Formative Evaluation of the Acceptance of HIV Prevention Artificial Intelligence Chatbots By Men Who Have Sex With Men in Malaysia: Focus Group Study.
Formative Evaluation of the Acceptance of HIV Prevention Artificial Intelligence Chatbots By Men Who Have Sex With Men in Malaysia: Focus Group Study.
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DOI：
10.2196/42055
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发表时间：
2022-10-06
影响因子：
2.2
通讯作者：
Ni, Zhao
中科院分区：
文献类型：
--
作者：
Peng, Mary L.;Wickersham, Jeffrey A.;Altice, Frederick L.;Shrestha, Roman;Azwa, Iskandar;Zhou, Xin;Halim, Mohd Akbar Ab;Ikhtiaruddin, Wan Mohd;Tee, Vincent;Kamarulzaman, Adeeba;Ni, Zhao
关键词：
移动技术正在日益发展，以支持医疗、护理和公共卫生的实践，包括艾滋病毒检测和预防。使用人工智能(AI)的聊天机器人是一种新颖的移动健康策略，可以在马来西亚的男男性行为者(MSM)中促进艾滋病毒检测和预防，MSM是一个艾滋病毒风险较高的难以接触的人群，但人们对这些关键人群的重要特征知之甚少。这项研究的目的是确定马来西亚MSM接受人工智能聊天机器人的障碍和促进者，该聊天机器人旨在帮助艾滋病毒测试和预防，涉及其感知的好处、限制和潜在用户的首选功能。我们在2021年7月至2021年9月期间对马来西亚的31名男男性接触者进行了5次基于网络的有组织的焦点小组访谈。采访首先使用NVivo(版本9；QSR International)进行录制、转录、编码和主题分析。随后，使用接受和使用技术的统一理论来指导数据分析，将与Chatbot接受的障碍和促进者相关的新兴主题映射到其4个领域：性能预期、努力预期、促进条件和社会影响。对于每个领域，确定了影响MSM接受AI聊天机器人的多个障碍和促进者。性能预期(即感知到的AI聊天机器人的有用性)受到MSM对AI聊天机器人传递准确信息的能力、其在信息传播和解决问题方面的有效性以及其提供情感支持和提高健康意识的能力的担忧。便利性、成本和技术错误影响了AI聊天机器人的工作预期(即感知的易用性)。据报告，与卫生保健专业人员和艾滋病毒自我检测的有效联系是MSM接受使用人工智能聊天机器人进行艾滋病毒检测的便利条件。与会者指出，影响马来西亚接受解决艾滋病毒问题的移动技术的社会影响(即社会政治气候)因素包括隐私问题、普遍的对同性恋的污名以及将同性性行为定为刑事犯罪。能够提高MSM对艾滋病毒预防AI聊天机器人的接受度的关键设计战略包括匿名用户设置；将聊天机器人嵌入MSM友好的基于网络的平台；以及提供与艾滋病毒检测、预防和治疗相关的用户指导问题和选项。这项研究为设计人工智能聊天机器人的关键特征和潜在的实施战略提供了重要的见解，该机器人是一种文化敏感的数字健康工具，以防止弱势和系统边缘化人群的污名化健康状况。这些特点不仅对为马来西亚男男性接触者设计有效、以用户为中心和文化定位的移动健康干预措施至关重要，而且还阐明了将社会耻辱考虑纳入卫生技术实施战略的重要性。
Mobile technologies are being increasingly developed to support the practice of medicine, nursing, and public health, including HIV testing and prevention. Chatbots using artificial intelligence (AI) are novel mobile health strategies that can promote HIV testing and prevention among men who have sex with men (MSM) in Malaysia, a hard-to-reach population at elevated risk of HIV, yet little is known about the features that are important to this key population. The aim of this study was to identify the barriers to and facilitators of Malaysian MSM’s acceptance of an AI chatbot designed to assist in HIV testing and prevention in relation to its perceived benefits, limitations, and preferred features among potential users. We conducted 5 structured web-based focus group interviews with 31 MSM in Malaysia between July 2021 and September 2021. The interviews were first recorded, transcribed, coded, and thematically analyzed using NVivo (version 9; QSR International). Subsequently, the unified theory of acceptance and use of technology was used to guide data analysis to map emerging themes related to the barriers to and facilitators of chatbot acceptance onto its 4 domains: performance expectancy, effort expectancy, facilitating conditions, and social influence. Multiple barriers and facilitators influencing MSM’s acceptance of an AI chatbot were identified for each domain. Performance expectancy (ie, the perceived usefulness of the AI chatbot) was influenced by MSM’s concerns about the AI chatbot’s ability to deliver accurate information, its effectiveness in information dissemination and problem-solving, and its ability to provide emotional support and raise health awareness. Convenience, cost, and technical errors influenced the AI chatbot’s effort expectancy (ie, the perceived ease of use). Efficient linkage to health care professionals and HIV self-testing was reported as a facilitating condition of MSM’s receptiveness to using an AI chatbot to access HIV testing. Participants stated that social influence (ie, sociopolitical climate) factors influencing the acceptance of mobile technology that addressed HIV in Malaysia included privacy concerns, pervasive stigma against homosexuality, and the criminalization of same-sex sexual behaviors. Key design strategies that could enhance MSM’s acceptance of an HIV prevention AI chatbot included an anonymous user setting; embedding the chatbot in MSM-friendly web-based platforms; and providing user-guiding questions and options related to HIV testing, prevention, and treatment. This study provides important insights into key features and potential implementation strategies central to designing an AI chatbot as a culturally sensitive digital health tool to prevent stigmatized health conditions in vulnerable and systematically marginalized populations. Such features not only are crucial to designing effective user-centered and culturally situated mobile health interventions for MSM in Malaysia but also illuminate the importance of incorporating social stigma considerations into health technology implementation strategies.
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DOI：
10.1186/1748-5908-4-50
发表时间：
2009-08-07
期刊：
Implementation science : IS
影响因子：
--
作者：
Damschroder LJ;Aron DC;Keith RE;Kirsh SR;Alexander JA;Lowery JC
通讯作者：
Lowery JC
影响因子：
5
作者：
Kim AJ;Yang J;Jang Y;Baek JS
通讯作者：
Baek JS
DOI：
10.1016/j.ijmedinf.2008.12.005
发表时间：
2009-06-01
影响因子：
4.9
作者：
Kijsanayotin, Boonchai;Pannarunothai, Supasit;Speedie, Stuart M.
通讯作者：
Speedie, Stuart M.
影响因子：
8.5
作者：
Baral S;Turner RM;Lyons CE;Howell S;Honermann B;Garner A;Hess R III;Diouf D;Ayala G;Sullivan PS;Millett G
通讯作者：
Millett G
影响因子：
4.4
作者：
Earnshaw, Valerie A.;Jin, Harry;Altice, Frederick L.
通讯作者：
Altice, Frederick L.