to thank Nathan Roman and USA Hockey for helping with data
collection. I would also like to acknowledge Dr. Rick McNeil, for your friendship, support
and your contribution to my professional studies and Dr. Nick Myers for providing timely
advice and support.

Finally, I would like to recognize the Spencer Research Training Grant, which

made this project possible and provided me with the ﬁnancial support to improve my

research skills.

iv

TABLE OF CONTENTS

LIST OF TABLES .................................................................................................... vii
LIST OF FIGURES ................................................................................................... viii
CHAPTER 1
INTRODUCTION ..................................................................................................... 1
Factors that Inﬂuence Coaching Motivation and Satisfaction ...................... 3
Hom’s Model of Coaching Effectiveness ..................................................... 3
Model of Coaching Efﬁcacy ......................................................................... 5
Satisfaction with Coaching ............................................................................ 9
Purpose .......................................................................................................... 13
Hypothesis and proposed model ................................................................... 13
CHAPTER 2
. REVIEW OF LITERATURE .................................................................................... 15
Coaching Development and Effectiveness Models ....................................... 16
Cote et a1. (1995) Coaching Development Model ................................... l6
Horn (2002) Coaching Effectiveness Model ........................................... 17
Coaching Efﬁcacy ......................................................................................... 19
Development of the Coaching Efﬁcacy Model ............................................. l9
Self-efﬁcacy theory background ............................................................. 19
Teacher efﬁcacy background .................................................................. 20
Development and examination of the Feltz et a] model .......................... 22
Research on coaching efficacy and coaching education ......................... 25
Research on outcomes of coaching efﬁcacy ........................................... 27
Research on sources of coaching efﬁcacy ............................................... 29
Coaching Process .......................................................................................... 31
Coaching Education ................................................................................ 36
Coaching Preparation Motives ................................................................ 36
Formal Coaching Education Programs ................................................... 37
Problems with Coaching Education Programs ........................................ 38
Critical Evaluation of Coaching Education Programs ............................ 39
Coaching Satisfaction .................................................................................... 41
Social Support and Satisfaction ............................................................... 43
Leadership and Satisfaction .................................................................... 45
_ Job Satisfaction ....................................................................................... 47
Work Motivation ..................................................................................... 49
Outcomes of Job Satisfaction .................................................................. 50
Summary ....................................................................................................... 5 1

CHAPTER 3

METHOD .................................................................................................................. 53
Study Design and Participants ....................................................................... 53
Instrumentation .............................................................................................. 56

Coaching Efficacy Scale ......................................................................... 56
Demographic Questionnaire .................................................................... 58
Satisfaction .............................................................................................. 58
Team ability and team improvement ....................................................... 61
Support .................................................................................................... 62
Procedure ....................................................................................................... 63
Data Analysis .................................................................... 64

CHAPTER 4

RESULTS .................................................................................................................. 67
Preliminary Analyses .................................................................................... 67
Descriptive Statistics ..................................................................................... 69
Correlations Among the Predictor and Criterion Variables .......................... 70
Tests of the Hypotheses ................................................................................. 72
Path analysis .................................................................................................. 75
Exploratory Analysis for Coaching Education .............................................. 77

DISCUSSION ........................................................................................................... 8 1
Implications for Coaches ............................................................................... 91
Limitations .................................................................................................... 93
Future Directions ........................................................................................... 94

APPENDICES ........................................................................................................... 97
Appendix A: Coaching Confidence Questionnaire ....................................... 97
Appendix B: Demographic Questionnaire .................................................... 98
Appendix C: Satisfaction Questionnaire ....................................................... 99
Appendix D: Consent form ........................................................................... 100

REFERENCES .......................................................................................................... 101

vi

Table 1

Table 2

Table 3

Table 4

Table 5

Table 6

Table 7

Table 8

Table 9

Table 10

Table 11

Table 12

Table 13

Table 14

Table 15

LIST OF TABLES

Means, Standard Deviations and Range for Age, Years of Coaching and

Playing Experience for the Participants .................................................. 54
Frequency of Age Level of Teams Coached by Participants .................. 54
Frequency Table for Sex and Ethnicity ................................................... 55
Coaching Experience ............................................................................... 55
Internal Consistency Estimates for CBS Dimensions ............................. 57
Factor Loadings for Satisfaction Measure .............................................. 61
Summary Statistics for Normality ........................................................... 68

Descriptive Statistics for Sources of Support, Satisfaction and Coaching
Efficacy ................................................................................................... 70

Pearson Correlation Coefﬁcients between Coaching Efﬁcacy and Social
Support .................................................................................................... 71

Pearson Correlation Coefficients for Coaching Efficacy and Sources 72

Results for Univariate Regressions for Mediational Effect of Coaching
Efﬁcacy ................................................................................................... 74

Means and Standard Deviations for Coaching Education Level ............. 78

Means and Standard Deviations for Coaching Education Level and First-
Order Factors of Coaching Efﬁcacy ........................................................ 78

Multivariate Analysis of Variance of Coaching Education Program
Level ........................................................................................................ 79

Multivariate Analysis of Variance of Coaching Education Program Level
while Controlling for Years of Coaching Experience ............................. 80

vii

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5

Figure 6

LIST OF FIGURES

Model of coaching effectiveness (Horn, 2002) ....................................... 4
Coaching efﬁcacy model (Feltz et al., 1999) ......................................... 6

Hypothesized model of coaching efﬁcacy and coaching satisfaction ..... 14

C6te et al. (1995) coaching model ......................................................... 17
Proposed model for the path analysis ...................................................... 75
Signiﬁcant parameter estimates for the reduced model .......................... 77

viii

CHAPTER 1

Introduction

Coaching by deﬁnition is the task of assisting an athlete to achieve the best
possible level of performance (Woodman, 1993). Coaching athletes can be a highly
rewarding experience and a number of factors can inﬂuence the level of enjoyment that a
coach has with his or her experience in an athletic leadership role. Athletic development
begins with interest in a sport or activity and the motivation to participate. Coaching at
the youth level often begins in much the same way; an interested person has the
motivation to share his or her experience and knowledge of a sport with young athletes.
Generally, the person coaching is trying to give back to the sport to help children improve
themselves as athletes and as people. A coach’s inﬂuence in this way has long been
associated with beneﬁts to athletes through improved performance, development of
character, athlete satisfaction, and a host of other positive outcomes (Baker, Yardley &
Cote, 2003; Gould, Greenleaf, Chung & Guinan, 2002; Gould, Greenleaf, Guinan &
Chung, 2002; Greenleaf, Gould & Dieffenbach, 2001). A coach’s behavior in trying to
improve athletic performance can also have a large inﬂuence on some negative athlete
outcomes, such as athlete attrition (Barnett, Smoll & Smith, 1992).

Although there have been numerous studies regarding coaching inﬂuences on
athlete outcomes, there has been a paucity of research on the benefits of coaching for the
coaches themselves. Understanding the motivation of participating in coaching, as well as
the aspects that lead to coaches’ satisfaction and retention, is important because it

ultimately impacts the athlete development cycle. That is, if a coach has been involved

with a team and developing the skills and attitudes of these athletes, but then quits, the
athletes’ progress is disrupted, and they have to start the cycle with another coach.
Coaching turnover has been linked to poorer performance in sport in numerous studies
(Goines, 1997; Koning, 2003; Rowe, Cenella, Renski, & Gorrn, 2004). If skilled coaches
are not ﬁnding some personal satisfaction in coaching, then their long-term retention and
motivation may be difficult to achieve (Andrew & Schwab, 1995, Raedeke, 2004;
Raedeke, Warren & Granzyk, 2002).

Understanding coaches’ participation motivation and satisfaction in coaching may
be as simple as a father or mother volunteering to coach a little league team, regardless of
knowledge of the sport or previous experience with coaching, or motivation that is
provided by being paid to coach. However, most coaches in the athletic development
cycle are not paid. For example, Martens (1984, 1996) estimates 2.5-3 million people
volunteer as youth sport coaches annually, in contrast to the 30,000 coaches employed
professionally each year in the United States (National Labor Bureau, 2002). Also, many
coaches are not parents. A year 2000 survey of participation in Canadian youth sport
revealed that 35% of youth athletes had a parent as a coach or team administrator
(Statistics Canada, 2000). Therefore, the issues surrounding one’s motivation to coach or
to stop coaching may be more complex than money or involvement with their own
children. Once a clearer understanding of the factors surrounding coaching motivation is
constructed, then ways to foster such inﬂuential factors can be produced and incorporated

into coaching development programs

Factors that Inﬂuence Coaching Motivation and Satisfaction

Numerous factors assessed in this study that may be linked to coaches’ motivation
and subsequent satisfaction with coaching including: coaching education, coaching
efﬁcacy, team factors (ability, perception of improvement), and personal factors (age,
experience). These factors are embedded into two models of coaching effectiveness (e.g.,
Feltz, Chase, Moritz, & Sullivan, 1999; Horn, 2002). In order to understand the
relationship of these factors to coaches’ motivation and satisfaction, the models are
presented in the following sections. Hom’s model of coaching effectiveness is the most
comprehensive model and the Feltz et a1. model is speciﬁc to coaching efﬁcacy.
Both are presented as the framework for coaching satisfaction.
Horn ’3 Model of Coaching Eﬂectiveness

Hom’s model (2002, see Figure 1) includes many of the variables assessed in this
study such as coaches’ personal characteristics (Box 3), coaches’ expectancies of their
athletes (Box 3) and coaches’ behavior (Box 4). Horn (2002) developed a working
coaching effectiveness model as a way to connect research on coaching inputs to athlete
outcomes. Horn included the factors from Cote’, Salmela, Trude], Baria and Russell’s
(1995) coaching model, but addressed additional factors and expanded on the outcomes
of coaching behaviors. Horn added organizational climate to the predictors of coaching
behavior, but more importantly, separated the coaching process into two boxes (Boxes 4
and 5). This model purports that coaches’ cognitions drive their behaviors. Horn also
indicated that coaching efﬁcacy is included in Box 3, which is titled “coaches personal
characteristics.” This may be conceptually troubling as, theoretically, efﬁcacy is a part of

Social Cognitive Theory (Bandura, 1986), which would frame efficacy as a cognition and

should be included in Box 4, not Box 3. Box 4 in Hom’s (2002) model includes
expectancies, values, beliefs, and goals, which all are inclusive of cognitions that affect
coaching behaviors. Coaches’ personal characteristics in the Horn model include such
categories as playing and coaching experience, critical thinking skills, decision making
styles and self-efﬁcacy. Boxes 3-5 are fairly undeﬁned and testing the conceptual links
may reveal that certain categories need to be reassessed and shifted. Ideally, the links
between the cognitive appraisals of one’s coaching will create a better deﬁned model. As
Feltz, Short, and Sullivan (in press) noted, the consequences of coaching behavior in
Hom’s model focus solely on athletes’ psychosocial growth and development and not on
other coaching factors, such as coaching commitment and burnout. Although Hom’s
model appears to be complex, any model must match the complexity of the construct that

it is purported to explain, and coaching effectiveness is an extremely complex construct.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  
   

 

 

 

 

 

 

  

 

Box 7
Athletes’ personal
Box 1 characteristics
Sociocultural Context ¢
Box 4 Box 8
B 2 Coaches’ Box 5 , Athlete perception,
Or , .0x 1 Cl' _. Expectancies, Coaches and evaluation of
ganrzatrona rmate values, beliefs Behavrors coaches’ behavior
and goals l ’ ‘
Box 3 Box 9
Coaches’ Personal Box 6 , Athletes’ self-
Characteristics Athletes perceptions, beliefs
performance & attitudes
and behavior ;
Box 10

Athlete motivation

 

 

 

 

 

Figure 1. Model of coaching effectiveness (Horn, 2002)

Including other theoretical models within a proposed model can create additional
complexities. For instance, as previously stated, coaching efﬁcacy is a cognition and
should not be grouped with coaches’ personal characteristics, but rather with Box 4, as
self-efﬁcacy beliefs are more related to coaches’ expectancies of athletes, values, and
beliefs. Coaching efﬁcacy is framed as a belief, and therefore should be included in Box
4. However, within social cognitive theory, efficacy beliefs inﬂuence goals and other
cognitions (Bandura, 1986, 1997), and could be a box of its own.

Horn (2002) calls for research examining the effects of coaches’ behavior, beliefs,
and personal characteristics on their own psychological responses and reactions that
inﬂuence coaching motivation. Speciﬁcally, Horn (2002) alludes to coaching burnout
(Dale & Weinberg, 1990), commitment to coaching (Raedeke, 2004) and satisfaction
with coaching. However, these coaching outcomes are not included in her model. The
present study targets the inﬂuence of coaching efficacy and personal characteristics (e. g.
experience, education, and age) as predictors on coaching satisfaction.

Model of Coaching Eﬁ‘icacy ( F eltz et al., 1999)

Coaches have expectations related to their coaching actions. Most believe that
they have the ability to affect change among their athletes. This belief is described by
Bandura (1977, 1997) as self-efﬁcacy. The theory of self-efﬁcacy refers to the extent one
believes he or she can be successful at a given task, which in turn, affects motivation and
action. Bandura (1997) also warns that although self-efficacy plays a crucial role in social
cognitive theory, it is not the sole determinant of action, as one will also see within
coaching. Bandura cites four main sources that contribute to the development of self-

efficacy: past performance accomplishments, vicarious experiences, verbal persuasion,

and physiological states. In applying the concept to coaching, Feltz et a1. (1999) deﬁned
coaching efﬁcacy as “the extent to which coaches believe they have the capacity to affect
the learning and performance of athletes.” While previous experience is a main construct
of efﬁcacy information, one area that may be related to experience is age of the coach. .
Even if a coach has less coaching experience, older coaches may have more vicarious
experience to draw on for efﬁcacy information.

In the development of a coaching efﬁcacy model, Feltz et al. (1999) described
four speciﬁc dimensions that contribute to general coaching efﬁcacy: game strategy
(GSE), motivation (ME), teaching techniques (TE), and character building efﬁcacy
(CBE) (see Figure 2). Feltz et a1. (1999) documented some important outcomes of
coaching efficacy, namely coaches with higher efficacy scores gave athletes more praise

and instruction than coaches with lower efﬁcacy scores.

 

 

 

 

Sources of Coaching Outcomes
Efﬁcacy Coaching Efﬁcacy
ELMO—IE Coaching behavior
Coaching Experience
Game Strategy Player/team
Prior Success . Satisfaction
p Motivation
Perceived Skill of . Player/team
Athletes Technique performance
Sc hool/Community Character Player/team
Support Burldrng efﬁcacy

 

 

 

 

 

 

 

 

 

Figure 2. Coaching efficacy model (Feltz et al., 1999)

Additionally, athletes reported higher satisfaction scores with coaches that
reported high coaching efﬁcacy (Myers, Tonsing & Feltz, 2005). Conversely,

commitment to coaching, a construct that was hypothesized as a possible motivational

outcome for coaches, was not related to coaching efficacy in Feltz et al. (1999), though
Kent and Sullivan (2003) did ﬁnd that commitment and retention of coaches was
predicated by coaching efficacy. Coaching efﬁcacy also has been found to relate to
leadership style (Sullivan. & Kent, 2003), coaches’ expectations of their teams’
performance (Chase, Lirgg, & Feltz, 1997), and team and player efﬁcacy (Vargas-
Tonsing, Warners, & Feltz, 2003). Outcomes of coaching efﬁcacy provide useful
information in coaching development, but discovering additional sources of coaching
efﬁcacy can provide important information to increase the level of coaching satisfaction
concurrently with increases in coaching efficacy.

Feltz et al. (1999) found that community, parental, and athletic directors’ support
were significant sources for creating a sense of coaching efﬁcacy for high school
coaches. Coaching experience and the coaches’ perception of the teams’ ability also
provided efﬁcacy information to coaches. Others have found similar results with Division
II and III collegiate coaches (Marback, Short, Short & Sullivan, 2005; Myers et al.,
2005). Malete and Feltz (2000) also found support for coaching education as a source of
efficacy.

As just noted, social support which can be thought of as a type of persuasion
within self-efficacy theory, was an important source of efficacy information for coaches
within the Feltz et a1. (1999) model. Social support can be deﬁned as information that
leads individuals to believe that they are esteemed and valued and that they participate in
a network of communication and mutual obligation (Cobb, 1976). In the coaching
efficacy literature, social support is used to measure the support levels for the coach by

athletes, parents, organizations, and the community. In addition to Feltz et al.’s (1999)

findings that parental, community, and athletic director support were significant sources,
Chase, Feltz, Hayashi, and Hepler (2005) also found that player support was an important
source of social support for coaching efficacy.

A coach’s own prior playing experience has also been shown to be a source of
coaching efﬁcacy information (Chase et al., 2005; Sullivan, Gee, & Feltz, in press).
Sullivan et al. (in press) assessed the relative importance of previous playing experience
(while controlling for coaching experience) as a predictor of coaching efﬁcacy and found
that playing experience was a stronger predictor of GSE than was coaching experience,
but not for the other dimensions of coaching efﬁcacy. Thus, for those aspects of coaching
that involve the application of practical game skills and knowledge, playing experience
may be an additional source of coaching efﬁcacy.

One additional predictor of coaching efﬁcacy that must be addressed is the
coaches’ perceptions of team ability, because ability has been shown to have a strong
relationship to efﬁcacy (Lirgg, George, Chase & Ferguson, 1996; Myers et al., 2005).
Lirgg, DiBrezzo and Smith (1994) found athlete ability to be the strongest predictor of
coaches’ efﬁcacy. Coaches’ perceived athlete ability may also be predictive of coaching
satisfaction, because athletes with high ability and high levels of skill improvement may
provide “success” information to coaches and a more enjoyable coaching experience. In
youth sport, particularly in volunteer coaching situations, athletes’ improvement may also
serve as “success” information, because team win/loss records are not published publicly
and do not follow the coach from year to year. Furthermore, in most youth sport
organizations, the expressed purpose is for increased activity level and skill acquisition

and improvement, not winning (Martens, 2004). For the present study, career winning

percentage and season win/loss records were not used, as they were deemed inappropriate
for this population, and were impossible to conﬁrm as accurate.
Satisfaction with Coaching

Satisfaction with one’s coaching experience may also be a factor that inﬂuences
coaching motivation and retention. This level of satisfaction may be inﬂuenced by
coaching efﬁcacy and the same sources of efﬁcacy information. Satisfaction with one’s
own performance provides important information regarding motivation to strive toward
certain goals. As Bandura (1997) states “efﬁcacy is not the sole determinant of action,”
satisfaction or personal meaning must also be a contributing force to the action of human
agency. If efﬁcacy is high, but a lack of social support provides negative information,
then those involved may begin to search out other means of activity that are more
beneﬁcial to the participant (Milner & Hoy, 2003). Feltz el al. (1999) expressed the need
for the examination of additional sources and outcomes of coaching efficacy. One
outcome that they did not include as a hypothesized motivational outcome of coaching
efﬁcacy was satisfaction with coaching. Satisfaction has been related to speciﬁc sources
of efficacy beliefs, such as professional preparation and community support (Matthes &
Duffy, 1989). In the field of teaching, outcomes of teaching efﬁcacy, such as satisfaction
with professional performance in teachers have been observed (W oolfolk-Hoy, 2000).
Woolfolk-Hoy also notes that satisfaction with performance is affected by the difﬁculty
of teaching assignment, which includes perception of student abilities and organizational
support. As previously mentioned, many factors contribute to the action of human
agency, and within this study, efﬁcacy beliefs and satisfaction are two factors believed to

have signiﬁcant effects on coaches. If a lack of coaching efficacy or coaching satisfaction

is recognized, then the development of coaches can be hindered as retention becomes an
issue and the end goal of athlete development slows.

