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Healthy Lifestyle Behaviors and Technostress: A Combined Lifestyle Score Analysis in 104,175 Spanish Workers
Marta González Rivas1, Ángel Arturo López-González1,2, Diego González Carrasco1
1ADEMA University School, University of the Balearic Islands, 07009 Palma, Spain.
Abstract:
Background: Technostress has emerged as a major occupational health concern in increasingly digitalized workplaces. Although organizational and technological determinants of technostress have been widely investigated, the potential influence of healthy lifestyle behaviors remains poorly understood. This study aimed to evaluate the association between a combined Healthy Lifestyle Score (HLS) and technostress in a large cross-sectional sample of Spanish workers. Methods: A cross-sectional study was conducted among 104,175 workers who underwent routine occupational health examinations between January 2021 and December 2024. The Healthy Lifestyle Score was constructed by assigning one point each for regular physical activity, high adherence to the Mediterranean diet, and non-smoking status, resulting in scores ranging from 0 to 3. Technostress was assessed using the Technostress Short Questionnaire (TCS-Short) and categorized as low, moderate, high, or very high. Logistic regression models were used to estimate crude and adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for high-to-very high technostress according to HLS categories. Results: Significant differences in technostress levels were observed across HLS categories (p < 0.001). The prevalence of high-to-very high technostress was 50.8% among workers with HLS = 0 and 50.7% among those with HLS = 1, decreasing markedly to 7.5% and 7.2% among workers with HLS = 2 and HLS = 3, respectively. After adjustment for sex, age, educational level, and social class, participants with HLS = 2 and HLS = 3 exhibited substantially lower odds of high technostress (OR = 0.073, 95% CI 0.068-0.078 and OR = 0.074, 95% CI 0.069-0.079, respectively) compared with those with HLS = 0. The categorical analysis suggested a threshold-like rather than progressive association, with substantially lower odds of high-to-very high technostress observed among workers with HLS = 2 and HLS = 3, whereas HLS = 1 did not show lower odds compared with HLS = 0. The final model demonstrated excellent discrimination (AUC = 0.902). Conclusions: Healthy lifestyle profiles were strongly associated with technostress in this large cross-sectional occupational sample. Workers with HLS = 2 and HLS = 3 showed markedly lower odds of high-to-very high technostress than those with HLS = 0, whereas HLS = 1 did not show lower odds. Component-specific analyses indicated that the associations differed substantially across the behaviors comprising the score, supporting interpretation of the HLS as an unweighted behavioral count rather than as a measure of equivalent contributions from each component.
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