Profiling Physical Activity Motivation Based on Reasons for Exercise: A Cluster Analysis Approach

Autor: Vanessa M. (Martinez) Kercher, Damon Burton, Michael A. Pickering, Kyle Kercher
Rok vydání: 2022
Předmět:
Zdroj: Psychological Reports. :003329412211194
ISSN: 1558-691X
0033-2941
DOI: 10.1177/00332941221119413
Popis: The purpose of this study is to identify profiles based on the reasons adults have for being physically active. A secondary purpose was to examine how profiles differ on motivational regulation and physical activity (PA). A total of 1275 (46.5 ± 16.8 years) participants were solicited from a hospital-affiliated wellness center, social media promotions, and a research volunteer registry. The Reasons to Exercise (REX-2) scale, International PA Questionnaire, Behavioral Regulation in Exercise Questionnaire-3, and demographic questionnaire were utilized to assess variables of interest with a cross-sectional survey. Using SPSS Version 26, K-cluster analysis was used to identify profiles based on the reasons for exercise that individuals identified as important. Multivariate analysis of variance (MANOVA) was used to assess profile differences followed by ANOVA. Four profiles were derived based on reason for exercise scores: a multi-reason positive ( N = 361), a multi-reason negative ( N = 232), an autonomous-focused ( N = 259), and a control-focused cluster ( N = 382) ( p < .001). These unique clusters differed significantly ( p < .001) from each other with respect to motivation to be active and PA. The multi-reason positive cluster engaged in higher levels of total moderate and vigorous PA minutes/week compared to the other clusters. Therefore, adult’s motivation for PA may be likely to be affected by a combination of different informal goals and valuing a number of goals that are both extrinsic/controlling (e.g., to look good) and autonomous/intrinsic (e.g., to feel good), may promote greater autonomous motivation regulation and greater PA levels than highly autonomous/intrinsic goals alone.
Databáze: OpenAIRE