The Effects of a Randomized Workplace Lifestyle Intervention - Using Web-Based Feedback with Health Behavior Theories for Self-Empowered Health and Health Literacy
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Abstract
Background: Railway employees are sedentary, constantly traveling, and at high risk of obesity. Internet-based health interventions may serve as an appropriate medium for a traveling target group. Many previously conducted interventions delivered via the Internet have shown moderate results, but many lack the use of well-established health behavior theories and aspects enhancing participants’ health literacy. Objectives: We evaluated the health effects of a web-based intervention using instant health feedback with well-established health behavior theories (i.e. stages of change) with or without added motivational interviewing over telephone. The overall study aim was to reach self-empowered health among our participants. Methods: 3,876 employees were e-mailed a web-based lifestyle questionnaire and randomly given either a: A) questionnaire, or B) questionnaire + interactive personalized automated health feedback, or C) questionnaire + interactive personalized automated health feedback + telephone counseling. The automatic feedback was based on the participants’ responses, level of motivation to change, and tailored to match their health needs. All feedback was saved at a personalized website. Telephone counseling was provided by the Quit-Smoking-Hotline, Alcohol Hotline, or Diet and Exercise Hotline. All three hotlines used Motivational Interviewing as their primary method for counseling. Nine months later, a follow-up questionnaire (version C) was e-mailed. Descriptive statistics were calculated. Chi-square tests, Kruskal Wallis, ANOVA, and GEE models were computed to study health improvements within/between the groups (A, B, and C), at baseline and follow-up. Results: 981 (66%) employees (men: 67%, mean age: 44yrs, mean BMI: 26.4kg/m2) participated at baseline and follow-up. At baseline, the intervention groups (B and C) reported higher motivation to improve dietary (48%-51%) and physical activity habits (60-63%), compared to group A (34% for diet; 50% for physical activity). At follow-up, the intervention groups were less motivated to make lifestyle changes, whereas group A increased (p<0.001) their motivation. No significant differences in health changes (diet, physical activity, alcohol intake, smoking, stress, and sleeping) with respect to the three different groups were found. Conclusion: Personalized automated health feedback did not render in effects on health and no improved health effects were found with added telephone counseling. However, our results point towards promising results on participants’ level of motivation to change health behaviors, from using automated personalized health feedback. Yet, motivation is the first step towards self-empowered health and the beginning to use health literacy as an asset.
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