METHODS: We use a case example of developing a conversational agent or chatbot to address racial inequities in breast cancer screening via mammography. With an interdisciplinary team including community members and operational leaders, we conducted a rapid evidence review and elicited qualitative data through interviews and focus groups using HCD methods to identify and prioritize key determinants (facilitators and barriers) of the evidence-based intervention (breast cancer screening) and the implementation strategy (chatbot). We developed a CPD using key determinants and proposed strategy mechanisms and proximal outcomes based in conceptual frameworks.
RESULTS: We identified key determinants for breast cancer screening and for the chatbot implementation strategy. Mistrust was a key barrier to both completing breast cancer screening and using the chatbot. We focused design for the initial chatbot interaction to engender trust and developed a CPD to guide chatbot development. We used the persuasive health message framework and conceptual frameworks about trust from marketing and artificial intelligence disciplines. We developed a CPD for the initial interaction with the chatbot with engagement as a mechanism to use and trust as a proximal outcome leading to further engagement with the chatbot.
CONCLUSIONS: The use of interdisciplinary methods is core to implementation science. HCD is a particularly synergistic discipline with multiple existing applications of HCD to implementation research. We present an extension of this work and an example of the potential value in an integrated community-engaged approach of HCD and implementation science researchers and methods to combine strengths of both disciplines and develop human-centered implementation strategies rooted in causal perspective and healthcare equity.
方法:我们使用一个案例,开发一个对话代理或聊天机器人来解决通过乳房X光检查进行乳腺癌筛查的种族不平等问题。拥有包括社区成员和运营领导者在内的跨学科团队,我们进行了快速的证据回顾,并通过访谈和焦点小组,使用HCD方法获得定性数据,以确定循证干预(乳腺癌筛查)和实施策略(chatbot)的关键决定因素(促进因素和障碍),并确定其优先级.我们使用关键决定因素开发了CPD,并基于概念框架提出了战略机制和近端结果。
结果:我们确定了乳腺癌筛查和聊天机器人实施策略的关键决定因素。不信任是完成乳腺癌筛查和使用聊天机器人的关键障碍。我们专注于最初的聊天机器人交互设计,以产生信任,并开发了CPD来指导聊天机器人的开发。我们使用了有说服力的健康信息框架和有关营销和人工智能学科信任的概念框架。我们开发了一个CPD,用于与聊天机器人的初始交互,将参与作为一种机制来使用和信任作为近端结果,从而进一步与聊天机器人互动。
结论:使用跨学科方法是实施科学的核心。HCD是一门特别协同的学科,具有HCD在实施研究中的多种现有应用。我们提出了这项工作的扩展,以及HCD和实施科学研究人员的综合社区参与方法和方法的潜在价值的一个例子,以结合两个学科的优势,并制定植根于因果视角和医疗保健公平的以人为本的实施策略。