J Clin Neurol.  2018 Oct;14(4):472-477. 10.3988/jcn.2018.14.4.472.

The Role of Information Processing Speed in Clinical and Social Support Variables of Patients with Multiple Sclerosis

  • 1Multiple Sclerosis Clinic and University of Buenos Aires Neurology Center, Ramos Mejía Hospital, Buenos Aires, Argentina. mbeizaguirre@gmail.com


Information processing speed is one of the most impaired cognitive functions in multiple sclerosis (MS). There are two tests widely used for evaluating information processing speed: the Symbol Digit Modalities Test (SDMT) and the Paced Auditory Serial Addition Test (PASAT). To analyze the relationship between processing speed and the clinical and social support variables of patients with MS.
A group of 47 patients with relapsing-remitting MS was studied, 31 were women and 16, men. Age: 39.04±13.17, years of schooling: 13.00±3.87, Expanded Disability Status Scale (EDSS): 2.78±1.81, and disease evolution: 8.07±6.26. Instruments of measure; processing speed: SDMT, PASAT, clinical variables: EDSS, Fatigue Severity Scale (FSS), Beck's Depression Inventory II (BDI-II), and social support: Medical Outcomes Study Social Support Survey (MOS).
Significant correlations were found between information processing speed and psychiatric, motor disability and social support variables. The SDMT correlated significantly and negatively with BDI-II, FSS, EDSS, and MOS (p < 0.05), whereas the PASAT correlated negatively with FSS and positively with MOS (p < 0.05). Information processing speed appeared as the performance predictor of these variables. The SDMT produced significant changes in EDSS (R2=0.343, p=0.000); FSS (R2=0.109, p=0.031); BDI-II (R2=0.124, p=0.018), and MOS (R2=between 0.212 and 0.379, p < 0.05).
Information processing speed has influence on the clinical variables and the social support of patients with MS. These aspects are important to bear in mind for therapeutic approach.


