以人为本设计人工智能驱动的压力预防数字疗法:关于 SHIVA 解决方案的多方利益相关者研讨会的观点

IF 3.6 2区 医学 Q1 HEALTH CARE SCIENCES & SERVICES
Marco Bolpagni , Susanna Pardini , Silvia Gabrielli
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引用次数: 0

摘要

背景人工智能驱动的数字疗法(DTx)通过促进五常医学的可扩展性,为加强压力预防提供了潜力,可为用户提供应对技能并改善精神健康的自我管理。本研究探讨了SHIVA以人为本的设计潜力,SHIVA是一种将虚拟现实和人工智能与SelfHelp+干预相结合的DTx,旨在了解利益相关者的观点和期望,从而影响其采用。我们与 12 位利益相关者(包括目标用户、数字健康设计师和心理健康专家)举行了研讨会,通过同行访谈探讨了采用人工智能的四个关键方面:结果利益相关者认为,基于人工智能的数据处理有利于在安全、保护隐私的环境中进行个性化治疗。虽然可穿戴设备被认为是必不可少的,但也有人对强制使用和 VR 头显的成本表示担忧。为提高参与度和防止辍学,最初的人工协助得到了青睐。与会者强调,透明度、可解释性和准确性对于压力检测模型至关重要。然而,在开发一个透明、可解释和准确的压力检测模型以确保用户参与、坚持和信任方面,挑战依然存在。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Human centered design of AI-powered Digital Therapeutics for stress prevention: Perspectives from multi-stakeholders' workshops about the SHIVA solution

Background

AI-powered Digital Therapeutics (DTx) hold potential for enhancing stress prevention by promoting the scalability of P5 Medicine, which may offer users coping skills and improved self-management of mental wellbeing. However, adoption rates remain low, often due to insufficient user and stakeholder involvement during the design phases.

Objective

This study explores the human-centered design potentials of SHIVA, a DTx integrating virtual reality and AI with the SelfHelp+ intervention, aiming to understand stakeholder views and expectations that could influence its adoption.

Methods

Using the SHIVA example, we detail design opportunities involving AI techniques for stress prevention across modeling, personalization, monitoring, and simulation dimensions. Workshops with 12 stakeholders—including target users, digital health designers, and mental health experts—addressed four key adoption aspects through peer interviews: AI data processing, wearable device roles, deployment scenarios, and the model's transparency, explainability, and accuracy.

Results

Stakeholders perceived AI-based data processing as beneficial for personalized treatment in a secure, privacy-preserving environment. While wearables were deemed essential, concerns about compulsory use and VR headset costs were noted. Initial human facilitation was favored to enhance engagement and prevent dropouts. Transparency, explainability, and accuracy were highlighted as crucial for the stress detection model.

Conclusion

Stakeholders recognized AI-driven opportunities as crucial for SHIVA's adoption, facilitating personalized solutions tailored to user needs. Nonetheless, challenges persist in developing a transparent, explainable, and accurate stress detection model to ensure user engagement, adherence, and trust.

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来源期刊
CiteScore
6.50
自引率
9.30%
发文量
94
审稿时长
6 weeks
期刊介绍: Official Journal of the European Society for Research on Internet Interventions (ESRII) and the International Society for Research on Internet Interventions (ISRII). The aim of Internet Interventions is to publish scientific, peer-reviewed, high-impact research on Internet interventions and related areas. Internet Interventions welcomes papers on the following subjects: • Intervention studies targeting the promotion of mental health and featuring the Internet and/or technologies using the Internet as an underlying technology, e.g. computers, smartphone devices, tablets, sensors • Implementation and dissemination of Internet interventions • Integration of Internet interventions into existing systems of care • Descriptions of development and deployment infrastructures • Internet intervention methodology and theory papers • Internet-based epidemiology • Descriptions of new Internet-based technologies and experiments with clinical applications • Economics of internet interventions (cost-effectiveness) • Health care policy and Internet interventions • The role of culture in Internet intervention • Internet psychometrics • Ethical issues pertaining to Internet interventions and measurements • Human-computer interaction and usability research with clinical implications • Systematic reviews and meta-analysis on Internet interventions
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