Using Social Identity Mapping to Understand the Implications Of

USING SOCIAL IDENTITY MAPPING TO UNDERSTAND THE IMPLICATIONS OF

STUDENT-ATHLETE GROUP COMPATIBILITY

Madison Alexandra Robertson

A thesis submitted to the Graduate Program in Kinesiology and Health Studies

in conformity with the requirements for

the degree of Master of Science

Queen’s University

Kingston, Ontario, Canada

(August 2019)

Abstract

Social Identity refers to the extent to which people define themselves based on the groups to which they belong (Tajfel, 1981). Despite an extensive body of literature spanning several fields of psychology, most research on social identity has involved membership with only one group. Considering that humans are a social species, often belonging to several groups concurrently, investigating implications for multiple memberships is warranted. The purpose of this study was to explore social identity compatibility in interuniversity athletes, with a specific interest in assessing associations with quality of life and academic and athletic performance. A total of 235 interuniversity athletes (57% female; Mage = 19.98 years; SD = 1.77) completed an online social identity mapping tool (oSIM; Cruwys et al., 2016), and questionnaires assessing the criterion variables. Results indicated that two mediation models were statistically significant.

First, general health quality mediated the relationships between the proportion of very incompatible groups and individual perceived athletic performance. Second, a specific dimension within health quality, emotional health quality, also mediated the relationships between the proportion of very incompatible groups and perceived athletic performance. These results are discussed in terms of both their theoretical and practical implications within the thesis. However, as a generally summary, our findings suggest the importance of experiencing harmony among group memberships, and that this is particularly important in populations with overt group affiliations. Within the thesis, limitations are also acknowledged (i.e., cross-sectional research design) and suggestions are made to promote future research using the novel online oSIM tool in sport.

Co-Authorship

My supervisor, Dr. Luc Martin, is co-author for this thesis. Dr. Tegan Cruwys and Dr.

Mark Bruner served as my thesis committee members and have had input during the conceptualization of the thesis and at the proposal defense. My supervisor, Dr. Luc Martin, offered guidance on study design, data collection, analysis, and provided feedback throughout the writing stages of the thesis. I (Madison Robertson) held the primary responsibility for study design, data collection, data analysis, and drafting and revising this written document.

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Acknowledgements

Without the constant support and help of many individuals, this thesis would not have become a reality. I would like to sincerely thank everyone involved in this project.

First, I would like to thank my supervisor, Dr. Luc Martin, for his guidance throughout the completion of my Master’s degree. Your positive attitude, patience, immense knowledge, and continued support (even from Australia) allowed me to succeed as a student and researcher. I could not have imagined having a better advisor and mentor throughout my Masters.

Thank you to my proposal committee members, Mark and Tegan, for your insight, encouragement, and thoughtful advice. Thank you for not only helping with this project, but also doing it around a 14-hour time difference. I would also like to thank my defense committee members, Dr. Jean Côté, Dr. Mark Bruner, Dr. Sebastian Harenberg, and Dr. Elijah Bisung for taking time out of their busy schedules to be a part of my defence.

I would like to thank all of my peers in the PLAYS research group, who supported, motivated, and helped me throughout my time as a Master’s student. Spending time with each of you never failed to put me in a good mood.

Mom and Dad, your unwavering support and love throughout all of my schooling, along with every other part of my life, got me to where I am now. I am forever grateful to everything you have done for me, and there are no words to express how much you both mean to me.

Mitchell, thank you for your continued support, love and letting me vent about school, even when you had no clue what I was talking about. Finally, I would like to thank everyone within interuniversity sports who were involved in this project. Coaches, athletes, and program directors

– I sincerely thank you for your time. Without you this project could not have happened.

Table of Contents

Abstract...... ii

Co-Authorship Statement...... iii

Acknowledgements...... iv

List of Tables...... viii

List of Figures...... ix

List of Abbreviations...... x

Chapter 1 Introduction...... 1

Chapter 2 Literature Review...... 4

2.1 Social Identity...... 4

2.2 Identifying with Several Groups ...... 6

2.3 Social Identity with Student-Athletes ...... 9

2.4 Study Purpose and Contextualization ...... 13

Chapter 3 Methods...... 15

3.1 Participants...... 15

3.2 Procedures...... 16

3.3 Measures...... 17

3.3.1 Group compatibility...... 17

3.3.2 Quality of life...... 20

3.3.3 Self-reported performance indices...... 20

3.4 Analysis...... 21

3.4.1 Data screening...... 21

3.4.2 Data analysis...... 21

Chapter 4 Results...... 23

4.1 Descriptive Statistics and Correlations...... 23

4.1.1 Group descriptive statistics...... 24

4.1.2 Group compatibility...... 26

4.1.3 Additional social identity dimensions...... 26

4.1.4 General and emotional health...... 27

4.1.5 Athletic and academic performance...... 30

4.2 Main Analysis...... 30

4.2.1 Mediation analysis...... 30

Chapter 5 Discussion...... 34

5.1 Limitations...... 42

5.2 Future Directions...... 43

Chapter 6 Conclusion...... 49

6.1 Personal Reflection...... 50

Disclosure Statement...... 52

Funding...... 52

References...... 53

Appendix A: Changes to Proposal...... 74

Appendix B: Coaching Recruitment Email...... 75

Appendix C: Letter of Information for Coaches/Athletes...... 76

Appendix D: Online Consent Form/Questionnaire Package...... 78

Appendix E: Questionnaire 2: Short-Form 36 Item Health Survey...... 80

Appendix F: Questionnaire 1: Demographics...... 85

Appendix G: Confidentiality Agreement...... 86

Appendix H: Completed oSIM Network...... 88

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List of Tables

Table 1. Descriptive Statistics and Pearson Correlation Coefficients...... 23

Table 2. Participant group assignment and descriptive statistics...... 25

Table 3. General oSIM Social Identity Descriptive Statistics ...... 27

Table 4. Summary of Information for SF-36 Health Quality Scales ...... 29

Table 5. Findings from the eight mediation analyses...... 31

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List of Figures

Figure 1. Traditional group compatibility approach in comparison to the one used in this study...... 19

Figure 2. Summary of the eight mediation models conducted for data analysis ...... 22

List of Abbreviations

36-SF: Short-Form 36-Item Health Survey

BP: Bodily Pain

CC: Cognitive Centrality

EH: Emotional Health

GH: General Health Perception

GPA: Grade Point Average

HC: Health Change

HRQoL: Health-Related Quality of Life

IGA Ingroup Affect

IGT: Ingroup Ties

NCAA: National Collegiate Athletic Association oSIM: Online Social Identity Mapping Tool

OUA: Ontario University Assocaition

PF: Physical Functioning

QoL: Quality of Life

REF: Role Limitations Because of Emotional Functioning

REP: Role Limitations Because of Physical Functioning

SCT Self-Categorization Theory

SF: Social Functioning

SIA: Social Identity Approach

SIM: Social Identity Mapping

SIT: Social Identity Theory

VT: Vitality

Chapter 1

Introduction

Social identity is generally understood as the extent to which people define themselves based on the groups to which they belong. Specifically, Tajfel (1981) defined social identity as,

“an individual’s self-concept which derives from his/her knowledge of his/her membership of a social group (or groups) together with the value and emotional significance attached to that membership” (p. 255). Identifying with social groups can lead to a range of benefits, including improved perceptions of cohesion (e.g., Ellemers, de Gilders, & Haslam, 2004), increased use of prosocial behaviours (e.g., Tyler & Blader, 2001), greater motivation (e.g., Ellemers et al., 2004), enhanced well-being (e.g., Bettencourt, Charlton., Eubanks, Kernahan, & Fuller, 1999; Cameron,

1999), and better physical health (e.g., Holt-Lunstad, Smith, & Layton, 2010). Consequently, researchers are advocating for continued investigation of the value of social identity in the physical activity domain (e.g., Stevens et al., 2017), and more specifically, within the context of sport (e.g., Rees, Haslam, Coffee, & Lavallee, 2015). Accordingly, the goal of this thesis was to extend the current literature by exploring the concept of group compatibility—a specific component of social identity—within a Canadian interuniversity sport (U Sports) population.

Considering the nascent body of literature pertaining to social identity in sport psychology, a brief summary herein will serve to orient the reader. First, the use of social identity as a lens to explore group dynamics in sport is not surprising given the inevitability of group process in this domain. Indeed, where there is sport, there are groups (e.g., Carron & Eys,

2012). For instance, even in traditional “individual” sports such as tennis, skiing, or boxing, athlete experiences are fundamentally shaped by interactions with teammates and competitors

(Evans, Eys, & Bruner, 2012). In relation to identity perceptions specifically, preliminary

research highlights their salience for a range of important athlete and team level outcomes.

Notably, a greater sense of social identity has been associated with improved perceptions of cohesion (Bruner, Boardley, & Côté, 2014), more frequent use of prosocial behaviours (Bruner,

Boardley, Benson, et al., 2017), heightened commitment and self-worth (Martin, Balderson,

Hawkins, Wilson, & Bruner, 2018), and general positive youth development (Vierimaa, Bruner,

& Côté, 2018). However, an important caveat to this line of research is the exclusive investigation of identity perceptions as they pertain to only one group. Given that people, including athletes, typically ‘belong’ to several groups at once (e.g., Cruwys et al., 2016; Forsyth,

2014), the absence of enquiry into the compatibility of these various group identities is significant. The extent to which an individual identifies with the various groups in their lives is an important consideration, as competing identities can create conflicting situations that negatively impact experiences in diverse and meaningful ways (e.g., Iyer, Jetten, Tsivrikos,

Postmes, & Haslam, 2009; Roccas & Brewer, 2002).

The extent of congruence between various social identities is termed group compatibility, and research reveals its significance for a range of outcomes, including improved task performance, health, and engagement in life (e.g., Carron & Garvie, 1978; Cheng, Shanchez-

Burks, & Lee, 2008; Rosenthal, London, & Levy, 2011). Indeed, although sport is emerging as a context of interest for social identity research, scholars have yet to explore the notion of group compatibility in an athletic population. Furthering this point, one sport specific sample that experiences clear memberships to several groups simultaneously is the interuniversity student- athlete community in Canada (U Sports). As their title suggests, ‘student-athletes’ have overt membership in at least two groups (i.e., as a student and as an athlete), and the degree of compatibility with regards to these identities is likely to impact their performance and general

well-being across domains. For example, a study by the National Collegiate Athletic Association

(NCAA), which is generally the United States equivalent to U Sports, found that student-athletes reported intense time requirements for their sport participation, and advocated having more time off for their studies and during their post-season (NCAA, 2016).

In recognizing the complexity of the social identities that individuals experience across their group memberships, scholars have created an online social identity mapping tool (oSIM) to explore the intricacies of these perceptions (Cruwys et al., 2016). This protocol was utilized in the current research to specifically expand our understanding of the compatibility that student- athlete’s experience in relation to their social identities. Given that athletic teams were expected to represent a common central feature across all participants (i.e., U Sports), and due to their overt boundaries and membership salience in this domain, the sport teams were used as the central group of analysis (i.e., ego-group centered approach). Accordingly, the compatibility experienced by athletes for their teams and the identities of all other groups were explored in relation to their general quality of life and performance perceptions in athletic and academic domains.

Chapter 2

Literature Review

This project was informed by several bodies of literature: (1) the social identity approach,

(2) general group dynamics principles, and (3) student-athlete specific research. The following sections will present these bodies of literature and discuss their relevance to the overarching research question.

