Using Machine Learning to Develop Just-in-Time Adaptive Interventions for Smoking Cessation

NACompletedINTERVENTIONAL
Enrollment

60

Participants

Timeline

Start Date

February 6, 2024

Primary Completion Date

November 22, 2024

Study Completion Date

November 22, 2024

Conditions
Smoking Cessation
Interventions
BEHAVIORAL

Android Wear smartwatch

All participants will wear an Android Wear smartwatch, and will complete ecological momentary assessments (EMA).

BEHAVIORAL

Adaptive Treatment

"Participants will have access to a Dashboard button in the InsightTM app that displays personalized statistics based on their progress and patterns in the study.The dashboard will update as more data is collected about the participant's smoking habits, starting in the pre-quit period and continuing through the post-quit period. Second, in the post-quit period, participants will receive treatment messages when the machine learning algorithm determines that they are at high risk for lapse.At the follow-up visit, participants will complete a survey to evaluate what they liked and disliked about the intervention, how accurate they thought the app was in predicting their risk, and how useful they found the dashboard."

DRUG

Nicotine Patch

At Visit 2, participants will be asked to begin their attempt to quit smoking and will receive a 12-week supply of nicotine replacement therapy (i.e., nicotine patches and gum)

BEHAVIORAL

interviewing-based counseling

At Visit 2, participants will be asked to begin their attempt to quit smoking and meet with a Tobacco Treatment Specialist, who will provide motivational interviewing-based counseling, help the participants develop a quit plan, and discuss relapse prevention. During the 6-weeks of the study, participants will have the option of attending up to 6 counseling sessions with the Tobacco Treatment Specialist, either in-person or via phone or web.

Trial Locations (1)

77030

The University of Texas Health Science Center at Houston, Houston

All Listed Sponsors
collaborator

National Institute on Drug Abuse (NIDA)

NIH

lead

The University of Texas Health Science Center, Houston

OTHER

NCT04839198 - Using Machine Learning to Develop Just-in-Time Adaptive Interventions for Smoking Cessation | Biotech Hunter | Biotech Hunter