A Multisite Canadian Study of Outcome of First-Episode Psychosis Treated in Publicly Funded Early Intervention Services
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to determine 1-year symptomatic outcome and its predictors in patients with FEP treated at 3 different publicly funded sites. METHOD: We evaluated FEP patients (n = 172) treated in specialized programs in 2 medium-sized centres and 1 large urban centre with an identical protocol for demographic variables, diagnosis, and duration of untreated psychosis (DUP) at entry, and positive, negative, and general psychopathology symptoms at entry, 6 months, and 1 year. We used a mixed model analysis of variance, with time and centre and interaction between time and centre as fixed effects and sex and DUP as covariates, to analyze data. RESULTS: A significant effect of time and time x centre interaction on positive, negative, and general symptom outcome was shown after controlling for ethnicity, education, and diagnosis. Patients showed significantly better outcome on all dimensions of symptoms in the 2 medium-sized centres, compared with the 1 large urban centre. Sex had a significant effect on negative and general symptoms, while DUP had no effect on any outcome measure. CONCLUSIONS: Similarly enriched EI services may produce different outcomes, even within a relatively homogeneous mental health system.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | high |
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".