Social Identity

The research presented in this section revolves around the social identity approach (SIA), which has its origins in the Social Identity Theory (SIT; Tajfel & Turner, 1979) and the Self-

Categorization Theory (SCT; Turner, Hogg, Oakes, Reicher, & Wetherell, 1987). SIT emphasizes the experiences involved with identifying with a particular social group, whereas

SCT focuses specifically on the cognitive processes and mechanisms involved in the categorization process of the self and others into social groups.

According to SIT, social identity generally involves a progression along three stages, transitioning from (1) self-categorization, to (2) depersonalization, to (3) self-stereotyping. In the first stage, an individual begins self-categorizing themselves as a member of a particular group.

According to Tajfel and Turner (1979), this process occurs when the differences between themselves and members of their group are smaller than the differences between themselves and members of other groups. The second stage, depersonalization, occurs when individuals no longer view themselves and their group members as a collection of idiosyncratic individuals, but rather, as belonging to a collective entity. Finally, in the third stage, individuals’ self-stereotype.

This involves the adoption of the values most demonstrative of their group. On the other hand,

social categorization (i.e., SCT) is a fundamental cognitive process that allows us to organize information about our world (Rosch, 1978). Here, SCT focuses specifically on the cognitive processes involved in self-categorization, noting different levels of inclusiveness (Turner et. al.,

1987), which Tajfel (1978) defined as the “ordering of the social environment in terms of groupings of persons in a manner which makes sense to the individual” (p. 59).

Research involving SIT and SCT has traditionally been concerned with the extent to which such manifestations impact intergroup relations (e.g., discrimination, prejudice). There are psychological consequences (e.g., honesty, loyalty, self-image) from the differentiation and conflict between an individual’s identified group (i.e., in-group) and other groups (i.e., out- groups; Brewer, 1979). Further, there are both psychological and physical health benefits obtained by identifying with a group, known as a form of ‘social cure’ (Haslam, Jetten, Cruwys,

Dingle, & Haslam, 2018). Indeed, social identification can reduce feelings of depression

(Cruwys, South, Greenaway, & Salam, 2004), prevent experiences of stress (Gallagher, Meaney,

& Muldoon, 2014), improve health behaviours (e.g., willingness to attend exercise classes;

Haslam, Jetten, Postmes, & Haslam, 2009), and assist in dealing with dementia, brain injury, and strokes (e.g., Clare, Rowlands, & Quin, 2008; Walsh, Muldoon, Gallagher, & Fourtune, 2015).

A group’s identity not only defines what it means to be a group member, but also the kinds of attitudes, emotions, and behaviours that are appropriate for members in various contexts. It also accounts, more specifically, for why individuals identify with a specific social category in various situations. From this, the situational factors in which a group participates can help explain certain aspects of an individual’s identification (i.e., personal identity, social identity; Turner, 1982; Turner et. al., 1987), but should also be considered in relation to the group as a whole. Indeed, the SIA generally, and SIT and SCT specifically, have been used to

explore how identity perceptions manifest or change depending on the groups one belongs to.

However, whereas these theories have been investigated extensively (e.g., Haslam et al., 2018), the extent to which one’s social identity is influenced by multiple group memberships, simultaneously, remains under-investigated.

Identifying with Several Groups

Tajfel and Turner (1979) defined a group as “a collection of individuals who perceive themselves to be members of the same social category” (p. 15). These social categories, or groups, can alter human behaviour and influence the extent to which an individual identifies with a given group (Hogg, 2006). Although humans have an innate need to belong and desire for interpersonal attachment (Baumeister & Leary, 1995), it is surprising that much of the research to date has focused on single group membership. Humans are a social species and typically belong to several groups at once (e.g., Cruwys et al., 2016). In fact, conservative estimates suggest that there are roughly 30 billion groups in existence at any given moment (Forsyth,

2014). Thus, it is important to consider the multiple groups that an individual perceives themselves to belong to, as internalizing group membership can allow for the perceptions of social identity to be investigated in relation to their impact on a host of outcomes, both physical and psychological in nature (e.g., Ashforth & Male, 1989; Haslam et al., 2009, Jetten, Haslam, &

Haslam, 2012). Moreover, past research has supported the idea that identifying with multiple groups may have a positive effect, including an increase in healthy behaviour and mental health in adolescent and adult populations (e.g., physical activity and healthy dieting; Sani, Madhok,

Nordury, Dugard, & Wakefield, 2015a, 2015b; Miller, Wakefield, & Sani, 2015, 2016).

As can be gleaned from previous sections, social identity is a complex phenomenon. As such, and to best capture the varying dimensions of social identity, Cruwys and colleagues

(2016) highlighted four main indices that should be considered. These include group importance

(e.g., Cameron, 2004; Ellemers, Kortekaas, & Ouwerkerk, 1999; Leach et al., 2008), ratings of group positivity (e.g., Best et al., 2014), group similarity (e.g., Roccas & Brewer, 2002), and group compatibility (e.g., Iyer et al., 2009). Pertaining to the latter, group compatibility is defined as the degree to which groups mutually satisfy each other’s behavioural preferences, and coexist in harmony. Positive group compatibility can lead to enhanced creative performance, improved well-being and mental health, and a greater sense of belonging (e.g., Cruwys et al.,

2016; Rosenthal et al., 2011). Similarly, compatibility has also been associated with overall psychological well-being and engagement in life (e.g., Chelladurai & Carron, 1981; Cheng,

Sanchez-Burks, & Lee, 2008; Landau, Greenberg, & Solomon, 2008), and adjustment to new life transitions (Iyer et al., 2009). Not surprisingly however, despite the various benefits attributed to group compatibility, incompatibility can result in negative experiences.

It is worth noting that research in the group compatibility domain has tended to focus less on groups themselves, and more on the relationships between groups as well as the degree to which those relationships may be (dys)functional (e.g., Benet-Martínex & Haritatos, 2005;

Ramarajan, 2014). Clearly, this is a complex undertaking as relationships between groups are impacted by individuals’ perceptions, which can be dynamic, layered, and unique. Roccas and

Brewer (2002) described this as social identity complexity, whereby an individual’s subjective representation of the interrelationships among his/her multiple group identities can be affected by stress levels and personal value priorities. High complexity involves acknowledgement of differentiation between in-group categories, while low complexity means that multiple identities are subjectively embedded in a single in-group representation (Roccas & Brewer, 2000).

Moreover, this concept indicates the degree of overlap perceived to exist between groups for

which a person is simultaneously a member. To ensure that identity is inclusive and compatible, one must acknowledge that being involved in multiple in-groups is not always expected to be convergent or complementary.

Concepts similar to social identity complexity, including identity integration, have also been highlighted as important in reference to social identity (e.g., Amiot, de la Sablonniere,

Terry, & Smith 2007; Hoang, Holloway, & Mendoza, 2011). Identity integration is a psychological experience involving multiple identity domains and is linked to psychological well-being (Erikson, 1968; Syed & McLean, 2016). Erikson’s (1968) notion of identity integration is defined as the heightened and conscious awareness of the sameness of the self across time and place; thus, giving individuals an understanding of who they are. This theory can help us understand how people cogitate the various groups they belong to, while experiencing novel identities in their lives. The interplay of three theorized levels of identity, including personal, social, and ego (Syed & McLean, 2016) can be used to help understand how a person makes sense of the various roles they engage with within the groups in their lives. Interestingly, identity integration is also used to help explain how multiple domains in one’s life interact with one another across various contexts (e.g., Walker & Syed, 2013).

Taken together, it is clear that identification with a group translates to a range of benefits for individuals, yet researchers are aware of the necessity to consider multiple group memberships, and how the complexity and compatibility of these various social identities manifest themselves and impact individuals. The sport context is an area that has received growing interest in social identity research, yet this body of work has involved the examination of identities pertaining to one group. Murrell and Gaertner (1992) are often credited as the first to investigate social identity with athletes in sport, demonstrating identity perceptions to be related

to winning percentage in a youth population. This work has been extended by others that have demonstrated associations with perceptions of cohesion (De Backer et al., 2011), hesitancy to adhere to problematic norms (Täuber & Sassenberg, 2012), and attributions for success and failure (Zucchermaglio, 2005).

A group of sport researchers have also adopted Cameron’s (2004) three-dimensional model of social identity comprised of ingroup ties (IGT; perceptions of bonding and similarity), ingroup affect (IGA; feelings associated with team membership), and cognitive centrality (CC; importance associated with team membership). These efforts have provided support for associations with cohesion (Bruner et al., 2014), use of prosocial and antisocial behaviours

(Bruner et al., 2018), heightened commitment and self-worth (Martin et al., 2018), and general positive youth development (Bruner et al., 2017; Vierimaa et al., 2018). Similarly, when athletes perceived their groups to demonstrate stronger boundaries for membership, and experienced interdependence during activities, their social identity increased (Bruner, Eys, Evans, & Wilson,

2015; Martin, Balderson, Hawkins, Wilson, & Bruner, 2017). Clearly, social identity is a salient construct in sport, yet as has been the case with the broader literature, these studies did not consider multiple identities, and rather, investigated perceptions pertaining to only their sport teams. The subsequent section will advocate for the necessity to investigate identity perceptions across several groups, which is particularly relevant for student-athletes who experience clear and overt membership to several groups, often with competing agendas.

Social Identity with Student-Athletes

Student-athletes represent a population that belong to at least two groups (e.g., athletics and academics) comprising overt membership boundaries. As such, these individuals are likely to experience multiple social identities, as they are expected to belong to and engage with both

academic and athletic domains simultaneously (Sturm, Feltz, & Gilson, 2011), while also managing the remainder of the groups in their lives (e.g., families, social circles). Previous studies have described the relationship between the student-athletes’ academic and athletic roles, as well as their commitments to sport (Adler & Adler, 1991; Meyer, 1990; Miller & Kerr, 2002).

Indeed, identifying with one group may take precedence over another (Lally, 2005), with evidence supporting much stronger athletic identities to contribute to the tendency to violate rules, demonstrate poor sportspersonship, and exhibit competitive aggressiveness (Visek,

Watson, Hurst, Maxwell, & Harris, 2010; Yukhymenko-Lescroart, 2018). However, identifying as an athlete has been found to be associated with positive outcomes, such as increased self- worth, commitment, perceived effort, team cohesion, and prosocial behaviours toward teammates (Bruner et al., 2018; Bruner et al., 2014; Martin et al., 2017). Yet, as indicated above, the substantial research on athletic identity has involved perceptions of only a single group.

Belonging to more than one group can have differing effects on student-athletes; thus, effecting their overall life experiences.

The importance of group processes and group behaviour with regard to performance outcomes and individual well-being in sport is well documented (Carron & Eys, 2012; Eys,

Bruner, & Martin, 2019). Social identity generally, and group compatibility specifically, can have a positive influence on multiple outcomes for student-athletes. One main outcome that has been highlighted as influential to an athlete’s experiences is quality of life (QoL). Quality of life can be defined as an individual’s perspective of their own perceived well-being and satisfaction with their physical, emotional, mental, social, and behavioural functioning (Chai et al., 2010;

Ravens-Sieberer et al., 2014). Health related QoL (HRQoL) is a subsection of QoL (Gu, Chang,

& Solmon, 2016), which focuses on health, namely physical, mental, and

social well-being (Ravens-Sieberer et al., 2006; The WHOQOL, 1998). Additionally, there are multiple dimensions that represent important components of an individual’s QoL, including physical functioning, physical health role limitations, bodily pain, general health, vitality, social functioning, emotional health, and mental health (e.g., Fahey, Whelan, & Maitre, 2005;

Marginean, 2004; Mercer, 2010).

