Evidence map›Paper›PMID 34724942›Full record

ArticleBMC nursing2021

Identifying the most important workplace factors in predicting nurse mental health using machine learning techniques.

Farinaz Havaei, Xuejun Ryan Ji, Maura MacPhee, Heather Straight

Open access · goldAbstract read
In one paragraph

Article in BMC nursing, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 2 pooled it
4.9field-weighted citation impact, top 5% 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

17 citing papers in PubMed, 2 syntheses or guidelines pooled it, 31 citations in OpenAlex.

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  11. Decoding machine learning in nursing research: A scoping review of effective algorithms.Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing · 2025
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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

4 authors at 2 institutions in 1 country.

Farinaz HavaeiUniversity of British Columbia (UBC), School of Nursing, 201-2211 Wesbrook Mall, Vancouver, BC, V6T 2B5, Canada. farinaz.havaei@ubc.ca.
Xuejun Ryan JiUBC Department of Educational and Counselling Psychology, and Special Education, 2125 Main Mall, Vancouver, BC, V6T 1Z4, Canada.
Maura MacPheeUniversity of British Columbia (UBC), School of Nursing, 201-2211 Wesbrook Mall, Vancouver, BC, V6T 2B5, Canada.
Heather StraightBritish Columbia Nurses Union, 4060 Regent Street, Burnaby, BC, V5C 6P5, Canada.
University of British Columbia · CARegistered Nurses' Association of Ontario · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesNurses are at a high risk of developing mental health problems due to exposure to work environment risk factors. Previous research in this area has only examined a few factors within nurses' work environments, and those factors were not conceptualized with the goal of improving workplace mental health. The purpose of this study is to identify the most important work environment predictors of nurse mental health using a comprehensive and theoretically grounded measure based on the National Standard of Psychological Health and Safety in the Workplace.

methodsThis is an exploratory cross-sectional survey study of nurses in British Columbia, Canada. For this study, responses from a convenience sample of 4029 actively working direct care nurses were analyzed using random forest regression methods. Key predictors include 13 work environment factors. Study outcomes include depression, anxiety, post-traumatic stress disorder (PTSD), burnout and life satisfaction.

resultsOverall, healthier reports of work environment conditions were associated with better nurse mental health. More specifically balance, psychological protection and workload management were the most important predictors of depression, anxiety, PTSD and emotional exhaustion. While engagement, workload management, psychological protection and balance were the most important predictors of depersonalization, engagement was the most important predictor of personal accomplishment. Balance, psychological protection and engagement were the most important predictors of life satisfaction.

conclusionsRoutine assessment with standardized tools of nurses' work environment conditions and mental health is an important, evidence-based organizational intervention. This study suggests nurses' mental health is particularly influenced by worklife balance, psychological protection and workload management.

Indexed as

Machine learningMental healthNational standard of psychological health and safetyNursingWork environment factors

Identifiers

PMID34724942
PMCPMC8559368
OpenAlexW3209555098

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.