Comparison of a Collective Intelligence Tailored Messaging System on Smoking Cessation Between African American and White People Who Smoke: Quasi-Experimental Design

Abstract

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). Background: PERSPeCT is a machine learning recommender system with a database of messages to motivate smoking cessation. PERSPeCT uses collective intelligence of users (i.e., preferences and feedback), demographic and smoking profiles to select motivating messages. PERSPeCT may be more beneficial for tailoring content to minority groups influenced by complex, personally relevant factors. Objective: The objective of this study was to describe and evaluate the use of PERSPeCT in African American smokers compared to White smokers. Methods: Using a quasi-experimental design, we compared African American smokers with a historical cohort of White smokers, who both received up-to 30 daily emailed tailored messages. Smokers rated the daily message in terms of perceived influence on quitting smoking for 30 days. Our primary analysis compared daily message ratings between the two groups using a t-test. We used a logistic model to compare 30-day cessation between the two groups and adjusted for covariates. Results: The study included 119 smokers (African Americans n=55; Whites n=64). At baseline, African American smokers were significantly more likely to report allowing smoking in the home (P<.01); all other characteristics were not significantly different between groups. Daily mean ratings were higher for African American than White smokers on 26 of the 30 days (P<.01). Odds of quitting as measured by 30-day cessation were significantly higher for African Americans (Odds Ratio: 2.3, 95% CI 1.04, 5.53, P=.03) and did not change after adjusting for allowing smoking at home. Conclusions: Our study highlighted the potential of using a recommender system to personalize for African American smokers. Clinical Trial: Clinicaltrials.gov NCT02200432; https://clinicaltrials.gov/ct2/show/NCT02200432