Barriers and facilitators to the integration of depression services in primary care in Vietnam: a mixed methods study
Bibliographic record
Abstract
BACKGROUND: Although the prevalence of depression in Vietnam is on par with global rates, services for depression are limited. The government of Vietnam has prioritized enhancing depression care through primary healthcare (PHC) and efforts are currently underway to test and scale-up psychosocial interventions throughout the country. With these initiatives in progress, it is important to understand implementation factors that might influence the successful integration of depression services into PHC. As the implementers of these new interventions, primary care providers (PHPs) are well placed to provide important insight into implementation factors affecting the integration of depression services into PHC. This mixed-methods study examines factors at the individual, organizational and structural levels that may act as barriers and facilitators to the integration of depression services into PHC in Vietnam from the perspective of PHPs. METHODS: Data collection took place in Hanoi, Vietnam in 2014. We conducted semi-structured interviews with PHPs (n = 30) at commune health centres and outpatient clinics in one rural and one urban district of Hanoi. Theoretical thematic analysis was used to analyse interview data. We administered an online survey to PHPs at n = 150 randomly selected communes across Hanoi. N = 226 PHPs responded to the survey. We used descriptive statistics to describe the study variables acting as barriers and facilitators and used a chi-square test of independence to indicate statistically significant (p < .05) associations between study variables and the profession, location and gender of PHPs. RESULTS: Individual-level barriers include low level of knowledge and familiarity with depression among PHPs. Organizational barriers include low resource availability in PHC and low managerial discretion. Barriers at the structural level include limited mental health training among all PHPs and the existing programmatic structure of PHC in Vietnam, which sets mental health apart from general services. Facilitators at the individual level include positive attitudes among PHPs towards people with depression and interest in undergoing enhanced training in depression service delivery. CONCLUSIONS: While facilitating factors at the individual level are encouraging, considerable barriers at the structural level must be addressed to ensure the successful integration of depression services into PHC in Vietnam.
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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 | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".