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1 Florida State University Libraries Electronic Theses, Treatises and Dissertations The Graduate School 2012 Motivation and Coping in the Sport of Triathlons Frederick David Dietrich Follow this and additional works at the FSU Digital Library. For more information, please contact

2 THE FLORIDA STATE UNIVERSITY COLLEGE OF EDUCATION MOTIVATION AND COPING IN THE SPORT OF TRIATHLONS By FREDERICK DAVID DIETRICH A Dissertation submitted to the Department of Education Psychology and Learning Systems In partial fulfillment of the requirements for the degree of Doctor of Philosophy Degree Awarded: Summer Semester, 2012 Copyright 2012 Frederick Dietrich All Rights Reserve i

3 Frederick Dietrich defended this dissertation on June 19, The members of the supervisory committee were: Robert Eklund Professor Directing Dissertation Lynn Panton University Representative Gershon Tenenbaum Committee Member David Eccles 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. ii

4 For my wife Karen, without whose support I would not have gotten this done. Also for my parents, educators. iii

5 TABLE OF CONTENTS LIST OF TABLES... vi LIST OF FIGURES... viii ABSTRACT... ix CHAPTER INTRODUCTION... 1 Self-Determination Theory... 3 Theory on Passion... 7 Cognitive Motivational Relational Theory of Emotions... 8 CHAPTER LITERATURE REVIEW Motivation Passion Coping in Sport Motivation and Coping in the Sport of Triathlons Research questions CHAPTER METHOD Participants Procedures Data Analysis CHAPTER RESULTS Research Question Research Question CHAPTER DISCUSSION Model on Passion, Motivation, and Coping Passion, Ironman Competitions, and Training Gender Differences Level of Participation Differences Strengths, Limitations and Future Research Directions APPENDIX A MANOVA TABLES APPENDIX B Measurement Model APPENDIX C APPENDIX D iv

6 INFORMED CONSENT LIST OF REFERENCES BIOGRAPHICAL SKETCH v

7 LIST OF TABLES 3.1 Minimums, Maximums, Means and Standard Deviations for Data Obtained from the First Survey Survey Structure Explanation of Variables for Comparison and Categorization Means, Standard Deviations, Minimums, Maximums, and Cronbach s for the BRSQ Subscales, and Passion Scales Means, Standard Deviations, Minimums, Maximums, and Cronbach s for the Situational BRSQ Subscales, CICS and A-SAGS Summary of Intercorrelations for Subscales of BRSQ and Passion Scale Range, Mean, Standard Deviations, and Cohen s d for Age, Years of Experience, Ironman s Completed, Strenuous Physical Activity, Metabolic Equivalent, Total Triathlons, and Passion Based on Gender Range, Mean, Standard Deviations, and Cohen s d for Age, Years of Experience, Ironman s Completed, Strenuous Physical Activity, Metabolic Equivalent, Total Triathlons, and Passion Based on Gender Means and Standard Deviations on Passion, LTEQ, and MET Scores by Triathlon Groups Obsessive Passion Post Hoc Statistics, Means, Standard Deviations and Effect Size Significant LTEQ Strenuous and MET Tukey Post Hoc Statistics, Means, Standard Deviations and Effect Size in Triathlete Groups ANOVAs by Ironman Participation for the Variables Harmonious and Obsessive Passion, and LTEQ 2 scores Robust Tests of Equality of Means Mean, Standard Deviations for Passion Type, Metabolic Equivalent, LTEQ Mild, Moderate and Strenuous Physical Activity, Years of Experience and Total Triathlon Events based on Ironman Participation Post Hoc Statistics and Effect Sizes for Harmonious and Obsessive Passion, Metabolic Equivalent, LTEQ Moderate and Strenuous Physical Activity, Years of Experience and Total Triathlon Events based on Ironman Participation vi

8 4.13 Pairwise Analysis Fit Indices Results for Subscale of Social Withdrawal with each of the other CICS Subscales Fit Indices Results for All Models Indirect Effects Testing Motivation as Mediators Between Passion and Coping Direct and Indirect Effects Testing Motivation as Mediators Between Passion and Coping C.1 Item Factor Loading and Residuals for Model 1.2 Depicted in Figure C.2 Item Factor Loadings and Residuals for Parceled Model 2 Depicted in Figure C.3 Item Factor Loadings and Residuals for Parceled Model 2.2 Depicted in Figure vii

9 LIST OF FIGURES 1.1 Representation of the Self-determination theory component, organismic integration theory (OIT; Ryan and Deci, 2007). Modified from Hagger and Chatzisarantis (2007) Model of associations between self-determination, coping, goal attainment, and variations in affect (Amiot, Gaudreau, & Blanchard, 2004) Model of relationships between dispositional perfectionism, motivation, coping, goal attainment and life satisfaction. + = positive relationship, - = negative relationship (Gaudreau & Antl, 2008) Proposed model integrating passion, motivation, and coping on goal attainment and future intentions to run triathlons Model 1 integrating passion, motivation, and coping on goal attainment and future intentions to run triathlons including pathway coefficients Model 1.2 with modification indices integrating passion, motivation, and coping on goal attainment and future intentions to run triathlons including pathway coefficients Model 2 with parceled indicators integrating passion, new motivation variables, and coping on goal attainment and future intentions to run triathlons including pathway coefficients Model with direct paths on to the outcome variable Goal Attainment Model with direct paths on to the outcome variable Future triathlon events Model 2.2 integrating passion, new motivation variables, and coping on goal attainment and future intentions to run triathlons including pathway coefficients B.1 The measurement model as tested allowing for MGA and EE errors to covary viii

10 ABSTRACT The purposes of this study were to examine the links between self-determination theory (Deci & Ryan, 1985) and the dualistic model of passion (Vallerand, 2008) and to examine the coping strategies used by triathletes differentiated by motivation and passion type. Additionally the differences between triathletes with sustained involvement in Ironman distance triathlons and those with little or no Ironman distance experience were also compared. Triathletes (n = 299) completed several measures assessing passion, motivation, leisure time exercise, coping strategies, and goal attainment via two online surveys. Structural equation modeling (SEM) methods were employed to test several models involving situational motivation (Lonsdale et al., 2008) and coping strategies (CICS; Gaudreau and Blondin, 2002) as mediators between passion and goal attainment and potential future triathlon event participation. Results revealed that the original full structural model did not fit to the data well but one with parceled indicators fit reasonable well to the data. Examination of the path coefficients, however, indicated that motivation and coping were mediators between passion and goal attainment but not future triathlon intentions. Harmonious passion was a strong predictor of situational autonomous motivation and coping was a moderately strong mediator between motivation and goal attainment. Future intentions to run triathlon events were better predicted by direct paths from autonomous motivation and obsessive passion. Keywords: Self-determination, passion, coping, triathlons ix

11 CHAPTER 1 INTRODUCTION Robert Singer (1996) suggested: There's got to be a way to associate regular involvement in vigorous physical activity as something we look forward to and are dedicated to something we miss when we don't do it (p. 249). Both Deci and Ryan s (1985) Self- Determination Theory (SDT) and Vallerand s dualistic model of passion (Vallerand et al., 2003; Vallerand, 2008) offer motivational explanations that potentially address Singer s interest in forwarding that suggestion. People repeatedly engage in activities they find enjoyable and are intrinsically motivated to participate in; some to the point where they become passionate about the activity and it becomes a part of their identity. Can an overall feeling of passion for the sport of triathlons predict motivation for participation in a specific competition and the coping strategies used to affect goal attainment and impact planned future participation? Is this a possible mechanism that can lead to sustained physical activity? Within the tenets of SDT, Deci and Ryan (1985) state that a person s motivation toward a particular activity will become self-determined if participating in that activity satisfies the three psychological needs of competence, autonomy, and relatedness. Therefore, people participate for internal reasons, such as pure enjoyment of the activity or because the activity is integrated into their identity. Individuals autonomously seek out an activity in an environment that helps to satisfy these needs and as a result become self-determined toward that activity. A person with less self-determined motivation participates for less internal reasons, such as feelings of guilt or in order to please someone else. Frederick and Ryan (1993) noted a difference in motivation type based on context, in particular either one of exercise or sport. Individuals in an exercise setting cited more extrinsic motivators that focused on body image while individual sport participants cited enjoyment as a main motivator to participate in their sport. Exercising for extrinsic motives can lead to poor adherence while intrinsic motives appear to indirectly foster adherence through positive affect (Markland & Ingledew, 2007). Therefore, the right environment can foster intrinsic motivation and thusly benefit sustainment of physical activity. The triathlon appears to provide just this environment. In 1982 the U.S. Triathlon Association and the American Triathlon Association merged to become USA Triathlon. Since that time, membership in this association has steadily grown to 1

12 its current enrollment of over 100,000. This number does not include those individuals who participate in triathlons but are not card-carrying USA Triathlon members (United States Olympic Committee, 2009). Since its inception, the sport has shown remarkable growth in participation. The triathlon combines three separate disciplines (i.e., swimming, cycling, running) into a single competitive event (United States Olympic Committee, 2009). The distance for each portion varies across the different type of events. For example sprints are comprised of a 750- meter swim, 20-kilometer cycle, and a 5-kilometer run and an Ironman/ultra distance consists of a 2.4-miles swim, 112-mile cycle, and a 26.2-mile run. Marathon and distance runners in San Diego, California started participating in triathlons as cross-training exercises with the first ever official event occurring in The ironman was born in Hawaii when one of those distance runners moved to the state. The popularity of the sport has grown steadily according to USA Triathlon (2009), with participation in recent years between 200,000 and 250,000 athletes competing in events each year. The overwhelming majority of these athletes are amateurs who vary in age. Despite its growing popularity, there is a dearth of scientific research on the motivation of individuals who initiate and continue participation in this sport. The Ironman distance has been growing in popularity as well. The Hawaii Ironman was the first of its kind (United States Olympic Committee, 2009). It has grown from a race involving 12 men in its first running in 1978 to a current race enrollment limited to 1800 participants from over 10,000 applicants (World Triathlon Corporation, 2010). There are now upwards of 10 annual Ironman distance events across the globe each year. The grueling aspects of the race have been depicted in media coverage and are evidenced by the number of did not finish race participants. Participating in the Ironman is both physically and mentally taxing. In part, people who want to finish an Ironman triathlon must be not only physically fit but also have strong motivation to complete the whole race. As a result, a person must also develop strategies to cope with the physical and psychological stressors involved in completing a race. In order to explore the psychological aspects of motivation and coping associated with participating in the Ironman triathlon one must understand the theories and models underlying these psychological constructs. The underlying theories and model examined for this 2

13 dissertation include: Self-determination theory (Deci & Ryan, 1985), the Dualistic model of Passion (Vallerand, 2008), and Cognitive Motivational Relational theory on stress and coping (Lazarus, 1999). Self-Determination Theory In order for human beings to participate in sport they must be motivated in some way to exhibit a specific set of behaviors in which they seek out a particular sport and develop a skill set through practice to compete. Deci and Ryan (1985, 2000) postulated a theory of selfdetermination (SDT) that has been tested by them and others, and has demonstrated considerable utility (e.g. Frederick & Ryan, 1993; Pelletier, Fortier, Vallerand, & Briere, 2001; Amiot, Gaudreau, & Blanchard, 2004). At its core is the continuum that ranges from intrinsic motivation to amotivation. Intrinsic motivation is when a behavior is performed because it is enjoyable. Extrinsic motivation is when a behavior is determined by an outside source, like a trophy. Finally, amotivation is when there is no desire to perform a specific behavior (Ryan & Deci, 2007). Ryan and Deci (2007) believe that human beings have in inherent propensity to seek out and learn new skills. They become proficient at these skills and do so without any external prompts. In SDT, this is known as intrinsic motivation and is the cornerstone (p. 2) of its theoretical foundation. Doing an activity for its own sake (Ryan & Deci, 2007, p. 2) is the hallmark of being intrinsically motivated. For example, a person who swims, not just to train or to seek the benefits of swimming, but because this individual enjoys the act of swimming would be said to be intrinsically motivated to do so. A component theory of SDT is the Cognitive Evaluation Theory (CET), which emphasizes the psychological needs that lead to intrinsic motivation (Deci & Ryan, 1980, 1985). Under CET, if a person s behavior satisfies the needs of competence and autonomy, then intrinsic motivation to engage in that behavior can be enhanced and/or maintained. Therefore, if people who compete in triathlons feel they are competent in the sport, and do so under their own volition, they are more likely to be intrinsically motivated to continue to train and compete. Another psychological need addressed by CET is a person s need for connection and to have a feeling of belonging in the context one is behaving. A sense of kinship with other triathletes may help to satisfy this need. So ultimately, a human being will seek out contexts in which one feels one belongs and exhibit behaviors that foster competency 3

14 and autonomy. Ultimately social environments, that foster a connectedness with others and one in which a person can display competence help to enhance intrinsic motivation. The interaction of the person and the environment in these contexts will eventually lead to repeated behavior where a person can meet these psychological needs. The context of sport is a perfect environment to study intrinsic motivation. Another component of SDT is the Organismic Integration Theory (OIT; Deci & Ryan, 1985), which expounds on the continuum from amotivation to intrinsic motivation by elaborating on the different levels of extrinsic motivation (Ryan & Deci, 2007). The continuum is based on a person s level of self-determination, of which autonomy is the key, in relation to this individual s behaviors and goals. If a person s behavior is controlled by an outside source, like being paid to compete, then that person is motivated through external regulation, is non-selfdetermined. Behaviors that are motivated by internal factors, such as enjoyment or meeting a psychological need, are more autonomous and therefore more self-determined. The various types of extrinsic motivation, as outlined in the OIT (Deci & Ryan, 1985), range from those controlled entirely by outside goals (i.e., external regulation) to internally guided behavior (i.e., integrated regulation) and are depicted in Figure 1.1. In the continuum, low self-determined behavior is controlled by sources outside the individual (i.e., external regulation). Introjected regulation is the next step along the continuum. Here the individual is controlled not by external rewards but by motivation to gain external approval or avoid external disapproval, for instance, from a coach or a parent. Additionally, introjected regulation might involve feelings of guilt or pride as the motivating factors. Following introjected regulation on the continuum is identified regulation, in which the motives are more self-determined and have to do with engaging in behaviors that adhere to personally held values. For instance, a person exercises because of a belief that one should be physically fit and active. Internalization of the behavior to the self is high in this case and highly self-determined, yet still extrinsically motivated because the individual is not engaging in the activity for the pleasure derived from the activity itself. The final step before true intrinsic motivation is integrated regulation. It is at this point where the behaviors become integrated into the self and the reasons for engaging in the activity are combined with other life goals. For instance, a person might engage in triathlon competitions because one has embraced a triathlete or Ironman/Ironwoman self-identity. While the act of competing may not be fully enjoyable in and of itself, the behavior is highly 4

15 self-determined. Finally, on the opposite side of the continuum from intrinsic motivation is amotivation. Individuals might not assign any value to participation in triathlons or they might believe they are incapable of participating due to their physical limitations. Figure 1.1. Representation of the Self-determination theory component, organismic integration theory (OIT; Ryan and Deci, 2007). Modified from Hagger and Chatzisarantis (2007). I, also, briefly discuss the Hierarchical Model of intrinsic and extrinsic motivation for sport and physical motivation as posited by Vallerand (2007). The hierarchical model incorporates five postulates that elaborate on the structure and theoretical background. The first postulate states that any study of motivation must include intrinsic motivation, extrinsic motivation and amotivation. The second postulate posits that intrinsic motivation, extrinsic motivation, and amotivation exist at the situational level, the contextual level and the global level. Motivation demonstrated at the situational level is motivation to engage in a specific activity, like a training run, or at any given moment in time. Motivation at the contextual level is motivation to participate in a given context, for instance to participate in a sport, like triathlons. Finally, motivation at the global level is an athlete s disposition or trait to interact with the environment in general. Postulate three states that motivation is determined by social factors and 5

16 that the higher levels of motivation (global or contextual) affect motivation at the lower levels. Within this postulate are three corollaries. Motivation is impacted by social factors (Corollary 3.1) from each level (global, contextual, or situational) that are mediated (Corollary 3.2) by the psychological needs satisfaction (competence, autonomy, and relatedness) and that there is a top down effect within the hierarchy (Corollary 3.3). In other words, motivation at the higher level can influence motivation at a lower level. For example, if a person is motivated to participate in triathlons intrinsically then this person will be intrinsically motivated to train for those events. In postulate 4 Vallerand contends that there is a recursive effect from the lower levels to the higher levels. This allows for motivation change. For example, an athlete who perhaps first engaged in the sport for external reasons, after having experienced intrinsic motivation repeatedly at the situational level, may begin to experience intrinsic motivation at the contextual level. Postulate 5 includes two corollaries that elaborate on the outcomes of motivation or more specifically the engagement of the sport behavior. Corollary 5.1 includes the notion that as one moves along the continuum, from intrinsic motivation to amotivation, positive consequences decrease. For example, in general a person who is highly self-determined and engaging in an activity for its own sake will have more positive affect than an individual who is not self-determined. Vallerand states in corollary 5.2 that each level of motivation has a corresponding level of consequences and is related to the level of motivation that led to it. It is important to note that an individual does not progress from extrinsic motivation toward intrinsic motivation as in a stage model, but rather that a person can fluctuate on the continuum anywhere from intrinsic motivation to external regulation or even amotivation at any given time (Ryan & Deci, 2007). This fluctuation can be the result in how much of the basic psychological needs of competence, autonomy, and relatedness are met. A person, who is highly autonomous, has high competency, and feels connected when engaging in a certain behavior will be intrinsically motivated or self-determined. At this point a person can develop a passion for an activity, like training for and participating in triathlons. It is also important to note that a person could be motivated to participate by multiple factors, for instance the motive to lose weight, as well as the motive to win prize money or a trophy. Vallerand s (2008) dualistic model on passion is discussed next. 6

17 Theory on Passion The dualistic model of passion (Vallerand et al., 2003; Vallerand, 2008) is grounded in SDT. Vallerand et al. define passion as, a strong inclination toward an activity that people like, that they find important, and in which they invest time and energy (p. 757; 2003). Individuals define themselves by what they are passionate about, for instance individuals who complete an Ironman triathlon call themselves either an Ironman or Ironwoman. Likewise people who participate regularly in triathlons might refer to themselves as a triathlete. Therefore from an SDT perspective, people who are intrinsically motivated to compete in triathlons may become so passionate about the sport that they integrate it into their identity (Vallerand, 2008). Vallerand (2008) and colleagues, (2003) posit that there are two types of passion, harmonious and obsessive. These two types are defined by how individuals have internalized the activity into their identity. Harmonious passion is the result of individuals autonomously internalizing the activity into their identity. A person who actively participates in the activity for the sake of the activity and has attached no contingencies to participation is said to display harmonious passion. Obsessive passion, on the other hand, is the result of partial internalization (and an absence of integration) of the activity into the self. In these instances, the activity defines the person and has contingencies, such as social acceptance and self-esteem, attached to it. People in this motivational category might participate in triathlons not for enjoyment, but rather out of a need to be accepted by others, or to satisfy a need for stimulation (e.g., skydiving for the adrenaline rush). As mentioned above, harmonious passion is the result of self-determined integration of the activity into a person s identity. Vallerand (2008) cites Deci and Ryan s (2000) concepts of intrinsic and integrated tendencies of a person as leading to passion. Therefore, if individuals autonomously select an activity and are intrinsically motivated to participate in it then they may eventually become passionate towards that activity. The activity is a harmonious part of the individual s life and acts in congruence with all the aspects of that person s self. As a result of engaging in the activity, a person is free to experience positive outcomes both during and after participation. For example, a person enjoys the act of racing in a triathlon and enjoys the effects resulting from physical activity afterwards. When done with the passionate activity, the person is free to engage in other activities and can skip training for a day or two without any ill effects, such as guilt, or negative affect. 7

18 In contrast, obsessive passion is implicated when an individual is controlled by the passionate activity (Vallerand, 2008). This controlling ability is the result of contingencies that the individual places on participating in the activity or sensory experiences attached to the activity (i.e. thrill seeking). It is in these instances where a person must participate in the activity at the expense of other activities. For example, a person might feel the need to get a training run in at the expense of preparing for an exam or job. A person might also participate in the activity at a detriment to physical well-being, for example training when injured or in hazardous conditions (e.g. swimming in high seas or running in a thunderstorm). If the individual fails to complete a scheduled training run or participate in an upcoming event, the result can be experienced negative affect or dissonance. Cognitive Motivational Relational Theory of Emotions Lazarus (1999) Cognitive Motivational Relational (CMR) theory of emotions is also germane to this research. The study of stress and coping dates back over 50 years and a thorough review can be found in Lazarus (1999). The CMR theory of emotions, involving appraisal and coping constructs, is the most widely accepted conceptual framework for the study of psychological stress. Lazarus posited that in encounters with any given situation, a cognitive process (i.e., appraisal) unfolds that directly results in the experience of stress emotions. In this view, situational appraisals involve construction of relational meaning about what that situation means personally in terms of the person s goals, ego involvement, and overall well-being. If a person perceives a threat to goals in goal-relevant situations, a series of appraisal processes are engaged to occur to define the nature of the threat. Following the appraisal process the person decides what can be done to cope with (i.e., reduce) the situational threat. From Lazarus perspective, appraisal and coping mediate the relationship between a stressful situation and the emotions elicited by that situation. In addition, Lazarus and Folkman (1984) believe that stress, appraisal, coping, and emotion are dynamic in nature and change over time as a situation unfolds. Finally, as defined by Lazarus and Folkman (1984), coping involves a person s cognitive and behavioral efforts to manage either a stressor or the emotions associated with that stressor. Coping is evident when the demands of a situation are taxing or exceeding the resources of the person. Several important issues can be discerned from this definition. First, the concept of 8

19 cognitive appraisal is fundamental to Lazarus and Folkman s (1984) definition and is discussed in more detail later. Second, coping efforts can change over time and can vary across contexts and situations. From this perspective, an individual s coping efforts can impact upon the nature of the situation, which, in turn, has the potential to exert influence upon the individual s situational appraisals. Finally, Lazarus (1999) CMR theory is process oriented. Therefore, individuals undergo a process of adopting different coping strategies within the same or different situations. Their coping responses also might simply change as the nature of the stressor changes. Coping strategies that work in one situation may not work in another and the process of adopting new strategies is done in order to facilitate the optimal strategy or strategies for that situation. For the purposes of this study, I focus more on the coping aspect of the theory than the appraisal process. As previously indicated, Lazarus (1999) theory is process oriented in focusing on how people appraise, cope, and emotionally experience situations, including within sport settings, encountered in their lives. The process of appraisal results in an emotional experience that is shaped by the specific coping behaviors of that individual. The appraisal and coping process are mediators between the person-environment interactions and the emotions ultimately experienced. The appraisal process, which occurs during a potentially stressful encounter, is broken into two components, primary and secondary appraisal. These cognitive processes work interdependently and result in the coping strategies employed and the emotions experienced. During primary appraisal, individuals determine if the situation affects their goals, values, or overall well-being. Lazarus (1999) defined four types of primary appraisals: harm/loss, benefit, threat, and challenge. The four types of primary appraisal processes are categorized by time. Harm/loss and benefit are appraisals that occur based on an experienced outcome, for example a loss of a loved one or the awarding of a bonus. Threat and challenge are the two primary appraisals that I focus upon, as they occur before the outcome of a situation has been determined. For instance, a triathlete might view a leg cramp as a threat to achieving a personally set time goal and, as a result, feel anxious or even self-anger for not warming up properly. Challenge appraisals occur when a situation arises that allows for achievement of a goal. An example of a challenge might be a situation in which an athlete experiences a slower than anticipated swim time. Prior experience in successfully making up lost time during the bike portion could allow the triathlete to view the current situation as a challenge. 9

