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Record W4220849183 · doi:10.1371/journal.pgph.0000187

Workplace violence and turnover intention among the Bangladeshi female nurses after a year of pandemic: An exploratory cross-sectional study

2022· article· en· W4220849183 on OpenAlexaff
Humayun Kabir, Saifur Rahman Chowdhury, Tajrin Tahrin Tonmon, Anjan Kumar Roy, Shimpi Akter, Mohammad Toyabur Rahaman Bhuya, Lukman Hossain, Shubrandu Sanjoy

Bibliographic record

VenuePLOS Global Public Health · 2022
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsSaskatchewan HealthSaskatchewan Health Authority
Fundersnot available
KeywordsCross-sectional studyPandemicTurnover intentionWorkplace violenceExploratory researchMedicinePsychologyCoronavirus disease 2019 (COVID-19)NursingEnvironmental healthHuman factors and ergonomicsPoison controlSocial psychologyJob satisfactionSociologyInternal medicine

Abstract

fetched live from OpenAlex

During the COVID-19 pandemic, workplace violence was widespread against healthcare personnel. Workplace violence (WPV) against nurses exhilarates their turnover intention (TI). The objective of this study was to investigate the association between workplace violence and turnover intention and also identify other factors associated with TI among Bangladeshi female nurses. An exploratory cross-sectional study was carried out among 881 female nurses between April 26 and July 10, 2021. The TI of the female nurses was the outcome variable of this study. The primary exposure variable was WPV faced by the nurses. Workplace Violence Scale (WPVS) was used to measure the WPV, and Turnover Intention Scale-6 (TIS-6) was used to measure the TI of the nurses. Multiple linear regression model was fitted to find the adjusted association of TI with WPV and other study variables. A stratified analysis by type of job (government vs. private) was also performed. The majority of the nurses (74.46%) faced low to high levels of WPV. The overall mean score of TIS was found 16.33 (± 4.72). Multiple linear regression analysis revealed that compared to government jobholders, the mean score of TIS (15.81 vs. 17.20) was found significantly higher among the private jobholders (p < 0.001). Nurses exposed to the intermediate and high level of WPV had a significantly higher TI score (β = 4.35, 95% CI: 3.36, 5.34) than the non-exposures. The TI of private jobholders was found significantly higher (β = 2.04, 95% CI: 1.09, 3.00) than the government jobholders. Compared to diploma degree holders, significantly higher TI was observed among the B.Sc. degree holders (β = 0.86, 95% CI: 0.22, 1.55) and M.Sc. degree holders (β = 1.46, 95% CI: 0.58, 2.34). Besides, the nurses who did not get timely salaries scored higher TI (β = 1.17, 95% CI: 0.12, 2.22). Moreover, the nurses who did not receive any training against WPV scored significantly higher TI (β = 1.89, 95% CI: 1.03, 2.74). The stratified analysis by type of job also revealed significant factors of TI in government and private settings. This study found a high prevalence of WPV and a high rate of TI among Bangladeshi female nurses. Moreover, this study explored an association between WPV and TI. The study findings could help policymakers facilitate a comfortable working environment by preventing WPV and addressing the factors to reduce nurses' frequent TI.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
models agreeAgreement compares identical category sets and study designs across arms.

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.100
GPT teacher head0.411
Teacher spread0.310 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations32
Published2022
Admission routes1
Has abstractyes

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