Rapid-Cycle Evaluation in an Early Intervention Program for Children With Developmental Disabilities in South India: Optimizing Service Providers' Quality of Work-Life, Family Program Engagement, and School Enrollment
Notice bibliographique
Résumé
Background: This paper explores how implementation and refinement of an early intervention (EI) program for children with delayed development was informed by an iterative, intentional and structured process of measurement. Providing access to early intervention therapy for children in rural areas of India is challenging due to a lack of rehabilitation therapists and programs. Following a biopsychosocial framework and principles of community-based rehabilitation, a non-governmental organization, Amar Seva Sangam (ASSA), overcame those barriers by designing a digital technology supported EI program in rural Tamil Nadu, India. Program objectives included providing service access; supporting program engagement, child development and school enrollment; and positioning the intervention for scale-up. This paper contributes to a growing body of literature on how program design and implementation can be informed through a cyclical process of data collection, analysis, reflection, and adaptation. Methods: Through several strands of data collection, the design and implementation of the EI program was adapted and improved. This included qualitative data from focus groups and interviews with caregivers and service providers, and a mobile application that collected and monitored longitudinal quantitative data, including program engagement rates, developmental progression, caregiver outcomes, and school enrollment status. Results: Measurements throughout the program informed decision-making by identifying facilitators and barriers to service providers' quality of work-life, family program engagement, and school enrollment. Consultation with key stakeholders, including caregivers and service providers, and data driven decision making led to continual program changes that improved service provider quality of work-life, program engagement and school enrollment. These changes included addressing gender-related work challenges for service providers; forming caregiver support networks; introducing psychological counseling for caregivers; providing medical consultations and assistive devices; creating community awareness programs; improving access to therapy services; focusing on caregiver education, motivation and support; and advocacy for accessibility in schools. Conclusion: The process of using evidence-informed and stakeholder driven adaptations to the early intervention program, led to improved service provider quality of work-life, greater program engagement, improved school enrollment and positioned the intervention for scale-up, providing lessons that may be beneficial in other contexts.
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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 | 0,007 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 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 ».