Minian Nadia, Mehra Kamna, Earle Mackenzie, Hafuth Sowsan, Ting-A-Kee Ryan, Rose Jonathan, Veldhuizen Scott, Zawertailo Laurie, Ratto Matt, Melamed Osnat C, Selby Peter
INTREPID Lab, Centre for Addiction and Mental Health, Toronto, ON, Canada.
Department of Family and Community Medicine, University of Toronto, Toronto, ON, Canada.
JMIR Res Protoc. 2023 Dec 11;12:e53556. doi: 10.2196/53556.
Varenicline is a pharmacological intervention for tobacco dependence that is safe and effective in facilitating smoking cessation. Enhanced adherence to varenicline augments the probability of prolonged smoking abstinence. However, research has shown that one-third of people who use varenicline are nonadherent by the second week. There is evidence showing that behavioral support helps with medication adherence. We have designed an artificial intelligence (AI) conversational agent or health bot, called "ChatV," based on evidence of what works as well as what varenicline is, that can provide these supports. ChatV is an evidence-based, patient- and health care provider-informed health bot to improve adherence to varenicline. ChatV has been programmed to provide medication reminders, answer questions about varenicline and smoking cessation, and track medication intake and the number of cigarettes.
This study aims to explore the feasibility of the ChatV health bot, to examine if it is used as intended, and to determine the appropriateness of proceeding with a randomized controlled trial.
We will conduct a mixed methods feasibility study where we will pilot-test ChatV with 40 participants. Participants will be provided with a standard 12-week varenicline regimen and access to ChatV. Passive data collection will include adoption measures (how often participants use the chatbot, what features they used, when did they use it, etc). In addition, participants will complete questionnaires (at 1, 4, 8, and 12 weeks) assessing self-reported smoking status and varenicline adherence, as well as questions regarding the acceptability, appropriateness, and usability of the chatbot, and participate in an interview assessing acceptability, appropriateness, fidelity, and adoption. We will use "stop, amend, and go" progression criteria for pilot studies to decide if a randomized controlled trial is a reasonable next step and what modifications are required. A health equity lens will be adopted during participant recruitment and data analysis to understand and address the differences in uptake and use of this digital health solution among diverse sociodemographic groups. The taxonomy of implementation outcomes will be used to assess feasibility, that is, acceptability, appropriateness, fidelity, adoption, and usability. In addition, medication adherence and smoking cessation will be measured to assess the preliminary treatment effect. Interview data will be analyzed using the framework analysis method.
Participant enrollment for the study will begin in January 2024.
By using predetermined progression criteria, the results of this preliminary study will inform the determination of whether to advance toward a larger randomized controlled trial to test the effectiveness of the health bot. Additionally, this study will explore the acceptability, appropriateness, fidelity, adoption, and usability of the health bot. These insights will be instrumental in refining the intervention and the health bot.
ClinicalTrials.gov NCT05997901; https://classic.clinicaltrials.gov/ct2/show/NCT05997901.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/53556.
伐尼克兰是一种用于治疗烟草依赖的药物干预手段，在促进戒烟方面安全有效。提高对伐尼克兰的依从性可增加长期戒烟的可能性。然而，研究表明，三分之一使用伐尼克兰的人在第二周就不再依从。有证据表明，行为支持有助于提高药物依从性。我们基于有效方法及伐尼克兰的相关知识，设计了一种名为“ChatV”的人工智能（AI）对话代理或健康机器人，它可以提供这些支持。ChatV是一个基于证据、由患者和医疗服务提供者提供信息的健康机器人，旨在提高对伐尼克兰的依从性。ChatV已被编程用于提供用药提醒、回答有关伐尼克兰和戒烟的问题，以及跟踪药物摄入情况和吸烟数量。
本研究旨在探讨ChatV健康机器人的可行性，检查其使用是否符合预期，并确定是否适合进行随机对照试验。
我们将进行一项混合方法可行性研究，对40名参与者进行ChatV的试点测试。将为参与者提供标准的12周伐尼克兰治疗方案，并让他们使用ChatV。被动数据收集将包括采用措施（参与者使用聊天机器人的频率、使用了哪些功能、何时使用等）。此外，参与者将在第1、4、8和12周完成问卷，评估自我报告的吸烟状况和伐尼克兰依从性，以及有关聊天机器人的可接受性、适宜性和可用性的问题，并参加一次访谈，评估可接受性、适宜性、保真度和采用情况。我们将使用试点研究的“停止、修改和继续”进展标准来决定是否进行随机对照试验是合理的下一步以及需要进行哪些修改。在参与者招募和数据分析过程中将采用健康公平视角，以了解和解决不同社会人口群体在采用和使用这种数字健康解决方案方面的差异。将使用实施结果分类法来评估可行性，即可接受性、适宜性、保真度、采用情况和可用性。此外，将测量药物依从性和戒烟情况以评估初步治疗效果。访谈数据将使用框架分析法进行分析。
该研究的参与者招募将于2024年1月开始。
通过使用预定的进展标准，这项初步研究的结果将为是否推进更大规模的随机对照试验以测试健康机器人的有效性提供依据。此外，本研究将探索健康机器人的可接受性、适宜性、保真度、采用情况和可用性。这些见解将有助于完善干预措施和健康机器人。
ClinicalTrials.gov NCT05997901；https://classic.clinicaltrials.gov/ct2/show/NCT05997901。
国际注册报告标识符（IRRID）：PRR1-10.2196/53556。
