A non-specialist worker delivered digital assessment of cognitive development (DEEP) in young children: a longitudinal validation study in rural India

Bhavnani, Supriya; Ranjan, Alok; Mukherjee, Debarati; Divan, Gauri; Prakash, Amit; Yadav, Astha; Lal, Chaman; Gajria, Diksha; Irfan, Hiba; Sharma, Kamal Kant; Todkar, Smita Dattatraya; Patel, Vikram; McCray, Gareth

Abstract

Background Cognitive development in early childhood is critical for life-long well-being. Existing cognitive development surveillance tools require lengthy parental interviews and observations of children. Developmental Assessment on an E-Platform (DEEP) is a digital tool designed to address this gap by providing a gamified, direct assessment of cognition in young children which can be delivered by front-line providers in community settings.

Methods This longitudinal study recruited children from the SPRING trial in rural Haryana, India. DEEP was administered at 39 (SD 1; N=1359), 60 (SD 5; N=1234) and 95 (SD 4; N=600) months and scores were derived using item response theory. Criterion validity was examined by correlating DEEP-score with age, Bayley’s Scales of Infant Development (BSID-III) cognitive domain score at age 3 and Raven’s Coloured Progressive Matrices (CPM) at age 8; predictive validity was examined by correlating DEEP-scores at preschool-age with academic performance at age 8 and convergent validity through correlations with height-for-age z-scores (HAZ) and early life adversities.

Findings DEEP-score correlated strongly with age (r=0.83, 95% CI 0.82-0.84) and moderately with BSID-III (r=0.50, 0.39-0.60) and CPM (r=0.37; 0.30 – 0.44). DEEP-score at preschool-age predicted academic outcomes at school-age (0.32; 0.25 – 0.41) and correlated positively with HAZ and negatively with early life adversities.

Interpretation DEEP provides a valid, scalable method for cognitive assessment. It’s integration into developmental surveillance programs could aid in monitoring and early detection of cognitive delays, enabling timely interventions.

Citation

Bhavnani, S., Ranjan, A., Mukherjee, D., Divan, G., Prakash, A., Yadav, A., Lal, C., Gajria, D., Irfan, H., Sharma, K. K., Todkar, S. D., Patel, V., & McCray, G. A non-specialist worker delivered digital assessment of cognitive development (DEEP) in young children: a longitudinal validation study in rural India

• Working Paper Type: Working Paper
• Deposit Date: Apr 17, 2025
• Public URL: https://keele-repository.worktribe.com/output/1079050
• Publisher URL: https://www.medrxiv.org/content/10.1101/2024.11.04.24316724v1