‘Opening up the mind’: problem-solving therapy delivered by female lay health workers to improve access to evidence-based care for depression and other common mental disorders through the Friendship Bench Project in Zimbabwe
Bibliographic record
Abstract
BACKGROUND: There are few accounts of evidence-based interventions for depression and other common mental disorders (CMDs) in primary care in low-income countries. The Friendship Bench Project is a collaborative care mental health intervention in primary care in Harare for CMDs which began as a pilot in 2006. CASE PRESENTATION: We employed a mixture of quantitative and qualitative approaches to investigate the project's acceptability and implementation, 4-8 years after the initial pilot study. We carried out basic descriptive analyses of routine data on attendance collected between 2010 and 2014. We also conducted five focus group discussions (FGDs) with LHWs in 2013 and 12 in-depth interviews, six with staff and six with patients, to explore experiences of the intervention, which we analysed using grounded theory. Results show that the intervention appears highly acceptable as evidenced by a consistent number of visits between 2010 and 2014 (mean 505 per year, SD 132); by the finding that the same team of female community LHWs employed as government health promoters continue to deliver assessment and problem-solving therapy, and the perceived positive benefits expressed by those interviewed. Clients described feeling 'relieved and relaxed' after therapy, and having their 'mind opened', and LHWs describing satisfaction from being agents of change. Characteristics of the LHWs (status in the community, maturity, trustworthiness), and of the intervention (use of locally validated symptom screen, perceived relevance of problem-solving therapy) and continuity of the LHW team appeared crucial. Challenges to implementation included the LHWs ongoing need for weekly supervision despite years of experience; the supervisors need for supervision for herself; training needs in managing suicidal and hostile clients; poor documentation; lack of follow-up of depressed clients; and poor access to antidepressants. CONCLUSIONS: This case study shows that a collaborative care intervention for CMDs is positively received by patients, rewarding for LHWs to deliver, and can be sustained over time at low cost. Next steps include evaluation of the impact of the intervention through a randomised trial, and testing of a technological platform for supporting supervision and monitoring clients' attendance.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".