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Assessing the importance of predictors of adherence to a digital self‑management intervention for osteoarthritis
OBJECTIVE: Treatment 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 settin...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9926753/ https://www.ncbi.nlm.nih.gov/pubmed/36782324 http://dx.doi.org/10.1186/s13018-023-03562-6 |
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author | Kiadaliri, Ali Dell’Isola, Andrea Lohmander, L. Stefan Hunter, David J. Dahlberg, Leif E. |
author_facet | Kiadaliri, Ali Dell’Isola, Andrea Lohmander, L. Stefan Hunter, David J. Dahlberg, Leif E. |
author_sort | Kiadaliri, Ali |
collection | PubMed |
description | OBJECTIVE: Treatment 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. METHODS: We 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. RESULTS: Mean (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. CONCLUSION: Person-level factors could only modestly explain the variations in adherence with sociodemographic characteristics, mainly age, accounting for the greatest portion of this explained variance. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13018-023-03562-6. |
format | Online Article Text |
id | pubmed-9926753 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-99267532023-02-15 Assessing the importance of predictors of adherence to a digital self‑management intervention for osteoarthritis Kiadaliri, Ali Dell’Isola, Andrea Lohmander, L. Stefan Hunter, David J. Dahlberg, Leif E. J Orthop Surg Res Research Article OBJECTIVE: Treatment 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. METHODS: We 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. RESULTS: Mean (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. CONCLUSION: Person-level factors could only modestly explain the variations in adherence with sociodemographic characteristics, mainly age, accounting for the greatest portion of this explained variance. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13018-023-03562-6. BioMed Central 2023-02-13 /pmc/articles/PMC9926753/ /pubmed/36782324 http://dx.doi.org/10.1186/s13018-023-03562-6 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Kiadaliri, Ali Dell’Isola, Andrea Lohmander, L. Stefan Hunter, David J. Dahlberg, Leif E. Assessing the importance of predictors of adherence to a digital self‑management intervention for osteoarthritis |
title | Assessing the importance of predictors of adherence to a digital self‑management intervention for osteoarthritis |
title_full | Assessing the importance of predictors of adherence to a digital self‑management intervention for osteoarthritis |
title_fullStr | Assessing the importance of predictors of adherence to a digital self‑management intervention for osteoarthritis |
title_full_unstemmed | Assessing the importance of predictors of adherence to a digital self‑management intervention for osteoarthritis |
title_short | Assessing the importance of predictors of adherence to a digital self‑management intervention for osteoarthritis |
title_sort | assessing the importance of predictors of adherence to a digital self‑management intervention for osteoarthritis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9926753/ https://www.ncbi.nlm.nih.gov/pubmed/36782324 http://dx.doi.org/10.1186/s13018-023-03562-6 |
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