Evidence map›Paper›PMID 30101896›Full record

ArticleIndustrial health2019

Durations of first and second periods of depression-induced sick leave among Japanese employees: the Japan sickness absence and return to work (J-SAR) study.

Motoki Endo, Yasuo Haruyama, Kiyomi Mitsui, Go Muto, Chihiro Nishiura, Keisuke Kuwahara, Hiroo Wada, Takashi Tanigawa

Abstract read
In one paragraph

Article in Industrial health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Motoki EndoDepartment of Public Health, Juntendo University Faculty of Medicine, Japan.
Yasuo HaruyamaDepartment of Public Health, Dokkyo Medical University, Japan.
Kiyomi MitsuiDepartment of Public Health, Showa University, Japan.
Go MutoDepartment of Epidemiology and Environmental Health, Juntendo University Faculty of Medicine, Japan.
Chihiro NishiuraDepartment of Safety and Health, Tokyo Gas Co. Ltd., Japan.
Keisuke KuwaharaTeikyo University Graduate School of Public Health, Japan.
Hiroo WadaDepartment of Public Health, Juntendo University Faculty of Medicine, Japan.
Takashi TanigawaDepartment of Public Health, Juntendo University Faculty of Medicine, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to clarify the difference between the durations of first and second periods of depression-induced sick leave and to identify predictors of a prolonged second period of depression-induced sick leave. Among Japanese employees who were registered in the Japan sickness absence and return to work (J-SAR) study, the subjects were those employees who returned to work after an initial period of depression-induced sick leave (F3; ICD-10, based on a psychiatrist's certificate), and returned to work after a second period of depression-induced sick leave. The subjects' second periods of sick leave (mean: 156.9 d) were longer than their first periods of sick leave (107.3 d) (Wilcoxon test, p=0.007). In the logistic regression analysis (Table 2), "longer duration of the first period of sick leave" (Odds ratio: 3.258, 95%CI: 1.780-5.963, p<0.001) was identified as a significant predictor of a longer recurrent period of sick leave. Individuals who experience a long initial period of depression-induced sick leave should be supported carefully by occupational health professionals after they RTW.

Indexed as

AdultDepressionFemaleHumansJapanMaleOccupational HealthReturn to WorkSick LeaveTime FactorsDepressionOP (occupational physicians)Recurrent sick leaveRTW (return to work)Sick leave

Identifiers

PMID30101896
PMCPMC6363587

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.