ArticleFrontiers in psychology2020
Proof of Concept of a Gamified DEvelopmental Assessment on an E-Platform (DEEP) Tool to Measure Cognitive Development in Rural Indian Preschool Children.
Article in Frontiers in psychology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed, 2 syntheses or guidelines pooled it, 26 citations in OpenAlex.
- Naturalistic assessments across the lifespan: Systematic review of inhibition measures in ecological settings.Neuroscience and biobehavioral reviews · 2024Pooled it
- Evaluating the validity of game-based assessments measuring cognitive function among children and adolescents: A systematic review and meta-analysis.Progress in brain research · 2023Pooled it
- Measurement of executive functioning in pre-school aged children in India: a scoping review.Current psychology (New Brunswick, N.J.) · 2026Article
- Through children's own lenses: assessing risky play tendencies via a tablet-based interface.Frontiers in psychology · 2026Article
- A systematic bibliometric and meta analysis of key factors and emerging AI and ML insights in shaping child cognitive development.Discover mental health · 2025Review
- Application of machine learning in early childhood development research: a scoping review.BMJ open · 2025Article
- A non-specialist worker delivered digital assessment of cognitive development (DEEP) in young children: A longitudinal validation study in rural India.PLOS digital health · 2025Article
- Scalable Transdiagnostic Early Assessment of Mental Health (STREAM): a study protocol.BMJ open · 2024Article
- Protocol of the Nutritional, Psychosocial, and Environmental Determinants of Neurodevelopment and Child Mental Health (COINCIDE) study.Wellcome open research · 2024Article
- The current landscape and future of tablet-based cognitive assessments for children in low-resourced settings.PLOS digital health · 2023Review
- Research Domain Criteria (RDoC): Progress and Potential.Current directions in psychological science · 2022Article
- The effect of cumulative early life adversities, and their differential mediation through hair cortisol levels, on childhood growth and cognition: Three-year follow-up of a birth cohort in rural India.Wellcome open research · 2022Article
- The Making and Evaluation of Digital Games Used for the Assessment of Attention: Systematic Review.JMIR serious games · 2021Review
- 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.EClinicalMedicine · 2021Article
- Converging disciplines for assessing child development.iScience · 2021Article
- Promoting Developmental Potential in Early Childhood: A Global Framework for Health and Education.International journal of environmental research and public health · 2021Review
- Evolving Concepts of the Schizophrenia Spectrum: A Research Domain Criteria Perspective.Frontiers in psychiatry · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Over 250 million children in developing countries are at risk of not achieving their developmental potential, and unlikely to receive timely interventions because existing developmental assessments that help identify children who are faltering are prohibitive for use in low resource contexts. To bridge this "detection gap," we developed a tablet-based, gamified cognitive assessment tool named DEvelopmental assessment on an E-Platform (DEEP), which is feasible for delivery by non-specialists in rural Indian households and acceptable to all end-users. Here we provide proof-of-concept of using a supervised machine learning (ML) approach benchmarked to the Bayley's Scale of Infant and Toddler Development, 3rd Edition (BSID-III) cognitive scale, to predict a child's cognitive development using metrics derived from gameplay on DEEP. Two-hundred children aged 34-40 months recruited from rural Haryana, India were concurrently assessed using DEEP and BSID-III. Seventy percent of the sample was used for training the ML algorithms using a 10-fold cross validation approach and ensemble modeling, while 30% was assigned to the "test" dataset to evaluate the algorithm's accuracy on novel data. Of the 522 features that computationally described children's performance on DEEP, 31 features which together represented all nine games of DEEP were selected in the final model. The predicted DEEP scores were in good agreement (ICC [2,1] > 0.6) and positively correlated (Pearson's
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.