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Multipl Sklerozlu Bireylerde Yorgunluk Belirleyicilerinin Tanımlanması

Yıl 2026, Cilt: 11 Sayı: 1, 7 - 12, 28.01.2026
https://doi.org/10.61399/ikcusbfd.1634191

Öz

Amaç: Bu çalışma, multipl sklerozlu (MS) bireylerde yorgunluğun belirleyicilerini; engellilik düzeyi, fiziksel performans, uykululuk ve depresyon gibi klinik ve demografik faktörleri değerlendirerek tanımlamayı amaçlamaktadır.
Gereç ve Yöntem: Bu kesitsel çalışmaya toplam 747 pwMS dahil edilmiştir. Yorgunluk, Modifiye Yorgunluk Etki Ölçeği (MYEÖ) kullanılarak değerlendirilmiştir. Yorgunluğun belirleyicilerini tanımlamak amacıyla toplam MYEÖ skoru ve alt boyutları (fiziksel, bilişsel, psiko-sosyal) temel alınarak çoklu doğrusal regresyon analizleri yapılmıştır. Bağımsız değişkenler; yaş, hastalık süresi, atak sayısı, hastalık modifiye edici tedavi (DMT) sayısı, Genişletilmiş Engellilik Durum Ölçeği (EDSS) skoru, Zamanlı 25 Adım Yürüme Testi (Z25AYT), Dokuz Delikli Peg Testi (DDPT), Epworth Uykululuk Ölçeği (EUÖ) ve Beck Depresyon Envanteri (BDE) idi.
Bulgular: Daha yüksek EDSS skoru (β=0,191, p<0,001), daha fazla uykululuk seviyesi (ESS, β=0,188, p<0,001) ve daha yüksek depresyon skorları (BDI, β=0,556, p<0,001) ile yüksek yorgunluk skorlarının anlamlı şekilde ilişkili olduğu bulundu. Daha yavaş yürüme performansı (Z25AYT) da anlamlı ancak daha zayıf bir yordayıcı olarak bulundu (β=-0,09, p=0,02). Benzer sonuçlar MYEÖ alt boyutlarında da gözlemlendi. DMT sayısı, hastalık süresi, atak sayısı ve DDPT performansı anlamlı yordayıcılar değildi.
Sonuç: Engellilik düzeyi, uykululuk ve depresyon, MS’li bireylerde yorgunluğun en belirgin yordayıcıları olarak öne çıkmıştır. Bu bulgular, yorgunluk yönetim stratejilerinde fiziksel, psikolojik ve uyku ile ilişkili değerlendirmelerin bütüncül şekilde ele alınmasının önemini vurgulamaktadır.

