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A Computerized Lifestyle Application to Promote Multiple Health Behaviors at the Workplace: Testing Its Behavioral and Psychological Effects

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TLDR
Matching an intervention to the motivational readiness of employees can make a health promotion program effective, and employees’ motivation, planning, social support, and lifestyle can be supported by a stage-matched intervention that focuses on both physical activity and healthy nutrition.
Abstract
Background: Preventive health behaviors, such as regular physical activity and healthy nutrition, are recommended to maintain employability and to facilitate the health of employees. Theory-based workplace health promotion needs to include psychological constructs and consider the motivational readiness (so-called stages of change) of employees. According to the stages, people can be grouped as nonintenders (not motivated to change and not performing the goal behavior), intenders (decided to adopt the goal behavior but not started yet), or actors (performing the goal behavior already). The tailoring to these stages can be done computer based and should make workplace health promotion more effective. Objective: It was tested whether a parsimonious computer-based health promotion program implemented at the workplace was effective in terms of lifestyle changes and psychological outcomes as well as body weight. We hypothesized that the stage-matched intervention would outperform the one-size-fits-all active control condition (standard care intervention). Methods: In a randomized controlled trial, a total of 1269 employees were recruited by a trained research assistant at their workplace during a routine medical examination. After excluding noneligible employees, 560 completed Time 1 (T1), and 384 also completed Time 2 (T2), achieving a retention rate of 68.6%. Two fully automated computer-based treatments were adopted: (1) an active control condition with information about benefits of exercise and healthy nutrition (n=52), or (2) a stage-matched multiple-behavior intervention that provided different psychological treatments to 9 subgroups, addressing stages of change (nonintenders, intenders, and actors per behavior; n=332). Baseline assessments (T1) on behavior, psychological constructs, and body weight were repeated after 4 weeks (T2). Results: The stage-matched intervention outperformed the active control condition for lifestyle changes containing physical activity and nutrition (χ 2 1 =3.5; P =.04, for N=384) as well as psychological variables (physical activity intention, P =.04; nutrition intention, P =.03; nutrition planning, P =.02; and general social support to live healthily, P =.01). When predicting a healthy lifestyle at follow-up, baseline lifestyle (odds ratio, OR, 2.25, 95% CI 1.73-2.92; P <.01) and the intervention (OR 1.96, 95% CI 1.00-3.82; P =.05) were found to be significant predictors. Physical activity planning mediated the effect of the intervention on the adoption of an overall healthy lifestyle (consisting of activity and nutrition, R 2 adj =.08; P <.01), indicating that if the stage-matched intervention increased planning, the adoption of a healthy lifestyle was more likely. Conclusions: Matching an intervention to the motivational readiness of employees can make a health promotion program effective. Employees’ motivation, planning, social support, and lifestyle can be supported by a stage-matched intervention that focuses on both physical activity and healthy nutrition. Occupational settings provide a potential to implement parsimonious computer-based health promotion programs and to facilitate multiple behavior change. [J Med Internet Res 2015;17(10):e225]

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References
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Modeling Health Behavior Change: How to Predict and Modify the Adoption and Maintenance of Health Behaviors

TL;DR: The Health Action Process Approach (HAPA) as mentioned in this paper suggests a distinction between preintentional motivation processes that lead to a behavioral intention, and postintentional volition processes that leads to the actual health behavior.

Modelando el cambio en el comportamiento de salud: Cómo predecir y modificar la adopción y el mantenimiento de comportamientos de salud

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A Primer on Maximum Likelihood Algorithms Available for Use With Missing Data

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