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Motivation In High School Sport Athletes: AStructural Equation ModelKristin L. ZomermaandThe Florida State University

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Recommended CitationZomermaand, Kristin L., "Motivation In High School Sport Athletes: A Structural Equation Model" (2012). Electronic Theses, Treatisesand Dissertations. Paper 5466.

THE FLORIDA STATE UNIVERSITY

COLLEGE OF EDUCATION

MOTIVATION IN HIGH SCHOOL SPORT ATHLETES:

A STRUCTURAL EQUATION MODEL

By

KRISTIN L. ZOMERMAAND

A dissertation submitted to the

Department of Educational Psychology and Learning Systems

College of Education

in partial fulfillment of the

requirements for the degree of

Doctor of Philosophy

Degree Awarded:

Fall Semester, 2012

ii

Kristin L. Zomermaand defended this dissertation on October 10, 2012.

The members of the supervisory committee were:

Robert Eklund

Professor Directing Dissertation

Lynn Panton

University Representative

Gershon Tenenbaum

Committee Member

Jeannine Turner

Committee Member

The Graduate School has verified and approved the above-named committee members, and

certifies that the dissertation has been approved in accordance with university requirements.

iii

To Corey, I could not have done this without you.

iv

ACKNOWLEDGEMENTS

Many people deserve acknowledgements for their help in this lengthy process. Thanks to Dr.

Robert Eklund for your guidance through this process. Thanks to Dr. Yanyun Yang for all your

knowledge and help during data analysis. Thanks to the faculty and staff at Louisiana College for

all your support over the last two years. Thanks especially to the assistance of my students at

Louisiana College; I appreciated your efforts and enthusiasm. Thanks to my family and friends

for your support. A special thanks to Corey Webster for his ideas and positive attitude.

v

TABLE OF CONTENTS

List of Tables ................................................................................................................................ vii

List of Figures .............................................................................................................................. viii

Abstract .......................................................................................................................................... ix

1. CHAPTER 1 ............................................................................................................................1

1.1 Introduction ....................................................................................................................1

1.2 Literature Review...........................................................................................................2

1.2.1 Youth Sport Participation and Attrition .............................................................2

1.2.2 Self-Determination Theory (SDT) .......................................................................

1.2.3 Empirical Support for SDT ................................................................................7

1.2.4 Achievement Goal Theory ...............................................................................11

1.2.5 Motivational Climate .......................................................................................12

1.2.6 Empirical Links between SDT and Motivational Climate ...............................17

1.2.7 Psychological and Behavioral Consequences of Motivation ...........................20

1.2.8 Multi-Level Modeling ......................................................................................21

1.2.9 Purpose and Hypotheses ..................................................................................21

2. CHAPTER 2 ..........................................................................................................................28

2.1 Method .........................................................................................................................28

2.1.1 Participants .......................................................................................................28

2.1.2 Measures ..........................................................................................................29

2.1.3 Procedures ........................................................................................................31

2.1.4 Data Analysis ...................................................................................................32

3. CHAPTER 3 ..........................................................................................................................35

3.1 Results ..........................................................................................................................35

3.1.1 Descriptive Statistics and Data Parceling ........................................................35

3.1.2 The Multi-Level Model....................................................................................41

3.1.3 Hypothesized and Modified Models ................................................................44

3.1.4 Indirect Effects .................................................................................................47

4. CHAPTER 4 ..........................................................................................................................51

4.1 Discussion ....................................................................................................................51

4.1.1 Discussion of Hypotheses ................................................................................51

4.1.2 Discussion of Indirect Effects ..........................................................................56

4.1.3 Limitations .......................................................................................................58

4.1.4 Future Research ...............................................................................................59

4.1.5 Conclusion .......................................................................................................59

APPENDICES ...............................................................................................................................61

A. MEASURES .........................................................................................................................61

B. CONSENT AND ASSENT FORMS ...................................................................................68

vi

C. IRB APPROVAL LETTERS ...............................................................................................70

D. RECRUITMENT E-MAIL ....................................................................................................74

REFERENCES ..............................................................................................................................75

BIOGRAPHICAL SKETCH .........................................................................................................86

vii

List of Tables

1 Demographic Information ..................................................................................................28

2 Participant Sport Experience..............................................................................................29

3 Descriptive Statistics of the Manifest Variables ................................................................37

4 Correlation Matrix for the Manifest Variables .................................................................38

5 Standardized Loadings for Individual CFA’s ....................................................................39

6 Reliability Statistics for Each of the Subscales..................................................................41

7 ICC and Design Effect Values for the Parceled Observed Variables ................................43

8 Model Fit Indices ...............................................................................................................44

9 Indirect Effects for Modified Model 2 ...............................................................................48

viii

List of Figures

1 Predicted relationships at the individual level ...................................................................24

2 Predicted relationships at the team level. ...........................................................................25

3 Predicted positive relationships at the individual level......................................................26

4 Predicted negative relationships at the individual level .....................................................26

5 Predicted positive relationships at the team level ..............................................................27

6 Predicted negative relationships at the team level .............................................................27

7 Standardized loadings and residuals for the hypothesized model. ...................................45

8 Standardized loadings and residuals for Modified Model 1 ..............................................46

9 Standardized loadings and residuals for Modified Model 2 ..............................................50

ix

Abstract

There is a movement in our culture today to keep young people physically active. Sport is one

avenue for physical activity, but teenagers involved in competitive sport often quit and never

return to any sort of physical activity (Vanreusal et al., 1997). In light of this, motivational

aspects of what keeps high school athletes involved in sport are important to consider. In the

current study, athletes on 31 high school sport teams were surveyed to assess their perceptions of

motivational climate, motivational needs, motivational regulations, and psychological outcomes.

In line with self-determination theory, results for the study showed that a perceived task climate

supported the athletes’ motivational needs. While relatedness and competence satisfaction were

integral parts of the model as anticipated, autonomy satisfaction did not have significant

associations with any other variable. Autonomous and controlled motivations were observed to

have significant relationships with the outcome variables of athletes’ perceived performance,

sport satisfaction, and intention to continue sport participation. Furthermore, a number of

variables were observed to act as potential mediators in the model. In sum, facets of sport

motivation including motivational climate and personal motivation regulations had an impact on

how satisfied high school athletes were in their sports, their perceptions of their performance,

and their intention to continue to participate in sport in the future.

1

Chapter 1

Introduction

A poster on the wall of a high school gymnasium featuring a smiling teenager playing

basketball says: “I used to play for my parents and my coach, but now I play for me.” This poster

exemplifies the net message of most of the theories of motivation that sport psychology

researchers have been working with and developing in recent decades. How does one move

from playing for others to playing for oneself? In the following pages, topics concerning youth

sport participation are discussed. These topics include youth sport participation, motivational

theories, and constructs, psychological and behavioral consequences of motivation, and

hierarchical modeling. In this dissertation study, athletes’ motivation in high school sport was

assessed to predict their intention to continue participation in sport, sport satisfaction, and sport

performance.

The first topic examined in the present study is the intention of youth to continue in sport.

Youth sport participation patterns are discussed and factors associated with continuing in sport

are examined. One cannot discuss teenage participation without acknowledging that there are

several other activity options available, but the concern for this study is an athlete wishing to

continue in sport and being satisfied in the sport.

The primary factor in youth sport participation for the current study is youth athlete

motivation. Two theories of motivation dominate the sport psychology literature: self-

determination theory and achievement goal theory. Self-determination and achievement goal

theorists speak of motivation from two different perspectives, but each describe fundamental

aspects of motivation in youth sport. Motivational climate is a construct related closely to

dispositional achievement goal theory, but instead of focusing on the nature of the individual,

motivational climate researchers focus on the environment surrounding the individual. The

coach is part of that environment and spends a great amount of time with the athlete. Coaches

have an immense impact on what happens in practice and on the playing field. The coach can

also be implicated in needs satisfaction support which is important in self-determination theory.

Therefore, the coach’s role is valuable to discuss and evaluate.

In the current study, structural equation modeling and multi-level modeling are discussed

in relation to nested data. Athletes on teams have been considered to be nested data and the

relationships of the motivational variables within these teams are discussed. Issues within

2

structural equation modeling and multi-level modeling like intraclass correlations and data

parceling are also mentioned.

Several high school sports teams participated in this study. The athletes’ self-reports of

their perceptions of their coaches, motivational needs and regulations, and well-being in sport

were assessed using structural equation modeling. Results of the structural equation model were

evaluated and discussed including direct effects within the model and indirect effects to

determine if mediation was occurring. Finally, conclusions about how motivation affects the

outcomes of performance, sport satisfaction, and intention to continue participation are

addressed.

Literature Review

Youth Sport Participation and Attrition

Youth participation in sport has continually increased over the years (Ewing & Seefeldt,

2002), especially with the growth of agency-sponsored sport programs across the country

(Seefeldt & Ewing, 1997). However, as increasing numbers of younger athletes participate,

more and more teenagers are becoming inactive (Corbin, Pangrazi, & Le Masurier, 2004), which

some researchers believe is one of the causes of the highest youth obesity rates in history (Lee,

Wechsler, & Balling, 2006). Vanreusel et al. (1997) conducted one of the few longitudinal

studies on youth sport participation and adherence to sport. Their findings indicated three

categories of sport participation. The first category consisted of those that never participated in a

sport. If a child never participated in sport, they were not going to participate in sport in the

future. The second and third categories were recreational sport athletes and competitive sport

athletes. Those who competed recreationally as youth were more likely to continue to participate

in recreational sport, but that those who participated in competitive environments as youth were

most likely to leave sport as teenagers and never participate in sport again. Vanreusal et al.

(1997) did not offer psychological reasons for this participation-dropout pattern. However, the

differences in reasons for sport participation must be studied in relation to and the environment

within which sport activity takes place. Knowing the reasons and motivations young people

participate in sport can help directing the management of sport programs as to how to promote

those facets deemed important for their programs.

Attrition from sport can be attributed to psychological, physical, and social reasons

(Fraser-Thomas, Cote, & Deakin, 2008; Weiss, Kimmel, & Smith, 2001; Weiss & Smith, 2002).

3

Several factors distinguished adolescent swimmers who dropped out and those who persisted in

swimming (Fraser-Thomas et al., 2008)). Adolescent sport drop-outs were more likely to have

specialized early, have fewer activities outside of swimming, and spend less time in “free play”

swims than those who persisted in their sport. Those who dropped out of swimming were also

less likely to experience any significant degree of one-on-one coaching. Drop-outs tended to

exhibit talent by winning races early in their swimming careers and, hence, were exposed to

more advanced training at very early ages. Drop-outs were also more likely to have fewer

friendships on their swim teams and to have parents who had been successful athletes themselves

(Fraser-Thomas et al., 2008). In additional studies, friendship and enjoyment within the sport are

important predictors of attrition and persistence, especially among young athletes (Weiss et al.,

2001; Weiss & Smith, 2002). In sum, a variety of factors have been highlighted as influential in

the choice to drop-out. These factors may play a role in the absence of or decline in participation

motivation (Fraser-Thomas et al., 2008).

While Fraser-Thomas et al. (2008) indicated that drop-outs experienced a relative

absence of one-on-one coaching, they did not describe the type of coaching that these dropouts

had experienced—and this coaching may have also contributed to swimmer attrition. One such

study of how the coach may affect attrition was conducted by Barnett et al. (1992). These

researchers evaluated the impact of a coaching intervention on the attrition of the athletes.

Coaches were taught behaviors that would promote a positive environment for the athletes. The

desirable behaviors included reinforcement of effort and good performance, corrective

instruction, mistake contingent encouragement, and technical instruction. The coaches were also

instructed to focus on effort and enjoyment, and were told to keep a self-reflection journal. The

intervention discouraged certain behaviors as well, including non-reinforcement of positive

behavior, punishment, punitive instruction, and blame. They found that those athletes whose

coaches had received the intervention were more likely to continue their sport involvement and

were less likely to leave their sport because of a negative coach-related experience.

Self-Determination Theory (SDT)

Self-determination was first described as an individual’s perception of the amount of

control that he or she feels over the environment and what happens to him or her (Deci, 1980).

As the theory has evolved, the theorists have broadened the theory to include more than the

4

singular issue of control. However, the idea that feeling self-determined promotes intrinsic

motivation and responsibility in individuals persists (Deci, 1995; Deci & Ryan, 1985).

Deci and Ryan (1985) assert that there are three general types of motivation: intrinsic,

extrinsic and amotivation. “Intrinsic motivation is the innate, natural propensity to engage one’s

interests and exercise one’s capacities…” (Deci & Ryan, 1985, p. 43). In other words, intrinsic

motivation is an individual’s natural desire to accomplish a task. Extrinsic motivation, in its

least self-determined form, involves the desire to complete an assignment or task to earn a

reward or avoid a punishment (Deci, 1980). However, rewards or punishments do not need to be

present for motivation to be extrinsic. Extrinsic motivation is also characterized by reasoning

that originates externally from the individual, such as a young boy cleaning his room because his

parent has taught him that good children clean their rooms. The boy does not clean the room

because he finds enjoyment or intrinsic satisfaction from the task, but instead because of an

external value placed on the behavior that the child has internalized to some degree. Thus, the

motivation is extrinsic in nature. Finally, amotivation, which is motivation that does not have an

aim like intrinsic or extrinsic motivation, is evident by the complete lack of desire to complete a

task. All three forms of motivation are influenced by individual differences and the environment

(Deci & Ryan, 1985).

Cognitive Evaluation Theory. Cognitive Evaluation Theory (CET) is a sub-theory of

SDT. CET is based on the premise that each individual has basic needs and that the fulfillment

of those needs represents the basis for motivation (Deci & Ryan, 1985). The three basic needs

essential in CET are autonomy, competence, and relatedness. These separate needs can work

together to produce self-determined motivation. Competence is the belief that one can complete

the task. When children choose to play a game that is too difficult for them, they will quickly

lose interest and move on to a task that is more within their skill set. Also, rewards and feedback

(or reinforcement), affect perceived competence which, in turn, produces intrinsic motivation if a

sense of autonomy is also present (Ryan & Deci, 2000). Autonomy is the feeling that the person

is in control of his/her actions and not being controlled by others. Activities that have self-

determining properties produce a desire to do the activity for its own sake and not for the sake of

anything else. Allowing a state of free choice promotes an autonomous environment (Deci &

Ryan, 1985). The third need of CET is relatedness. Ryan and Deci (2000) state that relatedness

is a complex need that varies in intensity depending on the task. A person is able to have

5

intrinsic motivation on a solitary activity without feeling connected to another person, but on

another task may need to feel related to teammates or a teacher in order be intrinsically

motivated. They also state that relatedness would be essential for overall well-being because

humans are social beings.

Organismic Integration Theory. As previously stated, motivation is a

multidimensional construct. It is fluid and represents a continuum from amotivation to intrinsic

motivation. Organismic Integration Theory (OIT) is another sub-theory of SDT that is focused

upon the fluid process of internalization of motivation. Internalization is the process by which

one takes external motivators and makes these his or her own (Deci & Ryan, 1985). The

continuum begins with amotivation, and then moves through the four regulations of extrinsic

motivation represented in OIT. The first stage is called external regulation. External regulation

is characterized by one acting in order to gain rewards or avoid the consequences of the action.

