Adapting and Evaluating an Artificial Intelligence-Based Chatbot through Patient and Stakeholder Engagement to Provide Information for Different Health Conditions: Master Protocol for an Adaptive Platform Trial Study (the MARVIN Chatbots) (Preprint)

Author:

MA YuanchaoORCID,Achiche SofianeORCID,Pomey Marie-PascaleORCID,Paquette JessecaORCID,Adjtoutah Nesrine,Vicente SergeORCID,Engler KimORCID,Patient Expert Committee MARVIN chatbotsORCID,Laymouna MoustafaORCID,Lessard DavidORCID,Lemire Benoît,Asselah Jamil,Therrien RachelORCID,Osmanlliu EsliORCID,Zawati Ma’n HORCID,Joly Yann,Lebouché BertrandORCID

Abstract

BACKGROUND

Self-management interventions are emphasized as a way to optimize health outcomes and care, but they necessitate supporting patients to access timely and reliable health information, which remains a challenge. In the realm of digital health, artificial intelligence-based chatbots capable of conversing with users in natural language have emerged as promising tools. However, it is imperative to conduct further research on their implementation. Besides, inclusive digital health research and responsive AI integration into healthcare necessitates active and sustained patients and stakeholder engagement.

OBJECTIVE

This manuscript presents the master protocol of the MARVIN chatbots study which has four objectives: 1) co-construct tailored AI chatbots for different healthcare settings; 2) assess their usability in a small participant sample context; 3) measure their implementation outcomes (usability, acceptability, appropriateness, adoption, and fidelity) in a large sample context; and 4) evaluate the impact of patient and stakeholder partnerships on their development. This adaptive platform trial consists of multiple parallel individual chatbot sub-studies sharing common objectives, with Objective 1 through 3 to be completed sequentially, and Objective 4 to be assessed throughout.

METHODS

The study will recruit patients and healthcare professionals from the McGill University Health Centre and the Centre hospitalier de l’Université de Montréal (both in Montreal, Canada). Four needs assessment focus groups with 20 participants and six co-construction workshops with a co-construction design committee will first be conducted to develop and test chatbots adapted to the relevant healthcare context. Thirty participants will then interact with MARVIN for three weeks and assess its usability through a survey and three focus groups. Positive usability outcomes will lead to public access of the chatbot for a one-year real world implementation study. Questionnaires will be administered online to 150 participants to measure usability, acceptability, and appropriateness, while meta-use data will inform adoption and fidelity. Following completion of each objective, focus groups will be conducted with the co-construction design committee to better understand stakeholders’ perspectives on their engagement in research.

RESULTS

From July 2022 to October 2023, this master protocol led to four sub-studies: 1) MARVIN for HIV (large-scale implementation expected to begin in mid-2024); 2) MARVIN “Pharma” to support community pharmacist in providing HIV care (usability study planned for mid-2024); 3) MARVINA for breast cancer, and 4) MARVIN Champ for pediatric infectious conditions (both in preparation with development to begin in early-2024).

CONCLUSIONS

The development and adaptation of the MARVIN chatbots is expected to improve patient self-management and healthcare efficiency. This master protocol comprehensively examines the implementation outcomes of chatbot interventions for patients and healthcare professionals. It will also contribute to best practice recommendations for patient and stakeholder engagement in digital health research. With appropriate design, this protocol can sustain long-term innovation translation, and deliver timely interventions to advance patient-centered personalized medicine.

CLINICALTRIAL

ClinicalTrials.gov identifier: NCT05789901 https://classic.clinicaltrials.gov/ct2/show/NCT05789901

Publisher

JMIR Publications Inc.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3