multiple sclerosis; cognition; social support

MeSH Terms

Automatic Data Processing*
Multiple Sclerosis*


1. Chiaravalloti ND, Christodoulou C, Demaree HA, DeLuca J. Differentiating simple versus complex processing speed: influence on new learning and memory performance. J Clin Exp Neuropsychol. 2003; 25:489–501. PMID: 12911103.
2. Cáceres F, Vanotti S, Rao S. RECONEM Workgroup. Epidemiological characteristics of cognitive impairment of multiple sclerosis patients in a Latin American country. J Clin Exp Neuropsychol. 2011; 33:1094–1098. PMID: 21978317.
3. Ruano L, Portaccio E, Goretti B, Niccolai C, Severo M, Patti F, et al. Age and disability drive cognitive impairment in multiple sclerosis across disease subtypes. Mult Scler. 2017; 23:1258–1267. PMID: 27738090.
4. Costa SL, Genova HM, DeLuca J, Chiaravalloti ND. Information processing speed in multiple sclerosis: past, present, and future. Mult Scler. 2017; 23:772–789. PMID: 27207446.
5. Goverover Y, Genova HM, Hillary FG, DeLuca J. The relationship between neuropsychological measures and the Timed Instrumental Activities of Daily Living task in multiple sclerosis. Mult Scler. 2007; 13:636–644. PMID: 17548444.
6. Goth-Owens TL, Martinez-Torteya C, Martel MM, Nigg JT. Processing speed weakness in children and adolescents with non-hyperactive but inattentive ADHD (ADD). Child Neuropsychol. 2010; 16:577–591. PMID: 20560083.
7. Shanahan MA, Pennington BF, Yerys BE, Scott A, Boada R, Willcutt EG, et al. Processing speed deficits in attention deficit/hyperactivity disorder and reading disability. J Abnorm Child Psychol. 2006; 34:585–602. PMID: 16850284.
8. Forn C, Belenguer A, Parcet-Ibars MA, Avila C. Information-processing speed is the primary deficit underlying the poor performance of multiple sclerosis patients in the Paced Auditory Serial Addition Test (PASAT). J Clin Exp Neuropsychol. 2008; 30:789–796. PMID: 18608672.
9. Smith A. Symbol digit modalities test: Manual. Los Angeles: Western Psychological Services;1982.
10. Vanotti S, Cores EV, Eizaguirre B, Angeles M, Rey R, Villa A, et al. Normatization of the symbol digit modalities test-oral version in a Latin American country. Appl Neuropsychol Adult. 2015; 22:46–53. PMID: 25529591.
11. Sampson H. Pacing and performance on a serial addition task. Can J Psychol. 1956; 10:219–225. PMID: 13374613.
12. Gronwall DM. Paced auditory serial-addition task: a measure of recovery from concussion. Percept Mot Skills. 1977; 44:367–373. PMID: 866038.
13. Vanotti S, Eizaguirre MB, Cores EV, Yastremis C, Garcea O, Salgado P, et al. Validation of the PASAT in Argentina. Appl Neuropsychol Adult. 2016; 23:379–383. PMID: 26980661.
14. Rao SM. The Cognitive Function Study Group of the National Multiple Sclerosis Society. A manual for the brief repeatable battery of neuropsychological tests in multiple sclerosis. Milwaukee: Medical College of Wisconsin;1990.
15. Benedict RH, Fischer JS, Archibald CJ, Arnett PA, Beatty WW, Bobholz J, et al. Minimal neuropsychological assessment of MS patients: a consensus approach. Clin Neuropsychol. 2002; 16:381–397. PMID: 12607150.
16. Benedict RH, Amato MP, Boringa J, Brochet B, Foley F, Fredrikson S, et al. Brief International Cognitive Assessment for MS (BICAMS): international standards for validation. BMC Neurol. 2012; 12:55. PMID: 22799620.
17. Vanotti S, Smerbeck A, Benedict RH, Caceres F. A new assessment tool for patients with multiple sclerosis from Spanish speaking countries: validation of the Brief International Cognitive Assessment for MS (BICAMS) in Argentina. Clin Neuropsychol. 2016; 30:1023–1031. PMID: 27668977.
18. Landrø NI, Celius EG, Sletvold H. Depressive symptoms account for deficient information processing speed but not for impaired working memory in early phase multiple sclerosis (MS). J Neurol Sci. 2004; 217:211–216. PMID: 14706226.
19. Diamond BJ, Johnson SK, Kaufman M, Graves L. Relationships between information processing, depression, fatigue and cognition in multiple sclerosis. Arch Clinical Neuropsychol. 2008; 23:189–199. PMID: 18053682.
20. Andreasen AK, Spliid PE, Andersen H, Jakobsen J. Fatigue and processing speed are related in multiple sclerosis. Eur J Neurol. 2010; 17:212–218. PMID: 19796282.
21. Glanz BI, Healy BC, Rintell DJ, Jaffin SK, Bakshi R, Weiner HL. The association between cognitive impairment and quality of life in patients with early multiple sclerosis. J Neurol Sci. 2010; 290:75–79. PMID: 19944429.
22. Dusankova JB, Kalincik T, Havrdova E, Benedict RH. Cross cultural validation of the Minimal Assessment of Cognitive Function in Multiple Sclerosis (MACFIMS) and the Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS). Clin Neuropsychol. 2012; 26:1186–1200. PMID: 23034066.