This is the least self-determined form of extrinsic motivation (Deci & Ryan, 1985). An

illustration of this stage is a young boy participating in his sport only because his parents are

giving him money to do so. The second stage, introjected regulation, is ego-involved. The

athlete needs the approval of others to perform the task. Introjected regulation represents the

first step towards internalizing the values that are present in the situation (Deci & Ryan, 1985).

The athlete now is participating in his sport not solely for the monetary reward, but also because

he knows that he would gain his parents’ approval. In the third stage, identified regulation, the

individual starts to acknowledge the purposes behind the task and identifies those values as his

own. Identified regulation is the beginning of a more self-determined form of motivation. At

this stage, the athlete starts to value participation for reasons like his own fondness for physical

fitness or existing sport friendships. Integrated regulation, the fourth stage, occurs when the

values that were once imposed extrinsically are not only owned by that individual, but he is also

able to fully integrate those values with other viewpoints on the matter and come to conclusions

on his own (Deci & Ryan, 1985). Finally, intrinsic motivation is the culmination of the theory

and represents the ideal motivational state (Ryan & Deci, 2000). External regulation and

introjected regulation are also known as the least self-determined or controlled motivation

regulations and, while still external in nature, identified and integrated regulations, along with

intrinsic motivation, are known as self-determined or autonomous motivation regulations

(Lonsdale, Hodge, & Rose, 2009).

6

In OIT, the process of internalization is postulated to depend on several situational and

individual factors. Three factors are especially important given the basic needs of autonomy,

competence, and relatedness. These factors are competence, control, and conflict. When a

person feels competent, the process of moving from extrinsic to intrinsic motivation becomes

simpler (Deci & Ryan, 1985). For instance, the athlete who is only playing a sport because he

knows it will get him a reward from his parents may start to appreciate the sport for its own sake

if he feels competent in the sport. Assessment of control is also important in the internalization

process. If the individual feels out of control or feels undue pressure coming from external

sources, the internalization process may be hindered. On the other hand, if the athlete feels in

control of the situation, the internalization process will proceed smoothly to intrinsic motivation.

Finally, a sense of internal conflict will also hinder the process. For instance, if a girl’s one

desire is to play the piano, but her parents force her to play a sport instead, this will result in a

conflict of values. The sport involvement will only be extrinsically motivated because the true

intrinsic motivation is directed elsewhere (Deci & Ryan, 1985). If her parents support her piano

playing, she will not have a conflict of values, will be intrinsically motivated to perform, and,

ultimately, enjoy the experience more.

Competition or the experience of winning and losing is an essential part of sport. The

concept of competition implies that two individuals or teams will vie to overcome each other.

Competition as a motivator has been a source of contention in the literature because it is extrinsic

in nature to want to win and extrinsic motivation has negative connotations. Deci and Ryan

(1985) address the issue of competition as an extrinsic motivator. They acknowledge that

competition is extrinsic in that it is an external consequence for an activity. However, the degree

to which winning motivates participation varies. As the internalization process continues,

competition may become identified with the individual and integrated with the individual’s

values. This would indicate a more self-determined form of extrinsic motivation. Yet, if the

pressure to win creates a need to win in order to increase self-esteem, this may undermine

intrinsic motivation (Deci & Ryan, 1985).

In summary, SDT is a multidimensional theory of motivation. The motivation continuum

ranges from amotivation to extrinsic regulation, introjected regulation, identified regulation,

integrated regulation, and fully intrinsic motivation. The theory also maintains that an

individual’s basic psychological needs of competence, autonomy, and relatedness are necessary

7

for one to move along the continuum to intrinsic motivation. An athlete who feels in control, has

no conflict of values, and believes he is competent in his sport, and has positive personal

relationships will be intrinsically motivated to participate.

Empirical Support for SDT

Several researchers have attempted to empirically ascertain the legitimacy of SDT in

many different populations and situations (Deci, Eghari, Patrick, & Leone, 1994; Grolnick &

Ryan, 1989; Taylor & Ntoumanis, 2007; Wilson & Rodgers, 2004). These populations and

situations range from youth to adult, classrooms to the playing field, and coaches to teachers.

Motivational strategies are important to study in each of these areas (Motl, 2007).

Satisfaction of needs. CET theorists state that there are three psychological needs that

are necessary to satisfy in order to produce intrinsic motivation: autonomy, competence, and

relatedness. McDonough and Crocker (2007) evaluated the degree to which these needs are

predictors of self-determined motivation. They especially looked at the significance of

relatedness, which they claimed was previously ignored in research. They found among adult

Canadian dragon-boaters, who row a canoe in teams of 18 to 20 people, that competence and

relatedness were the best predictors of self-determined motivation. Autonomy was not found to

be as strong of a predictor. Because being unified and following orders is imperative for dragon-

boating success, relatedness and competence established self-determined motivation. This may

clarify why relatedness rather than autonomy was more important in this particular study

(McDonough & Crocker, 2007).

The presence of any controlling or authoritative figure can have a negative impact on the

autonomy of the athletes (Grolnick & Ryan, 1989; Plant & Ryan, 1985) and being publicly self-

conscious can also be detrimental to perceptions of autonomy (Plant & Ryan, 1985). In an

investigation of elementary school children revealed, however, that parents who supported

autonomy were shown to increase autonomy in their children and, in turn, intrinsic motivation

(Grolnick & Ryan, 1989). These children also had higher academic perceived competence and

performed better in school. In addition, Grolnick, Ryan, and Deci (1991) found that perceived

competence was a better predictor of academic performance than autonomy.

Need satisfaction has been studied in educational situations as well as sport (Black &

Deci, 2000). Children, and especially young adolescents, need to be engaged, stimulated, and

have a feeling of independence in activities in order for intrinsic motivation to be present

8

(Shernoff & Vandell, 2007). Teachers and coaches, therefore, need to promote autonomy and

challenge for their students or athletes. However, one study found that teachers provided

autonomy support if they perceived that their students were already intrinsically motivated

(Taylor & Ntoumanis, 2007). In contrast, the same researchers also found that the teachers who

had high levels of self-determined motivation to teach provided more autonomy and emotional

support to their students, which increases levels of intrinsic motivation in their students (Taylor

& Ntoumanis, 2007). Ferrar-Caja and Weiss (2002) found that students in elective courses felt

more autonomous and had more self-determined motivation than students in required courses.

They also found that students in elective courses had higher levels of perceived competence than

those in required classes.

Internal perceived locus of causality, the degree to which one perceives that he/she is the

primary cause of what happens in life, is closely related to SDT because autonomy is an essential

aspect of both concepts (Turban, Tan, Brown, & Sheldon, 2007). Turban et al. (2007) studied

perceived locus of causality in educational settings and related it to SDT. They found that

students who had an internal rather than external perceived locus of causality used more effective

study strategies and exerted more effort in their classes. In other words, the students believed

that they were in control of their studies and were more intrinsically motivated to work hard and

perform well in their classes.

In a closely related study of perceived control and motivation, researchers divided

motivation in terms of the level of control perceived by the students (Ratelle, Guay, Vallerand,

Larose & Senecal, 2007). The levels of control utilized by the researchers were high

autonomous/ high controlled, moderate autonomous/ moderate controlled, and high controlled/

amotivation. The high autonomous/high controlled group showed the most persistence and

intention to persist in school (Ratelle et al., 2007). Perceived control is related to higher levels of

intrinsic motivation and persistence in academic settings.

Ferrar-Caja and Weiss (2000) found that self-determined motivation was beneficial in

physical education classes. Students who perceived their class environment as promoting of

learning and participation felt more self-determined. The children also reported this type of

setting as more enjoyable and fun. Other researchers have reported that young people not only

experience more enjoyment when feeling autonomous and self-determined, they also report more

intentions to continue in the task in which they are participating (Chatzisarantis, Biddle, & Meek,

9

1997).

Standage, Duda, and Ntoumanis (2003a) also assessed the value of the psychological

needs posited by SDT. These researchers found that while competence was the largest predictor

of self-determined motivation, all of the psychological needs (competence, relatedness, and

autonomy) were essential to the presence of intrinsic motivation. Unlike some other studies

(Deci et al., 1994; Hagger, Chatzisarantis, Culverhouse, & Biddle, 2003), however, Standage et

al. (2003a) found that autonomy was not as strong of a predictor of intrinsic motivation as

competence or relatedness needs. This study also showed a connection between self-determined

motivation and intention to continue in physical activity. Wilson and Rodgers (2004) conducted

a similar study appraising needs satisfaction and intention to exercise; self-determined

motivation was again found to an important predictor of intention to continue to exercise.

Additionally, researchers trained exercise class instructors in an intervention featuring

key aspects of SDT (Edmunds, Ntoumanis, & Duda, 2007). The researchers created two groups:

an SDT-trained instruction group and a control group. The SDT-trained instructors provided

autonomy support and positive feedback for the members of the exercise class. The leaders of

the control classes provided very little feedback and encouragement. The researchers found that

SDT class participants increased their levels of competence, perceived autonomy, and perceived

relatedness over time. The control group only increased in perceptions of competence. Those in

the SDT group attended class on a more regular basis, and had higher levels of affect than those

in the control group. Also, autonomy support and interpersonal involvement were found to be

predictors of intention to participate in exercise, supporting SDT. However, even though

participation in the SDT intervention classes was supposed to produce higher levels of self-

determined motivation, increased introjected regulation was also observed. The authors

explained this by the apparent social comparison that is inevitable in a class situation (Edmunds

et al., 2007).

The relationship between intention to continue participation in physical activity and

autonomy support was also researched by Goudas and Biddle (1995). They found that where

there was an autonomy supportive environment, intrinsic motivation was higher. This led in turn

to higher intentions to exercise. However, competence was found to be mediated by

performance in its prediction of intrinsic motivation. The outcome of the task affected the level

of the competence which the participant felt and lowered or raised intrinsic motivation. Guay,

10

Boggiano, and Vallerand (2001) subsequently investigated the effects of perceived competence

and autonomy on intrinsic motivation and found that intrinsic motivation appears to manifest

itself only when both are experienced in some degree.

Coaches, teachers, and parents have considerable influence in producing a needs

supportive atmosphere in sport, physical education, and exercise settings (Papaiounnou,

Ampatzoglou, Kalogiannis, & Sagovits, 2008). If a coach promotes autonomy and uses praise

instead of punitive techniques, the athletes will acquire higher needs satisfaction and self-

determined motivation, which includes intrinsic motivation, identified regulation, and integrated

regulation (Conroy & Coatsworth, 2007). Also, coaches who utilize negative-focused coaching

strategies have a negative effect on the situational motivation of athletes (Conroy, Kaye, &

Coatsworth, 2006).

Coatsworth and Conroy (2006) found that coaches who were trained to support the

psychological needs of the athletes produced athletes with higher levels of self-esteem,

especially for those athletes who had low self-esteem before the coach training took place.

Likewise, Gagne, Ryan, and Bargmann (2003) found that gymnasts reported the highest levels of

well-being when they felt that their psychological needs were being satisfied. If the coach was

perceived to be personally involved, the gymnasts had higher levels of self-esteem, and if the

coaches and parents were autonomy supporting, the gymnasts were more likely to have a self-

determined form of motivation. Interestingly, however, children of over-involved parents had a

more controlled form of motivation. Additionally, girls who had low self-esteem at the

beginning of the season seemed to benefit more from having a need supportive environment than

any other group (Gagne et al., 2003).

Furthermore, one’s experience of the integration of motivation regulations affects not

only in-the-moment motivation, but also the persistence of intrinsic motivation over time

(Pelletier, Fortier, Vallerand, & Breire, 2001). Pelletier et al. (2001) conducted a prospective

study of adolescent athletes, assessing motivational aspects and persistence in sport at three

different time points. They found that athletes with self-determined motivation had the highest

rate of persistence across all three time points while athletes assessed as being externally

regulated were less likely to persist throughout the entire study. Amotivated athletes were the

most likely to drop out. Wilson and Rodgers (2004) also found that those who had higher levels

of self-determined motivation had higher levels of intent to continue physical activity than those

11

with less self-determined motivations.

Situational and personal factors. Even if the teacher and/or coach are autonomy

supporting, there are other factors that could undermine intrinsic motivation. One such factor is

event outcome (i.e., winning, losing) because of potential associated perceptions of success or

failure (Reeve & Deci, 1996). Game outcome was found to affect intrinsic motivation only

when the athletes felt pressure to win. Participants’ self-worth seemed dependent on an extrinsic

event and the pressure to preserve their self-worth may have undermined their intrinsic

motivation. When the athlete did not feel pressure to achieve a victory, intrinsic motivation was

not affected (Reeve & Deci, 1996).

Gender is one personal factor that may be observed to act as moderating variable of need

satisfaction in SDT. Ntoumanis (2001a) found that females in physical education classes need to

feel more relatedness than males do. He also found that perceived competence seemed to be the

most important factor for building intrinsic motivation regardless of gender. Overall, Ntoumanis

(2001a) found that the satisfaction of all three psychological needs were necessary for fully self-

determined motivation.

Achievement Goal Theory

Some athletes seem to prefer competition while the sole purpose for others appears to

relate to self-improvement. Achievement motivation theoretical perspectives have been evident

in psychology for decades. deCharms (1968), for example, described achievement motivation as

“the disposition to strive for satisfaction derived from success in competition with some standard

of excellence,” (p. 181). This definition implies that motivation is a disposition or characteristic

of a person to focus on a goal and be motivated to achieve that goal. Proponents of achievement

goal theory (AGT) utilize this trait perspective as well (Nicholls, 1984).

Defining goal orientations is complex. Two facets of AGT are commonly discussed.

The first is the aforementioned dispositional achievement goal orientations (Nicholls, 1984).

The second is goal involvement varies from moment to moment, and is more situationally

dependent (Ames. 1992). A person can have a mastery goal for a task in one situation, and

another goal, as in wanting to perform better in the competition, in a different situation. Both of

these viewpoints are discussed throughout the coming sections.

Task and ego orientation. Athletes’ achievement goals can be divided into two main

goal orientation categories: ego and task orientation (Duda, 1989; Nicholls, 1984). Having an

12

ego (or performance) orientation means that a person is predisposed to view success in terms of

winning or in comparison to others. Having a task (or mastery) orientation indicates a will to

improve oneself in the task that one is undertaking (Duda, 1989; Duda, Chi, Newton, Walling, &

Catley, 1995; Duda & White, 1992; Grieve, Whelan, Kottke, & Meyers, 1994; Nicholls, 1984;

Williams & Gill, 1995). It must be noted that these are not ends of a continuum, but instead a

multidimensional approach can be utilized in which an athlete can be both high in task

orientation and ego orientation (Wang & Biddle, 2001).

An athlete who is high in task orientation tends to take an internal perspective to judge

him or herself (Nicholls, 1984). Also, a task-oriented athlete tends to focus on factors that are in

his or her control, such as effort. Those who are task-oriented relate increased effort with

increased ability, and take greater pride when mastering a skill (Nicholls, 1984). For instance, a

swimmer who is high in task orientation will increase effort to improve her personal times rather

than focusing on winning a race in most cases. If the swimmer was low in task orientation,

personal improvement would not be the primary motivator in increasing effort.

