NCT04720625

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

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

• Status: Completed
• Phase: N/A
• Study type: Interventional
• Enrollment: 757 (actual)
• Sponsor: University of Massachusetts, Worcester · Academic / Other
• Sex: All
• Age: 18 Years – 99 Years
• Healthy volunteers: Not accepted

Summary

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.

Conditions

• Tobacco Smoking

Interventions

Type	Name	Description
BEHAVIORAL	Adapt2Quit	Motivational text messages and quitline facilitation text messages will be sent to participants; these participants will receive Adapt2Quit (experimental) messages as well as quitline facilitation messages.
BEHAVIORAL	Control	Quitline facilitation text messages will be sent to participants; these participants will receive quitline facilitation-only messages.

Timeline

• Start date: 2021-06-28
• Primary completion: 2024-10-10
• Completion: 2025-03-31
• First posted: 2021-01-22
• Last updated: 2025-05-01

Locations

3 sites across 1 country: United States