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

Wan-Ju Cheng, Li-Chung Pien, Tomohide Kubo and Yawen Cheng
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Wan-Ju Cheng: Department of Psychiatry, China Medical University Hospital, Taichung 40447, 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

IJERPH, 2020, vol. 17, issue 15, 1-12

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.

Keywords: job automation; psychosocial work conditions; burnout; self-rated health; trend analysis (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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