A system that uses machine learning to help socio-economically disadvantaged smokers quit smoking

Adapt2Quit – A Machine-Learning, Adaptive Motivational System: RCT for Socio-Economically Disadvantaged smokers”

['FUNDING_R01'] · UNIV OF MASSACHUSETTS MED SCH WORCESTER · NIH-10818471

This study is testing a smart messaging system called Adapt2Quit that sends personalized encouragement to help smokers quit, especially focusing on those who might need extra support, and it will see how well it works compared to regular messages.

Quick facts

Phase['FUNDING_R01']
Study typeNih_funding
SexAll
SponsorUNIV OF MASSACHUSETTS MED SCH WORCESTER (nih funded)
Locations1 site (WORCESTER, UNITED STATES)
Trial IDNIH-10818471 on ClinicalTrials.gov

What this research studies

This research investigates Adapt2Quit, a machine-learning system designed to provide personalized motivational messages to help smokers quit. By analyzing individual smoker profiles and their feedback, the system adapts its messaging to improve engagement and effectiveness. The approach is innovative as it continuously learns from past smokers' experiences to enhance the relevance of its messages. The study will compare Adapt2Quit's effectiveness against a standard messaging system to evaluate its impact on smoking cessation, particularly among socio-economically disadvantaged smokers.

Who could benefit from this research

Good fit: Ideal candidates for this research are socio-economically disadvantaged individuals who smoke and are seeking to quit.

Not a fit: Patients who do not smoke or are not interested in quitting smoking may not benefit from this research.

Why it matters

Potential benefit: If successful, this research could significantly improve smoking cessation rates among socio-economically disadvantaged populations.

How similar studies have performed: Previous research has shown success with similar personalized messaging approaches, but this specific machine-learning application is novel.

Where this research is happening

WORCESTER, UNITED STATES

Researchers

About this research

  1. This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
  2. Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
  3. For full project details, budget, and progress reports, visit the official NIH RePORTER page below.

View on NIH RePORTER →

Last reviewed 2026-05-15 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.