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Digital self-management of hip and knee osteoarthritis and trajectories of work and activity impairments
OBJECTIVE: To investigate the trajectories of work and activity impairments among people participating in a digital self-management program for osteoarthritis (OA). METHODS: We conducted an observational longitudinal study using data for baseline, 3, 6, 9 and 12 months follow ups from people partici...
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/PMC10024026/ https://www.ncbi.nlm.nih.gov/pubmed/36934223 http://dx.doi.org/10.1186/s12891-023-06322-z |
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author | Kiadaliri, Ali Lohmander, L. Stefan Ignjatovic, Majda Misini Nero, Håkan Dahlberg, Leif E. |
author_facet | Kiadaliri, Ali Lohmander, L. Stefan Ignjatovic, Majda Misini Nero, Håkan Dahlberg, Leif E. |
author_sort | Kiadaliri, Ali |
collection | PubMed |
description | OBJECTIVE: To investigate the trajectories of work and activity impairments among people participating in a digital self-management program for osteoarthritis (OA). METHODS: We conducted an observational longitudinal study using data for baseline, 3, 6, 9 and 12 months follow ups from people participating in a digital OA treatment between June 2018 and September 2021. The Work Productivity and Activity Impairment–Osteoarthritis (WPAI–OA) questionnaire was used to measure work and activity impairments. We applied linear mixed models and group-based trajectory modelling (GBTM) to assess the trajectories of work and activity impairments and their variability. Dominance analysis was performed to explore the relative importance of baseline characteristics in predicting the trajectory subgroup membership. RESULTS: A total of 14,676 participants with mean (± standard deviation) age 64.0 (± 9.1) years and 75.5% females were included. The adjusted mean improvements in work impairment from baseline were 5.8% (95% CI 5.3, 6.4) to 6.1% (95% CI 5.5, 6.8). The corresponding figures for activity impairment were 9.4% (95% CI 9.0, 9.7) to 11.3% (95% CI 10.8, 11.8). GBTM identified five (low baseline–declining, moderate baseline–declining, high baseline–declining, very high baseline–substantially declining, and very high baseline–persistent) and three (low baseline–declining, mild baseline–declining, high baseline–declining) subgroups with distinct trajectories of activity and work impairments. Dominance analysis showed that baseline pain was the most important predictor of membership in trajectory subgroups. CONCLUSION: While participation in a digital self-management program for OA was, on average, associated with improvements in work and activity impairments, there were substantial variations among the participants. Baseline pain may provide useful insights to predict trajectories of work and activity impairments. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12891-023-06322-z. |
format | Online Article Text |
id | pubmed-10024026 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-100240262023-03-19 Digital self-management of hip and knee osteoarthritis and trajectories of work and activity impairments Kiadaliri, Ali Lohmander, L. Stefan Ignjatovic, Majda Misini Nero, Håkan Dahlberg, Leif E. BMC Musculoskelet Disord Research OBJECTIVE: To investigate the trajectories of work and activity impairments among people participating in a digital self-management program for osteoarthritis (OA). METHODS: We conducted an observational longitudinal study using data for baseline, 3, 6, 9 and 12 months follow ups from people participating in a digital OA treatment between June 2018 and September 2021. The Work Productivity and Activity Impairment–Osteoarthritis (WPAI–OA) questionnaire was used to measure work and activity impairments. We applied linear mixed models and group-based trajectory modelling (GBTM) to assess the trajectories of work and activity impairments and their variability. Dominance analysis was performed to explore the relative importance of baseline characteristics in predicting the trajectory subgroup membership. RESULTS: A total of 14,676 participants with mean (± standard deviation) age 64.0 (± 9.1) years and 75.5% females were included. The adjusted mean improvements in work impairment from baseline were 5.8% (95% CI 5.3, 6.4) to 6.1% (95% CI 5.5, 6.8). The corresponding figures for activity impairment were 9.4% (95% CI 9.0, 9.7) to 11.3% (95% CI 10.8, 11.8). GBTM identified five (low baseline–declining, moderate baseline–declining, high baseline–declining, very high baseline–substantially declining, and very high baseline–persistent) and three (low baseline–declining, mild baseline–declining, high baseline–declining) subgroups with distinct trajectories of activity and work impairments. Dominance analysis showed that baseline pain was the most important predictor of membership in trajectory subgroups. CONCLUSION: While participation in a digital self-management program for OA was, on average, associated with improvements in work and activity impairments, there were substantial variations among the participants. Baseline pain may provide useful insights to predict trajectories of work and activity impairments. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12891-023-06322-z. BioMed Central 2023-03-18 /pmc/articles/PMC10024026/ /pubmed/36934223 http://dx.doi.org/10.1186/s12891-023-06322-z 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 Kiadaliri, Ali Lohmander, L. Stefan Ignjatovic, Majda Misini Nero, Håkan Dahlberg, Leif E. Digital self-management of hip and knee osteoarthritis and trajectories of work and activity impairments |
title | Digital self-management of hip and knee osteoarthritis and trajectories of work and activity impairments |
title_full | Digital self-management of hip and knee osteoarthritis and trajectories of work and activity impairments |
title_fullStr | Digital self-management of hip and knee osteoarthritis and trajectories of work and activity impairments |
title_full_unstemmed | Digital self-management of hip and knee osteoarthritis and trajectories of work and activity impairments |
title_short | Digital self-management of hip and knee osteoarthritis and trajectories of work and activity impairments |
title_sort | digital self-management of hip and knee osteoarthritis and trajectories of work and activity impairments |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10024026/ https://www.ncbi.nlm.nih.gov/pubmed/36934223 http://dx.doi.org/10.1186/s12891-023-06322-z |
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