Evaluating the Implementation and Effectiveness of the SWITCH-MS: An Ecological, Multi-Component Adolescent Obesity Prevention Intervention.

International journal of environmental research and public health(2020)

引用 1|浏览14
暂无评分
摘要
Background: The purpose of this study was to evaluate the implementation and effectiveness of an ecological, multi-component adolescent obesity prevention intervention called School Wellness Integration Targeting Child Health-Middle School (SWITCH-MS). Methods: Following the effectiveness-implementation hybrid type 3 quasi-experimental design, seven middle schools (377 students) in Iowa, United States, were stratified into "experienced" (n = 3; 110 students) or "inexperienced" (n = 4; 267 students) groups to receive the 12-week SWITCH-MS intervention. To evaluate implementation, school informants (n = 10) responded to a survey and students completed behavioral tracking in the classroom on a website. For effectiveness evaluation, students in 6th, 7th, and 8th grades completed a validated questionnaire before and after intervention, to measure behaviors of physical activity (PA; "Do"), screen-based activity ("View"), and fruits and vegetable consumption ("Chew"). Results: The two groups of schools showed similar levels of implementation for best practices, awareness, and engagement. Behavioral tracking rate favored the experienced schools early on (47.5% vs. 11.7%), but differences leveled off in weeks 3-12 (sustained at 30.1-44.3%). Linear mixed models demonstrated significant time effects for "Do" (at school and out of school; p < 0.01) and "View" behaviors (p = 0.02), after controlling for student- and school-level covariates. Conclusions: This study demonstrates that prior experience with SWITCH-MS may not be a prominent factor for implementation and effectiveness, although greater experience is associated with favorable behavioral tracking when the intervention is first launched.
更多
查看译文
关键词
healthy-living behaviors,implementation science,obesity prevention,program evaluation,school wellness
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