20 A person analyzes available resources and coping strategies in the secondary appraisal process (Lazarus, 1999). The individual evaluates personal capabilities as well as the likelihood for success in, one or more, strategy implementations. A belief that the individual can effectively cope with a given situation affords challenge rather than threat perceptions. Once a person has gone through the appraisal process, the individual will then implement one or more coping strategies to alleviate a stressor. Coping mediates the appraisal process and the emotions experienced. Lazarus (1999) proposed that coping serves to address either the emotions associated with a stressor or the stressor directly. He labeled this functionality as either emotionfocused coping or problem-focused coping. Emotion-focused coping deals solely with the emotions that a situation elicits while problem-focused coping takes a more active approach by attempting to resolve a stressor with either cognitive or behavioral efforts (Folkman & Lazarus, 1980). Skinner, Edge, Altman, and Sherwood (2003) proposed more than just the two coping categories posited by Lazarus. Their argument was that both problem focused coping and emotion focused coping are not mutually exclusive. For example, a person who plans ahead not only solves the problem, but the act of doing so alleviates the emotions that stressor elicits as well. They analyzed over 100 assessments of coping, which resulted in a list containing 400 distinct ways of coping. Skinner et al. recommend a hierarchical system of 13 potential core families of coping strategies. These include problem solving, support seeking, escape, distraction, cognitive restructuring, rumination, helplessness, social withdrawal, emotional regulation, information seeking, negotiation, opposition, and delegation. Amiot, Gaudreau, and Blanchard (2004) establish three higher order dimensions of coping based on Lazarus and Folkman (1984) and Skinner et al. (2003): task-oriented coping, emotion-oriented coping, and disengagement-oriented coping. Disengagement oriented coping is characterized by mental and/or behavioral disengagement that either leads to denial or focusing on task irrelevant cues. For example, athletes experiencing a bad race might start to focus on their equipment more than refocusing their energy or on the intake of the proper, in race, supplements. According to Lazarus (1999) there are 15 discrete emotions and these emotions are elicited as a result of the appraisal process and how people cope with their threats, losses, or challenges. There are eight negative emotions, which include anxiety, fear, anger, guilt, shame, sadness, envy, and jealousy. Lazarus also states that there are seven positive emotions: hope, happiness, love, pride, relief, gratitude, and compassion. 10

21 Therefore, according to Lazarus CMR theory (1999) people encounter situations that they interpret as threats or challenges. They then employ one or many coping strategies to effectively deal with the stressor itself or the emotions elicited. Positive or negative emotions then result and in turn influence the appraisal process with respect to the current situation and future situations. 11

22 CHAPTER 2 LITERATURE REVIEW In the following section, I review the literature that is relevant to the theories and model previously discussed within the context of sport and exercise. First, it is important to point out that a triathlon is a sport composed of three common activities from exercise contexts. The three elements of a competition (swimming, cycling, and running) are common modes of exercise. Additionally, people may choose to participate in each of these activities for different reasons, for health/fitness or for competition or both. Therefore, it can be stated that the triathlon is representative of modes of exercise practiced in a sport setting and it is logical to look at the literature pertaining to motivation, passion and coping in both the exercise as well as sport contexts. Despite the growing popularity of the Ironman and triathlons, there is a dearth of research on the motivation of individuals to initiate and continue participation in this sport. There has, however, been much research done with running, and more specifically marathons. Triathlons and marathons have many similarities with respect to training as well as culture. Both are endurance events and as such require dedication to train multiple times a week, often for a very long period of time per session. The culture is similar to that evident in distance running as well. For example, when one attends local or regional events, that person will often meet the same people at each event. Similarly, the individual may join a local running or triathlon club in order to socialize with other runners or triathletes. As the triathlon evolved from athletes training for marathons, it seems appropriate to explore the marathon literature in hopes of drawing inferences for those participating in triathlons. The following paragraphs contain descriptions and definitions of the different motives for participating and I examine differences pertaining to motivation amongst runners, including age and gender. Additionally, the motivation to start running and maintain running, as well as the possibility of negative addiction, is discussed. Finally, how these motives might fit into the Self-determination Theory (Deci & Ryan, 1985) is addressed. 12

23 Motivation There is no one specific overarching motivational reason that leads people to begin running or training for a marathon (Leedy, 2001; Masters & Ogles, 1995; Masters, Ogles, & Jolton, 1993; Ogles & Masters, 2000). While health and fitness reasons are predominantly mentioned by runners, according to research, there are many motives (Ogles & Masters, 2003). Researchers have grouped the motivational reasons into different categories. While researchers differed on their methods of classification, common themes are evident. Carmack and Martens (1979) included physical health, psychological health, affiliation, goal achievement, tangible rewards, other s influence, and availability as categories in their study. Competition, affiliation, social recognition, health orientation, weight concern, self-esteem, personal goal achievement, psychological coping, and life meaning are another set of categories (Masters & Ogles, 1995; Ogles, Masters, & Richardson, 1995). Leedy (2001) listed health and fitness, challenges, and time alone as distinct categories. However, the simplest and most inclusive categorization appears in Ogles and Masters (2000) study, which included psychological, physical, social, and achievement reasons. Many of those listed previously fall into one of these four categories and it is on these that I elaborate. Psychological aspects of motivation include enhancing self-esteem, life meaning, and the use of running as a coping mechanism. Physical motives include health benefits and weight concerns. Meeting with like-minded individuals and recognition from family and friends comprise the social motive category. Finally, competition with other runners as well as competition with one s self fall under the achievement categorization. Some runners endorse many of these motives; however, some of the motives are specific to certain groups of individuals. The latter motives are discussed later. While the overall classification or categorical listing of motives posited by Ogles and Masters is interesting it is not, however, rooted in theory. Therefore I attempt, when possible, to integrate these categorical motives into the framework of SDT (Deci & Ryan, 1985) as I address each one individually. Psychological motives. The first category Masters and Ogles (2000) identified consists of the psychological reasons to run. The Motivations of Marathoners Scales is comprised of items that tap into the motives of individuals who run (Masters et al., 1993). Items representing psychological motives fell into three main categories: psychological coping, self-esteem and life meaning. Psychological coping items included to be less anxious, as a distraction from worries, to improve one s mood, and to solve problems. Self-esteem items were to feel 13

24 more confident, to feel proud, to have a sense of achievement, and to feel in control of one s body as well as the item to improve one s self-esteem. Running makes life more purposeful, makes one feel whole, makes one have a sense of belonging with nature, and to feel at peace comprised the life meaning category items. Leedy (2001) looked at running as an effective coping mechanism to deal with stress. Previous research indicates that running has shown to be therapeutic for individuals with depressive symptoms (Martinsen & Morgan, 1997). Leedy examined the differences of anxiety across a sample of runners. Participants in the study were comprised of individuals who ran a variety of different distances and not just marathons. Individuals used running as a stress reliever. Runners were categorized into recreational and committed runners based on mileage run per week, adherence to training, and the number of long runs completed. Therefore committed runners were so classified because they ran more per week, were more likely to run in spite of barriers and had completed longer distance runs. Leedy found that those runners who had a higher commitment to running had lower anxiety levels as well as less depressive symptoms. The psychological motives for running, as outlined by Masters and Ogles (2000), do not appear to fit neatly into self-determination theory. One could surmise that these motives could include both intrinsic and extrinsic reasons depending on the individual. A person who runs as an escape from the worries of everyday life might also enjoy the activity of running itself, therefore displaying both intrinsic and extrinsic motives. However, if another activity were substituted for running, which in turn relieves stress, would the behavior of running continue if it were not inherently enjoyable? The reward of less stress could also be considered extrinsic in nature. Physical motives. A second category as identified by Masters and Ogles (2000) involved physical reasons to run. Health and fitness were mentioned as a strong motivator to run in all of the studies researched. The MOMS differentiate physical health motives into two general categories: health orientation and weight concerns. Health orientation items were comprised of items that pertained to improving health, prolonging one s life, reducing the risk of heart attack, and to stay in physical condition. Weight concern items included to look leaner, help control weight, and to lose weight (Masters et al., 1993). Health and fitness reasons were the primary reason people started running and there are notable shifts in motives that are discussed later. Although these are categorized as physical motives the underlying motive 14

25 might actually be psychological in nature. For example, people who start running because a doctor has told them to lose weight have different motives than individuals who start running with the hopes of improving their appearance. Improving one s appearance has an underlying psychological motive associated with body image. Health and fitness motives can fall into different places along the self-determination continuum. Running to lose weight in order to gain approval from others or to improve one s appearance are examples of extrinsic motives, more specifically introjected regulation (Ryan & Deci, 2007). However, if people run in order to be healthy because they hold that value as important, they are demonstrating identified regulation. Social motives. The social aspects associated with running can be motivating for some runners. Social motives are factored into the two categories of recognition/approval or affiliation within the MOMS. Items falling under the recognition/approval category consist of the degree to which runners seek recognition for their participation and how other people look up to the runner. Runners cited a feeling of belonging when surrounded by fellow runners. They also identify themselves as runners and seek recognition from family and friends for competing in marathons. Running was also cited as a good way to meet friends. These aspects would fall into the affiliation subcategory of social motives in the MOMS (Masters et al., 1993). The social motives as outlined in the MOMS actually describe separate constructs within SDT, those addressing psychological needs and introjected regulation. The social motive, which involves being around other runners, is a prime example of meeting the need for relatedness as outlined by Ryan and Deci (2007). Being around other runners allows runners to feel like they belong and are connected, thusly satisfying a basic psychological need. Additionally, another psychological need (competence) is satisfied when runners receive recognition for their accomplishments, whether it is finishing a marathon and/or achieving a personal goal (e.g. a personal best time). By meeting these needs people are more likely to be self-determined in their motives. Additionally, the motive of seeking approval from others is a hallmark of introjected regulation, an example of which is when an individual runs to gain approval from others. For instance an individual may participate in triathlons in order to gain approval from an individual or group to which he wants to belong. Achievement motives. People can be motivated by achievement, as assessed by the MOMS, in one of two ways. The MOMS includes two subcategories of achievement motivation: 15

26 competition and personal goal achievement (Masters et al, 1993). Individuals who run for the sake of beating others characterize competition achievement motivation. However, people who run to better their own times or challenge themselves to run faster are self-referenced in their achievement motivation. These two distinctions run parallel to Nicholls Achievement Goal theory as outlined by Duda and Hall (2001). More specifically those individuals who cite competition against others as a main motivator are labeled as having more of an ego orientation. Individuals who are task oriented compete against themselves (Duda & Hall, 2001). The competition environment of a marathon or road race are contexts in which it is possible for an individual to satisfy the three psychological needs as addressed in the SDT (Deci & Ryan, 1985). Runners who choose, by their own volition, to run in a marathon demonstrate autonomy. The competitive environment also presents an opportunity for an individual to display competence, by either beating others or achieving a personal best. This environment can also satisfy the need for relatedness, as fellow runners will surround the individual at such an event. When all three psychological needs are met there is a greater possibility that the underlying motives are intrinsic and therefore self-determined. Competitive environments have controlling and informational aspects, both of which can impact intrinsic motivation (Deci & Ryan, 1985). As outlined in the CET, informational aspects of competition provide individuals with feedback on their competence. If the runner achieves a performance goal, resulting in feelings of efficacy, intrinsic motivation is enhanced. However, if there is outside or internal pressure to win the controlling aspects can undermine intrinsic motivation. Frederick and Ryan (1993) found a difference in participation motives based on context. While individuals cited both intrinsic and extrinsic motives for participation in both exercise and sport, those individuals engaging in sport had significantly higher intrinsic motivation. Exercisers were significantly more likely to cite extrinsic motives, for example to improve one s appearance, as a reason for their behavior. Specifically, Frederick and Ryan found that people engaging in individual sports showed a greater degree of interest/enjoyment and competence motivation. They also found that people engaging in exercise showed a greater propensity for body related motivation (e.g. to lose weight or look better). Gender differences. Research has also examined gender differences with respect to motives to train for a marathon and to run in general (Leedy, 2001; Ogles & Masters, 2003; 16

27 Ogles et al., 1995). Leedy (2001) found that women competing in 5K/10K, half-marathon, and marathon races scored higher on commitment than males. This was reflected in their higher scores on the adherence to training factor. Women also were more likely to report health/fitness and time alone as motivational reasons. Men cited challenge more than women as a motivation. In a cluster analysis of marathon runners, Ogles and Masters (2003) found that women fell almost entirely into the two clusters of running enthusiasts and lifestyle managers. Running enthusiasts endorsed all nine motives studied including health, weight concerns, affiliation, recognition, competition, personal goals, coping, self-esteem, and life meaning. Lifestyle managers cited personal goals, self-esteem, health, coping, weight concerns, and life meaning as main motives to train and run in a marathon. Men disproportionately comprised the remaining three clusters of personal goal achievers, personal accomplishers, and competitive achievers. All three of these clusters endorsed personal goal achievement as a main reason, while personal accomplishers additionally cited self-esteem and health reasons. Competitive achievers endorsed these, as well as, competition and life meaning. Based on these studies it appears that women tend to cite more psychological and physical motives to run while men generally cite personal achievement and competition as main reasons. This is not to say that they do so in exclusion of the other reasons but reflects women s general tendencies to focus more on physical and psychological health. Frederick and Ryan (1993) found similar results with bodyrelated concerns more salient among women as compared to men as an exercise or sport motive. Frederick and Ryan also reported that competence or interest/enjoyment motives were more prominent in men engaging in individual sports than men engaging in fitness activities. Age differences. Ogles and Masters (2000) compared older and younger male marathon runners across motivation and training habits and found significant differences. Runners over the age of 50 were classified as older adults while runners between the ages of 20 and 28 were labeled as younger adults. They hypothesized that older and younger runners would differ on motives and training habits with older runners citing health concerns more, where younger runners would be motivated by competition. They used the MOMS for their study and found that, as hypothesized, older runners were more strongly motivated to run for health reasons, life meaning, and affiliation with others. Younger runners were more motivated by personal goal achievements, but as whole both older and younger runners did not differ on competition as a main motivator. Competition, in fact was not a major reason that either group cited as 17

28 motivation to run a marathon. Additionally, they found that runners who endorsed affiliate motives were more likely to train with other people. A word of caution with these results as women did not participate in the study and therefore the results can only be generalized to male runners. In the cluster analysis done by Ogles and Masters (2003) younger runners comprised the personal goal achiever and competitive achiever more than older runners. However, there were no significant differences with respect to age across all five clusters. Initiating and maintaining behavior. The motivational reasons that runners cite for starting a training program differ from those that experienced runners cite to maintain their current program. Carmack and Martens (1979) in the development of their Commitment to Running scale found that runners cited certain psychological states as motives for training as they gained more experience. Masters and Ogles (1995) investigated differences in motivation to run a marathon for three distinct groups of runners: rookies, mid-level, and veteran marathoners. Previous research noted a shift from physiological to psychological reasons to run, as well as a shift from extrinsic to intrinsic motivation as runners gained more experience. It should be noted that individuals cite a variety of reasons, both intrinsic and extrinsic, to engage in behavior. According to Ryan and Deci (2007) these various reasons should be taken as a whole to determine the overall quality of motivation. For example, contrary to previous studies, Masters and Ogles found that veteran runners, runners who had run more than three marathons, had adopted an identity of a marathon runner and were motivated by variables that included recognition, health, and competition. The mid-level runners, running their second or third marathon, exhibited motivational variables similar to prior research. They cited more psychological aspects and personal achievements as motivation for running. Based on their data the researchers suggest that rookie marathoners are motivated by health and weight concerns, self-esteem, and personal goal achievements (Masters & Ogles, 1995). As runners gain more experience their reasons for continuing the sport change or their existing reasons become more or less salient. For the older runners, the shift that was observed can be attributed to higher levels of self-determination. Over time and experience the runners integrated their behavior more into their identity and as a result were more self-determined. A person might start running for health reasons and over time experience some personal achievements that sustain continued participation. A similar observation was made in exercisers wherein persistence with an exercise program was contingent on both intrinsic and well internalized extrinsic motivation (Ryan, 18

29 Frederick, Lepes, Rubio, & Sheldon, 1997). This could be due to meeting the psychological needs of competence, autonomy, and relatedness as outlined by Deci and Ryan (1985). At some point an athletic identity of a marathon runner is integrated into the self and the additional need for competition fosters the behavior to continue. Negative addiction. One of the consequences of motivation to run a marathon and commitment to running in general is the possibility of becoming negatively addicted to running (Leedy, 2001; Summers, Machin, & Sargent, 1983). Negative addition is characterized by the negative mood or anxiety experienced when an individual misses a run (Conboy, 1994; Rudy & Estok, 1989); a hallmark of obsessive passion as discussed later. The Commitment to Running (CR) scale developed by Carmack and Martens (1979) was found to be a good measure of running addiction with perceived addiction comprising 24% of the 42% total variance explained by the measure. Summers et al. (1983) used the CR when they examined the psychosocial factors associated with marathon running. They found a gender difference with women experiencing higher levels of withdrawal than men when a run was missed. Leedy s (2001) study looked at highly committed runners and negative addiction. The belief was that runners who were highly committed to their training would show signs of negative addition. The results, however, were to the contrary and highly committed runners demonstrated lower levels of depression and anxiety to recreational runners. Leedy surmised that those runners who experienced anxiety after missing a scheduled training session might be dependent on running as a coping mechanism for depression. In fact, running has been demonstrated to have a antidepressant effect and is often prescribed for individuals with depression (Martinsen & Morgan, 1997). There are some problems with labeling addiction as either positive or negative. Negative addiction as characterized in running is the result of negative moods or anxiety that are not relieved when an individual misses a scheduled run. In this case running acts as a coping mechanism for stress, much like excessive drinking or prescribed medications. The inherent problem is then when addiction is labeled as negative then there must be an opposite construct. Therefore what are the characteristics of positive addiction if there is such a construct? Models of self and marathon running. It would appear that each separate category of motivation to run taps into a specific psychological construct. Issues with weight and body image are cited frequently as reasons why individuals start running (Ogles & Masters, 2003) and 19

30 are examples of the various forms of extrinsic motivation according to Deci and Ryan (1985). The need to feel better about physical appearance and the need to project an attractive image to others (meeting social norms) are examples of non-self-determined motivation. This need to be seen by others as a fit runner also can fall into the affiliation category of motivation. Over time it appears that a runner s motives might shift from meeting physical needs to psychological ones (Masters & Ogles, 1995). One of the more intriguing psychological motives is that individuals cite running to improve their self-esteem. While research has shown that self-esteem can be influenced by exercise, there is some debate as to the level (Spence, McGannon, & Poon, 2005). Sonstroem and Morgan (1989) Exercise and Self-Esteem model (EXSEM) is a hierarchical model in which, self-esteem resides at the top and is supported by both physical competence and physical acceptance. Underneath physical competence is physical self-efficacy and underneath that is the behavior, in this case, running or training for a marathon. Direction of influence can be top down as well as bottom up within the model. A meta-analysis by Spence et al. (2005) examined several moderators and their effect on self-esteem but did not test Sonstroem and Morgan s model directly. They hypothesized that (a) individuals who experience a change in physical fitness will experience a change in self-esteem, (b) less physically fit individuals will experience more of a change in self-esteem than those more fit, (c) individuals with lower selfesteem scores will experience a greater change due to the change in fitness, and (d) exercise dose acts as a moderator as well with the higher dosage generating more change in self-esteem. Spence et al. found that exercise does indeed have an effect on self-esteem but not as much as previously reported. The type of program and change in fitness were shown to be significant moderators of self-esteem. Differences exercise dosage did not produce significant results. Results from the Spence et al. (2005) meta-analysis and Sonstroem and Morgan s EXSEM (1989) can help to explain the shift from physical to more psychological motives for runners as they become more experienced. After engaging the behavior over the course of a few months or years runners self-efficacy might increase as they are noticing better times and general ease of training compared to when they first started running. This increased self-efficacy is reflected in their overall physical competence, especially after they have run several marathons, which in turn will improve self-esteem. An inevitability of training for a marathon is general improved physical fitness and this would coincide with Spence et al. s results. 20

31 The motives for training for and participating in marathons can be grouped into four distinct categories: physical/health motives, psychological motives, achievement motives, and social motives. Runners across all ages and experience level cite physical/health motives as the primary reason that they initiated the behavior as well as maintained running. Younger runners are more likely to participate for achievement reasons but not exclusively. It seems that women are motivated almost equally by all the motives discussed. The desire to compete is predominantly male orientation but not as strong as once believed. While the possibility of negative addiction is present it appears that for the most part running is a good way to cope with psychological stress and can reduce anxiety levels. One of the limitations of the literature is that study participants have been disproportionately male. While the participation of women in marathons has increased over the course of the last thirty years, it is still a male-dominated event. According to runningusa.org ( 2012 Marathon, Half-Marathon, and State of the Sport Reports, 2012) in % of marathoners were women while in 2011 women comprised 41% of marathon participation. In contrast women comprised 59% of half-marathon competitors. It appears by these data women are more likely to run shorter distance events. The existing marathon motivational literature is atheoretical in nature. It is possible, however, to use SDT to explain the categorizations outlined by Masters and Ogles (2000) and associated findings on the behavior of beginner and experienced runners. Overall, researchers suggest that there are many motives that individuals combine to initiate and maintain behavior. Theses motives can vary with experience level and gender. Rookie marathoners are more likely to cite fitness and health motives amongst their reasons for initiating running (Masters & Ogles, 1995). Women in general also cite health and fitness motives for initiating and maintaining a running regimen (Leedy, 2001; Ogles & Masters, 2003). Men, however, tend to list competition and personal achievement as more salient amongst their motives (Ogles & Masters, 2003). While differences in frequency or saliency of motives were observed there was commonality among motives as well. Both men and women cite many reasons to run some more salient than others. Therefore, it should be pointed out that both men and women cite several motives for running none of which are mutually exclusive for age or gender. Therefore, people list both intrinsic as well as extrinsic motives for running in marathons. Individuals who place a higher value on health or weight loss motives are said to be less self-determined. More self-determined 21

32 individuals run because they enjoy it and/or have integrated the identity of a marathoner into their self. Initially people who first start running do so in order to satisfy extrinsic goals of losing weight, and improving their fitness but possibly over time they could adopt more intrinsic goals. The marathon environment is such that it can satisfy the psychological needs of competence, autonomy, and relatedness. Therefore, an individual could experience a shift towards more self-determined behavior as these needs are met. As a result of more selfdetermined behavior it is likely that an individual will maintain that behavior over time. Passion People with a passion for an activity (e.g., participating in triathlons) invest a lot of time, energy, and resources to ensure they can continue to participate in that activity (Vallerand et al., 2003). According to Vallerand and colleagues in order to be passionate, it is imperative that people genuinely like the activity and that it is important to them. The passion model is grounded in Self-Determination Theory although Vallerand contends that passion and intrinsic and extrinsic motivation are all identifiably different constructs albeit ones that share similar characteristics. According to Vallerand and colleagues there are two types of passion, harmonious and obsessive. A harmoniously passionate person has internalized the activity into his/her identity autonomously. In SDT this is a characteristic of integrated regulation and intrinsic motivation. An athlete with harmonious passion might say, I love running in triathlons, so I do it often and call myself a triathlete. In contrast obsessive passion is internalized in a controlling manner as a result of intrapersonal or interpersonal pressure. Contingencies, such as feelings of social acceptance or self-esteem, are attached to the activity. A person is then compelled to participate in the activity because of these contingencies, in effect becoming controlled by the activity itself. It is here where a link grounded in SDT can become difficult. Even though the activity is internalized, being controlled by the activity is not intrinsic in nature and because the person likes the activity it is not considered extrinsic either according to Vallerand et al. (2003). Obsessive passion shares characteristics with identified and introjected regulation within SDT. An athlete with obsessive passion might say, I am a triathlete and therefore I have to run in triathlons. Vallerand and colleagues (2003) developed a scale to measure the two types of passion. In a series of four studies they developed and validated the scale, compared the relationship of 22