Previous literature has highlighted the importance of health-related QoL for athletes, in which sport involvement can facilitate social integration, resulting in an increase in QoL (e.g.,

Collins & Kay, 2003; Ibbetson, Watson & Ferguson, 2003; Velija, 2009). Sport participation can be positively associated with an increase in the athlete’s health-related QoL, as sport engagement improves ones physical, mental, and social health (Constantinescu, 2011; Downward & Rasciute,

2011; Eime, Harvey, Brown, & Payne, 2010; Snyder et al., 2010). The impact of QoL on an athlete’s life experiences is an important outcome to consider, as research has shown that physical activity can positively impact health-related QoL in university students (Pedišić et al.,

2014). In terms of student-athletes, increases in social identity have been shown to lower depression levels, while increasing people’s sense of meaning, control, and self-esteem

(Greenaway, Cruwys, Haslam, & Jetten, 2015). However, limited research regarding the impact of social identity on QoL is available in sport generally, and with student-athletes specifically.

Emotional health, also known as mental health, is one dimension of HRQoL that has been highlighted as especially important for student-athletes. Previous literature has demonstrated poorer mental health among collegiate students, including instances of increased psychiatric disorders (e.g., American College Health Association, 2009; Schwartz, Beaver, & Barnes, 2015;

Wolanin, Gross, & Hong, 2015). Similarly, anxiety and depression are common mental health problems, with mental disorders such as depression, becoming increasingly common among

university students (Auerbach et al., 2016). This is a cause for concern, as negative mental health outcomes are also associated with lower personal self-esteem and overall health (e.g.,

Baumeister, Campbell, Krueger, & Voss, 2003; Pyszczynski, Greenberg, Solomon, Arndt, &

Schimel, 2004). Further, self-reported depressive symptoms have been reported as frequently with high performance athletes as non-athletes (Gorczynski, Coyle, & Gibson, 2017). Thus, understanding the implications of mental health, in addition to HRQoL, is an important avenue of study for the student-athlete population.

Studies support the notion that interuniversity student-athletes are more often engaged in academic and campus activities than their non-athlete counterparts, adding to their increasingly busy lifestyle (Umbach, Palmer, Kuh, & Hannah, 2006; Williams, Sarraf, & Umbach, 2006;

Wolniak, Pierson, & Pascarella, 2001). More interestingly, research on interuniversity NCAA athletes found that a majority of student-athletes supported the idea of providing breaks from their sport post-season, during holidays, and academic exam periods (NCAA, 2016).

Additionally, studies have found that students who participated in interuniversity athletics did not have a better grade point average (GPA; Hood, Craig, & Ferguson, 1992; Shulman &

Bowen, 2001) or greater outcomes in cognitive learning and motivation (Wolniak et al., 2001) when compared to non-athlete students. However, when considering their social identity, there is an improvement in academic success and motivation between those who identify more with their academic or athletic identities (Wolniak et al., 2001). In addition, when primed with athletic identity perceptions, students had lower self-regard and poorer performance on a challenging academic test than did those primed with an academic identity (Yopyk, & Prentice, 2010).

Accordingly, despite research efforts, continued investigations are needed to better understand student-athlete social identity, and its impact on academic and athlete performances.

Study Purpose and Contextualization

The primary purpose of this study was to investigate the degree to which Canadian interuniversity student-athletes’ social identities influenced their quality of life, and academic and sport specific performance. Through this process, I aimed to better understand the complexity of student-athlete social identities and the implications of the compatibility of their identities pertaining to salient groups in their lives. A secondary purpose of this research was to utilize the oSIM tool (Cruwys et al., 2016) within an interuniversity sport (i.e., U Sports) context.

This enabled us to further our understanding of social identity in student-athletes while also administering a novel methodology for measuring dimensions of social identity in sport.

An important point of emphasis to note is our decision with respect to the measurement of group compatibility for this research. Individuals belong to multiple groups at once, and across those memberships, there is a degree of compatibility or incompatibility. While group compatibility is important across all groups, one group may be more salient compared to others, depending on the primary role in which the individual may want to invest themselves in. The current population of interest was unique in the sense that they were all members of a similar group, interuniversity athletics (i.e., a sport team). Thus, and assuming that participant groups represented a network in line with network theory (e.g., Borgatti, Mehra, Brass, & Labianca,

2009; Crossley et al., 2015), this study used the concept of an ego centric approach to situate their U Sports team as the center of emphasis for this study. This approach facilitated a greater understand of how the compatibility of this group (the sport team) in relation to all other groups in their lives may impact important variables across the context of the student-athletes lives (i.e., well-being, academic and athletic performance). It was hypothesized that health quality would

mediate the relationship between group compatibility and performance measures for academic and athletic performance.

Chapter 3

Method

This study employed a cross-sectional research design involving a novel methodology to investigate the social identity group compatibility of U Sports student-athletes. Participants from intact U Sports teams completed the oSIM (Cruwys et al., 2016) and an online questionnaire package during the mid-point of their athletic seasons.

Participants

A total of 235 participants (n = 134 females) completed the oSIM and questionnaire package. Participants were obtained from four universities, with the majority of them coming from one university (i.e., 93% of the total sample). On average, the student-athletes ranged from

17 to 28 years of age (Mage = 19.98; SD = 1.77). Generally, 82.85% of the athletes did not live at home (n = 198) and their living arrangements varied from living alone to having as many as seven roommates. Of those who lived with roommates, 46.50% (n = 92) lived with people on their team. There was a total number of 17 interuniversity sport teams involved in this study, including both individual and team sports. Athletes came from a range of sports, including rugby

(n = 29), rowing (n = 8), cross country running (n = 18), ice hockey (n = 46), soccer (n = 53), fencing (n = 17), American football (n = 2), volleyball (n = 3), basketball (n = 14), synchronized swimming (n = 5), figure skating (n = 9), fast pitch baseball (n = 12), and water polo (n = 17).

The athletes ranged in experience, with 33.61% being in their first year of eligibility (n = 80),

28.15% in their second (n = 67), 17.65% in their third (n = 41), 15.97% in their fourth (n = 38), and 4.62% in their fifth (n = 11). Further, athletes self-reported as formal leaders (i.e., a designated team captain; 16.25%, n = 39) and/or informal leaders on their team (i.e., mentor, social convenor; 49.58%, n = 119).

The athletes all participated in interuniversity sport in Canada, which is officially termed

U Sports. For many of the sports at this level, it is among the highest level of competition for amateur athletes. Season lengths vary from 2 to 6 months, but all occur during the academic school year in Canada—September to April. These teams specifically participated in the Ontario

University Association (OUA) which involves extensive travel for weekend competitions, training 4 - 5 days per week, and competing 1-2 times a week. Furthermore, student-athletes must be enrolled in a minimum of 9 units per semester (3 full-time courses) to compete in their sport and must pass a minimum of 18 units (6 courses) from the previous academic year to continue competing in future years.

Procedures

Ethical approval from Queen’s University was obtained, and the directors of high- performance sport (or similarly titled position holders are other institutions) were contacted.

Although a formal collaboration with the high-performance director at one Canadian university facilitated data collection, we sought additional participation from other institutions to ensure an adequate sample size. The general sequence of communication was for the primary researcher to obtain permission from athletic directors to contact coaches using information publicly available online (e.g., university athletics websites). Emails were then sent to head coaches (Appendix B), asking them to respond to the research team over e-mail or phone to learn more about the study and, if they wished to volunteer their team, established a time for the researcher to introduce the study to the athletes. An information letter was also distributed to all coaches and athletes, which included all relevant information for the study (Appendix C). As a form of compensation for participation, athletes who completed the oSIM and questionnaire were included in a draw for one of three $50 gift certificates to the relevant university sport store.

The primary researcher met with the teams after a practice or during a team meeting, provided a tutorial to facilitate the use of the oSIM, and supervised the completion of the questionnaires in case any athletes had questions. Completion of the protocol took the participants 20-30 minutes, which included the consent form, oSIM protocol, questionnaires, and demographic information. Once participants completed the consent form (Appendix D), they were directed to the oSIM protocol. Upon completion of the oSIM, they were directed to complete the online questionnaire comprising the Short-Form 36-item Health Survey (36-SF;

Appendix E) and a brief demographic questionnaire including information on the athletes’ GPA and athletic performance (self-report Likert scale ranging from 1 – 10; Appendix F).

To ensure participant confidentiality, the oSIM and questionnaires were completed on personal held phones, tablets, or laptops. In addition, the researcher emphasized that no one would know athlete responses—other than the researchers—as any publication or presentation of data would be done in aggregate form. As per University policies, all electronic data are stored on a computer with firewall protection that is password-protected for 7 years, after which the data will be destroyed based on the available techniques at the time. Although no research assistants were ultimately involved in the project, the procedure of having them sign a letter of confidentiality was given ethical approval (Appendix G).

Measures

Group compatibility. To assess group compatibility, participants were asked to complete the oSIM developed by Cruwys and colleagues (2016). An example of a completed participant oSIM network can be seen in Appendix H. This protocol was administered at mid- season for each team, thus providing ample time for the various identities and the interactions between group memberships to manifest themselves. Although unidimensional measures of

social identity exist (Boen, Vanbeselaere, Pandelaere, Schutters, & Rowe, 2008; Postmes,

Haslam, & Jans, 2012), researchers also encourage the use of multidimensional inventories

(Cameron, 2004; Cameron & Lalonde, 2001; Ellemers et. al., 1999). The multidimensional nature of the oSIM is a particular strength as this method allowed researchers to visually represent and assess participants subjective experiences of group membership, while providing specific indices of group compatibility—among the other dimensions listed in Chapter 2 and described briefly in the subsequent paragraph. To ensure the accurate and proper completion of the oSIM, participants were subject to a brief description by the primary researcher and were required to engage in a tutorial post log in. This was also the point where participants provided consent by signing an online form (see Appendix D).

The oSIM has four distinct stages. First, participants create boxes that represent the number of groups for which they are members. Once the boxes are created, they are asked to indicate the relative importance of each group by altering the size of the box (larger boxes indicate greater importance). Participants are then instructed to position each box within the available space such that groups placed closely to one another (i.e., proximity) are similar to one another and groups that are farther apart are different from one another (as perceived by participants on whatever features deemed important to them). The proximity between boxes (i.e., groups) quantifies perceived overlap (vs. distinctiveness) of group memberships. Participants were also asked to provide information about each group by answering a series of questions of group positivity. The final stage, and the one utilized for the current thesis involved having participants join boxes (i.e., groups) with lines that indicate perceived compatibility (group compatibility) between various groups. The participants are prompted with a description of how

“easy versus hard” it is to be a member of those particular groups. Group Compatibility, then,

was calculated as the proportion of links between groups that are “very compatible.” With particular importance given to the results of the Group Compatibility step, two Group

Compatibility variables were computed. This included the proportion of very compatible links and proportion of very incompatible links, which stemmed from the two constructs developed by the oSIM, including number of happy links and number of unhappy links. These numbers were divided by the overall number of links connected to the varsity sport group, to determine the proportion of compatible links and proportion of incompatible links.

Within these four distinct stages of the oSIM, we took an Ego Centric approach to understanding the compatibility between social identity groups. Typically, as indicated in Figure

1, the compatibility between all groups is investigated and the proportion of all links are calculated. However, with the Ego Centric approach, the group of interest (i.e., sport team) was at the center of interest. Therefore, only the proportion of links between this group of interest and other social identity groups were calculated. Links that were not associated with the group of interest were not included.