Kaynakça

  • 1. Frischer JM, Weigand SD, Guo Y, Kale N, Parisi JE, Pirko I, Mandrekar J, Bramow S, Metz I, Brück W, et al. Clinical and pathological insights into the dynamic nature of the white matter multiple sclerosis plaque. Ann Neurol. 2015;78:710–21. DOI: 10.1002/ana.24497.
  • 2. Chitnis T, Glanz B, Jaffin S, Healy B. Demographics of pediatric-onset multiple sclerosis in an MS center population from the Northeastern United States. Multiple Sclerosis Journal. 2009;15:627–31. DOI: 10.1177/1352458508101933.
  • 3. Milo R, Kahana E. Multiple sclerosis: Geoepidemiology, genetics and the environment. Autoimmun Rev. 2010;9:A387–94. DOI: 10.1016/j.autrev.2009.11.010.
  • 4. von Bismarck O, Dankowski T, Ambrosius B, Hessler N, Antony G, Ziegler A, Hoshi M-M, Aly L, Luessi F, Groppa S, et al. Treatment choices and neuropsychological symptoms of a large cohort of early MS. Neurol Neuroimmunol Neuroinflamm. 2018;5. DOI: 10.1212/NXI.0000000000000446.
  • 5. Oh J, Vidal-Jordana A, Montalban X. Multiple sclerosis: clinical aspects. Curr Opin Neurol. 2018;31:752-9. DOI: 10.1097/WCO.0000000000000622.
  • 6. Freal JE, Kraft GH, Coryell JK. Symptomatic fatigue in multiple sclerosis. Arch Phys Med Rehabil. 1984;65:135–8.
  • 7. Fisk JD, Pontefract A, Ritvo PG, Archibald CJ, Murray TJ. The impact of fatigue on patients with multiple sclerosis. Can J Neurol Sci. 1994;21:9–14.
  • 8. Doesburg D, Vennegoor A, Uitdehaag BMJ, van Oosten BW. High work absence around time of diagnosis of multiple sclerosis is associated with fatigue and relapse rate. Mult Scler Relat Disord. 2019;31:32–7. DOI: 10.1016/j.msard.2019.03.011.
  • 9. Göksel Karatepe A, Kaya T, Günaydn R, Demirhan A, Çe P, Gedizlioğlu M. Quality of life in patients with multiple sclerosis. International Journal of Rehabilitation Research. 2011;34:290–8. DOI: 10.1097/MRR.0b013e32834ad479.
  • 10. Oliva Ramirez A, Keenan A, Kalau O, Worthington E, Cohen L, Singh S. Prevalence and burden of multiple sclerosis-related fatigue: a systematic literature review. BMC Neurol. 2021;21:468. DOI: 10.1186/s12883-021-02396-1.
  • 11. Vucic S, Burke D, Kiernan MC. Fatigue in multiple sclerosis: Mechanisms and management. Clinical Neurophysiology. 2010;121:809–17. DOI: 10.1016/j.clinph.2009.12.013.
  • 12. Kaya Aygunoglu S, Celebi A, Vardar N, Gursoy E. Correlation of Fatigue with Depression, Disability Level and Quality of Life in Patients with Multiple Sclerosis. Noro Psikiyatr Ars. 2015;52:247–51. DOI: 10.5152/npa.2015.8714.
  • 13. Thelen JM, Lynch SG, Bruce AS, Hancock LM, Bruce JM. Polypharmacy in multiple sclerosis: Relationship with fatigue, perceived cognition, and objective cognitive performance. J Psychosom Res. 2014;76:400–4. DOI: 10.1016/j.jpsychores.2014.02.013.
  • 14. Łabuz-Roszak B, Kubicka-Bączyk K, Pierzchała K, Machowska-Majchrzak A, Skrzypek M. Fatigue and its association with sleep disorders, depressive symptoms and anxiety in patients with multiple sclerosis. Neurol Neurochir Pol. 2012;46:309–17. DOI: 10.5114/ninp.2012.30261.
  • 15. Alvarenga-Filho H, Papais-Alvarenga RM, Carvalho SR, Clemente HN, Vasconcelos CC, Dias RM. Does fatigue occur in MS patients without disability? International Journal of Neuroscience. 2015;125:107–15. DOI: 10.3109/00207454.2014.909415.