33 harmonious and obsessive passion to affect, intrinsic and extrinsic motivation, and explored the implications of obsessive passion. Study 1 validated the scales factor structure and compared the two forms of passion relationship with the outcome of affect. They found that harmonious passion was associated with positive affect, flow, and concentration. Obsessive passion was associated with negative affect and conflict, specifically when the person could not engage in the activity. Study 2 attempted to differentiate the passion model from intrinsic and extrinsic motivation as a major predictor of positive and negative affect over the course of a sport season. Vallerand et al. used hierarchical multiple regression to determine the main contributor toward affect, as well as sport intention (whether the football players would return the following season). Data were collected twice during a single football season among 205 intercollegiate players in the Province of Quebec. They found the only significant predictor of positive affect at Time 2 was harmonious passion (ß =.36 p <.001). The only two significant predictors of behavioral intentions at Time 2 were obsessive passion (ß =.12, p <.10) and intentions at Time 1 (ß =.52). They also tested for an interaction between intrinsic and extrinsic motivation and passion on all outcomes with no significant effects found. However, context might be a limiting factor with respect to the results. Collegiate sports, especially football, are rigidly structured and do not allow for the individual to truly autonomously choose to participate in that activity at any time. Collegiate athletes are limited to participation in that sport at only the college level and cannot play either professionally or even year round. Additionally, football is a team sport and participation in the sport requires several individuals in order to play. Correlational data between the two types of passion and intrinsic and extrinsic motivation were either not performed or not reported. Regardless the link between harmonious and obsessive passion and intrinsic and extrinsic motivation should be further explored in various sport contexts. It would possibly be beneficial to explore the relationships in an individual sport that can be readily participated in year round. Harmonious and obsessive passion for activities has been studied with respect to various activities including dance (Rip, Fortin, & Vallerand, 2006), basketball (Vallerand, Mageau, Elliot, Dumais, & Rousseau, 2008), and gambling (Rousseau, Vallerand, Ratelle, Mageau, & Provencher, 2002) to name a few. The majority of these studies have dealt with relating passion with other constructs like psychological adjustment (Rousseau & Vallerand, 2003), physical health (Rip, Fortin, & Vallerand, 2006), aggression (Donohue, Rip, & Vallerand, 2009), and 23

34 performance (Vallerand, Mageau, Elliot, Dumais, & Rousseau, 2008). Vallerand et al. (2008) looked at deliberate practice as a mediator between harmonious and obsessive passion and performance. Deliberate practice has been proposed to play a key role in achieving high levels of performance (Ericsson, Krampe, & Tesh-Romer, 1993). Vallerand et al. posited that harmonious and obsessive passion would positively predict deliberate practice, which in turn would positively predict performance. Harmonious passion as well as obsessive passion both positively predicted deliberate practice, which supports Vallerand et al. s contention that passion is a determinant of sustained involvement with an activity that a person cares deeply about. They also found that the mechanism for improved performance was mastery goal attainment, which is the purpose of deliberate practice (Ericsson et al, 1993). Both passion types predicted the use of mastery achievement goals, however obsessive passion also predicted use of performanceapproach and performance-avoidance goals. Mastery achievement goals predicted deliberate practice while neither performance-approach nor performance-avoidance predicted deliberate practice. Performance-avoidant goals negatively predicted performance. Harmonious passion was also associated positively with subjective well-being. Both harmonious and obsessive passions appear to be factors in determining commitment to an activity, at least in practicing for competition (Vallerand, Mageau, Elliot, Dumais, & Rousseau, 2008). According to Ericsson et al. (1993), deliberate practice is not inherently enjoyable and if this is the case then an athlete is not intrinsically motivated to participate in deliberate practice. With respect to SDT then it is, perhaps, possible to say that one is not intrinsically motivated to participate in practice, but is intrinsically motivated to participate in actual competition. Harmonious and obsessive passion share many similarities with intrinsic and extrinsic motivation within self-determination theory. Intrinsic motivation and harmonious passion appear in whole to be very similar however there are some very subtle differences. Individuals who demonstrate harmonious passion for an activity spends a lot of their time practicing for and engaging in the activity and in fact like the activity for itself, which are characteristics of intrinsic motivation. The differences appear to lie in deliberate practice for the activity. According to Ericsson and colleagues (1993) definition, deliberate practice it is not always enjoyable and therefore not intrinsically rewarding according to Deci and Ryan (1985). This creates a puzzle for the triathlete, where the activities of deliberate practice (swimming, biking, 24

35 and running) are extremely similar if not exactly the same as in competition. Given the situation, either training or competition, psychological need satisfaction may hold the answer. A person training for a triathlon either in a pool, on a bike, or on a run, has displayed autonomy in choosing to train and can display competence by meeting training goals. If this individual is training with others the need for relatedness could be met as well and the result is intrinsic motivation. If this person is training alone, motivation might shift along the continuum toward integrated or identified regulation. All the while this individual is still harmoniously passionate for the activity. The passion construct therefore could be evident at the contextual or global level rather than at the situational level. An individual holds a passion for an activity but in different situations could be motivated either intrinsically and/or extrinsically. For example, a person has a passion for participating in triathlons, and is intrinsically motivated to ride and run because this individual finds these activities enjoyable, but does not enjoy swimming and demonstrates another form of motivation when engaging in this activity, for example integrated or identified regulation. The obsessive passion construct holds similarities with both intrinsic and extrinsic motivation. According to Vallerand (2007) a person with obsessive passion likes the activity for itself. In some cases the excitement derived by participation in the activity is what the individual craves. This is a characteristic of intrinsic motivation to experience, which is further elaboration of Deci and Ryan s Theory (2007). The integration of the activity into the self is a characteristic of integrated regulation, which is highly self-determined but not intrinsic motivation. Another characteristic that separates obsessive passion from intrinsic motivation is that the individual feels guilty if they do not perform the activity, which is associated with introjected regulation. Based on the situation (during an event or practicing for an event) a person s motivation could lie at any point or multiple points on the SDT continuum (Deci& Ryan, 1985). Therefore, theoretically a person who demonstrates harmonious passion for an activity could be motivated intrinsically and/or extrinsically to varying degrees at any given time during a race. If this is the case it bears similarities with Vallerand s (2007) hierarchical model of SDT. A person could be intrinsically motivated to participate in triathlons at the contextual level but at the situational level, either at a race or during any point in a competition, experience different forms of motivation. 25

36 While harmonious and obsessive passion have been studied in conjunction with other constructs such as performance (Vallerand, Mageau, Elliot, Dumais, & Rousseau, 2008), aggression in sport (Donohue, Rip, & Vallerand, 2009), and injury (Stephan, Deroche, Brewer, Caudroit, & Le Scanff, 2009), there has been no research comparing the difference in coping strategies between the two types of passion of which I am aware. There has been research done with respect to coping and self-determination theory and is discussed next. Coping in Sport In endurance races, one of the biggest stressors an athlete has to deal with is exertion pain. According to Brooks, Fahey and White (1996), noninjury pain in endurance sport can be the product of several factors. These factors include: a faster than comfortable heart rate, lactate build-up, depletion of muscle glycogen, respiratory muscle fatigue, and dehydration. All of these might occur in varying degrees during a long distance event such as a triathlon, the likelihood and frequency increasing the longer the event (i.e. Ironman). Therefore, it is imperative for athletes to cope with exertion pain in order to increase their chances to meet personally set goals. Kress and Statler (2007) studied exertion pain and coping strategies of nine former and current Olympic cyclists. In a grounded theory study, they found six higher order themes of pain, preparation, mental skills, mind/body, optimism, and control. They found that cyclists described their pain as ever present but their perceptions of it changing depending on where they were focusing. The mental skills they used included focusing on technical aspects of cycling or pedaling mechanics, body position, etc. as well as setting specific goals, utilizing positive selftalk, and imagery. Overall they accepted that exertion pain was a part of their sport and if they had control over it, for example setting the pace, their perception of it would be lessened. The results of this study are in line with Lazarus (1999) CMR theory. Based on the athletes perceptions of control, experience and effective use of coping strategies they were more likely to view exertion pain as a challenge and effectively deal with it. However, these nine athletes were elite cyclists and as a result had the experience and training to effectively cope with pain. A key element of Lazarus (1999) CMR theory is motivation and its impact on the appraisal and coping process. The integration of SDT and CMR theory is the focus of an article by Ntoumanis, Edmunds, and Duda (2009), and given the context of this paper is elaborated on 26

37 further. They proposed that the type of motivation could influence the appraisal process both directly and indirectly via SDT s psychological need satisfaction (autonomy, competence, and relatedness). When the three needs are satisfied, as with intrinsic motivation, integrated regulation, and identified regulation, an individual is more likely to appraise a stressful situation as a challenge. In contrast an individual with low autonomy and thwarted psychological needs, therefore experiencing either introjected regulation or external regulation, will perceive the stressful situation as a threat. Need satisfaction is also linked to secondary appraisals as autonomy and competence allow for the individual to have a sense of control over the situation. For example, triathletes in competition have chosen to participate and know that they have trained adequately for the race, in effect having control over their performance. Likewise the social support and interactions with other triathletes can provide emotional support as well as instrumental advice in race strategy, etc. A triathlete who is extrinsically motivated to compete may feel unprepared to race, a lack of control, and feel unable to cope effectively with any stressors that may arise during the competition. At this point I return to the concept of obsessive passion. An individual who is obsessively passionate for competing in triathlons may feel that it is imperative to participate in the race; in essence the activity is controlling this person s actions. Therefore, this individual might appraise a stressor within the competition or the competition itself as a threat. I elaborate more on this elsewhere in this paper. Coping responses are then indirectly influenced by motivation via the appraisal process. According to Lazarus (1999), when individuals appraise a stressful situation as a challenge and have perceived control over it, they are more likely to approach the situation and apply problemfocused coping strategies. When a situation is appraised as out of control and threatening, however, individuals are more likely to employ emotion-focused coping strategies. As a result of the appraisal process and coping outcome, the individual will experience the associated emotion. A challenge that is coped with effectively will lead to positive emotions and a threat that is not adequately coped with will lead to negative emotions. For example, a triathlete who is experiencing exertion pain during the running portion of a race may appraise and cope with the situation in two different ways. An individual experiencing highly self-determined motivation may appraise the pain as a challenge, something to overcome. This person then focuses energy on proper form and keeping a steady pace to overcome the temporary pain, knowing that the finish line is close. Upon completion of the race this individual then feels a sense of pride and 27

38 accomplishment for overcoming the pain. In contrast, a person experiencing low selfdetermination may appraise the pain as a threat to personal goals. This individual may think, this pain is going to keep me from making my time goal and get angry at this misfortune. This individual might view the body as out of control and use distracting thoughts or ruminate entirely on them, which may slow the individual s pace further. Upon completion of the race, this person is likely to experience dissatisfaction due to perceived inadequate physical conditioning. Gaudreau and Blondin (2002) developed a measure to assess athletes coping strategies in competitive sport settings initially called the Coping Strategies in Sport Competition Inventory (ISCCS) and later named Coping Inventory for Competitive Sport (CICS). They relied upon Lazarus and Folkman s (1984) definition and framework for coping. Their measure included ten coping subscales that upon analysis were clustered into higher order subscales of Task Oriented Coping (TOC) and Emotion Oriented Coping (EOC) strategies (Gaudreau & Blondin, 2002). TOC subscales included thought control, mental imagery, relaxation, effort expenditure, logical analysis, and seeking support. The cluster of EOC subscales included a mixture of emotionfocused strategies (venting of unpleasant emotion, social withdrawal) and avoidance-oriented strategies (mental distraction, disengagement). The initial scale included 95 items with the final scale including 39 items. French-Canadian athletes (N = 316) participated in the study to validate the CICS. Sports represented included golf, badminton, fire skating, gymnastics, alpine skiing, swimming, ice-hockey, deck-hockey, baseball, basketball, and volleyball. The four goals of the study included developing the scale and testing its structural validity, testing its convergent validity, testing its concurrent validity, and testing its differential validity. I focus more on the latter three goals. Gaudreau and Blondin (2002) assessed the convergent validity of the CICS by comparison to the French-Canadian translations of the Modified-COPE (MCOPE; Crocker & Graham, 1995) and the Ways of Coping Questionnaire (WOCQ: Folkman & Lazarus, 1985). Participants took either the WOCQ, eight subscales of the MCOPE, or the social desirability scale from the Personality Questionnaire for Athletes (QPS; Thill, 1979). The latter was not used in the convergent validity analysis. Several CICS subscales correlated significantly with subscales of the MCOPE and WOCQ as expected establishing convergent validity. The CICS subscales (i.e. effort expenditure, thought control, seeking support, mental distraction, disengagement/resignation, and venting of unpleasant emotion) and MCOPE subscales (i.e. 28

39 increased effort, positive reappraisal, seeking social support, mental disengagement, behavioral disengagement, and venting of emotion) correlated meaningfully with high associations. The authors point out that the sport specific nature of the CICS might explain why the correlations between it and the much broader MCOPE were not higher. Similarly the TOC and EOC subscales of the CICS showed moderate correlations to the TOC and EOC subscales of the MCOPE. This showed some support for the higher order subscales of the CICS. Gaudreau and Blondin also compared the correlations of the confronting/seeking social support scale of the WOCQ with the TOC subscale of the CICS and the WOCQ distancing/avoidance scale with the EOC subscale. Correlations of the scales were positive as expected. The authors cautioned the interpretation of the results due to the possibility of fluctuation of the factorial structure of the French-Canadian translation of the WOCQ across samples. Gaudreau and Blondin (2002) demonstrated concurrent validity by assessing the relationship between the coping strategy subscales of the CICS and appraisal and affective variables, as well as social desirability. The appraisal variables of perceived goal attainment, perceived relevance of the competition and sense of control were measured using three and five items respectively. Affective variables were measured by French-Canadian translations of the Positive and Negative Affect Scale (PANAS; Watson, Clark, & Tellegen, 1988) and the Competitive State Anxiety Inventory-2 (CSAI-2; Martens, Burton, Vealey, Bump, & Smith, 1990), which measures cognitive anxiety, somatic anxiety, and confidence. The authors found that athletes used TOC strategies more with increased perceived relevance of a competition. Athletes were less likely to use TOC strategies in competitions that were not valued as important by the individuals and perceived as non-threatening or non-challenging. Similarly, the athlete s sense of control increased with the use of TOC strategies (thought control, mental imagery, and effort expenditure) and decreased with EOC strategies like venting of unpleasant emotion and disengagement/resignation. When a person perceives control of the situation the need to reduce the unpleasantness is reduced. This could be due to appraising the situation as a challenge and having the capabilities to cope adequately, in this case with TOC strategies. TOC strategy use also increased with performance goal attainment. Gaudreau and Blondin posit that the relationship between coping and performance could be bi-directional. For instance performance goals are more likely to be achieved when using TOC strategies or that the achievement of performance goals facilitates the use of TOC strategies. 29

40 The final goal of Gaudreau and Blondin s (2002) study was to compare the use of coping strategies based on level of experience. Competition type was the basis for categorizing athletes experience level. Event types included international, national, provincial, and regional events. Elite athletes consisted of those athletes who participated in international and national level competitions. Athletes who competed in provincial and regional events were considered nonelite. Athletes (171 males and 145 females) ranged in age from 14 to 28 years. The authors had hypothesized that elite athletes would use more TOC and less EOC strategies than their non-elite counterparts. This would agree with Kress and Statler s (2007) findings described earlier, as well as other studies (Orlick & Partington, 1988; Thomas, Murphy, & Hardy, 1999). Results indicated that elite athletes used more mental imagery, relaxation, and effort expenditure than non-elite athletes. Elite athletes were also less likely to use venting of unpleasant emotions than non-elite athletes. A limitation of this study was the under-representation of male elite athletes in the sample (Guadreau and Blondin, 2002). Additionally, the numbers of elite athletes participating in national and international events were also under-represented. Most elite athletes were tested following competition in a provincial event and subsequently the level of competition less than they would have experienced in a national or international competition. As a result, the challenges faced in these events might not have warranted the need for different coping strategies. Additionally, the authors noted that the sample consisted of athletes from several different types of sport with both individual and team sports represented. Individual sport athletes might prefer social withdrawal, as a strategy while team sport athletes would favor seeking support from their teammates. The authors introduced expertise, gender, and type of sport as independent variables for future study. They also suggested using the measure pre/post and within competition to test the factorial structure s stability of coping. A follow-up study using the CICS addressed the associations with coping and selfdetermined behavior (Amiot, Gaudreau, & Blanchard, 2004). The study was conducted to test the mediating role of goal attainment in the relationship between coping and emotions. They also assessed the degree to which motivational quality predisposes athletes toward specific coping strategies. Figure 2.1 depicts the tested relationships between motivation, coping, goal attainment, and affect. Amiot and colleagues predicted that self-determined athletes would use predominantly TOC strategies and non-self-determined athletes would use predominantly disengagement-oriented strategies. They also assessed the mediating role of coping strategies on 30

41 goal attainment. They used the CICS to assess coping, the Sport Motivation scale (SMS; Briere, Vallerand, Blais, & Pelletier, 1995) to assess motivation, PANAS (Watson, Clark, & Tellegen, 1988), and the Attainment of Sport Achievement Goals Scale (A-SAGS; Gaudreau, Amiot, Blondin, & Blanchard, 2002). Data were analyzed using structural equation modeling (SEM) and path analysis to test the fit of the model depicted in Figure 2.1 (Amiot, Gaudreau, & Blanchard, 2004). The model proved to be an adequate fit to the data with 2 (15, N = 122) = 17.77, p =.28. Fit indices were NNFI =.967, CFI =.976 and RMSEA =.040. Amiot et al. (2004) tested two additional models to compare to the original model in order to confirm their hypothesis. Results showed evidence to support the mediating role of coping between motivation and goal attainment as well as the mediating role of goal attainment between coping and affect. The authors point out a limitation of their analysis with respect to the sample size. According to Tabachnick & Fidell, (2001), ideally a sample size of 200 or greater is preferred for SEM analysis. However, the complexity of the model tested was within acceptable standards with a participants-to-parameters ratio of close to 20 to 1. This allowed for reliable parameter estimates in the testing of the hypothesis. Figure 2.1. Model of associations between self-determination, coping, goal attainment, and variations in affect (Amiot, Gaudreau, & Blanchard, 2004). Based on the results of this study, Amiot and colleagues (2004) found that selfdetermined motivation was a positive predictor of the use of task-oriented coping strategies. 31

42 Likewise non-self-determined motivation was a positive predictor of disengagement-oriented coping strategies. They also showed evidence that goal attainment was a mediator between coping and affect. This is interesting in relation to Lazarus (1999) CMR theory, where the appraisal process and coping lead to the emotion experienced. Amiot and colleagues show evidence that outcome/goal attainment, regardless of strategy used, is important in determining affect. This is, of course, a result of coping strategy effectiveness. Athletes who are more selfdetermined are more likely to appraise a situation that could affect their goals as a challenge and use task-oriented coping strategies to address it. Appropriate coping strategies in turn allow the athlete to cope with the situation effectively and, more than likely, contribute to goal accomplishment fostering competency. Intuitively, goal achievement should lead to positive affect. Arguably this in turn fosters self-determination via satisfying the psychological need of competency, as outlined by Deci and Ryan (1985). The final study I address linking coping and motivation is by Gaudreau and Antl (2008). The authors examined the mediating role of sport related motivation and coping on life satisfaction before (Time 1) and after competition (Time 2). They also looked at the effect of dispositional perfectionism on self-determined and non-self-determined behavior, specifically evaluative concerns perfectionism and personal standards perfectionism. Evaluative concerns perfectionism (ECP) is the tendency of individuals to evaluate themselves harshly and to doubt their ability to succeed in their endeavors (Dunkley & Blankstein, 2000). They also believe that others require them to be perfect. Personal standards perfectionism (PSP) is an individual s tendency to set extremely demanding standards and to strive towards achieving them. ECP is widely believed to lead to negative outcomes while PSP is believed to lead to positive outcomes although support for this assumption is in question. A review of the empirical evidence in support of these two dimensions is beyond the scope of this paper and is not discussed. Gaudreau and Antl proposed that ECP was directly linked to non-self-determined behavior and PSP was linked to self-determined behavior. The model tested by Gaudreau and Antl is depicted in Figure 2.2. They hypothesized that, individuals with high life satisfaction before the competition will set high personal standards and are more likely to display self-determined motivation. In turn these individuals will be more likely to use task-oriented coping strategies, which will lead to goal attainment. The authors also hypothesized that goal attainment is positively linked to life satisfaction at Time 2. However, they expected that PSP would not 32

43 correlate with life satisfaction significantly. A second path that Gaudreau and Antl tested was that beginning with evaluative concerns perfectionism (see Figure 2.2). They hypothesized that ECP was positively linked to non-self-determined motivation, which in turn is positively linked to distraction-oriented and disengagement coping strategies. Disengagement oriented coping was hypothesized to be negatively linked to goal attainment. So a person who demonstrated ECP is more likely to be non-self-determined in sport and when faced with a stressful situation and is more likely to use either distraction or disengagement coping strategies. Disengagement from the activity is likely to hamper goal attainment, which results in less life satisfaction. Distraction oriented coping was not expected to be linked to goal attainment. Figure 2.2. Model of relationships between dispositional perfectionism, motivation, coping, goal attainment and life satisfaction. + = positive relationship, - = negative relationship (Gaudreau & Antl, 2008). Participants in Gaudreau and Antl s study (2008) included 186 French Canadian athletes (57% male, 43% female) ranging in age from 14 to 28 years. Average experience of the participants was 7.76 years. Similar to previous studies, athletes were competing in regional, 33

44 provincial, and national level events with the bulk of participants participating in provincial events. Sports included in the study were ice hockey, soccer, volleyball, broomball, tennis, badminton, and alpine skiing. The majority of participants (83%) were from the team sports of ice hockey, soccer, volleyball, and broomball with the remaining 17 % from the sports of tennis, badminton, and alpine skiing. However, tennis and badminton can be played as team sports as well. The participants completed a questionnaire at Time 1 (the last training session before an important competition) that included measures on life satisfaction, perfectionism, and motivation. The second questionnaire was administered at the first training session after the competition (Time 2). It included measures testing coping, goal attainment, and life satisfaction. Similar to the previous study the authors used the CICS (Gaudreau & Blondin, 2002) to assess coping, the French version of the SMS (Briere et al, 1995) to assess motivation, and the A-SAGS (Gaudreau et al, 2002) to assess goal achievement. Due to survey length items pertaining to integrated and introjected regulation were removed from the SMS for this study. The authors removed these items in response to coaches requirements of short assessments. They also used brief versions of the HF-MPS (Hewitt & Flett, 1991) and F-MPS (Frost, Marten, Lahart, & Rosenblate, 1990) to assess perfectionism that were developed by Cox, Enns and Clara (2002). They assessed life satisfaction using the Satisfaction with Life Scale (SWLS; Pavot & Diener, 1993). Gaudreau and Antl s (2008) results suggested that a partially mediated model fit the data best. All paths in the model (see Figure 2.2) were found to be significant with the exception of PSP and life-satisfaction at Time 1. In addition to the paths outlined in Figure 2.2 direct paths from PSP to TOC, ECP to distraction-oriented coping, and ECP to life satisfaction at Time 2 were found to be significant. An additional path from ECP to disengagement-oriented coping was near significance and retained in the model. The results show support for the partial mediation of self-determined motivation in the relationship between PSP and TOC during competition. Likewise non-self-determined behavior was a partial mediator between ECP and both distraction and disengagement-oriented coping. Perfectionism as a personality factor is shown to have an influence on both motivation and coping. This is congruous with a CMR standpoint as the person environment interaction involves not only the competition but also the person s appraisal of the situation as well as personality factors. A person who sets high standards for one s self is more likely to be self-determined, perhaps appraise a situation as a 34

