A Japanese Stress Check Program screening tool predicts employee long-term sickness absence: A prospective study

Akizumi Tsutsumi, Akihito Shimazu, Hisashi Eguchi, Akiomi Inoue, Norito Kawakami

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

Objectives: On December 1, 2015, the Japanese government launched the Stress Check Program, a new occupational health policy to screen employees for high psychosocial stress in the workplace. As only weak evidence exists for the effectiveness of the program, we sought to estimate the risk of stress-associated longterm sickness absence as defined in the program manual. Methods: Participants were 7356 male and 7362 female employees in a financial service company who completed the Brief Job Stress Questionnaire (BJSQ). We followed them for 1 year and used company records to identify employees with sickness absence of 1 month or longer. We defined high-risk employees using the BJSQ and criteria recommended by the program manual. We used the Cox proportional regression model to evaluate the prospective association between stress and long-term sickness absence. Results: During the followup period, we identified 34 male and 35 female employees who took long-term sickness absence. After adjustment for age, length of service, job type, position, and post-examination interview, hazard ratios (95% confidence intervals) for incident long-term sickness absence in high-stress employees were 6.59 (3.04-14.25) for men and 2.77 ( 1.32-5.83 ) for women. The corresponding population attributable risks for high stress were 23.8% (10.3-42.6) for men and 21.0% (4.6-42.1) for women. Conclusions: During the 1-year follow-up, employees identified as high stress (as defined by the Stress Check Program manual ) had significantly elevated risks for long-term sickness absence.

Original languageEnglish
Pages (from-to)55-63
Number of pages9
JournalJournal of occupational health
Volume60
Issue number1
DOIs
Publication statusPublished - 2018 Jan 1

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Keywords

  • Cox proportional hazard regression analysis
  • Incidence
  • Kaplan-Meier analysis
  • Mental health
  • Psychosocial work environment

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health

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