Rationale: Despite knowing the health benefits of tobacco cessation, there is a lack of AI-based cessation interventions, that address both smoking and smokeless tobacco (SLT) in India. Existing digital platforms often fail to comply with clinical cessation guidelines and underutilize features to facilitate active user engagement.

Novelty: The proposed Generative AI-based conversational interface through CARE will offer tailored cessation services including information on health risks, motivate users to quit, offer effective quitting strategies and reduce relapse through patient-supported networks. The key features will include, personalized quit plans, track quitting progress, milestones, behavioural support, reminders, and motivational messages. The interface will cater to both smoking and SLT users, address rural and urban users’ needs, and provide services in regional languages.

Objectives: To understand the facilitators and barriers tobacco users face in quitting and using digital interventions in the past. Based on this information, develop a Generative AI-based conversational interface to facilitate successful quit attempts.

Methods: The study will employ a pre-post, quasi-experimental single-group design without control, using a mixed-methods approach.  Participants will be current users of tobacco in any form seeking assistance from government tobacco cessation services. We will use the adapted version of the DISCOVER conceptual framework for the designing, development, implementation and evaluation of an AI-based conversational interface.

Expected outcomes: The primary outcomes will be successful quit attempts (tobacco cessation 3 months ago, who reported ever tobacco use), and increased intention to quit (current tobacco user thinking about quitting within next 3 months, 6 months or so) among tobacco users and the secondary outcome will be acceptability, usability and user engagement with the AI-based conversational interface.