In contrast, having high levels of ego orientation indicates a tendency for the athlete to

strive to win competitions and compares personal performance with an opponent’s or even a

teammate’s performance (Duda, 1989; Duda & White, 1992; Duda et al., 1995; Grieve et al.,

1994; Nicholls, 1984; Williams & Gill, 1995). Ego-oriented athletes tend to take an external

perspective and focus on these factors and their effects on performance (Nicholls, 1984; Vealey,

Hayashi, Garner-Holman, & Giacobbi, 1998). Those individuals who are ego-oriented are also

less likely to relate effort to success, but instead attribute successes to their ability (Duda & Hall,

2001). For example, an ego-oriented athlete may fail to exert high levels of effort when

confronted with failing to win a competition (Martin & Gill, 1991).

Motivational Climate

Although deCharms (1968) described achievement motivation as dispositional, he

claimed that motivation can be changed given an ego-involving or task-involving situation. The

idea that many factors affect an athlete’s goal orientation has been persistent in the literature.

Many situational and environmental factors are influential on the goal orientation of an athlete.

Motivational climate is the perceived environmental influence on the athletes. The athletes’

perceptions and interpretations of the situational influences are the central factors (Ames, 1992).

Perception is the assigning of others’ behaviors to certain categories, and, thereby, assigning the

13

individual as to what kind of person s/he is (Barrett, 2006). In the case of motivational climate,

the athlete’s perceptions of their coaches’, teammates’, and parents’ behaviors categorize the

motivational climate into one of two categories. The motivational climate can be perceived as

task-involved (mastery) or ego-involved (performance) as in achievement goal research. A task-

involved climate is one that is perceived to require a focus on the mastery of tasks and

improvement. An ego-involved climate is one that is perceived to require a focus on winning

competitions or being better than others. Just as in goal orientation research, mastery climate is

also thought to be more beneficial to the athlete than an ego-involved climate (Ames, 1992).

Perceived mastery climate has been shown to have a positive relationship with overall

satisfaction and higher perceived ability than performance climates (i.e. ego) (Boixados, Cruz,

Torregrosa, & Valiente, 2004). Those in a mastery climate were also more likely to have

positive views of fair play, while those in performance oriented climates were more likely to

support cheating as a way to get ahead in sports (Boixados et al., 2004).

In an experiment testing the effects of an ego-involved condition versus a task-involved

condition on the self-esteem and enjoyment of individuals on a novel task, researchers found that

the ego-involved condition led to less free-choice task participation and less enjoyment of the

task (Ryan, Koestner, & Deci, 1991). Ryan et al. (1991) hypothesized that when the

environment is ego-involved one’s self-esteem is put at risk because it is contingent upon the

outcome of the situation as in a win or a loss. Seeing the activity through to the outcome, then, is

necessary in order to safeguard one’s self-esteem.

Verbal feedback from those around the athlete has been shown to have a substantial

impact on the perceptions of the motivational climate. Merely the presence of any type of

feedback was shown to increase perceptions of both task and ego oriented climates (Viciana,

Cervello, & Ramirez-Lechuga, 2007). In a Smith, Fry, Ethington, and Li (2005) study, high

school female basketball players who perceived the verbal feedback from the coach as positive

and encouraging were more likely to view the climate as mastery oriented. On the other hand, if

the verbal feedback was viewed as negative and punitive, the climate was most likely to be

perceived as performance oriented. This study seems to show the direct connection between

coach behaviors and perception of climate.

Motivational climate and achievement goals are intertwined. However, motivational

climate seems to have been observed to have a greater impact on goal orientations than goal

14

orientations have on motivational climate. Gano-Overway and Ewing (2004), for example,

found that collegiate students participating in physical education classes changed their goal

orientations to match the perceived motivational climate of the class. A student who was high in

ego orientation at the onset of a class that was perceived as having a mastery involved climate

would experience a change in goal orientation to task as the class progressed. The opposite was

also found to exist. If a student who was high in task orientation experienced a performance

involved class, s/he would become more performance oriented over the duration of the class.

Because of these findings, the researchers concluded that teaching or coaching style would have

a significant impact on students or athletes’ views of how they measured their own improvement.

Authority figures are extremely influential on the climate of the situation (Ames, 1992).

Ames (1992) found that teachers create a positive or negative classroom environment. Others

have found similar results in sport psychology research. Reinboth and Duda (2006) claim that

coaches have a strong influence on the athletes’ perceptions of the climate and upon the athletes’

feelings of competence. It also appears to be the case that athletes perceiving a task-involved

climate tend to have a more positive view of their coaches than those who perceive an ego-

involved climate (Magyar & Feltz, 2003).

Several studies have focused on coach-initiated motivational climate. Coach-initiated

climate focuses on the role of the coach in creating the climate for the athlete. Bengoechea and

Strean (2007) found in a qualitative study that coaches were a large source of motivation for

youth athletes. They found that coaches were a source of perceived pressure, of support, of

control, and of motivational climate. All of these, in turn, affect motivation. In addition,

researchers found that type of coach was the strongest predictor of perceived climate

(Papaioannou, Ampatzoglou, Kalogiannis, Sagovits, 2008). Another study compared coach-

initiated climate to general contextual climate (Cervello et al., 2007). The coach-initiated

climate played a much more significant role for the athlete than any other contextual factor.

Athletes who were in a coach-initiated learning-oriented climate were more likely to have higher

levels of focus and flow experiences (Cervello et al., 2007).

Children’s perceptions of climate and their coaches’ influence on that has been shown to

consistently endorse mastery climate as favorable to performance climates (Cumming, Smoll,

Smith, & Grossbard, 2007). Cumming et al. (2007) found that children who perceived the

climate to be mastery oriented liked their coach more and enjoyed playing for their coach more

15

than if they perceived the climate as performance oriented. Also, those who perceived the

climate as mastery-focused thought more highly of their coach, perceived the coach to be more

sport knowledgeable, and a better teacher of skills. In addition, they were more likely motivated

to play for their coach in the future. This study also showed that winning did not affect the

perception of climate that the children had, but did affect the view of the coach as sport

knowledgeable or not. Winning, overall, was not considered very important to the youth who

ranged in age from 10 to 15.

Because coaches seem to have a substantial impact on motivational climate, interventions

focusing on the development of mastery oriented coaching styles are vital. Several different

coaching interventions have been set in place by recreation departments, leagues, and schools in

order for coaches to have better training (Smith, Smoll, & Cumming, 2007). Because these

organizations recognize the importance of positive coaching styles, it is important for quality

interventions based on theoretical research to be implemented.

Smith et al. (2007) have conducted research implementing a coaching intervention

focused on producing a positive task-involved climate. The intervention used was the Mastery

Approach to Coaching (MAC), which was adapted from an earlier intervention, Coach

Effectiveness Training (CET) (Smith, Smoll, & Curtis, 1979). This intervention is meant to

enhance the coach’s ability to support his or her athletes in a mastery supportive way, thus

producing a mastery climate. In the study, the intervention was used in pairing to show if there

was reduced anxiety in athletes whose coaches were exposed to the intervention (Smith et al.,

2007). While the intervention did not significantly produce a different motivational climate

compared to a control group (the control group was high in task-involvement as well), they did

find lower rates of attrition in the intervention group versus the control group (Smith et al.,

2007). Smoll, Smith, and Cumming (2007) found, using the MAC intervention, that teaching the

coaches concrete methods of creating a mastery involved climate also affected the athletes’

dispositional goal orientations. Those coaches who received the training were more effective in

creating task-orientations over the length of the season in their athletes than the coaches in the

control group where athletes’ goal orientations did not change over the course of a season.

Differing coaching styles may produce differing motivational climates. Adult athletes

preferred the positive feedback, training and instruction, and democratic coaching styles over

autocratic and social support styles (Sherman, Fuller, & Speed, 2002). However, this may not be

16

true for youth athletes. Turman (2001) found that the age of the athlete influenced which

coaching style the athlete preferred. Older athletes, in this study, were found to need less social

support than younger athletes. For instance, a senior on a particular team would need less

encouragement from the coach than a freshman on the same team.

Parents and peers can influence perceived climate as well. One study found that the

combined pressures from both parents and coaches resulted in maladaptive psychological and

behavioral outcomes. However, if both parents and coaches promoted a positive mastery

climate, the athletes reported better overall well-being (Ommundson, Roberts, Lemyre, & Miller,

2006). Friendships and peers also affect the climate. If friendships do not exist in sport,

motivation may be hindered (Patrick et al., 1999). In a qualitative analysis, Vazou, Ntoumanis,

and Duda (2005) found that peer-initiated climate takes on most of the same characteristics as

coach-initiated climate with a few exceptions. Peer-initiated climate, unlike coach-initiated

climate, includes issues of intra-team conflict and relatedness to teammates. This finding

supports the previously mentioned assumption of Patrick and colleagues (1999) that friendships

are important for promoting motivation. Teammates needed to feel connected to each other to

encourage a mastery climate. Also intra-team conflict like misunderstanding of roles and

jealousy may negatively affect the perception of climate especially for youth sport teams.

A related study looked at the effect of motivational climate on group cohesion (Hueze,

Sarrazin, Masiero, Raimbault, & Thomas, 2006). Group cohesion was defined in two ways:

group cohesion-task and group cohesion-social. Task cohesion is the ability of the team to work

together to accomplish a specific task. Social cohesion is how well the team gets along on a

personal level. The researchers found that if the team perceived a mastery climate, they were

more likely to have better task and social cohesion. The researchers also found that over time a

mastery climate led to higher levels of collective efficacy in the sport. Yet, an ego involved

climate led to lower levels of both task and social cohesion. The authors speculated that an ego

involved climate may interfere with the natural social growth of a team towards each other

causing lower cohesion (Hueze et al., 2006). An additional study found that performance

oriented climates may cause too much dissonance between players who are constantly being

compared to each other to afford the development of task or social cohesion (Ommundson,

Roberts, Lemyre, & Miller, 2005).

Although motivational climate is influenced by all people in the situation, coaches seem

17

to have the most influence in a sport situation (Smith et al., 2007). However, intervention studies

focused on producing a mastery climate are rare. Smith et al. (2007) suggested the need for

replication and further intervention studies to be conducted to verify the validity of MAC and

other interventions. These interventions come in the form of coach training programs which

provide coaches with a variety of learning opportunities and are considered valuable by the

coaches (Lemyre, Trudel, & Durand-Bush, 2007; Vargas-Tonsing, 2007). Climate seems to

influence how an athlete perceives his or her coach and also can affect the athlete’s perception of

his or her performance or level of success.

Empirical Links between SDT and Motivational Climate

Many factors affect a person’s motivation including cognitive, affective, perceptual, and

situational factors (Papaioannou, Milosis, Kismidou, & Tsigilis, 2007). This is evident in the

theories discussed to this point. Yet, are SDT and goal orientation completely separate from

each other? The factors which affect motivation may link the two theories to each other.

Ntoumanis (2001b) states,

…high task orientation can fulfill one or more of these needs (competence, autonomy,

relatedness) and, therefore, can enhance self-determined motivation. In contrast, high

ego orientation, especially coupled with low perceptions of competence, is not conducive

to the satisfaction of these needs. (p. 399).

Hence, factors linking the two theories have been studied. Standage and Treasure (2002) found a

strong relationship between task orientation and self-determined motivation for 12 to 14 year

olds in physical education classes. If an individual was high in task orientation no matter the

level of ego orientation that s/he had, s/he would be more likely to have high levels of self-

determined motivation. Those who were low in task orientation had higher levels of external

regulation than any other group, and those that had high ego orientation and low task orientation

had the highest levels of amotivation than any other group.

Models have been developed to test the relationships between task and ego orientation

and SDT constructs. One such study with Asian children concluded that task orientation and

perceived competence explained the majority of the variance in intrinsic motivation. In other

words, if an individual was task oriented and perceived that she was competent in her ability to

accomplish the task at hand, she would be intrinsically motivated towards the task. Task and ego

18

orientation was found to be related weakly to each other in this study, but ego orientation was not

related at all to intrinsic motivation (Sproule, Wang, Morgan, McNeill, & McMorris, 2007).

In one study, researchers linked perceived competence, intrinsic motivation, and task

orientation when concerned with physical activity participation (Papaioannou, Bebetsos,

Theodorakis, Christodoulidis, & Kouli, 2006). They found that there was a link between the

needs satisfaction of SDT and goal orientation theory in that those who were task-oriented and

intrinsically motivated were more likely to participate in physical activity. Ntoumanis (2001b)

found that if one was high in task orientation, he or she would be more likely to have high levels

of intrinsic motivation no matter the level of ego orientation of the person. Also, if one was low

in task orientation and high in ego orientation, levels of intrinsic motivation were found to be

lower.

Other researchers have looked at how certain types of goals affect intrinsic and extrinsic

motivation (Vansteenkiste, Matos, Lens, & Soenens, 2007; Vansteenkiste, Timmermans, Lens,

Soenens, & Van den Broek, 2008). These researchers state that there are two types of goals:

intrinsic and extrinsic. Intrinsic goals are about improvement and self-satisfaction while

extrinsic goals focus on power, being better than others, and attractiveness. These are similar to

the goals of task and ego, in which task would be intrinsic and ego would be extrinsic. These

researchers found that having intrinsic and extrinsic goals at the same time would be detrimental

to performance at that moment. They suggest that a person could have both intrinsic and

extrinsic goals, but that when completing a specific task, one type of goal takes precedence in the

moment (Vansteenkiste et al., 2007).

How motivational climate affects self-determined motivation has been observed in

previous research. Cox and Williams (2008) found that mastery climate and teacher support was

positively related to needs satisfaction of autonomy, relatedness, and competence and overall

intrinsic motivation. Perception of a mastery climate and teacher support was especially

important for the need of relatedness, and these variables were the strongest predictors of self-

determined motivation in youth athletes. Parish and Treasure (2003) found that a mastery

climate was positively related to more self-determined motivation, while a performance climate

was related to less self-determined motivation in middle school physical education classes.

Individual characteristics also seem to influence the perception the motivational climate.

In one study, it was demonstrated that a person is more inclined to perceive the environment as

19

task-involved if that person is also task-oriented. These individuals also had higher levels of

intrinsic motivation than those that were considered ego-oriented (Standage, Duda, &

Ntoumanis, 2003b). Skill level and age of the athlete were also examined as personal

characteristics that may affect perception of the climate for adolescent gymnasts. The results of

the study showed that perception of the climate did not change depending on the skill level of the

athlete. Yet, the older the gymnast was, the more likely she was to have higher levels of ego

orientation (Halliburton & Weiss, 2002).

Athletes’ perceptions of a positive motivational climate are not solely about the coach

generating a task-focused environment. A positive climate should also enhance enjoyment of the

activity, increase interest in sport, and produce positive future expectations (Newton, Watson,

Kim, & Beacham, 2006). Newton et al. (2006) suggested that in order for these essential

motivators to be realized, the climate must emphasize caring, goal-setting, and individual

responsibility for improvement. The idea that self-responsibility is an important aspect of a

positive motivational climate relates climate to SDT. A positive climate allows the athlete to

have a sense of autonomy and may help to increase intrinsic motivation.

In related research of needs satisfaction to motivational climate, university athletes were

asked about the perceived climate and how their perceived needs satisfaction changed over the

course of a season (Reinboth & Duda, 2006). They found that the needs of autonomy,

relatedness, and competence were positively related to a task-involving climate. An ego-

involving climate was not related to competence and autonomy in either direction, but was

negatively related to relatedness. This seems to indicate that when a coach puts emphasis on

outcomes, coach-athlete and athlete-athlete relationships might be affected (Reinboth & Duda,

2006).

