Mapping the adoption and implementation of artificial intelligence (AI)-based conversational interface for tobacco cessation: a scoping review protocol.
- 1Public Health Foundation of India (PHFI), New Delhi, 110030, India.
- 2HRIDAY, Green Park Extension, New Delhi, 110016, India.
- 3Public Health Foundation of India (PHFI), New Delhi, 110030, India. [email protected].
Abstract
Background
Tobacco use remains a leading global public health issue, accounting for nearly 8 million deaths annually. Despite ongoing efforts through various health interventions and programmes aimed at tobacco cessation, significant challenges persist, particularly in low- and middle-income countries (LMICs). The advent of artificial intelligence (AI)-driven conversational interfaces presents a promising, scalable approach to overcoming existing obstacles in traditional tobacco cessation initiatives. The aim of the scoping review is to systematically map and analyse the global evidence on the adoption and implementation of AI-based conversational interfaces for tobacco cessation. It will ultimately support strengthening the existing health system.Methods
This scoping review will follow the methodological framework outlined by Arksey and O'Malley and Levac et al. A comprehensive search will be conducted across four electronic databases: PubMed, CINAHL, Web of Science, and Scopus, using search terms related to AI-based conversational tools for tobacco cessation and implementation. The findings will be narratively synthesised, adopting the Consolidated Framework for Implementation Research (CFIR), structured according to its key domains. Review will follow the "Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Review (PRISMA-ScR)" guidelines.Conclusions/discussion
The review aims to identify the key barriers and facilitators for implementing AI-driven conversational interventions for tobacco cessation. It also seeks to identify best practices to support the effective integration of AI-driven cessation interventions across diverse healthcare contexts/settings. By mapping the global landscape and current evidence, particularly in the low-resource countries with high tobacco burden, this review will highlight the implementation challenges. Ultimately, this effort aims to support evidence-based deployment of AI-based conversational agents to achieve the WHO's target to reduce the prevalence of tobacco use by < 5%.Systematic review registration
The protocol has been prospectively registered on the "Open Science Framework (OSF)", https://doi.org/10.17605/OSF.IO/62FDB .
Related
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BibTeX
@article{kaur2026mapping,
title = {{Mapping the adoption and implementation of artificial intelligence (AI)-based conversational interface for tobacco cessation: a scoping review protocol.}},
author = {Navpreet Kaur and Priyobrat Rajkhowa and Shalini Bassi and Raj Mohan Panda and Monirujjaman Biswas and Mohai Menul Biswas and Monika Arora},
journal = {Systematic reviews},
year = {2026},
month = jul,
doi = {10.1186/s13643-026-03140-x},
url = {https://europepmc.org/article/MED/42902410},
note = {CC BY},
}
RIS
TY - JOUR
TI - Mapping the adoption and implementation of artificial intelligence (AI)-based conversational interface for tobacco cessation: a scoping review protocol.
AU - Navpreet Kaur
AU - Priyobrat Rajkhowa
AU - Shalini Bassi
AU - Raj Mohan Panda
AU - Monirujjaman Biswas
AU - Mohai Menul Biswas
AU - Monika Arora
PY - 2026
DA - 2026/07/01
JO - Systematic reviews
DO - 10.1186/s13643-026-03140-x
UR - https://europepmc.org/article/MED/42902410
AB - Background Tobacco use remains a leading global public health issue, accounting for nearly 8 million deaths annually. Despite ongoing efforts through various health interventions and programmes aimed at tobacco cessation, significant challenges persist, particularly in low- and middle-income countries (LMICs). The advent of artificial intelligence (AI)-driven conversational interfaces presents a promising, scalable approach to overcoming existing obstacles in traditional tobacco cessation initiatives. The aim of the scoping review is to systematically map and analyse the global evidence on the adoption and implementation of AI-based conversational interfaces for tobacco cessation. It will ultimately support strengthening the existing health system.Methods This scoping review will follow the methodological framework outlined by Arksey and O'Malley and Levac et al. A comprehensive search will be conducted across four electronic databases: PubMed, CINAHL, Web of Science, and Scopus, using search terms related to AI-based conversational tools for tobacco cessation and implementation. The findings will be narratively synthesised, adopting the Consolidated Framework for Implementation Research (CFIR), structured according to its key domains. Review will follow the "Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Review (PRISMA-ScR)" guidelines.Conclusions/discussion The review aims to identify the key barriers and facilitators for implementing AI-driven conversational interventions for tobacco cessation. It also seeks to identify best practices to support the effective integration of AI-driven cessation interventions across diverse healthcare contexts/settings. By mapping the global landscape and current evidence, particularly in the low-resource countries with high tobacco burden, this review will highlight the implementation challenges. Ultimately, this effort aims to support evidence-based deployment of AI-based conversational agents to achieve the WHO's target to reduce the prevalence of tobacco use by < 5%.Systematic review registration The protocol has been prospectively registered on the "Open Science Framework (OSF)", https://doi.org/10.17605/OSF.IO/62FDB .
SN - 2046-4053
ER -