Bhavnani Supriya, Ranjan Alok, Mukherjee Debarati, Divan Gauri, Prakash Amit, Yadav Astha, Lal Chaman, Gajria Diksha, Irfan Hiba, Sharma Kamal Kant, Todkar Smita, Patel Vikram, McCray Gareth
Child Development Group, Sangath, Saket, Delhi, India.
Indian Institute of Public Health Bengaluru, Public Health Foundation of India, Bengaluru, India.
PLOS Digit Health. 2025 May 16;4(5):e0000824. doi: 10.1371/journal.pdig.0000824. eCollection 2025 May.
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.
幼儿期的认知发展对终身幸福至关重要。现有的认知发展监测工具需要长时间的家长访谈和对儿童的观察。电子平台上的发育评估（DEEP）是一种数字工具，旨在通过提供一种游戏化的、对幼儿认知的直接评估来填补这一空白，这种评估可以由社区环境中的一线服务提供者进行。这项纵向研究从印度哈里亚纳邦农村的SPRING试验中招募儿童。在39（标准差1；N = 1359）、60（标准差5；N = 1234）和95（标准差4；N = 600）月龄时进行DEEP评估，并使用项目反应理论得出分数。通过将DEEP分数与年龄、3岁时的贝利婴儿发展量表（BSID-III）认知领域分数以及8岁时的瑞文彩色渐进矩阵（CPM）进行相关分析来检验效标效度；通过将学龄前的DEEP分数与8岁时的学业成绩进行相关分析来检验预测效度，并通过与年龄别身高z评分（HAZ）、社会经济地位（SES）和早期生活逆境的相关性来检验聚合效度。DEEP分数与年龄高度相关（r = 0.83，95%可信区间0.82 - 0.84），与BSID-III中度相关（r = 0.50，0.39 - 0.60），与CPM中度相关（r = 0.37；0.30 - 0.44）。学龄前的DEEP分数可预测学龄期的学业成绩（0.32；0.25 - 0.41），并与HAZ和SES呈正相关，与早期生活逆境呈负相关。DEEP为认知评估提供了一种有效、可扩展的方法。将其纳入发育监测项目有助于监测和早期发现认知延迟，从而能够及时进行干预。
