Center for Child and Family Policy, Sanford School of Public Policy, Duke University, Durham, North Carolina, United States of America.
Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.
PLoS One. 2023 Aug 30;18(8):e0290148. doi: 10.1371/journal.pone.0290148. eCollection 2023.
Ecological momentary assessment (EMA) minimizes recall burden and maximizes ecological validity and has emerged as a valuable tool to characterize individual differences, assess contextual associations, and document temporal associations. However, EMA has yet to be reliably utilized in young children, in part due to concerns about responder reliability and limited compliance. The present study addressed these concerns by building a developmentally appropriate EMA smartphone app and testing the app for feasibility and usability with young children ages 4-10 (N = 20; m age = 7.7, SD = 2.0).
To pilot test the app, children completed an 11-item survey about their mood and behavior twice a day for 14 days. Parents also completed brief surveys twice a day to allow for parent-child comparisons of responses. Finally, at the end of the two weeks, parents provided user feedback on the smartphone app.
Results indicated a high response rate (nearly 90%) across child surveys and high agreement between parents and children ranging from 0.89-0.97.
Overall, findings suggest that this developmentally appropriate EMA smartphone app is a reliable and valid tool for collecting in-the-moment data from young children outside of a laboratory setting.
生态瞬时评估(EMA)最大限度地减少了回忆负担,最大限度地提高了生态有效性,并已成为描述个体差异、评估情境关联和记录时间关联的有价值的工具。然而,EMA 在幼儿中尚未得到可靠地应用,部分原因是担心应答者的可靠性和有限的依从性。本研究通过构建一个适合儿童发展的 EMA 智能手机应用程序来解决这些问题,并对 4-10 岁的幼儿(N=20;m 年龄=7.7,SD=2.0)进行了可行性和可用性测试。
为了对应用程序进行试点测试,孩子们每天两次完成一项关于他们的情绪和行为的 11 项调查,为期 14 天。父母也每天两次完成简短的调查,以便对父母和孩子的反应进行比较。最后,在两周结束时,父母对智能手机应用程序提供了用户反馈。
结果表明,儿童调查的应答率很高(近 90%),父母和孩子之间的一致性也很高,范围从 0.89-0.97。
总体而言,这些发现表明,这种适合儿童发展的 EMA 智能手机应用程序是一种可靠且有效的工具,可用于在实验室环境之外从幼儿那里收集即时数据。