ArticleJournal of orthopaedic surgery and research2023
Assessing the importance of predictors of adherence to a digital self‑management intervention for osteoarthritis.
Article in Journal of orthopaedic surgery and research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Changes in health-related quality of life: a longitudinal registry study among over 15,000 participants of a digital education and exercise therapy for knee and hip osteoarthritis using EQ-5D-5L.Health and quality of life outcomes · 2026Article
- Strategies to Increase Patients' Adherence to Digital Therapeutics for Musculoskeletal Diseases: A Narrative Review.Yonsei medical journal · 2026Review
- Baseline pain medication is associated with longer duration of high adherence in a three-month digital treatment program for hip and knee osteoarthritis.Osteoarthritis and cartilage open · 2026Article
- Innovative approaches in discussions of diabetes among healthcare sector actors in Germany.Journal of public health policy · 2024Article
- Self-assessed performance-based function test versus patient-reported outcome measures for knee and hip osteoarthritis.BMC sports science, medicine & rehabilitation · 2024Article
- Sex and age differences in the patient-reported outcome measures and adherence to an osteoarthritis digital self-management intervention.Osteoarthritis and cartilage open · 2024Article
- The Impact of Intervention Design on User Engagement in Digital Therapeutics Research: Factorial Experiment With a Mixed Methods Study.JMIR formative research · 2024Article
- Exploring attitudes of people with chronic health conditions towards the use of group-based telerehabilitation: A qualitative study.Clinical rehabilitation · 2024Article
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Authors and funding
5 authors.
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Abstract
objectiveTreatment adherence is suggested to be associated with greater improvement in patient outcomes. Despite the growing use of digital therapeutics in osteoarthritis management, there is limited evidence of person-level factors influencing adherence to these interventions in real-world settings. We aimed to determine the relative importance of factors influencing adherence to a digital self-management intervention for hip/knee osteoarthritis.
methodsWe obtained data from people participating in a digital OA treatment, known as Joint Academy, between January 2019 and September 2021. We collected data on the participants' adherence, defined as the percentage of completed activities (exercises, lessons, and quizzes), at 3 (n = 14,610)- and 12-month (n = 2682) follow-up. We used dominance and relative weight analyses to assess the relative importance of sociodemographic (age, sex, place of residence, education, year of enrolment), lifestyle (body mass index, physical activity), general health (comorbidity, overall health, activity impairment, anxiety/depression), and osteoarthritis-related (index joint, fear of moving, walking difficulties, pain, physical function, wish for surgery, Patient Acceptable Symptom State) factors, measured at baseline, in explaining variations in adherence. We used bootstrap (1000 replications) to compute 95% confidence intervals.
resultsMean (SD) adherences at 3 and 12 months were 86.3% (16.1) and 84.1% (16.7), with 75.1% and 70.4% of participants reporting an adherence ≥ 80%, respectively. The predictors included in the study explained only 5.6% (95% CI 5.1, 6.6) and 8.1% (7.3, 11.6) of variations in 3- and 12-month adherences, respectively. Sociodemographic factors were the most important predictors explaining more variations than other factors altogether. Among single factors, age with a nonlinear relationship with adherence, was the most important predictor explaining 2.3% (95% CI 1.9, 2.8) and 3.7% (2.4, 5.3) of variations in 3- and 12-month adherences, respectively.
conclusionPerson-level factors could only modestly explain the variations in adherence with sociodemographic characteristics, mainly age, accounting for the greatest portion of this explained variance.
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