ArticleIndustrial health2023
Ten-year trends in long-term sickness absence among Japanese public servants: 2009-2018.
Article in Industrial health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 7 citations in OpenAlex.
- The Price of Absence: Productivity Costs and Sickness-Absence Episodes Attributable to Mental and Behavioral Disorders in the Brazilian Federal Workforce - A Nationwide Time-Series Study (2012-2024).PharmacoEconomics - open · 2026Article
- Patients seeking occupational health advice before and after COVID-19.Occupational medicine (Oxford, England) · 2026Article
- Machine learning prediction of long-term sickness absence due to mental disorders using Brief Job Stress Questionnaire data.Scientific reports · 2025Article
- Workplace gender composition and long-term sickness absence due to mental disorders: A retrospective cohort study.PCN reports : psychiatry and clinical neurosciences · 2025Article
- Impact of workplace factors on long-term sickness absence: A retrospective observational study comparing mental and physical illnesses.PCN reports : psychiatry and clinical neurosciences · 2025Article
- Impact of the COVID-19 pandemic on long-term sickness absences due to mental disorders in public servants: a retrospective observational study.BMC public health · 2025Observational
- Remote work and long-term sickness absence due to mental disorder trends among Japanese workers pre/post COVID-19.PloS one · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Sickness absences are a significant public health and economic problem worldwide. However, sickness absence diagnoses and trends have not been reported in much detail in Japan. This study was a retrospective cohort study. We examined data on certified diagnoses and the durations of sickness absence lasting over 90 days (long-term sickness absence) from 2009-2018 among city public servants in Japan. We found that 1) "Mental and behavioral disorders" (495.0-780.6 per 100,000 employees) was the most prevalent reason for long-term sickness absence, and "Mood disorders" (318.6-584.3 per 100,000 employees) was the most prevalent mental disorders diagnosis in each study year; 2) the prevalence of long-term sickness absence for mental disorders showed decreasing trends (781/100,000 in 2009 to 622/100,000 in 2018; [p=0.005, for the trend test]); 3) the trends differed by gender (p<0.05) and age (p<0.001); and 4) the duration of long-term sickness absence related to mental disorders (13.2 ± 9.0 months) was longer than long-term sickness absence resulting from all physical disorders except for diseases of the circulatory system (15.1 ± 11.6 months). Increased focus on significant depressive and neurotic disorders is needed when promoting mental health in the workplace.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.