Optimizing Decision Support for Tailored Health Behavior Change Applications

Rita Kukafka, In Cheol Jeong, Joseph Finkelstein

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

Abstract

The Tailored Lifestyle Change Decision Aid (TLC DA) system was designed to provide support for a person to make an informed choice about which behavior change to work on when multiple unhealthy behaviors are present. TLC DA can be delivered via web, smartphones and tablets. The system collects a significant amount of information that is used to generate tailored messages to consumers to persuade them in certain healthy lifestyles. One limitation is the necessity to collect vast amounts of information from users who manually enter. By identifying an optimal set of self-reported parameters we will be able to minimize the data entry burden of the app users. The study was to identify primary determinants of health behavior choices made by patients after using the system. Using discriminant analysis an optimal set of predictors was identified. The resulting set included smoking status, smoking cessation success estimate, self-efficacy, body mass index and diet status. Predicting smoking cessation choice was the most accurate, followed by weight management. Physical activity and diet choices were better identified in a combined cluster.

Original languageEnglish (US)
Title of host publicationMEDINFO 2015
Subtitle of host publicationeHealth-Enabled Health - Proceedings of the 15th World Congress on Health and Biomedical Informatics
EditorsAndrew Georgiou, Indra Neil Sarkar, Paulo Mazzoncini de Azevedo Marques
PublisherIOS Press
Pages108-112
Number of pages5
ISBN (Electronic)9781614995630
DOIs
StatePublished - Jan 1 2015
Event15th World Congress on Health and Biomedical Informatics, MEDINFO 2015 - Sao Paulo, Brazil
Duration: Aug 19 2015Aug 23 2015

Publication series

NameStudies in Health Technology and Informatics
Volume216
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365

Other

Other15th World Congress on Health and Biomedical Informatics, MEDINFO 2015
CountryBrazil
CitySao Paulo
Period8/19/158/23/15

Keywords

  • Consumer Behaviour
  • Decision Support Systems
  • Self-Management
  • Statistical Analysis

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

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  • Cite this

    Kukafka, R., Jeong, I. C., & Finkelstein, J. (2015). Optimizing Decision Support for Tailored Health Behavior Change Applications. In A. Georgiou, I. N. Sarkar, & P. M. de Azevedo Marques (Eds.), MEDINFO 2015: eHealth-Enabled Health - Proceedings of the 15th World Congress on Health and Biomedical Informatics (pp. 108-112). (Studies in Health Technology and Informatics; Vol. 216). IOS Press. https://doi.org/10.3233/978-1-61499-564-7-108