Technology-assisted task-sharing to bridge the treatment gap for childhood developmental disorders in rural Pakistan: an implementation science case study
Notice bibliographique
Résumé
BACKGROUND: As in many low-income countries, the treatment gap for developmental disorders in Pakistan is nearly 100%. The World Health Organization (WHO) has developed the mental Health Gap Intervention guide (mhGAP-IG) to train non-specialists in the delivery of evidence-based mental health interventions in low-resource settings. However, a key challenge to scale-up of non-specialist-delivered interventions is designing training programs that promote fidelity at scale in low-resource settings. In this case study, we report the experience of using a tablet device-based application to train non-specialist, female family volunteers in leading a group parent skills training program, culturally adapted from the mhGAP-IG, with fidelity at scale in rural community settings of Pakistan. METHODS: The implementation evaluation was conducted as a part of the mhGAP-IG implementation in the pilot sub-district of Gujar Khan. Family volunteers used a technology-assisted approach to deliver the parent skills training in 15 rural Union Councils (UCs). We used the Proctor and RE-AIM frameworks in a mixed-methods design to evaluate the volunteers' competency and fidelity to the intervention. The outcome was measured with the ENhancing Assessment of Common Therapeutic factors (ENACT), during training and program implementation. Data on other implementation outcomes including intervention dosage, acceptability, feasibility, appropriateness, and reach was collected from program trainers, family volunteers, and caregivers of children 6 months post-program implementation. Qualitative and quantitative data were analyzed using the framework and descriptive analysis, respectively. RESULTS: We trained 36 volunteers in delivering the program using technology. All volunteers were female with a mean age of 39 (± 4.38) years. The volunteers delivered the program to 270 caregivers in group sessions with good fidelity (scored 2.5 out of 4 on each domain of the fidelity measure). More than 85% of the caregivers attended 6 or more of 9 sessions. Quantitative analysis showed high levels of acceptability, feasibility, appropriateness, and reach of the program. Qualitative results indicated that the use of tablet device-based applications, and the cultural appropriateness of the adapted intervention content, contributed to the successful implementation of the program. However, barriers faced by family volunteers like community norms and family commitments potentially limited their mobility to deliver the program and impacted the program' reach. CONCLUSIONS: Technology can be used to train non-specialist family volunteers in delivering evidence-based intervention at scale with fidelity in low-resource settings of Pakistan. However, cultural and gender norms should be considered while involving females as volunteer lay health workers for the implementation of mental health programs in low-resource settings.
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Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,009 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,006 | 0,002 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 source (Gemma direct ou Codex distillé), 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 ».