Short report: moderations in exercise motivation - gender and age moderates the relations of motivation quality and exercise behavior

简报:运动动机的调节因素——性别和年龄调节动机质量与运动行为之间的关系

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Abstract

AIMS: Self-determined motivation has been found to be an important predictor of exercise behavior. Findings on gender and age differences are however mixed and previous research has called for studies to examine gender and age as potential moderating factors as they might influence how motivation quality affects exercise behavior. METHODS: Embedded in a controlled trial of a digital intervention aiming to promote exercise motivation, this study examined specific (longitudinal) pathways related to motivation quality, psychological need satisfaction and exercise behavior within the self-determination theory (SDT) process model in a sample of 318 adult employees. The participants completed web-based versions of Basic Psychological Needs in Exercise Scale, Behavioural Regulations in Exercise Questionnaire-2, and Leisure Time Exercise Questionnaire three times during a six weeks period. RESULTS: Moderation analyses revealed significant gender and age differences in the associations of motivation quality, basic psychological needs and exercise behavior over time. Several paths in the SDT-process model, linking psychological needs and motivation quality to exercise behavior, were moderated by gender and age. The stipulated mechanisms between exercise, motivation and psychological need satisfaction in the SDT-process model revealed to be stronger for women than for men, and stronger for older adults than for younger and middle-aged adults. The effect of amotivation on exercise was also significantly moderated by age in the full sample, by positively predicting light exercise for younger adults. CONCLUSIONS: Future recommendations are related to the examination of potential differences in opportunities of autonomy support in the social context based on factors such as gender and age, and also to further examine these factors as potential moderators instead of statistically controlling them as default.

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