Factors affecting adherence with telerehabilitation in patients with multiple sclerosis

In Cheol Jeong; Jiazhen Liu; Joseph Finkelstein

doi:10.3233/978-1-61499-951-5-189

Factors affecting adherence with telerehabilitation in patients with multiple sclerosis

In Cheol Jeong, Jiazhen Liu, Joseph Finkelstein

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

13 Scopus citations

Abstract

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 language	English
Title of host publication	Improving Usability, Safety and Patient Outcomes with Health Information Technology
Subtitle of host publication	From Research to Practice
Editors	Alex Mu-Hsing Kuo, Andre Kushniruk, Francis Lau, Elizabeth M. Borycki, Gerry Bliss, Helen Monkman, Abdul Vahabpour Roudsari, John A. Bartle-Clar, Karen L. Courtney
Publisher	IOS Press
Pages	189-193
Number of pages	5
ISBN (Electronic)	9781614999508
DOIs	https://doi.org/10.3233/978-1-61499-951-5-189
State	Published - 2019

Publication series

Name	Studies in Health Technology and Informatics
Volume	257
ISSN (Print)	0926-9630
ISSN (Electronic)	1879-8365

Keywords

exercise adherence
multiple sclerosis
telerehabilitation

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10.3233/978-1-61499-951-5-189

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Jeong, I. C., Liu, J., & Finkelstein, J. (2019). Factors affecting adherence with telerehabilitation in patients with multiple sclerosis. In A. M-H. Kuo, A. Kushniruk, F. Lau, E. M. Borycki, G. Bliss, H. Monkman, A. V. Roudsari, J. A. Bartle-Clar, & K. L. Courtney (Eds.), Improving Usability, Safety and Patient Outcomes with Health Information Technology: From Research to Practice (pp. 189-193). (Studies in Health Technology and Informatics; Vol. 257). IOS Press. https://doi.org/10.3233/978-1-61499-951-5-189

Jeong, In Cheol ; Liu, Jiazhen ; Finkelstein, Joseph. / Factors affecting adherence with telerehabilitation in patients with multiple sclerosis. Improving Usability, Safety and Patient Outcomes with Health Information Technology: From Research to Practice. editor / Alex Mu-Hsing Kuo ; Andre Kushniruk ; Francis Lau ; Elizabeth M. Borycki ; Gerry Bliss ; Helen Monkman ; Abdul Vahabpour Roudsari ; John A. Bartle-Clar ; Karen L. Courtney. IOS Press, 2019. pp. 189-193 (Studies in Health Technology and Informatics).

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title = "Factors affecting adherence with telerehabilitation in patients with multiple sclerosis",

abstract = "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.",

keywords = "exercise adherence, multiple sclerosis, telerehabilitation",

author = "Jeong, {In Cheol} and Jiazhen Liu and Joseph Finkelstein",

year = "2019",

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language = "English",

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editor = "Kuo, {Alex Mu-Hsing} and Andre Kushniruk and Francis Lau and Borycki, {Elizabeth M.} and Gerry Bliss and Helen Monkman and Roudsari, {Abdul Vahabpour} and Bartle-Clar, {John A.} and Courtney, {Karen L.}",

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Jeong, IC, Liu, J & Finkelstein, J 2019, Factors affecting adherence with telerehabilitation in patients with multiple sclerosis. in AM-H Kuo, A Kushniruk, F Lau, EM Borycki, G Bliss, H Monkman, AV Roudsari, JA Bartle-Clar & KL Courtney (eds), Improving Usability, Safety and Patient Outcomes with Health Information Technology: From Research to Practice. Studies in Health Technology and Informatics, vol. 257, IOS Press, pp. 189-193. https://doi.org/10.3233/978-1-61499-951-5-189

Factors affecting adherence with telerehabilitation in patients with multiple sclerosis. / Jeong, In Cheol; Liu, Jiazhen; Finkelstein, Joseph.
Improving Usability, Safety and Patient Outcomes with Health Information Technology: From Research to Practice. ed. / Alex Mu-Hsing Kuo; Andre Kushniruk; Francis Lau; Elizabeth M. Borycki; Gerry Bliss; Helen Monkman; Abdul Vahabpour Roudsari; John A. Bartle-Clar; Karen L. Courtney. IOS Press, 2019. p. 189-193 (Studies in Health Technology and Informatics; Vol. 257).

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

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AB - 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.

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Jeong IC, Liu J, Finkelstein J. Factors affecting adherence with telerehabilitation in patients with multiple sclerosis. In Kuo AM-H, Kushniruk A, Lau F, Borycki EM, Bliss G, Monkman H, Roudsari AV, Bartle-Clar JA, Courtney KL, editors, Improving Usability, Safety and Patient Outcomes with Health Information Technology: From Research to Practice. IOS Press. 2019. p. 189-193. (Studies in Health Technology and Informatics). doi: 10.3233/978-1-61499-951-5-189

Factors affecting adherence with telerehabilitation in patients with multiple sclerosis

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