Herzberg, Mausner & Snyderrnan (1959) developed the theory of motivation-
hygiene to explain the effect of job satisfaction on work motivation. Herzberg et a1.
explained motivation through satisﬁers such as: recognition, achievement, and personal
growth. This provides support to such predictors of coaching satisfaction as social
support, team improvement, and coaching education respectively. Maslow (1970) also
developed a popular theory of motivation focused on needs at various levels of
development, concluding with self-actualization, which embodies the overall feelings of
satisfaction with one’s life put into action. Although self-actualization is rare, it does
provide a theoretical argument that motivation derives its roots from satisfaction, just as
Herzberg et al. (1959) hypothesizes that motivation to work is born from satisfaction.

A significant issue with the development of both athletes and coaches is the
amount of annual turnover within each sport. Natural turnover will always be a part of
any sport with developing athletes. Reasons for natural turnover in athletes may include
the decision to concentrate on one sport, graduating from amateur age categories, and
injuries. The natural turnover in coaches also seems to take on a similar pattern, in which
parent-coaches leave with his or her child, or step out of coaching roles because of young
children at home or family commitments (Cunningham & Sagas, 2003). The type of
turnover that must be avoided for both athletes and coaches is the type that includes
dissatisfaction with the experience and with those who are responsible for contributing to
a positive experience (i.e., coaches, youth sport organization). If they are provided with a

rewarding and satisfying environment, more quality coaches may be compelled to stay on

10

as coaches and continue to contribute positively to the personal development of youth
athletes, regardless of participation of their own children. In assessing effective coaching,
one must realize that coaches’ cognitions (i.e., efﬁcacy) have a signiﬁcant impact on the
athletes, as well as on the coaches themselves. Coaching at the amateur level involves
athlete outcomes (e.g., athlete performance, athlete satisfaction, and athlete motivation)
as well as coaching outcomes (e.g., positive coaching behaviors and satisfaction with
coaching). These outcomes are important to such “ﬁnal outcomes” as coach retention,
athlete retention, and athlete development. Therefore, it becomes imperative to
understand the factors that contribute to coaching cognitions, as well as the effect of such
cognitions on coaching satisfaction.

The concepts of satisfaction and efficacy both stem from motivational research, as
Herzberg et al. (1959) and Maslow (1970) explained in their early social psychological
research. Their research portends that human agency is driven by motivation, and
motivation is driven by various factors, speciﬁcally satisfaction (Herzberg) and
actualization (Maslow), in addition to a sense of “self”. Bandura (1986) forwarded this
sense of “self” in motivation and human agency in sport through social cognitive theory.
The constructs of coaching satisfaction and coaching efﬁcacy have not yet been
connected in sport, although recent research has produced evidence that coaching
efﬁcacy predicts team satisfaction with the coach (Myers, Vargas-Tonsing & Feltz,
2005). Myers et al. forwarded the assertion that a coach with increased feelings of
conﬁdence in his or her ability to coach will have more satisﬁed athletes. As presented in
the teacher efﬁcacy literature, it would then be reasonable to believe that a coach who is

confident in his or her abilities to coach will also be more satisﬁed as a coach (Chapman

ll

& Lowther, 1982). Obviously, there are other factors that contribute to coaching
satisfaction; it would be naive to assume that efficacy is the sole determinant of
satisfaction, just as Bandura (1997) states that efﬁcacy is not the sole determinant of
human agency. Reason is served to hypothesize that efﬁcacy is a signiﬁcant predictor of
personal satisfaction.

It is also reasonable to assume that other factors that predict efficacy, such aspects
as previous experience, team abilities, education, and social support, would also
contribute to coaching satisfaction. It is imperative to ascertain the possible predictors of
coaching satisfaction, because this construct is somewhat overlooked, yet an important
inﬂuence on motivated behavior of coaches. This motivated behavior that inﬂuences
volunteers to continue to coach youth athletes needs to be understood. Understanding
coaches’ participation motivation is an important issue as researchers examine ways to
maximize the talents of good coaches, reduce coaching turnover, and thus minimize the
resources expended on developing coaches. In addition, maximizing coaches talent and
reducing coaching turnover should provide an improvement to the quality of the athletic
experience for kids, in both fun and skill development. Taking the relevant factors from
both models that were reviewed, the following model was constructed and tested to
examine the sources of coaching efﬁcacy and its mediating inﬂuence on coaching
satisfaction (see Figure 3). In my proposed model, the sources of coaching efﬁcacy that
Feltz et al. (1999) proposed are hypothesized to predict both coaching efficacy and

coaching satisfaction. Coaching efﬁcacy is also a predictor of coaching satisfaction.

12

Purpose

The main purpose of this study is to investigate the relationships between sources

of efficacy information and coaching efficacy with non-professional youth sport coaches

as predicted by the model of Feltz et al. (1999). Additional sources of coaching efﬁcacy -

- age of the coach and perceived skill improvement of the team -- and coaching

satisfaction as an additional efﬁcacy outcome were also investigated.

Hypotheses and Proposed Model

Four research hypotheses are assessed within a proposed mediational model based

on the Feltz et al. (1999) model represented in Figure 3.

1.

Coaching education, coaching experience, playing experience,
perceived ability of the team, perceived skill improvement of the team,
social support, and age of the coach are all significant predictors of
coaching efﬁcacy.

Coaching education, coaching experience, playing experience,
perceived ability of the team, perceived skill improvement. of the team,
social support, and age of the coach are all significant predictors of
satisfaction with coaching.

Coaching efﬁcacy positively predicts satisfaction with coaching.

As illustrated in Figure 3, coaching efficacy is a signiﬁcant mediator of
the sources of coaching efficacy information and coaching satisfaction.

13

 

Sources of Coaching
m
Coaching Education Level
Coaching Experience
Playing Experience
Perceived Ability of Team

Perceived skill
improvement of team

Social Support
Age of the coach

 

 

 

Total Coaching
Efﬁcacy

 

—>

 

 

 

 

 

 

Coaching Satisfaction

 

 

 

 

Figure 3. Hypothesized model of coaching efficacy and coaching satisfaction

14

CHAPTER 2

_ Review of Literature

Coaching is a unique and complex process that includes many roles, contexts and
outcomes. Initial developments in the science of coaching were constructed with the bio-
scientiﬁc and technique enhancement of athletes in mind (Woodman, 1993). Coaching
and the education of coaches were previously presented as a technical and fairly straight-
forward process. Recently, a shift has occurred in the literature, in an attempt to
understand the psychological and sociological development of coaches. Thus, the study
of effective coaches has shifted from an observable science of feedback patterns to the
“art and science” of interpersonal relations, social support, satisfaction, and other
emotional and cognitive precursors and outcomes, in addition to observable science
(Woodman, 1993). Whereas a scientiﬁc approach to coaching undoubtedly has made a
substantial contribution to the enhancement of athletic performance; science by its very
nature has often ignored the reality and relevant issues of personal interaction, which are
inherent within the coaching process (Potrac & Jones, 1999). Consequently, there is a
need to understand this process, but there are signiﬁcant gaps in the existing knowledge
of coaching and the interaction of the athlete, coach and situational context (Cushion &
Jones, 2001). However, Jowett and colleagues have begun an investigation into the
coach-athlete relationship and the interdependence of the affective, cognitive and
behavioral development of both the athlete and coach (J owett, 2003; Jowett & Chaundy,
2004; J owett & Cockerill, 2003). This chapter presents research intended to close these

gaps through the development of conceptual frameworks and research on coaching

15

effectiveness models, the coaching process, coaching education, coaching efficacy, and
coaching and leadership satisfaction.
Coaching Development and Eﬁectiveness Models

The restructuring of coaching models remains a pre-occupation of current
coaching research (e.g., Cote et al., 1995; Horn, 2002). The current coaching
effectiveness models outline the possible conceptual links between athlete learning and
coach effectiveness. An additional model focuses on coaching efﬁcacy and coaching
education (e.g., Feltz et al., 1999) and is covered in the following sections. This study, as
well, is attempting to further the development of the coaching efﬁcacy model (Feltz et al.,
1999) by including additional coaching outcomes that may affect coaching motivation
and coaching satisfaction.
Cote et al. (1995) Coaching Development Model

Cote et al. (1995, see Figure 4) initiated a coaching development model by
examining expert gymnastics coaches and assessing the content of the coaches’
knowledge. This was done in an attempt to understand necessary factors that affect
coaches’ knowledge and ultimately athlete performance. Using a qualitative inductive
analysis process, Céte et al. (1995) found that the coaches’ personal characteristics, the
athletes’ personal characteristics, and contextual or unstable factors (e.g., scoring politics,
parents) contributed to the coaching process. The coaching process includes the coaches’
knowledge of competition, practice and organizational techniques, which in turn lead to
the goal of developing athletes. This coaching model provided an initial step for
developing formal conceptual links between personal characteristics, knowledge, and

performance.

16

 

 

 

Goal: Athlete Development

 

 

 

Coaching Personal Athlete Personal
Characteristics Characteristics

 

 

 

  

 

 

   

Coaching Process
Training
Organization
Competition

 
     

 

 

 

Contextual Factors

 

 

Figure 4. C6te et al. (1995) Coaching Model

Horn (2002 ) Coaching Eﬂectiveness Model

Horn (2002, see Figure l) furthered the development of a working coaching
effectiveness model. As previously mentioned Horn included the factors from the C6te et
al. model, added various important additional factors and expanded the possible
outcomes of coaching behaviors. The most important development in Hon’s Model was
the separation of the coaching process into two boxes (Box 4 and 5). This primary focus
of this model is the supposition that coaches’ cognitions drive their behaviors. Box 3
which is titled “coaches personal characteristics,” includes coaching efﬁcacy. As
discussed earlier, the inclusion of a cognition (e. g., efﬁcacy, as deﬁned by Bandura
(1986) in Social Cognitive Theory) in a personal characteristics box may be incorrect.
Box 4, not Box 3 may be more appropriate to include coaching efﬁcacy in the model as
Box 3 includes expectancies, values, beliefs, and goals, which all are inclusive of

cognitions that affect coaching behaviors. Coaches’ personal characteristics in the Horn

17

model include such categories as playing and coaching experience, critical thinking
skills, and decision making styles. Boxes 3-5 may have signiﬁcant crossover and testing
the conceptual links may reveal a need to be reassess the included categories. As outlined
in Chapter 1, this dissertation assessed some of the links between boxes 2-4. Boxes 5-10
are also important to understanding coaching effectiveness. Box 5 is simply headed
coach behaviors, which in terms of research means leadership style and feedback
patterns. As Horn points out, this limited view of coach behaviors may be due to
measurement concerns. Identifying other types of coaching behaviors has been
problematic as accessibility and accurate measurement have been difﬁcult. Box 6, titled
athlete performance and behavior, is shown as a direct link from box 5 to box 9 (athlete
self-perceptions) and box 10 (athlete motivation). Athletic performance and behavior
could be framed as the end result of the model. Box 7, which includes athlete personal
characteristics, is linked to box 4 and box 8, which is athletes’ perceptions and evaluation
of the coaches’ behavior, which leads to box 9 which is the athletes’ self-perceptions
based upon their perception of the coaches’ behavior and interaction with them as
athletes. Essentially, Hom’s model links sources, such as personal characteristics and
beliefs of athletes and coaches, to behaviors of coaches and the athletes’ cognitive
appraisal of those behaviors, and the athletes’ subsequent behaviors. The area that seems
to be absent is the coaches’ cognitive appraisal of his or her and others’ behaviors.
Ideally, identifying the links between the cognitive appraisals of one’s coaching will
create a better defined coaching effectiveness model. As Feltz, Short, and Sullivan (in

press) noted, the consequences of coaching behavior in Hom’s model focus solely on

'18

athletes’ psychosocial growth and development and not on other coaching factors, such
as coaching commitment and burnout.
Coaching Efﬁcacy

Coaching efficacy, although only one element of the coaching process, provides
signiﬁcant insight into the study of developing effective coaches. Feltz et al. (1999)
defined coaching efficacy as “the extent to which coaches believe they have the capacity
to affect the learning and performance of their athletes” (p.765). Coaching efﬁcacy was
developed from the self-efﬁcacy literature (Bandura, 1986, 1997) and teacher efﬁcacy
literature (Ashton & Webb, 1986; Coldarci, 1992; Gibson & Dembo, 1984; Hoy &
Woolfolk, 1993; Woolfolk-Hoy, 2000), as teachers and coaches have similar end goals
for their students and athletes respectively. One important distinction must be mentioned
between the performance of athletes and the performance of students. Learning is
inherent to both students and athletes in the teacher-student relationship and coach-athlete
relationship, but the actual level of importance placed on performance and performance
measures may be more salient in sport, as performance in sport even at the youth level is
typically a public event.
Development of the Coaching Eﬂicacy Model

Self-efﬁcacy theory background. Bandura (1977) defines self-efﬁcacy as people’s
judgments of their capabilities to organize and execute courses of action required to gain
specific levels of attainment. Self-efﬁcacy is concerned with judgments of what one can
do with whatever skills one possesses, not with the actual skills. Bandura (1977, 1987)
presents self-efficacy as a part of his social cognitive theory, which deﬁnes human

behavior as a triadic, dynamic, and reciprocal interaction between personal factors,

19

previous behavior and the environment (Bandura, 1986). In social cognitive theory,
Bandura asserts several key constructs. The construct we are most concerned with is self-
reﬂective capabilities. Self-reﬂection enables people to analyze their thought processes
and experiences, and adjust their thinking accordingly. This construct is of particular
interest as one of the most important types of self-reﬂection is self-efﬁcacy. An argument
can be made that satisfaction is also self-reﬂective, or at least satisfaction with one’s
activity or career.

According to Bandura (1986, 1997) people develop perceptions about their own
capabilities, feelings, and characteristics that guide their behavior such as what one tries
to achieve, subsequent effort and commitment. These perceptions or efﬁcacious beliefs
guide action in many settings, and to understand sport coaching one must build upon this
understanding from other previously examined ﬁelds. Speciﬁcally, the effects of efﬁcacy
have led to research in various ﬁelds related to coaching, such as teaching. This began
with Denham and Michael (1981) who presented research in teacher efﬁcacy. They
deﬁned teacher efficacy as one’s sense that ideal teaching can bring about positive
changes in a student and teachers’ assessment of their abilities to bring about such
changes.

Teacher efﬁcacy background. There is a signiﬁcant amount of teacher efﬁcacy
literature that has linked high levels of teacher efﬁcacy to positive classroom behaviors
and outcomes. Hoy and Woolfolk (1993) suggest that high levels of efﬁcacy are
correlated with increased feelings that teachers can motivate their students, even the most
difficult of students. Teacher attrition also appears to be inﬂuenced by feelings of

efficacy, with low efﬁcacy teachers turning over more frequently than high efﬁcacy

20

teachers (Stinnet, 1970). Gibson and Dembo (1984) examined the relationship between
teacher efficacy and observable teacher behavior. They found that highly efficacious
teachers tend to have a stronger academic focus in their classrooms with more time spent
on task. On-task classroom activity includes instruction versus non-instructional activities
such as games and art.

Denham and Michael (1981) sought to investigate teacher efﬁcacy and its effect
on teaching effectiveness. After examining the literature and consulting with various
specialists in the ﬁelds of psychology, sociology, and education, they developed a
multidimensional model of teacher efﬁcacy. The researchers posited that a teacher’s
cognitive and affective appraisals have a reciprocal effect on their consequences and
antecedent convictions. The consequences were defined as teacher behaviors and student
outcomes, although teacher outcomes such as commitment or satisfaction were not
included in the model. Antecedents for teaching are similar to antecedents for coaching
efficacy: formal teacher training, previous experience, system variables and personal
variables. Formal teacher training has been found to increase efﬁcacy by giving teachers
the knowledge they feel is essential to teaching. It directly increases their sense of
preparedness (Housego, 1992) and their commitment to continue teaching (Woolfolk-
Hoy, 2000).

Coladarci (1992) defines commitment to teaching as an indicator of a teacher’s
psychological attachment to the profession. Coladarci looked at the relationship between
teacher efﬁcacy and commitment to the profession of teaching. Coladarci administered a
modified version of the Gibson and Dembo (1984) instrument for teacher efﬁcacy. A

school climate assessment appraising perceptions of working conditions for the teachers

21

and teacher personal characteristics was included in the study. Coladarci (1992) found
that personal and general efﬁcacies were strong predictors of commitment to teaching
and that a positive and supportive school climate predicted commitment. This ﬁnding
presents some support for the notion that increased efﬁcacy and social support can slow
professional attrition. In the process of developing coaches, practitioners and researchers
must understand the role that efﬁcacy plays in commitment and satisfaction of coaches.
Feltz et al. (1999) set forth to develop a specific model of coaching efﬁcacy utilizing
similar antecedents and outcomes to those presented in the teacher efﬁcacy literature.
Development and Examination of the F eltz et al. Model (1999).

Feltz et al. (1999) used the multidimensional model of teacher efﬁcacy by
Denham and Michael (1981), Bandura’s (1986) theory of self— efﬁcacy, and the work
done by Park (1992) to inﬂuence the conceptual development of a preliminary model of
coaching efficacy (See Figure 2 in Chapter 1). Speciﬁcally, Feltz et al. (1999) used the
National Standards for Athletic Coaches (N ASPE) and information from Park’s (1992)
exploratory factor analysis to forward the conceptual development of a measure that
included four factors elicited during the conceptual development stage. The factors
included GSE, which is the confidence that coaches have in their ability to coach during
competition and lead their team to successful performance (p. 766). TE entails the belief
coaches have in their ability to instruct the proper skills of the sport and detect errors in
execution of the technical skills. MB is the confidence that coaches have in their ability to
affect the psychological skill and physiological states of their athletes. Finally, CBE is

deﬁned as the confidence coaches have in their ability to inﬂuence the personal

22

development of and positive attitude toward sport in their athletes (Feltz et al. 1999, p.
766).