Figure 1. Traditional group compatibility approach in comparison to the one used in this study

Quality of life. To assess health-related quality of life (HRQoL), participants completed the Short-Form 36-item Health Survey (see Appendix E). This is a widely adopted measure of

HRQoL (Ware & Sherbourne, 1992), used to assess perceived level of functioning across several domains (Lox, Martin Ginis, & Petruzzello, 2014). The SF-36 measures nine domains of

HRQoL: physical functioning (PF), role limitations because of physical functioning (RPF), bodily pain (BP), general health perception (GH), health chance (HC), vitality (VT), social functioning (SF), role limitations because of emotional functioning (REF), and emotional health

(EH). These domains can be combined to create two components providing the overall assessment of HRQoL related to physical and mental health; physical component (PF, RPF, BP,

GH, HC, and VT) and mental component (EH, REF, SF, HC, and GH). The SF-36 is considered a generic measure of HRQoL, because it was not designed for any particular population (Lox, et. al., 2014). Eleven of the items must be reversed scored, whereby larger scores indicate improved health quality. Similar to previous studies using this questionnaire, the health quality variable was computed from the sum of all 32 items, while the emotional health quality variable was computed from the sum of 18 items pertaining to emotional or mental health (e.g., Matcham,

Norton, Steer, & Hotopf, 2016; McHorney, Ware, Lu, & Sherbourne, 1994).

Self-reported performance indices. Athletes were asked to rate their perceived athletic performance on a scale of 1 (poor performance) to 10 (strong performance) in comparison to athletes at the same level of competition. A second item pertained to academic performance, whereby athletes were asked to self-report their current GPA. It was originally expected that objective measures of performance would be obtained through a formal partnership with the high-performance director at the Universities; however, issues arose, and it was not possible to procure these data. Therefore, it was decided that self-reported measures would be used.

Analysis

Data screening. Descriptive and bivariate statistics were calculated and assumptions for

normality were assessed (e.g., skewness and kurtosis). A Shapiro–Wilk test revealed that participant perceptions of very incompatible groups were positively skewed and, as a result, were corrected using logarithmic transformation (Tabachnick & Fidell, 2013). Statistical assumptions for multiple regressions were met (e.g., normality, subscale internal consistency, linear relationships, and homoscedasticity; Tabachnick & Fidell, 2013). The preliminary analyses involved bivariate correlations and descriptive statistics (see Table 1). This included the calculation of Pearson correlations for all study variables. The magnitude of effect sizes for the regression paths was determined as 0.10, 0.30, and 0.50 for small, medium, and large effects

(Cohen, 1992). A p-value of less than 0.05 was considered to be statistically significant in all of the analyses. There was less than 5% of missing data, which was considered inconsequential and these were replaced using series mean replacement (Tabachnick & Fidell, 2013).

Data analysis. Results from the oSIM for group compatibility, the two components of

HRQoL (i.e., general health quality and emotional health), and self-reported GPA and athletic performance were summed and average scores computed. The mean, range, and median of each participant’s group compatibility scores from the oSIM was computed, for the number of total groups, number of total links, number of compatible links, and number of incompatible links.

The general health quality and emotional health scores were computed in accordance with previous research using the Short-Form 36-item Health Survey (e.g., McHorney et al., 1994), in which the mean of the total general health quality, total emotional health, and each of the nine health dimensions were calculated.

With regard to the main analyses, initial bivariate correlations were examined, followed by eight regressions using an SPSS macro termed PROCESS (model 4; Hayes, 2018).

Specifically, the regressions considered the relationship between the dependent variable (i.e., athletic performance and academic performance) with the perceived independent variable (i.e., proportion of very compatible links and very incompatible links). These links are specific to the student-athletes sport team, in which the sport team is the group of interest and the proportion of links are to other groups. These regressions also used either health quality or emotional health as a mediator. Eight different mediation models were conducted, and a summary of these models can be seen in Figure 2. The models included either the proportion of very compatible groups (1) or proportion of very incompatible groups (2) as the perceived variable. The two outcome variables were perceived athletic performance (1) or perceived academic performance (2).

Finally, the two mediator variables were health quality (1) and emotional health (2). Each combination of the six variables were used. For example, model 1-2-1 involved the proportion of very compatible groups (1) as the perceived variable, emotional health (2) as the mediator, and perceived athletic performance (1) as the outcome.

Figure 2. Summary of the eight mediation models conducted for data analysis

Chapter 4

Results

Descriptive Statistics and Correlations

Descriptive statistics and Pearson correlations for the measured variables are presented in

Table 1. As a general summary, overall health quality was positively related to emotional health quality (r = 0.94, p < 0.01), self-reported athletic performance was positively related with both general health quality (r = 0.26, p < 0.01) and emotional health quality (r = 0.24, p < 0.01), and self-reported academic performance was positively related with general health quality (r = 0.13, p < 0.05).

Table 1

Descriptive statistics, and Pearson correlation coefficient matrix of the measured variables

Variables Mean SD Range 1 2 3 4 5 6

1. Proportion of Very Compatible 0.29 0.38 0 - 1 1 Links 2. Proportion of Very Incompatible 0.04 0.14 0 - 1 -0.11 1 Links 3. General Health 63 - 101.77 12.75 -0.02 0.13 1 Quality 130 4. Emotional Health 58.40 8.93 29 - 78 -0.05 0.13 0.94** 1 Quality 5. Self-reported 6.82 1.70 0 - 10 0.06 -0.01 0.26** 0.24** 1 athletic performance 6. Self-reported 1.8 - - academic 3.46 0.61 0.09 0.03 0.13* 0.06 1 4.3 0.08 performance

Note. *p < 0.05. **p < 0.01

Group descriptive statistics. In Table 2, descriptive statistics are presented for the various social identity groups indicated by participants. Using the group typology advanced by

Lickel and colleagues (2000), groups were categorized into four sections including intimacy, task, social, and loose affiliation groups. In total, 45% of the groups were intimacy groups (n =

572) such as family, friends, housemates, and personal relationships. Task groups represented

34.63% of the groups (n = 437) which included varsity sport teams, additional sports, extracurricular clubs, and work related groups. Only 2.22% of the groups were social groups (n =

28) which included being a Canadian, socioeconomic status, gender, religion, political, and being an environmentalist. Finally, 17.83% of the groups were loose affiliations (n = 225), such as a school faculty, university, school classmate groups, and additional broad social groups (e.g., neighborhood or residence building group).

Table 2

Participant group assignment and descriptive statistics

Group Subgroups Number of % of total responses groups Intimacy Groups 572 45% Family 211 16.72% Friends 300 23.77% Housemates 52 4.12% Personal relationships 9 0.71% Task Groups 437 34.63% Varsity sport team 246 19.49% Other sports 37 2.93% Extracurricular club 62 4.91% Work 62 4.91% Other task groups 30 2.38% Social Groups 28 2.22% Canadian 4 0.32% Socioeconomic status 6 0.48% Gender/Sexuality 4 0.32% Religion 2 0.16% Politics 2 0.16% Environmentalist 3 0.24% Other 7 0.55% Loose Affiliation Groups 225 17.83% School faculty 127 10.06% University/General academics 55 4.36% School classmates 24 1.90% Other social groups 19 1.51%

Group compatibility. Table 2 displays the results for the group compatibility dimension of the oSIM. Results were separated into information regarding the U Sports team, following the

Ego Centric Approach, and all other groups identified by participants. Generally, there was an average of 5.84 (SD = 2.01) groups identified by each participant, ranging from 1 to 15 total groups. Within the U Sports team, there was an average of 2.13 links (SD = 1.37) connected to this group, with 0.84 (SD = 0.97) of them being compatible, and 0.22 (SD = 0.56) of them being incompatible. Additionally, 0.26 (SD = 0.28) of the links were very compatible, and 0.03 (SD =

0.11) of them were very incompatible. In terms of all groups identified by the participant in the oSIM, there were an average of 5.24 total links (SD = 3.21), with 4.24 (SD = 3.21) of them being compatible, and 1 (SD = 1.59) being incompatible.

Additional social identity dimensions. Table 3 displays the results for the additional three dimensions of the oSIM, including group importance, group positivity, and group similarity. For group importance, there was an average of 2.38 (SD = 1.17) groups that were rated important or had a perfect 3/3 rating for importance. The average number of positive groups, which had a score of 8, 9, or 10, was 4.34 (SD = 0.42). Finally, for group similarity, the average distance between groups was 1.18 (SD = 0.56), with most similar groups having 0 points, and more distinct groups having a maximum average distance of 3.6 points.

Table 3

General oSIM Social Identity Descriptive Statistics

Mean (M) Median SD Range

Number of groups 5.84 6 2.01 1 - 15

U Sports Number of Links 2.13 2 1.37 0 - 10 Group

Number of compatible 0.84 1 0.97 0 - 5 links

Number of incompatible 0.22 0 0.56 0 - 4 links

All Groups Number of Links 5.24 5 3.90 0 - 32

Number of compatible 4.24 4 3.21 0 - 29 links

Number of incompatible 1.00 0 1.59 0 - 11 links

Group Number of important 2.38 2 1.17 1 - 6 Importance groups (highest importance rating 3/3)

Group Number of positive 4.34 4.39 0.42 2 - 5 Positivity groups (8-10/10 score)

Group Average distance between 1.18 1.09 0.56 0 - 3.6 Similarity groups

General and emotional health. Table 3 displays the results for the physical and emotional health of participants. All items were summed to determine the general health of

participants out of a total of 136 possible points (M = 101.77, SD = 12.75), while specific items were summed to determine general emotional health (M = 58.40, SD = 8.93), out of 88 points, and general physical health (M = 63.77, SD = 7.02), out of 77 points. Moreover, health quality can further be divided into nine dimensions. Results showed that dimensions such as physical functioning (M = 2.88, SD = 0.40), energy and fatigue (M = 3.37, SD = 1.34), emotional well- being (M = 3.83, SD = 1.46), and social functioning (M = 3.09, SD = 1.40) were of the highest rated for participants. Interestingly, there were also lower scorings of the dimensions physical role functioning (M = 1.73, SD = 0.44), emotional role functioning (M = 1.59 SD = 0.49), and bodily pain (M = 2.15, SD = 1.40). For the purpose of this study, I have chosen to focus specifically on the general health quality and emotional health of the participants.

Table 4

Summary of findings from SF-36 Health Quality scales

Scales # of Items Mean SD

1. General Health 32 101.77 12.75

2. Emotional Health 16 58.40 8.93

3. Physical Health 22 63.77 7.02

a. Physical functioning 6 2.88 0.40

b. Role functioning/physical 4 1.73 0.44

c. Role functioning/emotional 3 1.59 0.49

d. Vitality 4 3.37 1.34

e. Emotional well-being 6 3.83 1.46

f. Social functioning 2 3.09 1.40

g. Bodily pain 2 2.15 1.13

h. General Health 4 2.45 1.37

i. Health Change 1 2.52 0.88

Athletic and academic performance. The average self-reported GPA was 3.35 (SD =

0.54), with a range of 1.8 to a perfect 4.3 GPA. Athletes also rated themselves out of ten in comparison to others from the same sport, position, and level of competition, where the average was 6.82 (SD = 1.81).

Main Analysis

Mediation analysis. All of the eight mediation models conducted are presented in Figure

1. In Table 4, it can be seen that the fifth regression (i.e., 2-1-1) indicated that health quality mediated the relationship between proportion of very incompatible links and self-reported athletic performance (b = 5.12, SE = 2.50, 95% CI [0.96, 10.62]), however the total (b = -0.75; t

(231) = -0.08; p = 0.94) and direct effects (b = -5.87; t (231) = -0.60; p = 0.55) we’re not significant. Additionally, it was found that health quality was also related to perceived sport performance, when controlling for the proportion of incompatible links (b = 0.035, t (231) =

4.13, p < 0.01). Approximately 1.63% of the variance in self-reported athletic performance was accounted for by the predictor variable (R2 = 0.0163). For the sixth regression (i.e., 2-2-1), results indicated that emotional health quality mediated the relationship between proportion of very incompatible links and self-reported athletic performance (b = 4.68, SE = 2.09, 95% CI

[1.06, 9.39]), however the total (b = -0.75; t (232) = -0.08; p = 0.94) and direct effects (b = -5.42; t (232) = -0.56; p = 0.58) were again, not significant. However, it was found that emotional health was also related to perceived sport performance, when controlling for the proportion of incompatible links (b = 0.046, t (231) = 3.75, p < 0.01). Approximately 1.63% of the variance in self-reported athletic performance was accounted for by the predictor variable (R2 = 0.0163).