23. Sundgren M, Maurex L, Wahlin Å, Piehl F, Brismar T. Cognitive impairment has a strong relation to nonsomatic symptoms of depression in relapsing-remitting multiple sclerosis. Arch Clin Neuropsychol. 2013; 28:144–155. PMID: 23291310.
24. Giedraitienė N, Kizlaitienė R, Kaubrys G. The BICAMS battery for assessment of lithuanian-speaking multiple sclerosis patients: relationship with age, education, disease disability, and duration. Med Sci Monit. 2015; 21:3853–3859. PMID: 26655632.
25. Sandi D, Rudisch T, Füvesi J, Fricska-Nagy Z, Huszka H, Biernacki T, et al. The Hungarian validation of the Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS) battery and the correlation of cognitive impairment with fatigue and quality of life. Mult Scler Relat Disord. 2015; 4:499–504. PMID: 26590654.
26. Amato MP, Portaccio E, Goretti B, Zipoli V, Iudice A, Della Pina D, et al. Relevance of cognitive deterioration in early relapsing-remitting MS: a 3 year follow-up study. Mult Scler. 2010; 16:1474–1482. PMID: 20729256.
27. Niino M, Mifune N, Kohriyama T, Mori M, Ohashi T, Kawachi I, et al. Apathy/depression, but not subjective fatigue, is related with cognitive dysfunction in patients with multiple sclerosis. BMC Neurol. 2014; 14:3. PMID: 24393373.
28. Jougleux-Vie C, Duhin E, Deken V, Outteryck O, Vermersch P, Zéphir H. Does fatigue complaint reflect memory impairment in multiple sclerosis? Mult Scler Int. 2014; 2014:692468. PMID: 24724029.
29. Costa DC, Sá MJ, Calheiros JM. The effect of social support on the quality of life of patients with multiple sclerosis. Arq Neuropsiquiatr. 2012; 70:108–113. PMID: 22311214.
30. Costa D, Sá MJ, Calheiros JM. [The effect of social support on the symptoms of depression experienced by Portuguese patients with multiple sclerosis]. Rev Neurol. 2011; 53:457–462. PMID: 21960385.
31. Aghaei N, Karbandi S, Gorji MA, Golkhatmi MB, Alizadeh B. Social support in relation to fatigue symptoms among patients with multiple sclerosis. Indian J Palliat Care. 2016; 22:163–167. PMID: 27162427.
32. Rommer PS, Sühnel A, König N, Zettl UK. Coping with multiple sclerosis-the role of social support. Acta Neurol Scand. 2016; 136:11–16. PMID: 27620927.
33. Barker-Collo SL. Quality of life in multiple sclerosis: does information-processing speed have an independent effect? Arch Clin Neuropsychol. 2006; 21:167–174. PMID: 16242906.
34. Poser CM, Paty DW, Scheinberg L, McDonald WI, Davis FA, Ebers GC, et al. New diagnostic criteria for multiple sclerosis: guidelines for research protocols. Ann Neurol. 1983; 13:227–231. PMID: 6847134.
35. Polman CH, Reingold SC, Banwell B, Clanet M, Cohen JA, Filippi M, et al. Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. Ann Neurol. 2011; 69:292–302. PMID: 21387374.
36. Kurtzke JF. Rating neurological impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology. 1983; 33:1444–1452. PMID: 6685237.
37. Paralyzed Veterans of America. Multiple Sclerosis Council for Clinical Practice Guidelines [Internet]. Buenos Aires: Paralyzed Veterans of America;1998. cited 2017 Dec 10. Available from: http://www.pva.org/media/pdf/fatigue1b772.pdf.
38. Beck AT, Steer RA, Brown GK. Manual for the Beck Depression Inventory-II. San Antonio (TX): Psychological Corporation;1996.
39. Brenlla ME, Rodríguez CM. [Adaptación argentina del Inventario de Depresión de Beck]. In : Beck AT, Steer RA, Brown GK, editors. [BDI-II. Inventario de Depresión de Beck]. 2nd ed. Buenos Aires: Paidós;2006.
40. Sherbourne CD, Stewart AL. The MOS social support survey. Soc Sci Med. 1991; 32:705–714. PMID: 2035047.
41. Rodríguez S, Enrique HC. [Validación Argentina del cuestionario MOS de apoyo social percibido]. Psicodebate. 2007; 7:155–168.
42. Roosendaal SD, Bendfeldt K, Vrenken H, Polman CH, Borgwardt S, Radue EW, et al. Grey matter volume in a large cohort of MS patients: relation to MRI parameters and disability. Mult Scler. 2011; 17:1098–1106. PMID: 21586487.
43. Kamenov K, Cabello M, Caballero FF, Cieza A, Sabariego C, Raggi A, et al. Factors related to social support in neurological and mental disorders. PLoS One. 2016; 11:e0149356. PMID: 26900847.
44. Chiaravalloti ND, Genova HM, DeLuca J. Cognitive rehabilitation in multiple sclerosis: the role of plasticity. Front Neurol. 2015; 6:67. PMID: 25883585.
45. Sandroff BM, Motl RW, Scudder MR, DeLuca J. Systematic, evidence-based review of exercise, physical activity, and physical fitness effects on cognition in persons with multiple sclerosis. Neuropsychol Rev. 2016; 26:271–294. PMID: 27447980.
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