45 challenge, and use coping strategies that will achieve those standards. A person with harsh selfevaluations and doubtful abilities is more likely to appraise a situation as a threat, be non-selfdetermined and is more likely to use distraction or disengage from the activity. Similar to the findings of Amiot et al. (2004) goal attainment was found to be a mediator between coping and post competition affect. In this study goal attainment positively affected life satisfaction. This of course makes sense, as one achieves one s goals one is more likely to feel positive affect and feel more satisfied with life. Gaudreau and Antl (2008) note several limitations to their study. The first limitation is the small sample size with respect to the sport types. They recommend future studies have a larger sample of athletes from a wider array of sports to increase generalization to the population as well as assess the invariance across subgroups. Of particular note are the possible differences in model fit between team and individual sports. Certain coping strategies might prove to be more effective, or more feasible, in certain sport contexts. For example, in a team sport athletes might be more likely to seek information from teammates or coaches during competition than an athlete in an individual sport. A more robust sample size, assessing model fit to a specific sport or category (i.e. individual sport) might be more feasible to meet the required n for a structural equation model analysis as well as increase power. Another limitation the authors address is the contextual nature of the motivation measure used in this study, which was situational in design. They cite Vallerand s (1997) hierarchical model of intrinsic and extrinsic motivation as reason for future studies to assess each construct at the appropriate level, global, contextual, or situational. This quite possible could result in stronger relationships between the constructs studied. The final limitation discussed is the absence of integrated and introjected motivation from the SMS (Briere et al., 1995). Gaudreau and Antl cite unpublished data in which the correlation between perfectionism and introjected regulation is identical to extrinsic motivation; however, this was with a student population and not athletes. They implore that future empirical evaluations include the subscales of introjected and integrated regulation. The triathlon is an individualized endurance sport that shares similarities with running a marathon and it can be reasonably assumed that motivation reasons to engage in the sport are similar for both contexts. Initial forays into the sport might be due to a need to improve one s health or fitness, or possibly to lose weight. For the novice initial motivation might be extrinsic in nature. As one participates more and more the motivation to continue might become 35

46 predominantly intrinsic in nature. After an individual starts to develop confidence and ability this person will be satisfying the psychological need for competence. By autonomously choosing to engage in triathlons, perhaps even joining a triathlon club, the individual is surrounded with like-minded people. These behaviors satisfy the remaining psychological needs of autonomy and relatedness as outlined by Deci and Ryan (1985). Over the course of one s repeated involvement in the activity, the integration of behavior into one s identity can occur. Perhaps at this level of involvement a passion develops for the activity. The passion can be harmonious with one s life or obsessive in nature. In order for the integration to occur one must experience success in the form of achieving one s goals. Success occurs as the result of meeting the challenges that arise during the course of a competition, such as exertion pain. Research has shown that coping strategies act as a mediator between motivation and goal achievement (Gaudreau& Blondin, 2002). Goal achievement also has been positively linked to positive affect (Amiot, Gaudreau, & Blanchard, 2004) and life satisfaction (Gaudreau & Antl, 2008). According to Ntoumanis et al. (2009) those high in self-determination (i.e. intrinsic motivation, integrated regulation) are more likely to view a stressful situation as a challenge to their goals rather than a threat. They are then more likely to use effective coping strategies to deal with that stressor. If successful, they are more likely to achieve their goals, which, leads to positive affect and life satisfaction. Gaudreau and others research has shown that self-determined motivation is positively linked to task-oriented coping strategies, which are in turn positively linked to goal achievement. They have also shown non-self-determined motivation is positively linked to distraction-oriented and disengagement-oriented coping strategies with disengagement-oriented coping strategies negatively linked to goal achievement. Theoretically, people who are extrinsically motivated to participate in a triathlon, when stressed, are more likely to view that stressor as a threat to achieving their goals and will cope by either distracting themselves from the stressor or disengaging themselves from the activity. Based on this research a question arises with respect to passion. If passion is grounded in self-determination theory, do the two constructs of harmonious and obsessive passion behave similarly to self-determined and non-determined motivation with respect to coping strategies? According to Vallerand, the conceptualization of harmonious passion is similar to highly selfdetermined motivation, therefore it is possible that a person with harmonious passion would appraise an in race stressor as a challenge and use TOC. Would a person demonstrating 36

47 obsessive passion view that same stressor as a threat? Or would obsessive passion be positively linked to distraction- or disengagement oriented coping strategies? Ultimately, if grounded in SDT, where and how does the passion model fit with SDT? In summary, there are benefits to participating and training for marathons that hold true for triathlons. Improved self-esteem, lower anxiety levels, social effects, and a general improvement in fitness all seem to play a part in the motivation to run. The popularity of the sport of triathlons has grown steadily according to USA Triathlon (2009), with participation in recent years between 200,000 and 250,000 athletes competing in events every year. The overwhelming majority of these athletes are amateurs who vary in age. Despite it s growing popularity there is a dearth of scientific research on the motivation of individuals who initiate and continue participation in this sport. The triathlon combines three separate disciplines (i.e., swimming, cycling, running) into a single competitive event (United States Olympic Committee, 2009). The distance for each portion can vary from sprints, (750-meter swim, 20 kilometer cycle, and a 5 kilometer run) to the Ironman/ultra distance (2.4 miles swim, 112 mile cycle mile run). The grueling aspects of the race, the Ironman distance in particular, have been depicted in media coverage of the race and are evidenced by the number of did not finish race participants. A person must have strong motivation to participate as well as develop strategies to cope with the physical and psychological stressors that occur during a race. The underlying theories and model examined in this study include: Self-determination theory (Deci & Ryan, 1985), the Dualistic model of Passion (Vallerand, 2008), and Cognitive Motivational Relational theory on stress and coping (Lazarus, 1999). Deci and Ryan (1985, 2000) postulated a theory of self-determination (SDT) that has been tested by them and others, and has demonstrated considerable utility (e.g. Frederick & Ryan, 1993; Pelletier, Fortier, Vallerand, & Briere, 2001; Amiot, Gaudreau, & Blanchard, 2004). At its core is the continuum that ranges from intrinsic motivation to amotivation. Intrinsic motivation is when a behavior is performed because it is enjoyable. Extrinsic motivation is when a behavior is determined by an outside source, like a trophy. Finally, amotivation is when there is no desire to perform a specific behavior (Ryan & Deci, 2007). Doing an activity for its own sake (Ryan & Deci, 2007, p. 2) is the hallmark of being intrinsically motivated. For example, a person who swims, not just to train or to seek the 37

48 benefits of swimming, but because this individual enjoys the act of swimming would be said to be intrinsically motivated to do so. Deci and Ryan (1985) posit that when people meet the three psychological needs of competency, autonomy, and relatedness they are more self-determined and more likely to be intrinsically motivated. If people who compete in triathlons feel they are competent in the sport, and do so under their own volition, they are more likely to be intrinsically motivated to continue to train and compete. Additionally, being around other triathletes may help satisfy the need for relatedness. A human being will seek out contexts in which one feels one belongs and exhibit behaviors that foster competency and autonomy. Ultimately social environments, that foster a connectedness with others and one in which a person can display competence help to enhance intrinsic motivation. The interaction of the person and the environment in these contexts will eventually lead to repeated behavior where a person can meet these psychological needs. The context of triathlons is a perfect environment to study intrinsic motivation. The dualistic model of passion (Vallerand et al., 2003; Vallerand, 2008) is grounded in SDT. Vallerand et al. define passion as, a strong inclination toward an activity that people like, that they find important, and in which they invest time and energy (p. 757; 2003). Individuals define themselves by what they are passionate about, for instance people who participate regularly in triathlons might refer to themselves as triathletes. Therefore from an SDT perspective, people who are intrinsically motivated to compete in triathlons may become so passionate about the sport that they integrate it into their identity (Vallerand, 2008). Vallerand (2008) and colleagues, (2003) posit that there are two types of passion, harmonious and obsessive. Harmonious passion is the result of individuals autonomously internalizing the activity into their identity. A person who actively participates in the activity for the sake of the activity and has attached no contingencies to participation is said to display harmonious passion. Obsessive passion, on the other hand, is the result of partial internalization (and an absence of integration) of the activity into the self. In those instances, the activity defines the person and has contingencies, such as social acceptance, attached to it. People in this motivational category might participate in triathlons not for enjoyment, but rather out of a need to be accepted by others, or to satisfy a need for stimulation (e.g., skydiving for the adrenaline rush). 38

49 As mentioned above, harmonious passion is the result of self-determined integration of the activity into a person s identity. Vallerand (2008) cites Deci and Ryan s (2000) concepts of intrinsic and integrated tendencies of a person as leading to passion. Therefore, if individuals autonomously select an activity and are intrinsically motivated to participate in it then they may eventually become passionate towards that activity. As a result of engaging in the activity, a person is free to experience positive outcomes both during and after participation. In contrast, obsessive passion is implicated when an individual is controlled by the passionate activity (Vallerand, 2008). This controlling ability is the result of contingencies that the individual places on participating in the activity or sensory experiences attached to the activity (i.e. thrill seeking). It is in these instances where a person must participate in the activity at the expense of other activities. For example, a person might feel the need to get a training run in at the expense of preparing for an exam or job. A person might also participate in the activity at a detriment to physical well-being, for example training when injured or in hazardous conditions (e.g. swimming in high seas or running in a thunderstorm). If the individual fails to complete a scheduled training run or participate in an upcoming event, the result can be experienced negative affect or dissonance. Previous research has examined the relationship between SDT and coping strategies. A study by Gaudreau and Antl (2008) examined the mediating role of sport related motivation and coping on life satisfaction before and after competition. The study included 186 French Canadian athletes from a variety of team and individual sports. Results of path analysis indicated that self-determined motivation was significantly positively linked to task-oriented coping (TOC) and non-self-determined motivation was significantly positively linked to distraction- and disengagement-oriented coping. TOC and disengagement-oriented coping were significant mediators between motivation and goal attainment. TOC was positively linked to goal attainment and disengagement-oriented coping was negatively linked. While harmonious and obsessive passion have been studied in conjunction with other constructs such as performance (Vallerand, Mageau, Elliot, Dumais, & Rousseau, 2008), aggression in sport (Donohue, Rip, & Vallerand, 2009), and injury (Stephan, Deroche, Brewer, Caudroit, & Le Scanff, 2009), there has been no research comparing the difference in coping strategies between the two types of passion of which I am aware. 39

50 The purposes of this study were to assess the relationships between intrinsic and extrinsic motivation, passion and coping strategies with respect to triathletes. The first purpose was to determine the similarities and differences between Deci and Ryan s SDT (1985) and Vallerand s Passion model (2008). I expected to find a clear theoretical link between self-determined motivation and harmonious passion. However, I expected a link between obsessive passion and intrinsic and/or extrinsic motivation to be weak if even present. A secondary purpose was to replicate the same relationships between SDT and coping strategies within the triathlon context (Amiot, Gaudreau, & Blanchard, 2004; Gaudreau & Antl, 2008; Gaudreau & Blondin, 2002). Similar to previous studies, it was hypothesized that self-determined motivation is positively linked to TOC and non-self-determined motivation is positively linked to distraction- and disengagement-oriented coping. This study also tested the mediating effects of coping on participation hypothesizing that TOC was positively linked to total triathlons completed and distraction- and disengagement-oriented coping were negatively linked to total triathlons completed. The final purpose was to explore the differences in coping strategies used by people demonstrating either harmonious or obsessive passion. It was hypothesized that people who demonstrate harmonious passion are more likely to use TOC strategies and individuals with obsessive passion are more likely to use distraction- or disengagement-oriented coping strategies and that similar mediating effects would be observed. Motivation and Coping in the Sport of Triathlons The triathlon environment also appears to be one that can engender passion. The dualistic model of passion (Vallerand et al., 2003; Vallerand, 2008) is grounded in SDT. Vallerand (2003) defines passion as people s inclination toward an activity that they like, invest time and energy, and one they find important. Individuals define themselves by what they are passionate about; for instance, individuals who complete an Ironman triathlon now call themselves either an Ironman or Ironwoman. Likewise, people who participate regularly in triathlons might refer to themselves as a triathlete. Therefore, from an SDT perspective, people who are intrinsically motivated to compete in triathlons may become so passionate about the sport that they integrate it into their identity (Vallerand, 2008). Vallerand (2008) and Vallerand et al. (2003) posit that there harmonious and obsessive types of passion. These passion types are defined by how individuals have internalized their engagement in an activity into their identity. Harmonious passion is the result of individuals 40

51 autonomously internalizing the activity into their identity. A person who actively participates in the activity primarily for the sake of the activity, and without contingencies for that participation, is said to display harmonious passion. Obsessive passion, on the other hand, is the result of partial internalization (and an absence of integration) of the activity into the self. In those instances, the person self-defines by reference to the activity but has contingencies (e.g., social acceptance, self-esteem) attached to it. People in this motivational category might participate in triathlons not for enjoyment, but rather out of a need to be accepted by others, or to satisfy a need for stimulation (e.g., skydiving for the adrenaline rush). Harmonious passion is the result of self-determined integration of the activity into a person s identity. Vallerand (2008) cites Deci and Ryan s (2000) concepts of intrinsic and integrated tendencies of a person as leading to passion. Therefore, if individuals autonomously select an activity, and are intrinsically motivated to participate in it, then they may eventually become passionate towards that activity. The activity is a harmonious part of the individual s life, and acts in congruence with all the aspects of that person s self. As a result of engaging in the activity, a person is free to experience positive outcomes during and after task engagement. For example, a person enjoys the act of racing in a triathlon, and enjoys the effects resulting from physical activity afterwards. When completing the passionate activity, the person is free to engage in other activities, and can skip training for a day or two without any ill effects, such as guilt, or negative affect. In contrast, obsessive passion is implicated when an individual is controlled by the passionate activity (Vallerand, 2008). This controlling ability is the result of contingencies that the individual places on participating in the activity, or sensory experiences attached to the activity (i.e. thrill seeking). It is in these instances where a person must participate in the activity at the expense of other activities. For example, a person might feel the need to get a training run in at the expense of preparing for an exam or job. A person might also participate in the activity at a detriment to physical well-being; for example, training when injured or in hazardous conditions (e.g. swimming in high seas or running in a thunderstorm). If the individual fails to complete a scheduled training run, or participate in an upcoming event, the result can be experienced negative affect or dissonance. A characteristic of passion is sustained participation in the activity over time (Vallerand, 2008). A person who maintains a level of training and participating in triathlons could be very 41

52 passionate about that activity. For this study and based on Vallerand s conceptualization of the construct, passion for triathlons will be considered at a contextual level, similar to the contextual level in Vallerand s hierarchical model of intrinsic and extrinsic motivation (1997, 2007). Vallerand s (1997, 2007) hierarchical model incorporates five postulates that elaborate on the structure and theoretical background. The first postulate states that any study of motivation must include intrinsic motivation, extrinsic motivation and amotivation. The second postulate posits that intrinsic motivation, extrinsic motivation, and amotivation exist at the situational level, the contextual level, and the global level. Motivation demonstrated at the situational level is motivation to engage in a specific activity, like a training run, or at any given moment in time. Motivation at the contextual level is motivation to participate in a given context, for instance to participate in a sport, like triathlons. Finally, motivation at the global level is an athlete s dispositional or trait to interact with the environment in general. Postulate three states that motivation is determined by social factors and that the higher levels of motivation (global or contextual) affect motivation at the lower levels. Within this postulate are three corollaries. Motivation is impacted by social factors (Corollary 3.1) from each level (global, contextual, or situational) that are mediated (Corollary 3.2) by the psychological needs satisfaction (competence, autonomy, and relatedness) and that there is a top down effect within the hierarchy (Corollary 3.3). In other words, motivation at the higher level can influence motivation at a lower level. For example, if a person is motivated to participate in triathlons intrinsically then this person will be intrinsically motivated to train for those events. In postulate 4 Vallerand contends that there is a recursive effect from the lower levels to the higher levels. This allows for motivation change. For example, an athlete who perhaps first engaged in the sport for external reasons, after having experienced intrinsic motivation repeatedly at the situational level, may begin to experience intrinsic motivation at the contextual level. Postulate 5 includes two corollaries that elaborate on the outcomes of motivation or more specifically the engagement of the sport behavior. Corollary 5.1 includes the notion that as one moves along the continuum, from intrinsic motivation to amotivation, positive consequences decrease. For example, in general a person who is highly self-determined and engaging in an activity for its own sake will have more positive affect than an individual who is not self-determined. Vallerand states in corollary 5.2 that each level of motivation has a corresponding level of consequences and is related to the level of motivation that led to it. 42

53 The triathlon is a combination of three separate exercise disciplines performed in one competition. This competitive environment, for many, fosters intrinsic motivation and passion. Many club triathletes talk about getting hooked when they participated in their first race and that they love the environment (Dietrich, unpublished). Several cite the camaraderie of training, and feeling of accomplishment after a good race as what motivates them. Others are motivated by the healthy lifestyle being a triathlete promotes. Based on data from a pilot study, this researcher found that club triathletes of varying ages are self-determined and are harmoniously passionate toward their activity. This in turn should lead to healthy behaviors in which a person will maintain a fitness regimen in order to participate in a triathlon event. However, according to Vallerand (2007), an obsessively passionate person participates in the activity often at the expense of other perhaps more important activities (e.g. preparing for a work presentation) as well as during unsafe conditions (e.g. cycling in snow and ice) or while injured. This study does not evaluate what is considered healthy or unhealthy, however, it can be inferred that people with obsessive passion toward triathlons might train excessively at a detriment to their health. It could be argued that the training regimen for an Ironman distance as well as the race itself has detrimental effects on the body. The level of dedication to training could be obsessive and hold similarities to exercise addiction. So it is important to compare both harmonious and obsessive passion between those that compete in the shorter distance triathlons with those who participated regularly in Ironman triathlons. Is a person who competes regularly in Ironman triathlons more likely to demonstrate obsessive or harmonious passion in comparison to a person who only competes in shorter distance events? If there is a difference then a future study can examine what level of training might be hazardous to one s health In order to sustain involvement to become passionate about an activity and in line with SDT (Deci & Ryan, 1985) a person must demonstrate competency in the activity. Competency can be achieved by improved performance. In order to improve performance a person must be able to effectively cope with race stressors effectively. Whether it is exertion pain or an equipment malfunction the appropriate coping strategy can help to achieve performance goals. Previous research has examined the relationship between SDT and coping strategies. Gaudreau and Antl (2008) examined the mediating role of sport related motivation and coping on life satisfaction before and after competition in 186 French Canadian athletes from a variety of team and individual sports. Results of path analysis indicated that self-determined motivation was 43

54 significantly and positively linked to task-oriented coping (TOC), and non-self-determined motivation was significantly positively linked to distraction- and disengagement-oriented coping. TOC and disengagement-oriented coping were significant mediators between motivation and goal attainment. TOC was positively linked to goal attainment and disengagement-oriented coping was negatively linked. While harmonious and obsessive passion have been studied in conjunction with other constructs, such as performance (Vallerand, Mageau, Elliot, Dumais, & Rousseau, 2008), aggression in sport (Donohue, Rip, & Vallerand, 2009), and injury (Stephan, Deroche, Brewer, Caudroit, & Le Scanff, 2009), there has been no research comparing the difference in coping strategies between athletes possessing the two types of passion of which I am aware. However, as passion is conceptualized at the contextual level and coping at the situational level, a mediator between the two is necessary. For this reason self-determined and non-self-determined motivation will be measured at the situational level. Postulate 3 in Vallerand s (1997, 2007) hierarchical model of intrinsic and extrinsic addresses this issue. Intrinsic and extrinsic motivation were measured at both the contextual level and at the situational level while passion was measured at the contextual level. Therefore, it was hypothesized that passion, at the contextual level, will predict motivation at the situational level. Harmonious passion should positively predict self-determined motivation and negatively predict non-self-determined motivation. The predictive power of obsessive passion will also be assessed, as it is unclear if obsessive passion is similar to self-determined or non-self-determined motivation based on Vallerand s (2008) conceptualization. In order to compete in a triathlon, even the shorter distance triathlons, a person must be motivated to do so and in order to finish, cope with any stressors that occur during a race. At the situational level, motivation was assessed with respect to a specific race event. At this time the coping strategies used were also assessed. It is hypothesized that motivation at the situational level acts as a mediator between passion and coping. Coping then acts as mediator between motivation and the outcome variables of goal attainment and future intentions (See Figure 2.3). A positive outcome of goal attainment possibly results in intentions to continue to participate in future events. Both direct effects (coping on future intentions) and indirect effects (with goal attainment as mediator) were tested. 44

55 Contextual Situational + SDM + TOC + + HHPP OP + + NSDM + DTOC Goal Attain + Future intentions + DNOC Figure 2.3. Proposed model integrating passion, motivation, and coping on goal attainment and future intentions to run triathlons. HP = harmonious passion; OP = obsessive passion; SDM = self-determined motivation; NSDM = non-self-determined motivation; TOC = task-oriented coping; DTOC = distraction oriented coping; DNOC = distraction-oriented coping; Goal Attain = goal attainment. The main purpose of this study was to test the model depicted in Figure 2.3. The model depicts motivation and coping strategies as mediators between passion and goal attainment as well as future intent to participate in triathlon events. It was hypothesized that harmonious passion will predict self-determined motivation at the situational level, which would, in turn, predict the use of task-oriented coping (TOC) strategies. TOC strategies would then be positively linked to goal attainment and future intentions to participate in more triathlons. Theoretically obsessive passion could positively predict both self-determined and non-self-determined motivation. Non-self-determined motivation previously has been shown to significantly predict the use of distraction- and disengagement-oriented coping strategies (Gaudreau & Antl, 2008). It was hypothesized that the use of distraction or disengagement coping strategies would lead to 45

56 individuals not achieving their goals and might lead to them not planning on participating in as many triathlons in the future. An additional purpose of this study was to assess the differences in types of passion, motivation and coping strategies based on age and event type. It was hypothesized that individuals who participate in Ironman distance triathlons will demonstrate a greater amount of obsessive passion when compared to individuals who only run the shorter distance events. Research questions Research question 1: Is a person who competes regularly in Ironman triathlons more likely to demonstrate obsessive or harmonious passion? And is the amount of self-reported training different among the two passion types? Do obsessively passionate people train more than those who demonstrate harmonious passion? Research question 2 (Figure 2.3): Do harmonious and obsessive passions differ on predicting situational motivation and coping strategies? Does motivation act as a mediator between passion and coping strategies? Do coping strategies act as mediators between motivation and goal attainment and future intentions? 46