Feltz et al. (1999) tested their model in a two-phase process utilizing high school
coaches. The ﬁrst phase included the preliminary scale development and an assessment
of the internal factor structure. They were able to develop a 24-item scale that provided a
reliable and valid four-factor ﬁrst-order model, and a single-factor second-order measure
of total coaching efﬁcacy. The second phase included assessing sources and outcomes of
the coaching efﬁcacy model. Feltz et al. (1999) acknowledged that the sources and
outcomes included in this study were not an exhaustive list, but merely a starting point
including sources and outcomes that were conceptually linked to efﬁcacy through the
teacher efﬁcacy and coaching effectiveness literature. Feltz et al. (1999) found that
perceived social support and previous coaching experience provided signiﬁcant efﬁcacy
information to coaches. Previous winning percentage and perceived team ability provided
information but the relationship was moderate. This may be due to the coaches’
realization that they cannot control specific outcomes like winning or the natural ability
of their athletes in a non-recruiting high school situation where they must coach whoever
joins the team. Feltz et al. (1999) also assessed outcomes of coaching efficacy and found
support for higher levels of feedback and praise. Players reported higher satisfaction with
the high-efﬁcacy coaches, and team performance was better for hi gh-efﬁcacy coaches.
This result provokes the idea that performance and coaching efficacy may have a
reciprocal relationship, similar to what has been found with collective efficacy and
performance (Myers, Payment & Feltz, 2004). Feltz et al. (1999) stimulated a provocative

line of research based upon their preliminary model of coaching efficacy with additional

23

leadership outcomes and behaviors, although coaching outcomes were limited to
behaviors. The construction of the coaching efﬁcacy model built upon the teacher
efficacy literature and the work of Park (1992).

Park (1992) developed a measure of coaching confidence that was a precursor to
the coaching efficacy model and utilized the work of Denham and Michael (1981) to
identify antecedents and consequences of coaching conﬁdence. Park’s work presented
antecedent variables including the coaches’ personal factors such as: education in
coaching, playing experience, coaching experience, and coaches’ win-loss records. The
antecedent variables were presented in concert with situational factors such as: teams’
win-loss record, athletes’ skill level and school support. Park posited that the antecedent
variables would predict consequent variables such as team performance and coaching
behaviors with coaching confidence as the mediating factor. Park (1992) reported
ﬁndings that support Feltz et al. (1999), as social support and coaching experience were
the most salient predictors of coaching conﬁdence. Park did not find support for
participation in formal coaching education, previous playing experience, prior win-loss
record, and team ability. Outcomes of coaching conﬁdence were examined and Park did
not find support for team performance as an outcome of coaching conﬁdence, but did
ﬁnd support for conﬁdence predicting coaches’ effort put forth in-season, but not out of
season. The operational definition of effort put forth by Park (1992), which included
hours spent planning and organizing, may not capture the entire construct of effort or
commitment by the coaches. Park (1992) did not ﬁnd support for coaching education as a

predictor variable, but with the recent emergence of coaching education as an important

24

factor in the development of coaches, it is believed that there is a relationship between
coaching efﬁcacy and formal coaching education.

Research on coaching eﬁ‘icacy and coaching education. Despite Park’s (1992)
finding, Malete and Feltz (2000) set out to examine the relationship between coaching
efﬁcacy and coaching education. In their study, high school coaches took part in a 12-
hour coaching education program that included topics on effective instruction and game
strategy, developing personal and social skills, positive coaching, and others. The
coaches who took part were compared to a control group of coaches at the same level
who had not participated in formal coaching education. Malete and Feltz (2000) found
support for the positive effect of coaching education on the coaches’ perceptions of
efﬁcacy with the trained coaches versus the untrained coaches. Although support for GSE
and TE was signiﬁcant, little support was found for motivational efﬁcacy; this could be
due to the content nature of the coaching program and the focus on instructional
techniques and positive coaching. Lee, Malete and Feltz (2002) also examined the
relationship between coaching certiﬁcation and coaching efﬁcacy in coaches in
Singapore. They found support for the positive relationship between coaching experience,
coaching education and coaching efficacy.

One concern with Malete and Feltz (2000) and Lee et al. (2002) is that coaching
knowledge was not exarrrined either prior to or after the coaching education program.
Malete and Feltz (2002) presented a two-week gap between measures, but two weeks
may not be enough time to assess a difference in coaching knowledge or efﬁcacy. These
studies made an assumption that merely attending a coaching education program would

have an effect on efficacy, which did prove to have a measurable effect. However,

25

considering the numerous other factors affecting efﬁcacy, coaching education in and of
itself may not provide as much meaningful information as intended and an increase in
coaching knowledge may be minimal. One other concern with Lee et al. (2003) regarding
the coaching education program utilized in Singapore is that CEP does not address
motivating athletes as a topic until coaches progress past the level of certiﬁcation
examined in this study, which may explain the lack of support found for ME.

Fun g (2002) examined community (i.e., volunteer) coaches in Hong Kong and the
effect of “task familiarity” on coaching efﬁcacy. Task familiarity included: coaching
experience, coaching education and hours spent coaching the previous year. Fun g
reported that mean scores for all four factors of coaching efﬁcacy increased with the level
of coaching education. Findings for the construct of “task familiarity” were in conﬂict
with previous literature. She found that game strategy was the least salient predictor of
coaching efficacy. This may be due to the values of coaches in Hong Kong, or the nature
of volunteer coaches, where game strategy knowledge may not be as valued as CBE and
subsequent behaviors. Fung (2002) examined the perceptions of efﬁcacy of high school
coaches in Hong Kong and conﬁrmed the findings that game strategy was rated the
lowest by coaches and character building was rated the highest. She concluded that
coaching education practitioners should focus more on game strategy during coaching
courses in Hong Kong. However, this solution may not apply to coaches in the United
States.

Kent and Sullivan (2003a) addressed some possible differences in American
coaches and coaches from other countries with coaching education programs by assessing

the differences between American and Canadian coaches and their level of efﬁcacy and

26

organizational commitment. Kent and Sullivan (2003a) propose that American university
coaches are more committed to their coaching position as they may be paid more or
exhibit other professional issues that provide higher levels of satisfaction, including
additional benefits. They also reported ﬁndings that GSE was rated signiﬁcantly higher in
American coaches; this could also be due to the importance placed by Americans on
winning, with game strategy as an important component to winning. In contrast, coaches
in Hong Kong focus on character building (Fung, 2002), which makes sense when
considering the values of most Asian cultures.

Research on outcomes of coaching eﬂicacy. Researchers have examined some of
the possible outcomes of coaching efﬁcacy, such as coaches’ commitment, leadership
style, and beliefs and behaviors of athletes. Kent and Sullivan (2003b) and Sullivan and
Kent (2003) looked at outcomes of coaching efficacy. Kent and Sullivan (2003b)
examined the relationship between coaching efﬁcacy and coaches’ organizational
commitment. There is a difference between commitment to coaching (Raedeke, Granczk
& Warren, 2000) and organizational commitment as deﬁned by Chelladurai (1999).
Chelladurai (1999) deﬁnes organizational commitment as a workers wholehearted
participation in organizational activities, exertion of efforts and performance in those
activities. Raedeke (2004) deﬁnes commitment to coaching as an attraction to and
satisfaction with coaching as a profession. Kent and Sullivan (2003b) studied the
organizational commitment of university coaches. They found support for the second-
order factor of total coaching efﬁcacy predicting affective and normative commitment.
The ﬁndings present an important result as commitment has been linked to satisfaction.

In the study, Kent and Sullivan (2003b) do not indicate if the participants are full-time,

27

part-time or volunteer coaches, as this relationship may have an effect on organizational
commitment, as well as satisfaction with such items as pay or personal recognition,
depending on the role of the coach as full or part-time.

Sullivan and Kent (2003) also studied coaching efficacy as a predictor of
leadership style. They used the Leadership Scale for Sport (LSS), developed by
Chelladurai and Saleh (1980), which may not provide enough leadership style
information, but does provide information on leadership behaviors. Chelladurai’s
multidimensional model of leadership provides some conﬂicting information on
leadership style, behaviors and decision making style. Regardless of the murkiness for the
purpose of the current study, Sullivan and Kent (2003) make a contribution to the
argument. The findings suggest that all factors of coaching efﬁcacy were highly
correlated with teaching and instruction behaviors, and that ME, TE and CBE were
correlated with social support. Sullivan and Kent (2003) did not ﬁnd support for
democratic and autocratic leadership style. This could possibly be explained in that
coaches may use their own personality as a natural leadership style, but positive coaching
behaviors are learned and enacted by conﬁdent coaches. This result also provides support
for Feltz et al. (1999) in that both high school and university coaches with high efficacy
display more praise, encouragement and positive coaching behaviors.

The effect of coaching efﬁcacy on positive coaching behaviors should then
provide information to the athletes and in turn increase player efﬁcacy and team efﬁcacy.
Vargas-Tonsing, Wamers and Feltz (2003) researched the predictiveness of coaching
efﬁcacy on team and player efficacy. In this study collegiate volleyball coaches and

athletes were examined. Coaching efficacy was found to predict collective team efﬁcacy,

28

but not player efficacy (Vargas-Tonsing et al., 2003). This could have been due to the
actual effect of coaches at the collegiate team level and the skill level that should have
been attained prior to reaching the collegiate ranks. The researchers found that ME and
CBE were the strongest predictors of team efficacy. This would be appropriate at the
collegiate level as the relationship a coach has with such highly skilled athletes would
involve motivation and personal development more than instruction (Bloom, Schinke &
Salmela, 1998). Thus, the consequences of coaching efﬁcacy may differ in coaches of
collegiate sports versus high school coaches.

Research on sources of coaching eﬂicacy. Researchers have examined some of
the sources of coaching efficacy, such as coaching experience, playing experience,
success, and social support. Feltz et al. (1999) assessed the sources of coaching efﬁcacy
in high school coaches, and as noted in the previous coaching and coaching efficacy
literature, context can have a very real effect on coaches and athletes. Myers, Tonsing,
and Feltz (2005) examined the relationship between coaching efﬁcacy and its sources,
coaching behaviors, personal characteristics and team variables. Social support, team
ability, previous coaching experience and career success were signiﬁcant sources of
efﬁcacy information. Team ability and career success predicted male coaches' efﬁcacy,
whereas team ability and social support were signiﬁcant predictors of female coaches’
efﬁcacy. Coaching efﬁcacy exerted different inﬂuences on male and female coached
teams (Myers et al. 2005). In men’s teams coaching efficacy predicted efficacy-
enhancing behaviors, team satisfaction and team success. On women’s teams coaching
efﬁcacy only predicted efﬁcacy-enhancing behaviors. This provides relevant information

that differential effects for male and female coaches and teams may occur.

29

Barber (1998) examined the differences in sources of coaching competence by
gender of the coach. Barber found that coaches relied on improvement of athletes as a
source of coaching competence information. Contrary to efﬁcacy research, success and
social support were not signiﬁcantly related to perceptions of coaching competence.
Barber’s (1998) study reported a very small amount of explained variance of the
construct, so the results should be assessed with caution. Marback et al. (2005) also
explored the sources of coaching confidence and difference by gender. Additionally,
Marback et al. (2005) examined the relationship between Feltz et al.’s, (1999) coaching
efﬁcacy model and Barber’s (1998) coaching competence construct. Marback et al.
(2005) found that male coaches’ perceptions of coaching efﬁcacy was higher on GSE and
ME and lower than females’ perception of CBE. The sources of coaching efﬁcacy found
to have a signiﬁcant relationship in this study included coaching experience, gender, as
well as Barber’s addition of social processes (i.e., feedback from athletes, affect of
athletes) that may be likened to Feltz et al.’s (1999) social support measure. Coaching
experience and social support have been consistent predictors of coaching efficacy.
Although playing experience has conceptual links to perceptions of efﬁcacy, it has not
been studied extensively in the coaching efﬁcacy literature.

One study that has examined playing experience as a source of coaching efficacy
is Sullivan et al. (in press). In this study, the researchers compared the predictive strength
of playing and coaching experience as sources of efﬁcacy information. Sullivan et al.
found that coaching experience provided signiﬁcant information to all four ﬁrst—order
factors of coaching efﬁcacy and playing experience only added predictive information to

game strategy efficacy. The sample was comprised of curling coaches. The sport of

30

curling at the competitive level is generally considered a strategy game, and does not
typically include intricate technical components or major motivational and emotional
components. Therefore, playing experience may have a signiﬁcant effect on the success
of curling coaches, and is very relevant to efﬁcacy information of curling coaches.
Sullivan et al. (in press) provide information to consider coaching experience and playing
experience as sources of coaching efﬁcacy. As studies of coaching efﬁcacy have
provided ample evidence for predictors and speciﬁc outcomes, Feltz et al. (1999) and
Sullivan, Paiement, Brachlow and Bagnell (2005) asserted that additional outcomes may
be relevant to coaching efficacy. In the present study, coaching satisfaction is one such
outcome that has been posited to have a relationship with coaching efﬁcacy.
Coaching Process

As discussed previously, the coaching process is not only a scientiﬁc one but also
a social one (Jones, Armour, & Potrac, 2002). As such, social activities involve
interaction between people regardless of gender, race, class, values and experience.
Accordingly, there has been increasing interest among researchers of the sociocultural
and contextual factors in investigations on the dynamic coaching process as indicated by
Horn (2002). Additionally, organizational climate is also a social factor in the
development of a coach. Within the framework of Horn’s model of coaching
effectiveness, a reasonable question to ask is how does the development of effective
coaches occur and where does development ﬁt into the model.

Development as a coach involves numerous factors including communication
skills, feedback patterns, and instructional techniques, each of which interacts in a social

environment. Martens and Gould (1979) examined volunteer coaches’ orientation

31

towards coaching. Their results revealed that coaches do understand that coaching and
youth sport are social processes, as coaches rated socialization outcomes as the most
important for youth sport. One caveat regarding the results of this study is that youth
sport has become “professionalized” and specialized in the past 25 years; therefore, the
results may not be indicative of the attitudes of today’s coaches. Social processes are still
of great interest in the development of coaches and athletes. Martens and Gould’s (1979)
study provided a number of pertinent ﬁndings. Namely, coaches with less experience
placed more emphasis on fun, and coaches with more formal training, experience, and a
career in education placed more emphasis on winning.

This result may be of concern as development of coaches includes formal
education and experience (i.e., mentorships), which should translate into positive
development of the athletes, but may refocus coaches on success outcomes and not skill
and personal development. Even legendary coaches focusmore on the development of
the athletes through instruction and drilling. Tharp and Gallimore (1978) observed
legendary UCLA basketball coach John Wooden to study his teaching technique and
athlete interaction skills. They outlined his coaching background to understand the
pyramid of success as presented by Wooden. Wooden (2004) reports that the pyramid of
success took him 15 years to conceptualize, organize, and complete and it mirrored his
coaching development. Tharp and Gallimore (1978) simply observed his coaching style,
which had been honed over 45 years. They observed Wooden providing instruction, error
correction/reinstruction, and encouragement (i.e., hustles) nearly 70% of the time, which
all relate to social interactions and teaching, the crux of his pyramid of success. In

developing coaches’ interaction with athletes, understanding how best to instruct and

32

having conﬁdence in one’s teaching technique may have important consequences to
athlete development.

Gallimore and Tharp (2004) reexamined their earlier data and enhanced the
previous study retrospectively. They found that in teaching, Coach Wooden planned
every interaction prior to presenting anything to the athletes. The results of these two
studies may speak to the importance of teaching technique efﬁcacy in developing
athletes. Although the other factors are important, if a coach of this stature, coaching elite
athletes spends 70% of his time teaching, then technique efﬁcacy and teaching coaches
how to teach may be a more relevant part of the coaching development process than is
presented in most coaching education programs.

Sage (1989) examined the entry of coaches into coaching and found that novice
coaches used personal experience and informal knowledge gathering in their teaching and
athlete development skills. Rushall (2004) warns against this type of coach development,
or as he cites, belief-based coaching. He encourages evidence-based coaching, because
utilizing knowledge learned only from observing leads to reintroduction of skills and
methods that may be incorrect and outdated. Rushall (2004) supports the development of
coaches through evidence-based training rather than experiential training, although there
is a signiﬁcant amount of research that supports the use of both evidence-based coaching
education and experience-based mentorships (Gilbert & Trude], 2001). Douge and Hastie
(1993) argue that effective coaching comes from knowledge, as well as self-reﬂection on
ones’ skills and interactions with others. They also cite the need for coaches to observe,

analyze, and modify their coaching to ﬁt the specific situation; this is typically learned in

33

action, therefore providing support for an experience-based component to coach
development.

Additionally, Bloom et al. (1998) contrast the communication skills needed by
novice and elite coaches. The skills needed by novice coaches are more basic, such as the
principles of positive feedback, and can be instructed in a formal coaching education
environment. For elite level coaches, communication skills need to be learned and
developed over time because the needs and coach-athlete relationships change to a
collegial advice seeking relationship at the elite levels. In constructing the beliefs of
youth coaches, it may be important to provide more interaction, both formal and
informal. Wilcox and Trude] (1998) examined how youth coaches construct their beliefs
about the important aspects of coaching. Their results revealed that winning and player
development were of somewhat equal importance to coaches, but character building and
sportsmanship were considerably less important and they suggest may be somewhat
falsely elevated in other research studies.

Abraham and Collins (1998) provide a provocative statement about research in
coach development. They posit the same concerns that Rushall (2004) presented, that
“accepted” knowledge is masked as expertise and erroneous information is promulgated
to new coaches. They also call for the inclusion of contextual information about the
coaches and the situation, as detailed in Horn’s (2002) model. It may be prudent to coach
development to separate sport and coaching knowledge as has been done in some
coaching education programs. The Canadian Association of Coaching provides all three
areas: sport-specific knowledge competency, general coaching competency, and formal

mentoring to provide a more thorough knowledge base for developing coaches. Abraham

34

and Collins (1998) also discuss the need for content knowledge, which is the sport
speciﬁc knowledge such as the specific skills and strategies needed for success in
whichever sport the coach is involved. It is also necessary to encourage the understanding
of process knowledge, which are basic teaching skills or pedagogical content, so coaches
can effectively instruct the youth athletes.

