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Record W3039800212 · doi:10.1097/nhh.0000000000000874

Workplace Violence Interventions Used by Home Healthcare Workers

2020· review· en· W3039800212 on OpenAlexaff
Tamara F. Small, Gordon Lee Gillespie, Emily Kean, Scott Hutton

Bibliographic record

VenueHome Healthcare Now · 2020
Typereview
Languageen
FieldSocial Sciences
TopicWorkplace Violence and Bullying
Canadian institutionsWorkplace Health, Safety and Compensation Commission
FundersNational Institute for Occupational Safety and Health
KeywordsPsychological interventionHealth careMedicineWorkplace violenceInclusion (mineral)Occupational safety and healthNursingEnvironmental healthSuicide preventionPoison controlPsychologySocial psychologyPolitical science

Abstract

fetched live from OpenAlex

The threat of workplace violence (WPV) is a significant occupational hazard for home healthcare workers (HHCWs). The purpose of this integrative review is to examine WPV interventions used by HHCWs to stay safe while working in the patient's home and community. The methodology used was the integrative review by , which allows for inclusion of experimental and non-experimental research, reflecting the state of the science on interventions used by HHCWs to mitigate and prevent WPV. A total of 17 articles pertained to interventions used by HHCWs. Interventions were further categorized by WPV Type. There are a number of interventions used for Type I and II WPV. However, interventions for Type III WPV are minimal and interventions for Type IV WPV are obsolete. Safety and health training were shown to be significant in increasing HHCWs' confidence and knowledge about WPV prevention. Researchers demonstrated safety and health training are effective in promoting a safe work environment and reducing incidents of WPV. This review begins to fill the gap in the literature on interventions used by HHCWs to mitigate and prevent WPV.

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

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)0.003
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0040.003
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.101
GPT teacher head0.421
Teacher spread0.320 · 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

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations17
Published2020
Admission routes1
Has abstractyes

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