Evaluation and Applications of the Clinically Significant Change Method with the Violence Risk Scale‐Sexual Offender Version: Implications for Risk‐Change Communication
Bibliographic record
Abstract
We examined the use of the clinically significant change (CSC) method with the Violence Risk Scale-Sexual Offender version (VRS-SO), and its implications for risk communication, in a combined sample of 945 treated sexual offenders from three international settings, followed up for a minimum 5 years post-release. The reliable change (RC) index was used to identify thresholds of clinically meaningful change and to create four CSC groups (already okay, recovered, improved, unchanged) based on VRS-SO dynamic scores and amount of change made. Outcome analyses demonstrated important CSC-group differences in 5-year rates of sexual and violent recidivism. However, when baseline risk was controlled via Cox regression survival analysis, the pattern and magnitude of CSC-group differences in sexual and violent recidivism changed to suggest that observed variation in recidivism base rates could be at least partly explained by pre-existing group differences in risk level. Implications for communication of risk-change information and applications to clinical practice are discussed.
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 | 0.057 | 0.148 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".