57 CHAPTER 3 METHOD Participants Participants included 632 individuals of whom 323 were men and 290 were women (9 participants did not identify their gender) ranging in age from 18 to 74 years of age (M = 37.87, SD = 11.85). Years of triathlon experience ranged from approximately 0 32 years with a mean of 5.69 years (SD = 5.97 years). Table 3.1 depicts participant demographic information and descriptive statistics. Only 299 participants completed the second portion of the survey and therefore only those corresponding data were used in the SEM procedure. Incomplete surveys included surveys where the participant started, but failed to finish, the survey, when a participant failed to answer major portions of the survey, or failed to answer the a majority of items in a subscale. Any participants responses that fell into this category were omitted from analysis and as a result only 299 responses were used in the analysis. Table 3.1 Minimum, Maximums, Means and Standard Deviations for Data Obtained from the First Survey N Minimum Maximum M SD Age Years of Experience Sprint Triathlons Olympic Triathlons Half-Ironman Triathlons Ironman Triathlons Total Events Future Sprint Triathlons Future Olympic Triathlons Future Half-Ironman Triathlons Future Ironman Triathlons Total Future Triathlons LTEQ1 Mild LTEQ 1 Moderate LTEQ 1 Strenuous LTEQ MET LTEQ = Leisure time exercise questionnaire; MET = Metabolic equivalent score 47

58 Table 3.1 above displays the minimums and maximums, means, and standard deviations for age, years of triathlon experience, triathlons completed, future triathlons planned in the next 12 months, LTEQ scores, and MET scores. Out of the 622 respondents to the first survey 524 responded as having engaged often in regular exercise that works up a sweat (LTEQ 2), 87 sometimes engaged in regular exercise, and 9 rarely engaged in regular exercise. Measures The four measures include the Behavioral Regulation in Sport Questionnaire (BRSQ; Lonsdale, Hodge, & Rose, 2008), the Passion Scale (Vallerand, et al., 2003), The LTEQ (Godin & Shephard, 1985), the Coping Inventory for Competitive Sport (CICS; Gaudreau & Blondin, 2002), and the Assessment of Sport Attainment Goals (Gaudreau & Amiot, in revision). Additional detail on all measures is provided below. The online survey was generated using Nquiretech Survey Management System by Sciberus (Decatur, GA). Leisure-Time Exercise Questionnaire (LTEQ). Godin and Shephard (1985), developed the LTEQ to assess weekly strenuous, moderate, and light physical activity. The LTEQ consists of two items. The first item assesses the quantity (events per week) of strenuous (i.e. running, jogging, vigorous swimming, vigorous long distance bicycling), moderate (fast walking, easy bicycling, easy swimming), and light activity (i.e. yoga, easy walking, golf) while the second item assesses the frequency of regular activity over a 7-day period. Researchers can use the results of the LTEQ to calculate a metabolic equivalent (MET) score. The questionnaire has been validated as a strong predictor of aerobic fitness (Godin & Shephard, 1985; Jacobs, Ainsworth, Hartman, & Leon, 1993). Jacobs et al. reported that the LTEQ had correlation coefficients with accelerometer derived MET scores of.32 and with four week history derived MET scores of.36. However, the correlation coefficients between each individual activity level of the LTEQ (light, moderate, and heavy) and four week MET scores were.47,.12, and.52 respectively. The correlation between the heavy or strenuous activity score seems to demonstrate the most validity with the actual derived MET scores done in the study. The MET score is calculated from the LTEQ by this formula: MET = 3(light) + 5(moderate) + 9(strenuous). This score is an estimate of the rate of oxygen consumption with one MET equaling 3.5 ml/kg/min (Brooks, Fahey, & White, 1996). For example if individuals indicated that they exercise three times a week by at an intensity level of a light walk, the resulting MET score will be 9 METS or nine times more than the resting metabolic rate. METs for the elements 48

59 in a triathlon are as follows: pleasure biking = 3-8 METs; jogging = 8-12 METs; and swimming = 4-8 METs (Brooks et al., 1996). The LTEQ was used to determine both exercise frequency as well as MET rate. Due to the nature of metabolic equivalent scores, a person who exercises multiple times a week at a lower intensity may have the same MET score as an individual who exercises only once at a strenuous level. Therefore, both raw frequency data were assessed as well as the overall MET score for analysis. BRSQ. The BRSQ is grounded in Deci and Ryan s SDT (1985), and was developed by Lonsdale and colleagues (2008) to assess the quality of athlete intrinsic motivation, extrinsic motivation, and amotivation. The measure includes 24 items with four items assessing each of the following subscales: general intrinsic motivation (IM), integrated regulation (IG), identified regulation (ID), introjected regulation (IJ), external regulation (EX), and amotivation (AM). The participants responses are measured on a 7-point Likert-type scale anchored at 1 (not at all true), 4 (somewhat true) and 7 (very true). The measure has demonstrated good reliability with Cronbach s alpha subscale coefficients ranging from.76 to.91 (Lonsdale, Hodge, & Rose, 2008). In a Confirmatory Factor Analysis (CFA) Lonsdale et al. reported a good fit to the data based on fit indices despite a significant scaled 2, 2 df=237, n=316 = , p <.01. They reported fit indices of CFI =.97, TLI =.97, and RMSEA =.07. In order to differentiate the measurement of motivation as either contextual or situational different instructions were used. The following verbiage was used at Time 1 to measure contextual motivation: Below are some reasons why people participate in sport. Using the scale provided, please indicate how true each of the following statements is for you. When deciding if this is one of the reasons why you participate, please think about all the reasons why you participate. There are no right or wrong answers, so do not spend too much time on any one question and please answer as honestly as you can. Some items may appear similar but please respond to all the statements by filling the appropriate circle. At Time 2, the following instructions were utilized to measure situational motivation: When answering the next set of questions please think about the event that you just completed and how you would answer these questions accordingly. Using the scale provided, please indicate how true each of the following statements is for you. When 49

60 deciding if this is one of the reasons why you participated in this recent event, please think about all the reasons why you participated. There are no right or wrong answers... Passion scale. Vallerand and colleagues (2003) developed the passion scale to test the dualistic model of passion. There are 16 items assessed on a 7-point Likert-type scale (1= do not agree at all to 7= very strongly agree). Harmonious (HP) and obsessive passion (OP) are assessed each by 6 items with an additional 4 items assessing if passion is present (PC; passion criteria). The passion scale has demonstrated moderate to strong reliability with Cronbach s of.80 and.89 for harmonious and obsessive passion respectively (Vallerand, Rousseau, Grouzet, Grenier, & Blanchard, 2006). A CFA showed a reasonable fit if the measurement model to the data for the two-factor structure of passion ( 2 df = 76, n = 206 = , p <.001; CFI =.93, SRMR =.077, RMSEA =.077) even though the 2 was significant. CICS. Gaudreau and Blondin (2002) developed the CICS to assess athletes coping strategies in competitive sport settings. There are 10 subscales measuring the following coping strategies: mental imagery (MI), effort expenditure (EE), thought control (TC), relaxation (R), logical analysis (LA), seeking support (SS), distancing/social withdrawal (SW), mental distraction (MD), disengagement (D) and venting of unpleasant emotions (VE). Item responses were provided on a 5-point Likert-type scale (from 1= not at all to 5= very strongly). The authors categorized the subscales hierarchically in three second-order dimensions. Task-oriented coping includes the subscales MI, EE, TC, R and LA. Distraction-oriented coping includes the SW and MD subscales. Disengagement (D) and VE are included in the second-order dimension of disengagement-oriented coping. Reliability reported by Gaudreau and Blondin ranged from Cronbach s alpha s of.67 (LA) to.87 (VE). An acceptable fit of the 10-factor model to the data based on fit indices was reported despite the significant 2 statistic (Bollen-Stine corrected 2 df = 652, n = 316 = , p =.03; CFI =.931, TLI =.921, RMSEA =.036). A-SAGS (Attainment of Sport Achievement Goals). Gaudreau and colleagues (2002) developed the A-SAGS to assess goal attainment after a specific competition. Items are measured on a 7-point Likert-type scale (1=not at all to 7=totally). The A-SAGS contains 12 items with four items each assessing the separate goal criteria of mastery, self-referenced, and normative goals. The measure has been used and validated in several studies (Amiot, Gaudreau, & Blanchard, 2004; Gaudreau & Antl, 2008; Gaudreau & Blondin, 2002) as well as showing good reliability (Cronbach s ranging from.86 to.93; Gaudreau & Antl, 2008). 50

61 Table 3.2 Survey Structure Item number Item description Survey 1 1 Informed Consent 2 In order to maintain your anonymity please enter a four-digit code followed by the third letter in your first name. The purpose of this code is to match up your responses in this survey to the follow up survey at a future date. Please make sure this is a code that you can remember easily. You will be prompted to enter it in the second survey. (Do not use your social security number) 3 Please enter your current age. 4 Please select your gender. 5 How many years have you been training for and participating in triathlon events? Enter number in years. (e.g. 5 years would be 5, 6 months would be 0.5 years) 6 Are you an active member (within the last 6 months) of a triathlon club (or any running, swimming, biking club)? An active member is one who attends meetings, trains with other club members, etc. 7 How would you classify your participation in triathlons (Self-Identified Participation level) Choose the best answer (Professional, competitive, recreational, purely for fitness, other) 8 Please indicate the amount of races you have run in total for each distance. Enter the total you have done in your lifetime for each. 9 LTEQ1 10 LTEQ2 11 Please indicate the amount of races you plan on running in the next year for each event type. Enter the total for the next 12 months BRSQ Passion scale 52 Date of next event 53 address Survey 2 1 ID code 2 Please indicate the amount of races you plan on running in the next year for each event type. Enter the total for the next 12 months BRSQ CICS A-SAGS 77 Please indicate the type of event you just competed in. (4 triathlon distances, 1 other choice) Note. LTEQ = Leisure Time Exercise Questionnaire, BRSQ = Behavioral Regulation in Sport Questionnaire, CICS = Coping Inventory for Competitive Sport, A-SAGS = Attainment of Sport Achievement Goals 51

62 Procedures Institutional Review Board (IRB) approval was obtained from the Florida State University (FSU) Human Subjects Committee for this study. Following approval the recruitment process began. I made contact with USAT in order to aid in recruitment. USAT agreed to include a link to the survey in a monthly newsletter. The following verbiage was included: Invitation to participate in an online study on motivation and coping in the sport of triathlons. Hello my name is Rick Dietrich and I am obtaining a PhD at Florida State University as well as an avid triathlete. For my doctoral dissertation I am studying what makes people want to train for and participate in triathlon/ironman competitions. I am also interested in how individuals deal with the physical and mental challenges of competition. My study includes two surveys, the first of which you can take any time after receiving this (just click the hyperlink below). I will contact you via with the link to the second survey (there are two questions at the end of the survey asking for the date of your next planned event and your address). The first online survey asks several questions pertaining to your triathlon experiences and motivational reasons (for example how many events and what type you have run in as well as multiple choice questions). Both surveys are completed online and take only about 10 to 15 minutes each to complete. Thank you in advance for your time and if you have any questions please feel free to contact me. You must be 18 years or older to take this survey. Full instructions as well as a request for consent are provided on the first page of the survey. Individuals were required to read the informed consent form and check a link acknowledging consent before being directed to the next page of the survey. Survey data were kept independent from contact information ( address), which was obtained at the end of the first online survey. In addition to an address, participants supplied the date of their next competition. The second link was forwarded to the participant within 24 to 48 hours of that date. All data were collected electronically and downloaded into an Excel file. 52

63 I obtained a sample size of 299 in order to test the model depicted in Figure 2.3 with Structural Equation Modeling (SEM). Rationalization for this sample size is discussed further under the heading Data Analysis. In order to achieve such a large sample size participants were recruited via several different means. The United States of America Triathlon Association (USAT) was initially contacted for assistance. After following a suggestion by a contact at USAT, a link to the survey was posted on the USAT Facebook page. After this course of action yielded only a few respondents, USAT agreed to attach a brief description of the study and a link to the survey in a weekly enewsletter, which was ed to their membership. A link to the survey was similarly posted on the Active.com Facebook page. The above efforts garnered few responses. I then contacted over 450 triathlon clubs across the United States via an soliciting participation from their members. In order to increase the likelihood of a response, each individual club president was sent a separate . The message included a personalized message to that specific club. This was done in order to reduce the appearance of a mass and insure maximum participation. Initial response rates to the first survey numbered 791 with 632 respondents fully completing all items to include the address and next event date. This information was, of course, critical for the distribution of the second survey link. As most triathlon events are scheduled for weekends the researcher ed a link to the second survey within 24 to 48 hours of completion of the event. For example, if a person indicated that her next event was on June 18 th,an was sent no later than June 20 th containing the link to the second online survey. Each respondent to survey 1 was individually ed with a reminder of the id code that was inputted in the first survey. A total of 493 s were sent to respondents to the first survey. Participants completed online surveys at two different time points. Each survey s basic structure is depicted in Table 3.1. The survey completed at the first time point included items pertaining to basic demographic information (e.g., gender, age), triathlon experience (i.e., type, amount), and two measures that assess motivation and passion as well as the Leisure-Time Exercise Questionnaire (LTEQ; Godin & Shephard, 1985). Data obtained at Time one were examined to answer the second set of research questions. Self-reported exercise bouts as well as MET scores were compared according to passion type. It was hypothesized that individuals who participate in multiple half-ironman and ironman competitions have either a higher MET score or report more individual bouts of exercise than those who only participate in sprint or Olympic 53

64 distance triathlons. It was also hypothesized that those individuals with higher MET scores and/or more bouts of exercise will show a greater tendency to be obsessively passionate. Data were also collected immediately following a recent but subsequent competition via a second online survey. Participants indicated their next race type and date in response to items 56 and 57 (See Table 3.2) in survey 1. Based on this information the second survey link was ed to the participant. Motivation at the situational level, coping strategies, goal attainment as well as planned future event participation was collected at Time 2. Due to an error in survey generation, one item was inadvertently left off of the survey: ID3 (because of the benefits of my sport). This item is very similar in wording to ID1 (because the benefits of sport are important to me). Results from this data set as well as from Time 1 were used to test the model depicted in Figure 2.3. In order to prevent participant survey burden, passion was not assessed at Time 2. An additional note, passion, as a construct was not expected to change from Time 1 to Time 2 due to its contextual nature. Situational motivation was assessed at Time 2 in order to compare to contextual motivation at Time 1. Vallerand (2007), in Corollary 3.3 of his hierarchical model states that higher levels of motivation may influence lower levels. However, differences in intrinsic and extrinsic motivation may exist between levels. At the contextual level a person may be highly self-determined to compete in triathlons in general, but at the situational level this person may only truly be self-determined to participate in the elements that he or she is competent in (e.g. biking and running). This person may be externally motivated to complete the swim portion of the event while intrinsically motivated to complete the bike and run portions. It is impossible to tease out this distinction however a change in overall intrinsic or extrinsic scores could indirectly indicate this. The time gap between assessments was similar to the one used in previous research (i.e., Amiot, Gaudreau, & Blanchard, 2004; Gaudreau & Antl, 2008). In both of these studies the researchers assessed motivation before a competition and goal attainment and coping immediately after competition. Vallerand et al. (2003) assessed future intentions on two separate occasions when developing the passion scale. It was expected that if a person achieves positive goal attainment, future intentions will remain constant or that person will plan to run in even more events. 54

65 Data Analysis Microsoft Excel, SPSS version 16.0 and MPLUS version 6 were used to analyze the data. Basic descriptive statistics were obtained using SPSS. Statistical analyses included, ANOVA, Bivariate correlations, Confirmatory Factor Analysis (CFA), and Structural Equation Modeling (SEM). In path analysis, SEM, and CFA, a non-significant 2 indicates a good fit to the data (Kline, 2005). Rules of thumb indicating a relatively good fit are CFI >.95, TLI >.95, RMSEA <.06, and SRMR <.08 (Hu & Bentler, 1999). Additionally, Kline (2005) indicates that an SRMR <.10 is considered favorable. Any respondents who failed to complete the surveys or entire portions of the measures were eliminated from the analysis. In order to reduce sampling error and produce reasonably stable results, the desired sample size was based on recommendations from Kline (2005) and calculated two separate ways. The first method was based on the ratio of cases to free parameters in the model. This is for the structural component of the model only. Ratios of 20:1 or 10:1 were used, with the latter being more realistic based on the complexity of the model. The number of free parameters as depicted in the model in Figure 2.3 is 25. Based on these ratios the sample size was targeted to be between 500 and 250 participants. A second method, based on power, was also utilized. Power is the probability of rejecting the null hypothesis when in fact it should not be rejected. MaCallum, Browne, and Sugawara (1996) proposed another approach to power analysis based on RMSEA ( ) and non-central 2 distribution. A web based computer program ( was used to generate the sample sizes needed to achieve a power of.5 and.8. A power of.8 is more desirable, however, often a power of.5 is more probable in the behavioral sciences (Kline, 2005). This web-based program was utilized to generate the syntax for both powers at.05 and.08, which was used in the R project. It requires the following information to generate the syntax: df, level, desired power, RMSEA (H o ), and RMSEA (H 1 ). Code was generated for each of the two power levels (.5 and.8) using df = 25 =.05, RMSEA (H o ) 0 =.05 and RMSEA (H 1 ) 1 =.08. The syntax was input into R and yielded sample size requirements of 277 and 550, for power =.5 and.8 respectively. Again the degrees of freedom were based on the structural portion of the model and not the full measurement model. Based on the above calculations a sample size varying from 250 to 550 individuals was targeted. 55

66 MANOVA and multiple ANOVAs were used to compare groups of people on variables. The variables depicted in Table 3.3 were used to answer research question 2. Each of the variables listed were compared with respect to weekly reported exercise bouts as well as MET score. Measurement reliability and structural validity were assessed via SPSS version 16.0 and MPLUS version 6. The data s reliability was calculated using SPSS. The results were compared to previously reported values. Cronbach s alpha was calculated for each scale as well. Confirmatory factor analyses were used to assess each individual measure s model fit via MPLUS and compared to previously reported values. Table 3.3 Explanation of Variables for Comparison and Categorization Variable Name (Label) Description Indicator IRONMAN (Triathlete) An individual who has never run an Ironman 0 (Limited Ironman) An individual who has run 1 to 2 Ironman Triathlons 1 (Ironman) An individual who has run 3 or more Ironman 2 PASSNTYPE4 (HPP) (HPP) (OPP) A person who scored an average of 4 or higher in Harmonious Passion scale but averaged lower than 4 in Obsessive Passion A person who scored an average of 4 or higher in Harmonious Passion and Obsessive Passion A person who scores an average of 4 or higher in Obsessive Passion but averaged lower than a 4 in Harmonious Passion Note: PASSNTYPE = Passion type; HPP = Harmonious passion; OPP = Obsessive passion During the course of SEM analyses, model fit problems became evident. A systematic approach was used to determine which subscales contributed to poor model fit. First the BRSQ was parceled based on Lonsdale et al. (2009). Next a step-by-step analysis of the CICS was performed. The CICS had several subscales and items that appeared to be contributing to the model s poor fit to the data. In order to improve model fit, a construct-by-construct analysis of the CICS was conducted to reveal which subscales were problematic, and additionally which particular items were problematic. In step 1, each subscale was analyzed separately to identify 56

67 problematic items. In step 2, pairwise combinations of subscales were conducted to indicate exactly which subscales were contributing to poor data fit. Step 3 involved building the measurement model of the CICS, subscale by subscale, and compared model fit between those subscales with and without problematic items by CFA. Items determined to be problematic were omitted. Finally, the CICS was parceled. The process is further discussed in the Results section. A statistical reason for parceling, as summarized in Little, Cunningham, Shahar and Widaman (2002), is that the parceled model is more parsimonious, reduces the likelihood of correlated residuals or dual loadings, and reduces sources of sampling error. Due to the relatively small sample size for the relatively large model and in order to analyze the data via SEM, a reduction in the complexity of the model was required. Items were parceled in order to reduce the complexity of the model and as a result model fit was improved. 57

68 CHAPTER 4 RESULTS Means, standard deviations, minimums, maximums and subscale reliability for the BRSQ and Passion scale from the first survey are shown in Table 4.1. Cronbach s alphas for each of the subscales in the BRSQ were lower than published reliability estimates (Lonsdale et al., 2008). Identified regulation s alpha was.69, where Lonsdale and his colleagues reported an alpha of.77. The intrinsic motivation subscale exhibited the highest Cronbach s alpha (.86), which was nearly identical to Lonsdale s study (.85) in The Cronbach s alphas for harmonious and obsessive passion (.83 and.84, respectively) were similar to those published by Vallerand et al. (2006). Table 4.1 Means, Standard Deviations, Minimums, Maximums, and Cronbach s for the BRSQ Subscales, and Passion Scales N Minimum Maximum M SD Intrinsic motivation Integrated regulation Identified regulation Introjected regulation External regulation Amotivation Harmonious Passion Obsessive Passion Note: N = sample size, BRSQ = Behavioral Regulation in Sport Questionnaire Table 4.2 depicts means, standard deviations, minimums, maximums and subscale reliability at Time 2 for situational BRSQ, the CICS, and A-SAGS. The reliability coefficients for the BRSQ subscales assessing situational motivation improved slightly over those from the first survey. There were no meaningful changes in observed internal consistency across the two 58

69 time points. Intrinsic motivation had the highest reliability at.91. The CICS alphas were higher or the same as those published by Gaudreau and Blondin (2002) with the exceptions of thought control (.64), logical analysis (.56), and distancing (SW;.49) which were lower. Table 4.2 Means, Standard Deviations, Minimums, Maximums, and Cronbach s for the Situational BRSQ Subscales, CICS and A-SAGS N Minimum Maximum M SD Intrinsic motivation Integrated regulation Identified regulation Introjected regulation External regulation Amotivation Mental imagery Effort expenditure Thought control Relaxation Logical analysis Seeking support Distancing (SW) Mental distraction Disengagement Venting Mastery goal Self-improvement goal Performance goal Note: N = sample size; BRSQ = Behavioral Regulation in Sport Questionnaire; SW = Social Withdrawal A possible explanation for the low reliability on these subscales could be that this measure was translated in into English from French and published coefficients were for the French version. Items within these subscales were revealed to be problematic and are discussed 59

70 further in the results section. The A-SAGS subscale reliability coefficients were all acceptable and similar to those published by Gaudreau and Amiot (2008). Table 4.3 Summary of Intercorrelations for Subscales of BRSQ and Passion Scale Non-self-determined Self-determined Subscale AM EX IJ ID IG IM HP OP AM EX.40** IJ.38**.44** ID -.11** ** IG -.10* *.48** IM -.40** -.17** -.17**.38**.46** HP -.25** -.11** **.59**.47** OP.12**.15**.26**.17**.36**.23**.22** Note: n = 624, BRSQ = Behavioral Regulation in Sport Questionnaire; AM = Amotivation; EX = External Regulation; IJ = Introjected Regulation; ID = Identified Regulation; IG = Integrated Regulation; IM = Intrinsic Motivation; HP = Harmonious Passion; OP = Harmonious Passion. *p <.05, **p <.01, Table 4.3 above depicts the bivariate correlations between the BRSQ and passion subscales. Significant correlations existed ( <.01 or <.05 levels) among all of the subscales except three. All of the non-self-determined variables were significantly and moderately (.38.44) correlated with one another. Likewise the three self-determined subscale variables were also significantly and moderately (.38.48) correlated. Harmonious passion was moderately positively correlated with the self-determined subscales of IM, IG, and ID (.47.59) and negatively correlated with the non-self-determined subscales of IJ, EX, and AM ( ), but only significantly with AM (r = -.25) and EX (r = -.11). Obsessive passion was positively 60

