Saf Health Work.
2019 Mar;10(1):95-102. 10.1016/j.shaw.2018.08.002.
Process Evaluation of a Mobile Weight Loss Intervention for Truck Drivers
- Affiliations
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- 1School of Public Health, Oregon Health & Science University and Portland State University, Portland, USA. bwipfli@pdx.edu
- 2Oregon Institute of Occupational Health Sciences, Oregon Health & Science University, Portland, USA.
- 3School of Nursing, John Hopkins University, Baltimore, USA.
- 4Division of Health Promotion & Sports Medicine, Oregon Health & Science University, Portland, USA.
- 5Department of Psychology, Portland State University, Portland, USA.
- 6Center for Health Research, Kaiser Permanente Northwest, Portland, USA.
- KMID: 2447329
- DOI: http://doi.org/10.1016/j.shaw.2018.08.002
Abstract
- 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 postintervention 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.
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