Process knowledge may be more easily gained through observation of coaches
and personal experience. Gould, Giannini, Krane and Hodge (1990) cite experience and
observation as important sources of process knowledge for coaches. Gilbert and Trudel
(2001) examined directly how coaches learn to coach. They imply that experience is a
very important part of coach development and suggest that coaching education use an
issue-based approach, which would provide practical knowledge to the learning process.
Additionally, they provide support for a reﬂective environment in coaching development
possibly with mentors or peers because coaches are already involved in personal
reﬂection. In the development of coaches, one ﬁnal skill that should be discussed is how
coaches frame their role as a coach within the athlete development cycle. Gilbert and
Trudel (2004) suggest that tacit role framing be taught in coaching education because
coaches will be more effective in their role if it is framed correctly during their
development as coaches. As coaches continue to develop their coaching skills through
education and endure experiences in which they and their athletes improve and
experience success, then their personal or “coaching” efficacy begins to increase (Feltz et

al., 1999; Woolfolk-Hoy, 2000).

35

Coaching Education

As children increasingly joined organized sports teams, the need to provide
training for coaches increased (Martens, 1984). As athletes progress through their
developmental stages, coaches must be prepared to provide adequate instruction to
athletes in an attempt to continue the development cycle. It is simply not enough to
expect volunteer coaches to know how to coach based upon limited playing experience or
limited understanding of pedagogical principles. Teachers are required to have a college
degree, yet we allow youth sport coaches to simply volunteer, even though the level of
influence can be similar. An argument could be made that coaches have enough time with
the athletes to have a significant inﬂuential effect, either positive or negative, on youth
athletes. Therefore, coaching education programs developed in response to this need for
training of coaches, such as Coaching Effectiveness Training (CET: Smith, Smoll, &
Curtis, 1979), American Sport Education Program (ASEP: Martens, 2004), Program for
Athletic Coaches Education (PACE: Seefeldt & Brown, 1990), the National Youth Sports
Coaches Association (NYSCA: 2003), and the National Coaches Certification Program
(NCCP) in Canada. One concern is the level of motivation that coaches have for
attending coaching education programs
Coaching Preparation Motives

Coaching education should be a standard requirement because many coaches do
not have any professional preparation prior to beginning coaching. Stewart and Sweet
(1992) examined the professional preparation of 288 high school coaches. They found
that 82% of coaches participated for “love of the kids” or “personal enjoyment”, but less

than 50% had any formal coursework in any topic related to coaching. While the

36

participation motives of coaches are encouraging to organizers of youth sport, the lack of
coaching preparation is discouraging. Houseworth, Davis and Dobbs (1990) indicated
that unprepared coaches lacked sufﬁcient knowledge in key areas of coaching and putting
competent and conﬁdent coaches into leadership positions should be more important than
promoting coaches that are interested for “personal satisfaction”. Weiss, Barber, Sisley
and Ebbeck (1991) examined female coaches who attended a coaching workshop then
completed a season-long internship. Although they found that 25% of the coaches had
low perceived coaching competence even after the internship, they did notice an increase
of conﬁdence in communication (89.7%) and motivation skills, as well as teaching skills,
knowledge of the game and leadership skills. Female coaches rated lack of sport-skill
knowledge as their greatest weakness, which contrasts the ﬁndings of Houseworth et al.
(1990) who did not find a difference between sexes and sport-specific knowledge.
F omtal Coaching Education Programs

Smith, Smoll and Curtis (1979) developed a coaching effectiveness training
program for little league baseball coaches based upon Bandura’s (1977) social-cognitive
theory. Smith et al. (1979) pioneered the vision of large scale improvement to youth
coaching through speciﬁc education. Their program was based upon teaching coaches
how to provide positive, meaningful instruction and continuous encouragement and limit
punishment and negative feedback. Smith et al. (1977) found that children evaluated the
trained coaches more positively than untrained coaches and that there was no difference
in the win-loss success of trained and untrained coaches, suggesting that on-field success
would not affect the evaluations. They also found that children who played for trained

coaches had higher post-season self-esteem, and children with lower pre-season self-

37

esteem were more attracted to trained coaches. This study did not measure whether the
athletes felt they improved, which is one factor in athlete development, but did indicate
that positive behavior by the coach increased attraction to the coach and a return to play
the following year. Support for coaching education began to increase during the decade
following this study.

Martens (2004) recognized the need for widespread coaches’ education and
developed ASEP, based upon similar principles of coaching, such as positive
reinforcement, encouragement, and sport knowledge. Martens did incorporate a more
broadly presented program to, include the needs for skill development. As Feltz, Short &
Sullivan (in press) noted, other programs, such as PACE, NYSCA, and NCCP are
generally similar and cover topics on legal responsibilities, prevention and care of athletic
injuries, organizing practices, motivating athletes, and sport-speciﬁc technical and
tactical skills. Their program lengths vary from 7 to 12 hours.

Problems with Coaching Education Programs

Houseworth et al. (1990) examined the features of these widely accepted
coaching education programs (e.g., ASEP, PACE, NYSCA, and NCCP). They
determined at that time that none of the programs provided direct development of, and
testing for, high school coaches. Houseworth et al. (1990) also examined the needs of
high school coaches themselves. The researchers indicated that coaches felt most
knowledgeable with sport speciﬁc skill, game strategy and teaching technique, and less
knowledgeable about motivation, psychology, injury prevention and physical training.
Coaches wanted information about topics on which they felt less knowledgeable.

Coaches in this study believed that coaching education should be a requirement prior to

38

any coaching assignment. Although coaches agreed that coaching education was
important, the authors acknowledged that actually getting coaches to participate has been
a long standing problem unless the program is mandatory.

It is a common conception that coaching education and coaching certiﬁcation are
one and the same. It would seem to reason that coaching education is the act of providing
resources and information to coaches to improve their knowledge. Coaching certiﬁcation,
on the other hand, should be a measure of minimal content or experiential knowledge that
must be possessed prior to beginning coaching; this can be identiﬁed by examination or
other minimum standard criteria. Campbell (1993) examined coaching education in
various countries and determined that coaching education takes on many forms
dependent upon the culture, politics, traditions and goals of the country. She presented a
thorough examination of coaching standards determined by certain European sporting
bodies and concluded that sport-speciﬁc knowledge, performance-related core knowledge
(i.e., motivation, psychology) and practical experience are key components to coaching
education. She also suggested that coaching certification is more important than general
coaching education, as minimum standards of knowledge must be attained and
recertification keeps coaches up to date on skills and information.

Critical Evaluation of Coaching Education Programs

In response to Campbell (1993) and sensing a need to better understand the
applied work in coaching education, Gilbert and Trudel (1999) developed a strategy to
evaluate coaching education programs. Their investigation utilized a case study of one
coach attending a single coaching seminar, which provides a weakness for generalizing to

other programs, but the information gleaned may be useful in developing formal

39

evaluations for coaching education. They determined that a thorough and well developed
national coaching education curriculum was not presented as intended and no new
knowledge was gained. Gilbert and Trudel (1999) suggest that one must consider the
coaches’ pre-existing knowledge base and the delivery of the material in developing
coaching education. If the coaching education program is not properly conducted or
delivered or if the information is repetitive or too elementary it may not provide efﬁcacy
information or any contribution to feelings of competence.

Building upon the Gilbert and Trudel (1999) study and Weiss et al. (1991) study,
Cushion, Armour and Jones (2003) argue that coaching education programs are
somewhat murky in their actual effectiveness in increasing coaching knowledge in the
application to the “ﬁeldwork” of coaching. Therefore, Cushion et al. (2003) indicate that
it may be more appropriate to build coaching education around workshops and formal
mentoring programs to maximize the effect of coaching education and increase levels of
conﬁdence and perceived competence prior to coaching one’s own team. They argue that
a workshop/mentoring program would provide praxis for coaches by combining coaching
knowledge, theory and practice to their repertoire prior to the responsibility of developing
athletes. Weirsma and Sherman (2005) followed Houseworth et al. (1990) with an
updated assessment of volunteer coaches’ beliefs about coaching certiﬁcation. Although
Cushion et al.’s suggestions are sound; Weirsma and Sherman provide some information
about barriers when addressing volunteer coaches. Their findings suggest that volunteer
coaches are interested in the content areas of psychological development, managerial
aspects of coaching and skill development of athletes. The coaches discussed barriers to

formal coaching education, such as time constraints and the transient nature of volunteer

40

coaches. Themes that arose from the volunteer coaches were activities such as: round
table discussions about problems that occur, mentoring relationships, and self-study.

One topic that was discussed in Weirsma and Sherman (2005) and may need to be
addressed in general coaching education programs is age-speciﬁc and level-speciﬁc
training sessions. Sullivan et al. (in press) have also addressed this issue and the difﬁculty
with varying contexts that coaches face in participating in coaching education.

Coaching Satisfaction

Satisfaction with coaching has largely been ignored in the sport psychology
literature. The outcome of coaching satisfaction has not been included in any of the
theories forwarded in the sport psychology or sport leadership literature. Chelladurai and
Ogasawara (2003) developed a measure of coaching satisfaction recently. By using
questionnaires from the job satisfaction literature and adapting the Reimer and
Chelladurai (1998) Athlete Satisfaction Questionnaire, Chelladurai and Ogasawara
forwarded the construct of coaching satisfaction. The primary problem with their measure
is the limited use, as the measure was intended for collegiate and professional coaches.
The categories that were outlined in their study included satisfaction with pay,
supervision, benefits, etc. Although a similar deﬁnition for satisfaction was used for their
study, a very different construct emerged and proved to be a signiﬁcant contrast to the
current study. Regardless, Chelladurai and Ogasawara (2003) found that the highest rated
categories were process-oriented and were consistent among Division I, III, and Japanese
college coaches. Categories such as coaching job, autonomy, and team performance were
rated the highest. Content-oriented categories such as pay, job security, and facilities

were rated the lowest. This may be an example of Herzberg et al’s theory (1959) that

41

process-oriented categories are actual measures of satisfaction, while the content-oriented
categories are actual measures of dissatisfaction.

Satisfaction is deﬁned as anything that brings about a happy feeling or the
fulﬁllment of a need, appetite or desire (Webster, 2005). Satisfaction, whether it is job
satisfaction, personal satisfaction or satisfaction with those who affect your daily
activities, can have a signiﬁcant effect on your motivation to work or perform. There is a
paucity of research on satisfaction with coaching and the limited research that has been
completed is derived from the theoretical background of organizational psychology and
job satisfaction (i.e., Chelladurai & Ogasawara, 2003). While relevant to this study, job
satisfaction literature may not adequately explain satisfaction and motivation of non-
professional coaches, due to the focus on satisfaction with pay, beneﬁts, supervision and
other extrinsic factors. I propose in this study that motivated behavior of volunteer
coaches may ﬁnd its roots intrinsically, with such constructs as coaching efﬁcacy and
satisfaction. Farrell, Johnston & Twynam (1998) examined the motivation of volunteer
coaches in sport and the relationship with satisfaction. They found that purposive
motivation was the most signiﬁcant contributor to motivation as a volunteer. Purposive
motivation is operationally deﬁned as the desire to do something useful and give back to
the community, which is a similar reason found in studying motives of youth sport
coaches. They found that volunteer satisfaction was related to organizational behavior
and support. A key component to satisfaction may be perceived social support, which has
been linked to such outcomes of coaching and leadership as satisfaction, burnout, and

commitment.

42

Social Support and Satisfaction

Coaches derive feedback from parents, athletes, the organizations they represent
and the community as a form of social support, either positive or negative. Coaches may
perceive a significant amount of pressure and stress due to the level of responsibility they
have to the athletes, parents, and organization they represent. There is a considerable
amount of literature that has examined the relationship between social support and
positive feelings and cognitions. In contrast, feeling a lack of support may cause stress
and a lower level of satisfaction with the activity. While parental support has been
hypothesized to be an important predictor of coaching satisfaction, the support of the
organization may also be an important factor in youth sports. This may be due to the
responsibility that a coach has to answer to the organizational board, and the organization
is responsible for important decisions about the team, including scheduling. In youth
sports, the organization has a similar role to the athletic director in the aforementioned
coaching efficacy studies. In many situations social support also comes from signiﬁcant
others. In youth sport, coaches have numerous signiﬁcant others, namely: the athletes, the
parents, the community and the youth organization they represent.

Taylor (1992) first discussed the main sources of stress for coaches, speciﬁcally:
interactions with fans, media, and parents. Additionally, he indicted that a lack of support
in any area of the coaches’ social network could cause an increase in stress level. In
reducing stress of the coach, Taylor (1992) indicates that support from the athletes may
play a significant role. In addition to Taylor’s premise, Cohen and Wills (1985) purport
that social support is beneﬁcial regardless of level of stress by providing positive affect,

the perception of stability and a sense of self-worth. Reimer and Chelladurai (1995) also

43

showed a positive relationship between social support from the coach and athlete
satisfaction. As presented earlier, at higher levels of competition, with a mutually
respectful environment, a reciprocal relationship between support and satisfaction may
occur with the coach and athletes. Support from the athletes may be an important part of
satisfaction, but support from the parents can have a signiﬁcant impact as well. Strean
(1995) quotes a coach as indicating that, “the hardest part of coaching is the parents, you
never please them, never” (p. 27). Also noted by Strean (1995), the coach discussed the
support of the good parents, “the 90% you never talk about, that 90% are good supportive
parents.”

Related to satisfaction, Kelley and Gill (1993) examined the predictors of burnout
in coaches. They found that social support was a strong predictor of burnout in coaches,
among other predictors such as win/loss record. Martin, Kelley and Eklund (1999) used
the Kelley and Gill (1993) study in developing a model based on stress and burnout in
athletic directors. Their findings conﬂicted with Kelley and Gill as they did not find
social support to be a signiﬁcant predictor of burnout. This may be due to the nature of
the hours and interaction difference between coaches (Kelley & Gill, 1993) and athletic
directors (Martin et al., 1999). Social support may be more vital to coaches as they deal
with athletes and parents on a daily basis. Athletic directors do much of their work behind
the scenes, and social support may not be as relevant to stress and burnout. Reimer and
Toon (2001) also measured social support, but they focused on the coach-athlete
relationship. They tested the athlete satisfaction questionnaire (ASQ), and validated the
result that positive social support behavior was predictive of higher athlete satisfaction

ratings, although gender moderated the effect. Davis (2002) provided some new insight

into social support; he examined collegiate athletic director behaviors and coaches’
ratings of satisfaction with their job. His ﬁndings revealed that organizational support
was a strong predictor of coaches’ satisfaction. Athletic director’s personal characteristics
did not produce a signiﬁcant effect on coaches’ satisfaction. The results outline a fairly
compelling argument that social support has an effect on one’s level of stress and
satisfaction in particular situations. Finally, in assessing which type of social support (i.e.,
social pressure) or lack of social support leads to the highest level of stress, Scantling and
Lackey (2005) examined the relationship between coaching turnover and stress through
four decades in high school sports. They indicated that pressure and stress was rated
higher on coaches in the 2000’s than in the previous three decades, which would make
social support even more important to satisfaction and retention of coaches now.
Scantling and Lackey also indicated that for the past two decades, parents of athletes
placed the most pressure on coaches, followed by the community/fans, and the
organization. Athletes were rated last among sources of pressure for coaches. This
finding may be relevant if coaches’ efﬁcacy beliefs are inﬂuenced more strongly by
positive social support and not sources of pressure or perceived threat. Coaching by
nature is a stressful environment, and strong leaders learn how to diffuse stress and
channel the social support they need to be successful.
Leadership and Satisfaction

Satisfaction as an outcome has been utilized in various leadership studies based
on the multidimensional model of leadership (Chelladurai, 1984; Chelladurai et al., 1988;
Home & Carron, 1985; Riemer & Chelladurai, 1995; Riemer & Toon, 2001). In

Chelladurai’s model, leader behaviors are suggested to be antecedents of member

45

satisfaction. The model proposes that the discrepancy between athletes’ perceived and
preferred leadership style would impact their level of satisfaction. Chelladurai (1984)
found that divergence in leadership behavior for athletes in various sports was associated
with three measures of satisfaction: satisfaction with performance, satisfaction with
leadership, and satisfaction with overall involvement. While coaches may not provide a
rating for satisfaction with leadership as they are the leader, satisfaction with
performance and overall involvement may be a relevant measure of satisfaction for the
coach. Horne and Carron (1985) studied the compatibility in coach-athlete dyads in
Canadian university volleyball, basketball, track and ﬁeld, and swimming athletes. They
found that lower divergence between preferred and perceived training and instruction,
social support, and rewarding leadership behaviors had higher levels of satisfaction. Also,
lower discrepancies between athletes’ perceived and preferred leadership behaviors led to
increased success. These ﬁndings were important because success has been found to be
associated with high athlete satisfaction.

Weiss and Friedrichs (1986) explored the inﬂuence of leader behaviors, coach
attributes, and institutional variables on performance and satisfaction of collegiate
basketball teams. They found that perceptions of all leader behavior dimensions were
predictive of team and individual satisfaction scores, and democratic behavior and social
support were the best forecasters of individual satisfaction. The link between social
support and satisfaction has been developed and it would serve to reason that coaches
would react to positive social support in the same way as athletes. Social support as one
predictor to satisfaction makes sense, but understanding the relationship of satisfaction on

other factors such as burnout, commitment and retention should be examined.

46

Job Satisfaction

Job satisfaction has been deﬁned as the feelings a worker has about his or her job
or job experiences in relation to previous experiences, current expectations or available
alternatives (Balzer et al., 1997). Job satisfaction is generally explained by either content
or process theories. Content theories are based on various specific measurable factors
such as pay, co-worker relationships, and supervision, which inﬂuence job satisfaction.
Process theories consider the process by which variables, such as expectancies, values
and needs, relate with the job to produce job satisfaction. Process theories represent the
interaction between these variables and their relationship to job satisfaction. Process
theories of satisfaction seem to relate better to satisfaction with coaching in volunteer or
non-professional settings. Additionally, expectancies, values and needs are also explained
in Hom’s (2002) model of coaching effectiveness.

Job satisfaction, as it relates to coaching, is an important factor given the
relationship found between job satisfaction and retention. There is a litany of research
that examines the relationship between satisfaction and turnover intentions of coaches.
Additionally, turnover of coaches has typically revealed a performance decrement in
teams. Dobson, Audas and Goddard (2002) examined the performance of British soccer
teams and coaching changes over a 25-year period. They concluded that team
performance suffers after a coaching change. Jacobs and Singell (1993) found similar
results in assessing turnover of managers in major league baseball in that teams generally
performed worse after a coaching change. Reasons for the performance decrement were
not examined, but turnover did provide decrement to the athlete development and

performance model. Goines (1997) also examined team performance after a turnover in

47

coaching in the NFL from 1984 to 1994. Goines’s study confirmed the Jacobs and Singell
(1993) study results that team performance decreases when coaches turnover. This
provides evidence for the importance of retention in the coaching ranks.

