Evidence map›Paper›PMID 40354568›Full record

ArticleScandinavian journal of work, environment & health2025

Workplace violence and fear of violence: an assessment of prevalence across industrial sectors and its mental health effects.

Vanessa Gash, Niels Blom

Abstract read
In one paragraph

Article in Scandinavian journal of work, environment & health, 2025. 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

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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. Article
  3. Workplace violence: A complex challenge demanding a systemic response.Scandinavian journal of work, environment & health · 2025
    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

2 authors.

Vanessa Gashity St Georges, University of London, London, UK. Vanessa.Gash.1@citystgeorges.ac.uk.
Niels Blom

Funding

Wellcome Trust
6 · The paper itself

Abstract

objectivesThis study aimed to (i) examine variance in the prevalence of workplace violence and fear of violence in the United Kingdom by industrial sector and (ii) determine the mental health effects thereof using longitudinal data.

methodsWe used the United Kingdom Household Panel Study (UKHLS), a nationally representative survey with mental health indicators collected annually allowing us to determine common mental disorders (CMD) at baseline, one year prior and one year later. Using weighted logistic regression and lagged dependent variable regression, we examined prevalence of violence and fear of violence by sector and the effect of violence on CMD risk. We supplemented our analyses with the views of those with lived experience.

resultsWorkers employed in public administration and facilities had the highest risks of workplace violence, with predicted probabilities (PP) of 0.138 [95% confidence interval (CI) 0.116-0.160], and these were not statistically different from the second highest sector of health, residential care, and social work (PP 0.118, 95% CI 0.103-0.133). Workplace violence increased CMD risk [adjusted odds ratio (ORadj) 1.400, 95% CI 1.182-1.658] as did fear of violence at work (ORadj 2.103, 95% CI 1.779-2.487), adjusting for prior CMD. Moreover, the effect of violence and fear of violence on CMD remained when we investigated CMD one year later.

conclusionsA high prevalence of workplace violence and fear of workplace violence was found in multiple different industrial sectors - >1 in 10 workers were exposed to violence in the last 12 months in 30% of sectors and >1 in 20 workers were exposed in 70% of sectors. Both violence and fear of violence were associated with enhanced CMD risk at baseline and one year later.

Indexed as

FearIndustryMental DisordersMental HealthWorkplaceWorkplace ViolenceAdultFemaleHumansLongitudinal StudiesMaleMiddle AgedPrevalenceSurveys and QuestionnairesUnited KingdomYoung Adult

Identifiers

PMID40354568
PMCPMC12416159

What OpenQuestion holds

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LicenceCC BY
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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.