ZHAW School of Management and Law, Zurich University of Applied Sciences, Winterthur, Switzerland.
Department of Informatics, University of Zurich, Zurich, Switzerland.
JMIR Hum Factors. 2024 Mar 18;11:e49647. doi: 10.2196/49647.
Physicians are currently overwhelmed by administrative tasks and spend very little time in consultations with patients, which hampers health literacy, shared decision-making, and treatment adherence.
This study aims to examine whether digital agents constructed using fast-evolving generative artificial intelligence, such as ChatGPT, have the potential to improve consultations, adherence to treatment, and health literacy. We interviewed patients and physicians to obtain their opinions about 3 digital agents-a silent digital expert, a communicative digital expert, and a digital companion (DC).
We conducted in-depth interviews with 25 patients and 22 physicians from a purposeful sample, with the patients having a wide age range and coming from different educational backgrounds and the physicians having different medical specialties. Transcripts of the interviews were deductively coded using MAXQDA (VERBI Software GmbH) and then summarized according to code and interview before being clustered for interpretation.
Statements from patients and physicians were categorized according to three consultation phases: (1) silent and communicative digital experts that are part of the consultation, (2) digital experts that hand over to a DC, and (3) DCs that support patients in the period between consultations. Overall, patients and physicians were open to these forms of digital support but had reservations about all 3 agents.
Ultimately, we derived 9 requirements for designing digital agents to support consultations, treatment adherence, and health literacy based on the literature and our qualitative findings.
目前，医生们被行政任务压得喘不过气来，用于与患者交流的时间非常少，这妨碍了健康素养、共同决策和治疗依从性。
本研究旨在探讨使用快速发展的生成式人工智能（如 ChatGPT）构建的数字代理是否有可能改善咨询、治疗依从性和健康素养。我们采访了患者和医生，以了解他们对 3 种数字代理（静默数字专家、交流数字专家和数字伙伴（DC））的看法。
我们对 25 名患者和 22 名医生进行了深入访谈，这些患者来自不同的年龄组，具有不同的教育背景，而医生则具有不同的医疗专业背景。使用 MAXQDA（VERBI Software GmbH）对访谈记录进行演绎编码，然后根据代码和访谈进行总结，再进行聚类解释。
患者和医生的陈述根据咨询的三个阶段进行分类：（1）作为咨询一部分的静默和交流数字专家，（2）将任务移交给 DC 的数字专家，以及（3）支持患者在咨询之间阶段的 DC。总的来说，患者和医生对这些数字支持形式持开放态度，但对所有 3 种代理都持保留意见。
最终，我们根据文献和我们的定性发现，为设计支持咨询、治疗依从性和健康素养的数字代理得出了 9 项要求。
