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Trends in Work Conditions and Associations with Workers’ Health in Recent 15 Years: The Role of Job Automation Probability

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  • Wan-Ju Cheng

    (Department of Psychiatry, China Medical University Hospital, Taichung 40447, Taiwan
    Department of Public Health, China Medical University, Taichung 40402, Taiwan)

  • Li-Chung Pien

    (Post-Baccalaureate Program in Nursing, College of Nursing, Taipei Medical University, Taipei 11031, Taiwan)

  • Tomohide Kubo

    (National Institute of Occupational Safety and Health, Kawasaki 214-8585, Japan)

  • Yawen Cheng

    (Institute of Health Policy and Management, Department of Public Health, National Taiwan University, Taipei 100, Taiwan)

Abstract

Job automation and associated psychosocial hazards are emerging workplace challenges. This study examined the trends in work conditions and associations with workers’ health over time in jobs with different automation probabilities. We utilized data from six waves of national questionnaire surveys of randomly selected 95,762 employees between 2001 and 2016. The Job Content Questionnaire, the Copenhagen Burnout Inventory, and the Self-Rated Health Scale were applied, and working time was self-reported. Automation probability was derived for 38 occupations and then categorized into three groups. Trends in work conditions and the associations between automation probability, work conditions and health were examined. We observed a 7% decrease in high automation probability jobs, an overall increase in job demands for and prevalence of shift work, and a decrease in job control. Workers with high automation probability jobs had low job demands, low job control and high job insecurity. Low automation probability was associated with burnout in logistic regression models. The odds ratio of job insecurity, long working hours, and shift work relating to health was higher in the later years of the surveys. In conclusion, there has been a decrease in high automation probability jobs. Workers employed in jobs with different levels of automation probability encountered different work condition challenges.

Suggested Citation

  • Wan-Ju Cheng & Li-Chung Pien & Tomohide Kubo & Yawen Cheng, 2020. "Trends in Work Conditions and Associations with Workers’ Health in Recent 15 Years: The Role of Job Automation Probability," IJERPH, MDPI, vol. 17(15), pages 1-12, July.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:15:p:5499-:d:391886
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    References listed on IDEAS

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    1. David H. Autor & David Dorn, 2013. "The Growth of Low-Skill Service Jobs and the Polarization of the US Labor Market," American Economic Review, American Economic Association, vol. 103(5), pages 1553-1597, August.
    2. Robert Drago & Mark Wooden & David Black, 2009. "Long Work Hours: Volunteers and Conscripts," British Journal of Industrial Relations, London School of Economics, vol. 47(3), pages 571-600, September.
    3. Andrew E. Clark, 2005. "Your Money or Your Life: Changing Job Quality in OECD Countries," British Journal of Industrial Relations, London School of Economics, vol. 43(3), pages 377-400, September.
    4. Patel, Pankaj C. & Devaraj, Srikant & Hicks, Michael J. & Wornell, Emily J., 2018. "County-level job automation risk and health: Evidence from the United States," Social Science & Medicine, Elsevier, vol. 202(C), pages 54-60.
    5. repec:ilo:ilowps:470451 is not listed on IDEAS
    6. Fiona Cocker & Nerida Joss, 2016. "Compassion Fatigue among Healthcare, Emergency and Community Service Workers: A Systematic Review," IJERPH, MDPI, vol. 13(6), pages 1-18, June.
    7. Huan-Cheng Chang & Mei-Chin Wang & Hung-Chang Liao & Shu-Fang Cheng & Ya-huei Wang, 2016. "Hazard Prevention Regarding Occupational Accidents Involving Blue-Collar Foreign Workers: A Perspective of Taiwanese Manpower Agencies," IJERPH, MDPI, vol. 13(7), pages 1-11, July.
    8. Frey, Carl Benedikt & Osborne, Michael A., 2017. "The future of employment: How susceptible are jobs to computerisation?," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 254-280.
    9. Tucker, Philip & Folkard, Simon., 2012. "Working time, health and safety a research synthesis paper," ILO Working Papers 994704513402676, International Labour Organization.
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    Cited by:

    1. Seong-Uk Baek & Jin-Ha Yoon & Jong-Uk Won, 2022. "Association between Workers’ Anxiety over Technological Automation and Sleep Disturbance: Results from a Nationally Representative Survey," IJERPH, MDPI, vol. 19(16), pages 1-12, August.

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