JOURNAL ARTICLE
Investigation of the Relationship Between Coping With the Disease and Affecting Cognitive, Physical, and Psychosocial Factors in People with Multiple Sclerosis.
Published In: Archives of Clinical Neuropsychology, 2024, v. 39, n. 5. P. 586 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Sagici, Ozge; Ozdogar, Asiye Tuba; Aslan, Taha; Ozakbas, Serkan 3 of 3
Abstract
This article focuses on the relationship between coping mechanisms in people with multiple sclerosis (pwMS) and various cognitive, physical, and psychosocial factors, including socio-demographic characteristics, disability, personality, stigma, quality of life, depression, and anxiety. In a cross-sectional study of 102 pwMS, coping strategies were assessed using the Coping with Multiple Sclerosis Scale (CMSS), and correlations were found between coping styles and measures such as disability level (Expanded Disability Status Scale, EDSS), quality of life (EuroQol-5D), neuropsychological symptoms, stigma, anxiety, and depression. Notably, higher disability and psychological distress were associated with increased use of physical assistance as a coping strategy and decreased acceptance of the disease, while better quality of life and lower stigma correlated with greater acceptance and problem-solving coping. The study highlights that coping strategies in pwMS vary according to disability, mental health status, stigma, and quality of life, suggesting the importance of addressing these factors in therapeutic approaches.
Additional Information
- Source:Archives of Clinical Neuropsychology. 2024/08, Vol. 39, Issue 5, p586
- Document Type:Article
- Subject Area:Health and Medicine
- Publication Date:2024
- ISSN:0887-6177
- DOI:10.1093/arclin/acad102
- Accession Number:178650445
- Copyright Statement:Copyright of Archives of Clinical Neuropsychology is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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