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技术为推动全球儿童健康研究带来的新机遇。

Emerging Opportunities Provided by Technology to Advance Research in Child Health Globally.

作者信息

van Heerden Alastair, Leppanen Jukka, Rotheram-Borus Mary Jane, Worthman Carol M, Kohrt Brandon A, Skeen Sarah, Giese Sonja, Hughes Rob, Bohmer Lisa, Tomlinson Mark

机构信息

Human Sciences Research Council, Pietermaritzburg, South Africa.

University of the Witwatersrand, Johannesburg, South Africa.

出版信息

Glob Pediatr Health. 2020 May 17;7:2333794X20917570. doi: 10.1177/2333794X20917570. eCollection 2020.

Abstract

Current approaches to longitudinal assessment of children's developmental and psychological well-being, as mandated in the United Nations Sustainable Development Goals, are expensive and time consuming. Substantive understanding of global progress toward these goals will require a suite of new robust, cost-effective research tools designed to assess key developmental processes in diverse settings. While first steps have been taken toward this end through efforts such as the National Institutes of Health's Toolbox, experience-near approaches including naturalistic observation have remained too costly and time consuming to scale to the population level. This perspective presents 4 emerging technologies with high potential for advancing the field of child health and development research, namely (1) affective computing, (2) ubiquitous computing, (3) eye tracking, and (4) machine learning. By drawing attention of scientists, policy makers, investors/funders, and the media to the applications and potential risks of these emerging opportunities, we hope to inspire a fresh wave of innovation and new solutions to the global challenges faced by children and their families.

摘要

联合国可持续发展目标所要求的当前儿童发育和心理健康纵向评估方法既昂贵又耗时。要切实了解在实现这些目标方面的全球进展,将需要一套全新的强大且具有成本效益的研究工具,旨在评估不同环境中的关键发育过程。虽然通过美国国立卫生研究院的“工具箱”等努力已朝着这一目标迈出了第一步,但包括自然观察在内的贴近体验式方法仍然成本过高且耗时过长,无法扩大到人口层面。本观点介绍了4项在推进儿童健康与发展研究领域具有巨大潜力的新兴技术,即(1)情感计算,(2)普适计算,(3)眼动追踪,以及(4)机器学习。通过引起科学家、政策制定者、投资者/资助者和媒体对这些新兴机遇的应用和潜在风险的关注,我们希望激发新一轮创新以及针对儿童及其家庭所面临的全球挑战的新解决方案。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef13/7235657/5477e31a2ceb/10.1177_2333794X20917570-fig1.jpg

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