Clinical, Cognitive and Demographic Determinants of Work Participation in Multiple Sclerosis: A Multicenter Cross-Sectional Study

TL;DR

This study finds that faster information processing and the absence of urinary symptoms are linked to being employed in people with multiple sclerosis.

Contribution

The study identifies information processing speed and lower urinary tract symptoms as novel predictors of employment in multiple sclerosis.

Findings

Higher information processing speed is associated with higher odds of employment in people with multiple sclerosis.

The presence of lower urinary tract symptoms is linked to lower odds of employment in people with multiple sclerosis.

Abstract

Background and Objectives: Employment is a major determinant of quality of life in people with multiple sclerosis (pwMS). This multicenter cross-sectional study aimed to identify which commonly studied demographic, disease-related, clinical, cognitive, and psychological variables, alongside the presence of lower urinary tract symptoms (LUTS), predict employment status in pwMS. Materials and Methods: Seventy-eight pwMS were classified as either full-time employed (n = 41) or non-employed (n = 37). Participants underwent clinical and neuropsychological assessment including disability status (Expanded Disability Status Scale; EDSS), fatigue (Modified Fatigue Impact Scale; MFIS), information processing speed (Symbol Digit Modalities Test; SDMT), depressive symptoms (Hospital Anxiety and Depression Scale-Depression; HADS-D), and LUTS status (presence/absence), alongside demographic and disease-related variables (sex, age, education level, relationship status, and disease duration). Results: Hierarchical binary logistic regression indicated that higher information processing speed was associated with higher odds of employment (OR = 1.11, p = 0.008), whereas the presence of LUTS was associated with lower odds of employment (OR = 0.13, p = 0.026). Disability severity, fatigue, depressive symptoms, demographic characteristics, and disease duration did not contribute in the final model (p > 0.05). Conclusions: Information processing speed and urinary dysfunction were associated with employment status in pwMS. Within the present sample, the multivariable model including these variables showed good discrimination between employed and non-employed participants. The findings should be interpreted as exploratory, and they require further confirmation in independent cohorts before any potential application is considered.