Sagas and Batista (2001) studied male and female collegiate coaches and their
turnover intentions. They found that there was no difference in satisfaction by sex, but
did report that as job satisfaction increased, intent to leave coaching decreased. Hart,
Hasbrook and Mathes (1986) examined the reasons for female coaches leaving the
coaching profession. They cite reasons such as value orientation toward coaching, or that
the cost does not equal the benefits. They did not find adequate results based upon their
hypothesis but allude to the idea that it was not ineffectiveness, role conﬂict or
discrimination. They did not examine coaches’ cognitions about the coaching experience
such as attraction or satisfaction.

Weiss and Stevens (1993) did assess the motivation and attrition of female
coaches at the high school level through the framework of social exchange theory. They
distinguished the motivation to coach with beneﬁts, costs and satisfaction with coaching.
Weiss and Stevens (1993) reported ﬁndings that satisfaction was related to retention of
female coaches. Cunningham and Sagas (2003) also examined the turnover intentions of
coaches. They presented results that indicated that inclusivity is a significant reason for
turnover intentions. Inclusivity is measured as a coaching cognition related to the
coaches’ relationship to others in the athletic department. Finally, Surujlal, Singh and
Hollander (2005) examined coaches’ turnover intentions and commitment based upon
ratings of job satisfaction. They reported that a higher level of job satisfaction was

positively related to commitment and negatively related to turnover intentions. Smucker

48

and Whisenant (2005) examined the satisfaction of coaches by comparing content- and
process-based approaches. They reported findings that suggest that coaches are more
satisfied with process-based approaches due to self-referent comparison and ﬁnd less
satisfaction with content approaches (i.e., pay) due to referent comparison to other
coaches. Thus, the coaches lack investment due to comparison to others in the
organization.
Work Motivation

Maehr and Braskamp (1986) forwarded a theory of work motivation, dubbed
personal investment theory. They describe its effect in organizational settings, especially
the function among adults in work setting with a task incentive. They conclude that
personal investment increases by knowing something about the cultural facets of an
organization, and can predict an employee’s job satisfaction and commitment. Further,
Maehr and Braskamp (1986) determined that motivation has something to do with the
inner energies of a person, and motivation drives and directs human behavior. Therefore,
personal investment theory is generally concerned with how people choose to invest their
energy, talent, and time in specific activities. Personal investment theory is a social
cognitive theory that emphasizes the role played by social contexts in shaping motivation
to participate. Additionally, the theory emphasizes the subjective meaning of situations as
framed by one’s belief systems, perceptions, goals and values, just as in Hom’s model
(2002). Maehr and Braskamp (1986) do consider the concept of motivation as it relates to
obtaining a meaningful and satisfying existence. No single inﬂuence alone will determine

a person’s motivation and various extrinsic inﬂuences may be affecting personal

49

motivation (Maehr & Braskamp, 1986). A satisfying experience then should lead to
greater satisfaction and higher levels of commitment.
Outcomes of Job Satisfaction

As previously mentioned, some of the related outcomes of satisfaction may
include both positive and negative outcomes, such as commitment and burnout
respectively. Raedeke (1997) ﬁrst examined burnout as a function of commitment and
satisfaction. He began by examining the levels of enjoyment, entrapment and
commitment of swimmers. His ﬁndings suggest that feelings of entrapment lead to higher
levels of burnout and less commitment. Raedeke, Granzyk, and Warren (2000) then
forwarded the same theoretical model to coaches. They reported results that include
higher levels of satisfaction indicate high levels of coaching commitment; high perceived
entrapment feelings led to higher levels of burnout. Also, the greater perceived level of
personal benefits and low costs correlated signiﬁcantly with satisfaction. Raedeke,
Warren and Granzyk (2002) followed the previous studies with a comparison of
commitment, satisfaction and coaching turnover between current and former club
swimming coaches. They determined that commitment and perceived beneﬁts were
signiﬁcantly related to satisfaction in coaches. They also examined the differences
between former and current coaches and determined that satisfaction provided a
significant difference between the two groups, although they reported that both current
and former coaches rated satisfaction highly. Many coaches indicated that coaching did
not meet their personal needs.

Identifying burnout in coaches from the sport commitment model was established

by Raedeke (2004) as a follow-up to his previous work. He reported that satisﬁed

50

coaches continued to experience attraction to coaching, and coaches that rated lower
levels of satisfaction also increased in their level of feelings of entrapment and
exhaustion. Therefore, examining a coach’s level of satisfaction and attraction to
coaching may be an important part of evaluating coaches, as it seems that positive and
negative affect and cognitions do not change with time, unless another event is enacted,
they only become stronger (Raedeke, 2004; Rushall, 2004). This may also have an effect
on other cognitions such as efﬁcacy.

Haugen and Short (2004) studied the relationship between coaching efficacy and
burnout in high school basketball coaches. Their findings suggest that high efﬁcacy
coaches are less likely than lower efficacy coaches to suffer from burnout by the end of
the season. In discussing coaching efﬁcacy, efﬁcacy and satisfaction have not previously
been linked, but Cunningham, Sagas and Ashley (2003) did study the effect of coaching
self-efficacy on turnover intentions, which has been related to satisfaction. They did not
ﬁnd support for their study, as efﬁcacy had a very small relationship with turnover
intentions. They postulate that other reasons may affect turnover intentions, such as
satisfaction and commitment, which they did not measure in their study. J aros (1997) did
examine these measures and found support for satisfaction and commitment having a
negative relationship with turnover intentions in non-sport organizations.

Summary

Coaching is a complex task that is affected by numerous factors, such as personal
characteristics, cognitions, values, behavior and social interactions. The relationship of
these factors affects both the development of coaches and the development of athletes. It

is of the utmost importance to understand participation motives of both coaches and

51

athletes. Athletes have garnered much of the attention in sport literature. The motivation
to coach needs to be thoroughly understood and satisfaction is one area of motivation that
has been overlooked. The literature alludes to certain predictors of satisfaction in other
areas of sport and organizations. This research should be adapted and applied to the sport
context more speciﬁcally. If the majority of coaches are volunteers, then understanding
the factors that affect their participation and retention should be evaluated. It does
become imperative as the role of a coach is to further the development of our youth as

athletes and people.

52

CHAPTER 3

Method

Study Design and Participants

This study was conducted using a survey questionnaire methodology and was
quantitative in nature. Participants for this study were 512 (496 male, 16 female) amateur
ice hockey coaches attending USA Hockey coaching certiﬁcation clinics in the
Northeastern and Midwestern United States. 560 coaches were provided questionnaires at
the clinics, 23 exercised their right to refuse participation. 537 coaches ﬁlled out surveys,
with 25 eliminated due to incomplete questionnaires. Tables 1-4 summarize the
descriptive statistics for the participating coaches. Participants ranged in age from 17 to
65 years old (11:37.93, SD=7.87). More than 97% of the coaches were white. Seventy-
seven percent of the coaches coached athletes younger than 14 years of age, 3.9%
coached athletes older than 18 years of age. The sample included 110 head coaches,
while 402 identiﬁed themselves currently as assistant coaches. The mean years of
coaching experience as a head coach was 1.09 years (SD=2.42) and experience as an
assistant was 2.45 years (SD: 2.52), with 67.5% of coaches with no experience as a head
coach and 46.1% having one year or less as an assistant. The average length of the
coaches’ previous total playing experience was 6.21 years, and encompassed youth
through professional playing experience. This includes 40% of coaches with no playing
experience at all, 40% reaching the high school level, 12.5 % playing collegiate hockey,
and 1.5% playing professionally. An unexpected ﬁnding in the data indicated that 14.2%
of the participants had no previous playing or coaching experience. The sample included

242 coaches who were USA Hockey Level 1 (initiation level) coaches, 129 who had

53

earned their Level 2 (introductory) certiﬁcate, 140 who were Level 3 (intermediate)

coaches.

Table 1

Means, Standard Deviations and Range for Age, Years of Coaching and Playing

Experience for the Participants

 

 

Variables (N = 512) Mean SD Range
Age of Coach 37.93 7.87 17-65
Total years of coaching experience 3.54 3.87 0-32
Total years of playing experience 6.21 5.96 0-23
Years as Head Coach 1.09 2.42 0-20
Years as Assistant Coach 2.45 2.53 0-21
Years played youth hockey 4.28 4.47 0-17
Years played high school hockey 1.19 1.60 0-5
Years played junior hockey .25 .76 0-4
Years played Major junior hockey .02 .25 0-4
Years played college hockey .31 .94 0-5
Years played professional hockey .04 .41 0-7

 

Table 2

Frequency of Age Level of Teams Coached by Participants

 

 

Age group coached (N =5 1 2 ) Frequency Pct%
Under-10 160 32.1
Under- 12 122 23.5
Under-l4 111 21.5
Under- 16 67 12.7
Under-18 32 6.3
Over-18 20 3 .9

 

54

Table 3

Frequency Table for Sex and Ethnicity

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Sex (N=512) Male Pct. Male Female.
Team Coached 477 92.7 35
Coach 496 96.5 16
Ethnicity (N=512) Frequency Percent
White 501 97.5
African American 1 .2
Native North American 4 .8
Asian-American 2 .5
Hispanic 2 .5
Other 2 .5
Table 4
Coaching Experience
Coaching Position Frequency Percent
Head Coach 110 23.0
Assistant Coach 402 77.0
Total 512 100.0
Experience as Head Coach Frequency Percent
None 346 67.7
1-2 years 94 18.3
3-5 years 44 8.7
6-10 years 21 4.2
11+ years 6 1.1
Experience as Assistant Frequency Percent
None 84 16.4
1-2 years 249 48.9
3-5 years 132 25.6
6-10 years 41 8.1
11+ years 6 1.1
Coaching Education Level Frequency Percent
Level 1- Initiation 242 47.5
Level 2- Introductory 129 25.2
Level 3- Intermediate 141 27.3
Playing Experience Frequency Percent
Youth hockey 312
High School hockey 217
Junior hockey 71
Major junior hockey 5
College hockey 66
Professional hockey 8

 

55

Instrumentation

Coaching Eﬁ‘icacy Scale (Feltz et al., 1999; see Appendix A). The CBS is a 24-
item multidimensional scale that was designed to measure a hierarchical model of
coaching efficacy that indicated a four ﬁrst—order factor structure converging to a second—
order general factor of total coaching efﬁcacy (TCE) (Myers et al., 2005). The four ﬁrst-
order factors include: GSE, ME, TE and CBE. Feltz et al. (1999) reported a conﬁrmatory
factor analysis (CFA) that revealed all signiﬁcant parameter estimates (p < .01) for the
first order factor structure, all R2 values surpassed .40, and the results indicated an
acceptable fit of the model using appropriate global indices of non-normed ﬁt index
(NNFI) =.88, comparative fit index (CFI) = .89, root-mean-square residual error of
approximation (RMREA) = .08. The second-order CFA indices regarding total coaching
efficacy differed slightly, but were also readily acceptable. Lee et al. (2002) and Sullivan
and Kent (2003) also found adequate goodness of fit tests for the model. Additionally,
internal consistency estimates of .93 for the total CBS and .90, .88, .89, and .87 for the
subscales of motivation, technique, character building, and game strategy, respectively,
were reported by Feltz et al. (1999). Subsequent studies utilizing the CES, as well as
internal reliability alphas for this study are summarized in Table 5. In each of these
studies Cronbach’s 0t’s are greater than .70, which is the generally acceptable minimum

criterion according to Nunnally (1970).

56

Table 5

Internal Consistency Estimates for CES Dimensions

 

 

Study TCE ME GSE TE CBE
Feltz et al. (1999) .93 .90 .87 .88 .89
Malete & Feltz (2000) n/a .92 .88 .82 .93
Kent & Sullivan (2003) n/a .90 .87 .84 .87
Myers, Tonsing, & Feltz (2005) .94 .90 .92 .84 .87
Paiement (2005) .89 .88 .91 .88 .84

 

The construction of the CES follows Bandura’s (1997) suggestions for
ascertaining valid efﬁcacy beliefs including conﬁdence in speciﬁc behaviors relevant to
the overall construct being measured. Each scale item begins with the stem “How
conﬁdent are you in your ability to. ...” Specific examples of coaching efﬁcacy questions
include “How conﬁdent are you in your ability to understand competitive strategies?”
(GSE). “How conﬁdent are you in your ability to detect skill errors?” (TE), “How
conﬁdent are you in your ability to maintain confidence in your athletes?” (ME), and
“How conﬁdent are you in your ability to instill an attitude of respect for others?” (CBE).

A 5-point Likert-scale ranging from no conﬁdence (1) to complete conﬁdence (5)
was used to assess coaching efficacy. This varies from the previously mentioned
coaching efﬁcacy studies, which employed a 10-point Likert—scale. Myers, Wolfe and
Feltz (2005) examined the range that coaches used within the 10-point scale version of
the CBS, and discovered that coaches failed to utilize 0-4 (which indicates low levels of
efﬁcacy) at a high enough frequency to warrant the inclusion of these lower-end
categories. Myers, Wolfe and Feltz (2005) suggested that employing a smaller scale
would allow for coaches to differentiate more readily between categories, and is within

the recommendations of the use of the Likert-scale (Likert, 1932). Furthermore, utilizing

57

a scale that includes no-confidence as the lowest rating was deemed appropriate as a
considerable proportion of participants (40%) had no previous experience coaching.

An additional note of caution was considered in this study with utilizing the CES
in its current format. Myers Wolfe and Feltz (2005) warned against the structural validity
of the second-order factor of total coaching efficacy in favor of the four ﬁrst-order factors
in most research featuring the CES. They provided psychometric evidence suggesting
that TCE should only be used when ascertaining outcomes in which total coaching
efficacy is one of several predictors. However, TCE was used in the current study as the
criterion variable of sources of satisfaction information and evidence showing signiﬁcant
relationships between sources and TCE exists (Feltz et al., 1999; Myers, Wolfe and Feltz,
2005).

Demographic Questionnaire (Appendix B). A demographic questionnaire was
designed for this study. The questionnaire solicited descriptive information on each coach
including: sex, age, sex of team coached, and ethnicity. Additionally, educational
background (level of formal education obtained), speciﬁc level of the USA Hockey
Coaching Education program (I-V) currently attained, present coaching position (Head or
Assistant), and number of years experience as a coach and hockey player at various levels
(youth, high school, junior, college, professional) were also included. Finally, hours of
preparation time devoted to coaching each week, and a question to conﬁrm that coaches
were amateur and not paid for their services concluded the demographic survey.

Satisfaction. (Appendix C). The need to develop a satisfaction measure for this
study was necessary, as no previously constructed measure of satisfaction was sufﬁcient

for the research question. Modifying a measure such as the Athlete Satisfaction

58

Questionnaire (ASQ; Reimer & Chelladurai, 1998) posed problems because their
complex 15-dimension, 56-item structure encompassed many speciﬁc areas that were not
modifiable to coaching satisfaction. Chelladurai and Ogasawara (2003) developed a
coaching satisfaction questionnaire that was somewhat related to the ASQ, but it too was
unsatisfactory within the context of this study. Theoretically, the Chelladurai and
Ogasawara questionnaire bases its focus on human resource management theory (Dawis
& Lofquist, 1984; Smith, Kendall, & Hulin, 1969). Thus, the dimensions developed in
their study were more theoretically similar to job satisfaction and content theory
measures of professional coaches, which focuses on external factors that affect
satisfaction. The intention of this study was based in social cognitive theory, and
reciprocal determinism in which satisfaction is due to the interaction experience and that
experience will modify the consequent behavior and inﬂuence perseverance to continue
the task of coaching. The dimensions that Chelladurai and Ogasawara (2003) identiﬁed
include such categories as: satisfaction with pay, job security, supervision, facilities, and
media support. Although two categories within their questionnaire may be appropriate,
coaching job and team performance, structurally, all of the dimensions should be utilized
as intended to retain validity. Therefore, this questionnaire was deemed inappropriate for
this reason and because the population sampled in the current study was comprised of
volunteer coaches of youth sport, not collegiate coaches performing their speciﬁed
professional job duties. Additionally, volunteer satisfaction questionnaires, such as the
one designed by Farrell et al. (1998) were not appropriate to utilize. Although volunteer
motivation is a relevant topic to this population, youth sport coaches have a signiﬁcant

level of interaction with the athletes and inﬂuence on the athletes’ subsequent

59

performance. Inﬂuence and interaction are not measured in volunteer satisfaction
questionnaires. The dimensions of volunteer satisfaction focus on communication with
organizers and other volunteers, as well as recognition for contribution to the activity.

Without a coaching satisfaction questionnaire that provided the necessary
questions to fit the intended population, it was imperative to develop an acceptable
measure of coaching satisfaction for this study. There is speculation that commitment,
success, enjoyment, and knowledge may be central themes to the process of coaching and
satisfaction with said process (Raedeke, 2004; Raedeke, Warren & Granzyk, 2002). For
the present study, the coaches’ perception of satisfaction with their coaching performance
was assessed by developing a measurement tool derived by modifying the athlete
perception scale originally constructed by Smoll, Smith, Curtis, and Hunt (1978).
Originally, a seven question instrument was adapted. The items regarded success,
enjoyment, knowledge, commitment and perceived attraction. The seven-item scale
developed for this study was modiﬁed from Smoll et al.’s (1978) measure that assessed
athletes’ satisfaction with several aspects of the coach and coaching behaviors.

The measure used in the current study included a 10-point Likert-scale to address
the coaches’ satisfaction with coaching and with their team. Examples of modiﬁed items
in this scale from the original Smoll et al. (1978) scale are “How much do you like
playing baseball?” [original] to “How much do you enjoy coaching hockey?”[modiﬁed]
and “How good is your head coach at teaching kids how to play baseball?”[original] to
“How much do you know about coaching kids?”[modiﬁed]. After developing the
modified seven-item measure and collecting data, a principle components analysis (PCA)

with oblique rotation was conducted to assess the factor structure. Results of the PCA

6O

revealed a single factor with ﬁve items that could be interpreted to assess satisfaction and
had an eigenvalue of 2.473 that explained 49.47% of the variance. Two questions
regarding perceived attraction (questions 3&4) were not included in the factor for two
reasons. The ﬁrst reason is a lack of statistical evidence of a contribution to the factor
structure. The second reason is conceptual, athlete attraction to the coach is not a
perception made by the coach about his or her experience, as the other ﬁve items were. A
CFA was conducted on the remaining ﬁve items. The ﬁve-item factor returned an
eigenvalue of 4.878 and explained 97.6% of the variance. Factor loadings from the CFA

are included in Table 6.

