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Record W4318671817 · doi:10.1111/jpm.12905

Short‐term risk assessment in the long term: A scoping review and meta‐analysis of the Brøset Violence Checklist

2023· review· en· W4318671817 on OpenAlexaff
Jacob Hvidhjelm, Lene Lauge Berring, Richard Whittington, Phil Woods, Jesper Bak, Roger Almvik

Bibliographic record

VenueJournal of Psychiatric and Mental Health Nursing · 2023
Typereview
Languageen
FieldSocial Sciences
TopicWorkplace Violence and Bullying
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsChecklistTerm (time)Meta-analysisSet (abstract data type)Risk assessmentHuman factors and ergonomicsPsychologyPoison controlMEDLINEMedicineMedical emergencyComputer scienceComputer securityPolitical scienceCognitive psychology

Abstract

fetched live from OpenAlex

WHAT IS KNOWN ON THE SUBJECT?: The Brøset Violence Checklist (BVC) has been widely translated and implemented in diverse mental healthcare settings to improve prevention of violence. It is valued as a brief but effective tool in clinical practice. WHAT THE PAPER ADDS TO EXISTING KNOWLEDGE?: This review is the largest and most comprehensive international review of the BVC conducted in the 25+ years since the inception of the instrument in 1995. It integrates findings from existing studies and establishes that the tool has many impressive strengths considering the brief time investment required for completion. The review reveals that the tool has been used in more than 20 different countries around the world in a variety of mental health and other settings as both a risk assessment tool to guide clinical practice and as a formally structured intervention to minimize violence. There is much variation in how the tool is implemented and scored in different services. This variation questions its applicability as a resource and consistency and its use needs attention. This variation in use also limits the conclusions regarding best practices. WHAT ARE THE IMPLICATIONS FOR PRACTICE?: The review supports the use of the BVC as one part of the package for mental health services committed to preventive action aimed at reducing violence and coercion. The review identified that the patient perspective was often absent when completing the BVC, and so this should be considered as an option by services as part of a collaborative philosophy of care. ABSTRACT: INTRODUCTION: Existing literature on the Brøset Violence Checklist (BVC) is examined in the context of usability, implementation and validity to provide evidence-based recommendations on its application and identify opportunities for future development. AIM/QUESTION: To identify current knowledge on the BVC and guide clinicians and researchers toward the next steps in using this tool in clinical practice to prevent violence in healthcare settings. METHOD: A scoping review approach with a meta-analysis supplement was adopted to broadly identify and map available evidence on the BVC and provide specific estimates of predictive validity in different contexts. RESULTS: Sixty-two studies conducted in 23 countries addressed the implementation of the BVC across various settings. Many studies adapted the original BVC, and the clinical utility was noted as an important feature. A meta-analysis of the original BVC format estimated a pooled area under the curve at 0.83 (95% CI 0.78-0.87) in a subset of 15 studies. DISCUSSION: The BVC combines high predictive validity and good clinical utility across a wide range of settings and cultures. It should continue to be incorporated into routine practice in mental health services focused on preventing violence and coercion. IMPLICATIONS FOR PRACTICE: Development of collaborative approaches with service users involved in assessing their own risk of future violence.

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)0.006
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.919
Threshold uncertainty score0.637

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.088
GPT teacher head0.491
Teacher spread0.403 · 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 designOther design
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

Citations39
Published2023
Admission routes1
Has abstractyes

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