GETTING AHEAD OF THE GAME: A PREVENTATIVE ASSESSMENT PLAN FOR INTERCOLLEGIATE ATHLETICS

While we know much about the psychology of sport, little gets translated onto the playing field. Typically, there is only consultation when a problem arises or when performance falls short. The purpose of this study was mainly exploratory in order to gather data on three factors of mental health, find any associations between those factors, and to predict any risk factors using demographic variables. Three validated measurement tools were used to measure burnout (Athlete Burnout Questionnaire; Raedeke & Smith, 2004), depression (Beck Depression Inventory-II; Beck et al., 1996), and transition readiness (British Athletes Lifestyle Assessment Needs in Career and Education; Lavallee & Wylleman, 1999). The three measures (ABQ, BDI, and BALANCE) were found to be positively associated based on non-parametric correlation analyses. Medium to large effect sizes were found between each pair, indicating that there are possibly shared factors between depression, burnout, and transition risk. Multiple regression analyses indicated no significant demographic predictors of burnout, depression, or transition readiness. The results of this study show that most student-athletes in this sample are at mild risk for burnout, depression, and transition issues. Mental health screenings, like this one, can provide valuable information to athletic administrations and help avoid larger issues in the future

Running for Your Life: Motivational Factors for Increased Physical Activity

The purpose of this study was to examine the relationship between message framing and behavioral expectancy in maintenance stage runners. Further, correlational analyses were computed to examine the relationship between level of motivation and Locus of Control (LOC). Motivation and LOC were measured before the participant was presented with positively, negatively, or neutrally framed messages (based on random assignment). Participants then answered a level of behavioral expectancy (i.e., how likely or unlikely they are to engage in this behavior) and an explanation of cognitive evaluation in the form of a qualitative question (why the provided message was persuasive or not). This stage was operationalized as running for at least one year, competing in at least one race per year, and running at least one mile per week. The sample consisted of mTurk (Amazon’s Mechanical Turk) users. Results indicated that the neutral message framing condition was significantly different in terms of behavioral expectancy from that of both the positive and negative message framing conditions. The positive and negative message framing conditions, however, did not result in significant differences in behavioral expectancy. Finally, while Locus of Control and levels of motivation are positively correlated in the literature, there was no significant correlation between these variables in this study. Conclusions from this research can be used to inform future health campaigns directed towards those already engaging in physical activity. Furthermore, results can be used to inform future research on message framing in non-active populations