The Role of Information Processing Speed in Clinical and Social Support Variables of Patients with Multiple Sclerosis.
10.3988/jcn.2018.14.4.472
- Author:
María Bárbara EIZAGUIRRE
1
;
Sandra VANOTTI
;
Angeles MERINO
;
Cecilia YASTREMIZ
;
Berenice SILVA
;
Ricardo ALONSO
;
Orlando GARCEA
Author Information
1. Multiple Sclerosis Clinic and University of Buenos Aires Neurology Center, Ramos Mejía Hospital, Buenos Aires, Argentina. mbeizaguirre@gmail.com
- Publication Type:Original Article
- Keywords:
multiple sclerosis;
cognition;
social support
- MeSH:
Automatic Data Processing*;
Cognition;
Depression;
Fatigue;
Female;
Humans;
Male;
Multiple Sclerosis*
- From:Journal of Clinical Neurology
2018;14(4):472-477
- CountryRepublic of Korea
- Language:English
-
Abstract:
BACKGROUND AND PURPOSE: 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. METHODS: 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). RESULTS: 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). CONCLUSIONS: 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.
