Violent behaviour in adolescents: assessment and formulation using a structured risk assessment tool
Bibliographic record
Abstract
SUMMARY Teenagers often present in crisis with risk issues, mainly risk to self but sometimes risk to others. Adolescent violence is commonplace and is not just the remit of adolescent forensic psychiatry. Clinicians may lack confidence assessing risk of violence and can neglect vital areas that are essential to reduce risk. Use of structured violence risk assessments enables the multi-agency professional network to formulate a young person's presentation and their violence in a holistic way and consequently develop targeted risk management plans addressing areas such as supervision, interventions and case management to reduce the risk of future violence. Of the several validated tools developed for young people, the Structured Assessment of Violence Risk – Youth (SAVRY™) is that most used by UK-based forensic adolescent clinicians. This article outlines the epidemiology, causes and purposes of violence among adolescents; discusses types of risk assessment tool; explores and deconstructs the SAVRY; and presents a fictitious risk formulation.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".