  • 16. Cortés-Pérez I, Sánchez-Alcalá M, Nieto-Escámez FA, Castellote-Caballero Y, Obrero-Gaitán E, Osuna-Pérez MC. Virtual Reality-Based Therapy Improves Fatigue, Impact, and Quality of Life in Patients with Multiple Sclerosis. A Systematic Review with a Meta-Analysis. Sensors. 2021;21:7389. DOI: 10.3390/s21217389.
  • 17. Torres-Costoso A, Martínez-Vizcaíno V, Reina-Gutiérrez S, Álvarez-Bueno C, Guzmán-Pavón MJ, Pozuelo-Carrascosa DP, Fernández-Rodríguez R, Sanchez-López M, Cavero-Redondo I. Effect of Exercise on Fatigue in Multiple Sclerosis: A Network Meta-analysis Comparing Different Types of Exercise. Arch Phys Med Rehabil. 2022;103:970-87.e18. DOI: 10.1016/j.apmr.2021.08.008.
  • 18. Thompson AJ, Banwell BL, Barkhof F, Carroll WM, Coetzee T, Comi G, Correale J, Fazekas F, Filippi M, Freedman MS, et al. Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria. Lancet Neurol [Internet]. 2018;17:162–73. DOI: 10.1016/S1474-4422(17)30470-2.
  • 19. Kurtzke JF. Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology. 1983;33:1444–52. DOI: 10.1212/wnl.33.11.1444.
  • 20. Johns MW. A new method for measuring daytime sleepiness: the Epworth sleepiness scale. Sleep. 1991;14:540–5. DOI: 10.1093/sleep/14.6.540.
  • 21. Izci B, Ardic S, Firat H, Sahin A, Altinors M, Karacan I. Reliability and validity studies of the Turkish version of the Epworth Sleepiness Scale. Sleep and Breathing. 2008;12:161–8. DOI: 10.1007/s11325-007-0145-7.
  • 22. Armutlu K, Keser I, Korkmaz N, Akbiyik DI, Sümbüloğlu V, Güney Z, Karabudak R. Psychometric study of Turkish version of Fatigue Impact Scale in multiple sclerosis patients. J Neurol Sci. 2007;255:64–8. DOI: 10.1016/j.jns.2007.01.073.
  • 23. BECK AT. An Inventory for Measuring Depression. Arch Gen Psychiatry. 1961;4:561. DOI: 10.1001/archpsyc.1961.01710120031004.
  • 24. Hisli Sahin N. Use of the Beck Depression Inventory with Turkish University Students: Reliability, validity and Factor Analysis [Internet]. Available from: https://www.researchgate.net/publication/233791614.
  • 25. Skjerbæk AG, Hvid LG, Boesen F, Taul-Madsen L, Stenager E, Dalgas U. Psychometric measurement properties and reference values of the six-spot step test, the six-minute walk test, the 25-foot walk test, and the 12-item multiple sclerosis walking scale in people with multiple sclerosis. Mult Scler Relat Disord. 2025;94:106242. DOI: 10.1016/j.msard.2024.106242.
  • 26. Feys P, Lamers I, Francis G, Benedict R, Phillips G, LaRocca N, Hudson LD, Rudick R. The Nine-Hole Peg Test as a manual dexterity performance measure for multiple sclerosis. Multiple Sclerosis Journal. 2017;23:711–20. DOI: 10.1177/1352458517690824.
  • 27. Induruwa I, Constantinescu CS, Gran B. Fatigue in multiple sclerosis — A brief review. J Neurol Sci. 2012;323:9–15. DOI: 10.1016/j.jns.2012.08.007.
  • 28. Chalah MA, Riachi N, Ahdab R, Créange A, Lefaucheur J-P, Ayache SS. Fatigue in Multiple Sclerosis: Neural Correlates and the Role of Non-Invasive Brain Stimulation. Front Cell Neurosci. 2015;9. DOI: 10.3389/fncel.2015.00460.
  • 29. Strober LB. Fatigue in Multiple Sclerosis: A Look at the Role of Poor Sleep. Front Neurol. 2015;6. DOI: 10.3389/fneur.2015.00021.
  • 30. Heine M, van de Port I, Rietberg MB, van Wegen EE, Kwakkel G. Exercise therapy for fatigue in multiple sclerosis. Cochrane Database of Systematic Reviews. 2015;2015. DOI: 10.1002/14651858.CD009956.

