Is supported self-management for depression effective for adults in community-based settings in Vietnam?: a modified stepped-wedge cluster randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: This study tested the effectiveness of a supported self-management (SSM) intervention to reduce symptoms of depression among adults compared with enhanced treatment as usual in community-based and primary care settings in Vietnam. METHODS: The cluster randomized trial included 376 adults in 32 communes in eight provinces. Eligible participants scored > 7 on the SRQ-20 depression scale. Patients with severe symptoms were excluded and referred to tertiary care. Randomization took place at the commune level. The immediate intervention group included 16 communes with 190 participants and the delayed group included 16 communes with 186 participants. Participants in communes randomized to the immediate intervention group received a two-month course of SSM, consisting of a workbook and supportive coaching. Those in communes randomized to the delayed group received enhanced treatment as usual and, for ethical purposes, received the SSM intervention after 4 months. The primary outcome is the effect of SSM on reduction in depression scores as indicated by a reduced proportion of participants with SRQ-20 scores > 7 at 2 months after commencement of SSM intervention. Blinding was not possible during intervention delivery but outcome assessors were blinded. Analysis was intention-to-treat. RESULTS: At 2 months, 26.4% of the intervention group and 42.3% of the delayed group had SRQ-20 scores > 7. The adjusted odds ratio of having depression between the intervention and control was 0.42 (p < 0.0001), 95% CI (0.28, 0.63). Receiving the intervention thus reduces the odds of having depression by 58%, compared with receiving the control after 2 months of treatment. No adverse events were reported. CONCLUSIONS: This trial is registered at ClinicalTrials.gov, number NCT03001063.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| 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 | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".