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数字健康与成瘾

Digital Health and Addiction.

作者信息

Marsch Lisa A

机构信息

Center for Technology and Behavioral Health, Geisel School of Medicine, Dartmouth College, 46 Centerra Parkway, Suite 315, Lebanon, New Hampshire USA.

出版信息

Curr Opin Syst Biol. 2020 Apr;20:1-7. doi: 10.1016/j.coisb.2020.07.004. Epub 2020 Jul 7.

DOI:10.1016/j.coisb.2020.07.004
PMID:32885099
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7462117/
Abstract

Digital technologies are rapidly changing how we understand and promote health. A robust and growing line of research has examined how digital health may enhance our understanding and treatment of addiction. This manuscript highlights innovations in the application of digital health approaches to addiction medicine, with a particular emphasis on advances in (1) real-time measurement of drug use events, (2) real-time measurement of the confluence of factors that surround drug use events, and (3) research examining how real-time measurement can inform responsive, in-the-moment interventions to prevent and treat substance use disorder. Although this manuscript focuses on addiction medicine as one exemplar of the striking impact of digital health, science-based digital health offers generalizable solutions to scaling-up unprecedented models of precision healthcare delivery across a broad spectrum of diseases across the globe.

摘要

数字技术正在迅速改变我们理解和促进健康的方式。一系列蓬勃发展且不断壮大的研究已经探讨了数字健康如何增进我们对成瘾的理解和治疗。本手稿重点介绍了数字健康方法在成瘾医学应用中的创新,特别强调了以下方面的进展:(1)药物使用事件的实时测量;(2)围绕药物使用事件的各种因素交汇的实时测量;(3)研究实时测量如何为预防和治疗物质使用障碍的即时响应干预提供信息。尽管本手稿将成瘾医学作为数字健康显著影响的一个范例,但基于科学的数字健康为在全球范围内扩大针对广泛疾病的前所未有的精准医疗模式提供了可推广的解决方案。

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本文引用的文献

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The application of digital health to the assessment and treatment of substance use disorders: The past, current, and future role of the National Drug Abuse Treatment Clinical Trials Network.数字健康在物质使用障碍评估与治疗中的应用:国家药物滥用治疗临床试验网络的过去、当前及未来作用。
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Workshop on the Development and Evaluation of Digital Therapeutics for Health Behavior Change: Science, Methods, and Projects.健康行为改变数字疗法的开发与评估研讨会:科学、方法与项目
JMIR Ment Health. 2020 Feb 26;7(2):e16751. doi: 10.2196/16751.
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Deep Digital Phenotyping and Digital Twins for Precision Health: Time to Dig Deeper.用于精准健康的深度数字表型分析和数字孪生:是时候深入挖掘了。
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