Constructing A Conversation-First Dialogue Model for Comprehensive, Evidence-Based Counseling for HPV Vaccination for Young Adults.

Lu Tang, Chenying Weng, Serena Hou, Lara S Savas, Ana C Neumann, Nicole Moore, Jane Hamilton, Daniel Rhee, Cui Tao, Licong Cui, Muhammad Tuan Amith
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Abstract

The human papillomavirus (HPV) vaccine has been shown to prevent several types of cancers; however, vaccination rates remain suboptimal. Effective patient-provider communication is key to promoting vaccination but is often hindered by various clinical barriers. Speech bots could be a promising solution by addressing common barriers and facilitating HPV vaccination uptake. We used a "conversation first" design approach to develop the interaction for speech bots to deliver HPV vaccination counseling to young adults. Two counseling strategies were developed and piloted: motivational interviewing (MI) and the theory-based approaches. Wizard of Oz experiments were conducted with young female adults (n = 24). Preliminary evidence shows that MI yielded higher usability than the theory-based approach. The theory-based approach significantly improved HPV vaccine beliefs and attitudes. These findings led to the development of a hybrid conversational model for future pilot testing and the eventual creation of a computable format for automated speech bots.

构建一个全面的、基于证据的年轻人HPV疫苗接种咨询的对话优先对话模型。
人类乳头瘤病毒(HPV)疫苗已被证明可以预防几种类型的癌症;然而,疫苗接种率仍然不够理想。有效的医患沟通是促进疫苗接种的关键,但往往受到各种临床障碍的阻碍。通过解决常见障碍和促进HPV疫苗接种,语音机器人可能是一个很有前途的解决方案。我们使用了“对话优先”的设计方法来开发语音机器人的交互,以向年轻人提供HPV疫苗接种咨询。两种咨询策略的发展和试点:动机访谈(MI)和理论为基础的方法。《绿野仙踪》的实验对象是年轻的成年女性(n = 24)。初步证据表明,人工智能比基于理论的方法产生了更高的可用性。以理论为基础的方法显著改善了人们对HPV疫苗的信念和态度。这些发现导致了混合会话模型的发展,用于未来的试点测试,并最终为自动语音机器人创建可计算格式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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