Three-year outcome of phase-specific early intervention for first-episode psychosis: a cohort study in Hong Kong
Bibliographic record
Abstract
AIM: Although phase-specific early intervention for first-episode psychosis has been implemented in many different parts of the world, limited medium-term outcome data are available in non-Western populations with relatively low mental health resources. The study aimed to determine the effectiveness of phase-specific early intervention in first-episode psychosis. METHOD: In this cohort study, we compared the 3-year outcome of 700 first-episode psychosis patients who received phase-specific early intervention with that of 700 patients matched for age, sex and diagnosis who received standard psychiatric care prior to early intervention. Using a structured data acquisition procedure, we determined functional outcome, symptom levels, relapse, recovery, suicidal behaviour and service utilization from clinical records. RESULTS: Patients in the early intervention group had longer full-time employment or study (P<0.001), fewer days of hospitalization (P<0.001), less severe positive symptoms (P=0.006), less severe negative symptoms (P =0.001), fewer suicides (P=0.009) and fewer disengagements (P=0.002) than the historical control group. Additionally, more patients in the early intervention group experienced a period of recovery (P=0.001), but the two groups had similar rates of relapse (P=0.08) and durations of untreated psychosis (P=0.72). CONCLUSIONS: The 3-year outcome in phase-specific early intervention compared favourably with that of standard psychiatric care, particularly with respect to functional outcome and reduction in hospitalizations, suicides and disengagements. However, intervention did not appear to reduce the rate of relapse.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".