Evidence map›Paper›PMID 30531106›Full record

ArticleIndustrial health2019

Relationship between treatment and period of absence among employees on sick leave due to mental disease.

Keiji Muramatsu, Yoshihisa Fujino, Tatsuhiko Kubo, Makoto Otani, Shinya Matsuda

Abstract read
PubMed Full text at PMC Publisher
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 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Age, Loneliness, and Social Media Use in Adults during COVID-19: A Latent Profile Analysis.International journal of environmental research and public health · 2023
    Article
  3. Article
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

5 authors.

Keiji MuramatsuDepartment of Preventive Medicine and Community Health, School of Medicine, University of Occupational and Environmental Health, Japan.
Yoshihisa FujinoDepartment of Environmental Epidemiology, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Japan.
Tatsuhiko KuboDepartment of Environmental Epidemiology, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Japan.
Makoto OtaniData Science Center of Occupational Health, University of Occupational and Environmental Health, Japan.
Shinya MatsudaDepartment of Preventive Medicine and Community Health, School of Medicine, University of Occupational and Environmental Health, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study used health insurance claims data to examine the relationship between the length of sick leave and treatment administered to employees who received middle- to long-term accident and sickness benefits for ≥91 d due to mood disorders, anxiety, and dissociative, stress-related, somatoform and other nonpsychotic mental disorders. Employees who received psychotherapy had significantly shorter leaves of absence over one year compared to those that did not. Treatment with psychotropic drugs was significantly higher among those on leave for ≤365 d than those on leave for ≥366 d. Age, sex and hospital treatment were not significantly associated with length of sick leave. These results suggest that professional psychological treatment is associated with length of sick leave.

Indexed as

AdultEmploymentFemaleHospitalizationHumansInsurance BenefitsMaleMental DisordersRetrospective StudiesSick LeaveTime FactorsHealth insurance claims dataMental healthProfessional psychological treatmentReturn to workSick leave

Identifiers

PMID30531106
PMCPMC6363582

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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.