Introducing supported self-management for depression to primary care in Vietnam: A feasibility study in preparation for a randomized controlled trial.
Bibliographic record
Abstract
INTRODUCTION: Although depression is a major contributor to the global burden of disease, services remain scarce in many low- and middle-income countries. In Vietnam, depression services are limited, and the government has recently prioritized primary care and community-based service integration. We conducted a pilot study in 2 districts of Hanoi to test the feasibility of (a) introducing a supported self-management (SSM) intervention for adult depression in primary care in Vietnam, and (b) conducting a randomized controlled trial (RCT) to test the effectiveness of the intervention. METHOD: We conducted focus groups with providers (n = 16) and community members (n = 32) to assess the appropriateness of an Antidepressant Skills Workbook for use in Vietnam. We trained providers (n = 23) to screen patients using the Self-Reporting Questionnaire-20 (SRQ-20) depression scale and to deliver SSM for a 2-month period. A total of 71 patients were eligible to participate in the study, with depression (SRQ-20) and disability (World Health Organization Disability Assessment Schedule 2.0) scores assessed at baseline and 1 and 2 months. RESULTS: Study results demonstrate the feasibility of conducting a full RCT in Vietnam and suggest that SSM is an appropriate care model for the Vietnamese context. There was a statistically significant decrease in depression symptoms on the SRQ-20 and in functional disability in all domains for the World Health Organization Disability Assessment Schedule 2.). CONCLUSION: Feasibility study results suggested that a full RCT was warranted. An unanticipated outcome of the study was the uptake of the model by the Ministry of Labor, Invalids, and Social Affairs in 2 additional provinces. (PsycINFO Database Record
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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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".