Self-harm in Child and Adolescent Psychiatric Inpatients: A Retrospective Study.
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".