Table 5

Findings from the eight mediation analyses

Model Total Effect Direct Effect Indirect Confidence R2 Effect Interval

1-1-1 0.27 0.30 -0.03 CI [-0.20, 0.15] 0.0006

1-2-1 0.23 0.33 -0.06 CI [-0.22, 0.10] 0.0029

1-1-2 0.14 0.14 -0.01 CI [-0.04, 0.03] 0.0072

1-2-2 0.14 0.14 -0.01 CI [-0.03, 0.02] 0.0029

2-1-1* -0.75 -5.87 5.12 CI [0.96, 10.62] 0.0163

2-2-1* -0.75 -5.42 4.68 CI [1.06, 9.39] 0.0163

2-1-2 1.73 0.83 0.90 CI [-0.12, 2.52] 0.0163

2-2-2 1.73 1.30 0.42 CI [-0.56, 1.72] 0.0010

Note: (*) mediation occurred

Health quality did not mediate the relationship between proportion of very compatible links and self-reported athletic performance (b = 0.27, t (231) = 0.91, p = 0.36). Approximately

0.06% of the variance in self-reported athletic performance was accounted for by the predictor

(R2 = 0.0006). The results also indicated that for proportion of very compatible links, the indirect coefficient was not significant for perceived athletic performance with health quality (b = -0.03,

SE = 0.09, 95% CI [-0.20, 0.15]), as the mediator, and therefore, mediation did not occur.

Health quality also did not mediate the relationship between the proportion of very compatible links and self-reported academic performance (b = 0.14, t (231) = 1.30, p = 0.20).

Approximately 0.72% of the variance in self-reported athletic performance was accounted for by the predictors (R2 = 0.0072). The results indicated that for proportion of very compatible links, the indirect coefficient was not significant for perceived academic performance with health quality (b = -0.01, SE = 0.02, 95% CI [-0.04, 0.03]) as the mediator, and therefore, mediation did not occur.

Similar to health quality, when using emotional health quality as the mediator between the proportion of very compatible links and self-reported athletic performance, there was no significant effect (b = 0.23, t (231) = 0.91, p = 0.36). This was also true for the relationship between proportion of very compatible links and self-reported academic performance (b = 0.14, t

(231) = 1.30, p = 0.20). For both models, approximately 0.29% of the variance in self-reported performance was accounted for by the predictors (R2 = 0.0029). The results also indicated that for proportion of very compatible links, the indirect coefficient was not significant for perceived athletic performance with emotional health quality (b = -0.06, SE = 0.02, 95% CI [-0.22, 0.10]) and perceived academic performance with emotional health quality (b = -0.01, SE = 0.01, 95%

CI [-0.03, 0.02]) as the mediator, and therefore, mediation did not occur.

Finally, when predicting the relationship between the proportion of very incompatible links and self-reported academic performance, there was no significant effect with health quality

(b = 1.73, t (232) = 0.49, p = 0.63) or emotional health quality (b = 1.73, t (232) = 0.49, p = 0.63) as the mediators. For health quality, approximately 1.63% of the variance in self-reported academic performance was accounted for by the predictors (R2 = 0.0163). Then, for emotional health quality, approximately 0.10% of the variance in self-reported academic performance was

accounted for by the predictors (R2 = 0.0010). The results indicated that for proportion of very compatible links, the indirect coefficient was not significant for perceived academic performance with health quality (b = 0.90, SE = 0.69, 95% CI [-0.12, 2.52]) or emotional health quality (b =

0.42, SE = 0.56, 95% CI [-0.56, 1.72]) as the mediators, and therefore mediation did not occur.

Chapter 5

Discussion

The purpose of this study was to explore the degree of compatibility between groups that

U Sports student-athletes identified with, and how this compatibility (or incompatibility) affected their perceptions of academic success and athletic performance. I also examined the extent to which this relationship was mediated by general quality of life and emotional health. The results indicated that, when groups were incompatible, quality of life generally, and emotional health specifically, mediated the relationship with perceptions of athletic performance. There was no significant relationship between group compatibility and athletic performance. Similarly, it was determined that there were no significant relationships between group compatibility (or incompatibility) with perceptions of academic performance. Throughout the subsequent sections,

I will first situate these findings within the broader social identity literature, and discuss specific findings related to group compatibility for this particular population. I will also discuss the novel

Ego Centric approach used within this thesis, followed by advancing several implications derived from the findings as well as suggestions for future research. I will then acknowledge certain limitations of the research and, finally, end with a general conclusion and reflection section describing my personal experiences pertaining to the research process (i.e., Chapter 6).

Identifying with a social group can benefit individuals in a variety of ways, including increased use of prosocial behaviours toward others and improved physical and psychological health (e.g., Ellemers et al., 2004; Holt-Lunstad et al., 2010; Tyler & Blader, 2001). Importantly, whereas SIT and SCT have been used extensively to investigate the implications associated with group identification (e.g., Brown, 2000), the extent to which one’s social identity is influenced by multiple groups simultaneously has received less attention. This is surprising given that

individuals typically belong to several groups at once (e.g., Cruwys et al., 2016). For instance,

Cruwys et al. (2016) noted an average of 6 to 7 simultaneous groups identified by individuals, which was similar to the student-athletes in the current study who noted belonging to an average of 5.84 (SD = 2.01) groups. Accordingly, it is likely that the identity experienced based on various group memberships differs, and also that the degree to which the various groups feature in an individual’s day to day life will vary. Whereas the relative number of groups that an individual identifies with was not of direct interest in the current thesis, the fact that the student- athletes belonged to a similar number of groups is noteworthy, especially given the empirical support for the importance of compatibility between groups (e.g., Hirsh & Kang, 2016;

Rosenthal et al., 2011). Thus, the degree to which membership could occur in harmony for the individuals in this study was expected to impact individual achievement in relevant domains.

A central finding was the presence of a significant effect between incompatible social identities and athletic performance, with health quality and emotional health acting as mediators.

These findings suggest that rather than the compatibility of groups, it was their incompatibility that was inversely associated with health quality and athletic performance. This coincides with previous research outside of sport, which indicates that incompatibility is linked to negative outcomes such as increased stress, lower perceptions of performance (i.e., academic work), and poor interpersonal relationships (e.g., Argyle, 1969; Settles, 2004). In relation to literature specific to SIT and SCT, positive social identity and a sense of belonging to a group can have positive implications for individuals (Hornsey, 2008; Tajfel & Turner, 1979; Turner et al., 1987).

However, when the compatibility between those groups, or social identities, is negative, these benefits are mitigated. In turn, such a situation can result in negative outcomes, such as role and group specific behavioural conflict (Hirsh & Kang, 2016). This may also be true for student-

athletes, as being a part of a sport team can foster significant bonds to teammates, but also overshadow other identities or groups that the athlete belongs to. Consequently, student-athletes may then be subject to possible negative outcomes, such as the decrease in perceptions of athletic performance identified in this research.

It is also important to discuss that health quality and emotional health both mediated the relationship between group incompatibility and perceptions of athletic performance. As described previously, this inverse relationship is a logical finding—when groups are not compatible, student-athlete’s overall well-being and emotional health are likely to suffer. When mental health is poor, such as having increased stress, emotional dysregulation, or generalised anxiety, these can impact both self- (e.g., athlete) and other- (e.g., coach) reported athletic performance (e.g., Gross et al., 2015; Kim, Woo, & Yng, 2014). Similar to my study, self- reported measures and the SF-36 questionnaire have been used to assess athletic performance and health quality (e.g., Kim, Woo, & Yng, 2014). Past research within the health field has indicated that the incompatibility between groups is associated with decreased well-being, including in populations with university students (Iyer et al., 2009). However, whereas there is some support for the implications of group incompatibility, much of the research to date has involved an emphasis on the positive aspects of the compatibility between groups (e.g., Cruwys et al., 2016; Rosenthal et al., 2011). Within this research, groups are typically measured in regard to how compatible groups are with each other. For example, Cruwys and colleagues (2016) examined if group compatibility increased after a group based social intervention, which worked to help people experiencing psychological distress in association with social isolation. However, incompatibility between groups is measured by the degree to which groups do not get along or work well with each other. The incompatibility between groups has been shown to be important

and therefore, additional research is needed to further understand the implications of not just the lack of compatibility, but the presence of incompatibility itself.

It was interesting to note that the perceived compatibility of groups was not significantly associated to either academic or athletic performance. This finding could perhaps be partially explained by the strength of the student-athlete’s identity with their various groups. Social psychological literature has suggested that the strength of social identities can change both quickly or gradually over time, depending on the situation (Easterbrook & Vignoles, 2012;

Oakes, Turner, & Haslam, 1991). At times, students may identify more with their athletic role, such as during playoffs and championships, but then focus on academic pursuits during exam periods. Interestingly, Adler and Alder (1991) found that athletes who identified most strongly with their athletic roles were also likely to experience greater identity difficulties. This could include a difficulty with transitioning to other groups and periods of their lives (e.g., beginning or ending university), resulting in feelings of disorientation and frustration (Kerr & Dacyshyn,

2000). Student-athletes belong to at least two groups at the same time (i.e., athletics and academics), and while the requirements for membership within these groups may compete, if an individual has the proper tools and support to manage those demands, the benefits or difficulties of group compatibility highlighted in previous research may be augmented or mitigated, respectively.

Another consideration pertaining to group compatibility findings could involve the gender composition of this sample (i.e., more female than male student-athletes). Although research suggests that holding multiple social identities at once may lead to numerous benefits

(e.g., enhanced well-being, performance; Brook, Garcia, & Fleming, 2008; Steffens, Jetten,

Haslam, Cruwys, Haslam, 2016; Zhang, Noels, Lalonde, & Salas, 2017), multiple identities can

also result in identity interference, in which the pressures of one identity interferes with the performance of another (Van Sell, Brief, & Schuler, 1981)—which occurs differently across individuals and based on gender. Indeed, interference between identities is associated with multiple negative psychological and physical consequences (Cooke & Rousseau, 1984; Kossek

& Ozeki, 1998), and for example, females may disidentify with their gender to avoid discrimination, thus reducing identity interference (Settles, 2004). This can be seen in the university setting, as past research has indicated that female student-athletes have had higher graduation rates (Eitzen & Sage, 1997) and greater academic orientation (Meyer, 1990) than their male counterparts. Woman also have indicated that they believe their amount of sport recognition within society is lower than males, and they therefore receive less social reinforcement and pressure as student-athletes (Meyer, 1990). The greater recognition males receive for their athletic accomplishments may encourage them to identify as athletes to a greater extent, while females could be more likely to identify equally as both an athlete and student. In turn, this could cause female student-athletes to actively balance the variety of groups to which they belong, as they may hold other groups outside of their sport team to a higher value. This phenomenon is supported through past research which indicates that female student-athletes maintain a better balance between their roles of students and athletes (Meyer, 1990; Miller &

Kerr, 2002; Riemer, Beal, & Schroeder, 2000). Consequently, future research may consider exploring additional variables as moderators to determine any potential differences in the experiences of group compatibility or incompatibility. These variables may include, for example, information such as gender, leaderships status, or team tenure.

