Individuals with mild MS with poor sleep quality have impaired visuospatial memory and lower perceived functional abilities

Accepted Manuscript Individuals with mild MS with poor sleep quality have impaired visuospatial memory and lower perceived functional abilities Catherine F. Siengsukon, PT, PhD, Mayis Aldughmi, PT, PhD, Melike Kahya, PT, Sharon Lynch, MD, Jared Bruce, PhD, Morgan Glusman, MA, Abigail Ness Norouzinia, MA, Sandra Billinger, PT, PhD PII:

S1936-6574(17)30082-1

DOI:

10.1016/j.dhjo.2017.04.011

Reference:

DHJO 610

To appear in:

Disability and Health Journal

Received Date: 26 August 2016 Revised Date:

18 April 2017

Accepted Date: 24 April 2017

Please cite this article as: Siengsukon CF, Aldughmi M, Kahya M, Lynch S, Bruce J, Glusman M, Ness Norouzinia A, Billinger S, Individuals with mild MS with poor sleep quality have impaired visuospatial memory and lower perceived functional abilities, Disability and Health Journal (2017), doi: 10.1016/ j.dhjo.2017.04.011. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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Individuals with mild MS with poor sleep quality have impaired visuospatial memory and lower perceived functional abilities Catherine F Siengsukon, PT, PhDa, Mayis Aldughmi, PT, PhDa, Melike Kahya, PTa, Sharon

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Lynch, MDb, Jared Bruce, PhDc, Morgan Glusman, MAc, Abigail Ness Norouzinia, MAc, Sandra Billinger, PT, PhDa a

Department of Physical Therapy and Rehabilitation Science, University of Kansas Medical

Department of Neurology, University of Kansas Medical Center, 3901 Rainbow Blvd, Mailstop

2012, Kansas City, KS, 66160 c

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Center, 3901 Rainbow Blvd, Mailstop 2002, Kansas City, KS, 66160

Department of Psychology, University of Missouri-Kansas City, 5030 Cherry St, Kansas City,

MO, 64110 Corresponding Author:

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Catherine Siengsukon, PT, PhD University of Kansas Medical Center

Physical Therapy and Rehabilitation Sciences

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3901 Rainbow Blvd, Mailstop 2002 Phone: +1-913-588-6913

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Fax: +1-913-588-4568

E-mail: [email protected] Keywords: sleep quality, cognitive function, physical function, multiple sclerosis Abstract word count: 240 Complete manuscript word count: 3,380 Number of reference: 54 Number of tables: 2 Number of figures: 0

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Funding: This study was supported by a NMSS Pilot Grant (PP2068) awarded to CS. A portion of this study was supported by the NIH Clinical and Translational Science Award grant (UL1 TR000001, formerly UL1RR033179), awarded to KUMC and internal funds provided by the

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KUMC School of Health Professions and the Department of Physical Therapy and Rehabilitation Science awarded to CS. SAB was supported in part by K01HD067318 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development. The content is solely the

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responsibility of the authors and does not necessarily represent the official views of the Eunice

Disclosure of Conflicts of Interest: Catherine F Siengsukon: N/A

Melike Kahya: N/A

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Mayis Aldughmi: N/A

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Kennedy Shriver National Institute of Child Health and Human Development

Sharon Lynch: Dr. Lynch has participated in multi-center clinical trials in MS funded by Biogen,

and Actelion,

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Genzyme, Teva, Sanofi, Novartis, Opexa, Roche, NIH, NMSS, Acorda, Sun Pharma, Vaccinex,

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Jared Bruce: Dr. Bruce provides unbranded talks for the Novartis Speakers Bureau and has served on the Novartis MS and Cognition Medical Advisory Board. Morgan Glusman: N/A

Abigail Ness Norouzinia: N/A Sandra Billinger: N/A

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Acknowledgements: The authors thank the many DPT students who assisted with the intervention study and the MidAmerica Chapter of the National Multiple Sclerosis Society for

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their assistance with this study.

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Abstract

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Background: Sleep disturbances are common in individuals with Multiple Sclerosis (MS), but

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the impact of poor sleep quality on cognitive and physical function in individuals with MS is less

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clear.

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Objective/Hypothesis: The purpose of this study was to examine the relationship between sleep

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quality and cognitive and physical function in individuals with mild MS.

