Antipsychotic prescribing practices and their association with rehospitalization in a forensic psychiatric sample
Bibliographic record
Abstract
While there is extensive literature examining the effectiveness of antipsychotic prescribing to patients with schizophrenia spectrum or other psychotic disorders in general psychiatric services, there is a dearth of studies examining antipsychotic prescribing practices and their effectiveness in forensic psychiatric services. Forensic psychiatric patients have unique challenges often due to their high-profile offences, public scrutiny, and legal requirements. This longitudinal, retrospective study aimed to examine antipsychotic prescribing and rehospitalization rates in a forensic psychiatric sample, along with relevant socio-demographic, clinical, and forensic characteristics. All patients had a psychotic illness and were prescribed antipsychotic medication. The sample included 153 patients, of which the majority were male (85.6%), Caucasian (71.2%), middle aged (30s to 50s), had schizophrenia or schizoaffective disorder (76.5%), had a substance use disorder (62.1%), and had a most serious index offence against the person (80.4%). Atypical antipsychotics accounted for the majority of antipsychotic prescriptions (75.9%) and the sample had an antipsychotic polypharmacy rate of 39.9%. The sample was divided into four primary antipsychotic formulation types, which were oral (34.0%), injection (39.2%), clozapine (19.0%), and subtherapeutic (7.8%). Regarding rehospitalization, 52.9% of the sample was rehospitalized, with the average number of rehospitalizations being 1.2 (SD = 1.7) and proportion of the follow up period rehospitalized being 16.4% (SD = 27.7%). Patients prescribed clozapine had numerically lower rates of rehospitalization than those prescribed oral and injection formulation types, but it was not statistically significant. With a 19.0% prescription rate, clozapine may be underutilized in this sample. Further research is needed to demonstrate the potential benefits of clozapine regarding rehospitalization in forensic psychiatric patients, as has already been done in general psychiatry. Advancing treatment of the high-profile forensic population can reduce stigma toward people with mental illness and criminal justice involvement.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".