心理学
教练
感知
集合(抽象数据类型)
目标设定
应用心理学
焦点小组
社会心理学
营销
计算机科学
业务
神经科学
程序设计语言
作者
Julie A. Partridge,Bobbi A. Knapp,Brittany D. Massengale
出处
期刊:Journal of Strength and Conditioning Research
[Ovid Technologies (Wolters Kluwer)]
日期:2013-10-21
卷期号:28 (6): 1714-1721
被引量:85
标识
DOI:10.1519/jsc.0000000000000288
摘要
CrossFit is a growing fitness trend in the United States; however, little systematic research has addressed specific motivational principles within this unique exercise environment. The purpose of the study was to explore the influence of gender and membership time on perceptions of motivational climate and goals within the CrossFit environment. Specifically, people may set goals related to self-improvement (i.e., mastery) or focus on their performance in comparison to others (i.e., performance). Motivational climate refers to an individual's perception of being encouraged to focus on either mastery or performance goals from CrossFit trainers. A total of 144 members (88 females; 56 males) completed questionnaires to assess participants' perceptions of CrossFit goal structures and perceptions of the motivational climate encouraged by the trainer within their CrossFit box. Results indicated a significant main effect for gender on preferred goals (p ≤ 0.05), with males reporting higher levels of performance approach goals and females reporting higher levels of master avoidance goals. Participants who reported shorter membership times were found to have significantly higher mastery-related goals than individuals who reported longer membership times (p ≤ 0.05). The results from the study suggest that practitioners should consider how perceptions of the motivational climate and goals in group-based exercise settings such as CrossFit may vary based on demographic variables, and that these differences may impact how to most effectively motivate, encourage, and instruct group members, particularly with regard to helping members set goals that most effectively address their approach to the CrossFit regimen.
科研通智能强力驱动
Strongly Powered by AbleSci AI