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

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. 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), socioeconomic status (SES) and early life adversities. 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 SES and negatively with early life adversities. 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.

Authors

Institutions

Publication Details

Journal
PLOS Digital Health
Published
2025-05-16
DOI
https://doi.org/10.1371/journal.pdig.0000824
Citations
1
Primary Topic
Infant Development and Preterm Care
Type
article
Field-Weighted Citation Impact
3.49

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Astha Yadav, Gareth McCray, Hiba Irfan, Alok Ranjan et al.
1 citations
PLOS Digital Health
Infant Development and Preterm Care
3.49
article

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

Astha Yadav, Gareth McCray, Hiba Irfan, Alok Ranjan, Debarati Mukherjee, Vikram Patel, Gauri Divan, Diksha Gajria, Kamal Kant Sharma, Amit Prakash, Smita Todkar, Chaman Lal
article en
1 citations

Abstract

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. 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), socioeconomic status (SES) and early life adversities. 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 SES and negatively with early life adversities. 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.

PLOS Digital HealthVol. 4(5)
Harvard University (US), Manipal Academy of Higher Education (IN), Sangath (IN), Harvard Global Health Institute (US), Keele University (GB), Public Health Foundation of India (IN)
Wellcome Trust, The Wellcome Trust DBT India Alliance
Openalex Percentile: Top 10%
Infant Development and Preterm Care
3.49
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.