‘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
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».