Evidence map›Paper›PMID 34599409›Full record

ArticleInternational archives of occupational and environmental health2022

Identifying the risk features for occupational stress in medical workers: a cross-sectional study.

Ruican Sun, Cailin Zhang, Keyao Lv, Yajia Lan

Open access · bronzeAbstract read
In one paragraph

Article in International archives of occupational and environmental health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
4.1field-weighted citation impact, top 6% of its field
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

9 citing papers in PubMed, 22 citations in OpenAlex.

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  9. The Status of Occupational Stress and Its Influence on the Health of Medical Staff in Lanzhou, China.International journal of environmental research and public health · 2022
    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

4 authors at 2 institutions in 1 country.

Ruican SunDepartment of Preventive Medicine, School of Public Health, Chengdu Medical Collage, Chengdu, Sichuan, China.
Cailin ZhangDepartment of Disciplinary Inspection Office, West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
Keyao LvDepartment of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
Yajia LanDepartment of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China. yajialan501@126.com.ORCID http://orcid.org/0000-0002-9818-3057
Sichuan University · CNChengdu Medical College · CN

Funding

National Natural Science Foundation of China 82073521
6 · The paper itself

Abstract

objectiveOccupational stress is considered a worldwide epidemic experienced by a large proportion of the working population. The identification of characteristics that place people at high risk for occupational stress is the basis of managing and intervening in this condition. In this study, we aimed to identify and validate the risk features for occupational stress among medical workers using a risk model and nomogram.

methodsThis cross-sectional study included 1988 eligible participants from Henan Province in China. Occupational stress and worker-occupation fit were measured with the Depression, Anxiety and Stress Scales (DASS-21) and Worker-Occupation Fit Inventory (WOFI). The identification of risk features was achieved through constructing multiple logistic regression model, and the risk features were used to develop the risk model and nomogram. Receiver operating characteristic (ROC) curves and calibration plots were generated to assess the effectiveness and calibration of the risk model.

resultsAmong 1988 participants in our study, there were 42.5% (845/1988) medical workers experienced occupational stress. The risk features for occupational stress included poor work-occupation fit (WOF score < 25, expected risk: 77.3%), nurse population (expected risk: 63.1%), male sex (expected risk: 67.2%), work experience duration of 11-19 years (expected risk: 54.5%), experience of a traumatic event (expected risk: 65.3%) and the lack of a regular exercise habit (expected risk: 60.2%). For medical workers who have these risk features, the expected risk probability of occupational stress would be 90.2%.

conclusionThe current data can be used to identify medical workers at risk of developing occupational stress. Identifying risk features for occupational stress and the work-occupation fit can support hierarchical stress management in hospitals.

Indexed as

Occupational StressAnxietyCross-Sectional StudiesHealth PersonnelHumansMaleOccupationsSurveys and QuestionnairesNomogramOccupational stressRisk featuresRisk model

Identifiers

PMID34599409
PMCPMC8486163
OpenAlexW3203078291

What OpenQuestion holds

Textmetadata
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.