Self-harm in children and young people who die by suicide: UK-wide consecutive case series
Bibliographic record
Abstract
Background An improved understanding of the factors associated with self-harm in young people who die by suicide can inform suicide prevention measures. Aims To describe sociodemographic and clinical characteristics and service utilisation related to self-harm in a national sample of young people who died by suicide. Method We carried out a descriptive study of self-harm in a national consecutive case series ( N = 544) of 10- to 19-year-olds who died by suicide over 3 years (2014–2016) in the UK as identified from national mortality data. Information was collected from coroner inquest hearings, child death investigations, criminal justice system and National Health Service serious incident reports. Results Almost half (49%) of these young people had harmed themselves at some point in their lives, a quarter (26%) in the 3 months before death. Girls were twice as likely as boys to have recent self-harm (40 v . 20%; P < 0.001). Compared to the no self-harm group, young people with recent self-harm were more likely to have a mental illness diagnosis (63 v. 23%; P < 0.001); misused alcohol (19 v. 9%; P = 0.07); experienced physical, sexual or emotional abuse (17 v. 3%; P < 0.01); and recent life adversity (95 v. 75%; P < 0.001). Furthermore, they were more likely to be in contact with mental health services (60 v. 10%), or emergency departments or general physicians for a mental health condition (52 v. 10%) in the 3 months before death. Conclusions Presentation to services in young people who self-harm is an important opportunity to intervene through comprehensive psychosocial assessment and treatment of underlying conditions.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".