The findings of these studies demonstrate that the theories of motivation most prevalent

in sport literature do not stand alone. Constructs among the theories are interrelated, which adds

to the complexity of explaining motivation. When combining the theories, however, a more

complete and accurate depiction of individual motivational states can be represented. This is not

a new idea. Deci and Ryan (1985), in fact, mention the role of goals and the effects of the

environment on self-determined motivation. Despite the recognition of the need for further

research, it was not until recently that researchers attempted to validate the theoretical links

among the theories.

20

Psychological and Behavioral Consequences of Motivation

Vallerand (1997) postulated that three levels of behavioral consequences exist: cognitive,

affective, and behavioral. Examples of these behavioral effects are mentioned by Vallerand

(1997). The psychological and behavioral consequences vital to persistence in sport are many,

but for the purpose of the present study, performance which is a behavioral consequence,

intention to continue sport participation which is a cognitive consequence, and the affective

consequence of sport satisfaction are assessed.

Performance is not a variable that has been used as an outcome of motivation often in the

literature. However, Vallerand and Losier (1999) suggest that performance is an essential

motivational outcome that should be studied. Gillet, Vallerand, Amora, and Baldes (2010) used

an objective measure of performance, results in a judo tournament, as an outcome. Cumming et

al. (2007) utilized won-loss record as a predictor of athletes’ perceptions of the coach, but not as

a motivational outcome. Being able to perform well is important to most participants in sport

including athletes, coaches, and parents. However, does being intrinsically motivated or having

a specific motivational climate improve an athlete’s or team’s performance? Coaches may be

less likely to adopt a different coaching style promoting a needs supportive task-involved climate

if their athletes’ performances do not improve.

In light of the fact that the act of participation in sports is a consequence of the

combination of environmental factors acting on an individual’s motivation, assessing the

participants’ intentions to participate is important. Intention to participate has been used as a

variable to assess the likelihood of future physical activity participation in several studies in

relation to motivation (Bray et al., 2005; Loney, Standage, & Lewis, 2008; Mouratidis,

Vansteenkiste, Lens, & Sideridis, 2008; Standage et al., 2003b). Mouratidis et al. (2008)

proposed that intention to continue participation is an indicator of one’s level of engagement in

the activity; while Bray et al. (2005) suggest that intention to participate is also an indicator of

level of enjoyment in the activity. Finally, intention to participate can be used as a predictor of

actual behavior (Hagger et al., 2003), which is the primary focus of the present study.

Intrinsic motivation and a positive task-involved climate have been associated with the

subjective well-being and sport satisfaction of athletes (Boixados et al., 2004; Ryan & Deci,

2000). Satisfaction in sport has also been linked to persistence in sport (Barnett et al., 1996).

The more athletes are satisfied with their experiences in sport, the more likely they are to

21

continue their participation (Barnett et al., 1996). Because satisfaction in sport is a predictor of

sport adherence, it is of value to assess in the present study.

Multi-Level Modeling

The use of multi-level modeling as a statistical procedure is a recent addition to sport

psychology literature. Researchers have realized the importance of using this particular

modeling technique in order to accurately represent nested data. In the past, single-level linear

models have been used to show the relationship between group variables and individual

variables. While this seemed to be the best representation of the data in the past, this method

problematically required researchers to ignore the violation of the assumption of independence of

the data (Hoyle, Georgesen, & Webster, 2001; Papaioannou et al., 2004). Violating this

assumption leads to larger degrees of Type I error and a greater chance of the data being

statistically significant while, in truth, the data may not be significant (Papaioannou et al., 2004).

According to Raudenbush and Byrk (2002), hierarchical modeling is essential to

educational research, as in the case of students in classrooms, which is very comparable to

athletes on sports teams. Students in classrooms have three points of influence: a) individual

growth throughout an academic year, b) the effects of personal characteristics and experiences,

and c) the influence of classroom organization, teacher characteristics, and behaviors. These

variables are nested within each other making a multi-level model. The first level consisted of

the observations over time, which was nested in the individual person with personal

characteristics, which was nested in the classroom environment (Raudenbush & Byrk, 2002).

This sequence is easily transferred to the team sport environment. The individual performance

of an athlete is nested in the athletes with their own personal characteristics, which are nested in

teams and are affected by the behaviors and characteristics of the coach. In other words,

researchers cannot dismiss the nested nature of athletes on teams when assessing personal

characteristics or performance of athletes.

Purpose and Hypotheses

As discussed previously, participation in youth sport declines rapidly in the teenage

years. Motivation plays a role in why youth do not intend to continue in sport, and the coach has

an influence on the motivation of the athlete. Recently, however, the coach’s influence on the

team has been assessed using multi-level analyses. The purpose of the current study was to

continue evaluating the coach’s influence on youth sport motivation using aspects of SDT and

22

motivational climate in a multi-level model. In the proposed study, the relationship of

motivational climate with the athletes’ need satisfaction and motivation regulations, and in turn

the relationships with the athletes’ psychological outcomes such as intention to continue in sport

using a hierarchical model were examined. Controlling for the effects of the team as a group

provided more accurate measures of effects at the individual level.

Figures 1 and 2 illustrate the proposed structures at each level. Figure 1 shows the

proposed level 1 structure in a path diagram. Figure 2 is a path model for level 2. All of the

variables from level 1 were also to be assessed at level 2 except for intention to continue in sport,

which was to be a level 1 outcome only. Figures 3 and 5 depict the proposed positive

relationships at level 1 and level 2. Figures 4 and 6 depict the proposed negative relationships at

level 1 and level 2.

Within the first two hypotheses for the current examination, probable associations at each

level are delineated. For the additional hypotheses, specific aspects of the proposed model are

defined. Motivational climate has been assessed as an individual level and team level variable

(Cumming et al., 2007). However, because of team effects, climate should be a stronger

predictor at the team level than at the individual level. Based on pilot study data, coaches said

that relatedness was a very important aspect of motivating athletes (Zomermaand, 2010).

Therefore, in this model, the athlete’s need of relatedness satisfaction was assessed in

comparison to competence and autonomy. Because the coaches in the pilot study also mentioned

providing success to athletes, competence satisfaction may be just as important as relatedness

satisfaction (Zomermaand, 2010). Hence, this inquiry focused on the difference between

relatedness satisfaction and autonomy satisfaction within the model. Furthermore, prior research

has shown that intrinsic motivation has been related to intention to continue in physical activity

(Papaioannou, 2006), and intrinsic motivation is more closely related to integrated regulation

than identified regulation (Deci & Ryan, 2000). This study investigated this relationship at the

individual and team levels. Finally, prior research indicated that an athlete’s needs satisfaction

(Gagne et al., 2003) and mastery climates produce improved athlete satisfaction in sport

(Ommundsen et al., 2003). This relationship was examined further in the proposed study.

The hypotheses tested in this investigation included:

1. Task-involved climate, motivational needs satisfaction, intrinsic motivation, integrated

regulation, and identified regulation would be positive predictors of self-perceived

23

performance and sport satisfaction at the individual and team levels, and intention to

continue in sport at the individual level.

2. Ego-involved climate, introjected regulation, external regulation, and amotivation would

inversely predict sport performance and sport satisfaction at the individual and team

levels, and intention to continue in sport at the individual level.

3. Motivational climate would have stronger associations with the psychological outcomes

at level 2 than at level 1.

4. Relatedness satisfaction would be a better predictor of the psychological outcomes within

the model than autonomy satisfaction at level 1 and level 2.

5. Intrinsic motivation and integrated regulation would have stronger associations with

intention to continue in sport than identified regulation.

6. Athlete needs satisfaction (competence, relatedness, and autonomy) and a positive

mastery climate would be better predictors of sport satisfaction than identified regulation,

integrated regulation, and intrinsic motivation.

24

Task

Ego

Autonomy

Relatedness

Competence

Intrinsic

Motivation

Introjected

Regulation

Amotivation

Performance

Satisfaction

Intention

Integrated

Regulation

Identified

Regulation

External

Regulation

+

+

+

‐

‐

+

+

+

‐

‐

‐

+

+

+

‐

‐

‐

++

+

‐

‐

‐

+

+

+

+

+

+

+

+

+

‐

‐

‐

‐‐

‐

‐

‐

‐

Figure 1: Predicted relationships at the individual level.

25

Figure 2: Predicted relationships at the team level.

26

Figure 3: Predicted positive relationships at the individual level.

Ego

Autonomy

Relatedness

Competence

Introjected

Regulation Performance

Satisfaction

Intention

External

Regulation

Amotivation

Figure 4: Predicted negative relationships at the individual level.

27

Figure 5: Predicted positive relationships at the team level.

Figure 6: Predicted negative relationships at the team level.

28

Chapter 2

Method

Participants

The participants were 342 high school athletes aged 14 to 18 years from 31 high school

teams in the southern and midwestern United States. There were 208 males and 134 females

participating in football, basketball, baseball, soccer, and softball. Demographic information is

provided in Table 1 and the participants’ sport experience is provided in Table 2. Because the

athletes were minors, participation in the study required parental informed consent and athlete

informed assent that detailed participant rights (Appendix B). This study was approved by the

institutional review board (Appendix C).

Table 1. Demographic information (N = 342).

Demographic Frequency Percentage

Gender

Male 208 60.8

Female 134 39.2

Ethnicity

African American 31 9.1

Asian American 3 0.9

Hispanic American 10 2.9

Native American 2 0.6

Caucasian 289 84.5

Mixed Race 5 1.5

Pacific Islander 1 0.3

Sport

Football 124 36.3

Basketball 77 22.5

Baseball 34 9.9

Softball 60 17.5

Soccer 47 13.7

Year in School

Freshman 104 30.4

Sophomore 89 26.0

Junior 98 28.7

Senior 50 14.6

29

Table 2. Participant sport experience.

Mean Standard

Deviation Minimum Maximum

Years in Sport 5.98 3.71 1 15

Years Playing for Current Coach 1.84 1.14 1 9

Sports Played Competitively 2.94 2.05 1 5

Measures

Motivational Climate Scale for Youth Sports (MCSYS; Smith et al., 2008). The

MCSYS consisted of 12 total items with two factors: mastery-initiating and ego-initiating. Each

factor had six items (i.e. winning games is the most important thing for the coach and the coach

makes players feel good when they improved a skill) scored on a 5-point Likert scale ranging

from 1 (not at all true) to 5 (very true). Smith et al. (2008) reported the internal consistency of

the mastery-initiating and ego-initiating factor at α = .84, and α = .75, respectively. The test-

retest reliability of the MCSYS was found to be .84 for mastery-initiating items and .76 for ego-

initiating items. Concurrent validity was supported by positive correlations with similar scales.

The mastery-initiating factor related positively (r = .28, p < .001) to task orientation and the ego-

initiating factor related positively (r = .33, p < .001) to ego orientation in the Perception of

Success Questionnaire (POSQ) (Smith et al., 2008). Positive relationships also were found for

mastery-initiating climate and task orientation (r = .43, p < .001) and for ego-initiating climate

and ego orientation (r = .41, p < .001) of the Achievement Goal Scale for Youth Sports (Smith et

al., 2008).

Psychological Need Satisfaction in Exercise Scale (PNSE; Wilson, Rogers, Rogers, &

Wild, 2006). The PNSE was developed to assess competence, autonomy, and relatedness

satisfaction in exercise participants. The three needs each represented a factor of the scale with

six items per factor. The 18 items were modified to inquire about sport skills and sport

participation rather than exercise. For example, the item I feel confident that I can do even the

most challenging exercises was changed to I feel confident that I can do even the most

challenging skills. Wilson et al. (2006) reported the internal consistencies of the factors as α =

.91 for both the competence and autonomy subscales, and α = .90 for the relatedness subscale.

30

Validity evidence for the subscales of the PNSE was assessed by comparing it with the

competence and perceived choice subscales of the Intrinsic Motivation Inventory (IMI), and the

relatedness subscale of the Exercise Motivation Inventory (EMI; Wilson et al., 2006). The

correlations indicated strong validity evidence with correlations of r = .82, .78, and .92 for the

perceived competence subscales, the perceived autonomy and perceived choice subscales, and

the relatedness subscales respectively (Wilson et al., 2006).

Behavioral Regulation in Sport Questionnaire (BRSQ; Lonsdale, Hodge, & Rose,

2008). The BRSQ had six subscales with four items each, assessing intrinsic motivation in

general. The 24 items starting with the stem I participate in my sport followed by a reason for

sport participation (i.e. because it’s fun and because the benefits of sport are important to me) are

scored on a 7-point Likert scale ranging from 1 (not at all true) to 7 (very true). The internal

consistencies of the subscales were within the acceptable range (amotivation = .83, external

regulation = .79, introjected regulation = .87, identified regulation = .88, integrated regulation =

.90, intrinsic motivation-general = .73) (Lonsdale et al., 2008). Validity evidence was provided

for the BRSQ by Lonsdale et al. (2008) comparing the subscales to flow and burnout scales.

They reported that amotivation, external regulation, and introjected regulation were negatively

related to flow (r = -.31, -.25. -.16) and positively related to burnout (r = .65, .52, .43).

Identified regulation, integrated regulation, and intrinsic motivation were positively related to

flow (r = .21, .36, .36), and negatively related to burnout (r = -.11, -.23, -.50) in concordance

with SDT.

Performance. Performance was assessed with three self-report items. Each participant

rated him or herself on a scale ranging from 1 (extremely poor performance) to 10 (extremely

good performance) for each item (i.e. rate how well you are currently performing, rate how well

you have performed overall this season, and rate your improvement since the beginning of the

season).

Intention to participate. Intention to participate was assessed using three items

modified from Chatzisarantis et al. (1997), which assessed the intention of youth to participate in

physical activity in the future. The items (I am determined to play sport at least 3 times a week

after the season is over; I intend to play sport at least 3 times a week during the off-season; I

plan to continue to play sport next season) are scored on a 7-point Likert scale ranging from 1

(very unlikely) to 7 (very likely). Chatzisarantis et al. (1997) reported an internal consistency of

31

α = .90 for the scale. Validity evidence for the 3-item intention scale was given by correlations

with motivation regulations according to SDT (Chatzisarantis et al., 1997). They reported that

intention to exercise was positively related to intrinsic motivation, identified regulation, and

introjected regulation (r = .41, .43, .21). Amotivation was negatively related to intention to

exercise (r = - .29). External regulation did not show significant relationships with intention to

exercise. Integrated regulation was not assessed in relationship to intention to exercise.

Sport Satisfaction Scale (Duda & Nicholls, 1992). The 5-item satisfaction subscale

(i.e. I usually have fun doing sports) was utilized for this study. Each item was rated on a 5-point

Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). Duda and Nicholls (1992)

reported a reliability coefficient of α = .94 for this subscale. Validity evidence was not provided.

Procedures

The recruitment of teams varied in method depending on several factors including

location of teams, availability, and approval from school administrators and athletic directors.

First, Florida State University Human Subjects Committee approval was attained and high

school administrators were contacted to gain consent for their students to participate. Most of

the participating schools and teams were chosen through the researcher’s personal connections

with coaches and schools or with the assistance of her Introduction to Psychology students at a

southern liberal arts college. In return for credit in her class, the students provided contact

information and connected the researcher to coaches from their own former high schools, most

of which were in the southern United States. Teams selected were currently in-season, contained

more than 10 members, and were not individual sports. Due to the in-season requirement, data

collection took several months to accommodate differing high school sport seasons.

