Outcome measures in muscular dystrophy rehabilitation: an ICF content comparison approach to the most commonly used MD scales
Introduction: Functioning is the reason to be of rehabilitation as it is essential to the lives of people who suffer from a disease. The International Classification of Functioning, Disability and Health (ICF) can help in designing a functioning profile of a patient, identifying needs for rehabilita...
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Main Authors: | , , , , , |
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Format: | Article |
Language: | English |
Published: |
Medical Journals Sweden
2025-01-01
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Series: | Journal of Rehabilitation Medicine |
Subjects: | |
Online Access: | https://medicaljournalssweden.se/jrm/article/view/40327 |
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Summary: | Introduction: Functioning is the reason to be of rehabilitation as it is essential to the lives of people who suffer from a disease. The International Classification of Functioning, Disability and Health (ICF) can help in designing a functioning profile of a patient, identifying needs for rehabilitation plans and measuring the results of an intervention.
Objective: To identify the outcome measurement instruments reported in clinical studies in muscular dystrophies (MDs) and provide an ICF content analysis.
Method: A systematic literature review was conducted until October 2022, using Medline, PubMed, and Scopus databases. Papers assessing outcomes related to functioning in patients with MDs were included.
Results: A total of 116 papers were included and all identified outcome measures were linked to the ICF. Inter-researcher agreement for the linking process was 0.82. The analysed instruments focused mainly on aspects of body functions, followed by activities and participation. General scales were more comprehensive than specific.
Conclusions: The application of ICF in this research enhances the understanding of functioning of patients with MDs and the need to develop more specific but comprehensive scales tailored to the needs of MD patients, and can guide clinicians in a assessing patients through a biopsychosocial perspective.
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ISSN: | 1651-2081 |