Within previous research on social identity and group compatibility, the populations of interest have typically been university students or the general adult population (Beckwith, Best,

Dingle, Perryman, & Lubman, 2015; Cruwys et al., 2016; Haslam, Cruwys, & Haslam, 2014). It is worth noting that this study utilized a unique population, namely student-athletes, which should be considered when discussing the current findings. A unique feature of this research is the use of a population that explicitly belongs to numerous co-existing groups at a single time, and whose groups inherently vie for their time within a shared greater context. For example, student-athletes have overt memberships to athletics and the university/specific program, and these groups are inextricably interconnected. A student-athlete is consistently managing the time demands of their athletic and academic requirements, along with a variety of other commitments within their lives (e.g., Adler & Adler, 1991). Although previous samples utilized in social identity research also have many time demands (e.g., university students, stroke recovery patients; Cruwys et al., 2016; Haslam et al., 2008), the membership to two overt mandatory groups in this research is novel. Often, student-athletes face a unique set of challenges and demands, having to balance intensive sport participation while keeping up with their coursework and academic commitments (e.g., NCAA, 2016). Further, when determining where to direct attention, academic performance is frequently compromised for the benefit of sport responsibilities (Bok, 2003). Findings from this thesis suggest that incompatibility experienced among groups also negatively impacted perceptions of athletic performance.

It is also worth discussing associations pertaining to the outcome variables (i.e., academic and athletic performance) in relation to the self-reported and subjective nature of their assessment. Although no relations were demonstrated with group compatibility, preliminary analyses showed perceptions of academic and athletic performance to be positively related to general health quality and emotional health. In line with previous research, this shows relations between student-athlete well-being and performance in these two salient domains (Mooney,

Charlton, Soltanzadeh, & Drew, 2017). Nevertheless, academic performance was not significant for any of the mediation models, and athletic performance was not with the group compatibility models. I would like to note that the original intention for this study was to obtain objective data for the outcome variables, however self-reported single item measures for performance were ultimately used. To provide context for this decision, an agreement was made with a university’s

High-Performance Director to obtain objective measures for academic and athletic performance; however, due to unforeseen circumstances out of my control, this expected outcome was not achieved. As a consequence, I am aware of the limitations involved with self-reported questionnaires, such as the increased possibility of response bias (Campbell & Fiske, 1959) and inflation of inferences for correlational and causal relationships (Borman, 1991). It is possible that some of the variability within the self-reported GPA or athletic performance measures occurred as a result of participants providing inaccurate or socially desirable responses. One benefit of implementing self-report items, however, was the ability to measure how the participants involved thought they were doing in their academic- and sport-based pursuits.

Further, it is also important to consider that previous research on student-athletes’ academic success has primarily used GPA as the primary measurement of student success (e.g., Grandy,

Lough, & Miller, 2016; Meridew et al., 2018). Other variables that may represent academic success, such as attendance, content comprehension, or enjoyment of learning could be considered in future research.

Whereas the current study informs our understanding of the implications for the incompatibility of groups, it is also important to recognize the novel approach utilized within this research. This approach was made possible through the use of the oSIM as a novel instrument to explore social identity generally, and in sport specifically. The ability of this tool to provide a

multidimensional analysis of an individual’s social world allows researchers to consider four distinct indicators of social identity. While this study only considered group compatibility, the ability to also measure the number of groups one belongs to, the relative importance of each group, and the perceived overlap (vs. distinctiveness) of group membership presents numerous future research opportunities. Through the use of the oSIM tool, I was able to assess participants subjective experiences with group membership, while considering the compatibility between their sport group and other identified groups. As such, this research supported the use of this online methodology as a novel way to explore perceptions of social identity in sport.

Specifically, although research has involved interesting approaches such as qualitative methods

(e.g., Bruner et al., 2017) or daily diary research (e.g., Benson & Bruner, 2018), much of the literature in sport to date has utilized self-report questionnaires that were either adapted for the context (e.g., Martin et al., 2018) or sport specific measures (e.g., Bruner & Benson, 2018). The oSIM provides another alternative to researchers interested in exploring social identity in athletic populations, while also enabling them to explore the other three indices not assessed in the current research.

A final important consideration worth discussing involves the intentionality of emphasizing the sport team as the main group of interest. Indeed, group compatibility has typically been assessed by considering all groups identified by an individual equally (Beckwith et al., 2019; Cheng et al., 2008; Cruwys et al., 2016; Iyer et al., 2009). However, a unique aspect of this research was the use of what we have described as an Ego Centered approach. A comparison of these two approaches is depicted in Figure 1 within Chapter 3. This approach was possible because of the unique population chosen, as all participants had a specific group (i.e., sport team) that could be studied as the center of a network. Further, such an approach allowed

us to focus on the compatibility of one group in comparison to all others, which differs from the general compatibility scores obtained across all groups in previous research. It is however also appropriate to mention the potential limitation of using this approach. I acknowledge that I am imposing the idea that sport teams represented the central group for these participants, even though this may not be the case for all of them. However, due to the scarcity of research in this domain, I was most interested in the results pertaining to the athletic group and thus, positioned it as the most central group in terms of this thesis.

Limitations

It is important to acknowledge certain limitations of this research. A main limitation involved the cross-sectional design, which precluded the inference of causality. Since data collection occurred at a single time-point, there is limited information determining the cause and effect relationship between group incompatibility and the outcome variables of interest. Future research could look to replicate these findings through prospective or longitudinal studies, collecting data at multiple time-points throughout an athletic/academic school year. A longitudinal design assessing both perceptions of group compatibility over the duration of a single sport season and/or multiple sport seasons would address this limitation. Frequent data collection periods could also be helpful for this type of research, given the dynamic nature of group processes (Carron & Eys, 2012), and that periods of high demand differ for various groups in university settings (Adler & Adler, 1991). In relation to social identity specifically, recent daily diary research supports the fluctuations that occur in relation to identity perceptions

(Benson & Bruner, 2018), so more frequent completions of the oSIM could be an important next step.

Another limitation involved the delivery method of the oSIM. Although the oSIM was traditionally delivered using paper and pencils, an online version was developed to facilitate analysis and improve user experiences (e.g., Cruwys et al., 2016). Whereas the online protocol enabled a more user-friendly delivery, participants in the current study did report difficulties completing the app on smaller devices such as mobile phones or iPads. The inability of the app to fit properly within smaller screens made it difficult to navigate groups for participants and should be considered in future research when using the oSIM. Providing participants with computers to complete the study, requesting that they bring larger screened devices, or creating a more mobile-friendly version of the oSIM would be advisable. Finally, this study’s population is limited to sport-specific generalizations. Research has yet to examine perceptions of social identity and various constructs across extracurricular settings (e.g., sport compared to drama or school clubs), even though there has been an increase in research longitudinally investigating extracurricular activities with positive developmental outcomes (e.g., Fredericks & Eccles,

2008). With the convenient oSIM methodology, additional research should be conducted in a variety of settings to examine and compare the implications of social identity across group-based and task-oriented contexts.

Future Directions

Being one of the first studies to utilize the oSIM within a university athletics environment, this thesis provides insight for future research on social identity within the sport context. In utilizing this protocol, I was able to highlight the relative significance that group incompatibility can have on participant perceptions of athletic performance through overall and mental well-being, while identifying implications of our results. It is my hope that this research might inform future intervention protocols used to enrich experiences for student-athletes.

In terms of theoretical implications, the use of the oSIM related to important group dynamics constructs seems relevant, whereby this research can be extended to investigate other relevant constructs. As one example, the compatibility of various group identities could be studied to determine if it impacts the cohesiveness experienced within different groups.

Identifying with social groups has already been associated with an improvement in perceptions of cohesion (e.g., Bruner et al., 2014; Ellemers et al., 2004; Jackson & Smith, 1999). A next step would be associating these results with group compatibility; investigating if the compatibility, or incompatibility, between groups then effects the cohesiveness experienced within groups. This could be especially important within sport research, as higher perceptions of cohesion have been associated with increased performance, efficacy, passion, and satisfaction, as well as decreased anxiety and depression (e.g., Carron, Colman, Wheeler, & Stevens, 2002; Kozub & McDonnell,

2000; Paradis, Martin, & Carron, 2012; Spink, Wilson, & Odnokon, 2010). Further, scholars have advanced questionnaires that can reliably assess perceptions of cohesion in academic-based groups (e.g., Bosselut, Heuzé, Castro, Fouquereau, & Chevalier, 2018), which would be a relevant measurement tool for use in student-athlete populations.

Another interesting avenue of research would be exploring the intra-team conflict experiences within various group memberships. It is possible that individuals may experience more intra-team conflict when their groups are causing additional stress (i.e., are incompatible).

Conflict between groups is inevitable (e.g., Robbins & Judge, 2010), which may result in potential negative performance and relationship implications (e.g., De Dreu & Weingart, 2003).

For example, research focused on work performance determined that intra-group conflict was associated with job stress, absenteeism, intentions to leave the group, and reduced productivity

(e.g., Almost, 2006). Accordingly, assessing conflict within groups is essential in understanding

possible potential implications for individuals, including student-athletes. The oSIM is a feasible tool that can be used to highlight groups that may conflict, or not get along, with each other (i.e., incompatible groups) providing researchers with applicable information and allowing them to further investigate the outcomes of intra-team conflict. Considering there is a lack of research pertaining to intra-group conflict within the sport setting (Paradis, Carron, & Martin, 2014), additional research would benefit this field.

Lastly, this research can be used to consider the various roles people occupy in the different groups that they belong to. Perhaps certain groups are more associated with higher status, or more preferable, roles for individuals. The oSIM may be a useful tool that allows researchers to better highlight the various roles participants identify themselves in, and determine if these roles are associated with the compatibility of groups. Literature has shown that in interdependent groups whereby performance is the main goal, the differentiation and specialization of role responsibilities is key to success of their team (Wageman, Fisher, &

Hackman, 2009). Indeed, role clarity and acceptance are critical structural elements involving athletes in sport. For example, how well an athlete understands their role has been positively associated with perceptions of group cohesion, leadership behaviours, and individual role performance (Bray, Beauchamp, Eys, & Carron, 2005; Boselut, McLaren, Eys, & Heuzé, 2012).

Researchers have objectively measured the role expectations and experiences of athletes

(Benson, Eys, & Irving, 2016), so exploring whether these have any relation to the identity experienced across the relevant groups in their lives would be an interesting future direction.

Research involving social identity and youth athletes is steadily accumulating (e.g.,

Bruner et al., 2014; 2015; 2017, Martin et al., 2018). Youth have a need for social interaction and intimacy with their peers (Wagner, 1996), and sport membership has the ability to fulfill a

fundamental human need for belonging (Allen, 2003; Baumeister & Leary, 1995). The oSIM protocol may provide an alternative way to explore social identity perceptions in youth, that goes beyond traditional questionnaire formats. When working with youth, dealing with ethical implications and appropriate methodologies can be difficult (e.g., Greig, Taylor & MacKay,

2013), however researchers advocate for approaches that consider children’s own views and opinions (e.g., Mayall, 2000; O’Kane, 2000). The oSIM protocol is an ideal tool when research is conducted with minority or vulnerable groups such as a youth population (Cruwys et al.,

2016). Having a visual, interactive tool could be enjoyable for them while allowing for active reflection and providing valuable subjective information on their social groups.

