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Record W4300687928 · doi:10.1111/inr.12802

Workplace violence against Bangladeshi registered nurses: A survey following a year of the COVID‐19 pandemic

2022· article· en· W4300687928 on OpenAlex
Saifur Rahman Chowdhury, Humayun Kabir, Dipak Chandra Das, Mahfuzur Rahman Chowdhury, Mahmudur Rahman Chowdhury, Ahmed Hossain

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Nursing Review · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicWorkplace Violence and Bullying
Canadian institutionsMcMaster UniversityImpact
Fundersnot available
KeywordsWorkplace violenceChecklistNursingMedicineOccupational safety and healthLogistic regressionPandemicCross-sectional studyPublic healthFamily medicineSuicide preventionPoison controlPsychologyCoronavirus disease 2019 (COVID-19)Medical emergency

Abstract

fetched live from OpenAlex

AIMS: To investigate the prevalence of workplace violence and its associated factors among Bangladeshi registered nurses. BACKGROUND: Workplace violence is prevalent among nurses, particularly in developing countries. However, the issue has never been examined in Bangladeshi nurses. METHODS: Between February 26 and July 10, 2021, this cross-sectional survey involving 1264 registered nurses was conducted. Workplace violence was determined by the Workplace Violence Scale (WVS). A multivariable logistic regression model was fitted to find the factors associated with workplace violence. This study complies with the EQUATOR (STROBE) checklist. RESULTS: Of the 1264 nurses, 885 (70%) nurses reported being exposed to workplace violence in the previous year. Three hundred twenty-four (324; 25.6%) nurses reported physical violence, whereas 902 (71.4%) nurses reported nonphysical violence. According to the multivariable logistic regression model, male nurses, nurses in the Sylhet division, emergency department nurses, nurses working extended hours, and non trained nurses to tackle workplace violence were prone to physical violence. Furthermore, public hospital nurses and non trained nurses to tackle workplace violence were more likely to be exposed to nonphysical violence. Nurses who had not been exposed to workplace violence were satisfied with their current job, but those who had been exposed to workplace violence were dissatisfied and intended to leave their current job. CONCLUSIONS AND IMPLICATIONS FOR NURSING AND HEALTH POLICY: High prevalence of workplace violence underscores nurses' current working conditions, which are particularly poor in public hospitals and emergency departments. Moreover, the COVID-19 pandemic put unprecedented pressure on the whole healthcare system and caused various difficulties for healthcare workers. To develop a zero-violence practice environment, health authorities should implement policy-level interventions. Healthcare staff should be guided to deal more successfully with patients and coworkers to create a positive working environment.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.850
Threshold uncertainty score0.505

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.099
GPT teacher head0.404
Teacher spread0.305 · 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