The selected teams’ coaches determined an appropriate time to distribute parental

informed consent forms and athlete informed assent forms to be taken home for the parents to

read and sign. Usually, one or two weeks passed before the forms were returned to the

researcher and the teams were either given the internet link for the online survey or were given

the hard copy version of the questionnaire (Appendix A). The first teams that agreed to

participate received the online survey, but because this version of the questionnaire was finished

at the discretion of the athlete, individual completion rates were less than 20% for over 400

original participants, and several teams receiving the online version failed to have even one

member complete the questionnaire. Therefore, it was decided that a monitored paper

32

questionnaire would guarantee higher completion rates. The hard copy version was distributed

by the coaches in a classroom or practice setting depending on the coach’s preference. The

survey took approximately 10 minutes for the athletes to complete. The completed online

questionnaires were stored on the researcher’s computer and were password protected and the

paper surveys were stored at the researcher’s private residence. All responses were kept

confidential.

Data Analysis

Structural equation modeling (SEM; Stapleton, 2006) was used to analyze the data. The

hypotheses focused on multi-level modeling allowing for the determination of models at each

level of involvement. Figures 1 and 2 illustrate the effects that were evaluated on both the

individual and team levels. Model fit was to be determined at the individual and team levels.

The model fit index standards used for this study were: Comparative Fit Index (CFI) ≥ .9,

Tucker-Lewis Index (TLI) ≥ .9, Standardized Root Mean Square Residual (SRMR) ≤ .08, and

Root Mean Square Error of Approximation (RMSEA) ≤ .05 (Stapleton, 2006). Hu and Bentler

(1999) suggested that these model fit indices should be different: CFI ≥ .95, TLI ≥ .95, SRMR ≤

.08, and RMSEA ≤ .06 in order to lower the rate of committing a Type II Error (the probability

of rejecting a correct alternative hypothesis). Moreover, they advocated that researchers need to

use a combination of the indices in order to assess acceptable model fit. Because the indices

measure different aspects of how well the model fits, utilization of only one index could result in

an incorrect result (Hu & Bentler, 1999). Marsh, Hau, and Wen (2009) stated that using the

model fit index requirements is not sufficient for determining acceptable model fit. For example,

models that were hypothesized to contain negative pathway coefficients that result in a model

with positive pathways may have acceptable model fit, but does not adequately represent the

theoretical basis of the study. Marsh et al. (2009) also noted that a limitation of Hu and Bentler

(1999) was the lack of consideration of nested data; the revised model fit standards may not be

acceptable for nested data. For the current study, multiple indices were used and the models were

assessed as to the direction and significance of the pathways. In addition, the revised model fit

indices may not work for nested data and as the current study utilized nested data, the model fit

standards were kept at the traditional levels.

Data Parceling. Data parceling was considered to simplify the exceedingly complex

model in order to adhere to the principle of parsimony which states that when given the option

33

between a complicated model and a simpler model that demonstrates the same constructs, the

researcher should choose the simpler model (Kline, 2011). In addition, Little, Cunningham,

Shahar, and Widaman (2002) suggested that using data parceling is acceptable when assessing

the latent constructs within an SEM instead of the structure of observed variables. Data

parceling can be done in place of correlating residuals of the observed items. In fact, the items

are simply the mode utilized to measure the latent variables and are inconsequential to

understanding the theory. Also, if the goal of the researcher is to evaluate the latent variable

structure, just-identified latent constructs may be more beneficial because these only have one

solution unlike overidentified latent variables which have multiple solutions allowing for

instability in the model. Parceling allows the researcher to have the ideal just-identified structure

(Little et al., 2002). The observed variable structure was not the primary focus of this study

because the measures used for the current model had established reliability and validity as

previously described. Instead, the focus of the current model was on the relationship between

the latent variables fitting with Little et al.’s (2002) assertion.

Critics of data parceling warn against parceling to conceal loading complications with the

original indicators (Little et al., 2002). In addressing this issue, confirmatory factor analyses

(CFA) were conducted for each of the latent variables using the original data in order to

demonstrate that data parceling was done in order to simplify an extremely complex model and

reduce the number of parameters instead of disguising errors in the original data analyses.

The items were parceled so that each latent variable in the proposed model would have

two to four observed indicators. The five motivation regulations measured by the BRSQ

(Lonsdale et al., 2008) were parceled into two constructs: autonomous motivation (intrinsic

motivation, integrated, and identified regulations) and controlled motivation (introjected and

external regulations) (Lonsdale, Hodge, & Rose, 2009). Predictors for autonomous motivation

were calculated by multiplying the first item score for intrinsic motivation in the BRSQ by two

and adding the first item score of both integrated and identified regulation. The process was

repeated for each of the remaining three item scores for each construct. Predictors for controlled

motivation were calculated by multiplying the first item score for external and introjected

regulation by two, adding those together, and, once again, repeating that process for the

remaining three item scores for both constructs. This process produced two latent variables with

34

four predictors each (Lonsdale et al., 2009). The variable amotivation was not parceled; instead,

the original four indicators from the BRSQ were used.

The indicators for the remaining latent variables were parceled by adding together two

items at a time. For example, the latent variable task climate was measured using six observed

items (a2, a4, a6, a7, a9, and a11) from the MCSYS (Smith et al., 2008). These were then

parceled together by adding the scores for a2 and a4, a6 and a7, a9 and a11, creating three new

indicators for task (i4, i5, and i6). This method was repeated for each of the latent variables

except performance and intention, which were scored with only three items each in the

questionnaire.

Intraclass Correlations. As stated earlier, multi-level modeling is used when the data

are nested and the assumption of independence is violated, leading to a greater chance of

committing a Type I error (Hoyle et al., 2001; Papaioannou et al., 2004). Nonetheless, in multi-

level modeling, sample size and the intraclass correlation (ICC) may influence the validity of the

parameter estimates within the model. The ICC describes the amount of dependence the

clustered scores have on each other (Maas & Hox, 2005). According to Maas and Hox (2005),

design effect or the estimate of how much the standard errors are underestimated is influenced by

the ICC for a variable. The simple formula for design effect is 1 + (average cluster size – 1) *

ICC. An ICC and design effect was calculated for each parceled variable to assess the validity of

using multi-level modeling for the current study.

35

Chapter 3

Results

The purpose of this study was to determine how perceived motivational climate affects

needs satisfaction, intrinsic and extrinsic motivation regulations, intention to continue sport

participation, sport satisfaction, and performance using a two-level structural equation model

(SEM) to account for the nesting of individuals in teams.

SEM, unlike other modeling techniques, specifically estimates measurement error. In

SEM, latent and observed variables can be used as outcome variables and the error terms

represent variance that is unexplained by the predictors (Kline, 2011).

Descriptive Statistics and Data Parceling

Descriptive statistics (see Table 3) and correlations among the manifest variables were

calculated (see Table 4). Reliability statistics were determined for the subscales (see Table 6).

Each subscale was found to be reasonably reliable for this sample. In addition, CFA analyses

were calculated for each individual subscale to assess the latent variables using the original non-

parceled data in order to validate the use of data parceling in the analyses. Table 5 shows the

loadings for each of the items for the subscales. Most of the loadings for the latent variables

were acceptable. A few item loadings were troublesome for the individual CFA’s. Item a4 (see

Table 5) in the Task Climate subscale had a small loading compared to the other items in the

subscale. It was found that a4 had a very small standard deviation (SD = .83) indicating that the

responses to that item did not vary much across the participants. The mean response for item a4

was 4.39 (out of a 5-point scale) indicating a high rate of affirmative responses. Not

surprisingly, high school athletes in general were encouraged to learn new skills by their

coaches. While this is congruent with the theory, the attenuated variation of the responses caused

minor problems with the statistical analysis. In addition, for the ego climate subscale similar

issues regarding small variation were found with the item standard deviations very close to one.

However, because these items have been used consistently in the past (Cumming et al., 2007;

Smith et al., 2008) and have a solid theoretical basis, they were included in the data parceling.

Item b1 for intrinsic motivation resulted in a negative residual which indicates a

statistical impossibility for this item because it suggests that the latent variable accounted for

more than 100% of item variance. After further review of the data, it was ascertained that all of

the standard deviations for the items predicting the latent variable intrinsic motivation (b1, b2,

36

b3, and b4) were all close to one (1.11, 1.06, 1.15, and 1.39) while other subscales from the

BRSQ had larger standard deviations, which provides for improved statistical analysis. For

instance, the standard deviations for the external regulation items (b17, b18, b19, and b20) were

closer to two (2.08, 1.83, 1.86, and 1.86). The small size of variation made the individual CFA

difficult for the Mplus 6.0 software to calculate. It was also noted that the average score for

items for intrinsic motivation were very high on the seven point scale (6.43, 6.40, 6.33, and 5.99)

whereas the means for the items predicting external regulation were in the middle of the scale

(3.13, 2.63, 2.58, and 2.60). The high means and low standard deviations demonstrate the small

size of the variation across the sample which signifies that almost all of the athletes agreed that

they played sports because they enjoyed it, liked their sport, thought their sport was fun, and

found their sport pleasurable. One adjustment of this CFA may have been to correlate the

residuals of certain items (Little et al., 2002) as suggested by the Mplus 6.0 modification indices.

However, data parceling was being considered to reduce the number of parameters and, as

previously mentioned, data parceling may be done in place of correlating residuals (Little et al.,

2002). Additionally, despite these statistical issues, based on SDT the parceled variable

autonomous motivation could not exist without the intrinsic motivation facet as intrinsic

motivation is the culmination of the self-determination continuum. As each item had been shown

to be valid in past studies (Lonsdale et al., 2009), and in order to remain consistent with this

method of data parceling, the data parceling analysis continued to include all of the intrinsic

motivation items. Item b11 was slightly problematic in the individual CFA. However, in order to

remain consistent with others using the BRSQ (Lonsdale et al., 2009), and with SDT, b11 was

included in the data parceling analysis.

37

Table 3. Descriptive Statistics of the Manifest Variables.

Variable N Mean Standard

Deviation Variance Minimum Maximum

Task Climate 342 4.30 0.63 0.39 2.17 5.00

Ego Climate 340 2.73 0.77 0.60 1.00 5.00

Autonomy 340 5.28 1.11 1.23 2.00 7.00

Relatedness 341 5.34 1.33 1.78 1.00 7.00

Competence 339 5.51 1.09 1.19 1.60 7.00

Autonomous

Motivation 336 5.94 1.02 1.03 3.06 7.00

Controlled

Motivation 340 3.56 1.51 2.27 1.00 7.00

Amotivation 340 2.16 1.49 2.22 1.00 7.00

Performance 334 7.01 1.65 2.72 1.00 10.00

Sport

Satisfaction 341 4.21 0.83 0.69 1.00 5.00

Intention to

Continue 339 5.10 1.62 2.63 1.00 7.00

Note. Task and ego climate were scored from 1 (not at all true) to 5 (very true). Autonomy, relatedness, and

competence were scored from 1 (strongly disagree) to 7 (strongly agree). Autonomous and controlled motivations

and amotivation were scored from 1(not at all true) to 7 (very true). Performance was scored from 1 (extremely poor

performance) to 10 (extremely good performance). Sport Satisfaction was scored from 1 (strongly disagree) to 5

(strongly agree). Intention to continue was scored from 1 (very unlikely) to 7 (very likely).

38

Table 4. Correlation Matrix for the Manifest Variables.

Task Ego Autonomy Relatedness Competence Autonomous

Motivation

Controlled

Motivation Amotivation Performance Satisfaction Intention

Task 1.00 .25** -.08 -.07 -.01 .13* .30** .06 -.00 -.08 -.04

Ego 1.00 .15** .22** .25** .37* .05 -.15** .05 .15** .07

Autonomy 1.00 .39** .52** .44** -.13* -.28** .10 .27** .23**

Relatedness 1.00 .41** .42** -.16** -.27** .23** .30** .32**

Competence 1.00 .56** -.11* -.32** .25** .31** .30**

Autonomous

Motivation 1.00 -.05 -.56** .17** .34** .34**

Controlled

Motivation 1.00 .34** .05 -.09 .00

Amotivation 1.00 -.12* -.22** .28**

Performance 1.00 .09 .15**

Satisfaction 1.00 .28**

Intention 1.00

*Significant correlations (p < .05).

**Significant correlations (p < .01)

39

Table 5. Standardized Loadings for Individual CFA’s.

Latent Variable Indicator

Standardized

Loadings

Task Climate

A2: The coach makes players feel good when they improved a skill. .533

A4: The coach encourages us to learn new skills. .109

A6: The coach tells players to help each other get better. .181

A7: The coach tells us that trying our best is the most important thing. .537

A9: The coach says that teammates should help each other improve their

skills. .649

A11: The coach says that all of us are important to the team’s success. .612

Ego Climate

A1: Winning is the most important thing for the coach .368

A3: The coach spends less time with players who aren’t as good. .519

A5: The coach tells us which players on the team are the best. .057

A8: The coach pays the most attention to the best players. .095

A10: Players are taken out the game if they make a mistake. .422

A12: The coach tells us to try to be better than our teammates. .608

Autonomy

C6: I feel free to participate in sport in my own way. .668

C7: I feel free to make my own decisions in my sport. .794

C8: I feel like I have a say in choosing the skills that I do. .740

C9: I feel free to choose which sport I participate in. .345

C10: I feel like I am the one who decides what sports that I do. .408

Relatedness

C11: I feel attached to my coaches because they accept me for who I am. .816

C12: I feel like I share a common bond with my coaches when we work

together. .850

C13: I feel a sense of camaraderie with my coaches because we

participate in sport for the same reasons. .830

C14: I feel close to my coaches and teammates who appreciate how

difficult sport can be. .763

C15: I feel connected to my coaches when we work together. .852

C16: I feel like I get along with my coaches while we work together. .840

Competence

C1: I am able to complete the skills that are personally challenging. .726

C2: I can do even the most challenging skills. .871

C3: I feel confident in my ability to perform skills that personally

challenge me. .852

C4: I feel capable of doing even the most challenging skills. .844

C5: I feel good about the way I am able to complete challenging skills. .705

Intrinsic

Motivation I participate in my sport…

B1: because I enjoy it. ---a

B2: because I like it. -.084

B3: because it’s fun. .306

B4: because I find it pleasurable. .212

Integrated

Regulation I participate in my sport…

B5: because it’s part of who I am. .189

B6: because it’s an opportunity to just be who I am. .291

B7: because what I do in sport is an expression of who I am. .872

B8: because it allows me to live in a way that is true to my values. .424

40

Table 5 Continued.

aB1 and B11 were removed from the CFA.

