Predicting student involvement in campus recreation programs

Purpose: To identify factors that predict the frequency of campus recreation (CR) use at a 4-year, public university in the mid-Atlantic region. Methods: Students were given an online survey to collect a variety of student lifestyle and health information, including campus residency status, gender, year, height, weight, academic discipline, semester credit hour enrollment, and job hours per week during the semester. Analysis participants (n = 1561) were divided into two subsets, one with 90% of the subjects, and one with 10% of the subjects. A stepwise multiple regression analysis was performed on the 90% subset with the predictor variables. Two regression equations were generated, one for predicting CR access in minutes per semester and the other for predicting access in days per semester. The 10% subset of participants was then used to cross validate the regression equations using a Pearson Product Moment correlation and a T test for paired comparisons. Results: An individual’s academic discipline (t = -4.788, p = 0.000) and gender (t = 2.329, p = 0.020) were significant predictors of CR minutes per semester (r2 = 0.036). The CR days per semester were significantly predicted (r2 = 0.049) by an individual’s academic discipline (t = -4.805, p = .000), gender (t = -2.211, p = .027), job hours per week (t = -2.338, p = .020), and campus residency (t = -2.385 p = .017). In the cross validation group, actual CR minutes per semester and predicted minutes per semester were significantly correlated (r = 0.164, p = 0.035) and CR reported and predicted CR days per semester were significantly correlated (r = 0.328, p = 0.002). There were no significant differences (p \u3e 0.05) between the actual and predicted values within the cross validation group. Conclusion: Academic discipline and gender were found to be significant predictors of CR access in minutes per semester, while academic discipline, gender, job hours per week, and campus residency were shown to be significant predictors of CR use in days per semester. The usefulness of these variables as predictors is limited, as indicated by the low R2. CR administrators can use these predictors in order to develop effective ways to increase student participation