Systematic review of behavioral obesity interventions and their persuasive qualities

Anna Xu, Taridzo Chomutare, Sriram Iyengar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations


In this systematic review of weight loss interventions, we reviewed interventions aimed at maintaining weight loss, and identify persuasive elements that drive weight maintenance. Methods: We searched the Medline database for long-term obesity interventions, and targeted randomized control trials that aimed to reduce weight among adults for over 12 months, and extracted outcomes related to body weight change. Results: Seventeen publications were in the final review. Tailoring, or group counseling led by a health care professional, was shown to have a significant effect on long-term weight loss. Positive effects were also obtained by personalization (one-on-one counseling), competition (competing against other people trying to lose weight), and reminders. Conclusion: Maintaining weight loss long-term as so far eluded researchers, but results suggest that that some elements of the interventions are more greatly associated with weight maintenance than others. Future interventions might be more effective if they were based on persuasive technology.

Original languageEnglish (US)
Title of host publicationPersuasive Technology - 9th International Conference, PERSUASIVE 2014, Proceedings
Number of pages11
ISBN (Print)9783319071268
StatePublished - 2014
Externally publishedYes
Event9th International Conference on Persuasive Technology, PERSUASIVE 2014 - Padua, Italy
Duration: May 21 2014May 23 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8462 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other9th International Conference on Persuasive Technology, PERSUASIVE 2014


  • behavior
  • obesity
  • Persuasive technology
  • systematic review

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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