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Record W2170091849 · doi:10.5430/jha.v2n4p31

Addressing health workers’ exposure to violence at Lebanese emergency departments: What do the stakeholders think?

2013· article· en· W2170091849 on OpenAlexvenueno aff
Mohamad Alameddine, Nasser Yassin

Bibliographic record

VenueJournal of Hospital Administration · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicWorkplace Violence and Bullying
Canadian institutionsnot available
Fundersnot available
KeywordsStakeholderOccupational safety and healthHealth carePublic relationsMedicineSuicide preventionBusinessNursingPoison controlPolitical scienceEnvironmental health

Abstract

fetched live from OpenAlex

Healthcare settings are notorious for exposing their employees to high levels of verbal and physical violence. A recent study on occupational violence at Lebanese Emergency Departments (EDs) revealed that 70% of surveyed ED workers were exposed to at least one incidence of violence over the last twelve months. Acting on the findings of this study a multi-stakeholder policy forum was held with key ED stakeholders to discuss possible policy and practice changes to reduce health workers’ exposure to occupational violence. Stakeholder deliberations revealed that the root causes of violence in EDs could be classified under three main categories relating to the administration of EDs including the presence of antiviolence policies, the management of human resources, and balancing patient expectations. Stakeholders built a consensus on a number of remedial actions at the societal, health care facility and policy levels. Engaging with various stakeholders in an open forum was a unique initiative that contributed to building a consensus among key stakeholders on a road map to help protect health workers in EDs and beyond.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.686
Threshold uncertainty score0.773

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0000.000
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 head0.066
GPT teacher head0.347
Teacher spread0.281 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations4
Published2013
Admission routes1
Has abstractyes

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