Evaluating the use of a recommender system for selecting optimal messages for smoking cessation: patterns and effects of user-system engagement
Authors
Chen, JinyingHouston, Thomas K.
Faro, Jamie M.
Nagawa, Catherine S.
Orvek, Elizabeth Aaker
Blok, Amanda C.
Allison, Jeroan J.
Person, Sharina D.
Smith, Bridget M.
Sadasivam, Rajani S.
UMass Chan Affiliations
Graduate School of Biomedical SciencesDivision of Biostatistics and Health Services Research, Department of Population and Quantitative Health Sciences
Division of Health Informatics and Implementation Science, Department of Population and Quantitative Health Sciences
Document Type
Journal ArticlePublication Date
2021-09-26Keywords
Computer-tailored health communicationDigital health intervention
Engagement
Motivational messaging
Recommender system
Smoking cessation
Epidemiology
Health Communication
Health Information Technology
Health Services Administration
Health Services Research
Substance Abuse and Addiction
Metadata
Show full item recordAbstract
BACKGROUND: Motivational 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. METHODS: We 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. RESULTS: We 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. CONCLUSIONS: 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. TRIAL REGISTRATION: Registration Identifier: NCT03224520 . Registration date: July 21, 2017.Source
Chen J, Houston TK, Faro JM, Nagawa CS, Orvek EA, Blok AC, Allison JJ, Person SD, Smith BM, Sadasivam RS. Evaluating the use of a recommender system for selecting optimal messages for smoking cessation: patterns and effects of user-system engagement. BMC Public Health. 2021 Sep 26;21(1):1749. doi: 10.1186/s12889-021-11803-8. PMID: 34563161; PMCID: PMC8465689. Link to article on publisher's site
DOI
10.1186/s12889-021-11803-8Permanent Link to this Item
http://hdl.handle.net/20.500.14038/46990PubMed ID
34563161Related Resources
Rights
Copyright © The Author(s) 2021. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.Distribution License
http://creativecommons.org/licenses/by/4.0/ae974a485f413a2113503eed53cd6c53
10.1186/s12889-021-11803-8
Scopus Count
Except where otherwise noted, this item's license is described as Copyright © The Author(s) 2021. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
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