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

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

The purpose of this study is to evaluate the feasibility and preliminary effectiveness of delivering a personalized, just-in-time adaptive intervention driven by machine learning prediction of smoking lapse risk in real time.

Inclusion Criteria:

• a score greater than or equal to 4 on the Rapid Estimate of Adult Literacy in Medicine Short Form (REALM-SF),12
• willingness to quit smoking 14 days after the baseline visit
• no contraindications to using Nicotine replacement therapy (NRT).
• If participants would like to use their own phone to complete the EMAs, they must additionally have an Android smartphone (Android 5.2 or higher), and be willing to install the InsightTM mHealth app on their phone.

Exclusion Criteria:

• currently smoking less than 5 cigarettes per day