Prolonged duration of untreated psychosis in nonaffective first-episode psychotic disorders compared to other psychoses
Bibliographic record
Abstract
Introduction. While the consequences of the duration of untreated psychosis (DUP) represent an active area of research, less attention has been focused on the determinants of the DUP. This analysis assessed several potential determinants of the DUP from a practice-based survey. Method. Data on selected patients in their first treatment episode for psychotic symptoms were obtained from 104 practicing physicians. Patients with a long DUP (n=31), defined as >4 weeks, were compared to patients with a short DUP (≤4 weeks, n=28). Results. The long-DUP group had a higher percentage of patients with nonaffective psychotic disorders (58%) compared to the short-DUP group (29%). The median DUP among those with nonaffective psychotic disorders was 8 weeks, compared to 3 weeks among those with other psychotic disorders. The long-DUP group had a higher percentage of patients rated as uncertain about or denying a mental illness (55% compared to 25% in the short-DUP group). The presence of negative symptoms approached significance in terms of differentiating between the two groups, with 66% of the long-DUP group having negative symptoms compared to 39% of the short-DUP group. When three variables (nonaffective psychotic disorder versus other psychoses, insight, and negative symptoms) were entered into a logistic regression model, only diagnostic category remained an independently significant predictor. Conclusion. In this practice-based sample, patients with nonaffective psychotic disorders were more likely to have a longer DUP than patients who developed psychotic symptoms in the context of mood disorders, substance use disorders, or other disorders.
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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 | 0.000 | 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) | 0.002 | 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".