 

 

Table 6

Factor Loadin gs for Satisfaction Measure

Item Factor
Success .70
Enjoyment .99
Commitment .77
Knowledge hockey .95
Knowledge coaching .70

 

Team ability and team improvement (Appendix C). In addition to the satisfaction
measures, coaches were also asked to rate the ability of their team and to rate their
perceptions of their athletes’ level of improvement over the course of the season. The
team ability measure was taken from Park’s (1992) one-item measure of overall
perceived ability of the team, “How would you rate the overall ability of the athletes on
your team this year?” Feltz et al. (1999) reported test-retest reliability of this question at

.83. Myers, Wolfe and Feltz (2005) also utilized this measure, but cautioned that need for

61

more items to assess the construct of team abilities may be warranted. The current
questionnaire also assessed the coach’s perception of the team’s improvement. The
improvement question was “How would you rate the overall improvement of your
athletes so far this season?” Perceived team improvement was used as an indicator of
team success instead of the past winning percentage variable that Feltz et al. (1999) and
Myers, Tonsing and Feltz (2005) used because in youth sport settings, team records are
not public knowledge or archived after a season, and athlete improvement may be as
salient to the coaches as winning. Both perceived team ability and perceived team
improvement were measured on a lO-point Likert scale ranging from 0 (poor) to 10
(excellent).

Support (Park, 1992; Appendix C). Park (1992) also developed a social support
questionnaire, which contained ﬁve questions regarding coaches' perceptions of support
for their teams from their athletic director, faculty, students, parents, and the community.
Each support question was scored on a 10-point Likert scale ranging from “not at all
supportive” (0) to “extremely supportive” (9). This cognitive appraisal of social support
has been shown to be predictive of coaches’ efﬁcacy beliefs (Feltz et al., 1999; Myers,
Tonsing, & Feltz, 2005). Additionally, Feltz et al. (1999) indicated acceptable levels of
test-retest reliability of 80-89 for the ﬁve items of social support. In the current study, a
four-item questionnaire was used to assess social support on a 10-point Likert-scale
ranging from 0 (poor) to 9 (excellent), to rate their perception of the level of support
given to them by appropriate signiﬁcant others. In amateur ice hockey, the coach has four
groups that hold an interest in their programs. The four groups include the athletes on the

team, the parents of the athletes on the team, the local youth hockey organization they

62

represent, and the local community as a whole. The lO-point Likert-scale was used within
this measure because evidence suggests that coaches’ ratings of factors external to
themselves (i.e., community support) encourage the utilization of the full range of the
scale (Feltz et al., 1999; Myers, Wolfe & Feltz, 2005).
Procedure

Permission to conduct the study was granted by the University’s Institutional
Review Board (see Appendix E) and USA Hockey. The participants were recruited from
USA Hockey Level 1, 2, and 3 coaching clinics in the Midwestern and Northeastern
United States that were held within the ﬁnal six weeks of the 6-month long season. The
sample included respondents who were participants at the coaching clinics; the level 1
clinic was an initiation level and is targeted at ﬁrst-year coaches. Level 2 clinics are
called introductory level and are for more experience coaches, level 3 clinics are for
intermediate level coaches with at least three years of coaching experience. The timing of
data collection was selected to allow participants to gain the experience necessary to
accurately assess their perceptions of efﬁcacy, satisfaction, social support, and athlete
improvement. Participation in this study was requested during the welcome statement of
the coaching clinic. All coaches in attendance (560 total) at the clinics were then
provided with a consent form (see Appendix D) and the coaching efﬁcacy, satisfaction,
and demographic questionnaires. Instructions were read aloud to the participants,
including the right to refuse participation. Following the instruction period, the coaches
were given 15 minutes to complete the questionnaires. All consent forms and
questionnaires were then collected, including blank forms from coaches who refused to

participate.

63

Data Analysis

Data analysis was conducted in a three-step process. The ﬁrst step involved the
examination of data for missing data points, outliers, and tests of the assumptions of
normality. Missing data were handled after assessing the effect and trend of the missing
data. The effect and seriousness of missing data depends on several factors: the size of the
data set, the number of missing cases within that set, and the randomness of the missing data
(T abachnick & Fidel], 2001). The size of the original data set was large (N=537) and the
number of missing cases was small (1.5%); therefore, there was no danger of a signiﬁcant
loss of statistical power do to missing data. Upon in-depth examination of these missing
cases, I determined that the missing values were distributed randomly throughout the entire
sample. The analyses for outliers and normality were done by creating frequency tables and
graphs, examining means, variance, kurtosis and skewness statistics for all variables
collected. Results for these tests are presented in Chapter 4, Table 7.

The second step in data analysis included the calculation of descriptive statistics
for the relevant variables utilized in testing the hypotheses. Pearson-product moment
correlations were calculated for all of the predictor variables with the four dimensions of
coaching efﬁcacy and satisfaction to determine (a) if there was a sufﬁcient relationship
between each predictor variable and each criterion variable to warrant inclusion in tests
of the hypotheses, (b) if there was a sufficient relationship between each predictor
variable and TCE for the latter to be used as the single measure of coaching efﬁcacy, and

(c) if there was any possible mutlicollinearity among the predictor variables.

64

The third step in the data analysis examined the four hypotheses. First a correlation
matrix was created with the predictors and the coaching efﬁcacy dimensions. The predictor
variables showed signiﬁcant correlations with most of the dimensions of TCE and also with
TCE, therefore the ﬁrst hypothesis that coaching education, coaching experience, playing
experience, perceived ability of the team, perceived skill improvement of the team, social
support, and age of the coach are all signiﬁcant predictors of coaching efﬁcacy, was
tested with a univariate multiple regression (MR) analysis with TCE as the criterion variable.
Further examination of the correlations suggested that the four dimensions of the CES should
also be assessed as criterion variables, then a multivariate multiple regression (MMR)
analysis was to used to test the ﬁrst hypothesis. Although it is a reasonable assumption that
gender also would be a predictor of coaching efﬁcacy, for this study gender was not used
because of the small number of female coaches.

The second hypothesis, i.e., coaching education, coaching experience, playing
experience, perceived ability of the team, perceived skill improvement of the team, social
support, and age of the coach are all signiﬁcant predictors of satisfaction with coaching,
was tested with a MR analysis with coaching satisfaction as the criterion variable after a
correlation matrix was created to conﬁrm the presence of a relationship of the variables
with coaching satisfaction. The third hypothesis, coaching efﬁcacy positively predicts
satisfaction with coaching, stated a bivariate relationship and was tested with a bivariate
regression analysis.

The fourth hypothesis, which states that, coaching efﬁcacy is a signiﬁcant
mediator of the sources of coaching efficacy information and coaching satisfaction, was
tested first by using criteria set forth by Barron and Kenney (1986) for determining the

mediating inﬂuence of a variable. According to Barron and Kenney, three conditions must

65

be met to demonstrate the mediating inﬂuence of coaching efﬁcacy. The ﬁrst condition is
that the sources of efﬁcacy must signiﬁcantly predict coaching efﬁcacy. The second
condition to be met is that the sources of efﬁcacy must signiﬁcantly predict coaching
satisfaction. The third step is that coaching efﬁcacy must predict coaching satisfaction and
the effect of the sources of efﬁcacy information must be altered when coaching efﬁcacy is
entered into the equation. In addition to the Barron and Kenney procedure, a path analysis

was conducted using AMOS 5.0 to test the overall model ﬁt. The ﬁt indices included chi-
square statistic ()8), the Non-normed Fit (NNFI), the Comparative Fit (CPI), and Root

Mean Square Residual Error of Approximation (RMSEA).

66

CHAPTER 4

Results

The results are presented in several sections, beginning with the preliminary analysis to
evaluate the accuracy of the data. The second section presents descriptive data for the
participants and correlations among the variables to determine if there were sufﬁcient
relationships to warrant their inclusion in tests of the hypotheses. The third section
presents the results of the hypotheses and a path analysis for the proposed model in
Hypothesis 4.
Preliminary Analyses

The preliminary analyses were conducted to evaluate the effect of missing data,
the accuracy of data entry, and normalcy of the data. Initial data entry was performed
using SPSS 13.0; all data were coded and entered into an SPSS spreadsheet. There were
very few instances of missing data within any individual questionnaire, and only three
participants omitted answers from an entire section located on a single separate page. The
omitted sections indicate that these particular participants were not thorough in answering
the questionnaire, but the omission appeared to be random. Furthermore, no other
participant questionnaire included more than three missing data points. Due to the high
number of participants, I decided a listwise elimination was appropriate for any subject
who provided missing data. The listwise elimination then presented an N of 512 for the
following analyses.

The data were analyzed for incorrect entry and outliers using descriptive and

frequency analyses, as well as visual comparison between questionnaires and the data

67

spreadsheet. An inspection of the minimum and maximum values for out of range and
outlying values was completed. Results indicated that no incorrect values were entered,
and the entire range of answers was used in the completion of the instruments. The
treatment of potential outliers within this study was not of concern as initial descriptive
analyses indicated that the entire range within the Likert-scale was used on cognitive
questionnaires and values entered in the demographic questionnaire were within the
expected range. Skewness and kurtosis values for each of the variables were examined to
assess the assumption of normality (see Table 7). The variables’ skewness values for the
measures ranged from -.13 to ~89, and kurtosis values ranged from .95 to -.57. The
skewness and kurtosis values for the variables were different from zero, indicating that
none of the distributions was perfectly normal, although all of the values were within +/-1
SD, so reasonable assumptions about normality could be made, as this indicates that no

substantial departure from normality occurred (Tabachnick & Fiddell, 2001).

 

 

Table 7

Summary Statistics for Normality
Variable N Skewness Kurtosis
Coaching Efficacy 512 -. l 8 .68
Motivation Efficacy 512 -.24 .29
Teaching Efficacy 512 -.25 -.23
Game Strategy Efﬁcacy 512 -. 13 .50
Character Building Efﬁcacy 512 -.32 -.58
Support of the athletes on the team 512 -.62 .47
Support of my parents 512 -.85 .95
Support of my local community 512 -.58 .26
Support of the hockey organization 512 -.88 .86
Perception of team ability 512 -.51 .67
Perception of team improvement 512 -.64 .92
Coaching Satisfaction 512 -.81 .82

 

68

Descriptive Statistics

Descriptive statistics for the subscales of coaching efficacy, proposed sources of
efficacy, and coaching satisfaction are presented in Table 8. The values for each of the
variables and the related statistics appear to be representative of the expected responses
by the population of respondents. There are some speciﬁc values that may be of
particular interest. Specifically, the disparity among support measures, with support from
the athletes (M: 7.07, SD: 1.16) having the highest average and lowest disparity, and the
support from the local community (M: 5.81, SD=1.81) presenting the lowest mean and
the highest dispersion among the four social support measures. The perception of team
ability (M: 5.62, SD=1.42) and team improvement (M: 6.66, SD=1.30) also provided
ample dispersion and a moderate difference in means among the coaches’ perceptions of
the two performance measures regarding athletes. Additionally, coaching satisfaction
(M: 7.14, SD=.92) was rated as relatively high and the dispersion among scores was
relatively low, indicating that on the whole coaches are fairly satisﬁed with their
experience coaching youth sports. The efﬁcacy scales also provided some insight;
character building efficacy was rated exceptionally high on a 5-point scale (M=4.31; SD

.55), while game strategy efficacy was rated considerably lower (M=3.49; SD=.64).

69

Table 8

Descriptive Statistics for Sources of Support, Satisfaction and CoachinLEﬁ‘icacy

 

Variable N M SD Minimum Maximum
Total Coaching Efficacy 512 3.83 .51 1.67 5.00
Motivation Efﬁcacy 512 3.85 .53 1.86 5.00
Teaching Efficacy 512 3.65 .71 1.20 5.00
Game Strategy Efﬁcacy 512 3.49 .64 1.00 5.00
Character Building Efﬁcacy 512 4.31 .55 2.75 5.00
Support of the athletes on the 512 7.07 1.16 2.00 900
team
Support of the parents 512 6.51 1.55 .00 9.00
Support of my local community 512 5.81 1.81 .00 9.00
SUPP?“ 9f the “OCR” 512 6.38 1.68 .00 9.00
organization
Perception of team ability 512 5.62 1.42 1.00 9.00
Perception of team improvement 512 6.66 1.30 1.00 9.00
CoachiﬂSatisfaction 512 7.14 .92 3.40 9.00

 

Correlations among the Predictor and Criterion Variables

In an attempt to ascertain which predictors showed sufficient relationship with
coaching efﬁcacy and coaching satisfaction and whether there was any multicollinearity
among them, Pearson—product moment correlations were calculated for all variables. To
assess the relationship between social support and coaching efﬁcacy, Pearson—product
moment correlations were calculated for all four social support items and the four
dimensions of coaching efﬁcacy. Results indicated that all areas of social support
correlated significantly with all four subdomains of coaching efﬁcacy. Given the
consistency of the correlations, total support (r = .35) was used as the variable to
represent social support as a source of coaching efﬁcacy. Table 9 displays the

correlations between coaching efﬁcacy and social support.

70

Table 9

Pearson Correlation Coefﬁcients between Coaching Efﬁcacy and Social Support

 

 

 

Coaching Efﬁcacy
Total
Social Support Coach Coaching Game Characte'
Satisfaction Efficacy Motivation Technique Strategy Building
Total Support .41* .35* .37 * .22* .25* .32*
Parents .34* .24* .25* .14* .19* .21*
Community .26* .19* ‘ .21* .13* .12* .21*
Organization .29* .26* .28* . 18* .17* .25*
Athletes .44* .37 * .40* .23* .28* .31*

 

* Correlation is signiﬁcant at the 0.01 level (2-tailed).

Pearson-product moment correlations were also used to asses the relationships
among the other predictor variables, coaching efficacy dimensions, and coaching
satisfaction. Results are presented in Table 10. Results indicate that all the proposed
predictors correlated significantly with TCE and GSE. Playing experience produced high
correlations with TCE (r: .38), TE (r: .55) and GSE (r=.39). This analysis provided
enough evidence to make a reasonable assumption that all sources should be included in
the MR using TCE as the criterion variable for Hypothesis 1 and coaching satisfaction for
Hypothesis 2. Furthermore, none of the correlations were high enough to consider the

threat of multicollinearity.

71

Table 10

Pearson Correlation Coefﬁcients for Coaching Efﬁcacy and Sources

Coaching Efﬁcacy

 

 

S Total
ources .

Coaching Coaching Game Character

Satisfaction Efﬁcacy Motivation Teaching Strategy Building

Playing ,3... H
experience .29 .38 .12** 55*»: 39am: .05
Coaching ....,. 7 **
experience ’30 “‘4 ~17” -20** .26** .12**
Age of Coach -.14** -.16** 304 -.28** -.19** .06
Coaching
Education 16** 15** .07 ,13** .19** .08
Level
Team ability .27** .15** .17** .08 .16** .07
Team ** **
Improvement '31 '28 ~26” -23** .21** .19**

 

** Correlation is signiﬁcant at the 0.01 level (2-tailcd).
* Correlation is signiﬁcant at the 0.05 level (2-tailed).

Tests of the Hypotheses

The first hypothesis stated that coaching education, coaching experience, playing
experience, perceived ability of the team, perceived skill improvement of the team, social
support, and age of the coach are all significant predictors of coaching eﬁicacy. This
hypothesis was tested in 3 MR analysis using all seven predictors and TCE as the
criterion variable. Results indicated that the MR produced a signiﬁcant result, F (7, 505)
=30. 71; p<.0001) and a strong predictive relationship (R: .55; R2=.30) thus supporting
the hypothesis. The strongest predictors of TCE within the MR were social support (,6 =
.23) and playing experience (ﬂ = .29). Only coaching education level (,6 = .07, p: .121)

and team ability (,6 = -.05, p: .314) were non-significant in the MR.

72

The second hypothesis stated that coaching education, coaching experience,
playing experience, perceived ability of the team, perceived skill improvement of the
team, social support, and age of the coach are all significant predictors of satisfaction
with coaching. This hypothesis also was tested using all seven predictors and coaching
satisfaction as the criterion variable. Results indicated that the MR produced a signiﬁcant
result, F ( 7, 505 ) =36.9I; p<.0001), and a strong predictive relationship (R: .58,-
R2=.34) thus supporting the hypothesis. The strongest predictors of TCE within the MR
were social support (,6 = .30) and coaching experience (,6 = .25). Again, coaching
education level (,6 = .05, p: .250) and team ability (,6 = .06, p: .141) were non-signiﬁcant
in the MR.

The third hypothesis stated a bivariate relationship between coaching efﬁcacy and
coaching satisfaction and was tested using a bivariate regression with TCE as the
predictor variable. The result of a linear regression of coaching efficacy on satisfaction
indicated a significant result, F(1, 505 ) =43] .41 ; p<.0001, and a strong predictive
relationship (R2 =.45;ﬂ=.6 7) thus supporting the hypothesis.

The fourth hypothesis stated that the role of coaching efﬁcacy was mediational
between the predictors and satisfaction, as was indicted in Chapter 1. Therefore, an
analysis was conducted to test the application of the conditions set forth for a mediational
relationship by Barron and Kenney (1986). The previous multiple regressions provided
information about the speciﬁc strength of the predictors of coaching efﬁcacy and
satisfaction. The predictors found to have a signiﬁcant contribution included: social
support, team improvement, playing experience, coaching experience, and age of coach.

Coaching education level and team ability were not included, as their contribution was

73

not supported in the previous multiple regressions. The predictors were then subjected to
additional MR analyses with coaching satisfaction as the criterion variable while
controlling for coaching efficacy to test the mediational relationship prior to conducting a
path analysis.

Results for the MR on coaching satisfaction while controlling for coaching
efficacy revealed that social support and coaching experience were at least partially
mediated by coaching efficacy. Furthermore, the inﬂuence of playing experience, team
improvement and the age of the coach on coaching satisfaction was completely mediated

by coaching efﬁcacy. Results for all three analyses are presented in Table 11.

 

 

 

 

 

Table 11
Results for Univariate Regressions for Mediational Eﬂect of Coaching Efﬁcacy

Control for

Coach Efﬁcacy Coaching Satisfaction Coaching Efﬁcacy

Predictors B P B P B P
Social Support .23 .000 .29 .000 .17 .000
Coaching .065 .121 .047 .250 .013 .707
Education Level
Coaching .190 .000 .247 .000 .151 .000
Experience
Playing Experience .286 .000 .214 .000 .066 .063
Team Improvement .195 .000 .141 .001 .042 .256
Age of Coach -.098 .001 -.109 .009 -.060 .092
Team Ability -.045 .314 .064 .142 .087 .018
Coaching Efﬁcacy .514 .000

 

The previous analyses provided evidence to include the significant predictors from the

univariate regression analyses in the path analysis as modeled below in Figure 5.

