Predicting recreation priorities

Abstract

Non-profit recreation departments are in the business of predicting and meeting constituents' recreation needs. However, scant research has been conducted that examines factors that determine these needs. Recreation need can be defined as the priority that constituents assign different recreation initiatives that an agency might undertake. Antecedents of recreation priorities may include demographic characteristics, activity participation, life stage, and constraints. The purpose of this study was to determine the relative contribution of these factors for predicting recreation priorities. Data was collected using a self-administered questionnaire distributed to all households at Fort Hood military housing post in Texas. The questionnaire was designed with focus group input to ascertain what activities, constraints, and recreation priorities families perceive on post. Respondents were also asked to indicate the ages of household members, their income, and education level. Data was collected in Spring 2002 and yielded 1,078 useable questionnaires, which constituted a 19.2% response rate. Factor analyses with principal component extraction and Varimax rotation was undertaken to determine categories of activity participation, constraints, and recreation priorities. Then, multiple linear (hierarchical) regression was performed to explore relationships. Adjusted R² values, R² change, and standardized beta coefficients were examined to establish the relative contribution of independent variables. Study respondents were largely married (92%), female (82%), the spouses of military personnel (63%), and had children living at home (65%). Regression analyses revealed that life stage variables were the best predictors of recreation priorities. Constraints were the second best predictors. Little relationship was observed between respondents' demographic characteristics and their recreation priorities. Results indicated that respondents prioritized recreation initiatives that would improve their individual or family recreation. However, just 11% of variance was explained with even the best regression model. These findings suggest that recreation and park practitioners must consider including life stage variables when assessing constituent recreation priorities. Leisure researchers should take note of the viability of constraints as an independent variable. Furthermore, researchers can regard these findings as a first step in theory development of recreation priorities.