Defining the Predictors of Fatigue in People with Multiple Sclerosis

Yıl 2026, Cilt: 11 Sayı: 1, 7 - 12, 28.01.2026
https://doi.org/10.61399/ikcusbfd.1634191

Öz

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.

Kaynakça

  • 1. Frischer JM, Weigand SD, Guo Y, Kale N, Parisi JE, Pirko I, Mandrekar J, Bramow S, Metz I, Brück W, et al. Clinical and pathological insights into the dynamic nature of the white matter multiple sclerosis plaque. Ann Neurol. 2015;78:710–21. DOI: 10.1002/ana.24497.
  • 2. Chitnis T, Glanz B, Jaffin S, Healy B. Demographics of pediatric-onset multiple sclerosis in an MS center population from the Northeastern United States. Multiple Sclerosis Journal. 2009;15:627–31. DOI: 10.1177/1352458508101933.
  • 3. Milo R, Kahana E. Multiple sclerosis: Geoepidemiology, genetics and the environment. Autoimmun Rev. 2010;9:A387–94. DOI: 10.1016/j.autrev.2009.11.010.
  • 4. von Bismarck O, Dankowski T, Ambrosius B, Hessler N, Antony G, Ziegler A, Hoshi M-M, Aly L, Luessi F, Groppa S, et al. Treatment choices and neuropsychological symptoms of a large cohort of early MS. Neurol Neuroimmunol Neuroinflamm. 2018;5. DOI: 10.1212/NXI.0000000000000446.
  • 5. Oh J, Vidal-Jordana A, Montalban X. Multiple sclerosis: clinical aspects. Curr Opin Neurol. 2018;31:752-9. DOI: 10.1097/WCO.0000000000000622.
  • 6. Freal JE, Kraft GH, Coryell JK. Symptomatic fatigue in multiple sclerosis. Arch Phys Med Rehabil. 1984;65:135–8.
  • 7. Fisk JD, Pontefract A, Ritvo PG, Archibald CJ, Murray TJ. The impact of fatigue on patients with multiple sclerosis. Can J Neurol Sci. 1994;21:9–14.
  • 8. Doesburg D, Vennegoor A, Uitdehaag BMJ, van Oosten BW. High work absence around time of diagnosis of multiple sclerosis is associated with fatigue and relapse rate. Mult Scler Relat Disord. 2019;31:32–7. DOI: 10.1016/j.msard.2019.03.011.
  • 9. Göksel Karatepe A, Kaya T, Günaydn R, Demirhan A, Çe P, Gedizlioğlu M. Quality of life in patients with multiple sclerosis. International Journal of Rehabilitation Research. 2011;34:290–8. DOI: 10.1097/MRR.0b013e32834ad479.
  • 10. Oliva Ramirez A, Keenan A, Kalau O, Worthington E, Cohen L, Singh S. Prevalence and burden of multiple sclerosis-related fatigue: a systematic literature review. BMC Neurol. 2021;21:468. DOI: 10.1186/s12883-021-02396-1.
  • 11. Vucic S, Burke D, Kiernan MC. Fatigue in multiple sclerosis: Mechanisms and management. Clinical Neurophysiology. 2010;121:809–17. DOI: 10.1016/j.clinph.2009.12.013.
  • 12. Kaya Aygunoglu S, Celebi A, Vardar N, Gursoy E. Correlation of Fatigue with Depression, Disability Level and Quality of Life in Patients with Multiple Sclerosis. Noro Psikiyatr Ars. 2015;52:247–51. DOI: 10.5152/npa.2015.8714.
  • 13. Thelen JM, Lynch SG, Bruce AS, Hancock LM, Bruce JM. Polypharmacy in multiple sclerosis: Relationship with fatigue, perceived cognition, and objective cognitive performance. J Psychosom Res. 2014;76:400–4. DOI: 10.1016/j.jpsychores.2014.02.013.
  • 14. Łabuz-Roszak B, Kubicka-Bączyk K, Pierzchała K, Machowska-Majchrzak A, Skrzypek M. Fatigue and its association with sleep disorders, depressive symptoms and anxiety in patients with multiple sclerosis. Neurol Neurochir Pol. 2012;46:309–17. DOI: 10.5114/ninp.2012.30261.
  • 15. Alvarenga-Filho H, Papais-Alvarenga RM, Carvalho SR, Clemente HN, Vasconcelos CC, Dias RM. Does fatigue occur in MS patients without disability? International Journal of Neuroscience. 2015;125:107–15. DOI: 10.3109/00207454.2014.909415.
