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设计人工智能驱动的医疗保健助手以惠及弱势群体:南非大学生的离散选择实验

Designing Artificial Intelligence-Powered Health Care Assistants to Reach Vulnerable Populations: A Discrete Choice Experiment Among South African University Students.

作者信息

Zheng Amy, Long Lawrence, Govathson Caroline, Chetty-Makkan Candice, Morris Sarah, Rech Dino, Fox Matthew P, Pascoe Sophie

机构信息

Department of Epidemiology, Boston University School of Public Health, Boston, MA.

Department of Global Health, Boston University School of Public Health, Boston, MA.

出版信息

Mayo Clin Proc Digit Health. 2025 Jul 10;3(3):100248. doi: 10.1016/j.mcpdig.2025.100248. eCollection 2025 Sep.

Abstract

OBJECTIVE

To understand what preferences are important to university students in South Africa when engaging with a hypothetical artificial intelligence-powered health care assistant (AIPHA) to access health information using a discrete choice experiment.

PATIENTS AND METHODS

We conducted an unlabeled, forced choice discrete choice experiment among adult South African university students through Prolific, an online research platform, from June 26, 2024 to August 31, 2024. Each choice option described a hypothetical AIPHA using 8 attribute characteristics (cost, confidentiality, security, health care topics, language, persona, access, and services). Participants were presented with 10 choice sets each comprised of 2 choice options and asked to choose between the 2. A conditional logit model was used.

RESULTS

Three hundred participants were recruited and enrolled. Most participants were Black, born in South Africa, heterosexual, working for a wage, and had a mean age of 26.5 years (SD, 6.0). Language, security, and receiving personally tailored advice were the most important attributes for AIPHA. Participants strongly preferred the ability to communicate with the AIPHA in any South African language of their choosing instead of only English and receive information about health topics specific to their context including information on clinics geographically near them. The results were consistent when stratified by sex and socioeconomic status.

CONCLUSION

Participants had strong preferences for security and language, which is in line with previous studies where successful uptake and implementation of such health interventions clearly addressed these concerns. These results build the evidence base for how we might engage young adults in health care through technology effectively.

摘要

目的

通过离散选择实验,了解在与假设的人工智能驱动的医疗保健助手(AIPHA)互动以获取健康信息时,哪些偏好对南非大学生很重要。

患者与方法

2024年6月26日至2024年8月31日,我们通过在线研究平台Prolific对成年南非大学生进行了一项无标签的强制选择离散选择实验。每个选择选项使用8个属性特征(成本、保密性、安全性、医疗保健主题、语言、角色、访问权限和服务)描述了一个假设的AIPHA。向参与者展示10组选择,每组由2个选择选项组成,并要求他们在两者之间进行选择。使用了条件logit模型。

结果

招募并纳入了300名参与者。大多数参与者是黑人,出生在南非,异性恋,有工作收入,平均年龄为26.5岁(标准差为6.0)。语言、安全性和获得个性化建议是AIPHA最重要的属性。参与者强烈倾向于能够用他们选择的任何南非语言与AIPHA交流,而不仅仅是英语,并接收与他们情况相关的健康主题信息,包括附近诊所的信息。按性别和社会经济地位分层时,结果一致。

结论

参与者对安全性和语言有强烈偏好,这与之前的研究一致,在这些研究中,此类健康干预措施的成功采用和实施明确解决了这些问题。这些结果为我们如何通过技术有效地让年轻人参与医疗保健建立了证据基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e85c/12337867/ace54bf350f2/gr1.jpg

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