Abstract
BackgroundMotivational messaging is a frequently used digital intervention to promote positive health behavior changes, including smoking cessation. Typically, motivational messaging systems have not actively sought feedback on each message, preventing a closer examination of the user-system engagement. This study assessed the granular user-system engagement around a recommender system (a new system that actively sought user feedback on each message to improve message selection) for promoting smoking cessation and the impact of engagement on cessation outcome.MethodsWe prospectively followed a cohort of current smokers enrolled to use the recommender system for 6 months. The system sent participants motivational messages to support smoking cessation every 3 days and used machine learning to incorporate user feedback (i.e., user’s rating on the perceived influence of each message, collected on a 5-point Likert scale with 1 indicating strong disagreement and 5 indicating strong agreement on perceiving the influence on quitting smoking) to improve the selection of the following message. We assessed user-system engagement by various metrics, including user response rate (i.e., the percent of times a user rated the messages) and the perceived influence of messages. We compared retention rates across different levels of user-system engagement and assessed the association between engagement and the 7-day point prevalence abstinence (missing outcome = smoking) by using multiple logistic regression.ResultsWe analyzed data from 731 participants (13% Black; 73% women). The user response rate was 0.24 (SD = 0.34) and user-perceived influence was 3.76 (SD = 0.84). The retention rate positively increased with the user response rate (trend test P < 0.001). Compared with non-response, six-month cessation increased with the levels of response rates: low response rate (odds ratio [OR] = 1.86, 95% confidence interval [CI]: 1.07–3.23), moderate response rate (OR = 2.30, 95% CI: 1.36–3.88), high response rate (OR = 2.69, 95% CI: 1.58–4.58). The association between perceived message influence and the outcome showed a similar pattern.ConclusionsHigh user-system engagement was positively associated with both high retention rate and smoking cessation, suggesting that investigation of methods to increase engagement may be crucial to increase the impact of the recommender system for smoking cessation.Trial registrationRegistration Identifier: NCT03224520. Registration date: July 21, 2017.
Highlights
Motivational messaging is a frequently used digital intervention to promote positive health behavior changes, including smoking cessation
High user-system engagement was positively associated with both high retention rate and smoking cessation, suggesting that investigation of methods to increase engagement may be crucial to increase the impact of the recommender system for smoking cessation
Engagement and smoking cessation To assess the impact of user-system engagement on smoking cessation, we examined the association between engagement and the 7-day point prevalence abstinence at 6-month follow-up
Summary
Motivational messaging is a frequently used digital intervention to promote positive health behavior changes, including smoking cessation. Motivational messaging is a frequently used function in digital health interventions and has been adopted in several real-world smoking cessation programs [1,2,3,4,5]. Most CTHC systems are rulebased, where patients’ baseline characteristics (e.g., age, race, sex) are matched to if- rules to select messages [6, 21]. One limitation of these systems is that they use pre-designed rules, and when being used, do not seek user feedback to improve message selection
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