Latent Variable Indicator Standardized

Loadings

Identified

Regulation

I participate in my sport…

B9: because the benefits of sport are important to me. .542

B10: because it teaches self-discipline. .945

B11: because I value the benefits of my sport. ---a

B12: because it is a good way to learn things which could be useful to

me in my life. .769

Introjected

Regulation I participate in my sport…

B13: because I would feel ashamed if I quit. .345

B14: because I would feel like a failure if I quit. .249

B15: because I feel obligated to continue. .678

B16: because I would feel guilty if I quit. .929

External Regulation I participate in my sport…

B17: because if I don’t other people will not be pleased with me. .616

B18: because I feel pressure from other people to play. .846

B19: because people push me to play. .845

B20: to satisfy people who want me to play. .828

Amotivation I participate in my sport…

B21: but I wonder what’s the point. .992

B22: but I question why I continue. .994

B33: but the reasons why are not clear to me anymore. .975

B24: but I question why I am putting myself through this. .708

Performance

D1: Rate how well you are currently performing. .929

D2: Rate how well you have performed overall this season. .914

D3: Rate your improvement since the beginning of the season. .551

Sport Satisfaction

E1: I usually have fun doing my sport. .931

E2: I usually enjoy playing my sport. .938

E3: I usually find my sport interesting. .885

E4: I usually get involved in practices. .722

E5: In practice, I usually feel that time flies. .447

Intention to

Continue

F1: I am determined to play sport at least 3 times a week after the

season is over. .794

F2: I intend to play sport at least 3 times a week during the off-

season. .881

F3: I plan to continue to play sport next season. .609

41

Table 6. Reliability Statistics for Each of the Subscales.

Latent Variable

Cronbach’s

Alpha

Task Climate .77

Ego Climate .70

Autonomy .75

Relatedness .93

Competence .90

Intrinsic Motivation .89

Integrated Regulation .83

Identified Regulation .86

Introjected Regulation .86

External Regulation .85

Amotivation .91

Performance .78

Sport Satisfaction .87

Intention to Continue .83

The Multi-Level Model

Model specification. As the structural model was being constructed, it became apparent

that the model was exceedingly complex with a large number of degrees of freedom.

Simplification of the model was necessary in order to attempt multi-level modeling. Data

parceling, as previously mentioned, was conducted and reduced the parameters from 180 free

parameters to 123 free parameters at level 1. However, when the model at level 2 was attempted,

the model was not identified and the Mplus 6.0 software could not calculate the model with the

large number of parameters as the level 2 model was hypothesized to be very similar to the level

1 model. The Mplus 6.0 creators were contacted to assist with the specification of the model. L.

K. Muthén (personal communication, March 3, 2012) stated that having more parameters than

clusters in the model has not been studied previously, and, therefore, no one knows what effect

having more parameters than clusters at level 2 would have on the standard errors in the model.

For this reason, the Mplus 6.0 software does not allow models to be specified that have more

parameters than clusters at level 2. As there were only 31 teams (clusters) and over 100

parameters in the model, the model could not be specified as hypothesized at level 2.

42

Intraclass correlations. In addition to the model non-identification at level 2, ICC

values also produced concern. Table 7 shows the ICC and design effect values, the estimate of

how much the standard errors are underestimated, for the parceled items in the current study. In

general, a design effect greater than two is acceptable (Maas & Hox, 2005); less than half of the

design effects calculated were greater than two. It was concluded that the parameter estimates of

the second level model could not be trusted. Because of the model non-identification and the

uncertainty of the parameter estimates at level 2, it was determined that a multi-level analysis

was not feasible for the data. However, because the data were grouped, the violation of the

assumption of independence needed to be taken into account. To ameliorate this violation, the

Mplus 6.0 syntax was designated to consider the clusters at the single level.

43

Table 7. ICC and Design Effect Values for the Parceled Observed Variables.

Latent Variable Parceled

Variable ICC

Design

Effect

Autonomous Motivation H1 .250 3.25*

H2 .426 4.834*

H3 .461 5.149*

H4 .245 3.205*

Controlled Motivation H5 .057 1.513

H6 .096 1.864

H7 .084 1.756

H8 .080 1.72

Task Climate I1 .174 2.566*

I2 .179 2.611*

I3 .150 2.35*

Ego Climate I4 .167 2.503*

I5 .219 2.971*

I6 .195 2.755*

Competence J1 .191 2.719*

J2 .190 2.71*

J3 .115 2.035*

Autonomy K1 .044 1.396

K2 .072 1.648

K3 .118 2.062*

Relatedness L1 .067 1.603

L2 .099 1.891

L3 .059 1.531

Satisfaction M1 .070 1.63

M2 .065 1.585

Performance N1 .076 1.684

N2 .104 1.936

N3 .126 2.134*

Intention to Continue O1 .061 1.549

O2 .052 1.468

O3 .050 1.45

*Acceptable design effects.

44

Hypothesized and Modified Models

Figure 7 shows the standardized loadings and residuals for the hypothesized model

adjusted for the parceled indicators. SEM procedures within MPlus 6.0 with the robust

maximum likelihood estimator (MLE) were utilized to assess model fit (see Table 8). The

hypothesized model did not have good model fit based on the following standards that were

utilized: RMSEA < .05; CFI > .90; TLI > .90; SRMR < .08.

While the model did not fit well, a few observations were made of pathways that may

have had an impact on the model results: (a) while perceived task climate predicted significantly

all of the needs (autonomy, relatedness, and competence), perceived ego climate was not related

significantly to any of the psychological needs; (b) autonomy failed to predict any of the

motivation regulations and amotivation; and (c) controlled motivation and amotivation did not

significantly predict any of the outcome variables. Based on the results of the hypothesized

model, it was determined that there may be direct effects from task and ego climate to the

motivation regulations and amotivation as well as direct effects from autonomy, relatedness, and

competence to performance, satisfaction, and intention to participate.

These pathways were added to Modified Model 1 (Figure 8) and model fit is shown in

Table 8. Model fit for the modified model improved; however, the fit was still not in the

acceptable range. Several new direct effects were shown to be significant; yet, autonomy still

did not significantly predict any other variable.

Table 8. Model Fit Indices.

Chi-Square (df)

RMSEA

(95% CI) CFI TLI SRMR

Hypothesized

Model 1291.549* (533) .065 (.060-.069) .887 .873 .099

Modified Model 1 1110.938* (518) .058 (.053-.063) .911 .898 .059

Modified Model 2 756.86* (400) .051 (.045-.057) .936 .926 .070

*Significant chi-square (p < .001)

45

Figure 7. Standardized loadings and residuals for the hypothesized model.

*Significant pathways (p < .05).

46

Figure 8. Standardized loadings and residuals for Modified Model 1.

*Significant pathways (p < .05).

47

Amotivation did not predict any of the outcome variables and was only negatively

predicted by task climate. Researchers do not agree on how to utilize amotivation in structural

models; some researchers include it as a variable (Ratelle et al., 2007; Standage, Duda, &

Ntoumanis, 2005) and some do not (Fahlman, Martin, McCaughtry, & Shen, 2009; Lonsdale et

al., 2009; Murcia, Lacarcel, & Alvarez, 2010; Wallhead, Haggar, & Smith, 2010). As a

construct, amotivation may not be beneficial in predicting behavior because those who are

amotivated are motivationally directionless and do not act with behavioral intent (Deci & Ryan,

2002). One of the primary objectives of the current study was to understand a young athlete’s

intention to continue in sport. If those that have amotivation do not act with any intention, it is

reasonable to assume that amotivation would not predict intention to continue sport participation

in the model. For that reason amotivation was not included in Modified Model 2.

Model fit for Modified Model 2 was acceptable (see Table 8) and is shown in Figure 9.

Notable direct effects included the following: (a) relatedness and competence both predicted

significantly performance and intention; (b) autonomous motivation predicted significantly

satisfaction and intention; and (c) autonomy continued to not significantly predict any other

variable.

Indirect Effects

Several of the latent variables (autonomy, relatedness, competence, autonomous

motivation, and controlled motivation) could act as mediators in Modified Model 2. Analyses of

the indirect effects showed a number of significant pathways (see Table 9). It was ascertained

that competence mediated the pathways from task climate to performance, satisfaction, and

intention to participate. Autonomous motivation also was shown to be a significant mediator of

numerous pathways. Together, competence and autonomous motivation combined to mediate

pathways from task climate to intention and task climate to satisfaction. Interestingly, controlled

motivation only mediated the pathway from ego climate to performance.

48

Table 9. Indirect Effects for Modified Model 2.

Model Pathway

Task Climate Indirect Effect

� Competence � Satisfaction .060

� Autonomy � Satisfaction .033

� Relatedness � Satisfaction .068

� Autonomous Motivation � Satisfaction .088*

� Controlled Motivation � Satisfaction -.002

� Competence � Autonomous Motivation � Satisfaction .035*

� Autonomy � Autonomous Motivation � Satisfaction .006

� Relatedness � Autonomous Motivation � Satisfaction .008

� Competence � Controlled Motivation � Satisfaction .001

� Autonomy � Controlled Motivation � Satisfaction .000

� Relatedness � Controlled Motivation � Satisfaction .001

� Competence � Intention .077

� Autonomy � Intention -.017

� Relatedness � Intention .115*

� Autonomous Motivation � Intention .073*

� Controlled Motivation � Intention .003

� Competence � Autonomous Motivation � Intention .029*

� Autonomy � Autonomous Motivation � Intention .005

� Relatedness � Autonomous Motivation � Intention .007

� Competence � Controlled Motivation � Intention -.001

� Autonomy � Controlled Motivation � Intention .000

� Relatedness � Controlled Motivation � Intention -.002

� Competence � Performance .144*

� Autonomy � Performance -.037

� Relatedness � Performance .084*

� Autonomous Motivation � Performance -.030

� Controlled Motivation � Performance .005

� Competence � Autonomous Motivation � Performance -.012

� Autonomy � Autonomous Motivation � Performance -.002

� Relatedness � Autonomous Motivation � Performance -.003

� Competence � Controlled Motivation � Performance -.002

� Autonomy � Controlled Motivation � Performance .000

� Relatedness � Controlled Motivation � Performance -.003

49

Table 9 Continued.

Model Pathway

Ego Climate Indirect Effect

� Autonomy � Satisfaction -.008

� Relatedness � Satisfaction -.014

� Autonomous Motivation � Satisfaction .040*

� Controlled Motivation � Satisfaction -.018

� Autonomy � Autonomous Motivation � Satisfaction -.001

� Relatedness � Autonomous Motivation � Satisfaction -.002

� Autonomy � Controlled Motivation � Satisfaction .000

� Relatedness � Controlled Motivation � Satisfaction .000

� Autonomy � Intention .004

� Relatedness � Intention -.023

� Autonomous Motivation � Intention .033*

� Controlled Motivation � Intention .032

� Autonomy � Autonomous Motivation � Intention -.001

� Relatedness � Autonomous Motivation � Intention -.001

� Autonomy � Controlled Motivation � Intention .000

� Relatedness � Controlled Motivation � Intention .000

� Autonomy � Performance .009

� Relatedness � Performance -.017

� Autonomous Motivation � Performance -.014

� Controlled Motivation � Performance .052*

� Autonomy � Autonomous Motivation � Performance .000

� Relatedness � Autonomous Motivation � Performance .001

� Autonomy � Controlled Motivation � Performance .000

� Relatedness � Controlled Motivation � Satisfaction .001

*p < .05

Figure 9. Standardized loadings and residuals for Modified Model 2.

*Significant pathways (p < .05).

Chapter 4

Discussion

The purpose of the current study was to evaluate the coach’s role on youth sport

motivation using aspects of SDT and motivational climate. Youth sport participation declines

rapidly in the teenage years (Corbin et al., 2004) and understanding the aspects of motivation

that influence high school sport participation was one of the primary interests of the current

study. Motivational antecedents of sport satisfaction and self-reported quality of performance

were also assessed.

Discussion of Hypotheses

There were six hypotheses tested for the current study:

1. Task-involved climate, motivational needs satisfaction, intrinsic motivation, integrated

regulation, and identified regulation would be positive predictors of self-perceived

performance and sport satisfaction at the individual and team levels, and intention to

continue in sport at the individual level.

2. Ego-involved climate, introjected regulation, external regulation, and amotivation would

inversely predict sport performance and sport satisfaction at the individual and team

levels, and intention to continue in sport at the individual level.

3. Motivational climate would have a stronger associations with the psychological outcomes

at level 2 than at level 1.

4. Relatedness satisfaction would be a better predictor of the psychological outcomes within

the model than autonomy satisfaction at level 1 and level 2.

5. Intrinsic motivation and integrated regulation would have stronger associations with

intention to continue in sport than identified regulation.

6. Athlete needs satisfaction (competence, relatedness, and autonomy) and a positive

mastery climate would be better predictors of sport satisfaction than identified regulation,

integrated regulation, and intrinsic motivation.

It was hypothesized that the predictors of intention to continue in sport, sport satisfaction,

and perceived performance would be different from level 1 at level 2 because teams are expected

to behave differently from individuals. However, the design effect values were less than two

making the parameter estimates at the second level unreliable. Thus, conducting a multi-level

model was not feasible for the data; however, the nested nature of the data was accounted for

52

within the model syntax. Hypothesis 3 and the references to level 2 in hypotheses 1, 2, and 4

were not tested. This discussion focuses instead on the implications of the structural model

results at level 1.

Furthermore, because data parceling was used to simplify and clarify the model,

hypothesis 5 was not tested as intrinsic motivation, integrated, and identified regulations were

parceled into the latent variable autonomous motivation. While there is theoretical basis for using

each individual motivational regulation (Chatzisarantis, Hagger, Biddle, Smith, & Wang, 2003),

the latent variable structure was already complex and using each motivation regulation would not

have added much new information to the study.

Hypothesis 1. Modified Model 2 partially supported hypothesis 1. Task climate was

positively related to each of the needs satisfaction as hypothesized. This is in agreement with

researchers (Cox & Williams, 2008; Reinboth & Duda, 2006) who also found that mastery

climate satisfied the needs of autonomy, relatedness, and competence. Furthermore, this

supports Ntoumanis’ (2001b) assertion that having a mastery focus can satisfy these

psychological needs. Moreover, task climate significantly related to autonomous motivation

which is consistent with the findings of Parish and Treasure (2003) indicating that coaches who

emphasize a task climate also help to promote the motivation integration process from extrinsic

motivation to a more intrinsic or autonomous style. A direct effect from task climate to

autonomous motivation indicates that athletes who perceive a task climate not only will have

their motivational needs satisfied, but also will experience support for their autonomous

motivation.

Participants’ ratings regarding their needs of autonomy, relatedness, and competence

each provided some intriguing results. Relatedness satisfaction was not significantly associated

with autonomous or controlled motivations. This is inconsistent with researchers who found that

relatedness need satisfaction positively predicted autonomous motivation in dragon boat racers

(McDonough & Crocker, 2007) and elementary physical education students (Standage et al.,

2003a). This result may be explained by the fact that measurement of the variable relatedness, in

this case, focused on the athletes’ feelings of relatedness satisfaction toward their coaches. For

these athletes to have an autonomous motivation, the need of relatedness may have been satisfied

by the presence of friends on the team or parental support rather than by their coaches. For

example, previous research has shown that, for young athletes, peers are an important influence

53

on the sporting environment (Vazou et al., 2005). These athletes may have experienced

camaraderie among their teammates which, in turn, supported their autonomous motivation

regulations.

It is noteworthy, however, that relatedness satisfaction was significantly associated with

the outcome variables. In other words, if the athletes felt close to or connected to their coaches,

they were more likely to rate their performances as better, be more satisfied with their sport

experience, and were more likely to want to continue in their sport. Similarly, Edmunds et al.

(2007) also found that interpersonal involvement was related to ratings of intention to participate.

Relatedness satisfaction from the coach may be more essential for athletes to continue in sport

long term than for their own personal autonomous motivation.

