Cocreation of a conversational agent to help patients adhere to their varenicline treatment: A study protocol

Abstract

Objective: Varenicline is the most efficacious approved smoking cessation medication, making it one of the most cost-effective clinical interventions for reducing tobacco-related morbidity and mortality. Adhering to varenicline is strongly associated with smoking cessation. Healthbots have the potential to help people adhere to their medications by scaling up evidence-based behavioral interventions. In this protocol, we outline how we will follow the UK's Medical Research Council's guidance to codesign a theory-informed, evidence-based, and patient-centered healthbot to help people adhere to varenicline. Methods: The study will utilize the Discover, Design and Build, and Test framework and will include three phases: (a) a rapid review and interviews with 20 patients and 20 healthcare providers to understand barriers and facilitators to varenicline adherence (Discover phase); (b) Wizard of Oz test to design the healthbot and get a sense of the questions that chatbot has to be able to answer (Design phase); and (c) building, training, and beta-testing the healthbot (Building and Testing phases) where the Nonadoption, Abandonment, Scale-up, Spread, and Sustainability framework will be used to develop the healthbot using the simplest sensible solution, and 20 participants will beta test the healthbot. We will use the Capability, Opportunity, Motivation-Behavior (COM-B) model of behavior change and its associated framework, the Theoretical Domains Framework, to organize the findings. Conclusions: The present approach will enable us to systematically identify the most appropriate features for the healthbot based on a well-established behavioral theory, the latest scientific evidence, and end users’ and healthcare providers’ knowledge.