  • 16. Cortés-Pérez I, Sánchez-Alcalá M, Nieto-Escámez FA, Castellote-Caballero Y, Obrero-Gaitán E, Osuna-Pérez MC. Virtual Reality-Based Therapy Improves Fatigue, Impact, and Quality of Life in Patients with Multiple Sclerosis. A Systematic Review with a Meta-Analysis. Sensors. 2021;21:7389. DOI: 10.3390/s21217389.
  • 17. Torres-Costoso A, Martínez-Vizcaíno V, Reina-Gutiérrez S, Álvarez-Bueno C, Guzmán-Pavón MJ, Pozuelo-Carrascosa DP, Fernández-Rodríguez R, Sanchez-López M, Cavero-Redondo I. Effect of Exercise on Fatigue in Multiple Sclerosis: A Network Meta-analysis Comparing Different Types of Exercise. Arch Phys Med Rehabil. 2022;103:970-87.e18. DOI: 10.1016/j.apmr.2021.08.008.
  • 18. Thompson AJ, Banwell BL, Barkhof F, Carroll WM, Coetzee T, Comi G, Correale J, Fazekas F, Filippi M, Freedman MS, et al. Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria. Lancet Neurol [Internet]. 2018;17:162–73. DOI: 10.1016/S1474-4422(17)30470-2.
  • 19. Kurtzke JF. Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology. 1983;33:1444–52. DOI: 10.1212/wnl.33.11.1444.
  • 20. Johns MW. A new method for measuring daytime sleepiness: the Epworth sleepiness scale. Sleep. 1991;14:540–5. DOI: 10.1093/sleep/14.6.540.
  • 21. Izci B, Ardic S, Firat H, Sahin A, Altinors M, Karacan I. Reliability and validity studies of the Turkish version of the Epworth Sleepiness Scale. Sleep and Breathing. 2008;12:161–8. DOI: 10.1007/s11325-007-0145-7.
  • 22. Armutlu K, Keser I, Korkmaz N, Akbiyik DI, Sümbüloğlu V, Güney Z, Karabudak R. Psychometric study of Turkish version of Fatigue Impact Scale in multiple sclerosis patients. J Neurol Sci. 2007;255:64–8. DOI: 10.1016/j.jns.2007.01.073.
  • 23. BECK AT. An Inventory for Measuring Depression. Arch Gen Psychiatry. 1961;4:561. DOI: 10.1001/archpsyc.1961.01710120031004.
  • 24. Hisli Sahin N. Use of the Beck Depression Inventory with Turkish University Students: Reliability, validity and Factor Analysis [Internet]. Available from: https://www.researchgate.net/publication/233791614.
  • 25. Skjerbæk AG, Hvid LG, Boesen F, Taul-Madsen L, Stenager E, Dalgas U. Psychometric measurement properties and reference values of the six-spot step test, the six-minute walk test, the 25-foot walk test, and the 12-item multiple sclerosis walking scale in people with multiple sclerosis. Mult Scler Relat Disord. 2025;94:106242. DOI: 10.1016/j.msard.2024.106242.
  • 26. Feys P, Lamers I, Francis G, Benedict R, Phillips G, LaRocca N, Hudson LD, Rudick R. The Nine-Hole Peg Test as a manual dexterity performance measure for multiple sclerosis. Multiple Sclerosis Journal. 2017;23:711–20. DOI: 10.1177/1352458517690824.
  • 27. Induruwa I, Constantinescu CS, Gran B. Fatigue in multiple sclerosis — A brief review. J Neurol Sci. 2012;323:9–15. DOI: 10.1016/j.jns.2012.08.007.
  • 28. Chalah MA, Riachi N, Ahdab R, Créange A, Lefaucheur J-P, Ayache SS. Fatigue in Multiple Sclerosis: Neural Correlates and the Role of Non-Invasive Brain Stimulation. Front Cell Neurosci. 2015;9. DOI: 10.3389/fncel.2015.00460.
  • 29. Strober LB. Fatigue in Multiple Sclerosis: A Look at the Role of Poor Sleep. Front Neurol. 2015;6. DOI: 10.3389/fneur.2015.00021.
  • 30. Heine M, van de Port I, Rietberg MB, van Wegen EE, Kwakkel G. Exercise therapy for fatigue in multiple sclerosis. Cochrane Database of Systematic Reviews. 2015;2015. DOI: 10.1002/14651858.CD009956.
Toplam 30 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Fizyoterapi
Bölüm Araştırma Makalesi
Yazarlar

