Adapt2Quit - An Adaptive Motivational System for Socio-Economically Disadvantaged Smokers

Adapt2Quit - A Machine-Learning, Adaptive Motivational System: RCT for Socio-Economically Disadvantaged Smokers

The goal of this research is to test the Adapt2Quit computer program that uses participant input (message rating on how much the text motivational message might influence one to quit smoking) to select and text motivational messages that are more likely to help a user stop smoking. This Adapt2Quit system will be compared with a quitline facilitation-only control (text messages will be sent to facilitate quitline use). The primary research hypothesis is that the Adapt2Quit recommender-selected messages will be more effective than a texting quitline facilitation-only control for smoking cessation among socioeconomically disadvantaged (SED) smokers.

The Adapt2Quit trial (NCT04720625) is a randomized controlled trial testing a machine-learning-driven text messaging system aimed at increasing smoking cessation rates among socioeconomically disadvantaged adults.

The 6-month study compares an adaptive, personalized motivational messaging intervention against standard Quitline facilitation, utilizing AI to select tailored behavioral prompts based on user feedback.

Inclusion Criteria:

• Current smoker
• Socioeconomically disadvantaged (SED) (using the following criteria: unemployed or underemployed, low income as defined by the federal poverty level guidelines, uninsured or underinsured, and/or have less than a high school education)
• English-speaking
• Active in care (at least two clinical visits in the last year)
• Have a texting-enabled cell phone

Exclusion Criteria:

• Not a current smoker
• Adults unable to consent
• Individuals who are not yet adults (infants, children, teenagers)
• Prisoners
• Pregnant women
• Pilot study participants