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Methods: Forty individuals with relapsing-remitting or secondary-progressive MS (50.3 ±11.6

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years of age) participated. The Pittsburgh Sleep Quality Index (PSQI) was used to index sleep

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quality. A PSQI of ≤5 was considered good sleep quality and > 5 was considered poor sleep

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quality. Cognitive function was assessed using a battery of cognitive tests, and physical function

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was assessed using 2 objective measures and a self-report measure.

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Results: Thirteen individuals (32.5%) indicated good sleep quality and 27 (67.5%) of the

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participants reported poor sleep quality. Those with good sleep quality performed significantly

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better on a visuospatial memory test (p=0.025) and reported higher functional abilities (p<0.001)

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compared to those with poor sleep quality. There was no difference in performance on the

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cognitive tests of verbal memory, information processing, or executive function, or the objective

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function measures. Individuals with poor sleep quality had higher levels of fatigue, depression,

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and anxiety, and lower quality of life.

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Conclusions: Visuospatial memory appears to be the memory domain particularly associated

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with poor sleep quality in people with mild MS. Also, individuals with mild MS with poor sleep

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quality may underestimate their functional abilities.

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Introduction Sleep disturbances in individuals with Multiple Sclerosis (MS) are very common. Approximately 50% of individuals with MS have a diagnosable sleep disorder, and up to 67%

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report some sort of sleep disturbance.1-3 It is thought that a higher percentage of individuals with

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MS have an unrecognized and undiagnosed sleep disorder.4,5 A recent large national survey by

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Brass et al.5 found that more than 70% of the 2375 individuals with MS who participated in the

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study screened positive for at least one or more sleep disorder, but only less than 13% had been

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diagnosed indicating a large number of individuals with MS have an undiagnosed and therefore

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untreated sleep disorder. Sleep disturbances in individuals with MS have been overlooked by

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clinicians and researchers for years,6 and more emphasis should be put on the importance of

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sleep quality in individuals with MS.

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Sleep disturbances in individuals with MS are classified as either primary (caused by the

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disease itself), or secondary (caused by disease-accompanied factors such as pain, medication

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usage, anxiety, depression, spasticity, sexual dysfunction, and bladder problems).2,7,8 Primary

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sleep disturbances may result from the demyelination of the suprachiasmatic nucleus (SCN),9

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which coordinates and regulates circadian rhythms. There is also evidence suggesting that the

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imbalance and alterations in the cytokine levels resulting from the inflammatory and

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autoimmune responses characteristic of MS may contribute to sleep disturbances such as

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excessive daytime sleepiness and insomnia.10

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Studies indicate that poor sleep quality in individuals with MS is an independent predictor of

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reduced quality of life,6,11 and can affect aspects of daily living, such as self-care, work ability,

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physical function, psychological well-being, and interpersonal relationships.6,11,12 Furthermore,

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poor sleep quality is strongly associated with fatigue which is the most commonly reported

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symptom in MS7,13 and further reduces functional abilities and quality of life of these

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individuals.

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Poor sleep quality has also been associated with a decline in several cognitive processes in healthy young and older adults.14,15 A recent population-based study by Song et al.15 on

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community dwelling older men demonstrated that decreased time spent in REM sleep and

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higher time spent in stage N1 sleep are associated with cognitive decline over a four year period

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even after controlling for comorbidities such as depression and sleep disordered breathing.

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Another study found that poor self-reported sleep was associated with a decline in attentional and

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executive functional tasks in healthy young adults.14

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Cognitive impairments are common in individuals with MS, affecting up to 70% of the population, and have been found to be associated with functional disability and

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unemployment.16,17 However, the relationship between sleep quality and cognitive function in

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individuals with MS is not well understood. A study by Cameron et al.18 found that individuals

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with MS with cognitive impairments reported poorer self-reported sleep quality, but which

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cognitive domains are associated with poor sleep quality in individuals with MS remains

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unknown. Understanding the relationship between sleep quality and cognition in individuals with

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MS is important because treatment options that target specific sleep disorders or disturbances

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may be a mechanism to address cognitive impairments. Therefore, one of the primary aims of

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this study was to explore the relationship between sleep quality and cognitive function in

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individuals with MS. We hypothesized that individuals with MS with poor sleep quality would

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have poorer cognitive function compared to individuals with MS with good sleep quality.

