Promoting Smoking Cessation in the Community Via "Quit to Win" Contest 2026: Engagement-Focused GenAI-based Chatbot for Real-Time Smoking Cessation Support

Official title

Building Capacity and Promoting Smoking Cessation in the Community Via "Quit to Win" Contest 2026: Real-time Smoking Cessation Instant Messaging Support Using a Engagement-Focused Large Language Model (LLM)-Based Chatbot

Overview

The goal of this trial is to learn if chatbot-based instant messaging works to help smoking cessation in general adult smokers. It will also learn about the experience, attitude, and perception of using an LLM-based chatbot. The main questions it aims to answer are: 1. Will an engagement-focused LLM-based chatbot smoking cessation intervention have a non-inferior validated abstinence rate than the control group? 2. Will an LLM-based chatbot smoking cessation intervention have a non-inferior self-reported abstinence rate, smoking reduction rate, and smoking cessation services use rate than the control group? Researchers will compare an LLM-based chatbot smoking-cessation intervention to a human-led instant messaging support group (brief advice based on AWARD and personalised active referral) to determine whether chatbot-based instant messaging support promotes smoking cessation. Participants in the intervention group will receive: 1. AWARD advice 2. Personalised active referral 3. 12 weeks of chatbot-based instant messaging support (via WhatsApp)

Detailed description

Although smoking prevalence in Hong Kong has declined to 9.1% in 2023, achieving the government's target of 7.8% by 2025 remains a major public health challenge. Unassisted "cold turkey" quitting has a long-term success rate of less than 5%, whereas evidence-based behavioural and pharmacological interventions can raise success rates to approximately 20% or higher. However, existing cessation services in Hong Kong face a critical utilisation gap: only 17.5% of smokers have engaged with professional services, and merely 23% have used nicotine replacement therapy. This underutilisation suggests that traditional human-resource-intensive models may lack accessibility, scalability, and local appeal. Generative AI, particularly large language models, offers a transformative solution by delivering consistent, scalable, and personalised support. In the 2025 "Quit to Win" round, investigators integrated an LLM-based chatbot via WhatsApp and received positive qualitative feedback. Yet quantitative analysis revealed a sharp decline in engagement, with weekly participation dropping from 32% in week 1 to 14% by week 12, indicating that conversational ability alone does not guarantee sustained user commitment. To address this implementation gap, investigators have developed an engagement-focused GenAI companion that incorporates structured onboarding, context-aware personalisation, multimodal (text/audio) input, empathetic support, habit-aligned reminders, localised humour, and gamified features such as success stories and knowledge quizzes. Therefore, the current study aims to test, via a two-arm non-inferiority randomised controlled trial, the effectiveness of a comprehensive intervention combining brief cessation advice (AWARD), personalised active referral, and this engagement-enhanced GenAI chatbot support compared with human-led instant messaging counselling among current smokers who join the Quit to Win Contest across all 18 districts of Hong Kong.

Interventions

• Behavioral AWARD advice
  A brief (30-60 seconds) face-to-face or remote smoking cessation advice delivered using the validated AWARD model: Ask about smoking history; Warn about high health risks (accompanied by a health warning leaflet); Advise quitting as soon as possible and setting a quit date (to qualify for contest prizes); Refer to smoking cessation services using a referral card; Do it again - repeat the intervention at each follow-up, encouraging re-quitting after relapse or relapse prevention after success.
• Behavioral Brief leaflet on health warning and smoking cessation
  A two-sided, colour-printed A4 leaflet covering: (1) absolute risk of death from smoking; (2) full list of diseases caused by active and second-hand smoking; (3) ten pictorial warnings of health consequences on one page for maximum impact; (4) benefits of smoking cessation; and (5) simple encouraging messages to quit.
• Behavioral Referral card
  A three-folded card containing brief information and highlights of existing smoking cessation services in Hong Kong, contact methods, motivational messages, and strong supporting slogans.
• Behavioral Self-help smoking cessation booklet
  A generic booklet provided covering: benefits of quitting, smoking-related diseases, methods to quit, how to handle withdrawal symptoms, a quitting declaration, and other practical tips.
• Behavioral Personalized active referral
  Smokers will be introduced to various SC services in Hong Kong (via the referral card) and motivated to use them. Well-trained SC ambassadors will assist smokers in choosing their favourite or most convenient type of service. Research staff will assist participants in booking or re-booking the SC services at the 1- and 2-month follow-ups (after very brief questionnaire surveys). Participants' contact information will be forwarded to SC service providers within 7 days, and providers are expected
• Behavioral 12 weeks of chatbot-based instant messaging support
  Participants in the intervention group will receive 12 weeks of instant messaging support delivered by an LLM-based chatbot (GPT-4o or newer) on WhatsApp, supporting text and audio input. Using prompt engineering, agent techniques, and Retrieval-Augmented Generation, the chatbot delivers theory-based 5As/5Rs-structured interventions alongside freeform, on-demand support, with engagement features including personalisation, proactive check-ins, and interactive Quick Commands.
• Behavioral 12 weeks of human-led instant messaging support
  Participants in the control group will receive 12 weeks of instant messaging support delivered by a trained human counsellor via WhatsApp. Using the same theoretical frameworks as the chatbot intervention, the counsellor will provide real-time behavioural and psychosocial support grounded in the 5As/5Rs models, Motivational Interviewing (MI), and evidence-based Behaviour Change Techniques (BCTs). The support will be personalised according to each participant's sociodemographic characteristics, s
• Behavioral Reminder messages
  WhatsApp messages on follow-up survey reminders.

Primary outcome measures

• Biochemically validated abstinence [Time frame: 6-month follow-up]

Secondary outcome measures (10)

• Biochemically validated abstinence [Time frame: 3-month follow-up]
• Self-reported 7-day point prevalence abstinence [Time frame: 3- and 6-month follow-ups]
• Self-reported reduction [Time frame: 1-, 2-, 3- and 6-month follow-ups]
• Self-reported use of smoking cessation service [Time frame: 1-, 2-, 3- and 6-month follow-ups]
• Prolonged abstinence [Time frame: 3-month and 6-month follow-ups]
• Quit attempt [Time frame: 1-, 2-, 3-, and 6-month follow-ups]
• Post-cessation weight change [Time frame: 6-month follow-up]
• Self-reported mental health conditions [Time frame: Baseline and 6-month follow-up]
• Self-reported smoking-related health conditions [Time frame: Baseline and 6-month follow-up]
• Chatbot user experience [Time frame: 3-month follow-up]

Eligibility criteria

Inclusion criteria

• Hong Kong residents aged 18 years or above
• Smoke at least one cigarette (including heated tobacco products) per day or use an e-cigarette daily in the preceding 3 months
• Able to communicate in Cantonese (including reading and writing Chinese)
• Saliva cotinine level ≥30 ng/mL
• Intention to quit or reduce smoking
• Have WhatsApp installed
• Able to use WhatsApp for communication

Exclusion criteria

• Smokers who have communication barriers (either physical or cognitive)
• Smokers who are currently participating in other smoking cessation programs or services

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: No

Study design

Allocation

Randomized

Model

Parallel assignment

Masking

Single blind

Primary purpose

Health services research

Study locations

Hong Kong · 1 center

• Hong Kong Council on Smoking and Health (COSH) — Hong Kong

Identifiers

NCT: NCT07649044 · QTW2026

Primary sources (government registries)

• ClinicalTrials.gov (US NIH)

View this study on ClinicalTrials.gov ↗