Effectiveness of a peer-facilitated, recovery-focused self-illness management program for adults with first-episode psychosis: A randomized controlled trial
Bibliographic record
Abstract
Abstract Background Psychosocial interventions for people with mental illness are increasingly focusing on facilitating recovery and self-care. Despite evidence from Europe on the short-term effects of recovery self-planning programs for people discharged from crisis resolution teams, similar programs and supporting evidence in other countries or healthcare contexts are lacking, particularly regarding cultural adaptation and long-term assessment. This randomized controlled trial compared a 4-month peer-facilitated, recovery-focused self-illness management (Peer-RESIM) program for Chinese adults with first-episode psychosis with psychoeducation (PE) and treatment as usual (TAU). Methods Patients ( N = 198) were recruited from four Integrated Community Centres for Mental Wellness in Hong Kong and randomly assigned to the Peer-RESIM, PE, or TAU group (66/group). The primary outcomes were recovery and functioning levels; the secondary outcomes were psychotic symptoms, problem-solving ability, rehospitalization rate, and service satisfaction. Assessments were conducted at baseline and immediate, 9, and 18 months postintervention. Results The generalized estimating equation test revealed that the Peer-RESIM group reported significantly greater improvements in recovery, functioning, problem-solving ability, psychotic symptoms, average duration of rehospitalizations, and service satisfaction ( p = 0.01–0.04, small to large effect sizes) than the TAU group at all three posttests and the PE group at 18 months postintervention. Conclusions The Peer-RESIM can enhance long-term recovery and self-care in adults with early-stage psychosis.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".