A randomized controlled trial of an acceptance-based, insight-inducing medication adherence therapy (AIM-AT) for adults with early-stage psychosis
Bibliographic record
Abstract
This study aimed to test the effectiveness of an acceptance-based medication adherence intervention for people with early-stage psychosis. An assessor-blind, three-arm randomized controlled trial design was used. One hundred and twenty-six participants who were adults with ≤3 years of psychosis were recruited from four district Integrated Community Centers for Mental Wellness in Hong Kong. They were randomly assigned to receive a 10-session acceptance-based, insight-inducing medication adherence therapy (AIM-AT) intervention, a conventional psychoeducation group program, or usual treatment (n = 42 per group). Primary outcomes were medication adherence and insight into the illness/treatment. All study outcomes were measured at recruitment and immediately, 6 months, and 12 months post-intervention. Participants in the AIM-AT experienced statistically significant improvements in the primary outcomes (levels of medication adherence and insight into illness/treatment), when compared to those in the other two groups over the 12-month follow-ups. The AIM-AT group also had significantly greater improvements in psychotic symptoms, psychosocial functioning, service satisfaction, length of rehospitalization, and total number of patients hospitalized over the follow-up period. These findings support the effectiveness of the AIM-AT to improve medication adherence, psychosocial health, and service satisfaction in people 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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".