Competence satisfaction significantly related to autonomous motivation, whereas neither

relatedness satisfaction nor autonomy satisfaction was associated with autonomous motivation,

controlled motivation, and amotivation. This indicates that competence may be more essential to

the integration process of motivation regulations than autonomy or relatedness satisfaction for

high school athletes. Similarly, Sproule et al. (2007) found that competence was influential in

enhancing intrinsic motivation. It may be for high school athletes that competence is the one

motivational need that is directly associated with intrinsic motivation because finding inherent

value in the activity of sport is more likely when athletes feel as if they are able to complete the

tasks of the activity.

In the current study, competence satisfaction also was shown to have direct effects on

perceived performance and intention to continue in sport. It seems logical that those who felt

they were able to do the task at hand also felt that they were playing well overall for the season.

Those who felt competent also were more likely to want to continue to play their sport even into

the off-season, which is contrary to a study which found that perceived competence did not

predict sport continuance in adolescent soccer players in Spain (Calvo, Cervello, Jimenez,

Iglesias, & Murcia, 2010). However, if teenagers were participating in any activity in high

school, it seems likely that they would be more likely to continue their participation if feeling

that they were able to accomplish the tasks of that activity. For example, a member of the

marching band would be more likely to continue playing in the band if he felt able to play his

instrument well.

54

Arguably, the most intriguing aspect of the model was that the autonomy need

satisfaction latent variable was not significantly associated with any of the other latent variables.

This is inconsistent with prior research on SDT (Deci et al., 1994; Hagger et al., 2003; Hein &

Hagger, 2007; McDonough & Crocker, 2007; Milne et al., 2008; Reinboth & Duda, 2006; Wang

& Biddle, 2001). This result may perhaps be explained by the use of high school team sport

athletes as participants in this study. While high school athletes do have freedom in sport choice,

once they are a part of a team, they may be accustomed to having the coach as the primary

authority in that setting. High school athletes, in essence, surrender their autonomy because they

trust that the coaches’ decisions are in their best interest. They may not need autonomy

satisfaction to increase their autonomous motivation because they do not hold the expectation of

autonomy within their sport setting. If a coach says, “jump,” the athlete happily responds, “how

high?” without the threat of decreased autonomous motivation.

The variable autonomous motivation was significantly associated with sport satisfaction

and intention to continue in sport which supports Hypothesis 1 and previous research (Wilson &

Rodgers, 2004); however, it was not associated with the self-ratings of performance. Controlled

motivation, on the other hand, was only a significant predictor of performance, which is notable.

The athletes with higher levels of autonomous motivation may not have needed to validate their

play with higher ratings of their performance as much as those who had higher levels of

controlled motivation. One can conclude that those with higher levels of autonomous motivation

were playing for fun or because they wanted to play their sport, while those with higher levels of

controlled motivation were playing because of external motivators and may have needed to be

playing well to make their participation worthwhile. For example, a football player may play the

sport because of parental pressure or for the social status awarded to football players in a

southern high school and may need to justify his participation by believing that he is playing well

because he does not have the innate enjoyment of the activity that would be present if he had

higher levels of autonomous motivation.

Hypothesis 2. Hypothesis 2 was not supported by the model as there were no significant

inverse pathways. This result is discordant with previous findings (Pelletier et al, 2001;

Reinboth & Duda, 2006; Rodgers, 2004; Smith et al., 2007). However, the absence of inverse

relationships seems to indicate that ego climate and controlled motivation did not have a

substantial negative association with the participants’ satisfaction in their sport and their

55

intention to continue playing. While neither ego climate nor controlled motivation was

associated with sport satisfaction or intention to continue in sport, neither was associated with

the athletes not enjoying their sport or not wishing to continue their participation as well. The

observation of non-significant pathways also gives credence to the idea that competition is not a

negative aspect of sports. These athletes are participating in a competitive environment. At this

point in their sporting careers, most are not playing just because it is fun or because of social

benefits, but also because they experience the joys of competing and challenging themselves. In

light of this, it is comforting to know that a competition-focused environment was not associated

with potentially adverse outcomes in these younger athletes.

Hypothesis 4. Hypothesis 4, on the other hand, was supported by the model. Autonomy

satisfaction was not significantly associated with any of the other latent variables; whereas,

relatedness satisfaction was significantly associated with each of the outcome variables. This

supports a previous finding where high school and youth sport coaches valued relationships with

their athletes over providing autonomy support (Zomermaand, 2010). It may be inferred based

on these results that athletes are in agreement with coaches that the coach-athlete relationship

needs to be positive and supportive to produce sport satisfaction, intention to continue in sport,

and a higher self-assessment of performance. This may be because coaches provide essential

feedback on athletes’ performances and coaches are sources of several aspects of motivational

information (Begoechea & Streen, 2007). These aspects could impact the participants’ ratings of

the outcomes of the present study.

Hypothesis 6. Hypothesis 6 was not supported as autonomous motivation was

significantly associated with sport satisfaction along with relatedness satisfaction, but autonomy

and competence satisfaction did not have significant relationships with sport satisfaction. For

these high school athletes, higher levels of satisfaction in sport were found to be associated with

the satisfaction of the need of relatedness and/or with higher levels of autonomous motivation.

This result may indicate that satisfaction of the need of competence, while seemingly a facet

required for autonomous motivation, is not sufficient for sport satisfaction. Athletes can feel

competent without being satisfied or can be satisfied in their sport without feeling competent.

Likewise, Biddle, Wang, Chatzisarantis, and Spray (2003) did not find that competence

significantly influenced sport enjoyment, but Scarpa and Nart (2012) did find a positive

relationship between competence and enjoyment. These conflicting results may be due to

56

problems in using multiple measurements of competence (Biddle et al., 2003) or may be due to

differing populations and settings. Nonetheless, it seems that sport satisfaction in high school

sport may be less about how competent athletes feel, but more about the social aspects of sport

such as being among their peers and feeling supported by their coaches.

Discussion of Indirect Effects

The pathways for indirect effects within the model were evaluated. There seems to be

evidence suggesting that competence and autonomous motivation may mediate the pathways

from task climate to sport satisfaction and intention to participate. These constructs within SDT

have also been found to mediate relationships in other models with differing variables (Ambrose

& Anderson-Butcher, 2007; Cox & Williams, 2008; Lonsdale et al., 2009; Silva et al., 2010;

Standage et al., 2003). These results may mean that for a task climate to produce feelings of

sport satisfaction and intention to continue in sport, competence satisfaction and higher levels of

autonomous motivation might need to be present as well. As previously discussed, competence

may not be sufficient for sport satisfaction. However, it perhaps is key mediator in the model

pathways that result in sport satisfaction and intention to participate. For example, if a coach

emphasizes mastery by encouraging skill-focused activities, and athletes feel more competent in

those skills which contributes to building autonomous motivation, athletes might be more likely

to be enjoying the sport in which they are participating and wish to continue playing the sport.

This seems to be in agreement with Standage et al. (2003) who found that self-determined

motivation and needs satisfaction variables mediated the relationships between mastery climate

and intention to participate in physical activity.

Autonomous motivation also was a sole mediator of the pathways from task climate to

satisfaction, task to intention, ego climate to intention, and ego climate to satisfaction. In other

words, having an autonomous style of motivation mediated the relationships from the

motivational climates to the outcome variables which coincides with past research that found that

motivation regulations mediated relationships in a model that included psychological outcomes

such as exhaustion (Lonsdale et al., 2009). These results seem to indicate that motivational

climate does not solely have a direct effect on a high school athlete’s perception of their

happiness in sport or whether or not they are going to play the sport even when it is not in

season. The coach could be producing a task climate, but if the athlete does not have an

autonomous style of motivation, the athlete may not feel happy in the situation and want to

57

continue participating. Likewise, if the coach is producing an ego climate, athletes may not feel

dissatisfied with their sport experience because their autonomous style of motivation was already

in existence.

Additionally, it was observed that relatedness satisfaction acted as a mediator of the

pathway from task climate to intention to continue and the pathway from task to performance.

This finding supports prior research suggesting that relatedness, competence, and autonomy

satisfaction act as mediators in structural models involving SDT constructs (Standage et al.,

2003). Once again, the presence of a task climate was not sufficient for positive feelings of

performance and the intention to continue playing sport; the athlete may also need to have felt a

sense of relatedness satisfaction with the coach. This seems to point to the necessity of coaches

not only to focus on mastery, but to emphasize a personal relationship with their players to

encourage their sense of confidence in their performance and their desire to continue playing

sport well into the future. Once again, coaches are essential to providing feedback to the athletes

which seems to promote overall well-being in sport.

Furthermore, competence satisfaction was a sole mediator of the pathway from task

climate to self-rated performance. This observation supports the idea that those who believe they

are competent in their abilities also believe that they are performing well (Horn, 1985). However,

it is critical to note that this may only happen if a task climate also is present. Competence was

not a significant mediator from ego climate to perceptions of performance. A task climate

satisfied motivational needs of relatedness and competence which, in turn, produced positive

outcomes of well-being in the athletes. This may show itself in sport situations such as a soccer

player who finds that her coach focuses on skill improvement producing positive feelings in

herself that she can accomplish those skills, and, consequently, she performs well in practice and

in competition.

Finally, it is intriguing to note the pathways with perceived performance as the outcome

variable. The use of self-reported performance as an outcome variable is rare in the literature. If

performance was used as a variable, others have used objective measures of performance like

winning percentages (Cumming et al., 2007) or results of a tournament (Gillet et al., 2010).

Using the objective outcome of performance, Gillet et al. (2010) found that self-determined

motivation was a mediator of the autonomy support to performance pathway which is

inconsistent with the present study in which it was observed that controlled motivation acted as a

58

mediator of the pathway from ego climate to performance. This could indicate that those who are

experiencing an ego climate and have a controlled motivational style validate their participation

by perceiving their performance as high. These athletes may perhaps be participating in their

sport because they are very skilled at what they do. There are anecdotal accounts that suggest

that some accomplished young athletes do not always participate in sport because of their love

for it, but because of external forces and accomplishments that make it difficult or almost

impossible to quit their sport. In his autobiography, the former tennis phenomenon Andre Agassi

admits that he played tennis for many years even though he hated the sport. He played because

everyone around him pushed him to play and because tennis was what he did well (Agassi,

2009). Future research could focus more specifically on the mediating effects of controlled

motivation on the ego climate and performance relationship.

Limitations

Although this study provided interesting findings, there were several limitations. This

study was conducted using cross-sectional data. Cause-effect relationships cannot be determined

from this data and predicting performance in differing situations and over time would be

inadvisable. Additionally, the data were collected through a self-report survey that was

monitored by the athletes’ coaches. Relying on self-report brings in to question the honesty and

accuracy of the responses. Even though confidentiality was emphasized, the athletes may have

wanted to be perceived as having the socially desirable traits of satisfaction, being intrinsically

motivation, and as a good athlete. In addition, because the coach was present, these athletes may

not have trusted that their coaches were not going to read their responses and, therefore, felt

pressure to rate their perceptions of the coaches as more socially acceptable inadvertently

skewing the results. Furthermore, this study would have benefited from having several more

teams participate. Higher numbers of participants and groups not only would have allowed the

Mplus 6.0 software to calculate the models, but it may have influenced the ICC values to allow

for multi-level modeling to be conducted. It was also noted in data analysis that for some of the

variables there was very little variability across the groups resulting in some difficulty with the

models’ analyses. A wider demographic and geographic sample may have been needed to

increase the variability. Moreover, more males than females participated in this study which

may have influenced the perceptions of the variables. Males may differ from females in their

views of the coach and of motivation which may have affected the overall data. Lastly, the

59

researcher was not present when the questionnaires were being completed by the participants.

The questionnaires were either administered by the coaches of teams or were self-administered

online not allowing the participants to ask for clarification on the individual items or on each

section which may have altered some of the responses.

Future Research

In future studies, multi-level modeling ought to be used to model these pathways at the

team level. The nested nature of athletes on teams, like students in classrooms, necessitates that

for sport psychology researchers hierarchical modeling might be a better option when working

with team sports. Researchers should also continue to investigate the indirect effect pathways

observed in the present model. Studies may be developed that specifically investigate mediations

that may exist with the latent variables of the present study. For example, task climate satisfied

each of the three motivational needs, but only relatedness and competence served as mediators

within the model. This finding could be examined further. Furthermore, because most of the

participants who partook in this study were from one state in the southern United States and were

all members of teams and not individual sport athletes, similar research should be conducted

with differing populations and settings. Specifically, it would be intriguing to investigate

whether or not these same relationships exist for high school individual sport athletes like

swimmers or tennis players. These athletes are still on teams for their high school, but do not

work together in the same way as team sport athletes. Finally, as this was cross-sectional survey

research, other research methods should be employed using similar variables. Experimental

research could be done that manipulates the coach-initiated motivational climate and then

evaluates its effects on athletes’ and teams’ motivational regulations and the outcomes of

performance, sport satisfaction, and intention to continue in sport.

Conclusion

With the renewed emphasis within our culture on keeping young people physically

active, it is paramount for researchers to understand psychological and environmental aspects of

sport participation. The current study evaluated the impact of motivational climate,

psychological needs satisfaction, and motivational regulations on intention to continue

participation in sport, sport satisfaction, and self-rated performance. The results indicated that

task climate, feeling related to the coach, feeling competent, and autonomous motivation are

factors in sport satisfaction and intention to continue in sport for high school athletes.

60

Task climate was found to be associated with the satisfaction of the motivational needs of

autonomy, relatedness, and competence; while an ego climate was not related to any of the

psychological needs. Feelings of competence in sport were found to have a direct effect on an

autonomous motivation making it more likely that high school athletes will have a sense of

satisfaction and will continue to play their sport even when the season is complete.

Perception of performance was included as an outcome variable in the model to provide

a concrete reason for coaches to adopt mastery and needs supported coaching styles, and the

results seem to support that reasoning. It was found that perceived performance was predicted

by the athlete’s perception that the need of relatedness was satisfied by the coach and the

athlete’s perception of competence in performing the skills of their sport. A task climate

supports the athletes’ motivational needs and then, in turn, the athletes want to continue in sport,

are happier playing their sport, and actually perceive their performances as good. However, it

must also be mentioned when discussing perception of performance that the pathway from ego

climate to controlled motivation to performance was also significant indicating that an athlete did

not need to perceive a task climate or have their motivational needs satisfied to see their

performance as positive. In this model, with the outcome measures of athlete well-being, task

climate and the satisfaction of needs seem to be central facets of improved psychological

outcomes in the athletes.

In conclusion, many coaching clinics and certifications are available for those looking to

improve as coaches. As part of these continuing education programs, promoting mastery in

practice and competition environments in order to support athletes’ motivational needs

satisfaction should be included in the instruction. Coaches also ought to focus on building

relationships with their athletes. These relationships seem to be a key factor in keeping athletes

satisfied in their sports participation, their overall performances, and their intention to continue

their sport participation. The goal of coaches undoubtedly is to have positive competition results

(i.e. win), but the well-being of athletes should also be paramount. Promoting a positive

motivational environment accomplishes that mission.

61

Appendix A

Measures

Motivational Climate Scale for Youth Sports (Smith, Smoll, & Cumming, 2008)

Here are some statements about what your current team is like. Please read each one and mark

the number that is most correct. If there was more than one coach on your team, the questions

are about the coach that you spend most of your time with.

