Evidence map›Paper›PMID 37789556›Full record

ArticleJournal of occupational health

Industry differences in psychological distress and distress-related productivity loss: A cross-sectional study of Australian workers.

Kristy Burns, Elizabeth-Ann Schroeder, Thomas Fung, Louise A Ellis, Janaki Amin

Abstract read
In one paragraph

Article in Journal of occupational health. 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.

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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

5 authors.

Kristy BurnsDepartment of Health Systems and Populations, Faculty of Medicine and Health Sciences, Macquarie University, Sydney, New South Wales, Australia.ORCID https://orcid.org/0000-0002-3060-4812
Elizabeth-Ann SchroederDepartment of Health Systems and Populations, Faculty of Medicine and Health Sciences, Macquarie University, Sydney, New South Wales, Australia.ORCID https://orcid.org/0000-0003-0236-2833
Thomas FungDepartment of Health Systems and Populations, Faculty of Medicine and Health Sciences, Macquarie University, Sydney, New South Wales, Australia.ORCID https://orcid.org/0000-0003-2601-0728
Louise A EllisDepartment of Health Systems and Populations, Faculty of Medicine and Health Sciences, Macquarie University, Sydney, New South Wales, Australia.ORCID https://orcid.org/0000-0001-6902-4578
Janaki AminDepartment of Health Systems and Populations, Faculty of Medicine and Health Sciences, Macquarie University, Sydney, New South Wales, Australia.ORCID https://orcid.org/0000-0003-2161-9366

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis research uses Australian survey data to identify industries with high rates of psychological distress, and to estimate productivity impacts in the form of work loss and cutback days.

methodsAnalyzing cross-sectional data from the 2017/2018 National Health Survey, industry prevalence of psychological distress (Kessler Screening Scale) was compared using ordered logistic regression. Productivity outcomes were distress-related work loss days and work cutback days in the previous 4 weeks. Losses were analyzed using zero-inflated negative binomial regression.

resultsThe sample consisted of 9073 employed workers [4497 males (49.6%), 4576 females (50.4%)]. Compared to the reference industry, Health, the odds of very high distress for males were highest in Information media and telecommunications (OR 2.4; 95% CI 1.2-4.6) and Administrative and support services (OR 2.5; 95% CI 1.2-5.0), while for females the odds were highest in Accommodation and food services (OR 2.0; 95% CI 1.5-2.8) followed by Retail (OR 1.6; 95% CI 1.2-2.0). Very high distress was associated excess productivity losses. Industry of occupation did not impact on productivity loss over and above distress.

conclusionsSubstantial psychological distress was reported which impacted on productivity. High-risk industries included Information media and telecommunications, Accommodation and food services, and Retail.

Indexed as

EfficiencyStress, PsychologicalAustraliaCross-Sectional StudiesFemaleHumansMaleSurveys and Questionnairescross-sectional studydistressindustrymental healthoccupational health

Identifiers

PMID37789556
PMCPMC10547932

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.