Practically, findings from this thesis could also be used to inform future intervention protocols aimed at enriching experiences for student-athletes. Established team building frameworks (e.g., Carron & Spink, 1993) could be used in conjunction with the oSIM to provide coaches with an in-depth understanding of the various groups that their athletes belong to. In fact, coaches have been found to spend a considerable amount of time trying to understand the social interactions and grouping tendencies of their athletes (Martin, Evans, & Spink, 2016).

Given the importance of the social environment in sport (e.g., Eys, Bruner, & Martin, 2019), it is vital for coaches to have a clear understanding of the social dynamics within their teams. The oSIM findings can be used to help coaches understand the demands and social worlds of their athletes, providing them with additional information needed to facilitate team functioning and behaviours.

From an athlete’s perspective, the oSIM can be used as an additional tool to personal- disclosure mutual-sharing (PDMS) team building protocols. The PDMS is used to allow teammates to share their personal experiences and thoughts with others, to develop closer

relationships and get to know their teammates better (e.g., Dunn & Holt, 2004; Barker, Evans,

Coffee, Slater, & McCarthy, 2014). The PDMS has been shown to foster increased empathy, trust, and confidence, by allowing group members to better understand each other’s personal experiences (Dunn & Holt, 2004; Holt & Dunn, 2006). Through incorporating the oSIM into this protocol, athletes could not only share their personal thoughts, but also their social groups and describe what each group means to them. The visual and practical attributes of the oSIM could make it easier for athletes to express their own thoughts and experiences in a unique and meaningful manner. This would allow their teammates and coaches to have a better understanding and appreciation for each individual’s life experience, consequently creating a more positive and accepting environment.

Finally, the oSIM could also be useful in providing athletes with a reflective experience.

Previous literature has highlighted the positive outcomes that are associated with self-reflection in sport, such as maximizing performance enhancement (Jonker et al., 2012), self-awareness, and evaluation skills (Faull & Cropley, 2009). These positive outcomes can be further applied to student-athletes through the use of the oSIM tool. As indicated by Cruwys and colleagues

(2016), this protocol has the ability to potentially change a person’s social-psychological reality, offering a restorative experience for those involved. The oSIM could allow athletes to view and understand their own social worlds, an opportunity that many might not engage with otherwise.

For example, at the end of a sport season or before an important competition, coaches could use this tool to allow student-athletes to reflect on their own lives, and possibly highlight some areas of concern that may need more attention in the future. Coaches have been shown to have the ability to support athlete reflection (Collins & Durand-Bush, 2014), and could therefore use a variation of the oSIM to encourage and facilitate this task. Through the use of this tool, athletes

may be interested in not only understanding and improving the dynamics of their social worlds, but also reflecting on their own personal experiences as student-athletes.

Chapter 6

Conclusion

The incompatibility experienced between a sport team and the remaining groups in a student-athlete’s life has implications for their well-being and perceived athletic performance.

Specifically, using a novel oSIM approach to explore social identity compatibility and situating the research within an Ego Network approach, this study highlighted the negative influence that incompatible groups can have on perceived athletic performance. Additionally, these findings support previous literature involving the importance of QoL and emotional health, whereby these variables mediated the relationship between group incompatibly and sport performance. From this study, we further determined that student-athletes are a population that explicitly belong to numerous co-existing groups at a single time. This population lacks research within the social identity domain, and thus warranted further investigation. The use of the novel oSIM provided us with the ability to focus on group compatibility and allowed for the implementation of an Ego

Network approach.

Future research utilizing specific objective performance outcomes, as well as utilizing the oSIM in divergent contexts, may provide additional support and further our understanding of experiencing multiple social identities, specifically within interuniversity sport. Additional practical uses of this research and the oSIM includes informing intervention protocols, assisting with team building activities, and providing reflective opportunities for student-athletes. I am hopeful that this study will generate further interest in the use of the oSIM within sport research, as well as promote its use to support student-athletes within universities through some of the proposed practical intervention strategies listed above.

Personal Reflection

Completing this thesis has been the most meaningful, worthwhile experience during the course of my academic journey. Throughout the process of completing my thesis, I was able to develop a wide variety of research skills that can be employed in a variety of contexts and research projects. I was able to hone my quantitative research skills, while using novel research methodologies, such as the oSIM, and broadening my understanding of the statistical analysis process. Additionally, learning how to put forward a research question and subsequently, taking the necessary steps to answer that question was a significant aspect of my thesis process. Within any future career or research opportunity, the ability to identify and systematically solve a problem is an extremely valuable skill.

While this opportunity was rewarding, there were also many challenges that tested my abilities as a researcher. The most challenging portion of this thesis was the process of conducting statistical analyses, specifically deciding which analysis to use for my study.

However, this challenge also presented a good learning experience. Knowing my own strengths and weaknesses, I was aware that this portion of my thesis may take more time and patience. I learned to ask for help when needed, and to take the necessary time to understand the foundation of what I was learning. Without understanding where the statistical tests came from, I would not be able to know how to properly use them. As I read about and conducted my statistical analyses,

I became more confident in my abilities as a researcher. I hope to take this experience and apply it to future opportunities, as difficult tasks are inevitable but now I know how to approach and conquer them.

Completing my Master’s thesis was an important step in my journey through academia and working towards my future career. I believe the knowledge I gained from this research has

prepared me for a successful future. This experience not only helped me as a Master’s student, but also as a young professional. Similar to my research topic, I belong to multiple social groups and have numerous social identities within my life. Through my research, I was able to reflect on my past experiences, as an athlete and student, and in the present, as a business owner, student, and employee. I hope to take what I have learned throughout this research process and apply it to my forthcoming research positions, while continuing to develop my skills and challenge myself to become a better researcher. I believe this has been an extremely valuable and humbling experience, that has allowed me to feel more prepared and excited for my upcoming academic and career vocations.

Going forward, I hope to improve the critical analysis aspect of my research process, specifically when constructing my discussion. The amount of logic and in-depth reasoning required to analyze and explain research is vast, yet vital. It is crucial that I am able to present a clear and comprehensive explanation of my research within my writing. This was one aspect of the research process I struggled with, and therefore hope to continue to work on in order to properly analyze, solve, and present my research.

I would be remiss not to comment on the benefit of collaborating with others throughout this research process, whether it be my peers or supervisors. Through partnering with researchers at the University of Queensland, Australia, I had the opportunity to use a novel methodology, the oSIM. The importance of networking and developing meaningful relationships with other researchers was evident throughout my time as a Master’s student. Through these connections, I was able to obtain a variety of opinions and receive feedback for my research, allowing for a more comprehensive understanding of my topic. Receiving this advice from researchers of all standings and fields added to my experience, as they were each able to contribute unique

perspectives towards my project. I hope to continue to connect with others like this in the future, within research and other aspects of my career. Additionally, through the guidance and support provided by my supervisor, I was able to reflect on what it means to be a good mentor and leader. Having a knowledgeable and caring supervisor motivated me to put my best foot forward while working on my thesis, and also emulated the type of leader I hope to be in the future.

Overall, the process of this thesis was an intriguing and engaging experience. I enjoyed incorporating my interest in sport, as well as health quality, into my research topic. I developed many valuable skills and have learned things, that will be useful in my future research and professional careers.

Disclosure statement

No potential conflict of interest is reported by the authors

Funding

This work was supported by the Social Sciences and Humanities Research Council (SSHRC) as a graduate scholarship for the first author.

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Appendix A

Changes to Proposal

Originally, objective measures were proposed for the methods. However, due to recruitment issues, and as approved by all proposal committee members (Drs. Luc Martin, Mark Bruner, and

Tegan Cruwys), we decided to obtain subjective self-reported measures for athletic performance and academic GPA outcomes.

Appendix B

Coach Recruitment Email “Social Identity Mapping for Student-Athletes”

Dear [name of coach], My name is Madison Robertson and I am a Master’s candidate at Queen’s University in the School of Kinesiology and Health Studies. I have obtained your contact information from your university’s athletics website. My area of research is sport psychology and I am recruiting interuniversity athletes for participation in a project that will determine whether athlete’s social identity influences one’s experiences in various contexts, specifically athletic achievement, quality of life, and performance in sport. As such, I would like to ask your athletes to take part in this project. I have attached a letter of information that would be distributed to your athletes to provide them with more information about the proposed project. Should you agree to have your athletes participate, they will be asked to complete an online Social Identity Mapping application, and questionnaires, regarding quality of life. The program and questionnaire should take approximately 25-35 minutes. To thank them for their time, participants who complete the SIM app and questionnaire portion will be placed into a draw to win one of three $50 gift certificates to the university sport store. While there are no direct benefits for your athletes as an participant, they will be making important contributions to our research. We anticipate that this study will help us to better understand the social identity of athletes in interuniversity athletics. I would like to take this opportunity to thank you for the consideration of your team’s involvement. Please do not hesitate to contact me if you have any questions or comments. In addition, if you have any concerns, please feel free to contact the Chair of the General Research Ethics Board at chair. GREB@queensu. ca or 613-533-6081. If you agree to having your athletes review our letter of information, please respond via email or phone at the contact information below. Thank you very much for your time, I look forward to hearing from you. Sincerely,

Madison Robertson, MSc candidate School of Kinesiology and Health Studies Queen’s University 28 Division Street, Kingston, ON, K7L 3N6 Office: KHS 401 Phone: (613) 533-6000 ext. 78207 Email: 12mar9@queensu. ca

Appendix C

Letter of Information for Coaches/Athletes “Social Identity Mapping for Student-Athletes”

This letter is meant to provide information pertaining to a research project for which your team has been invited to participate. This research is being conducted by Madison Robertson, a Master’s candidate under the supervision of Dr. Luc Martin. The studies results will be published in academic journals and conferences, yet all findings will be presented in aggregate form with no identifiable information. This study has been granted clearance by the General Research Ethics Board according to Canadian research ethics principles (http://www. ethics. gc. ca) and Queen's University policies (http://www. queensu. ca/urs/research-ethics).

What is this study about? The purpose of this study is to determine if interuniversity athlete’s experiences with different groups influences their general quality of life and athletic experiences. This study will utilize a Social Identity Mapping App and the completion of two questionnaires (all completed online), and should take approximately 25-35 minutes of your time. Is my participation voluntary? Yes. Although it be would be greatly appreciated if you would answer all material, you should not feel obliged to answer any material that you find objectionable or that makes you feel uncomfortable. You may also withdraw at any time without experiencing negative consequences. A coding sheet will be kept separate from your data to link your name to your data should you wish to withdraw from the study. If you decide to withdraw before or during the study, simply contact Madison Robertson (using the contact information provided at the end of this letter). You should feel absolutely no pressure to take part or continue participation if you do not want to. Furthermore, any reporting of data in publications or presentations will be done in aggregate form. With this in mind, you’re our identity may still be inferred due to the small pool of possible participants. However, we will take every precaution to protect your identity to the best of our abilities.

What are the benefits of participating in this research? There are no direct benefits to you as a participant although you will be making important contributions to our research. We anticipate that this study will help us to better understand the social identity of athletes in interuniversity athletics. To thank you for your time, participants who complete the SIM app and questionnaire portion will be placed into a draw to win one of three $50 gift certificates to the university sport store.

What will happen to my responses? We will keep your responses confidential. The only people who will have access to the identities of participants, through student email, will include Madison Robertson and Luc Martin. Any other members of the research team will only have access to de-identified data and interview transcripts and will have signed a confidentiality agreement. In addition, we will have your name and contact information in a separate location to

that of your questionnaire and recorded interview data. Data will be stored in a controlled access location (e. g., locked office, password protected files) in the School of Kinesiology and Health Studies at Queen’s University for a minimum of seven years after the completion of the study as per University requirements. Although we might present our findings at conferences or in other outlets, no individual information will be included. Should you be interested, you are entitled to a copy of the findings, which could come in the form of the actual refereed publication or a general summary.

