Clinical and social determinants of duration of untreated psychosis in the ÆSOP first-episode psychosis study
Bibliographic record
Abstract
BACKGROUND: Despite considerable research investigating the relationship between a long duration of untreated psychosis (DUP) and outcomes, there has been much less considering predictors of a long DUP. AIMS: To investigate the clinical and social determinants of DUP in a large sample of patients with a first episode of psychosis. METHOD: All patients with a first episode of psychosis who made contact with psychiatric services over a 2-year period and were living in defined catchment areas in London and Nottingham, UK were included in the AESOP study. Data relating to clinical and social variables and to DUP were collected from patients, relatives and case notes. RESULTS: An insidious mode of onset was associated with a substantially longer DUP compared with an acute onset, independent of other factors. Unemployment had a similar, if less strong, effect. Conversely, family involvement in help-seeking was independently associated with a shorter duration. There was weak evidence that durations were longer in London than in Nottingham. CONCLUSIONS: These findings suggest that DUP is influenced both by aspects of the early clinical course and by the social context.
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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 | 0.003 |
| 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 | 0.001 |
| 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".