Process Evaluation of a Mobile Weight Loss Intervention for Truck Drivers

Wipfli, Brad; Hanson, Ginger; Anger, Kent; Elliot, Diane L.; Bodner, Todd; Stevens, Victor; Olson, Ryan

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자료유형: 학술저널

저자정보: Wipfli, Brad (School of Public Health, Oregon Health & Science University and Portland State University) Hanson, Ginger (School of Nursing, John Hopkins University) Anger, Kent (Oregon Institute of Occupational Health Sciences, Oregon Health & Science University) Elliot, Diane L. (Division of Health Promotion & Sports Medicine, Oregon Health & Science University) Bodner, Todd (Department of Psychology, Portland State University) Stevens, Victor (Center for Health Research, Kaiser Permanente Northwest) Olson, Ryan (Oregon Institute of Occupational Health Sciences, Oregon Health & Science University)

저널정보: 산업안전보건연구원 Safety and health at work : SH@W Safety and health at work : SH@W 제10권 제1호

발행연도: 2019.1

수록면: 95 - 102 (8page)

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Background: In a cluster-randomized trial, the Safety and Health Involvement For Truck drivers intervention produced statistically significant and medically meaningful weight loss at 6 months (-3.31 kg between-group difference). The current manuscript evaluates the relative impact of intervention components on study outcomes among participants in the intervention condition who reported for a post-intervention health assessment (n = 134) to encourage the adoption of effective tactics and inform future replications, tailoring, and enhancements. Methods: The Safety and Health Involvement For Truck drivers intervention was implemented in a Web-based computer and smartphone-accessible format and included a group weight loss competition and body weight and behavioral self-monitoring with feedback, computer-based training, and motivational interviewing. Indices were calculated to reflect engagement patterns for these components, and generalized linear models quantified predictive relationships between participation in intervention components and outcomes. Results: Participants who completed the full program-defined dose of the intervention had significantly greater weight loss than those who did not. Behavioral self-monitoring, computer-based training, and health coaching were significant predictors of dietary changes, whereas behavioral and body weight self-monitoring was the only significant predictor of changes in physical activity. Behavioral and body weight self-monitoring was the strongest predictor of weight loss. Conclusion: Web-based self-monitoring of body weight and health behaviors was a particularly impactful tactic in our mobile health intervention. Findings advance the science of behavior change in mobile health intervention delivery and inform the development of health programs for dispersed populations.

#Intervention process evaluation #Mobile health #Occupational health #Weight loss

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