Applying Collective Intelligence in Health Recommender Systems for Smoking Cessation: A Comparison Trial

Santiago Hors-Fraile, Math J.J.M. Candel, Francine Schneider, Shwetambara Malwade, Francisco J. Nunez-Benjumea, Shabbir Syed-Abdul, Luis Fernandez-Luque, Hein De Vries

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


Background: Health recommender systems (HRSs) are intelligent systems that can be used to tailor digital health interventions. We compared two HRSs to assess their impact providing smoking cessation support messages. Methods: Smokers who downloaded a mobile app to support smoking abstinence were randomly assigned to two interventions. They received personalized, ratable motivational messages on the app. The first intervention had a knowledge-based HRS (n = 181): It selected random messages from a subset matching the users' demographics and smoking habits. The second intervention had a hybrid HRS using collective intelligence (n = 190): It selected messages applying the knowledge-based filter first, and then chose the ones with higher ratings provided by other similar users in the system. Both interventions were compared on: (a) message appreciation, (b) engagement with the system, and (c) one's own self-reported smoking cessation status, as indicated by the last seven-day point prevalence report in different time intervals during a period of six months. Results: Both interventions had similar message appreciation, number of rated messages, and abstinence results. The knowledge-based HRS achieved a significantly higher number of active days, number of abstinence reports, and better abstinence results. The hybrid algorithm led to more quitting attempts in participants who completed their user profiles.

Original languageEnglish
Article number1219
JournalElectronics (Switzerland)
Issue number8
Publication statusPublished - Apr 1 2022


  • Behavior change
  • Demographic filtering
  • Engagement
  • Health recommender systems
  • Message appreciation
  • Smoking cessation

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Signal Processing
  • Hardware and Architecture
  • Computer Networks and Communications
  • Electrical and Electronic Engineering


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