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Digital self-management of hip and knee osteoarthritis and trajectories of work and activity impairments

Kiadaliri, Ali LU orcid ; Lohmander, L Stefan LU orcid ; Ignjatovic, Majda Misini LU ; Nero, Håkan LU and Dahlberg, Leif E LU (2023) In BMC Musculoskeletal Disorders 24. p.1-11
Abstract

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... (More)

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.

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Please use this url to cite or link to this publication:
author
; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
BMC Musculoskeletal Disorders
volume
24
article number
207
pages
1 - 11
publisher
BioMed Central (BMC)
external identifiers
  • pmid:36934223
  • scopus:85150423609
ISSN
1471-2474
DOI
10.1186/s12891-023-06322-z
project
Digital education and physical therapy for people with musculoskeletal pain
language
English
LU publication?
yes
additional info
© 2023. The Author(s).
id
e9b6caae-8151-4f88-89d3-4d119d194838
date added to LUP
2023-03-19 13:07:47
date last changed
2024-04-19 21:30:04
@article{e9b6caae-8151-4f88-89d3-4d119d194838,
  abstract     = {{<p>OBJECTIVE: To investigate the trajectories of work and activity impairments among people participating in a digital self-management program for osteoarthritis (OA).</p><p>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.</p><p>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.</p><p>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.</p>}},
  author       = {{Kiadaliri, Ali and Lohmander, L Stefan and Ignjatovic, Majda Misini and Nero, Håkan and Dahlberg, Leif E}},
  issn         = {{1471-2474}},
  language     = {{eng}},
  month        = {{03}},
  pages        = {{1--11}},
  publisher    = {{BioMed Central (BMC)}},
  series       = {{BMC Musculoskeletal Disorders}},
  title        = {{Digital self-management of hip and knee osteoarthritis and trajectories of work and activity impairments}},
  url          = {{http://dx.doi.org/10.1186/s12891-023-06322-z}},
  doi          = {{10.1186/s12891-023-06322-z}},
  volume       = {{24}},
  year         = {{2023}},
}