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In addition, poor sleep quality may impact physical function in individuals with MS,

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possibly through direct mechanisms or through the association between sleep quality and

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common comorbidities in individuals with MS such as fatigue, spasticity, pain, and

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depression7,11 that may in turn affect physical function. A study by Merlino et al.11 demonstrated

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that poor sleep quality was an independent predictor of decreased physical quality of life in

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individuals with MS. However, the relationship between sleep quality and physical functional

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measures has never been explored in individuals with MS. Therefore, the second aim of this

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study was also to explore the association between sleep quality and physical function including

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physical endurance, performance of simulated ADL’s, and subjective functional status in

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individuals with MS. We hypothesized that individuals with MS with poor sleep quality would

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have poorer physical function compared to individuals with MS with good sleep quality.

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Methods

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Forty individuals with relapsing-remitting or secondary-progressive MS were recruited to

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participate in this study. Participants were recruited from (1) the MS clinic at the University of

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Kansas Medical Center, (2) the Mid-America Chapter of National MS Society, (3) personal

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referral from consented subjects, area physicians, or study personnel, and (4) The University of

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Kansas Medical Center Frontiers Research Participant Registry. Exclusion criteria included: (1)

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known untreated sleep disorder, including individuals with medical diagnosis of sleep apnea,

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insomnia, or restless leg syndrome who have not been treated due to potential differential effects

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of sleep disorders on the nervous system, (2) history of alcohol/drug abuse or nervous system

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disorder other than MS, (3) severe physical, neurological, or sensory impairments that would

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prevent completion of testing, (4) developmental history of learning disability or attention-

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deficit/hyperactivity disorder, (5) relapse and/or corticosteroid use within four weeks of

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assessment, (6) uncorrected vision loss that would interfere significantly with testing, and (7)

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score less than 24 on Mini Mental State Exam.19 This project was approved by and conducted in

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accordance with the Institutional Review Board at the University of Kansas Medical Center.

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Informed consent was obtained in writing from each individual prior to participation in the study.

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Procedure

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The Pittsburgh Sleep Quality Index (PSQI)20 was used to assess self-reported sleep quality over

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the previous month. PSQI consists of 9 questions and ranges in score from 0 to 21, with a higher

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score indicating poorer sleep quality. Following baseline assessment, participants were divided

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into two groups based on their sleep quality. A PSQI of ≤5 was considered good sleep quality

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and > 5 was considered poor sleep quality.20

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The Brief Visuospatial Memory Test (BVMT)21 was used to assess visuospatial memory.

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Participants were shown a display of six geometric figures for 10 seconds over 3 trials. The total

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number of figures recalled was used as the reported outcome measure. The Hopkins Verbal

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Learning Test (HVLT)22 was used to assess verbal memory. The HVLT consists of the examiner

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reading aloud a list of 12 words over 3 trials. Following each trial, the participant repeated as

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many words as they could recall. The total number of correct words recalled was the outcome

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measure used. Information processing was assessed using the Paced Serial Additions Test

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(PASAT)23 and the oral form of the Symbol Digit Modalities Test (SDMT)24. The PASAT

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consists of 60 single-digit numbers presented via audio recording using a set time interval

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between each number. Participants were tested using a 3 second interval and a 2 second interval,

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but only performance on the 2 second interval is reported. The participant was asked to state the

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sum of the last two digits before the next digit is revealed. There are 60 items in the PASAT and

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the total number of correct responses was used as a reported outcome measure. For the SDMT, a

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series of symbols was placed in front of the participant with a key at the top of the page. The

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participants were instructed to use the key to quickly say the number that matches the

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corresponding symbol. The total number of correct responses in 90 seconds was used as the

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reported outcome measure. The Stroop Test25 was used to assess executive functioning. It

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requires participants to inhibit the natural response (reading a word) and replace it with another

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response (saying a color). Each participant is given a list of X’s printed in colored ink and a list

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of words printed in colored ink. The participant is instructed to name the color of the ink. They

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are given 45 seconds to name as many colors as they can. The reported outcome measure of this

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test is an interference score that is the difference between the two conditions while normalizing

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for number of x’s using the following formulae: x-words/x.

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To assess physical function, three tests were used: the Six Minute Walk Test (6MWT)26

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to assess walking ability, the Physical Performance Test (PPT)27 to assess performance of

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common ADL’s, and the Functional Status Questionnaire (FSQ)28 to assess self-report functional

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abilities. For the 6MWT, participants walked between two cones spaced 15 meters apart for six

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minutes, and total meters walked was the outcome reported. The PPT simulates ADL’s of

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varying degrees of difficulty, such as simulated eating, lifting a book from a table to an above

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shoulder shelf, and putting on and removing a jacket. It consists of 9 tasks and each task is

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scored on a scale 0 to 4, with 0 indicating unable to perform task and 4 indicating ability to

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perform the task within the fastest time category. The FSQ consists of 34 items including a self-

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care domain, a mobility domain and a domestic life domain. A higher score (maximum score of

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100) indicates higher self- reported functionality.

