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Record W86228320 · doi:10.1177/070674371405900304

Preventing Suicide among Inpatients

2014· review· en· W86228320 on OpenAlexaffvenue
Isaac Sakinofsky

Bibliographic record

VenueThe Canadian Journal of Psychiatry · 2014
Typereview
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsPoison controlSuicide preventionInjury preventionHuman factors and ergonomicsMedicineOccupational safety and healthPsychiatryPsychologyMedical emergency

Abstract

fetched live from OpenAlex

OBJECTIVE: Inpatient suicide comprises a proportionately small but clinically important fraction of suicide. This study is intended as a qualitative analysis of the comprehensive English literature, highlighting what is known and what can be done to prevent inpatient suicide. METHOD: A systematic search was conducted on the Cochrane Library, PubMed, Embase, Web of Knowledge, and a personal database for articles on cohort series, preferably controlled, of inpatient suicide (not deliberate self-harm or attempted suicide, unless they also dealt specifically with suicide data). RESULTS: A qualitative discussion is presented, based on the findings of the literature searched. CONCLUSIONS: The bulk of inpatient suicides actually occur not on the ward but off premises, when the patient was on leave or had absconded. Peaks occur shortly after admission and discharge. It is possible to reduce suicide risk on the ward by having a safe environment, optimizing patient visibility, supervising patients appropriately, careful assessment, awareness of and respect for suicide risk, good teamwork and communication, and adequate clinical treatment.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.816
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.049
GPT teacher head0.342
Teacher spread0.293 · 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.

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

Citations97
Published2014
Admission routes2
Has abstractyes

Explore more

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