The limitations outlined above provide a concise guide for designing future research on elite athlete motivation and mental health.
7.7.1 Sample
1) Successful and world-class elite (Swann et al., 2014) teams could be recruited in order to elucidate the motivation and mental health of athletes competing at the highest level. Given the unique and severe stressors that such athletes face (Hughes & Leavey, 2012), their inclusion would likely reveal novel findings related to the variables investigated in this thesis. In order to facilitate this, it could be necessary to recruit athletes from different countries, which would be possible due to the online data collection system. Previous research has shown motivational differences by country and culture (Chantal et al., 1996), making the inclusion of such athletes potentially impactful.
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2) Individual sport athletes could be recruited because they likely would provide different data to team-sport athletes (e.g., Lastella, Roach, Halson, & Sargent, 2015). For example, such athletes may report lower relatedness scores due to the absence of teammates, but higher competence scores due to their lack of reliance on others to execute their skills. Notably, inventories (e.g., PMCSQ-II) may have to be modified or replaced for such a sample because their items (e.g., “on this team, the coach thinks only the starters contribute to the success of the team”) do not apply to individual sport athletes.
3) Male and female teams in each sport could be recruited because they experience similar schedules, demands, training loads, et cetera, thereby facilitating direct comparisons. 4) Analyses comparing the data of “improvers” versus “non-improvers” could provide
interesting findings related to motivation and mental health. Specifically, motivation and mental health may be characterised differently between the two groups and/or there may be unique cross-sectional and longitudinal associations that point to why the groups responded differently to sport involvement (e.g., greater perceptions of a task climate among those whose sleep quality improved over time).
7.7.2 Measures
1) A measure of basic needs thwarting could be considered for future studies that integrate motivation-related and mental health variables. The Psychological Need Thwarting Scale (Bartholomew, Ntoumanis, Ryan, & Thøgersen-Ntoumani, 2011) could complement the BNSSS, allowing for concurrent assessment of negative and positive experiential states, respectively, and potentially revealing more comprehensive findings related to mental health outcomes.
2) In order to move beyond athletes’ self-reported perceptions of the environment, which may not equate with observed behaviours (Smith, Tessier, et al., 2016), future studies could utilise an observational tool (Smith, Quested, et al., 2016) to measure the motivational climate. The Multidimensional Motivational Climate Observation System (Smith, Tessier, et al., 2015) could be an ideal choice because it draws from both SDT and AGT perspectives, and contains lower order behavioural strategies that may be associated with basic needs, motivation, and related outcomes.
3) Carefully chosen supplementary data could be gathered from athletes in order to more comprehensively analyse their motivation and mental health. For example, game schedules and results, minutes played, injury status, and training load plausibly have
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associations with motivation (e.g., Lemyre et al., 2006) and mental health (e.g., Yang et al., 2014), and would be of interest to stakeholders from a practical viewpoint.
7.7.3 Design
1) The compliance-promotion strategies outlined above are all researcher-based and, therefore, could be supplemented with participant-based strategies in future longitudinal research (Trost, McIver, & Pate, 2005). For example, the athletes could be asked to complete a weekly log with a time and checkmark to indicate that they have engaged in monitoring. Beyond this, further researcher-based strategies could include posting reminder signage in locker rooms, and regularly visiting teams to provide in- person reminders and reinforce that scores are being monitored consistently. It could also be useful for researchers to provide broad feedback during the season so that athletes feel they are getting something tangible from their participation. An important consideration in this regard would be not to provide so much data that athletes change their behaviour, given that the purpose of the study is to monitor, rather than intervene. In line with this, showing athletes an example of output during the introductory presentation could increase interest from the outset. Similarly, advising athletes that their data will inform the development of a targeted off-season intervention (e.g., Smith et al., 2007) could be another useful strategy to improve compliance because it emphasises that they will benefit from participation.
2) It could be effective to align the data collection schedules for each team, such that the pre- and post-season measures are at consistent points (e.g., two weeks before first game and two weeks after last game). Although a uniform data collection period could also be optimal for future research, it may present challenges when sports have different season lengths. That is, 25 weeks may capture the full season for basketball, but not soccer. However, specifying a minimum data collection period that incorporates at least three administrations of the motivation-related measures would allow trajectories to be examined more accurately. In Chapter Six, two teams did not reach the 25-week mark, resulting in their exclusion from motivation-related analyses over three time points. 3) Given the cross-sectional SEM in Chapter Four and longitudinal associations reported
throughout this thesis, it could be fruitful to explore a longitudinal SEM between motivation-related and mental health variables. In particular, a cross-lagged panel model (e.g., Lonsdale & Hodge, 2011) would be optimal for testing reciprocal effects. The current data could facilitate a three-wave model because nine club teams
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participated in 25 or more weeks of data collection, thereby reporting scores for motivation-related variables three times. In order to test the most parsimonious model, it could be useful to omit variables that were less inter-related with other variables in this thesis (e.g., sleep quality), and to utilise the SDI to represent the six motivation regulations (e.g., Hein & Jõesaar, 2014).
4) A coach-based motivational climate intervention could be a useful approach for translating the findings from this thesis into practice. For example, a 12-week intervention combining fortnightly meetings and educational booklets regarding need supportive strategies has been shown to improve motivation and related outcomes in team sports (Langan et al., 2015). Such a study could examine the feasibility of a coach- based intervention in improving motivation and subsequent mental health, and potentially provide implications for future parent/peer-based interventions.
7.8 Conclusion
This thesis comprises the first body of peer-reviewed research that concurrently assesses seven motivation-related and mental health variables among semi/competitive-elite athletes over an extended period of time. It characterises and quantifies changes in these variables, thereby facilitating an in-depth comparison of student-athletes and club athletes, while also investigating cross-sectional and longitudinal associations between variables. In doing so, this thesis supports and extends theoretical knowledge by linking two areas that are rarely studied together. It also provides practical implications for stakeholders in elite sport, and guidance for future research in sport psychology. Beyond longitudinally characterising the motivation and mental health of 253 elite team-sport athletes, the data support the predominant stability of the former and instability of the latter. It is evident that mental health improves as the athletic season progresses, which is consistent with some, but not all, previous studies. Additionally, the SEM posits that mental health should be considered as an outcome of motivation in the HMIEM, such that different motivation regulations can promote or undermine mental health. In line with this, the data reveal numerous novel cross-sectional and longitudinal associations between motivation-related and mental health variables, potentially indicating reciprocal relationships between the two areas. That is, it is possible that mental health may influence motivation, which is an important consideration for future research and practice. Collectively, the results of this thesis have important messages for the field of sport psychology and potentially beyond, in that insights into motivation and mental health are likely applicable to other domains in which behaviour change and well-being are valued.
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