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Process Evaluation of a Mobile Weight Loss Intervention for Truck Drivers

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 co...

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Autores principales: Wipfli, Brad, Hanson, Ginger, Anger, Kent, Elliot, Diane L., Bodner, Todd, Stevens, Victor, Olson, Ryan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Occupational Safety and Health Research Institute 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6428992/
https://www.ncbi.nlm.nih.gov/pubmed/30949387
http://dx.doi.org/10.1016/j.shaw.2018.08.002
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author Wipfli, Brad
Hanson, Ginger
Anger, Kent
Elliot, Diane L.
Bodner, Todd
Stevens, Victor
Olson, Ryan
author_facet Wipfli, Brad
Hanson, Ginger
Anger, Kent
Elliot, Diane L.
Bodner, Todd
Stevens, Victor
Olson, Ryan
author_sort Wipfli, Brad
collection PubMed
description 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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spelling pubmed-64289922019-04-04 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 Saf Health Work Original Article 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. Occupational Safety and Health Research Institute 2019-03 2018-08-21 /pmc/articles/PMC6428992/ /pubmed/30949387 http://dx.doi.org/10.1016/j.shaw.2018.08.002 Text en © 2019 Occupational Safety and Health Research Institute http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Original Article
Wipfli, Brad
Hanson, Ginger
Anger, Kent
Elliot, Diane L.
Bodner, Todd
Stevens, Victor
Olson, Ryan
Process Evaluation of a Mobile Weight Loss Intervention for Truck Drivers
title Process Evaluation of a Mobile Weight Loss Intervention for Truck Drivers
title_full Process Evaluation of a Mobile Weight Loss Intervention for Truck Drivers
title_fullStr Process Evaluation of a Mobile Weight Loss Intervention for Truck Drivers
title_full_unstemmed Process Evaluation of a Mobile Weight Loss Intervention for Truck Drivers
title_short Process Evaluation of a Mobile Weight Loss Intervention for Truck Drivers
title_sort process evaluation of a mobile weight loss intervention for truck drivers
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6428992/
https://www.ncbi.nlm.nih.gov/pubmed/30949387
http://dx.doi.org/10.1016/j.shaw.2018.08.002
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