71 correlated with all the subscales of the BRSQ though weakly, the strongest being.36 with IG. The harmonious and obsessive passion subscales were correlated significantly (r =.22, p <.01 level. Due to the large sample size many weak correlations (.1 and lower) were significant. The following analysis did not pertain to a particular hypothesis. A MANOVA was run with SPSS version 16 software looking for any interactions between Self-identified level of participation, gender, and Ironman participation. Dependent variables were total events, the LTEQ scores, MET scores, harmonious and obsessive passion with years of experience and age as covariates. The only significant interactions were Gender by Ironman, while self-identified participation level (Trilevel) by Gender by Ironman approached significance (p =.061). Results are depicted in Appendix A. Follow up ANOVAs revealed with respect to Gender by Ironman the only significant differences existed on the dependent variable Total Events, F(2,573) = , p <.001, partial 2 p =.065. Of the 290 women who responded 36 (12%) had participated in 1 Ironman competition while only 15 (5%)had competed in 2 or more Ironman competitions. Of the 323 men who responded 65 (20%) had participated in 1 Ironman competition and 34 (11%) had participated in more than 2 Ironman competitions. Women on average participated in around 16 events while men participated in 24. The difference in total events run existed between women who had run more than 2 Ironman competitions and men who had run more than 2 Ironman competitions. Several one-way ANOVAs were run to examine potential differences in passion with respect to gender, and self-identified level of participation. While these analysis do not directly answer the research questions they do offer some insight to the population studied. Multiple ANOVAs by gender were performed and showed a significant difference between men and women in the following variables: Men had higher means on years of triathlon experience F(1,610) = 10.31, p =.001, 2 p =.017, Cohen s d = 0.26, total events completed F(1,611) = 12.86, p <.001, 2 p =.021, Cohen s d = 0.29, future planned events F(1,611) = 13.62, p <.001, 2 p =.022, Cohen s d = 0.31, and Ironman competitions completed F(1,611) = 6.65, p =.01, 2 p =.011, Cohen s d = Women averaged higher then men in obsessive passion F(1,609) = 15.46, p <.001, 2 p =.025, Cohen s d = Strenuous activity as determined by 2 answering the first question of the LTEQ approached significance, F(1,601) = 3.46, p =.06, p =.006, Cohen s d = 0.15, with men having the higher mean. There was no significant difference 61

72 between men and women on harmonious passion, MET scores, age, or any of the SDT motivation categories. All means and standard deviations can be found in Table 4.4. Table 4.4 Range, Mean, Standard Deviations, and Cohen s d for Age, Years of Experience, Ironman s Completed, Strenuous Physical Activity, Metabolic Equivalent, Total Triathlons, and Passion Based on Gender Women Men Range M (SD) Range M (SD) Cohen s d Age (years) (11.85) (11.97) 0.12 Years of experience (4.76) (6.87) 0.26 Total triathlons (19.87) (34.65) 0.29 Ironman distance completed (1.41) (1.92) 0.21 LTEQ Strenuous (2.96) (3.46) 0.15 MET (31.14) (39.33) 0.12 Total Future planned events (2.86) (2.90) 0.31 Harmonious Passion (0.57) (0.93) 0.50 Obsessive Passion (1.33) (1.25) 0.43 Note: LTEQ = Leisure Time Exercise Questionnaire; MET = Metabolic Equivalent Score Table 4.5 Means and Standard Deviations for Age, Years of Experience, Total Events, Ironman Triathlons and Planned Future Triathlons Based on Self-Identified Participation Level Self-labeled Triathlete category Age Years of Experience M (SD) Total events Ironman Triathlons M (SD) Future Triathlons M (SD) M (SD) M (SD) Professionals (n=5) 24 (3.24) 5.8 (3.42) (15.76) 0 (0) (1.51) Competitive (n=275) 37 (12.13) 7.16 (6.96) (35.81) 1.09 (2.24) 6.93 (2.95) Recreational (n=276) 39 (11.13) 4.71 (4.83) (19.99) 0.41 (1.24) 4.92 (2.37) Fitness (n=55) 40 (13.43) 3.97 (5.02) 9.91 (12.64) 0.09 (0.44) 3.98 (2.39) Other (n=10) 34 (11.27) 2.34 (1.26) 6.00 (4.49) 0 (0) 3.40 (2.55) Note: Means with standard deviation in parentheses Out of the 622 individuals who responded to the first part of the survey, five identified themselves as professional triathletes, 275 as competitive triathletes, 276 as recreational triathletes, 55 as purely for fitness triathletes, and 10 as other. Table 4.5 depicts means and standard deviations for age, years of experience, total events, Ironman triathlons completed, and 62

73 future total events. The same information for harmonious and obsessive passion, LTEQ scores and MET scores are depicted in Table 4.6. Multiple ANOVAs were performed to identify any significant differences on the dependent variables based on self-labeled triathlon experience. Significant age, years of triathlon experience, total events, Ironman triathlons, total planned future triathlons, harmonious and obsessive passion, LTEQ 1 Strenuous, and MET scores differences were noted. Due to the uneven number of participants in each classification, Levene s test was employed to determine any violation of the assumption of homogeneity for each variable in the ANOVA. In the event of a violation in homogeneity a Welch s adjustment was used to determine differences among groups. Those variables requiring the Welch s adjustment were age, years of experience, total events, total Ironman events, total planned future triathlons, obsessive passion, LTEQ 1 strenuous, LTEQ 2, and MET scores. A significant mean age difference among groups was obtained, F(4,24.19) = 20.67, p <.001, 2 p =.02. A Tukey s post hoc test indicated a difference between the professional and recreational triathletes (p =.05, Cohen s d = 1.31) purely for fitness triathletes (p =.03, Cohen s d = 1.26). In both cases the mean age of fitness (M = 40) and recreational triathletes (M = 39) were greater than professional triathletes (M = 24). In addition a significance difference among groups in years of triathlon experience was obtained, F(4,24.56) = 16.27, p <.001, 2 p =.05. A Tukey s post hoc test indicated a difference between competitive and fitness triathletes (p =.002, Cohen s d = 0.48), and between competitive and recreational triathletes (p <.001, Cohen s d = 0.41). There was no difference between recreational and fitness triathletes based on years of experience. Competitive triathletes had significantly more years of experience (M = 7.16 years) than fitness triathletes (M = 3.97 years) and recreational triathletes (M = 4.71 years). A significant difference also existed in total events, F(4,25.15) = 23.13, p <.001, 2 p =.085, and planned future events F(4,22.01) = 38.10, p <.001, 2 p =.37 among groups. A Tukey s post hoc test indicated that competitive triathletes have participated in more total events (M = years) than recreational triathletes (M = years, p <.001, Cohen s d = 0.53) and fitness triathletes (M = 9.91 years, p <.001, Cohen s d = 0.58). The Tukey s post hoc test revealed that there was a difference in future events planned between professional triathletes and competitive (p =.02, Cohen s d = 1.25), recreational (p <.001, Cohen s d = 2.41), fitness (p < 63

74 .001, Cohen s d = 2.83), and other (p <.001, Cohen s d = 3.16) triathletes. There was also a difference between competitive and recreational triathletes (p <.001, Cohen s d = 0.75), fitness (p <.001, Cohen s d = 1.03), and other triathletes (p <.001, Cohen s d = 1.20). On average professional triathletes plan to run in around 10 events in the next 12 months, competitive triathletes around 7, recreational triathletes just around 5, with fitness and other triathletes close to 4. Actual means and standard deviations are depicted in Table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difference between groups was also noted in the amount of Ironman triathlons reported, F(4,618) = 7.74, p <.001, 2 p =.05. The Welch s adjustment was not performed due to the fact that one of the groups, Professionals, had variance of 0.0, and was removed from analysis. The original ANOVA F statistic was used with respect to the remaining groups. Tukey s post hoc tests showed a difference between competitive triathletes and recreational (Cohen s d = 0.38) as well as fitness triathletes (Cohen s d = 0.49). Means were 1.09, 0.41 and 0.09 for competitive, recreational, and fitness triathletes respectively. None in the professional or other group reported participating in an Ironman triathlon. However, there were only 5 individuals who identified themselves as professionals. A significant difference among groups existed in harmonious passion, F(4,614) = 7.87, p <.001, 2 p =.05. A Tukey s post hoc test indicated that competitive triathletes (M = 5.53) were higher than recreational (M = 5.28) and fitness triathletes (M = 4.80) on harmonious passion scores (p <.01, Cohen s d = 0.27, and p <.001, Cohen s d = 0.79, respectively). Additionally, 64

75 there was a statistical difference in harmonious passion scores between recreational and fitness triathletes (p =.004, Cohen s d = 0.50) with recreational triathletes scoring higher. A significant difference among groups on the other dimension of the passion scale, obsessive passion, was also noted, F(4,21.49) = 19.23, p <.001, 2 p =.11. Professional triathletes scored higher (M = 3.97) than recreational (M = 2.32) and fitness triathletes (M = 1.85), but not competitive triathletes (M = 2.99). Competitive triathletes scored significantly higher than both recreational triathletes and fitness triathletes. Recreational triathletes scored significantly higher than fitness triathletes. Table 4.7 shows the respective statistics of the Tukey s post hoc tests as well as the means, standard deviations, and effect sizes. While none of the respective means are above 4, it is interesting to note that triathletes who label themselves as more competitive exhibit more of a tendency to be obsessively passionate toward the activity and have very strong effect sizes. Table 4.7 Obsessive Passion Post Hoc Statistics, Means, Standard Deviations and Effect Size Group Tukey s p- Cohen s d value Professional (M = 3.97 SD = 1.43) Recreational (M = 2.32 SD = 1.09) Fitness (M = 1.85 SD = 0.92) Competitive (M = 2.99 SD = 1.24) Recreational (M = 2.32 SD = 1.09) < Fitness (M = 1.85 SD = 0.92) < Recreational (M = 2.32 SD = 1.09) Fitness (M = 1.85 SD = 0.92) Finally, Table 4.8 depicts the post hoc statistics among groups on the variables LTEQ strenuous and MET scores. LTEQ strenuous scores were significantly higher in Professionals, followed by Competitive, and then Recreational Triathletes, F(4,17.42) = 9.81, p <.001, 2 p =.087 as were MET scores F(4,17.46) = 8.76, p <.001, 2 p =.071. Professionals significantly differed from competitive (d = 1.47), recreational (d = 2.73), fitness (d = 1.96) and other triathletes (d = 1.56) on LTEQ strenuous scores as well as MET scores. Competitive triathletes differed from both recreational (d = 0.53) and fitness triathletes (d = 0.50) on both LTEQ strenuous and MET scores as well. 65

76 Table 4.8 Significant LTEQ Strenuous and MET Tukey Post Hoc Statistics, Means, Standard Deviations and Effect Size in Triathlete Groups Group Tukey s p-value LTEQ Strenuous Professional (M = SD = 6.98) Competitive (M = 6.65 SD = 3.58) Recreational (M = 5.03 SD = 2.43) < Fitness (M = 4.89 SD = 3.25) < Other (M = 4.80 SD = 3.01) Competitive (M = 6.65 SD = 3.58) Recreational (M = 5.03 SD = 2.43) < Fitness (M = 4.89 SD = 3.25) MET Professional (M = SD = 48.77) Competitive (M = SD = 39.20) Recreational (M = SD = 28.50) Fitness (M = SD = 36.58) Other (M = SD = 37.81) Competitive (M = SD = 39.20) Recreational (M = SD = 28.50) < Fitness (M = SD = 36.58) Note: LTEQ = Leisure time exercise questionnaire; MET = Metabolic Equivalent Score Cohen s d Research Question 1 The first research question was: Is a person who competes regularly in Ironman triathlons more likely to demonstrate obsessive or harmonious passion? And is the amount of self-reported training different among the two passion types? Do obsessively passionate people train more than those who demonstrate harmonious passion? In order to answer the first research question participants were classified into 3 separate groups based on Ironman Triathlon participation. Individuals who self-reported never having run an Ironman triathlon were classified into the Triathlete group of which there were 467. Individuals who reported having competed in 1 or 2 Ironman triathlons were classified as Ironman, and individuals who reported competing in 3 or more events were classified as Sustained Ironman, and numbered 103 and 50 respectively. Multiple One-way ANOVAs were performed to determine any differences among these three classifications on the following variables: Harmonious Passion, Obsessive Passion, MET score, years of experience, total events, and LTEQ scores. Table 4.11 depicts the means and standard deviations for these variables across each classification. 66

77 Table 4.9 ANOVAs by Ironman Participation for the Variables Harmonious and Obsessive Passion, and LTEQ 2 scores. df F p 2 p HP 2, OP 2, LTEQ1mild 2, Note: HP = Harmonious Passion; OP = Obsessive Passion; LTEQ = Leisure Time Exercise Questionnaire; p 2 = partial eta squared. Due to the uneven number of participants in each classification Levene s tests were performed to detect any violation of the assumption of homogeneity for each variable in the ANOVA. The following variables violated that assumption based on the Levene s statistic: MET, LTEQ Moderate, Strenuous, and LTEQ2, years of experience, and total events. As a result, the Welch s adjustment statistic was used to perform the ANOVA for these variables. The ANOVAs and Welch s adjustment statistics are depicted in Tables 4.9 and There was a significant difference among groups on both passion variables, HP, OP, MET scores, LTEQ moderate, LTEQ strenuous, LTEQ2, years of experience, and total events. Table 4.10 Robust Tests of Equality of Means Statistic a s ws p 2 p MET Welch > YXP Welch > Events Welch > LTEQ1str Welch > LTEQ1mod Welch LTEQ2 Welch Note: a. Asymptotically F distributed; MET = Metabolic Equivalent Score; YXP = Years of triathlon experience; Events = Total events run; LTEQ = Leisure Time Exercise Questionnaire; str = Strenuous; mod = moderate; 2 p = partial eta squared. 67

78 Table 4.11 Mean, Standard Deviations for Passion Type, Metabolic Equivalent, LTEQ Mild, Moderate and Strenuous Physical Activity, Years of Experience and Total Triathlon Events based on Ironman Participation. Triathlete Ironman Sustained Ironman Variable M SD M SD M SD HP OP MET LTEQ Mild LTEQ Moderate LTEQ Strenuous LTEQ YXP Total Events Note: HP = Harmonious Passion; OP = Obsessive Passion; MET = Metabolic Equivalent Score; YXP = Years of triathlon experience; LTEQ = Leisure Time Exercise Questionnaire A Tukey s Post Hoc test was performed along with the One-way ANOVAs to determine which groups were different on each variable. Results are depicted in Table Ironmen differed from Triathletes with a higher mean on harmonious passion, Cohen s d = Sustained Ironmen had higher MET scores than Triathletes, Cohen s d = 0.81, and Ironmen had higher MET scores than Triathletes, Cohen s d = Sustained Ironmen had higher LTEQ strenuous scores than Triathletes, Cohen s d = 0.76, and Ironmen had a Higher LTEQ strenuous scores than Triathletes, Cohen s d = Sustained Ironmen had higher LTEQ moderate scores than Triathletes, Cohen s d = Sustained Ironmen had more years of triathlon experience than Ironmen, Cohen s d = 1.02, and Triathletes, Cohen s d = 1.94, while Ironmen had more years of triathlon experience than Triathletes, Cohen s d =

79 Table 4.12 Post Hoc Statistics and Effect Sizes for Harmonious and Obsessive Passion, Metabolic Equivalent, LTEQ Moderate and Strenuous Physical Activity, Years of Experience and Total Triathlon Events based on Ironman Participation. Variable Comparison Groups Tukey s p-value Cohen s d HP Triathlete and Ironman MET Triathlete and Ironman < Triathlete and Sustained Ironman < LTEQ Strenuous Triathlete and Ironman < Triathlete and Sustained Ironman < LTEQ Moderate Triathlete and Sustained Ironman Years of Triathlon Triathlete and Ironman < Experience Triathlete and Sustained Ironman < Ironman and Sustained Ironman < Total Events Triathlete and Ironman < Triathlete and Sustained Ironman < Ironman and Sustained Ironman < OP Triathlete and Ironman Triathlete and Sustained Ironman Ironman and Sustained Ironman Note: HP = Harmonious passion; LTEQ = Leisure time exercise questionnaire; MET = Metabolic Equivalent Score Sustained Ironmen had participated in more total triathlon events experience than Ironmen, Cohen s d = 1.07, and Triathletes, Cohen s d = 2.11, while Ironmen had participated in more total events than Triathletes, Cohen s d = While the ANOVA indicated that there was a difference between groups on the OP variable, the Tukey s post hoc test did not indicate a significant difference between groups. A visual inspection of the means revealed that Sustained Ironmen had the highest mean at 2.88, followed by Ironmen at 2.80, and Triathletes at 2.52, however the effect size, measured by Cohen s d, between groups did not exceed A comparison among groups on passion types was originally planned. Comparison of several variables based on a dichotomized passion scale had been intended by comparing those who scored higher than a 4 on the HP with those who scored higher than a 4 on obsessive passion. However, due to the nature of the data such a dichotomization was not possible. While 575 scored a 4 or higher on the harmonious passion subscale only 94 out of 622 individuals 69

80 scored a 4 or higher on obsessive passion. Also of note is that only 91 of those individuals who scored a 4 or higher on obsessive passion also scored higher than a 4 on the harmonious passion subscale leaving only 3 individuals who averaged above a 4 on obsessive passion and below a 4 on harmonious passion. Therefore a comparison of those individuals high in harmonious and those high in obsessive passion was not possible. Forty-seven individuals out of the sample scored lower than a 4 on both scales. As a result of this occurrence the participants were divided into three separate groups: those who scored higher than a 4 in harmonious passion, those who scored higher than a 4 in both harmonious and obsessive passion, and those who scored a 4 or higher only on obsessive passion. Based on several one way ANOVAs the three groups only differed on LTEQ strenuous F(2,562) = 3.03, p =.049, 2 p =.01. This did not require a Welch s adjustment. A Tukey s post-hoc test revealed a difference in LTEQ 1 Strenuous between those who scored high only in harmonious passion (M = 5.71) and those who scored high in both harmonious and obsessive passion (M = 6.58) with an effect size of Cohen s d = There was no difference between those who scored high in harmonious passion only or those who scored high in obsessive passion only. Research Question 2 To test the hypothesis for research question 2 confirmatory factor analyses (CFA) were performed on the passion scales, BRSQ, CICS and A-SAGS utilizing the 299 participants who completed both parts of the survey followed by structural equation modeling which tested the model depicted in Figure 2.3. A two-factor CFA was performed on the passion scale, with harmonious passion (HP) and obsessive passion (OP) representing the two factors. The model resulted in a poor fit to the data, 2 df = 53, n = 299 = , p <.001, and fit indices of CFI =.86, TLI =.83, and RMSEA =.112. The only fit index that indicates a good fit is the SRMR =.07 which also was the only one that matched that reported by Vallerand et al. (2006). Standardized factor loadings for all the items ranged from.591 to.837. An additional CFA, which allowed item residuals within each subscale to covary improved the CFA to indicate a good fit, 2 df = 45, n = 299 = 89.28, p =.0001, and fit indices of CFI =.97, TLI =.96, and RMSEA =.057, SRMR =.056. Only those items residuals recommended by the Mplus software modification indices were included. This would indicate that some of the unexplained variance was shared across items. 70

81 A 6-factor CFA was performed on the BRSQ (Lonsdale et al., 2008) with IM, IG, ID, IJ, EX, and AM as the 6 factors. The model resulted in a reasonably good fit to the data with 2 df = 215, n = 299 = , p <.001, and fit indices of CFI =.94, TLI =.93, RMSEA =.06, and SRMR =.05. The 2 was significant (hence indicating model misfit to the data), but both the RMSEA and SRMR indicated a good fit to the data, and the CFI and TLI results were very close to the rule of thumb cut off of.95. Standardized factor loadings for the items ranged from.631 to.879. Due to an error in survey generation, one item was inadvertently left off of the survey: ID3 (because of the benefits of my sport). This item is very similar in wording to ID1 (because the benefits of sport are important to me). Factor loadings for items ID1, ID2, and ID4 were.599,.698, and.699, respectively. A 10-factor CFA was performed on the CICS (Gaudreau & Blondin, 2002) as well. The factors included MI, EE, TC, R, LA, SS, SW, MD, D, and VE. Some fit indices indicated a poor model fit to the data, 2 df = 657, n = 299 = , p <.001, CFI =.86, TLI =.85, while others indicated a reasonable to good fit, RMSEA =.05, SRMR =.07. Factor loadings for the items on the CICS ranged from.071 to.870. Those items with factor loadings under.50 were TC1(.404; I tried not to be intimidated by other athletes) and TC4 (.342; I tried not to think about my mistakes), LA3 (.260; I thought about possible solution in order to manage the situation), SW1 (.100; I kept my distance from other athletes) (Note: this item had been modified from the original translation of I took my distance from other athletes), and SW4 (.071; I searched for calmness and quietness). The two most problematic items with respect to factor loadings were those having to do with distancing or social withdrawal. It is possible the wording of item SW1 was confusing and therefore resulted in the low factor loading. This confusion most likely was a result of the translation from French to English, even with the modification made for this study. The English translation of Item SW4 would likely be better suited to the coping mechanism of relaxation. Although modification indices in the Mplus output supported this contention, this item did not significantly load onto the relaxation factor when tested. As a result, the item remained as an indicator of SW when tested in the full model. Further CFA were run with the CICS as to address the problematic areas of the measure and are discussed in detail later. A 3-factor CFA was performed on the A-SAGS (Gaudreau et al., 2002). While the 2 was significant ( 2 df = 51, n = 299 = , p <.001) and RMSEA was.081, other fit indices indicated a good fit to the data. Fit indices that indicated a good fit were CFI =.96 and SRMR = 71

82 .05. The TLI was just below the rule of thumb indicator of.95 at.94. Factor loadings ranged from.563 to.858. Structural Equation Modeling was also performed using the Mplus statistical software. Model 1 (depicted in Figure 2.3) tested the second research question on whether harmonious and obsessive passions differ on predicting situational motivation and coping strategies, and whether motivation acts as a mediator between passion and coping strategies. The model also tested whether coping strategies act as mediators between motivation and goal attainment and future intentions. Initial model testing included direct paths from harmonious and obsessive passion to self-determined, and non-self-determined motivation and from self-determined and non-selfdetermined behavior toward TOC, distraction-oriented coping, and disengagement-oriented coping. Paths from each of the coping variables to both goal attainment and future events were also included in the model. Additionally, a direct path from goal attainment toward future events was also included. Some fit indices indicated a poor model fit to the data 2 df = 3637, n = 299 = , p <.0001, CFI =.59, and TLI =.58, while some indicated a reasonable model fit to the data, RMSEA =.072; SRMR =.098. The model s factor loadings are depicted in Figure 4.1. All path coefficients are standardized. Due to the poor fit of the model it was inappropriate to modify the pathways of this model. 72

83 Contextual Situational ** HP OP.674** ** SDM.198** -.311** NSDM.497**.155* ** TOC.84 DTOC.387**.162* **.028 Goal Attain.049 Future intentions ** DNOC Figure 4.1. Model 1 integrating passion, motivation, and coping on goal attainment and future intentions to run triathlons including pathway coefficients. HP = harmonious passion; OP = obsessive passion; SDM = self-determined motivation; NSDM = non-selfdetermined motivation; TOC = task-oriented coping; DTOC = distraction oriented coping; DNOC = disengagement-oriented coping; Goal Attain = goal attainment. * p <.05, ** p <.01 73