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Due to their known association with sleep quality and possible impact on cognitive and

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physical function, depression, anxiety, and fatigue were also assessed. Depression was assessed

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using the Beck Depression Index-Fast Screen (BDI)29. It consists of 7 items and each item is

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scored 0 to 3, with higher scores indicating more severe depressive symptoms. Anxiety was

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characterized with the State-Trait Anxiety Inventory (STAI)30. The subscale STAI-S was used to

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examine current anxiety level, and the subscale STAI-T was used to assess trait or general

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feelings of anxiety. STAI-S has a total score of 44 and STAI-T has a total score 46, with higher

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scores indicating increased anxiety symptoms. Fatigue was evaluated using the Modified Fatigue

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Impact Scale (MFIS)31. It consists of 21 items and each item is scored from 0 to 4. A higher

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score indicated increased fatigue during the past month. Quality of life was determined by the

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Multiple Sclerosis Quality of Life-54 Instrument (MSQoL)32. It consists of 54 items divided into

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2 composite scores (physical and mental) and each composite is scored from 0-100; higher

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scores indicate better quality of life. Demographic information including age, sex, and disease

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duration was gathered. MS disease severity was assessed using the Multiple Sclerosis Functional

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Composite (MSFC)33.

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All the assessments were administered in one visit by trained research personnel. The 6WMT, PPT, and 25 ft walk test for the MSFC were completed by MA. The cognitive tests and

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questionnaires were completed by MG and ANN. Participants were encouraged to rest between

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assessments as needed. Data were collected as part of an intervention study.

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Statistical Analysis

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SPSS for Windows version 22.0 software (SPSS Inc., Chicago, IL, USA) was used for the

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analysis. Mann-Whitney U tests were used to determine between group differences on

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demographic, cognitive function, physical function, and psycho-social measures. Mann-Whitney

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U tests were used due to lack of normality of the data. Nonparametric effect size34 were

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calculated to examine the difference between the groups in the outcome measures and was

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interpreted as small d = .2, medium d = .5, and large d = .835. Spearman’s rho correlations

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assessed the relationship between PSQI and demographic, cognitive function, physical function,

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and psycho-social variables. The level of significance was set at p < .05.

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Results

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Of the 40 participants (50.3 ±11.6 years of age), 13 (32.5%) indicated good sleep quality and 27

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(67.5%) reported poor sleep quality. Demographic characteristics did not differ significantly

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between the groups (see Table 1). The sample consisted of individuals primarily with mild

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disease severity. Using the pre-defined cut points to classify sleep quality, the individuals with

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poor sleep quality had an average of 9.2±2.6 on the PSQI compared to the individuals with good

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sleep quality who had an average of 3.6±1.4 (p<0.001; Table.1).

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For the cognitive function measurements, those with good sleep quality performed significantly better on the visuospatial memory test (BVMT) compared to those with poor sleep

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quality. Also, there was a trend towards significant group difference on the SDMT to assess

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information processing with a small effect size (p=0.073, d=0.29). There was no statistically

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significant difference on the verbal memory test (HVLT), PASAT to assess information

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processing, or executive functioning test (Stoop test). For the physical function measurements, there were no statistically significant difference

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between the groups on performance of walking ability (6MWT) or common ADLs (PPT), but the

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individuals with good sleep quality had significantly higher scores on the self-report functional

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abilities (FSQ) compared to those with poor sleep quality .

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Comparison of the psycho-social variables demonstrated that those with poor sleep

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quality had a statistically significant higher level of fatigue (MFIS), depression (BDI), current

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and general anxiety (STAI-S and STAI-T), and lower level of physical health (MSQoL-physical

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composite score) and mental health (MSQoL-mental composite score) compared to people with

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good sleep quality (Table.2).

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Discussion

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This study demonstrates that individuals with mild MS with poor sleep quality show reduced

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visuospatial memory and self-report functional ability and a trend towards reduced information

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processing on the SDMT, but there were no differences between those with good sleep quality

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and those with poor sleep quality on performance of verbal memory, speed of information

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processing assessed by the PASAT, or executive functioning or objective measures of physical

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function. This study also supports prior studies that individuals with MS with poor sleep quality

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experience increased fatigue, reduced quality of life, increased depressive symptoms, and

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increased current and general anxiety levels.3,11,36

This study supports evidence that the majority of individuals with MS experience reduced

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sleep quality. Prior studies3,11,37 found 47.5-70.0% of individuals with MS had poor sleep quality.

