Factors affecting adherence with telerehabilitation in patients with multiple sclerosis

In Cheol Jeong, Jiazhen Liu, Joseph Finkelstein

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

13 Scopus citations


The goal of this study was to identify predictors of telerehabilitation adherence in patients with multiple sclerosis (MS). An adherence prediction model was based on baseline patient characteristics. Such a model may be useful for identifying patients who require higher levels of engagements in the early stages of home telerehabilitation programs. The resulting set of predictive features included education, patient satisfaction with the program, and psychological domain of the MS Impact Scale. Resulting prediction of high and low adherence had overall 80.0% accuracy, 81.8% sensitivity, and 77.8% specificity. We concluded that the baseline patient information may be instrumental in personalizing levels of support and training necessary for active patient participation in telerehabilitation.

Original languageEnglish
Title of host publicationImproving Usability, Safety and Patient Outcomes with Health Information Technology
Subtitle of host publicationFrom Research to Practice
EditorsAlex Mu-Hsing Kuo, Andre Kushniruk, Francis Lau, Elizabeth M. Borycki, Gerry Bliss, Helen Monkman, Abdul Vahabpour Roudsari, John A. Bartle-Clar, Karen L. Courtney
PublisherIOS Press
Number of pages5
ISBN (Electronic)9781614999508
StatePublished - 2019

Publication series

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


  • exercise adherence
  • multiple sclerosis
  • telerehabilitation


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