84 Contextual Situational ** HP OP **.23 SDM **.536**.194** * TOC.84 DTOC.383**.389**.468**.261* *.422** Goal Attain.023 Future intentions ** NSDM ** DNOC **.79 Figure 4.2. Model 1.2 with modification indices integrating passion, motivation, and coping on goal attainment and future intentions to run triathlons including pathway coefficients. HP = harmonious passion; OP = obsessive passion; SDM = self-determined motivation; NSDM = non-self-determined motivation; TOC = task-oriented coping; DTOC = distraction oriented coping; DNOC = disengagement-oriented coping; Goal Attain = goal attainment. * p <.05, ** p <.01 74

85 The Mplus output included modification indices of pathways to add in order to improve model fit. These recommended pathways were added to Model 1 syntax and the model was rerun in Mplus. Modifications that were in line with theoretical conceptualization included allowing the disturbances of self-determined motivation to covary with non-self-determined motivation, also allowing the coping variables disturbances to covary with each other. The model fit showed little improvement, and still indicated a poor fit to the data, 2 df = 3633, n = 299 = , p <.0001, CFI =.59, TLI =.58, RMSEA =.071 and SRMR =.085. Path coefficients are depicted in Figure 4.2. Again due to poor model fit further empirical testing of the model was needed starting with a systematic examination at each individual measure. To re-test the model individual measures were analyzed to determine which subscales were contributing to the model s poor fit to the data. Based on recommendations from Hodge et al. (2011) and Lonsdale et al. (2009) the items from the BRSQ were weighted into four items to create two new motivation factors, autonomous motivation (AuM) and controlled motivation (CoM). These two factors (or latent) variables replaced the self-determined and non-selfdetermined motivation variables in the original model. For autonomous motivation each individual IM item score was doubled and then added to the IG and ID score. For example Intrinsic motivation item 1 was doubled and added to integrated regulation item1 and identified regulation item 1 to form a new indicator labeled autonomous motivation item 1, [(IM1 2 ) + IG1 +ID1] = AuM1. For controlled motivation External Regulation and Introjected regulation were each doubled and added, [(EX 2) + (IJ1 2)] = CoM1. The amotivation items were not used in creating the four new indicators labeled CoM as amotivation is not a form of regulation. Weighting the items in this way creates a self-determination index to better understand the entire range of regulation (Lonsdale et al., 2009). The result was that each factor has only four parceled indicators compared to the prior model where the self-determined motivation and nonself-determined motivation variables had 12 individual items. A CFA on the new parceled BRSQ was performed revealing fit indices that indicated a good fit of the model to the data, 2 df = 19, n = 299 = 35.30, p =.013, CFI =.99, and TLI =.98, RMSEA =.053, SRMR =.028. Following the CFA a SEM procedure for model 1.3 was performed. This consisted of replacing the selfdetermined motivation factor with autonomous motivation and the non-self-determined motivation factor with controlled motivation utilizing the now parceled indicators. The model fit the data better than previous models, but still overall model fit to the data was poor. The 2 75

86 statistic was significant, 2 df = 2370, n = 299 = , p <.000,1 and CFI =.88 and TLI =.87, did not indicate a good fit to the data. The RMSEA indicated a good fit to the data, RMSEA =.043 and the SRMR =.081 indicated a reasonable fit. Based on factor loadings of items in the CICS, its items and subscales were further examined via CFA. Each subscale in the CICS was analyzed in Mplus to determine which items and subscales were the most problematic possibly contributing to the poor model fit to the data. A systematic approach was implemented. First, each subscale was modeled to determine which items were contributing to poor model fit. Those subscales with problematic items were TC, LA, and SW (Distancing). Those items with small factor loadings were removed to see if the other items factor loadings increased. Items that were removed were TC4, LA3, and SW3. Independently from the above analysis, pairwise analyses were run in Mplus to determine problematic subscales and items. All subscales were paired together and considered as two factor CFAs including all items for each subscale. For example MI and EE where run in a twofactor CFA, then MI and TC, and so forth. Fit indices and item loadings were considered in the determining which subscale and/or items were problematic. Uniformly the distancing subscale (SW) showed poor fit whenever paired with another subscale from the CICS. Other subscales that showed poor fit but to a lesser degree were TC and LA. Table 4.13 depicts the fit indices for each pairwise analysis of SW and the other CICS subscales. Other pairwise fit indices are not depicted. Following the pairwise analyses the subscales were added one by one to the measurement model in order to determine where model fit began to degrade according to the fit indices. After each model was tested, fit was assessed and another factor was added. For example, model fit was assessed with a three factor model including the subscales of MI, EE, and R yielding 2 df = 41, n = 299 = 47.21, p =.2339, RMSEA =.02, CFI =.99, TLI =.99, SRMR =.04. All fit indices indicated a good fit of the model to the data; therefore another factor (SS) was then added to the model and another CFA was performed. Two separate CFAs were performed with the subscale of LA. One CFA included all four items and another was performed sans LA3. The omission of LA3 yielded a better fit as noted by an in a majority of the fit indices. Fit indices with all LA items, RMSEA =.046, CFI =.95, TLI =.94, SRMR =.052. Fit indices with only 3 LA items, RMSEA =.045, CFI =.96, TLI =.95, SRMR =.048. Similarly, two of the items of the subscale Thought Control were removed. The remaining items were TC2 and TC3. The most 76

87 problematic subscale was SW, which was omitted in its entirety from the model. Problematic items that were removed from the model included LA3, TC1 and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ustification for removal of the entire SW subscale and items LA3, TC1 and TC4 are as follows. The distancing or social withdrawal subscale was removed as a whole for several reasons. The theoretical reason for removing the subscale was rooted in the fact that during a race it is hard to remove or isolate oneself from the other athletes. They are all around the competitor. Therefore, a participant could interpret the items to be referring to before and/or after the race (even so it is hard to physically isolate oneself from the other competitors) or during the race, introducing a disparity between how the participants answered these items. Therefore, it is possible this confusion led to the poor model fit of this subscale in the analysis. Additionally SW4 is worded in such a way that it could be confused with the Relaxation subscale. Initial analysis in Mplus provided a modification index to do just that. As indicated in the results the subscale also did not contribute to model fit during the pairwise analyses with a majority of the other subscales. Due to these factors it was decided to eliminate the subscale in its entirety from the final model. LA3 also showed low factor loadings and contributed to poor model fit. When removed 77

88 the construct and items performed better. The LA3 item is different from the other items in such a way to be problematic. Items LA1 (I analyzed my past performance), LA2 (I analyzed the weaknesses of my opponents), and LA4 (I analyzed the demands of the competitions) differed from LA3 (I thought about possible solutions in order to manage the situation). Items 1, 2, and 4 are concerned with analyzing the existing competition and situation while item LA3 is more solution focused and as such did not explain much of the variance of the construct. The two items that were removed from the thought control construct were TC1 (I tried not to be intimidated by other athletes) and TC4 (I tried not to think about my mistakes). These differed from the items TC2 (I tried to get rid of my doubts by thinking positively) and TC3 (I replaced my negative thoughts with positive ones). Items 1 and 4 outline a strategy of thought stoppage while items 2 and 3 deal more with reframing and positive self-talk. While thought stoppage and positive reframing are often paired as a coping strategy an analysis of the data suggests that the two might be better separated into two separate subscales. Due to their poor path coefficients TC1 and TC4 were removed from this analysis. In the future perhaps two separate subscales are needed or the existing items can be modified to reflect both the thought stoppage and positive reframing aspects of the coping strategy. For example, the items as they exist now could be changed to I tried not to be intimidated by other athletes by reflecting on how hard I had trained for this event, and I tried not to think about my mistakes by focusing on what I had done successfully. Finally, all items were parceled, except MD for the final model (Model 2.2). MD was not parceled because these four items were the only indicators for the latent variable of distractionoriented coping. The six items of each passion subscale were parceled into two separate parcels of 3 items each. The parcels were created in SPSS by taking the average of the items. Each latent variable in the model had at least two parcels that acted as indicators. A model of the indicators is depicted in Appendix C. During the process a modification index indicated that there was a strong correlation between the coping subscale of EE and the goal attainment subscale of MGA. An analysis of the items revealed that there was much similarity between the two constructs. The effort expenditure subscale included the items: I committed myself by giving a consistent effort, I gave a relentless effort, and I gave my best effort. The mastery goal attainment subscale consisted of the items: During the last competition, I executed my movements correctly, provided a quality effort, concentrated on the task at hand, and mastered 78

89 the difficulties of the situation. In particular, the three items of the EE subscale and MGA2 are worded similarly and both subscales address a similar construct. This relationship had an effect on model fit. In the final model (Model 2.2) the residuals for these two parcels of items were allowed to covary. This statistical method was the least obtrusive, and was justifiable as the similarities in items most likely contributed to the correlation. Table 4.14 depicts the fit indices for each model tested.!"#$%&'()'& &!"#$%&'"()*$+)*,-#*$./0$1--$2/')-*$ $ *+,%$& -./01% & 3 & '.$ 4& 2*345& 6-7&!87& 32*2& *+,%$&)& '(9& :9:)(;<& <=<>&?&(@@@)& (@>9& (A:& (A;& (@:;& *+,%$&)(9& '(<& :9<<('<& <=<<&?&(@@@)& (@>)& (A:& (A;& (@;A& *+,%$&)(<& BC"& <=;9('<& 9<>@&?&(@@@)& (@'<& (;;& (;>& (@;)& *+,%$&9& '('& =@9(9>:& <<)&?&(@@@)& (@A9& (:)& (:@& (@=:& *+,%$&9(9& '(A& A>=(9>& <9;&?&(@@@)& (@A@& (:9& (:)& (@==& 5/#)6$*+,%$D&9&"B,&9(9&E%1%&E.FG&H"1I%$%,&.B,.I"F+1D&+B&$"F%BF&J"1."#$%D(& $ & & The combination of pruning of items from the CICS and then parceling the items reduced the model complexity and subsequently improved model fit greatly over the previous models. Model complexity was reduced by a reduction in degrees of freedom, as well as reduction in estimated parameters. Model 2 with the parceled indicators was run in Mplus using the MLR estimation setting making the results robust to non-normality. Model fit was improved over Model 1. While the 2 statistic was significant, 2 df =331, n=299 = , p <.0001, RMSEA (.052) and SRMR (.069) indicated a good model fit to the data and CFI (.91) and TLI (.90) indicated a reasonable model fit. Path coefficients are depicted in Figure

90 Contextual Situational ** HP OP.664** ** AuM **.144** -.162*.079 TOC.872 DTOC.358**.295**.547** ** Goal Attain.141 Future intentions * CoM ** DNOC ** Figure 4.3. Model 2 with parceled indicators integrating passion, new motivation variables, and coping on goal attainment and future intentions to run triathlons including pathway coefficients. HP = harmonious passion; OP = obsessive passion; AuM = autonomous motivation; CoM = controlled motivation; TOC = task-oriented coping; DTOC = distraction oriented coping; DNOC = disengagement-oriented coping; Goal Attain = goal attainment. * p <.05, ** p <

91 Harmonious passion was a significant predictor of both autonomous (.664) and controlled motivation (-.162). Autonomous motivation was a significant positive predictor of task-oriented coping (.547) and task-oriented coping positively predicted goal attainment (.547). Controlled motivation similarly positively predicted distraction-oriented coping (.358), as well as disengagement-oriented coping (.361). Obsessive passion positively predicted both autonomous (.144) and controlled motivation (.151). Autonomous motivation predicted disengagement oriented coping (-.175) and disengagement oriented coping negatively predicted goal attainment (-.374). Future intentions did not have any significant predictors. Additionally, the disturbances from task-oriented coping and distraction-oriented coping were positively correlated (.295) and task-oriented coping and disengagement-oriented coping negatively correlated (-.248). Two other models were tested to determine any direct relationships between the predictor variables (HP, OP, AuM, CoM, TOC, DTOC, DNOC) and the outcome variables (Goal attainment and future intentions) that are not evident in the hypothesized model. Figures 4.4 and 4.5 depict these models. A model that had only direct paths from each of the 8 variables on to Future intentions was tested. While the 2 statistic was significant, 2 df = 314, n = 299 = , p <.0001, the fit indices indicated a reasonable model fit to the data, RMSEA =.054, CFI =.92, TLI =.90, and SRMR =.063. Only obsessive passion and autonomous motivation significantly predicted future intentions. The path coefficients were.208 (p =.005) from obsessive passion and.214 (p =.033) from autonomous motivation. Similarly another model was tested that had direct paths only from each variable on to goal attainment. This model fit the data reasonably well with a significant 2 df = 295, n = 299 = , p <.0001, and fit indices indicating a reasonable fit, RMSEA =.055, CFI =.92, TLI =.91 and SRMR =.064. Significant pathways existed from CoM (.215, p =.003), TOC (.518, p <.01), and DNOC (-.519, p <.01). The last two TOC and DNOC are represented as significant in the hypothesized model as well. Based on these results Model 2 was modified to include these significant pathways. 81

92 HP OP.029 AuM.090 CoM.215** Goal Attain TOC.518** DTOC DNOC -.519** Figure 4.4. Model with direct paths on to the outcome variable Goal Attainment. HP = harmonious passion; OP = obsessive passion; AuM = autonomous motivation; CoM = controlled motivation; TOC = task-oriented coping; DTOC = distraction oriented coping; DNOC = disengagement-oriented coping; Goal Attain = goal attainment. * p <.05, ** p <

93 HP OP.208** AuM.214* CoM TOC DTOC Future events DNOC Goal Attain.161 Figure 4.5. Model with direct paths on to the outcome variable Future triathlon events. HP = harmonious passion; OP = obsessive passion; AuM = autonomous motivation; CoM = controlled motivation; TOC = task-oriented coping; DTOC = distraction oriented coping; DNOC = disengagement-oriented coping; Goal Attain = goal attainment. * p <.05, ** p <.01. The modifications added to Model 2 were direct paths each from obsessive passion and autonomous motivation to future intentions, as well as a direct path from controlled motivation to goal attainment and are depicted in Figure 4.6. The fit indices for Model 2.2 remained very 83

94 similar to Model 2 with 2 df = 328, n = 299 = , p <.0001, CFI =.92, TLI =.91, indicating close to a good fit to the data, while the RMSEA =.050 and SRMR =.066, both indicated a good fit. Each pathway that was added to the model was significant (p <.05). The path coefficient from autonomous motivation to future intention was significant but not strong (.162, p <.05). However, the pathway from obsessive passion to future intentions was significant at (.208, p <.01). The pathway from controlled motivation to goal attainment was also significant (.185, p <.01. The addition of these three pathways actually increased the strength of some of the existing path coefficients. The most noticeable difference was in the path from disengagement-oriented coping to goal attainment, which increased in strength from to Also of note were the residuals for both goal attainment and future intentions were smaller in Model 2.2. Therefore, the addition of these three direct pathways reduced the unexplained variance for the variables of goal attainment and future intentions. In order to assess the mediating effects of motivation and coping, illustrated in Figure 4.6, Mplus was used to test the indirect effects of these variables. The results are depicted in Table Autonomous motivation acted as a significant mediator between harmonious passion and task-oriented coping as well as between obsessive passion and task-oriented coping. Autonomous motivation was also a significant mediator between harmonious passion and DNOC. Controlled motivation acted as a significant mediator between harmonious passion and DTOC. Controlled motivation also was a significant mediator between obsessive passion and DTOC and DNOC. The strongest mediation effect was that of AuM between the variables HP and TOC (indirect effect =.353, p <.01). The next strongest mediation effect was that of AuM between harmonious passion and DNOC (indirect effect = -.116, p <.01). The rest of the mediation effects were weak not exceeding indirect effect =.1. 84

95 Contextual Situational * ** TOC.300**.571** 1.0 AuM ** ** HP.149** Goal Attain ** OP -.165* ** DTOC.185** **.121 Future intentions.161* CoM ** DNOC **.208**.832 Figure 4.6. Model 2.2 integrating passion, new motivation variables, and coping on goal attainment and future intentions to run triathlons including pathway coefficients. HP = harmonious passion; OP = obsessive passion; AuM = autonomous motivation; CoM = controlled motivation; TOC = task-oriented coping; DTOC = distraction oriented coping; DNOC = disengagement-oriented coping; Goal Attain = goal attainment. * p <.05, ** p <

96 !"#$%&'()*&!"#$%&'()*++&'(,)-&,($".)/0($12($0")2,)/&#$2(0%,)3&(4&&")52,,$0")2"#)607$".) &!+,& -!+,& -.+,& /0&& & & & 12345%67&%88%67&9:;<=& &(>*>??& B())C??& 12345%67&%88%67&9,D<=& &(>CE??& B()A*??& & & & & +0& & & & 12345%67&%88%67&9:;<=& %67&%88%67&9,D<=& 80(&H&/0&I&J"5KD24D;L&M"LL4D2N&+0&I&D#L%LL4O%&M"LL4D2N&:;<&I&";7D2DKD;L&KD74O"74D2N&,D<&I&6D275D$$%3&%KD74D2N&!+,&I&7"LP&D54%27%3&6DM42QN&-!+,&I&34L75"674D2&D54%27%3&6DM42QN& Similarly a test on mediation of the coping variables was also performed using the Mplus statistical program. Results are depicted in Table There was no mediation between motivation and future intentions by coping. Both TOC and DNOC were significant mediators between autonomous motivation and goal attainment and DNOC was a mediator between controlled motivation and goal attainment. None of the other indirect effects were significant. The mediation effect of TOC between AuM and goal attainment was the strongest (indirect effect =.305, p <.01). The mediation effect of DNOC between AuM and goal attainment was very weak (indirect effect =.075, p <.01. The mediation effect of DNOC between CoM and goal attainment was weak at (indirect effect =.154, p <.01). Item factor loadings and residuals are depicted in Appendix C for Models 1.2, 2, and 2.2. Factor loadings ranged from.133 to.818 for Model 1.2. Model 2 loadings ranged from.410 to.939 and from.417 to.940 for Model 2.2. The main difference between Models 1.2 and 2 was the weighting of the items from the BRSQ into four items for autonomous motivation and four items for controlling motivation as well as parceling all the items to load onto the latent variables. Three direct pathways were added to Model

97 !"#$%&'()*&!"#$%&'()*'+)*"#$%&',--$%&.'/$.&")0'12&"3(&"2)'(.'1$*"(&2#.'4$&5$$)'6(.."2)'()*'728")0' & +,"$&-.."/01%0.& 23.34%&/0.%0./,05& & -36& & & 7/4%8.&%99%8.& :;-& &&()*<=& &&&&(DEF==& &&(E)F& &&&G(EE*& &G(EEF& &&&&(EHF==& &G(E)D& :;-& &&(EDH& :;-& &G(EE)& :;-& &&(EEJ&!,."$&>0?/4%8.& &&&&(DH'==& &&(E'<&!,."$&%99%8.& &&&&(DH'==& &&(<E'==& & & & B,6& & & 7/4%8.&%99%8.& &&&&()KF==& :;-& &&&G(EFH& &G(EED& &&&G(E')& &G(ED)&& &&&G()F'==& &&(E<K& :;-& &&(E<<& :;-& &G(EEH& :;-& &G(EEF& :;-& &G(E)J&!,."$&>0?/4%8.& &&&G(<F<==& &G(E)'&!,."$&%99%8.& &&&G(E*H& &G(E)'& 92&$L&-36&M&"3.,0,1,35&1,./N"./,0O&B,6&M&8,0.4,$$%?&%1,./,0O&!AB&M&."5P&,4/%0.%?& 8,Q/0RO&7!AB&M&?/5.4"8./,0&,4/%0.%?&8,Q/0RO&7:AB&M&?/5%0R"R%1%0.&,4/%0.%?&8,Q/0RO&+I&M& R,"$&".."/01%0.O&=8':'(EFO&==8&S&(E)& 87

98 CHAPTER 5 DISCUSSION Can an overall feeling of passion for the sport of triathlons predict motivation at a later date for participation in a specific competition and the coping strategies used to affect goal attainment and impact planned future participation? Is this a possible mechanism that can lead to sustained physical activity? These were the questions at issue in examining the model postulated in this study and the answers appear to be possibly. Based on model fit criteria, Model 2.2 showed the best fit to the data. In this model, it was proposed that passion for triathlons would predict situational motivation and that the type of motivation would predict the type of coping. In turn, it was suggested that the type of coping would predict whether triathletes were more likely to achieve their goals. While many pathways were significant, the residuals indicate that much of the variance was unexplained in the model latent variables. Model on Passion, Motivation, and Coping Overall, the tested model held true to the hypothesized model differing only in two instances of pathway coefficient direction. The pathway from autonomous motivation to distraction-oriented coping was predicted to be negative, as well as the pathway from disengagement-oriented coping to future intentions. Both of these pathways were positive though neither was significant. The path coefficient from Autonomous motivation to distractionoriented coping was.056. The pathway from disengagement-oriented coping to future intentions was.077. The remaining pathway coefficients exhibited the same direction as the model proposed in Figure 2.3, however, several were not significant. An examination of the path coefficients in Model 2.2 (Figure 4.6) indicates that harmonious passion, which was determined at time 1, was a fairly strong predictor of autonomous motivation at the situational level, which was assessed at time 2. Obsessive passion also contributed to the explained variance of autonomous motivation, but not as strongly as harmonious passion. Both path coefficients were significant at p <.01. In contrast to autonomous motivation, the passion variables did not explain much of the variance of controlled motivation. Harmonious passion was a weak but negative predictor of controlled motivation. Therefore, an individual with high harmonious passion was less likely to exhibit controlled motivation. Obsessive passion was also a weak predictor of controlled motivation. This was 88

99 expected because harmonious passion, as conceptualized by Vallerand (2008), is the result of a self-determined integration of the activity into a person s identity. Also as conceptualized by Vallerand (2008), a person who displays obsessive passion has only partially internalized the activity into the self and would display more of the characteristics of identified regulation, but not as much of integrated regulation or intrinsic motivation. With that in mind it is possible that the weak relationship with autonomous motivation is due to this partial integration. However, when looking at the bivariate correlations obsessive passion was correlated stronger with integrated regulation and intrinsic motivation than identified regulation. Deci and Ryan s (1985) SDT also posits that one can be motivated both intrinsically and extrinsically at the same time. Therefore, it is possible that the obsessively passionate triathlete is motivated by both intrinsic and extrinsic factors at the situational level. However, it appears that obsessive passion did not explain that much of the variance of either autonomous or controlled motivation. While passion is rooted in SDT, it is as conceptualized by Vallerand and colleagues a separate construct, and as such only explains part of the variance of autonomous and controlled motivation. As predicted, autonomous motivation was a strong to moderate predictor of task-oriented coping with a path coefficient of.534, p <.01. This relationship, as well as the pathway from task-oriented coping to goal attainment, replicated the results of Gaudreau and Antl (2008) where the path coefficients from self-determined motivation to task-oriented coping was.35 and from task-oriented coping to goal attainment was.54, both significant (p <.05). Autonomous motivation significantly predicted disengagement-oriented coping. While the path coefficient was weak it can be inferred that those triathletes that are high in autonomous motivation are less likely to use disengagement oriented coping strategies. These results indicate that a triathlete who is more intrinsically motivated is more likely to use coping strategies that address a particular stressor rather than strategies that disengage a person from the competition. Task oriented coping strategies include using mental imagery, refocusing effort, and positive thought reframing. Based on Lazarus s (1999) CMR theory and as postulated by Ntoumanis et al. (2009), the self-determined triathlete would see the stressor as a challenge rather than a threat, and use an effective coping strategy, perhaps one that has been learned over time, to achieve that individual s goals. An autonomous and competent triathlete is more likely to have the requisite coping skills needed to address any race stressor. 89

