Concurrent validity of the personality assessment screener in a large sample of offenders.
Bibliographic record
Abstract
Mental health problems are disproportionately prevalent in forensic and correctional settings, and there have been numerous attempts to develop screening tools to evaluate individuals in such contexts. This study investigates the clinical utility of the Personality Assessment Screener (PAS; Morey, 1997), a brief self-report measure of risk for emotional and behavioral dysfunction, in a large mixed-gender offender sample (N = 1,658). The PAS is a 22-item measure derived from the Personality Assessment Inventory (PAI; Morey, 1991, 2007), a more comprehensive self-report instrument widely used to assess for psychological disturbances among forensic and correctional populations. We examined the ability of the PAS to concurrently predict clinically significant elevations on the PAI and several other indicators of symptomatology and dysfunction. Collectively, results suggest that PAS total and element (subscale) scores show considerable promise in screening inmates for serious problems with emotional and behavioral functioning, though interpretive ranges used to categorize PAS scores in clinical and community settings may require revision for criminal justice populations. We discuss the applied value of the PAS for detecting specific areas of dysfunction relevant to risk management (e.g., aggression, suicidality) and for concentrating resources on offenders with the most immediate and severe need for psychological services. (PsycINFO Database Record
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 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".