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This incidence of poor sleep quality within a sample of individuals with MS is directly in-line

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with our findings (67.5% with poor sleep quality) in individuals with mild MS. This high

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prevalence of poor sleep quality is concerning considering the association between sleep and

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fatigue7,13 as well as physical and psychological well-being.6,11,12 In addition, chronic sleep

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insufficiency is associated with increased incidence of accidents and increased mortality as well

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as contributes to the development of several health problems, including hypertension,

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cardiovascular disease, obesity, depression, and diabetes.38,39 Identifying and addressing the

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factors contributing to poor sleep quality in individuals with MS may improve current health as

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well as reduce future health issues.

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This study provides novel findings as the association between sleep quality and cognitive function has never to our knowledge been examined in individuals with MS. Interestingly, the

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individuals with mild MS with poor sleep quality performed worse only on the visuospatial

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memory test as well as demonstrated a moderately worse performance (although not statistically

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significant) on one measure of information processing (the SDMT). However, there was no

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statistically significant difference between the groups on the verbal memory test, the PASAT to

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assess information processing, or the executive function test. People with insomnia have been

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shown to exhibit cognitive impairments40,41 including impaired information processing speed,

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attention, and memory,42 and shorter sleep duration and reduced sleep efficiency was associated

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with tests of sustained attention and working memory in older adults.43 However, older adults

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with insomnia performed similarly on cognitive and psychomotor performance tests compared to

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age-matched normative data.44 A study by Saint Martin et al.45 2012 found no difference in tests

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of cognitive function between nearly 300 community-dwelling older adults with good sleep

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quality and those with poor sleep quality except for on a test of speed of information processing.

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The study by Benitez and Gunstad14 in healthy young adults found poor sleep quality, sleep

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duration, and medication use were associated with reduced attentional and executive functioning

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abilities. Sutter et al46 suggests that a depressive symptom mediates the relationship between

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sleep quality and cognitive function in healthy older adults. Although there was a significant

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difference in depressive symptoms (BDI) between the good sleep quality group and the poor

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sleep quality group in the current study, both groups would be considered to have minimal

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depressive symptoms, thus perhaps mitigating potential differences in cognitive function.

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Another possibility for why there was a difference in performance on the BVMT but not the

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other cognitive function measures may be due to the role of sleep in learning and memory

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consolidation. Sleep is thought to enhance learning and memory, and perhaps visuospatial

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memory is particularly impacted by pre-testing sleep duration or quality. Additional studies are

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needed to support this contention. The higher levels of generalized and state anxiety in those with poor sleep quality is not

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surprising. Hyperarousal of the central nervous system and a heightened stress response are

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thought to be underlying causes of anxiety47 as well as contributing factors to insomnia48.

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Although individuals were excluded from participating in the study if they had a known sleep

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disorder, such as insomnia, it is possible a high percentage of participants experienced an

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unknown and undiagnosed sleep disorder. Recent studies found that 32%5 to 46%49 of

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individuals with MS screened positive for moderate to severe insomnia. Also, it is possible that

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poor perceived function may interfere with an individual’s ability to easily change position while

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sleeping which may contribute to greater sleep disturbance and poorer sleep quality. Future

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studies are needed to verify these contentions.

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An interesting finding is that the individuals with poor sleep quality reported lower functional ability on a self-report questionnaire compared to those with good sleep quality but

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there was no statistical difference in objective measures of functional abilities between the

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groups.50 In fact, the performance on the 6MWT and Physical Performance Test were extremely

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similar between groups. It is possible that individuals with MS with poor sleep quality

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underestimate their function abilities. This contention is supported by studies that demonstrate

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self-report cognitive function is poorly associated with objective measures of cognitive

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function.51,52 Previous studies have showed that individuals with MS who are fatigued and have

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depressive symptoms are more likely to have reduced physical quality of life.50,53 In addition, a

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study by Stroud et al.54 demonstrated that individuals with MS who exercise regularly (defined

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as at least 30 minutes of exercise two times a week) have less fatigue and less depressive

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symptoms compared to non-exercisers.

