Mistakes in interpersonal perceptions: Social cognition in aggressive forensic psychiatry patients
Bibliographic record
Abstract
BACKGROUND: While there is an established link between untreated psychosis and aggression, an enhanced understanding of the role of social cognition is still needed. AIMS: To examine social cognitive functioning among patients in a specialist forensic mental health service who had been deemed not criminally responsible for acts of violence due to a psychotic disorder. It was hypothesised, first, that such patients would show reduced social cognitive functioning compared with healthy, nonviolent comparison participants and, second, that those who continued to be aggressive while inpatients would demonstrate significant reductions compared to the now nonaggressive group. METHODS: The study samples were of 10 recently aggressive and 15 not-recently aggressive patients and 20 healthy, nonviolent comparison participants. Each completed the Toronto Empathy Questionnaire (TEQ), the Reading the Mind in the Eyes Test-Revised (RMET) and the Interpersonal Perception Task-15 (IPT-15). RESULTS: There was no significance between group differences on the RMET and TEQ. The patient group as a whole, however, showed significant interpersonal misperceptions, with specific misperceptions on IPT-15 deception and kinship subscales, while at the same time lacking self-awareness of their errors. Misperceptions on the IPT-15 competition subscale were unique to recently aggressive patients. CONCLUSIONS: Select aspects of reduced social cognitive functioning were found among not criminally responsible patients with psychosis who had committed violent acts and who continued to act aggressively while forensic inpatients. These findings enhance our understanding of the role of social cognition in predisposing toward violence and the potential importance of incorporating interventions which improve social cognition directly. We suggest also the potential for future research using virtual reality technologies in treatment.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".