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支持青少年参与人工智能驱动的数字健康行为改变干预措施。

Supporting Adolescent Engagement with Artificial Intelligence-Driven Digital Health Behavior Change Interventions.

机构信息

Department of Pediatrics, University of California, San Francisco, San Francisco, CA, United States.

Department of Computer Science, North Carolina State University, Raleigh, CA, United States.

出版信息

J Med Internet Res. 2023 May 24;25:e40306. doi: 10.2196/40306.

Abstract

Understanding and optimizing adolescent-specific engagement with behavior change interventions will open doors for providers to promote healthy changes in an age group that is simultaneously difficult to engage and especially important to affect. For digital interventions, there is untapped potential in combining the vastness of process-level data with the analytical power of artificial intelligence (AI) to understand not only how adolescents engage but also how to improve upon interventions with the goal of increasing engagement and, ultimately, efficacy. Rooted in the example of the INSPIRE narrative-centered digital health behavior change intervention (DHBCI) for adolescent risky behaviors around alcohol use, we propose a framework for harnessing AI to accomplish 4 goals that are pertinent to health care providers and software developers alike: measurement of adolescent engagement, modeling of adolescent engagement, optimization of current interventions, and generation of novel interventions. Operationalization of this framework with youths must be situated in the ethical use of this technology, and we have outlined the potential pitfalls of AI with particular attention to privacy concerns for adolescents. Given how recently AI advances have opened up these possibilities in this field, the opportunities for further investigation are plenty.

摘要

理解和优化青少年对行为改变干预措施的特定参与度,将为提供者提供机会,促进一个难以吸引且特别重要的年龄群体的健康改变。对于数字干预措施,将过程级数据的巨大规模与人工智能 (AI) 的分析能力相结合,不仅可以了解青少年的参与程度,还可以改进干预措施,以提高参与度,并最终提高疗效,这方面潜力巨大。以 INSPIRE 以叙事为中心的青少年饮酒风险行为数字健康行为改变干预 (DHBCI) 为例,我们提出了一个利用 AI 实现 4 个目标的框架,这些目标与医疗保健提供者和软件开发人员都相关:衡量青少年的参与度、模拟青少年的参与度、优化当前的干预措施以及生成新的干预措施。必须在伦理使用该技术的基础上,对青少年进行该框架的实施,我们还概述了 AI 的潜在陷阱,特别关注青少年的隐私问题。鉴于最近 AI 技术的进步为该领域带来了这些可能性,进一步研究的机会很多。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9809/10248780/f22880a764c5/jmir_v25i1e40306_fig1.jpg

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