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助力未来的公共卫生研究人员和临床医生利用聊天机器人、虚拟现实及其他人工智能技术开发数字健康干预措施。

Empowering tomorrow's public health researchers and clinicians to develop digital health interventions using chatbots, virtual reality, and other AI technologies.

作者信息

Comulada W Scott, McQueen Catherine, Lang Cathy M

机构信息

Department of Psychiatry and Biobehavioral Sciences, Semel Institute Center for Community Health, University of California, Los Angeles, Los Angeles, CA, United States.

Department of Health Policy and Management, University of California, Los Angeles, Los Angeles, CA, United States.

出版信息

Front Public Health. 2025 Jul 8;13:1577076. doi: 10.3389/fpubh.2025.1577076. eCollection 2025.


DOI:10.3389/fpubh.2025.1577076
PMID:40697845
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12279801/
Abstract

BACKGROUND: Artificial Intelligence (AI)-based digital health interventions incorporating technologies like chatbots and augmented/virtual reality are reshaping the healthcare delivery landscape. The rollout of these technologies warrants updated graduate curricula to train future healthcare professionals. In response, the authors incorporated additional topics relevant to digital health intervention development into a graduate-level digital health communication course and evaluated student feedback. METHODS: The authors developed four lectures on two-/one-way digital health messaging strategies, AI/large language models, chatbots, and augmented/virtual reality, and a chatbot development tutorial as a lab. They evaluated students' perceptions of the course and the benefits of the new content after course completion through standard and supplemental course evaluations. RESULTS: Eleven of 16 enrolled students completed the course evaluation, and 8 completed the supplemental survey. Most students were from the school of public health and reported female gender. One of 8 students completing the survey reported prior experience creating chatbot and AR/VR content. The overall average course rating was high (7.45 out of 9). Open-ended survey responses about the new content were mixed with enthusiasm and questions about its relevance over content on traditional communication modalities in preparation for public health work. CONCLUSION: Student feedback underscored course content value, along with guidance to better emphasize how chatbots and augmented/virtual reality are relevant to clinical and public health practices. More applications relevant for diverse populations could elucidate the value of new technologies for students who will develop digital-based interventions. Applications focusing on commonalities could also solidify students' understanding of intervention development principles that will remain, as technologies evolve.

摘要

背景:基于人工智能(AI)的数字健康干预措施,融合了聊天机器人以及增强/虚拟现实等技术,正在重塑医疗服务格局。这些技术的推出需要更新研究生课程,以培养未来的医疗专业人员。作为回应,作者将与数字健康干预开发相关的其他主题纳入了一门研究生水平的数字健康通信课程,并评估了学生的反馈。 方法:作者开发了四门讲座,内容涉及双向/单向数字健康信息传递策略、人工智能/大语言模型、聊天机器人以及增强/虚拟现实,并开发了一个聊天机器人开发教程作为实验课。他们通过标准和补充课程评估,在课程结束后评估了学生对课程的看法以及新内容的益处。 结果:16名注册学生中有11名完成了课程评估,8名完成了补充调查。大多数学生来自公共卫生学院,且报告为女性。完成调查的8名学生中有1名报告有创建聊天机器人和AR/VR内容的经验。课程总体平均评分较高(9分制中为7.45分)。关于新内容的开放式调查反馈既有热情,也有关于其与传统通信方式内容在为公共卫生工作做准备方面的相关性的疑问。 结论:学生反馈强调了课程内容的价值,同时也提供了指导,以便更好地强调聊天机器人和增强/虚拟现实与临床和公共卫生实践的相关性。更多针对不同人群的应用可以向开发基于数字的干预措施的学生阐明新技术的价值。专注于共性的应用也可以巩固学生对干预开发原则的理解,这些原则将随着技术的发展而持续存在。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/974a/12279801/0947ec9847f2/fpubh-13-1577076-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/974a/12279801/0947ec9847f2/fpubh-13-1577076-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/974a/12279801/0947ec9847f2/fpubh-13-1577076-g001.jpg

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本文引用的文献

[1]
Development of a GPT-4-Powered Virtual Simulated Patient and Communication Training Platform for Medical Students to Practice Discussing Abnormal Mammogram Results With Patients: Multiphase Study.

JMIR Form Res. 2025-4-17

[2]
Roles, Users, Benefits, and Limitations of Chatbots in Health Care: Rapid Review.

J Med Internet Res. 2024-7-23

[3]
Outpatient reception via collaboration between nurses and a large language model: a randomized controlled trial.

Nat Med. 2024-10

[4]
Feasibility of combining spatial computing and AI for mental health support in anxiety and depression.

NPJ Digit Med. 2024-1-26

[5]
Embodied Conversational Agents for Chronic Diseases: Scoping Review.

J Med Internet Res. 2024-1-9

[6]
Large Language Models in Medical Education: Comparing ChatGPT- to Human-Generated Exam Questions.

Acad Med. 2024-5-1

[7]
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J Educ Health Promot. 2023-9-29

[8]
Chatbots for HIV Prevention and Care: a Narrative Review.

Curr HIV/AIDS Rep. 2023-12

[9]
AI in medical education: medical student perception, curriculum recommendations and design suggestions.

BMC Med Educ. 2023-11-9

[10]
Telehealth interventions during COVID-19 pandemic: a scoping review of applications, challenges, privacy and security issues.

BMJ Health Care Inform. 2023-8

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