The Validity and Reliability of the Violence Risk Scale–Youth Version in a Diverse Sample of Violent Young Offenders
Bibliographic record
Abstract
The Violence Risk Scale–Youth Version (VRS-YV; S. Wong, Lewis, Stockdale, & Gordon, 2004-2011) is a risk assessment and treatment planning tool for youths designed to assess violence risk, identify dynamic risk factors or treatment targets, and evaluate changes in risk from treatment or other change agents. We examined the psychometric properties of the VRS-YV on a diverse sample of 147 young offenders. The tool demonstrated high internal consistency (α = .90) and interrater reliability (intraclass correlation coefficient [ICC] = .90). Exploratory factor analysis (EFA) identified three factors: Interpersonal Aggression, Antisocial Tendencies, and Family Problems. VRS-YV static, dynamic, and total scores significantly predicted violent and general recidivism, including youth and adult outcomes, with moderate to high accuracy (area under the curve [AUC] = .65-.77); however, results varied among ethnic/cultural, gender, and developmental subgroups. The VRS-YV also demonstrated strong convergent validity with two well-established youth forensic assessment tools. Clinical implications of these findings and future research directions are discussed in this article.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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".