74

Predictors

 

Social Support

 

 

Perceived skill improvement

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

of team
\ Total Coaching __, Coaching Satisfaction
Playing Experience Efﬁcacy
Age of the Coach

 

 

 

 

Coaching Experience

 

 

 

 

Figure 5. Proposed model for the path analysis

Path analysis

The path analysis was designed to measure the relationship between the coaches’
sources of efﬁcacy information, coaching efficacy, and coaching satisfaction. The path
analysis was performed using AMOS 5.0. The full model was put forth in the initial
analysis and included social support (,6 =.275), team improvement (,6 =.179), playing
experience (,6 2.296), age of coach (,6 =-.103) and coaching experience (,6 =.197) as
predictors of TCE and social support (,6 =.216), coaching experience (,6 =.141) and TCE
(3:563) as predictors of coaching satisfaction. The initial path analysis revealed a poor
fit, x2 (13) =266.5; age of coach was the weakest variable (,6=-.006, p =.008). The NNFI
(.69) and CFI (.68) were significantly less than .90, which is the generally accepted limit
to good ﬁt of a path model. The RMSEA should be under .08, but was also not

considered a good ﬁt (RMSEA: .191). A second analysis was conducted after reducing

75

the model by eliminating age of coach as a predictor variable. The global ﬁt indices were
considerably improved, but still inadequate regarding the generally accepted levels. The
chi-square was greatly reduced but still large, x2 (8) = 120.91, p <.001, the NNFI (.83)
and CF] (.83) were also improved but less than the accepted .90. The RMSEA was still
not considered a good ﬁt (RMSEA: .162). The previous data in the multiple regressions
as well as the Pearson-product moment correlations were re—examined in an attempt to
provide a lucid model. It was determined that only the predictors that provide little or no
inﬂuence would be reduced. The previous conceptual arguments for the importance of
efﬁcacy sources and the small beta weight indicated that team improvement could be
reduced.

The further reduced model was examined as the ﬁnal path analysis was
conducted. This model included social support and coaching experience as partially
mediated by coaching efficacy and playing experience being fully mediated by coaching
efﬁcacy. The global ﬁt indices produced accepted levels for a good ﬁt, the chi-square was
signiﬁcant, x2 (4) = 15.96, p =.003. The NNFI = .98. the CFI = .98 were also signiﬁcantly
higher than .90. The RMSEA (.075) was also a good ﬁt because it was lower than the
acceptable level of .08. Therefore, the data examined did create a more acceptable ﬁt by
reducing the model. The ﬁnal path analysis included social support (6 =.323), playing
experience (6 =.334), and coaching experience (,6 =.183) as predictors of TCE and social
support (,6 =.213), coaching experience (,6 =.I39) and TCE (6:568) as predictors of

coaching satisfaction. The reduced model is presented in Figure 6.

76

Predictors

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

.213
Social Support
23
Playing EXPerience 334 Total Coaching 563 Coaching
Efﬁcacy Satisfaction
.183
Coaching Experience
.139

 

Figure 6. Significant Parameter Estimates for the Reduced Model

Exploratory Analysis for Coaching Education

Due to the nature of the research questions, the importance of coaching education,
previous research on coaching education and coaching efﬁcacy (Malete & Feltz, 2000)
and the recruitment of the participants at a coaching education program, an exploratory
analysis was conducted to assess the inﬂuence of coaching education level (1-3) on
coaching efﬁcacy and coaching satisfaction. Tables 12 and 13 display the means and
standard deviations for each of the coaching education levels, coaching efﬁcacy and
satisfaction. A MANOVA was conducted with the three levels of USA Hockey coaching
education as the independent variable. Coaching education level was signiﬁcant, Wilks
2. =.934; F(12,1038) = 3.02, p < .001. Total coaching efﬁcacy, F(2,509) = 7.51, p = .001,
and satisfaction, F ( 2,509) = 7.33, p = .001 were also significant. The ﬁrst order factors of
coaching efﬁcacy were also analyzed. Game strategy efﬁcacy, F( 2,509) = 11.12, p <
.001, technique efficacy, F( 2,509) = 4.16, p = .016, and character building efﬁcacy,
F ( 2,509) = 3.71, p = .025, provided a significant result. Only motivation efﬁcacy,
F ( 2,509) = 2.31, p =.101, was not significant. Results for the MANOVA are reported in

Table 14.

77

Table 12

Means and Standard Deviations for Coaching Education Level

 

 

Coaching Ed Level N Mean Std. Dev

Coaching Efficacy Initiation- I 242 3.76 .53
’ Introductory- II 129 3.77 .42

Intermediate- 111 141 3.95 .47

Total 512 3.81 .49

Satisfaction Initiation- I ' 242 6.99 .96
Introductory- H 129 7.21 .77

Intermediate- [[1 141 7.35 1.04

Total 512 7.15 .95

 

Table 13

Means and Standard Deviations for Coaching Education Level and F irst-Order Factors

 

 

of Coaching Eﬂicacy
Coach Ed Level N Mean SD
Efficacy Introductory- II 129 3.82 .50
Intermediate- 111 141 3.95 .50
Total 512 3.88 .53
Teaching Efficacy Initiation- I 242 3.60 .77
Introductory- H 129 3.66 .65
Intermediate- 111 141 3.82 .69
Game Strategy Initiation- I 242 3.47 .72
Efﬁcacy Introductory- II 129 3.51 .55
Intermediate- III 141 3.78 .58
Total 512 3.57 .65
Character Building Initiation- I 242 4.28 .51
Efﬁcacy Introductory- II 129 4.21 .51
Intermediate- 111 141 4.38 , .58
Total

512 4.29 .53

 

78

Table 14

Multivariate Analysis of Variance of Coaching Education Program Level

 

 

Coaching Education Level Sum Sq Df . M Sq F Sig.
Satisfaction 12.940 2 6.470 7.333 .001
Coaching Efﬁcacy 3.569 2 1.785 7.507 .001

Motivation Efficacy 1.280 2 .640 2.305 .101

Teaching Efﬁcacy 4.289 2 2.145 4.157 .016

Game Strategy Efﬁcacy 9.164 2 4.582 11.124 .000

Character Building

2.095 2 1.048 3.709 .025

Efﬁcacy

 

Although conceptually three levels of coaching education were represented in this
sample, it would be naive to assume that coaching education was independent of
coaching experience, as the CEP program presented to the participants was also a year by
year progressive certification program (i.e., level 1 is taken in the ﬁrst year, level 2 is
taken in the second year). Therefore, a MANOVA was conducted on coaching efﬁcacy
with coaching education level as the independent variable and coaching experience as the
covariate. Coaching education level when controlling for coaching experience was not
significant, Wilks /I =.966; F(12,1038) = 1.52, p = .112. Neither total coaching efﬁcacy
nor satisfaction provided signiﬁcant results. Additionally, of the ﬁrst order factors of
coaching efficacy only game strategy efﬁcacy was significant, R2: .08, F ( 2,509) = 3.22,
p = .041. This indicates that coaching education level may not have an effect on coaching
efficacy beyond what they obtain through experience, except when considering game
strategy.

Results for the MANOVA controlling for coaching experience are presented in Table 15.

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Table 15

Multivariate Analysis of Variance of Coaching Education Program Level while

Controlling for Years of Coaching Experience

 

 

 

Coaching Education Level Sum Sq Df M Sq F Sig.
Satisfaction 2.001 2 1.000 1.205 .300
Coaching Efficacy .808 2 .404 1.764 .172

Motivation Efﬁcacy .264 2 .132 .486 .615

Teaching Efficacy .615 2 .307 .610 .544

Game Strategy Efficacy 2.550 2 1,275 3.221 .041

Character Buildin

. g 1.176 2 .588 2.095 .124

Efficacy

Summary

In summary, in this study increased levels of social support, playing experience,

and coaching experience predicted higher ratings of total coaching efficacy. Additionally,

increased levels of social support, more coaching experience and higher ratings of total

coaching efﬁcacy served as predictOrs of higher ratings of satisfaction with coaching.

Furthermore, coaching education may not have an effect on coaching efﬁcacy when

controlling for years of coaching experience.

80

CHAPTER 5

Discussion

The purpose of this study was to investigate the relationship between coaching
efﬁcacy and coaching satisfaction, and their relationships to personal characteristics (i.e.,
experience, age, etc.) of youth hockey coaches within the framework of the Feltz et al.
(1999) model. The ﬁrst hypothesis stated that coaching efﬁcacy of volunteer youth
coaches would be predicted by the seven sources outlined in the models. Support was
found for this hypothesis with previous coaching experience, social support and playing
experience providing the most efﬁcacy information to youth hockey coaches. Team
improvement was also a signiﬁcant predictor, but did not provide a large contribution to
the equation. Age of the coach was signiﬁcant and provided a small contribution.
Although, age was negatively correlated with coaching efﬁcacy and coaching education,
indicating that younger coaches perceived higher levels of efﬁcacy and had achieved
higher levels of coaching education, which may contribute to higher efficacy beliefs.
However, coaching education level and team ability did not provide a significant
contribution to coaching efﬁcacy in this study.

These ﬁndings support Feltz et al.’s (1999) model and their previous research that
social support and coaching experience appear to be important sources of coaching
efﬁcacy. Social support and coaching experience have consistently been revealed to
predict coaching efﬁcacy. Myers et al. (2005) provided evidence that social support and
coaching experience were relevant sources of efﬁcacy information. Feltz et al. examined

high school coaches, while Myers et al. (2005) examined collegiate coaches. Therefore,

81

one would assume that social support and coaching experience are fairly stable and
consistent predictors in any coaching situation. Marback et al. (2005) also found support
for coaching experience and support from athletes as signiﬁcant predictors of coaching
efﬁcacy. Social support as a source of coaching efficacy in youth sport coaches is not a
surprising result. Social support, or lack thereof, can be found in comments made by
players, parents, or organizational leaders to the coach, as well as body language and
actions directed at the coach or made to additional significant others. Although, coaches
with higher efﬁcacy may also command more respect from parents. If the type of
behavior exhibited by parents is perceived as positive, the coach gamers that information
as positive approval of his or her coaching actions, which in turn boosts the coach’s level
of efﬁcacy.

Previous coaching experience was also supported, and according to Bandura,
(1997) is the most salient source of information on which to base efficacy judgments. In
general, a coach with more experience will have developed methods of teaching skills,
manipulating game strategy, evaluating talent, and other coaching skills that serve to
provide efﬁcacy information based upon such measures as athlete improvement, which
was also supported in this study.

Perception of team improvement were presented in this study as a way to provide
success information to youth coaches, where perceptions of team ability and overall
win/loss success may not be the end goal in youth sports. Although perception of team
improvement was not as strong a predictor of coaching efficacy as were social support

and playing experience, its significance provides a novel corroboration to the Feltz et al.

82

(1999) model and supports what Chase et al. (2005) found as important efﬁcacy sources
in their interviews with high school coaches.

In contrast, perceptions of team ability as a predictor of coaching efficacy did not
find support in this study as it did in Myers et al. (2005). Myers et al. surmised that the
importance placed on team ability and the subsequent inﬂuence on efﬁcacy may be due
to the competitive nature of collegiate sports. Although, in youth sports there may be a
difference as a youth coach must coach the players they are given and ideally, recruiting
does not exist as it does at the collegiate level. Although in a collegiate sport team ability
is a direct reﬂection of a coaches’ recruiting success. Perhaps this provides ample
explanation for the ﬁndings that team improvement was supported and team ability was
not supported, as youth sport does not have the same competitive nature, therefore youth
coaches may derive perceptions of efficacy from different sources than collegiate coaches
(i.e. recruiting, team ability).

Playing experience was another predictor of coaching efﬁcacy that found support
in this analysis. This supports the ﬁndings of Sullivan et al. (in press) as they found that
previous playing experience was a signiﬁcant source of game strategy efﬁcacy, but was
moderated by coaching experience in other areas of coaching efﬁcacy. Park (1992) did
not ﬁnd support for playing experience as a source of coaching conﬁdence, and explained
that previous playing experience was not a requisite component of coaching competence.
An example of good coaching being unrelated to playing experience may be found in
Scotty Bowman, the legendary Hall of fame coach for Detroit, Pittsburgh and Montreal
of the NHL, who guided his teams to twelve Stanley Cups in the late 1970’s through

2002. Scotty never played above junior hockey, could barely skate, and did not step foot

83

on the ice for a team practice from 1991 until his retirement in 2002. Although playing
experience may contribute to coaching efﬁcacy of youth-aged athletes, it might not offer
a strong inﬂuence to confidence in coaching more experienced athletes, such as at the
collegiate and professional levels that typically have more playing experience than their
coaches. In addition, at higher levels of coaching, other aspects of coaching efﬁcacy that
playing experience may not account for are probably more important, such as skill
diagnostics, motivation, recruitment, and management. Future research is necessary to
examine the inﬂuence of playing experience at different levels of coaching and with
various dimensions of coaching efﬁcacy.

As Feltz et al. (in press) noted, the associations between specific sources and the
dimensions of coaching efﬁcacy are likely to be dependent on the level of coaches
involved (e. g., youth, high school, or collegiate) and organizational factors of the
program (e.g., premier leagues, size of school, competitive divisions). Thus, they
suggested that years of playing and coaching experience may be most important to TE
and GSE at the youth level; coaching experience may be most important to GSE and ME
at the high school level; and, perceived team ability may be most closely tied to ME and
CBE at the college level. Coaching experience and social support appear to cut across
coaching levels and coaching efﬁcacy dimensions. Future research is needed to
understand the sources of coaching efﬁcacy by coaching levels in a systematic fashion.

The second hypothesis stated that coaching satisfaction will be predicted by the
same aforementioned seven sources. This hypothesis was also supported, with social
support, coaching experience and playing experience again providing the largest

contribution. Furthermore, coaching education level and team ability did not provide a

84

signiﬁcant contribution to this analysis. Social support supplied a stronger beta for
satisfaction than for efﬁcacy, even though social support provides efﬁcacy information,
support from signiﬁcant others can also lead directly to such satisfaction issues as
commitment, enjoyment, and burnout. Vealey, Udry, Zimmerman and Soliday (1992)
examined coaching burnout and found that a lack of social support led to higher levels of
burnout in coaches. Raedeke and his associates (Raedeke, 1997; Raedeke et al., 2000,
Raedeke et al., 2002) examined the effect of satisfaction on burnout and found that social
support was a signiﬁcant predictor of satisfaction and satisfaction subsequently affected
burnout.

While burnout and commitment are related outcomes of satisfaction (Raedeke et
al., 2000), they also have been examined in relation to coaching efﬁcacy. Haugen and
Short (2004) found support for the relationship between coaching efﬁcacy and burnout,
and Kent and Sullivan (2003) found that coaching efficacy predicted coaching
commitment. Therefore, if continued coaching commitment increases the athlete
development cycle, and is predicated by coaching efﬁcacy and satisfaction, then both
coaching efﬁcacy and satisfaction must be developed and nurtured. Weiss and Freidrichs
(1986) ﬁrst presented the notion that social support leads to increases in satisfaction
within sports. Reimer and Toon (2001) found similar results between social support and
athlete satisfaction. Specifically, those athletes who perceive more support from coaches
will report higher levels of satisfaction with the coach. Davis (2002) found that the actual
number of interactions between the coach and signiﬁcant others provided social support
information to the coach and led to higher levels of satisfaction for the coach. Although

social support is typically a perception, there may need to be actual overt interaction

85

between significant others and the coaches that provides coaches with information for
accurate perceptions about social support (Ladd, 1981).

Social support as a predictor of satisfaction in youth coaches is logical, because
coaches who meet with abnormal resistance or opposition by signiﬁcant others (i.e.,
parents) may not experience enough beneﬁt to continue on as a coach in a non-
professional (non-paid) setting. Although, opposition could be framed as negative social
support and may not be the same as a lack of social support, it would provide similar
information to the coach. Social support has been a consistent ﬁnding in providing
efficacy information and had a significant effect on satisfaction in this study. A lack of
social support or a perception of negative support could certainly provide a stressful
environment for coaches and present burnout as a possibility. Although, burnout may not
be a large issue among youth sport coaches because the rewards may not provide enough
incentive to push oneself to such a stress level that burnout would be the resultant
outcome. That is, youth sport coaches may drop out before they become burned out, and
if they drop out, they would not be in the data set in which to measure such constructs.
This may explain the high mean ratings of satisfaction in the descriptive data. Volunteer
youth coaches who experience a waning level of satisfaction will discontinue coaching
prior to experiencing the negative effects of burnout, but the discontinuation may stem
from a lack of support, or experience. The problems that coincide with high rates of
turnover still exist, such as a decrement of athletic performance (Dobson et al. 2002;
Koning, 2003), and a break in the athlete development cycle, as proposed in Chapter 1.

This reiterates Cunningham and Sagas’ (2002) findings that coaching turnover is

related to career satisfaction, but coaches with more experience rated coaching

86

satisfaction higher than coaches with less experience. Experience was tested in two ways,
previous playing experience and previous coaching experience. Speciﬁcally,
Cunningham and Sagas (2002) found that coaches with more playing experience reported
higher levels of satisfaction and lower turnover intentions. This may be due to the
coaches’ commitment to the sport, as coaches with signiﬁcant playing experience may be
committed to the sport as a way of life. Coaches with no playing experience, on the other
hand, frame their experience as a passive participant and may not understand the life
commitment to the sport as compared to the commitment of a coach with a 20-year
playing career. Thus, the more social support that coaches perceive they have, the more
playing experience, and the more coaching experience, the more satisﬁed they should be
with their coaching experience and their chances of dropping out should be less. Years of
coaching experience were also a signiﬁcant predictor of satisfaction with coaching. This
could be due to coaching style or as mentioned beforehand, coaches who are not satisﬁed
by their experience dropout or burnout and do not continue to coach. As for coaching
style, as coaches gain experience, they learn how to garner social support from signiﬁcant
others and handle problems that, ideally, limit the amount of unpleasant experiences and
increases satisfaction. Additionally, tenure of coaching experience can be related to
success in many situations, and success may not be directly related to satisfaction, but
practically, people are usually more satisﬁed after a successful performance.

One pertinent ﬁnding in the first two analyses was the lack of contribution found
from coaching education. Malete and Feltz (2000) and Lee et al. (2002) both found
support for coaching education as a predictor of coaching efficacy. The results of this

study did not support these findings. This may be due to the use of coaching education

87

levels and not just dichotomous groups of those who had completed coaching education
versus those who had not completed a coaching education program. Fung (2002) assessed
coaches who were attending three ordered levels of coaching education, much like the
current study, and found similar results. Both Fung (2002) and the results of this study
found that coaches with more coaching education experience had higher mean scores on
the efficacy scales. While differences were found in this study, when years of coaching
experience was included as a covariate, the only signiﬁcant difference between coaches’
ratings of their coaching efﬁcacy within the three levels of coaching education was for
GSE. This may explain the lack of a contribution to the regression equation, as the
contribution of coaching education is explained partially by years of coaching experience,
which is a strong predictor of both efﬁcacy and satisfaction. This suggests that coaching
education contributes to GSE more than the other efficacies, which supports previous
findings (Lee et al., 2002; Malete & Feltz, 2000). This could also indicate that the
coaching education programs presented by USA Hockey focus on topics related to the
sport of hockey and less on motivational and character—building skills.

