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Record W2584542755

Self-harm in Child and Adolescent Psychiatric Inpatients: A Retrospective Study.

2016· article· en· W2584542755 on OpenAlexaffabout
Naista Zhand, Katherine Matheson, Darren Courtney

Bibliographic record

VenuePubMed · 2016
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsCentre for Addiction and Mental HealthChildren's Hospital of Eastern Ontario
Fundersnot available
KeywordsHarmMedicineDemographicsPsychiatryPsychiatric hospitalInpatient careUnit (ring theory)PsychologyDemographyHealth care
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: This study presents a comprehensive report of children and adolescents who engaged in self-harm during their admission to a psychiatric inpatient unit. METHOD: A chart review was conducted on all admissions to an acute care psychiatric inpatient unit in a Canadian children's hospital over a one-year period. Details on patients with self-harm behaviour during the admission were recorded, including: demographics, presentation to hospital, self-harm behaviour and outcome. Baseline variables for patients with and without self-harm behaviour during admission were compared. RESULTS: Self-harm incidents were reported in 60 of 501 (12%) admissions during the one-year period of the study. Fourteen percent of patients (50 of 351) accounted for total number of 136 self-harm incidents. Half of these incidents (49%) occurred outside of the hospital setting, when patients were on passes. Using the Beck Lethality Scale (0-10), mean severity of the self-injury attempts was 0.33, and there were no serious negative outcomes. CONCLUSION: Self-harm behaviour during inpatient psychiatric admission is a common issue among youth, despite safety strategies in place. While self-harm behaviour is one of the most common reasons for admission to psychiatric inpatient unit, our understanding of nature of these acts during the admission and contributing factors are limited. Further research is required to better understand these factors, and to develop strategies to better support these patients.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.117
Threshold uncertainty score0.233

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.018
GPT teacher head0.261
Teacher spread0.243 · 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 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

Citations13
Published2016
Admission routes2
Has abstractyes

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