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面向患者的聊天机器人:在应对数字素养挑战和隔离风险的同时提高医疗保健可及性——一项混合方法研究

Patient-facing chatbots: Enhancing healthcare accessibility while navigating digital literacy challenges and isolation risks-a mixed-methods study.

作者信息

Moore Annie A, Ellis Jessica R, Dellavalle Natalia, Akerson Marlee, Andazola Matt, Campbell Eric G, DeCamp Matthew

机构信息

Department of Medicine, General Internal Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.

Center for Bioethics and Humanities, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.

出版信息

Digit Health. 2025 Apr 28;11:20552076251337321. doi: 10.1177/20552076251337321. eCollection 2025 Jan-Dec.

Abstract

OBJECTIVE

Digital communication between patients and healthcare teams is increasing. Most patients find this effective, yet many patients remain digitally isolated, a social determinant of health. This study investigates patient attitudes toward healthcare's newest digital assistant, the chatbot, and perceptions regarding healthcare access.

METHODS

We conducted a mixed methods study among patient users of a large healthcare system's chatbot integrated within an electronic health record. We purposively oversampled by race and ethnicity to survey 617/3089 (response rate 20%) patient users online using de novo and validated items. In addition, we conducted semi-structured interviews with users (n = 46) purposively sampled based on diversity, age, or select survey responses between November 2022 and May 2024.

RESULTS

In surveys, 213/609 (35.0%) felt they could not understand the chatbot completely, and 376/614 (61.2%) felt the chatbot did not completely understand them. Of 238 users who felt completely understood by the chatbot, 178 (74.8%) believed the chatbot was intended to help them access healthcare; in comparison, of 376 users who felt not completely understood, 155 (41%) believed the chatbot was intended to help access ( < 0.001). In interviews, among themes observed, Black, Hispanic, less educated, younger, and lower-income participants expressed more positivity about the chatbot aiding healthcare access, stating convenience and perceived absence of judgment or bias.

CONCLUSION

Patients' experience with the chatbot appears to affect their perception of the intent of the chatbot's implementation; those adept at chatbot communication or within historically less trusting groups may prefer a quick, non-judgmental answer to questions via the chatbot rather than human interaction. Although our findings are limited to one health system's existing chatbot users, as patient-facing chatbots expand, attention to these factors can support healthcare systems' efforts to design chatbots that meet the unique communication needs of all patients, expressly those at risk of digital isolation.

摘要

目的

患者与医疗团队之间的数字通信正在增加。大多数患者认为这很有效,但仍有许多患者在数字方面处于孤立状态,这是一种健康的社会决定因素。本研究调查了患者对医疗领域最新数字助手——聊天机器人的态度,以及对医疗服务可及性的看法。

方法

我们在一个大型医疗系统集成于电子健康记录中的聊天机器人的患者用户中开展了一项混合方法研究。我们按种族和族裔进行了有目的的过度抽样,以使用全新和经过验证的项目对617/3089名(回复率20%)患者用户进行在线调查。此外,我们在2022年11月至2024年5月期间,基于多样性、年龄或选定的调查回复,对用户(n = 46)进行了有目的抽样的半结构化访谈。

结果

在调查中,213/609名(35.0%)患者觉得他们不能完全理解聊天机器人,376/614名(61.2%)患者觉得聊天机器人没有完全理解他们。在238名觉得被聊天机器人完全理解的用户中,178名(74.8%)认为聊天机器人旨在帮助他们获得医疗服务;相比之下,在376名觉得没有被完全理解的用户中,155名(41%)认为聊天机器人旨在帮助获得医疗服务(<0.001)。在访谈中,在观察到的主题中,黑人、西班牙裔、受教育程度较低、较年轻和低收入的参与者对聊天机器人帮助获得医疗服务表达了更多的积极态度,称其方便且感觉没有评判或偏见。

结论

患者与聊天机器人的体验似乎会影响他们对聊天机器人实施意图的认知;那些擅长聊天机器人沟通的人或历史上信任度较低的群体可能更喜欢通过聊天机器人快速获得无评判的问题答案,而不是人际互动。尽管我们的研究结果仅限于一个医疗系统的现有聊天机器人用户,但随着面向患者的聊天机器人的扩展,关注这些因素可以支持医疗系统努力设计出满足所有患者独特沟通需求的聊天机器人,特别是那些有数字孤立风险的患者。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/715c/12041682/b05cc9a4b0d5/10.1177_20552076251337321-fig1.jpg

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