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A Generalized Structural Equation Model Approach to Long Working Hours and Near-Misses among Healthcare Professionals in Japan

Author

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  • Tatsuhiko Anzai

    (Department of Biostatistics, M&D Data Science Center, Tokyo Medical and Dental University, Tokyo 113-8510, Japan)

  • Takashi Yamauchi

    (Department of Public Health and Environmental Medicine, The Jikei University School of Medicine, Tokyo 105-8461, Japan)

  • Masaki Ozawa

    (School of Medicine, Tokyo Medical and Dental University, Tokyo 113-8510, Japan)

  • Kunihiko Takahashi

    (Department of Biostatistics, M&D Data Science Center, Tokyo Medical and Dental University, Tokyo 113-8510, Japan)

Abstract

(1) Background: Near-miss incidents are the foundation of major injuries. They are warning signs that loss is imminent. Long working hours are a risk factor for near-misses along with sleep problems, job-related stress, and depressive symptoms. This study aimed to evaluate the indirect effects of long working hours via mediating variables on near-miss occurrences among Japanese healthcare professionals. (2) Methods: 1490 Japanese healthcare professionals’ reports from a web-based survey of workers in October 2018 were analyzed to evaluate total, direct, and indirect effects of long working hours on near-misses. We applied a generalized structural equation model with three mediating variables: sleep problems, job-related stress, and depressive symptoms. (3) Results: The total effect and direct effect of the categories of working hours longer than 41 h per week (h/w) for occurrence of near-misses were not significantly higher than that of 35–40 h/w. However, for indirect effects on occurrence of near-misses that first passed through job-related stress, there were higher reports for each category compared to 35–40 h/w, with odds ratios (OR) and 95% confidence intervals (95% CI) of OR = 1.12, 95% CI (1.07, 1.21) for 41–50 h/w; 1.25, (1.14, 1.41) for 51–60 h/w; and 1.31, (1.18, 1.51) for ≥ 61 h/w. (4) Conclusion: The results suggest that reducing working hours might improve job-related stress, which could reduce near-misses and prevent injuries.

Suggested Citation

  • Tatsuhiko Anzai & Takashi Yamauchi & Masaki Ozawa & Kunihiko Takahashi, 2021. "A Generalized Structural Equation Model Approach to Long Working Hours and Near-Misses among Healthcare Professionals in Japan," IJERPH, MDPI, vol. 18(13), pages 1-11, July.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:13:p:7154-:d:588265
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    References listed on IDEAS

    as
    1. Lara Christina Roll & Oi-ling Siu & Simon Y.W. Li & Hans De Witte, 2019. "Human Error: The Impact of Job Insecurity on Attention-Related Cognitive Errors and Error Detection," IJERPH, MDPI, vol. 16(13), pages 1-61, July.
    2. Zhipeng Zhou & Chaozhi Li & Chuanmin Mi & Lingfei Qian, 2019. "Exploring the Potential Use of Near-Miss Information to Improve Construction Safety Performance," Sustainability, MDPI, vol. 11(5), pages 1-21, February.
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