The effectiveness of a Supported Self-management task-shifting intervention for adult depression in Vietnam communities: study protocol for a randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Depressive disorders are one of the leading causes of disease and disability worldwide. In Vietnam, although epidemiological evidence suggests that depression rates are on par with global averages, services for depression are very limited. In a feasibility study that was implemented from 2013 to 2015, we found that a Supported Self-management (SSM) intervention showed promising results for adults with depression in the community in Vietnam. This paper describes the Mental Health in Adults and Children: Frugal Innovations (MAC-FI) trial protocol that will assess the effectiveness of the SSM intervention, delivered by primary care and social workers, to community-based populations of adults with depression in eight Vietnamese provinces. METHODS/DESIGN: The MAC-FI program will be assessed using a stepped-wedge, randomized controlled trial. Study participants are adults aged 18 years and over in eight provinces of Vietnam. Study participants will be screened at primary care centres and in the community by health and social workers using the Self-reporting Questionnaire-20 (SRQ-20). Patients scoring >7, indicating depression caseness, will be invited to participate in the study in either the SSM intervention group or the enhanced treatment as usual control group. Recruited participants will be further assessed using the World Health Organization's Disability Assessment Scale (WHODAS 2.0) and the Cut-down, Annoyed, Guilty, Eye-opener (CAGE) Questionnaire for alcohol misuse. Intervention-group participants will receive the SSM intervention, delivered with the support of a social worker or social collaborator, for a period of 2 months. Control- group participants will receive treatment as usual and a leaflet with information about depression. SRQ-20, WHODAS 2.0 and CAGE scores will be taken by blinded outcome assessors at baseline, after 1 month and after 2 months. The primary analysis method will be intention-to-treat. DISCUSSION: This study has the potential to add to the knowledge base about the effectiveness of a SSM intervention for adult depression that has been validated for the Vietnamese context. This trial will also contribute to the growing body of evidence about the effectiveness of low-cost, task-shifting interventions for use in low-resource settings, where specialist mental health services are often limited. TRIAL REGISTRATION: Retrospectively registered at ClinicalTrials.gov, identifier: NCT03001063 . Registered on 20 December 2016.
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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 | 0.030 | 0.026 |
| Meta-epidemiology (narrow) | 0.008 | 0.004 |
| Meta-epidemiology (broad) | 0.016 | 0.007 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.068 | 0.009 |
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".