Risk Assessment Instruments in Clinical Practice
Bibliographic record
Abstract
OBJECTIVE: To determine whether the items in one of the most widely validated instruments of violence risk assessment, the Historical-Clinical-Risk Management-20 (HCR-20), are used in review board hearings to assess the risk of violence by people found Not Criminally Responsible on account of Mental Disorder (NCRMD). METHOD: This study was conducted from October 2004 to August 2006 in Quebec's sole forensic psychiatric hospital and 2 large civil psychiatric hospitals designated for the care of people declared NCRMD in the Montreal metropolitan area. The risk assessments presented by clinicians at annual review board hearings and the boards' rationale for the release or detention of people found NCRMD were contrasted with the risk assessments conducted by the research team using the HCR-20. The final sample was comprised of 96 men. RESULTS: Very few of the risk factors identified by prior research (HCR-20 items) were mentioned in the hearing process, whether in clinical reports, discussions during the hearing, or in the disposition justification. CONCLUSIONS: The findings confirm that there remains a significant gap between research evidence and risk assessment practice.
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 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 | 0.096 | 0.346 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".