What are the risks of participating in this research? There are minor risks associated with participating in this study. Due to a small pool of possible participants, your identity may be inferred even though we report data only in aggregate form. However, we will protect your identity to the best of our abilities. Furthermore, due to the nature of some of the questions, you may be asked to reflect your current health status. In rare instances, this might elicit thoughts of loneliness or lack of belonging, and we will do everything possible to minimize this potential. As a precautionary measure for the rare circumstance that you may become upset following the completion of the app or questionnaire, it is important to understand that you are not required to answer any questions that you are uncomfortable with. You can be provided, from the researcher, with your university student services, local clinics, or phone line through the Canadian Mental Health Association (http://www. cmha. ca/get-involved/find-your-cmha/) if any of these questions trigger emotional distress.

What if I have concerns? Any questions about study participation may be directed to lead researcher Madison Robertson or supervising researcher Luc Martin (contact information below). A I know that I may also contact the Chair of the General Research Ethics Board (613- 533-6081) at Queen’s University or the General Research Ethics Board (GREB) at 1-844-535- 2988 (Toll free in North America) or chair. GREB@queensu. ca (1-613-533-2988 if outside North America) if I have any ethical concerns

Again, thank you. Your interest in participating in this research study is greatly appreciated. Sincerely,

Madison Robertson, MSc candidate Dr. Luc Martin, PhD School of Kinesiology and Health Studies Assistant Professor Queen’s University School of Kinesiology and Health Studies 28 Division Street, Kingston, ON, K7L 3N6 Queen’s University Office: KHS 401 28 Division Street, Kingston, ON, K7L 3N6 Phone: (613) 533-6000 ext. 78207 Office: KHS 301T Email: 12mar9@queensu. ca Phone: (613) 533–6000 x79140 Email: luc. martin@queensu. ca

Appendix D

Online Consent Form/Questionnaire Package “Social Identity Mapping for Student-Athletes”

1. I have read the Letter of Information and have had any questions answered to my satisfaction.

2. I understand that the results will be published in academic journals and conferences, yet all findings will be presented in aggregate form with no identifiable information.

3. I understand that I will be participating in the study titled “Social Identity Mapping for Student-Athletes” which means that I will be asked to complete the following Social Identity Mapping App (10-15 minutes), and questionnaire package (10-15 minutes each) at one time point.

4. I understand that my participation in this study is completely voluntary and that I may withdraw at any time without experiencing any negative consequences. I understand that I may withdraw at any time without experiencing negative consequences. I understand that a coding sheet will be kept separate from my information to link my name to my data should I wish to have my data removed. I also understand that every effort will be made to maintain the confidentiality of the data now and in the future. Only the researchers at Queen’s University will have access to this data. The only people who will have access to the identities of participants, through student email, will include Madison Robertson and Luc Martin. Any other members of the research team will only have access to de-identified data and interview transcripts and will have signed a confidentiality agreement. The data may also be published in professional journals or presented at scientific conferences, but any such presentations will be of general findings and will never breach individual confidentiality. Should I be interested in the findings, I will be entitled to a copy of the results either in publication form or a general summary.

5. I understand there are minor risks associated with participating in this study. However, due to the nature of some of the questions, you may be asked to reflect your current health status. In rare instances, this might elicit thoughts of loneliness or lack of belonging, and we will do everything possible to minimize this potential. As a precautionary measure for the rare circumstance that you may become upset following the completion of the app or questionnaire, it is important to understand that you are not required to answer any questions that you are uncomfortable with. You can be provided, from the researcher, with your university student services, local clinics, or phone line through the Canadian Mental Health Association (http://www. cmha. ca/get-involved/find-your-cmha/) if any of these questions trigger emotional distress.

6. I am aware that if I have any questions, concerns, or complaints, I may contact Madison Robertson (12mar9@queensu. ca) or Luc Martin (luc. martin@queensu. ca). I know that I may also contact the Chair of the General Research Ethics Board (613-533-6081) at Queen’s University or the General Research Ethics Board (GREB) at 1-844-535-2988 (Toll free in North America) or chair. GREB@queensu. ca (1-613-533-2988 if outside North America) if I have any ethical concerns

I have read the above statements and freely consent to participate in this research:  Yes  No

Name: ______Date: ______

*If you would like to receive the summary personally, please include your email address:

______.

Appendix E

Questionnaire 2: Short-Form 36 Health Survey

This survey asks for your views about your health. This information will help keep track of how you feel and how well you are able to do your usual activities! For each of the following questions, please circle the number that best describes your answer.

1. In general, would you say your health is:

Excellent 1

Very good 2

Good 3

Fair 4

Poor 5

2. Compared to one year ago,

Much better now than one year ago 1

Somewhat better now than one year ago 2

About the same 3

Somewhat worse now than one year ago 4

Much worse now than one year ago 5

3. The following items are about activities you might do during a typical day. Does your health now limit you in these activities? If so, how much?

(Circle One Number on Each Line) Yes, Yes,

Limited Limited a a Lot (1) Little (2)

a. Vigorous activities, such as running, lifting heavy objects, 1 2 3 participating in strenuous sports b. Moderate activities, such as moving a table, 1 2 3 pushing a vacuum cleaner, bowling, or playing golf c. Lifting or carrying groceries 1 2 3 d. Climbing several flights of stairs 1 2 3 e. Climbing one flight of stairs 1 2 3 f. Bending, kneeling, or stooping 1 2 3

4. During the past 4 weeks, have you had any of the following problems with your work or other regular daily activities as a result of your physical health?

a. Cut down the amount of time you spent on work or other activities Yes No b. Accomplished less than you would like Yes No c. Were limited in the kind of work or other activities Yes No d. Had difficulty performing the work or other activities (for example, it took extra Yes No effort)

5. During the past 4 weeks, have you had any of the following problems with your work or other regular daily activities as a result of any emotional problems (such as feeling depressed or anxious)?

(Circle One Number on Each Line) a. Cut down the amount of time you spent on work or other activities Ye No b. Accomplished less than you would like Yes No c. Didn't do work or other activities as carefully as usual Yes No

6. During the past 4 weeks, to what extent has your physical health or emotional problems interfered with your normal social activities with family, friends, neighbors, or groups?

Not at all 1

Slightly 2

Moderately 3

Quite a bit 4

Extremely 5

7. How much bodily pain have you had during the past 4 weeks?

None 1

Very mild 2

Mild 3

Moderate 4

Severe 5

Very severe 6

8. During the past 4 weeks, how much did pain interfere with your normal work (including both work outside the home and housework)?

Not at all 1

A little bit 2

Moderately 3

Quite a bit 4

Extremely 5

These questions are about how you feel and how things have been with you during the past 4 weeks. For each question, please give the one answer that comes closest to the way you have been feeling. (Circle One Number on Each Line)

All Most A Some A of of Good of Little

9. How much of the time during the past 4 the the Bit of the of the weeks . . . the Time Time Time Time Time a. Did you feel full of pep? 1 2 3 4 5 6 b. Have you been a very nervous person? 1 2 3 4 5 6 c. Have you felt so down in the dumps that 1 2 3 4 5 6 nothing could cheer you up? d. Have you felt calm and peaceful? 1 2 3 4 5 6 e. Did you have a lot of energy? 1 2 3 4 5 6 f. Have you felt downhearted and blue? 1 2 3 4 5 6 g. Did you feel worn out? 1 2 3 4 5 6 h. Have you been a happy person? 1 2 3 4 5 6 i. Did you feel tired? 1 2 3 4 5 6

10. During the past 4 weeks, how much of the time has your physical health or emotional problems interfered with your social activities (like visiting with friends, relatives, etc. )? (Circle One Number)

All of the time 1

Most of the time 2

Some of the time 3

A little of the time 4

None of the time 5

Definitely 11. How TRUE or FALSE is each of the Definitely Mostly Don’t Mostly False following statements for you. (Circle One True Know Know False Number on Each Line) a. I seem to get sick a little easier than other 1 2 3 4 5 people

b. I am as healthy as anybody I know 1 2 3 4 5 c. I expect my health to get worse 1 2 3 4 5 d. My health is excellent 1 2 3 4 5

Appendix F Questionnaire 1: Demographics Name: ______

Age (in years): ______

Gender:  Female  Male  Other

Hometown: ______

Do you currently live at home:  Yes  No

How many roommates do you have: ______

How many roommates are also teammates: ______

Program of Study: ______Year of Program: ______

Current GPA: ______

Sport: ______

Year of Eligibility: ______

Current position on team: ______

Are you a formal leader (i.e., designated team captain)  Yes  No

Are you an informal leader (i.e., mentor, role model, representative)  Yes  No

Likert out of 10 (Out of 10 please describe in comparison to others in the same sport who take part in your position and at this level of competition, how you describe your athletic performance right now)

Please describe at this point in the season where you would rate your team’s performance out of a possible 0 to 10, 0 being very poor and 10 being outstanding)

Appendix G

Confidentiality Agreement

Staff/Student Name: I acknowledge that Queen's University at Kingston (hereinafter called "Queen's") has in its possession, and with the authority to disclose, in confidence, certain information (“Confidential Information”) relating to specific research projects being conducted by Madison Robertson under the supervision of Dr. Luc Martin in the field of sport and exercise psychology. Confidential Information includes, without limitation, computer programs, discoveries, inventions, techniques, documents, data and information concerning the study or other research programs of Researcher or his/her affiliates, and of information with respect to Researcher's patients or staff. The Confidential Information will be given to me in order to perform duties as a research assistant (the “Work”) related to the Researcher’s project(s). In consideration of working on such project(s), I agree that I will keep in confidence and trust all Confidential Information and will not directly or indirectly use the Confidential Information, nor disclose any Confidential Information to any person or entity, except in the course of performing duties assigned with respect to the studies. I agree that I shall be free to use information that: a. is known to me prior to the receipt of the said Confidential Information from Queen's as evidenced by written documentation; or b. lawfully is or becomes public knowledge through no default of this Agreement; or c. is provided to me by any third party with a bona fide right to do so; or d. is approved for release by written permission of the Vice Principal (Research) of Queen's University

Upon the termination of the Work, I undertake to return all Confidential Information pertaining thereto which has been provided by Queen's and all copies thereof or to destroy the same at the option of Queen's. This agreement is to be effective upon the date of signing, and shall be interpreted and construed in accordance with laws of the Province of Ontario, Canada.

By: ______

Dated at ______this ______day of ______, 20___.

Witness: ______

Please retain a copy of this agreement for your records and provide one to the Researcher. I understand that the researcher may acknowledge the use of my services in any reporting on the research. I have indicated below whether I wish that acknowledgement to be anonymous or whether it may recognize me by name.

 I do NOT wish my name to be associated with the acknowledgement of the use of a data collector in data gathering for the research.

Any questions about study participation may be directed to lead researcher Madison Robertson or supervising researcher Luc Martin (contact information below). Any ethical concerns about the study may be directed to the Chair of the General Research Ethics Board at chair. GREB@queensu. ca or 613-533-6081.

Sincerely,

Madison Robertson, MSc candidate Dr. Luc Martin, School of Kinesiology and Health Studies Assistant Professor Queen’s University School of Kinesiology and Health Studies 28 Division Street, Kingston, ON, K7L 3N6 Queen’s University Office: KHS 401 28 Division Street, Kingston, ON, K7L 3N6 Phone: (613) 533-6000 ext. 78207 Office: KHS 301T Email: 12mar9@queensu. ca Phone: (613) 533–6000 x79140 Email: luc. martin@queensu. ca

Appendix H

Completed oSIM Network

Note: Figure example of a participants completed oSIM network