Dentists Readiness for AI-Powered Smoking Cessation Interventions in India: A cross-Sectional Study

Abstract

Tobacco use remains one of the most significant preventable public health challenges globally 
and in India, contributing extensively to oral diseases, systemic illnesses, and premature 
mortality. Dentists, owing to their routine clinical interaction with patients and their ability to 
detect early oral manifestations of tobacco use, are strategically positioned to play a critical 
role in tobacco screening and smoking cessation counselling. Despite this, tobacco cessation 
activities are not uniformly integrated into routine dental practice due to time constraints, lack 
of structured protocols, and limited training. 
With the rapid advancement of artificial intelligence (AI) in healthcare, new opportunities have 
emerged to support behavioural change interventions through personalised, efficient, and 
evidence-based digital tools. AI-powered smoking cessation applications, decision-support 
systems, and conversational agents have have shown increasing effectiveness in enhancing 
adherence, tailoring interventions, and supporting sustained behaviour change. However, the 
successful integration of such technologies into dental practice depends largely on dentists’ 
awareness, attitudes, readiness, and perceived feasibility of adoption. 
The present study adopts a quantitative cross-sectional research design to examine the role of 
dentists in the context of AI-powered smoking cessation interventions in India. Data were 
systematically collected from 100 registered dental practitioners using a structured self
administered questionnaire assessing awareness of AI, current tobacco cessation practices, 
attitudes toward AI-based interventions, readiness for adoption, and perceived implementation 
challenges. Reliability analysis demonstrated satisfactory internal consistency for the Attitude 
Scale (α = 0.74) and Readiness Scale (α = 0.77). Significant associations were observed 
between demographic variables and AI-related outcomes (p < 0.05). Descriptive and inferential 
statistical analyses were conducted using appropriate statistical techniques. 
The findings reveal high engagement in tobacco screening and counselling, positive attitudes 
toward AI-enabled smoking cessation tools, and strong readiness for adoption, despite limited 
formal training exposure. The study highlights the critical need for structured training 
programs, curricular integration, and institutional support to facilitate effective 
implementation. The results have important implications for dental education, preventive 
dentistry, and public health policy, particularly in strengthening AI-supported tobacco control 
strategies within dental settings. 
The study contributes to emerging literature on AI-enabled preventive dentistry and supports 
the integration of digital behavioural interventions into routine oral healthcare practice.