The issue of what topics should be addressed in coaching education is a recurring
theme in the coaching education literature (Woodman, 1993). Specifically, it is unclear
what topics are central to coaching youth sports, and how important specific game
strategy topics are to general coaching education. Based on personal involvement in the
USA Hockey coaching education program, strategy is the main topic of the clinics. Many
clinics are designed to bring in collegiate and professional coaches to give “chalk talks”
to the coaches in attendance about systems and strategies utilized at the collegiate and

professional levels. This may be inappropriate for a beginning youth coach who would

88

beneﬁt more from information regarding legal and ethical behavior, teaching and
pedagogical techniques, and personnel and parent management. The curriculum is set up
to instruct on the basic topics, but the freedom of the instructors to adapt the coaching
clinic programs, leaves coaches without the necessary information that has been
forwarded in the curriculum (Gilbert & Trudel, 1999).

Finally, the ﬁnding that coaching education did not present a signiﬁcant result on
coaching efﬁcacy when controlling for years of coaching experience may be indicative
that coaches receive their educational experience from practical means. This may provide
evidence that supports the impetus for mentored coaching experience or internships as a
portion of the coaching education programs. If experience provides such prominent
coaching efﬁcacy information, then support for Gilbert and Trudel’s (2001) proposition
that active experience becomes a part of coaching education may be the most logical step
in further development of coaching education. Their proposition also provides support for
including mentored experience in the Sullivan et al. (2005) coaching education model.

The third hypothesis stated that coaching efﬁcacy would signiﬁcantly predict
satisfaction with coaching as an outcome. This hypothesis was supported and provides
another novel corroboration to the Feltz et al. (1999) model; there is no previous research
link between coaching efﬁcacy and satisfaction. Chelladurai and Ogasawara (2003)
discussed the importance of predictors of satisfaction and subsequent satisfaction on
outcomes such as commitment and retention. Feltz et al. (1999) also indicate that such
coaching outcomes may be relevant to the coaching efﬁcacy model. A strong sense of
self-efficacy as a coach can lead a coach to feel successful and satisﬁed even in times of

opposition. This is where confidence and satisfaction make a practical connection. If a

89

coach has confidence in his or her abilities and believes that s/he did a good job, then
subsequent satisfaction is likely to occur, regardless of measurable success. This result
also addresses the missing link to coaching outcomes in Hom’s Model of coaching
effectiveness (2002). If coaches’ beliefs, values and cognitions have a link to the
affective cognitions of coaches, then coaches have deﬁnitive outcomes that provide
information to make the coaching effectiveness model more complete. The inclusion of
coaching outcomes in Horn’s model may be necessary to forward a more complete
understanding of coaching effectiveness.

The final hypothesis stated that coaching efﬁcacy would mediate the relationship
between the seven sources and satisfaction with coaching. The model was analyzed with
a path analysis and results showed that playing experience was mediated by coaching
efficacy, and social support and coaching experience were partially mediated. These
findings provide unique pathways between playing experiences, social support and
coaching efficacy and satisfaction. As discussed previously, social support has both a
direct and indirect (through coaching efficacy) relationship with satisfaction. Significant
others can present information and actions that both provide efﬁcacy information and
lead directly to satisfaction with the experience of coaching. Opposition from parents and
the organization may lead a confident coach to lower levels of satisfaction, while support
for the coach, even if the coach lacks conﬁdence, may also occur. Generally, positive
social support presents coaches with information that lead them to believe they are doing
a good job, which leads to an increase in efficacy. This increase in efﬁcacy, as well as the
positive affect ascertained from the social support, should lead to increased satisfaction.

This increase in satisfaction supports Raedeke et al.’s (2002) premise that increased

90

commitment will reduce turnover intentions. Turnover is less likely to occur when
coaches are satisﬁed and committed to the coaching profession. (Cunningham & Sagas,
2002).

Implications for Coaches

The ﬁndings of this study indicate that coaching efﬁcacy has a signiﬁcant
relationship with coaching satisfaction. Although the study design does not support a
conclusion that efﬁcacy beliefs affect coaching satisfaction, it is predictive of higher
levels of satisfaction and in accord with Bandura’s (1977, 1997) theory of self-efﬁcacy.
The predictors of both coaching efﬁcacy and satisfaction include coaching experience
and social support. The practical information regarding increasing coaching efﬁcacy and
satisfaction is probably best directed at coaching education programs. The purpose of
coaching education is to increase knowledge and conﬁdence of novice coaches.
Therefore the implication of social support as a predictor of both would be to include
social support as a topic in coaching education programs.

Many believe social support to be a passive activity in which one receives
approval, acceptance or endorsement from others. However, this belief runs counter to
the social-cognitive perspective (Bandura, 1986) that people are active participants in
creating their own environments. Social support can be an active process in which one
pursues the social support that is needed. This occurs naturally in many leadership
situations, and many times provides the impetus for new leadership within a team.
Gamering social support in a positive manner can be accomplished with such activities as
team social functions or parties, parent orientation meetings, and fundraising activities

(Feltz et al., in press). Typically, open communication is one of the strongest precursors

91

to social support from parents and administrators. If parents feel that they are informed
and understand the intentions of the coach, they are more likely to provide the requisite
support. If a coach has not informed his or her superiors or the athletes’ parents the
coaches’ intentions, then problems can arise and support may wane.

Teaching coaches how to garner social support may be a valuable commodity that
should be added to coaching education.- Arming coaches with the knowledge of how to
deal with parents and administrators can be invaluable, and the proper methods for team
meetings, and Open communication should be instructed. This may provide more
satisfaction among coaches as well as parents. Coaching education requires more
information than simply providing “chalk talks” from professional coaches. Providing
real information to coaches on how to deal with real problems, such as parent interaction
and parental support, should be a part of any coaching education program.

A second implication is the addition of mentored experiences to all coaching
education programs. Coaching experience has consistently appeared as a predictor of
coaching efficacy (e.g., Feltz et al., 1999; Fung, 2002; Myers et al., 2004). Conﬁdent
coaches typically have the ability to address challenges and report higher levels of
satisfaction. Therefore, it may be prudent to provide experiences where coaches are set
up for success and not failure. By requiring a mentored coaching experience, coaches
would get the opportunity to gain valuable experience under an experienced coach.
Ideally this would help to build coaching efficacy and coaches would perceive
themselves to be better prior to taking head coaching duties that may require expectations
that exceed the coaches’ capabilities. Coaching education has been shown to increase

coaching efﬁcacy (Malete & Feltz, 2000), as efﬁcacy has been in turn, shown to predict

92

satisfaction with coaching. Although coaching education did not provide a signiﬁcant
contribution within this study, it has been shown to have positive effects and may be most
effective as a combined classroom and mentored experience. A combined coaching
education experience that provides ample coaching knowledge and experience should
provide relevant efﬁcacy information. In conclusion, two additional areas of coaching
education that may provide important information to coaches are dealing with social
support and experiential coaching education. Experiential coaching education would
include such activities as coaching internships, mentorships and directed study in which
coaches gain experience as a coach under the direction of a master or professional coach.
Limitations

There are some limitations to this study. The first limitation regards the design.
The study presented a one-shot questionnaire submitted at the two-thirds mark through
the hockey season. Although Bandura (1997) indicates that efﬁcacy beliefs are predictive
over time within the assessed situation, the number of inexperienced coaches in this study
may create a situation where efﬁcacy information such as performance accomplishments
and verbal persuasion have more impact on efﬁcacy beliefs and may be less stable than
the beliefs of veteran coaches. Feltz et al. (1999) provided sufﬁcient evidence to assume
test-retest reliability of the CES, which supports the notion that the measure is valid.
Myers et al. (2005) called for research to assess the stability of coaching efﬁcacy over the
course of a season, which also addresses this as a limitation of concern reiterating that
efﬁcacy beliefs may be less stable with less experienced coaches. Additionally, it was
necessary to measure coaches at a minimum of two-thirds through the season, as the

inexperienced coaches needed time to formulate a sense of efﬁcacy belief for this specific

93

coaching situation. An improvement for future studies may be to examine efﬁcacy
change by measuring at the one-third, two-third and end points of the season.

A second limitation to this study was the lack of availability of an adequate tool to
measure coaching satisfaction. Although Chelladurai and Ogasawara (2003) did construct
a coaching satisfaction measure based upon factors inﬂuencing job satisfaction, it was
deemed insufﬁcient for our purposes. One major concern with adopting satisfaction
questionnaires adapted from industrial/organizational psychology literature like
Chelladurai and Ogasawara’s questionnaire are the content factors assessed, which
include job satisfaction with pay, supervision, beneﬁts, ofﬁces, etc. This is problematic
for the non-professional coaches. As non-professional coaches make up 97% of the 2.5-3
million coaches in North America, it may be more appropriate to develop a measure that
can be utilized by the majority of coaches. Utilizing a measure that was constructed for
coaches that are employed full-time by colleges and professional sports teams and
ascertains information about such professional expectations would not provide a valid
measure of satisfaction with volunteer or amateur coaching positions. The questionnaire
adapted from Smoll et al. (1979) and Raedeke et al. (2002) focuses more on process
satisfaction and future commitment. This was deemed a more appropriate measure for
this study.

Future Directions

Based on the literature review and ﬁndings of this study, recommendations for
future research directions are presented. As previously mentioned, future research is
needed to develop a measure of coaching satisfaction with non-professional coaches. The

use of qualitative methods will help to deﬁne a coaching satisfaction construct that is

94

sharply focused on the volunteer coach and a process-based approach to coaching
satisfaction. This study has provided evidence that suggests satisfaction with coaching
needs to be further understood and may provide some insight into such outcomes as
coaching dropout and burnout.

Additionally, researchers should look at the development of coaching efﬁcacy and
satisfaction in different contexts, such as temporal development, possibly over a single
season or multiple seasons. Gathering data at several time points during the season may
provide a more representative picture of the development of coaches’ conﬁdence and
ﬂuctuations in satisfaction throughout the year. This could provide insight into the nature
of the changes in conﬁdence and satisfaction, particularly with new and developing
coaches throughout their first season. This study should also provide information about
the inﬂuence of ﬂuctuating perceived social support and team performance on coaches’
efficacy and satisfaction. Within a temporal study, the question of a reciprocal
relationship may be addressed.

Another direction of future research in coaching efficacy and satisfaction should
include an assessment of gender of the coaches and athletes. Previous research on
coaching confidence and gender (Barber, 1998; Vealey etal., 1992) has been limited to
female athletes and both genders for coaches, but male athletes have not been assessed
and it is conceivable that the coaches’ efficacy and satisfaction outcomes may vary
depending on athletes’ gender and coaches’ gender in a four-way model. This study did
include male and female athletes and coaches, but the representation of female coaches
was too small to be analyzed effectively. Marback et al. (2005) did ﬁnd support for

gender of the coach as predictor of GSE and CBE, and it may provide information about

95

satisfaction, as well as social support perceptions. Therefore, future research should
include sufficient data to take these variables into consideration.

One additional direction that should be examined is comparing the perceptions of
the coaches’ efficacy to the athletes’ and parents’ perceptions of the coaches’
competence, as well as the athletes’, parents’, and coaches’ level of satisfaction with the
coach and his or her coaching. In studying the congruence between the parent, athlete and
coaches’ perceptions, researchers may be able to acquire more inedepth information into
the social support, efﬁcacy and satisfaction relationships. Based upon the results of this
study, higher congruence between perceptions of competence and efﬁcacy may lead to
higher levels of perceived social support and coaching satisfaction. This may include the
use of interventions, such as coach training or mentoring during the season to assess

changes with direct coaching development.

96

Appendix A
Coaching Confidence Questionnaire

Coaching conﬁdence refers to the extent to which coaches believe that they have the capacity to affect the
learning and performance of their athletes. Think about how conﬁdent you are as a coach. Rate your
conﬁdence for each of the items below. Your answers will be kept completely conﬁdential.

How conﬁdent are you in your ability to—-

No Low Moderate High Complete

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

(Circle the most appropriate answer) Conﬁdence Conﬁdence

1, help athletes maintain conﬁdence in 1 2 3 4 5
themselves?

2, Recognize opposing team’s strengths during 1 2 3 4 5
competition?

3. mentally prepare athletes for game strategies? 1 2 3 4 5

4, understand competitive strategies? 1 2 3 4 5

5. instill an attitude of good moral character? 1 2 3 4 5

6. build the self-esteem of your athletes? 1 2 3 4 5

7. demonstrate the skills of your sport? 1 2 3 4 5

8, adapt to different game/meet situations? 1 2 3 4 S

9, Recognize opposing team’s weakness during 1 2 3 4 5
competition?

10. motivate your athletes? 1 2 3 4 5

11, make critical decisions during competition? 1 2 3 4 5

12. build team cohesion? 1 2 3 4 5

13. instill an attitude of fair play among your 1 2 3 4 5
athletes?

14, coach individual athletes on technique? 1 2 3 4 5

15, build the self-conﬁdence of your athletes? 1 2 3 4 5

16, develop athletes' abilities? 1 2 3 4 5

l7. Maximize your team’s strengths during 1 2 3 4 5
competition?

18. Recognize talent in athletes? 1 2 3 4 5

19. promote good sportsmanship? 1 2 3 4 5

20, detect skill errors? 1 2 3 4 5

21. adjust your game strategy to fit your team’s 1 2 3 4 5
talent?

22, teach the skills of your sport? 1 2 4

23, build team conﬁdence? 1 2 3 4

24. instill an attitude of respect for others? 1 2 3 4 5

 

 

 

 

 

 

 

97

Appendix B
Coaches Background Information Questionnaire

Please check only one answer per question-
1. Your sex: (1) Male, (2) Female

2. Primary sex of your team: ( 1) Male , (2) Female

3. Level/age group of team coaching. (e.g. U-19, Pee-wee):

 

4. Your ethnic afﬁliation: _ (l) Caucasian,
__ (2) African American
__ (3) Native North American Indian
_ (4) Asian American
__ (5) Hispanic
__ (6) Other

 

5.Your Age:

6. Educational Background: (check highest level competed)

(1) Did not complete High School _(2) High School graduate

(3) Less than 2 years college/tech _(4) 2 or more years college
(5) Bachelor’s degree _(6) Some Master Level work
(7) Master’s degree _(8) Some Doctoral level work

(9) Completed Doctorate

7. If attended college, what was undergraduate major? . Master’s
major

 

Doctorate degree?
8. Your Level of USA Hockey Coaching certiﬁcation? 1 2 3 4 5

9. Present position. (1) Head, (2) Assistant

 

10. Total numbers of years coaching hockey (Head) (Assistant).

11. Number of years playing. (1) Youth; _(2)High School (3) Junior A, B
at each level
_(4)Major Junior _(5) College (6) Professional

12. Approximately how many hours per week do you spend involved in fulﬁlling your coaching
duties, planning etc. ? In season Out of season

 

13. Are you paid for your present coaching duties? (1) NO (2) Yes

98

Appendix C
Coaching Satisfaction/ Support Questionnaire

Not at all Very/A lot
1. How successful do you feel as a coach 0 1 2 3 4 5 6 7 8 9
2. How much do you enjoy coaching hockey 0 1 2 3 4 5 6 7 8 9
3. I feel that my players like me 0 1 2 3 4 5 6 7 8 9
4. I feel that my players like hockey 0 1 2 3 4 5 6 7 8 9
5. I would like to coach again next season 0 1 2 3 4 5 6 7 8 9
6. How much do you know about hockey? 0 l 2 3 4 5 6 7 8 9

7. How much do you know about coaching kids?0 1 2 3 4 5 6 7 8 9

Poor Excellent
9. How would you rate the overall ability of the
athletes on your team this year? 0 1 2 3 4 5 6 7 8 9

10. How would you rate the overall improvement 0 1 2 3 4 5 6 7 8 9
of your athletes so far this season?

11. In comparison with your perception of the ideal youth sports program, how would
you rate the support given to you by the parents of your athletes?

0123456789

12. In comparison with your perception of the ideal youth sports program, how would
you rate the community support for your team? 0 1 2 3 4 5 6 7 8 9

13. In comparison with your perception of the ideal youth sports program, how would
you rate the support given to you by the organization that runs your program?

0123456789

14. In comparison with your perception of the ideal youth sports program, how would
you rate the support given to you by your athletes? 0 1 2 3 4 5 6 7 8 9

99

Appendix D
Coaching-Efﬁcacy Study Consent Form

You are being asked to participate in a study conducted by graduate student Craig
Payment under the supervision of Deborah Feltz, Ph.D., from Michigan State University.
The purposes of this study are to examine 1) Coaching conﬁdence in motivational
behaviors and 2)Speciﬁc behaviors related to coaching satisfaction. It is believed that the
project will have practical applications within coaching education.

As part of this research, you will be asked to complete questionnaires during the hockey
season. The questionnaires (approximately 10 minutes to complete) will contain items
speciﬁc to coaching confidence and coaching behaviors.

Your participation in this study will remain private and confidential, no one except the
principal investigators will have access to these responses or to participation records. At
the end of the project, responses will be presented at the group level to ensure the
confidentiality of individual responses. Group-based ﬁndings will be made available to
those who are interested. Your privacy will be protected to the maximum extent
allowable by law.

Your participation in this study would be greatly appreciated. However, please know that
you may refuse to participate or withdraw from the project at any time and without
penalty, you may also refuse to answer any speciﬁc question. If you would like to
participate, please sign this form and return it.

If you have any questions concerning this study, please contact Dr. Deborah Feltz, at
517.355.4732 [dfeltz@msu.edu] or Craig Payment at 517.355.4763
[payment5@msu.edu]. Additionally, If you have any questions or concerns regarding
your rights as a study participant, or are dissatisﬁed at any time with any aspect of this
study, you may contact - anonymously, if you wish - Peter Vasilenko, Ph.D., Chair of the
University Committee on Research Involving Human Subjects (UCRIHS) by phone:
(517) 355-2180, fax: (517) 432-4503, email address: ucrihs@msu.edu, or regular mail:
202 Olds Hall, East Lansing, MI 48824.

Thank you for your time and cooperation,

 

 

 

 

Dr. Deborah Feltz, Principal Investigator Date
Craig Payment, Graduate Student Date
I, . have been informed of the study and agree to
participate.

Signature Date

100

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