Background: Individuals with multiple sclerosis (MS) experience a clinical course that is highly variable with daily fluctuations in symptoms significantly affecting functional ability and quality of life. Yet, understanding how MS symptoms co-vary and associate with physical and psychological health is unclear.
Objective: The purpose of the study was to explore variability patterns and time-bound relationships across symptoms, affect, and physical activity in individuals with MS.
Methods: The study employed a multivariate, replicated, single-subject repeated-measures (MRSRM) design and involved four individuals with MS. Mood, fatigue, pain, balance confidence, and losses of balance were measured daily over 28 days by self-report. Physical activity was also measured daily over this same time period via accelerometry. Dynamic factor analysis (DFA) was used to determine the dimensionality and lagged relationships across the variables.
Results: Person-specific models revealed considerable time-dependent co-variation patterns as well as pattern variation across subjects. Results also offered insight into distinct variability structures at varying levels of disability.
Conclusion: Modeling person-level variability may be beneficial for addressing the heterogeneity of experiences in individuals with MS and for understanding temporal and dynamic interrelationships among perceived symptoms, affect, and health outcomes in this group.
Keywords: Modeling; Mood; Multiple sclerosis; Symptoms; Variability.
Copyright © 2016 Elsevier Inc. All rights reserved.