Browsing by Author "Şimşek, Yasemin"

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    Multipl Sklerozlu Bireylerde Yorgunluk Belirleyicilerinin Tanımlanması
    (2026) Özdoğar, Asiye Tuba; Alizada, Said; Şimşek, Yasemin; Ozakbas, Serkan; Yeşiloğlu, Pervin
    Objective: This study aimed to define the predictors of fatigue in people with multiple sclerosis (MS, pwMS) by evaluating clinical and demographic factors, including disability level, physical performance, sleepiness, and depression. Material and Methods: A total of 747 pwMS were included in this cross-sectional study. Fatigue was assessed using the Modified Fatigue Impact Scale (MFIS), and multiple linear regression analyses were performed to determine the predictors of fatigue based on total MFIS and its subdomains (physical, cognitive, psychosocial). Independent variables included age, disease duration, number of relapses, number of disease- modifying therapies (DMTs), Expanded Disability Status Scale (EDSS) score, Timed 25-Foot Walk (T25FW), Nine-Hole Peg Test (N-HPT), Epworth Sleepiness Scale (ESS), and Beck Depression Inventory (BDI). Results: Higher fatigue scores were significantly associated with increased EDSS scores (β=0.191, p<0.001), greater sleepiness (ESS, β=0.188, p<0.001), and higher depression scores (BDI, β=0.556, p<0.001). Slower walking performance (T25FW) was also a significant but weaker predictor (β=-0.09, p=0.02). Similar patterns were observed across MFIS subdomains. Number of DMTs, disease duration, number of relapses, and N-HPT performance were not significant predictors. Conclusion: Disability level, sleepiness, and depression were the most prominent predictors of fatigue in pwMS. These findings emphasize the importance of integrating physical, psychological, and sleep-related assessments into comprehensive fatigue management strategies for pwMS.