100 Controlled motivation was a significant and moderate predictor of both distraction and disengagement coping strategies. The non-self-determined triathlete who is not fully invested or passionate in the activity is more likely to appraise the situation as a threat and utilize a coping strategy that avoids the stress or emotions associated with falling short of one s goal. Distraction coping strategies might include mentally distracting oneself from race fatigue or the fact that the person is doing poorly. Disengagement coping strategies include venting and resigning oneself to a poor performance. The non-self-determined triathlete, who has not satisfied the need of competency, might not have the requisite coping strategies to effectively address any race stressor. These results replicated the findings from Amiot et al. (2004) and Gaudreau and Antl (2008). Both studies indicated that the type of motivation predicted the likelihood of using certain coping strategies. Self-determined motivation predicted a higher incidence of taskoriented coping strategies and non-self-determined motivation predicted the likelihood of using either disengagement oriented strategies (Amiot et al., 2004) and both disengagement- and distraction-oriented coping strategies (Gaudreau & Antl, 2008). The variance of task-oriented coping was almost entirely explained by autonomous motivation with controlled motivation not contributing significantly. Harmonious passion contributed positively and significantly via an indirect effect through autonomous motivation onto task-oriented coping. Triathletes who have integrated the activity fully into their selfschema (Vallerand, 2008), and who generally like the activity and participate for the sheer enjoyment of it (Deci & Ryan, 1985) are more likely to fully engage in a race, view it as challenge, and will focus their efforts on strategies that will increase the likelihood of achieving their goals. Controlled motivation appeared to explain most of the variance for both distraction and disengagement-oriented coping. Triathletes whose motivation are more controlled, and are not participating for enjoyment, are more likely to distract themselves from any stressor that threatens the achievement of their goals. It appears that they may also be more likely to resign themselves to falling short of their goals and vent the emotions that coincide with the stressor or situation. The significant predicting variables for goal attainment were task-oriented coping, disengagement-oriented coping and controlled motivation. Task-oriented coping was a moderate to strong predictor of goal attainment. As mentioned above this relationship was also evident in Gaudreau and Antl s 2008 study, as well as Amiot et al. (2004). Another significant contributor 90

101 to the amount of variance explained for goal attainment was disengagement-oriented coping, which was also a moderate to strong negative predictor. Controlled motivation was a weak positive predictor of goal attainment. It stands to reason that a triathlete who uses task oriented coping strategies is more likely to attain their goals, whether they are mastery, self-improvement or performance goals, than an athlete who uses disengagement strategies (Gaudreau & Antl, 2008). Goals can be considered a form of external regulation, as such explaining the relationship with controlled motivation. As posited by Deci and Ryan (1983) multiple forms of regulation, internal and external, can motivate athletes concurrently. Thus, while the self-determined athlete participates for the sake of enjoyment he or she will also set goals for each competition. Achieving those goals will also foster the triathlete s feeling of competence, which will contribute to more self-determined behavior. However, goal attainment was not a significant predictor of future intentions. Perhaps, immediately after an event is an inappropriate time to ask about future race intentions, as the triathlete may not be pondering running more races than already planned in the next 12 months. A better question may have been: based on the results of this competition how likely are you to participate in more races then you have planned over the next 12 months? Contrary to what was hypothesized, none of the coping strategies or goal attainment significantly predicted future intentions. Additionally, the coping did not mediate the relationship between motivation and future intentions, as there were no significant indirect effects between these variables. Direct paths from autonomous motivation and obsessive passion significantly predicted future intentions. Triathletes who are more intrinsically motivated will tend to plan on running more events simply because they enjoy participating in them. More events mean more opportunities for enjoyment. As mentioned previously competing is an opportunity to demonstrate competence and interact with other triathletes. Because the athlete chooses to run in an event, the psychological need of autonomy is being addressed, as outlined by Deci and Ryan (1983). The context of the event is an environment where the other needs of competency and relatedness could possibly be met. As Vallerand (2008) posited an obsessively passionate triathlete is defined by the activity of running triathlons, then that person feels the need to run in as many events as possible to maintain that identity. The strongest predictor of future intentions was obsessive passion with a path coefficient of.208. Vallerand et al. (2003) similarly found that obsessive passion was a significant predictor of future intent (.12, p <.10) to return to play 91

102 football by college student athletes. The only other significant predictor in that study was a previous intent to return. The tendencies of this sample to be more self-determined and harmoniously passionate toward triathlons are most likely due to the nature of selection of participants. Most participants were recruited from triathlon clubs and subsequently were more likely to be self-determined toward this activity. According to SDT (Deci & Ryan, 1985), individuals who engage in behavior that could lead to the satisfaction of one or more psychological needs (competency, autonomy, and relatedness) are more self-determined. Members of a triathlon club have chosen to be a part of the club, most likely to be around fellow triathletes, individuals who share their same hobby. This context could lead to satisfying two of the needs as outlined by Deci and Ryan, both relatedness and autonomy. Competency could be reinforced in this environment as well, as often people who achieve personal records are recognized and rewarded at club meetings. At any given time while participating in a club activity the possibility to meet a psychological need is possible. There is another possibility that there is something inherent in triathlons that might lead to harmonious passion at least for a particular subset of people. No prior research was discovered that assessed the mediating relationship of motivation between passion and coping. Based on the results of this study it appears that autonomous motivation and controlled motivation act as mediators between passion and coping. Controlled motivation is a mediator between both passion types and distraction- and disengagementoriented coping. A triathlete who is harmoniously passionate is more likely to be participating for pure enjoyment purposes, and is motivated for an event autonomously, more self-determined, and more likely to use task oriented coping skills at that event. Triathletes who display characteristics of obsessive passion could be participating in that event based on both autonomous and controlled motivation. They might feel they have to participate in the event to gain social acceptance or because to not do so might be a threat to their self-esteem (Vallerand et al., 2003). If they exhibit more controlled or non-self-determined motivation for that event they are more likely to use distraction and disengagement oriented strategies (Gaudreau & Antl, 2008). If they are more autonomously motivated they are more likely to use task oriented coping strategies. The non-significant pathway from goal attainment to future intentions indicated that it was not a strong predictor of future intentions, at least not at the situational level. Perhaps future 92

103 intentions cannot be predicted based on the goals attained at only one race, at the situational level, or in close proximity of completing that event. As stated previously Vallerand et al., (2003) found only obsessive passion to be a predictor of future intentions. A question for future studies would be to look at change in intentions over the course of a triathlon season based on achievement. Would repeated achievement of goals lead to more or less participation? However, obsessive passion and autonomous motivation were significant positive predictors of future intentions. To some degree being autonomously motivated to participate in an event leads to more participation. According to Deci and Ryan (1985) competitive environments can be both a controlling and informational. In such and environment if the achieved goal provides information on competence, intrinsic motivation is fostered. Therefore participating in more events provides triathletes with more opportunities to foster intrinsic motivation. They are satisfying two of Deci and Ryan (1985) requisites for self-determined motivation, autonomy and relatedness. The triathlete chooses to participate and is among other triathletes at the race. Achievement of the goal at this time might not influence future intentions but perhaps achievement of the goal influenced autonomous motivation. The model as tested did not explore this possibility and perhaps future studies could evaluate the possibility that in fact autonomous motivation at the situational level might act as a mediator between goal attainment and future intentions. Passion shares many similarities with aspects of Deci and Ryan s SDT (1985), but the model as conceptualized by Vallerand et al. (2003) holds several distinctions from the theory. Table 4.4 depicts the correlations between the BRSQ subscales and the passion subscales (Vallerand, et al., 2003). The correlations between harmonious passion and the self-determined subscales of the BRSQ were all moderate to fairly strong and significant. The strongest correlations were between HP and integrated regulation and identified regulation. Harmonious passion was also negatively correlated with the non-self-determined subscales of the BRSQ, although only significant with amotivation and external regulation. This is in congruence with how Vallerand has conceptualized harmonious passion; as an autonomous internalization of the activity into one s identity. Individuals have internalized this activity into their identity and have become triathletes and enjoy the activity for its own sake. According to Vallerand obsessive passion is the result of partial internalization with attached contingencies. People would participate in order to satisfy a need for excitement or to be accepted by others. A partial 93

104 integration could possibly be reflected in stronger correlations between obsessive passion and the BRSQ subscales of external regulation, introjected regulation, and especially identified regulation. This is not the case with this sample. Correlations between obsessive passion and all of the subscales of the BRSQ were significant and positive but fairly weak, the strongest with integrated regulation at.36 followed by.26 with introjected regulation. A possible explanation of this could be that obsessive passion, as Vallerand has posited, is different than non-selfdetermined motivation. Those who reported higher levels of obsessive passion also reported higher levels of harmonious passion. The results indicate that there is a strong link between harmonious passion and self-determined motivation and a weak link between obsessive passion and both self-determined and non-self-determined motivation at least for the triathlete population sampled in this study. Both of these links are demonstrated with the model as tested. Passion, Ironman Competitions, and Training Research question 1 asked whether a person who competes regularly in Ironman triathlons is more likely to demonstrate obsessive or harmonious passion? The answer to research question one is that while statistically there appears to be a difference between Triathlete, Ironman, and Sustained Ironman groups on harmonious passion, in actuality the three groups appear to be the same. Results indicate that triathletes, at least those sampled in this study, scored high in harmonious passion and relatively low in obsessive passion. Whether that is the nature of the context of the sport or the participants of this study is unknown based on the data collected. Is the amount of self-reported training different among the two passion types? Do obsessively passionate people train more than those who demonstrate harmonious passion? The answers to research question one suggest that a people who run the Ironman distance races repeatedly did not show a higher incidence in obsessive passion than the people who did not. Data suggests that the obsessively passionate triathletes appeared to engage in more strenuous training, however these individuals also showed a high incidence of harmonious passion as well. The answers also suggest that with respect to training both passion types might share some of the explained variance. The bivariate correlations revealed that the two scales were correlated significantly although low (r =.22). This is supported by Vallerand et al. s (2008) study in which both passion types predicted the use of mastery achievement goals, which in turn 94

105 predicted deliberate practice. Deliberate practice is not inherently enjoyable (Erricson et al., 1993), however, it is required to improve performance. Therefore, with respect to strenuous exercise, if it was engaged in for the specific purpose of improved performance, it could be considered deliberate practice, and both passion types are required. However, the LTEQ only asks the incidence of strenuous activity and not exact type. Therefore, it can only be inferred that the strenuous activity reported could be considered deliberate practice. In addition to the LTEQ future studies should elaborate on training habits to include, distances swum, biked, and run per week. Gender Differences The women surveyed by this study ran fewer events, had fewer years of experience, planned to participate in fewer events over the course of the following year, and actually responded as being on average more obsessively passionate about the sport of triathlons (although the average was less than 4). While women on average had run significantly fewer events than men and planned to run less they are not different on LTEQ and MET. This suggests that women train just as much as men but are not running as many races. Ogles and Masters (2003) had found men to endorse personal goal achievement and competition as main reasons for participating in marathons while women endorsed a variety of reasons. This might explain why women train as much as men but participate in fewer events. Men might have a higher need to display competence and run more races while women do not have to satisfy that need as often. There is no existing research that documents a difference in obsessive passion based on gender. Leedy (2001) reported that women running in 5/10k runs, half marathons, and marathon races scored higher on commitment than males. Based on the research of Ogles and Masters (2002) women were more likely to cite psychological and physical motives to run. The women in this study scored significantly higher than men on obsessive passion, but not harmonious passion. It is possible that in order to meet psychological and physical benefits of triathlons, women tend to report higher levels of obsessive passion. Satisfying this need might be a reflection of a controlling aspect of the sport as outlined by Vallerand s (2008) conceptualization, foregoing other activities to gain the psychological and physical benefits that training provide. It is important to note that the level of obsessive passion (M = 3.33, SD = 1.33) was not extreme at all for women or men with regard to this population and that according to the final model tested in 95

106 this study, obsessive passion only explained some of the variance of autonomous motivation. Level of Participation Differences Data were also analyzed based on how the participants classified their triathlon participation, which were either as a professional, competitive, recreational, fitness or other reason triathlete. These groups were compared and a multiple ANOVAs showed that they differed on the following variables: age, years of triathlon experience, total events, Ironman events, planned future events, harmonious and obsessive passion, LTEQ strenuous and MET score. Professional triathletes differed significantly in age from fitness triathletes and approached significance with recreational triathletes. As athletes age, their ability to compete as professionals declines due to the age-related physical declines they experience (Rittweger, Prampero, Maffulli & Narici, 2009). It can be inferred that, with this decline, professional athletes careers tend to be limited in years and as such professional athletes tend to be younger. The difference in ages between these groups is therefore no surprise. The fitness and recreational athletes tended to be older than competitive triathletes as well. As an athlete ages, perhaps the need to be competitive or to classify oneself as competitive declines as one s physical ability declines. Competitive triathletes had significantly more years of triathlon experience (M = 7.16) than recreational (M = 4.71) and fitness triathletes (M = 3.97). As a triathlete becomes more competent in the sport, he or she could also tend to become more competitive. Based on the years of experience of fitness triathletes and recreational triathletes, it is possible that these triathletes have not developed the competencies yet to become competitive. Over time as these athletes build their cardiovascular endurance and strength, as well as technique, they may label themselves as competitive triathletes whereas initially they labeled themselves as participating just for fitness or recreational purposes. This is in line with previous research that stated that motives to initiate an activity are more for physical or fitness reasons rather than psychological reasons (Carmack & Martens, 1979; Masters & Ogles, 1995). Thus according to the SDT (Deci & Ryan, 1985), it is possible that a triathlete develops more competence within the sport with more participation and as a result becomes more competitive as well as more intrinsically motivated. The average years of triathlon experience for professional athletes in this sample was just under 6 years. As stated previously, the window for a professional career is limited, but 96

107 triathletes can still consider themselves competitive even if they are not competing as a professional. ANOVAs also revealed a difference between the groups in total events and future events planned. Professional triathletes reported having run the most events (M = 41.20). For obvious reasons professional triathletes plan to run a greater number of events, as the sport is their livelihood and the more events they run the more likely they are to earn money from both sponsorships and possible prize money. Similar to years of experience competitive triathletes had run more events on average (M = 29.16) than recreational triathletes (M = 13.75) and fitness triathletes (M = 3.97). Because competitive triathletes have been participating in the sport longer, it is very logical that they would have run more events than the other two groups. Professional and competitive triathletes planned to run more events than recreational fitness and other triathletes. Competitive triathletes plan to run more events than recreational and fitness triathletes as well. It is possible that these events allow them to display their competency to themselves and others. Additionally, competitive triathletes scored higher in harmonious passion as well as obsessive passion than recreational and fitness triathletes. As Vallerand (2007) stated people who are passionate about an activity will engage in that activity more than those who are not passionate about an activity. The mechanism for the relationship with future events was addressed in Model 2.2, which indicated that obsessive passion and autonomous motivation were the only predictors of future events. While neither professional nor competitive triathletes had a high incidence of obsessive passion they were significantly higher than recreational and fitness triathletes. Professional triathletes displayed the highest level of obsessive passion of all the groups and were statistically different from both recreational and fitness triathletes. Professional triathletes train and participate for a number of reasons. Due to the nature of it being their profession, it is possible that they feel controlled by the activity, as it pays the bills. That being said, the obsessive passion as reported by professionals had a mean of just fewer than 4 on a 7- point Likert-type scale. There were also only five professional triathletes surveyed in this study, and this is not a large enough number to be able to generalize the results to the professional triathlete population. 97

108 Strengths, Limitations and Future Research Directions This study has several major strengths. Triathletes were sampled from across the United States and data were collected at two separate points in time. The second time point collected data in close proximity to each participant actually competing in a triathlon event. With that recent event salient in their minds, the participants were more likely able to answer accurately about their experiences. There are several limitations that need to be addressed pertaining to this study and addressed in future studies of this nature. The first is the homogeneous nature of the sample. The sample was predominantly self-determined, harmoniously passionate, and comprised of mostly triathlon club athletes. Individuals who are members of clubs are more likely to be selfdetermined as is evidenced by this sample and can be explained under the tenets of Deci and Ryan s (1985) SDT. An individual who participates in triathlon club activities is satisfying the relatedness need and has demonstrated autonomy in choosing to be a member, as well as continuing to participate in the sport. Also, he or she may demonstrate competence to other club members and goal achievements are often reinforced in the club environment. The sample utilized for this study predominantly displayed characteristics of harmonious passion. Another limitation may be in the nature of the passion scale itself. As evidenced by the results of this study, a person may demonstrate characteristics of both harmonious and obsessive passions. The passion model is not dichotomous in its nature, and as such, it was difficult to tease out differences between the two aspects of passion and compare variables based on passion type. The main issue is that as Vallerand (2008) has conceptualized that harmonious and obsessive passions are separate with the difference being the integration of the activity into the identity as a major tenet of the model. Results from this study indicate that a person can display both, evidenced by the 92 triathletes out of 624 who scored higher than a 4 on both subscales of the passion measure. Out of the 299 participants that were included in the SEM only 1 scored higher than a 4 on obsessive passion while 44 scored higher than a 4 on both subscales. Still the majority of the sample (237) scored a 4 or higher in harmonious passion alone. Are those who scored higher on both subscales at a transition point were harmonious passion is waning while obsessive passion is on the rise or vice versa? Future studies on passion should be longitudinal in nature and if possible follow an individual as an athlete develops passion for an activity. Future studies on obsessive passion should address the negative consequences of obsessive 98

109 passion, for example exercising when injured. With research questions that include whether those individuals who score high in obsessive passion show a higher incidence of injury? Also whether professional or athletes who consider themselves competitive are more likely to score higher in obsessive passion? Future analysis should explore the true nature of obsessive passion. It appears that harmonious passion is tied closely with self-determined motivation while obsessive passion is related to both self-determined and non-self-determined behavior. Further development of the passion scale is needed. If passion is dichotomous then a scale that reflects that dichotomy is needed. The results from this study indicate that a person can display characteristics of both harmonious and obsessive passion. Based on the understanding of the passion model is this possible? Can an individual be passionate about an activity with it being integrated into one s identity and still be controlled by it at the same time. If the answer is yes, then passion is more of a situational construct than contextual or global. Use of measures first developed in French and translated to English was also a limitation in this study. For example, some item wordings could be confusing, or as in the case of SW4, might actually be a better indicator of a separate subscale. In this case SW4 as it is currently written is better suited to indicate relaxation than social withdrawal. By more accurately translating the actual meaning of the item so that it corresponds with the subscale it is testing, a more reliable measure will be created. Additionally, determining if the coping strategies as they are constructed in the measure appropriate for the context of the triathlon. Modification of items may be required for them to make sense in this context. Another limitation with the study was sample size given the complexity of the hypothesized model. The model s complexity had to be reduced through parceling of measurement indicators in order to achieve a good fit to the data. Had a larger sample been obtained it is possible parceling would not have been required. A larger sample could possibly have allowed the full structural model to be tested. It would be interested to see if the results would be similar to those in this study. It is possible that a larger sample would yield more individuals who are high in obsessive passion only. Another limitation was that an order effect was not controlled for in the study. However, results of a pilot study, which included the BRSQ, Passion scale, and CICS, indicated that survey order did not affect responses, and as such, all participants took the same order of measures 99

110 within each survey. Therefore an order effect may have occurred and should be controlled for in future studies. While the results of this study are promising there is still much to learn about how Passion and Motivation are demonstrated in the context of Triathlon. How is passion developed in the sport? How long does it take to become harmoniously passionate toward the activity? Can an individual start out as harmoniously passionate and then transition to being obsessively passionate? What is the true nature between the passion scales? Are the results of this study only a snapshot of individuals transitioning between passion types or can you be both at the same time? 100

111 APPENDIX A MANOVA TABLES 101

112 Tests of Between-Subjects Effects Source Dependent Variable Type III Sum of Squares df Mean Square F Sig. Corrected Model Ttlevts 3.132E LTEQ1str b LTEQ1mod c LTEQ1mild d LTEQ e MET 1.112E HPAVG g OPAVG h Intercept Ttlevts LTEQ1str LTEQ1mod LTEQ1mild LTEQ MET HPAVG OPAVG Age Ttlevts LTEQ1str LTEQ1mod LTEQ1mild LTEQ MET HPAVG OPAVG YXP Ttlevts LTEQ1str LTEQ1mod

113 LTEQ1mild LTEQ MET HPAVG OPAVG Trilevel Ttlevts LTEQ1str LTEQ1mod LTEQ1mild LTEQ MET HPAVG OPAVG Gender Ttlevts LTEQ1str LTEQ1mod LTEQ1mild LTEQ MET HPAVG OPAVG IRONMAN Ttlevts LTEQ1str LTEQ1mod LTEQ1mild LTEQ MET HPAVG OPAVG Trilevel * Gender Ttlevts

114 LTEQ1str LTEQ1mod LTEQ1mild LTEQ MET HPAVG OPAVG Trilevel * IRONMAN Ttlevts LTEQ1str LTEQ1mod LTEQ1mild LTEQ MET HPAVG OPAVG Gender * IRONMAN Ttlevts Trilevel * Gender * IRONMAN LTEQ1str LTEQ1mod LTEQ1mild LTEQ MET HPAVG OPAVG Ttlevts LTEQ1str LTEQ1mod LTEQ1mild LTEQ MET HPAVG

115 OPAVG Error Ttlevts LTEQ1str LTEQ1mod LTEQ1mild LTEQ MET HPAVG OPAVG Total Ttlevts LTEQ1str LTEQ1mod LTEQ1mild LTEQ MET 3.865E6 595 HPAVG OPAVG Corrected Total Ttlevts LTEQ1str LTEQ1mod LTEQ1mild LTEQ MET HPAVG OPAVG a. R Squared =.630 (Adjusted R Squared =.617) b. R Squared =.146 (Adjusted R Squared =.115) c. R Squared =.037 (Adjusted R Squared =.001) d. R Squared =.051 (Adjusted R Squared =.016) e. R Squared =.054 (Adjusted R Squared =.019) 105

116 f. R Squared =.151 (Adjusted R Squared =.120) g. R Squared =.089 (Adjusted R Squared =.056) h. R Squared =.171 (Adjusted R Squared =.141) 106

117 APPENDIX B MEASUREMENT MODEL e AuM1 AuM2 AuM3 AuM4 MI EE TC R LA SS e AuM TOC MGA SGA PGA HP1 HP2 HP MD 1 MD 2 MD 3 MD 4 GL OP1 OP2 OP CoM DTOC DNOC Future Events CoM1 CoM2 CoM3 CoM4 Figure B.1. The measurement model as tested allowing for MGA and EE errors to covary. HP = Harmonious Passion; OP = Obsessive Passion; AuM = Autonomous motivation; CoM = Controlled motivation; TOC = Task oriented coping; EX = External Regulation; AM = Amotivation; MI = Mental Imagery; EE = Effort Expenditure; TC = Thought Control; R = Relaxation; LA = Logical Analysis; SS = Seeking Support; SW = Social Withdrawal/Distancing; MD = Mental Distraction; D = Disengagement; VE = Venting of Unpleasant Emotions; MGA = Mastery Goal Attainment; SGA = Self-Improvement Goal Attainment; PGA = Performance Goal Attainment D VE 107

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122 APPENDIX D INFORMED CONSENT 112