Asiye Tuba Özdoğar 0000-0003-0043-9374

Said Alizada 0009-0004-7126-1475

Pervin Yeşiloğlu 0009-0005-1409-4719

Yasemin Şimşek 0000-0003-3714-1993

Serkan Ozakbas 0000-0003-2140-4103

Gönderilme Tarihi 6 Şubat 2025
Kabul Tarihi 9 Mayıs 2025
Yayımlanma Tarihi 28 Ocak 2026
Yayımlandığı Sayı Yıl 2026 Cilt: 11 Sayı: 1

Kaynak Göster

APA Özdoğar, A. T., Alizada, S., Yeşiloğlu, P., … Şimşek, Y. (2026). Defining the Predictors of Fatigue in People with Multiple Sclerosis. İzmir Katip Çelebi Üniversitesi Sağlık Bilimleri Fakültesi Dergisi, 11(1), 7-12. https://doi.org/10.61399/ikcusbfd.1634191
AMA Özdoğar AT, Alizada S, Yeşiloğlu P, Şimşek Y, Ozakbas S. Defining the Predictors of Fatigue in People with Multiple Sclerosis. İKÇÜSBFD. Ocak 2026;11(1):7-12. doi:10.61399/ikcusbfd.1634191
Chicago Özdoğar, Asiye Tuba, Said Alizada, Pervin Yeşiloğlu, Yasemin Şimşek, ve Serkan Ozakbas. “Defining the Predictors of Fatigue in People with Multiple Sclerosis”. İzmir Katip Çelebi Üniversitesi Sağlık Bilimleri Fakültesi Dergisi 11, sy. 1 (Ocak 2026): 7-12. https://doi.org/10.61399/ikcusbfd.1634191.
EndNote Özdoğar AT, Alizada S, Yeşiloğlu P, Şimşek Y, Ozakbas S (01 Ocak 2026) Defining the Predictors of Fatigue in People with Multiple Sclerosis. İzmir Katip Çelebi Üniversitesi Sağlık Bilimleri Fakültesi Dergisi 11 1 7–12.
IEEE A. T. Özdoğar, S. Alizada, P. Yeşiloğlu, Y. Şimşek, ve S. Ozakbas, “Defining the Predictors of Fatigue in People with Multiple Sclerosis”, İKÇÜSBFD, c. 11, sy. 1, ss. 7–12, 2026, doi: 10.61399/ikcusbfd.1634191.
ISNAD Özdoğar, Asiye Tuba vd. “Defining the Predictors of Fatigue in People with Multiple Sclerosis”. İzmir Katip Çelebi Üniversitesi Sağlık Bilimleri Fakültesi Dergisi 11/1 (Ocak2026), 7-12. https://doi.org/10.61399/ikcusbfd.1634191.
JAMA Özdoğar AT, Alizada S, Yeşiloğlu P, Şimşek Y, Ozakbas S. Defining the Predictors of Fatigue in People with Multiple Sclerosis. İKÇÜSBFD. 2026;11:7–12.
MLA Özdoğar, Asiye Tuba vd. “Defining the Predictors of Fatigue in People with Multiple Sclerosis”. İzmir Katip Çelebi Üniversitesi Sağlık Bilimleri Fakültesi Dergisi, c. 11, sy. 1, 2026, ss. 7-12, doi:10.61399/ikcusbfd.1634191.
Vancouver Özdoğar AT, Alizada S, Yeşiloğlu P, Şimşek Y, Ozakbas S. Defining the Predictors of Fatigue in People with Multiple Sclerosis. İKÇÜSBFD. 2026;11(1):7-12.