谷歌浏览器插件
订阅小程序
在清言上使用

Identifying the Most Proximal Multi-Level Factors Associated with Meeting Each of the 24-H Movement Behavior Recommendations in a Sample of Autistic Adults.

Disability and health journal(2022)

引用 0|浏览17
暂无评分
摘要
Background: Autistic adults have poorer 24-h movement behaviors, including lower levels of physical activity, more time spent being sedentary, and shorter sleep duration than neurotypical adults. Social ecological frameworks posit that 24-h movement behaviors are determined by multi-level domains; however, not known is which multi-level factors are most important to meeting each of the 24-h movement behavior guidelines among autistic adults.Objective: This study examined the relative importance of a range of multi-level determinants on meeting guidelines for the 24-h movement behaviors of aerobic physical activity, sedentary behavior, and sleep.Methods: We administered at cross-sectional electronic survey to a national self-selecting, convenience sample of autistic adults and caregivers of autistic adults residing in the USA. We used machine learning to examine the relative variable importance (VIMP) of 55 multi-level variables with meeting recom-mendations for physical activity, sedentary behavior, and sleep duration. VIMPs >0 indicate predictive variables/domains.Results: A greater number of group activities attended in the last 3-months, and greater independence in completing activities of daily living were most important to meeting aerobic physical activity guidelines. Group activity participation and marital status were important to meeting sedentary behavior guidelines while having a fewer number of comorbidities was most important to achieving adequate sleep.Conclusions: These data support hypotheses about the role of family and social level interventions tar-geting movement behaviors in autistic adults.(c) 2022 Elsevier Inc. All rights reserved.
更多
查看译文
关键词
Sleep duration,Physical activity,Sedentary behavior,Social -ecological,Autism spectrum disorder,Machine -learning
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要