Not at All True Somewhat True Very True

1. Winning games is the most important

thing for the coach. 1 2 3 4 5

2. The coach makes players feel good

when they improved a skill. 1 2 3 4 5

3. The coach spends less time with the

players who weren’t as good.

1 2 3 4 5

4. The coach encourages us to learn new

skills.

1 2 3 4 5

5. The coach tells us which players on

the team are the best.

1 2 3 4 5

6. The coach tells players to help each

other get better. 1 2 3 4 5

7. The coach tells us that trying our best

is the most important thing. 1 2 3 4 5

8. The coach pays the most attention to

the best players. 1 2 3 4 5

9. Coach says that teammates should

help each other improve their skills. 1 2 3 4 5

10. Players are taken out of the game if

they make a mistake. 1 2 3 4 5

11. The coach says that all of us are

important to the team’s success. 1 2 3 4 5

12. Coach tells us to try to be better than

our teammates. 1 2 3 4 5

62

BRSQ—Behavioral Regulation in Sport Questionnaire (Lonsdale et al., 2008)

Please indicate to what extent each of the following items is true of yourself.

I participate in my sport… Not at all true Somewhat true Very True

1. Because I enjoy it. 1 2 3 4 5 6 7

2. Because I like it. 1 2 3 4 5 6 7

3. Because it’s fun. 1 2 3 4 5 6 7

4. Because I find it

pleasurable. 1 2 3 4 5 6 7

5. Because it’s a part of who

I am. 1 2 3 4 5 6 7

6. Because it’s an

opportunity to just be

who I am.

1 2 3 4 5 6 7

7. Because what I do in

sport is an expression of

who I am.

1 2 3 4 5 6 7

8. Because it allows me to

live in a way that is true

to my values.

1 2 3 4 5 6 7

9. Because the benefits of

sport are important to me. 1 2 3 4 5 6 7

10. Because it teaches me

self-discipline. 1 2 3 4 5 6 7

11. Because I value the

benefits of my sport. 1 2 3 4 5 6 7

12. Because it is a good way

to learn things which

could be useful to me in

my life.

1 2 3 4 5 6 7

13. Because I would feel

ashamed if I quit. 1 2 3 4 5 6 7

14. Because I would feel like

a failure if I quit. 1 2 3 4 5 6 7

15. Because I feel obligated

to continue. 1 2 3 4 5 6 7

16. Because I would feel

guilty if I quit. 1 2 3 4 5 6 7

17. Because if I don’t other

people will not be

pleased with me.

1 2 3 4 5 6 7

18. Because I feel pressure

from other people to play. 1 2 3 4 5 6 7

19. Because people push me

to play. 1 2 3 4 5 6 7

63

20. To satisfy people who

want me to play. 1 2 3 4 5 6 7

21. But I wonder what’s the

point. 1 2 3 4 5 6 7

22. But I question why I

continue. 1 2 3 4 5 6 7

23. But the reasons why are

not clear to me anymore. 1 2 3 4 5 6 7

24. But I question why I am

putting myself through

this.

1 2 3 4 5 6 7

64

The Psychological Need Satisfaction in Exercise Scale (revised for sport) (Wilson, et al., 2006)

Please indicate how strongly agree or disagree with the following statements.

Strongly Strongly

Disagree Disagree Agree Agree

1. I feel that I am able to

complete skills that are

personally challenging.

1 2 3 4 5 6 7

2. I feel confident that I can

do even the most

challenging skills.

1 2 3 4 5 6 7

3. I feel confident in my

ability to perform skills

that personally challenge

me.

1 2 3 4 5 6 7

4. I feel capable of doing

even the most

challenging skills.

1 2 3 4 5 6 7

5. I feel good about the way

I am able to complete

challenging skills.

1 2 3 4 5 6 7

6. I feel free to participate in

sport in my own way. 1 2 3 4 5 6 7

7. I feel free to make my

own decisions in my

sport.

1 2 3 4 5 6 7

8. I feel like I have a say in

choosing the skills that I

do.

1 2 3 4 5 6 7

9. I feel free to choose

which sport I participate

in.

1 2 3 4 5 6 7

10. I feel like I am the one

who decides what sports

that I do.

1 2 3 4 5 6 7

11. I feel attached to my

coaches because they

accept me for who I am.

1 2 3 4 5 6 7

12. I feel like I share a

common bond with my

coaches when we work

together.

1 2 3 4 5 6 7

13. I feel a sense of

camaraderie with my

coaches because we

participate in sport for the

1 2 3 4 5 6 7

65

same reasons.

14. I feel close to my coaches

and teammates who

appreciate how difficult

sport can be.

1 2 3 4 5 6 7

15. I feel connected to my

coaches when we work

together.

1 2 3 4 5 6 7

16. I feel like I get along with

my coaches while we

work together.

1 2 3 4 5 6 7

66

Intention to Participate (Chatzisarantis et al., 1997)

Please indicate how likely each item is for you.

Very Unlikely Likely Very Likely

1. I am determined to play

sport at least 3 times a

week after the season is

over.

1 2 3 4 5 6 7

2. I intend to play sport at

least 3 times a week

during the off-season.

1 2 3 4 5 6 7

3. I plan to continue to play

sport next season. 1 2 3 4 5 6 7

Sport Satisfaction (Duda & Nicholls, 1992)

Please indicate your level of agreement or disagreement with each of the following items.

Stongly Disagree Agree Strongly

Disagree Agree

1. I usually have fun doing my sport. 1 2 3 4 5

2. I usually enjoy playing my sport. 1 2 3 4 5

3. I usually find my sport interesting.

1 2 3 4 5

4. I usually get involved in practices.

1 2 3 4 5

5. In practice, I usually feel that time

flies.

1 2 3 4 5

Performance

On a scale of 1 (extremely poor performance) to 10 (extremely good performance) rate how well

you think you are performing in your sport.

1. Rate how well you are currently performing. ____________

2. Rate how well you have performed overall this season. __________

3. Rate your improvement since the beginning of the season. _________

67

Demographic Assessment

1. ____ Male _____ Female

2. Ethnicity

a. African American

b. Asian

c. Hispanic

d. Native American

e. White/Caucasian

f. Other (please specify)________________________________

3. Sport ________________________

4. Number of years in sport ____________

5. Number of years playing for your current coach _____________

6. Number of sports played competitively _______________

7. Year in School

a. Freshman

b. Sophomore

c. Junior

d. Senior

68

Appendix B

Consent and Assent Forms

Parental Informed Consent Form

This study is being conducted by Kristin Zomermaand, PhD student, Department of

Educational Psychology and Learning Systems (Sport Psychology) at Florida State University.

The purpose of this study is to assess the experiences of athletes in high school team sports.

Please read this form carefully before allowing your child to participate.

If you consent to your child participating in this study, your child will be asked to answer

several questions about your child’s sport experience. This one-time survey will last

approximately a half an hour. The information obtained in this study will be used to improve our

knowledge of the high school athlete sport experience.

There is minimal risk associated with taking part in this study. Your child does not have

to provide any information which he/she does not feel comfortable providing. Your child is free

to decline to answer any question he/she so chooses. Participation in this study is voluntary.

Your child may withdraw from this study at any time and his/her answers will not be used.

All information regarding your child’s identity will be kept confidential to the extent

afforded by law. All materials including any written materials will be stored securely at the

researcher’s home. Electronic copies of the materials will be password protected. These

materials will be used only by the researcher.

If you have any questions in regards to this study feel free to contact the researcher,

Kristin Zomermaand, at any time in the course of the study. If you are concerned about the study

or if you feel your child has been put at risk, please contact the Florida State University IRB at

2010 Levy St., Research Building B, Suite 276, Tallahassee, FL 32306-2742, or by phone at

850-644-8633.

Please make a copy of this form for your records.

I have read the above information. I consent to my child’s participation in this study.

______________________________ ____________________________

Signature of Parent Date

69

Informed Assent Form

This study is being conducted by Kristin Zomermaand, PhD student, Department of

Educational Psychology and Learning Systems (Sport Psychology) at Florida State University.

This study is about your personal sport experience and the purpose of this study is to become

more familiar with athlete experiences in team sports. Please read this form carefully before

deciding whether or not to participate.

If you agree to participate in this study, you will be asked to provide your e-mail address

at the bottom of this form. The link to the questionnaire website will be sent to this e-mail

address. You will be asked to complete a questionnaire about your sport experience online. This

one-time survey will last approximately a half an hour. The information gained in this study will

be used to improve our knowledge of the high school athlete sport experience.

There is minimal risk associated with taking part in this study. You do not have to give

any information which you do not feel comfortable giving. You do not have to answer any

question if you do not want to. Participation in this study is voluntary. You may withdraw from

this study at any time and your answers will not be used.

All information about your identity will be kept confidential to the extent afforded by

law. No one, including coaches, teachers, and school administrators, will have access to your

answers. These and any other materials, including any written materials, will be stored securely

at the researcher’s home. Electronic copies of the materials will be password protected. These

materials will be used only by the researcher.

If you have any questions in regards to this study feel free to contact the researcher,

Kristin Zomermaand at any time in the course of the study. If you are concerned about the study

or if you feel you have been put at risk, please contact the Florida State University IRB at 2010

Levy St., Research Building B, Suite 276, Tallahassee, FL 32306-2742, or by phone at 850-644-

8633.

I have read the above information. I agree to participation in this study.

______________________________ ____________________________

Signature of Participant Date

E-mail: ________________________________________________________________

(The website link for the questionnaire will be sent to this address upon receipt of this form.)

70

Appendix C

IRB Approval Letters

From: Human Subjects (humansubjects@magnet.fsu.edu)

To: Kristin Zomermaand Date: Mon, November 9, 2009 10:46:08 AM

Cc: Robert Eklund

Subject: Use of Human Subjects in Research - Approval Memorandum

Office of the Vice President For Research

Human Subjects Committee

Tallahassee, Florida 32306-2742

(850) 644-8673 · FAX (850) 644-4392

APPROVAL MEMORANDUM

Date: 11/9/2009

To: Kristin Zomermaand

Address: 2750 Old Saint Augustine Rd. #G61 Tallahassee, FL 32301

Dept.: EDUCATIONAL PSYCHOLOGY AND LEARNING SYSTEMS

From: Thomas L. Jacobson, Chair

Re: Use of Human Subjects in Research

Motivation in Youth Sport: A Hierarchical Model

The application that you submitted to this office in regard to the use of human subjects in the

research proposal referenced above has been reviewed by the Human Subjects Committee at its

meeting on 11/04/2009. Your project was approved by the Committee.

The Human Subjects Committee has not evaluated your proposal for scientific merit, except to

weigh the risk to the human participants and the aspects of the proposal related to potential risk

and benefit. This approval does not replace any departmental or other approvals, which may be

required.

If you submitted a proposed consent form with your application, the approved stamped consent

form is attached to this approval notice. Only the stamped version of the consent form may be

used in recruiting research subjects.

If the project has not been completed by 11/3/2010 you must request a renewal of approval for

continuation of the project. As a courtesy, a renewal notice will be sent to you prior to your

71

expiration date; however, it is your responsibility as the Principal Investigator to timely request

renewal of your approval from the Committee.

You are advised that any change in protocol for this project must be reviewed and approved by

the Committee prior to implementation of the proposed change in the protocol. A protocol

change/amendment form is required to be submitted for approval by the Committee. In addition,

federal regulations require that the Principal Investigator promptly report, in writing any

unanticipated problems or adverse events involving risks to research subjects or others.

By copy of this memorandum, the Chair of your department and/or your major professor is

reminded that he/she is responsible for being informed concerning research projects involving

human subjects in the department, and should review protocols as often as needed to insure that

the project is being conducted in compliance with our institution and with DHHS regulations.

This institution has an Assurance on file with the Office for Human Research Protection. The

Assurance Number is IRB00000446.

Cc: Robert Eklund, Advisor

HSC No. 2009.3274

72

Office of the Vice President For Research

Human Subjects Committee

Tallahassee, Florida 32306-2742

(850) 644-8673 · FAX (850) 644-4392

RE-APPROVAL MEMORANDUM

Date: 8/12/2011

To: Kristin Zomermaand

Address: 2750 Old Saint Augustine Rd. #G61 Tallahassee, FL 32301

Dept.: EDUCATIONAL PSYCHOLOGY AND LEARNING SYSTEMS

From: Thomas L. Jacobson, Chair

Re: Re-approval of Use of Human subjects in Research

Motivation in Youth Sport: A Hierarchical Model

Your request to continue the research project listed above involving human subjects has been

approved by the Human Subjects Committee. If your project has not been completed by

8/8/2012, you must request a renewal of approval for continuation of the project. As a courtesy, a

renewal notice will be sent to you prior to your expiration date; however, it is your responsibility

as the Principal Investigator to timely request renewal of your approval from the committee.

If you submitted a proposed consent form with your renewal request, the approved stamped

consent form is attached to this re-approval notice. Only the stamped version of the consent

form may be used in recruiting of research subjects. You are reminded that any change in

protocol for this project must be reviewed and approved by the Committee prior to

implementation of the proposed change in the protocol. A protocol change/amendment form is

required to be submitted for approval by the Committee. In addition, federal regulations require

that the Principal Investigator promptly report in writing, any unanticipated problems or adverse

events involving risks to research subjects or others.

By copy of this memorandum, the Chair of your department and/or your major professor are

reminded of their responsibility for being informed concerning research projects involving

human subjects in their department. They are advised to review the protocols as often as

necessary to insure that the project is being conducted in compliance with our institution and

with DHHS regulations.

73

Cc:

HSC No. 2011.6751

74

Appendix D

Recruitment E-mail

Dear

Hi, my name is Kristin Zomermaand. I am a doctoral candidate at Florida State University. I am

conducting research regarding the athlete’s experience in team sports. I was wondering if you

would allow your athletic teams to participate in this research. I am looking for teams (varsity,

junior varsity, or freshman) which are in mid-season. The athletes will need approximately 15

minutes to fill out an online survey in which they will be asked questions pertaining to their

experience as a high school athlete. The survey does not ask personal questions and the athletes’

identities will be kept confidential. Parental consent forms will be sent out to the parents if you

are willing to allow participation in this study. Participation in this study is completely voluntary.

This research is being conducted as part of my doctoral dissertation. Your school’s participation

would be greatly appreciated. The results will be provided to you if you would like.

If you have any questions, please feel free to respond to this e-mail. I would be happy to talk

further about this study with you.

Thanks for your consideration,

Kristin L. Zomermaand, M. A.

Doctoral Candidate

Sport Psychology

Educational Psychology and Learning Systems

College of Education

Florida State University

75

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Biographical Sketch

Kristin Zomermaand

Kristin L. Zomermaand was born in Sioux Center, IA and developed a love for sport and

psychology at a young age. She played soccer and studied psychology at Dordt College where

she was named a two-time Academic All-American before moving to California to study

Applied Sport Psychology at John F. Kennedy University. She received her Master of Arts

Degree in 2003. Kristin continued her education at Florida State University where she pursued a

Doctoral degree in Sport Psychology. In the process of her studies she has worked with many

teams and athletes as a sport psychology consultant. She published her first article in 2010 and

has continued her research into motivation in sport. From 2010-2012, she was full-time faculty

at Louisiana College in Pineville, LA and continues to teach online classes for the Human

Behavior Department there.