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Suicide and self‐harm in in‐patient psychiatric units: a study of nursing issues in 31 cases

2000· article· en· W2022513255 on OpenAlexaff
Kevin Gournay, Len Bowers

Bibliographic record

VenueJournal of Advanced Nursing · 2000
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsInstitute of Health Services and Policy Research
Fundersnot available
KeywordsInquestAuditHarmReceiptMedicinePsychiatryNursingFamily medicinePsychologyPolitical science

Abstract

fetched live from OpenAlex

A significant number of incidents of suicide and self-harm occur whilst patients are in receipt of care as in-patients. This audit comprises 31 cases which were referred to the first author for expert opinion, each case being the subject of legal action brought by patients and/or their families. The cases were referred from 31 different NHS trusts across England. All concerned suicide/serious self-harm in people in receipt of in-patient care. The aims of this audit were to carry out a detailed assessment of the 31 individual cases, so as to provide a nursing dimension to already established enquiries in this area and also to examine whether specific issues might be the subject of more systematic research. Further, this paper aims to provide some insights in the area of litigation, where nurses are becoming increasingly involved. The same broad approach to information-gathering and analysis was used, comprising a systematic review of case records, trust policies, expert reports and, where appropriate, inquest transcriptions. The sample comprised 12 suicides and 19 cases of serious self-harm. Factors associated with these events include: being male, having a dual diagnosis of mental illness and drug/alcohol abuse, and age between 21 and 30 years. Of the 12 deaths, five occurred in hospital, four by hanging and one by drowning. The audit highlighted environmental factors associated with these events which, arguably, could be simply addressed. There was a considerable variation in the content and quality of observation policy and practice. The results of this audit point to the need for further research but, above all, provide evidence requiring urgent action by the Department of Health regarding the setting of national standards.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.397
Threshold uncertainty score0.685

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.037
GPT teacher head0.383
Teacher spread0.347 · 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 designObservational
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

Citations55
Published2000
Admission routes1
Has abstractyes

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