Examining The Potential for Psychosocial Variables to Predict Summer Workout Completion for Collegiate Basketball Players

Andy Gillham, University of South Dakota College, USA
Eva Gillham, Educational Services of America, USA

Theme: Motivation and self-perceptions

Poster Number: 50

Program ID: POS-1

Presentation: October 3, 2013 5:30 pm - 7:00 pm

Room: Napoleon


The 2010-2011 NCAA Division II Manual rule states that when school is not in session and the team is out of season, athletes can only participate in voluntary activities. The present study was conducted to examine various antecedent psychosocial variables (i.e., motivational climate, athlete burnout, motivational style and sport confidence) and their effect on the percentage of summer workouts completed by Division II collegiate basketball players. A sample of 252 varsity college basketball players completed a comprehensive instrument packet that included the Perceived Motivational Climate in Sports Questionnaire-2 (PMCSQ-2; Newton, Duda, & Yin, 2000), Competitive Motivational Styles Questionnaire (CMSQ; Gillham, Gillham, & Burton, 2012), Sources of Sport Confidence Questionnaire (SSCQ; Vealey, Hayashi, Garner-Holman, & Giacobbi; 1998), and Athlete Burnout Questionnaire (ABQ; Raedeke & Smith, 2001) within the first three weeks of their competitive season. A second data collection asking for only the percentage of summer workouts completed took place via e-mail approximately five months after the conclusion of the athletes’ competitive seasons. Bivariate correlations and regression analysis were used to determine the relationships among antecedent and consequent variables. Significant correlations of workout percentage to motivational climate split in accordance with task climate subscales (i.e., positive) and ego climate subscales (i.e., negative). Negatively valenced subscales (i.e., failure evader from CMSQ and three from the ABQ) demonstrated significant inverse relationships with the percentage of workouts completed. All variables exhibiting a significant correlation with percentage of workouts completed were utilized for regression analysis. R was significantly different from zero, F(12, 90) = 3.284, p < .01, with R2 = .336 and adjusted R2 was .233. These results provide insight for coaches, especially for athlete recruitment and role identification. The potential to expand this work to exercisers by identifying profile characteristics related to exercise adherence will also be discussed.

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