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Short-Term Effects of an mHealth Intervention on Healthy Behaviors and Cardiometabolic Health in Sedentary Employees:
Yun-Ping Lin1,2, Shu-Hua Lu1,2, Kwo-Chen Lee1,2
1Department of Nursing, China Medical University Hospital, Taichung, Taiwan.
Background:
Sedentary employees face increased chronic health risks due to physical inactivity, immobility, and unhealthy eating behavior. Although mobile health (mHealth) interventions show promise in improving lifestyle behaviors, their effectiveness in occupational settings remains underexplored. Building on previous workplace interventions, this study developed and evaluated a mobile-enabled web app, SIMPLE HEALTH, developed with Din-J Design Co, Ltd, integrating activity tracking, healthy eating, and behavioral support for sedentary employees.
Objective:
This study evaluated the short-term effects of a 12-week mHealth intervention on physical activity, sedentary behavior, dietary habits, and cardiometabolic health indicators among sedentary employees in Taiwan.
Methods:
A 2-arm quasi-experimental study was conducted at 2 aerospace industrial workplaces. A total of 101 sedentary employees (mean age 46.9, SD 12.2 years; 52/101, 51.5% female) were enrolled from 2 worksites that were assigned by coin toss to either the intervention condition (n=50) or the control condition (n=51). The intervention group participated in the SIMPLE HEALTH program, an mHealth intervention grounded in Social Cognitive Theory and the Ecological Model, consisting of 8 components: activity tracking, goal setting, behavior logging, reminders, personalized advice, educational and motivational electronic booklets, and individual and team challenges. The control group received 6 print educational booklets. Cardiometabolic biomarkers, objectively measured physical activity (Fitbit Charge 3; Fitbit Inc), occupational sitting (occupational sitting and physical activity questionnaire), and dietary behavior (3-day photographic food records and the healthy eating behavior inventory) were assessed at baseline and 12 weeks. Data were analyzed using generalized estimating equations following the intention-to-treat principle.
Results:
At 12 weeks, the intervention group showed a significant increase in step counts (adjusted mean difference, MD 1227.13, 95% CI 2.90-2451.36; P=.049), a more favorable between-group change in moderate physical activity (adjusted MD 0.17, 95% CI 0.01-0.33; P=.04), and favorable dietary behaviors, including reduced intake of calories (adjusted MD -144.59, 95% CI -276.57 to -12.60; P=.03), carbohydrates (adjusted MD -19.88, 95% CI -37.99 to -1.78; P=.03), fats (adjusted MD -6.99, 95% CI -13.69 to -0.29; P=.04), and grains (adjusted MD -1.46, 95% CI -2.43 to -0.50; P=.003), and increased vegetable intake (adjusted MD 0.47, 95% CI 0.06-0.88; P=.02), compared to the control group. Favorable trends were noted in diastolic blood pressure (adjusted MD -2.38, 95% CI -4.99 to 0.22; P=.07) and soft lean mass (adjusted MD 0.34, 95% CI -0.06 to 0.75; P=.10). Both groups showed significant within-group improvements in low-density lipoprotein cholesterol (intervention: P=.01; control: P=.03), body fat percentage (intervention: P<.001; control: P=.01), waist circumference (intervention: P=.001; control: P=.002), and occupational sitting (intervention: P<.001; control: P=.03), and occupational walking (intervention: P=.01; control: P=.046), but between-group differences were nonsignificant.
Conclusions:
The 12-week mHealth intervention improved physical activity and dietary behaviors and showed favorable trends in cardiometabolic indicators among sedentary employees. These findings support integrating mHealth programs into employee wellness initiatives to promote healthy behaviors, mitigate productivity loss, and reduce chronic disease burden. Further research should assess long-term sustainability, scalability, and cost-effectiveness in diverse occupational settings.
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