Violence Risk Assessment of Civil Psychiatric Patients with the HCR-20: Does Gender Matter?
Bibliographic record
Abstract
Over the past three decades, much has been learned about risk factors associated with violence. Subsequently, significant advances have occurred in terms of the conceptualization as well as the communication of violence risk; in particular, numerous risk assessment measures have been developed in order to inform violence prevention efforts. However, most such instruments have been validated predominantly in male populations and research examining their application across genders is scarce. This study investigated the performance of one of the most established violence risk assessment schemes—the Historical/Clinical/Risk Management-20 (HCR-20)—in a sample of 52 men and 48 women receiving short-term inpatient psychiatric care. Results indicated that the HCR-20 as well as its components predicted both the occurrence and imminence of violent outcomes and gender did not moderate those relationships. Exploratory analyses revealed gender differences in the baseline item and scale ratings. Additionally, the HCR-20 demonstrated an association with violent victimization.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".