Long‐term effects of a community intervention for early identification of first‐episode psychosis
Bibliographic record
Abstract
OBJECTIVE: To assess whether an Early Case Identification Program (ECIP) for first-episode psychosis (FEP), which showed no significant short-term effects, has a delayed impact on duration of untreated psychosis (DUP). METHOD: Using a historical control design, FEP patients were assessed on clinical variables over three consecutive phases, 2 years prior, 2 years during and 3 years after implementation of the ECIP. Additional analyses were conducted on non-affective and schizophrenia spectrum psychoses cases only. RESULTS: There was no overall significant difference in DUP across the three phases. For cases treated within the first year of illness a nonsignificant reduction in DUP to less than 2 months observed during the active phase was sustained post-ECIP. CONCLUSION: In some jurisdictions community-wide early case detection may fail to have an immediate or delayed effect on DUP, especially for cases who normally present for treatment with DUP >1 year.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".