Effect of the telemedicine-supported multicomponent exercise therapy in patients with knee osteoarthritis: study protocol for a randomized controlled trial

Author:

Feng Yuan,Wu Yan,Liu Huizhen,Bao Tianjie,Wang Chongyang,Wang Zezhang,Huang Jielei,Jiang Yiwei,He ChengqiORCID,Zhu SiyiORCID

Abstract

Abstract Introduction The rising prevalence of knee osteoarthritis is placing a considerable strain on the global healthcare system. To address this issue, telemedicine-supported multicomponent exercise therapy has emerged as a promising approach. This therapy combines exercise, patient education, and health coaching to empower knee osteoarthritis patients to manage their condition from the comfort of their homes. Nevertheless, there are some existing limitations in the current research on this approach, including challenges related to patient compliance and the absence of objective evaluation methods. Methods and analysis Patients diagnosed with knee osteoarthritis, who have not undergone knee surgery in the past year, will be recruited for a randomized controlled trial. The trial will include an intervention group and a control group. The intervention group will receive an mHealth app-based multicomponent exercise therapy, consisting of exercise therapy, patient education, and health coaching. Meanwhile, the control group will receive usual care, involving drug therapy and patient education. The primary outcome of the trial will be the measurement of pain intensity, assessed using a visual analog scale at baseline and at 4, 8, and 12 weeks of the post-intervention. To analyze the data, a two-factor, four-level repeated measures ANOVA will be used if the assumptions of homogeneity of variance and sphericity are met. If not, a mixed effects model will be employed. Discussion The aim of the study is to evaluate the effectiveness of multicomponent exercise therapy aimed at enhancing pain self-management for knee osteoarthritis patients in the comfort of their own homes. The intervention incorporate wearable devices equipped with advanced deep learning systems to monitor patients' adherence to the prescribed at-home exercise regimen, as well as to track changes in outcomes before and after the exercise sessions. The findings from this trial have the potential to enhance both the accessibility and quality of care provided to knee osteoarthritis patients, offering valuable insights for future improvements in their treatment and management. Trial registration Chinese Clinical Trials Registry, ChiCTR2300073688. Registered on 19 July 2023, https://www.chictr.org.cn/bin/project/edit?pid=199707. World Health Organization International Clinical Trials Registry Platform, https://trialsearch.who.int/Trial2.aspx?TrialID=ChiCTR2300073688.

Funder

National Natural Science Foundation of China

National Innovation and Entrepreneurship Training Project for Undergraduate

Sichuan University Postgraduate Education Reform Project

Publisher

Springer Science and Business Media LLC

Subject

Pharmacology (medical),Medicine (miscellaneous)

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