Evidence map›Paper›PMID 34346135›Full record

ArticleJournal of occupational health2021

A cross-sectional study of infection control measures against COVID-19 and psychological distress among Japanese workers.

Yoshino Yasuda, Tomohiro Ishimaru, Masako Nagata, Seiichiro Tateishi, Hisashi Eguchi, Mayumi Tsuji, Akira Ogami, Shinya Matsuda, Yoshihisa Fujino, CORoNaWork project

Erratum issuedAbstract read
In one paragraph

Article in Journal of occupational health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Yoshino YasudaDepartment of Environmental Epidemiology, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Japan, Kitakyushu, Japan.
Tomohiro IshimaruDepartment of Environmental Epidemiology, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Japan, Kitakyushu, Japan.ORCID https://orcid.org/0000-0002-9334-1423
Masako NagataDepartment of Occupational Health Practice and Management, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Japan, Kitakyushu, Japan.ORCID https://orcid.org/0000-0002-2459-2624
Seiichiro TateishiDepartment of Occupational Medicine, School of Medicine, University of Occupational and Environmental Health, Japan, Kitakyushu, Japan.ORCID https://orcid.org/0000-0002-9774-6479
Hisashi EguchiDepartment of Mental Health, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Japan, Kitakyushu, Japan.ORCID https://orcid.org/0000-0002-4153-8574
Mayumi TsujiDepartment of Environmental Health, School of Medicine, University of Occupational and Environmental Health, Japan, Kitakyushu, Japan.ORCID https://orcid.org/0000-0002-9579-4418
Akira OgamiDepartment of Work Systems and Health, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Japan, Kitakyushu, Japan.ORCID https://orcid.org/0000-0002-4940-3818
Shinya MatsudaDepartment of Preventive Medicine and Community Health, School of Medicine, University of Occupational and Environmental Health, Japan, Kitakyushu, Japan.ORCID https://orcid.org/0000-0002-8472-8909
Yoshihisa FujinoDepartment of Environmental Epidemiology, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Japan, Kitakyushu, Japan.ORCID https://orcid.org/0000-0002-9126-206X
CORoNaWork project

Funding

Anshin ZaidanChugai Pharmaceutical Co., Ltd.Health, Labour and Welfare Sciences Research Grants H30-josei-ippan-002Health, Labour and Welfare Sciences Research Grants H30-roudou-ippan-007Hitachi Systems, Ltd.The Collabo-Health Study GroupUniversity of Occupational and Environmental Health
6 · The paper itself

Abstract

objectivesThis study examined the relationship between the status of infection control efforts against COVID-19 in the workplace and workers' mental health using a large-scale Internet-based study.

methodsThis cross-sectional study was based on an Internet monitoring survey conducted during the third wave of the COVID-19 epidemic in Japan. Of the 33 302 people who participated in the survey, 27 036 were included in the analyses. Participants answered whether or not each of 10 different infection control measures was in place at their workplace (eg, wearing masks at all times during working hours). A Kessler 6 (K6) score of ≥13 was defined as mild psychological distress. The odds ratios (ORs) of psychological distress associated with infection control measures at the workplace were estimated using a multilevel logistic model nested in the prefectures of residence.

resultsThe OR of subjects working at facilities with 4 or 5 infection control measures for psychological distress was 1.19 (95% confidence interval [CI]: 1.05-1.34, P = .010), that in facilities with 2 or 3 infection control measures was 1.43 (95% CI: 1.25-1.64, P < .001), and that in facilities with 1 or no infection control measures was 1.87 (95% CI: 1.63-2.14, P < .001) compared to subjects whose workplaces had ≥6 infection control measures.

conclusionOur findings suggest that proactive COVID-19 infection control measures can influence the mental health of workers.

Indexed as

COVID-19Infection ControlPsychological DistressAdultCross-Sectional StudiesEmploymentFemaleHumansJapanMaleMiddle AgedSARS-CoV-2Surveys and QuestionnairesCOVID-19Japanoccupational healthprevention and controlpsychological distress

Identifiers

PMID34346135
PMCPMC8335571

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.