{"title":"一名非专业工作人员提供了幼儿认知发展(DEEP)的数字评估:印度农村的一项纵向验证研究。","authors":"Supriya Bhavnani, Alok Ranjan, Debarati Mukherjee, Gauri Divan, Amit Prakash, Astha Yadav, Chaman Lal, Diksha Gajria, Hiba Irfan, Kamal Kant Sharma, Smita Todkar, Vikram Patel, Gareth McCray","doi":"10.1371/journal.pdig.0000824","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":74465,"journal":{"name":"PLOS digital health","volume":"4 5","pages":"e0000824"},"PeriodicalIF":7.7000,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12084064/pdf/","citationCount":"0","resultStr":"{\"title\":\"A non-specialist worker delivered digital assessment of cognitive development (DEEP) in young children: A longitudinal validation study in rural India.\",\"authors\":\"Supriya Bhavnani, Alok Ranjan, Debarati Mukherjee, Gauri Divan, Amit Prakash, Astha Yadav, Chaman Lal, Diksha Gajria, Hiba Irfan, Kamal Kant Sharma, Smita Todkar, Vikram Patel, Gareth McCray\",\"doi\":\"10.1371/journal.pdig.0000824\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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.</p>\",\"PeriodicalId\":74465,\"journal\":{\"name\":\"PLOS digital health\",\"volume\":\"4 5\",\"pages\":\"e0000824\"},\"PeriodicalIF\":7.7000,\"publicationDate\":\"2025-05-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12084064/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"PLOS digital health\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1371/journal.pdig.0000824\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/5/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"PLOS digital health","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1371/journal.pdig.0000824","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/5/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
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.