Assessing risk for aggression in forensic psychiatric inpatients: An examination of five measures.
Why this work is in the frame
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Bibliographic record
Abstract
The present study examined risk for inpatient aggression, including treatment-related changes in risk, using a battery of 5 forensic instruments. The relative contributions of different types of risk factors to the assessment of risk for inpatient outcomes were also assessed. The Historical-Clinical-Risk Management-20V3, Short-Term Assessment of Risk and Treatability, Violence Risk Scale, Violence Risk Appraisal Guide-Revised, and Psychopathy Checklist-Revised were rated from archival information sources on a sample of 99 adult forensic inpatients from a Canadian psychiatric hospital. Pretreatment and posttreatment ratings were obtained on all dynamic study measures; associations between risk and change ratings with inpatient aggression were examined. Significant pretreatment-posttreatment differences were found on the HCR-20V3, START, and VRS; pretreatment scores on these measures each demonstrated predictive accuracy for inpatient aggression (AUC = .68 to .76) whereas the PCL-R and VRAG-R did not. HCR-20V3, VRS, and START dynamic scores demonstrated incremental predictive validity for inpatient aggression to varying degrees after controlling for static risk factors. Dynamic change scores from these 3 measures also demonstrated incremental concurrent associations with reductions in inpatient aggression after controlling for baseline risk. Several instruments demonstrated predictive validity for inpatient aggression and clinical/dynamic risk and change scores had unique associations with this outcome. The present findings suggest that risk assessments using the HCR-20 V3, START, and VRS may inform the management and reduction of inpatient aggression, as well as assessments of dynamic risk more generally. (PsycINFO Database Record
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it