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A major limitation of the present study is the relatively small sample size. This study provides effect sizes to adequately power future studies to better ascertain the relationship

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between poor sleep quality and cognitive function. Furthermore, due to cross-sectional design, it

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is difficult to ascertain the direct relationship between the predictors of poor sleep and poor sleep

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quality itself. Longitudinal studies are needed to determine the direct relationship. Individuals

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with severe impairments that would prevent completion of testing were excluded, so these

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findings should be interpreted in light that individuals in this study had mild disease severity. In

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addition, participants were divided into groups based on the PSQI, which is a subjective

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measurement of sleep quality. It is possible that individuals with MS may overestimate or

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underestimate their sleep quality. Therefore, an objective measurement of sleep quality, such

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using actigraphy, may be an option to objectively assess sleep quality in this population. Also,

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while individuals were excluded from participating if they had a known untreated sleep disorder

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(such as sleep apnea, insomnia, and restless leg syndrome), it is possible that some individuals

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participating in this study had an unknown sleep disorder. In a large national survey, more than

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70% of individuals with MS screened positive for one or more sleep disorders5. Therefore, the

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factors contributing to poor sleep quality cannot be determined and may be due to unknown

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sleep disorders, poor sleep hygiene, the disease process, or other reasons.

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Conclusion

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This study highlights the high prevalence of poor sleep quality in individuals with MS and its

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relationship with reduced cognitive abilities and physical functioning. Furthermore, visuospatial

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memory and self-reported functional abilities is lower in individuals with MS with poor sleep

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quality. Future studies should consider if interventions to address poor sleep quality in

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individuals with MS may improve visuospatial memory and perceived functional abilities. In

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addition, health care providers should be encouraged to assess and treat sleep disorders and other

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factors contributing to poor sleep quality in individuals with mild MS. As our study shows a high

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correlation with anxiety and depression, treatment of these disorders may also lead to an

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improvement in sleep quality, and subsequently an improved quality of life.

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Poor sleep quality (n=27; 67.5%) 51.5±11.4 23/4 24/3

Good sleep quality (n=13; 32.5%) 47.8±12 13/0 9/4

p-value

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0.345 Age (years) Sex (F/M) Disease type (RR/SP) 0.732 Disease 11.96±9.1 12.54±7.93 duration (years) 0.057 MSFC .792±1.9 .69±.796 0.276 MMSE 28.9±1.5 28.4±1.7 <0.001 PSQI 3.6±1.4 9.2±2.6 Table 1. Demographic characteristics. Data is reported as (Mean±SD). MSFC: Multiple Sclerosis Functional Composite, MMSE: Mini Mental Status Examination, PSQI: Pittsburgh Sleep Quality Index

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Poor sleep quality (n=27)

Good sleep quality (n=13)

p-value

21.63±8.6 25.41±3.9 30.4±8.5 49.89±10.75 0.4±0.12

26.62±7 27±5.5 34.31±8.4 56.31±9 0.35±0.9

0.025* 0.512 0.168 0.073 0.308

Effect Size

Cognitive Function:

Physical Function:

0.35 0.11 0.22 0.29 0.16

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BVMT HVLT PASAT SDMT Stroop test

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404.3±156 0.977 <0.01 6MWT (meters) 409.4±135.6 23.38±5.1 0.955 <0.01 PPT 23.37±4.9 91.24±6.6 <0.001* 0.55 FSQ 76.54±12.75 Psycho-social Measures: 23.8±17.3 0.001* 0.49 MFIS 41±14.6 76.8±17.96 0.007* 0.42 MSQol-physical 60.2±16.8 82.3±12.5 0.003* 0.45 MSQoL-mental 65.0±17.4 1.46±1.9 0.007* 0.43 BDI 3.89±2.9 26.69±8.8 0.009* 0.41 STAI-S 34.42±10.1 29.77±8.3 <0.001* 0.53 STAI-T 42.35±9.9 Table 2. Comparison of outcome variables in individuals with poor sleep quality versus good sleep quality. Data is reported as (Mean±SD). BVMT: Brief Visuospatial Memory Test, HVLT: Hopkins Verbal Learning Test, PASAT: Paced Auditory Serial Addition Test, SDMT: Symbol Digit Modalities Test, 6MWT: Six Minute Walk Test, PPT: Physical Performance Test, FSQ: Functional Status Questionnaire, MFIS: Modified Fatigue Impact Scale, MSQoL: Multiple Sclerosis Quality of Life-54 Instrument, BDI: Beck Depression Index, STAI-T: State-Trait Anxiety Inventory-Trait, STAI-S: State-Trait Anxiety Inventory-State