The association of a novel digital tool for assessment of early childhood cognitive development, 'DEvelopmental assessment on an E-Platform (DEEP)', with growth in rural India: A proof of concept study. (July 2021)

• Record Type: Journal Article
• Authors: Bhavnani, Supriya; Mukherjee, Debarati; Bhopal, Sunil; Sharma, Kamal Kant; Dasgupta, Jayashree; Divan, Gauri; Soremekun, Seyi; Roy, Reetabrata; Kirkwood, Betty; Patel, Vikram
• Is Part Of: EClinicalMedicine. Volume 37(2021)
• Publication Date: 2021-07
• Subjects: Early childhood development -- Serious game -- Cognitive development -- Digital assessment; Medicine -- Research -- Periodicals; Medical policy -- Periodicals; Clinical Medicine; Health Policy; Public Health; Medical policy; Medicine -- Research; Periodical; Electronic journals; Periodicals; 613
• DOI: 10.1016/j.eclinm.2021.100964
• Languages: English
• ISSNs: 2589-5370

Abstract

Abstract: Background: There is an urgent need to fill the gap of scalable cognitive assessment tools for preschool children to enable identification of children at-risk of sub-optimal development and to support their timely referral into interventions. We present the associations between growth in early childhood, a well-established marker of cognitive development, and scores on a novel digital cognitive assessment tool called DEvelopmental Assessment on an E-Platform (DEEP) on a sample of 3-year old pre-schoolers from a rural region in north India. Methods: Between February 2018 and March 2019, 1359 children from the Sustainable Programme Incorporating Nutrition and Games (SPRING) programme were followed up at 3-years age and data on DEEP, anthropometry and a clinical developmental assessment, the Bayley's Scale of Infant and Toddler Development, 3rd edition (BSID-III) was collected. DEEP data from 200 children was used to train a machine learning algorithm to predict their score on the cognitive domain of BSID-III. The DEEP score of the remaining 1159 children was then predicted using this algorithm to examine the cross-sectional and prospective association of growth with the DEEP score. Findings: The magnitude of the concurrent positive association between height-for-age and cognitive z -scores in 3-year olds was similar when cognition was measured by BSID-III (0.20 standard deviations increase for every unit change in specifically age-adjusted height (HAZ), 95% CI = 0.06–0.35) and DEEP (0.26 CI, 0.11–0.41). A similar positive prospective relationship was found between growth at 18 (0.21 CI, 0.17–0.26) and 12-months (0.18 CI, 0.13–0.23) and DEEP score measured at 3-years. Additionally, the relationship between growth and cognitive development was found to be dependant on socioeconomic status (SES). Interpretation: In this study, we suggest the utility of DEEP, a scalable, digital cognitive assessment tool, to measure cognition in preschool children. Further validation in different and larger datasets is necessary to confirm our findings. Funding: The SPRING Programme was funded through a Wellcome Trust programme grant and the follow-up study by the Corporate Social Responsibility initiative grant from Madura Microfinance Ltd.