Work Difficulties in People with Multiple Sclerosis

• Published in: Journal of occupational rehabilitation Vol. 34; no. 3; pp. 606 - 617
• Main Authors: Ponzio, Michela, Podda, Jessica, Pignattelli, Elena, Verri, Anna, Persechino, Benedetta, Vitturi, Bruno Kusznir, Bandiera, Paolo, Manacorda, Tommaso, Inglese, Matilde, Durando, Paolo, Battaglia, Mario Alberto
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.09.2024; Springer; Springer Nature B.V
• Subjects: Adolescent; Adult; Aged; Clinical Psychology; Comorbidity; Cross-Sectional Studies; Employment; Employment - statistics & numerical data; Environmental Health; Fatigue; Fatigue - epidemiology; Fatigue - psychology; Female; Health Psychology; Humans; Italy - epidemiology; Male; Medicine; Medicine & Public Health; Mental health; Middle Aged; Mood Disorders - epidemiology; Mood Disorders - psychology; Multiple sclerosis; Multiple Sclerosis - complications; Multiple Sclerosis - epidemiology; Multiple Sclerosis - psychology; Occupational Medicine/Industrial Medicine; Orthopedics; Quality of Life; Regression analysis; Regression models; Rehabilitation; Risk Factors; Subgroups; Unemployment; Unemployment - statistics & numerical data; Vocational rehabilitation; Workplace - psychology; Young Adult; Italy; Disability; Multiple sclerosis; Employment; Work difficulties
• ISSN: 1053-0487; 1573-3688; 1573-3688
• DOI: 10.1007/s10926-023-10149-9

Purpose This study identifies potential predictors of unemployment and describes specific work difficulties and their determinants in a subgroup of employed people with multiple sclerosis (PwMS). The specific work difficulties were evaluated using a validated tool that measures the impact of respondents’ symptoms and of workplace features. Methods A cross-sectional study was carried out in Italy during 2021–2022. The subjects included were adults (18–65 years) with a diagnosis of MS, currently employed or unemployed. Logistic regression models were used to determine the association between each potential determinant and employment status, while linear regression models were used to determine the association between determinants and specific work difficulties. Results The main risk factors associated with a higher risk of being unemployed were being older, living in the South of Italy/islands, and having a higher disability level, while protective factors against unemployment were having a high level of education and ‘stable’ employment (an open-ended contract). Fatigue was found to be associated with all work difficulties analyzed; mood disorders emerged as the main predictors of mental health-related work difficulties; level of disability and comorbidity significantly impacted physical health-related ones, and a good quality of life was found to improve both workplace-related and mental health-related difficulties at work. Conclusion Identifying the most significant difficulties is a crucial step in the development of vocational rehabilitation interventions tailored to maximize the ability of PwMS to handle their job-related duties and demands.