Quality of life for persons living with multiple sclerosis (MS) is significantly lower than population norms. Fatigue, both physical and cognitive, is one of the most prevalent and debilitating symptoms of MS that decrease quality of life. Cognitive fatigue presents similarly to sensory overresponsiveness, but the connection has not been explored.
Purpose.
This study aims to describe how sensory-processing preferences and cognitive fatigue relate to variances in quality of life for people with MS.
Method.
A cross-sectional design was used with 30 people living with MS to complete the Adolescent/Adult Sensory Profile (AASP), Modified Fatigue Impact Scale, and RAND-36. Spearman’s coefficient measured nonparametric correlations between variables.
Findings.
People with MS who have high scores in low registration, sensory sensitivity, and sensation avoidant quadrants of the AASP also have higher levels of cognitive fatigue and poorer quality of life. Those with high scores in sensory seeking experience greater quality of life and less cognitive fatigue.
Implications.
The findings shape clinical practice by supporting the assessment of sensory processing alongside fatigue, offering individualized intervention planning to shape fatigue management, and fostering hope and quality of life for persons living with MS.
AyresA. J. (1971). Characteristics of types of sensory integrative dysfunction. American Journal of Occupational Therapy, 25, 329–334.
2.
AyresA. J. (1972). Sensory integration and learning disorders. Torrance, CA: Western Psychological Services.
3.
AyresA. J. (1979). Sensory integration and the child. Torrance, CA: Western Psychological Services.
4.
Ben-AviN.AlmagorM.Engel-YegerB. (2012). Sensory processing difficulties and interpersonal relationships in adults: An exploratory study. Psychology, 3, 70–77. doi:10.4236/psych.2012.31012
5.
BenedictR. H. B.WahligE.BakshiR.FishmanI.MunschauerF.…Weinstock-GuttmanB. (2005). Predicting quality of life in multiple sclerosis: Accounting for physical disability, fatigue, cognition, mood disorder, personality, and behaviour change. Journal of Neurological Sciences, 231, 29–34. doi:10.1016/j.jns.2004.12.009
6.
Benito-LeónJ.MoralesJ. M.Rivera-NavarrosJ.MitchellA. J. (2003). A review about the impact of multiple sclerosis on health-related quality of life. Disability and Rehabilitation, 25, 1291–1303. doi:10.1080/09638280310001608591
CharvetL.SerafinD.KruppL. B. (2014). Fatigue in multiple sclerosis. Fatigue: Biomedicine, Health & Behavior, 2, 3–13. doi:10.1080/21641846.2013.843812
9.
DeLucaJ.GenovaH. M.HillaryF. G.WylieG. (2008). Neural correlates of cognitive fatigue in multiple sclerosis using functional MRI. Journal of the Neurological Sciences, 270, 28–39. doi:10.1016/j.jns.2008.01.01
10.
DunnW. (2001). The sensations of everyday life: Empirical, theoretical, and pragmatic considerations. American Journal of Occupational Therapy, 55, 608–620. doi:10.5014/ajot.55.6.608
11.
Engel-YegerB.DunnW. (2011a). Exploring the relationship between affect and sensory processing patterns in adults. British Journal of Occupational Therapy, 74, 456–464. doi:10.4276/030802211X13182481841868
12.
Engel-YegerB.DunnW. (2011b). Relationship between pain catastrophizing level and sensory processing patterns in typical adults. American Journal of Occupational Therapy, 65, e1–e10. doi: 10.5014/ajot.2011.09004
13.
FilippiM.RoccaM. A.ColomboB.FaliniA.CodellaM.ScottiG.ComiG. (2002). Functional magnetic resonance imaging correlates of fatigue in multiple sclerosis. NeuroImage, 15, 559–567. doi:10.1006/nimg.2001.1011
14.
FiskJ. D.RitvoP. G.RossL.HaaseD. A.MarrieT. J.SchlechW. F. (1994). Measuring the functional impact of fatigue: Initial validation of the Fatigue Impact Scale. Clinical Infectious Diseases, 18(Suppl. 1), S79–S83. doi:10.1093/clinids/18.Supplement_1.S79
15.
HaysR. D.MoralesL. S. (2001). The RAND-36 measure of health-related quality of life. Annals of Medicine, 33, 350–357. doi:10.3109/07853890109002089
16.
IarocciG.McDonaldJ. (2006). Sensory integration and the perceptual experience of persons with autism. Journal of Autism and Developmental Disorders, 36, 77–90. doi:10.1007/s10803-005-0044-3
17.
KinnealeyM.KoenigK. P.SmithS. (2011). Relationships between sensory modulation and social supports and health-related quality of life. American Journal of Occupational Therapy, 65, 320–327. doi:10.5014/ajot.2011.001370
18.
KinnealeyM.OliverB.WilbargerP. (1995). A phenomenological study of sensory defensiveness in adults. American Journal of Occupational Therapy, 49, 444–451. doi:10.5014/ajot.49.5.444
19.
KisleyM. A.NoeckerT. L.GuintherP. M. (2004). Comparison of sensory gating to mismatch negativity and self-report perceptual phenomena in healthy adults. Psychophysiology, 41, 604–612. doi:10.1111/j.1469-8986.2004.00191.x
20.
KlemenJ.ChambersC. D. (2012). Current perspectives and methods in studying neural mechanisms of multisensory interactions. Neuroscience and Biobehavioral Reviews, 36, 111–133. doi:10.1016/j.neubiorev.2011.04.015
21.
KosD.KerckhofsE.CarreaI.VerzaR.RamosM.JansaJ. (2005). Evaluation of the Modified Fatigue Impact Scale in four different European countries. Multiple Sclerosis, 11, 76–80. doi:10.1191/1352458505ms1117oa
LaneS. J.LynnJ. Z. (2011). Sensory integration research: A look at past, present, and future. Sensory Integration: Special Interest Section Quarterly, 34, 1–3.
24.
LarsonR. D. (2013). Psychometric properties of the Modified Fatigue Impact Scale. International Journal of MS Care, 15, 15–20. doi:10.7224/1537-2073.2012-019
25.
MahoneyJ. R.LiP. C. C.Oh-ParkM.VergheseJ.HoltzerR. (2011). Multisensory integration across the senses in young and old adults. Brain Research, 1426, 43–53. doi:10.1016/j.brainres.2011.09.017
26.
MillerL. J.LaneS. J. (2000). Towards a consensus in terminology in sensory integration theory and practice: Part 1: Taxonomy of neurophysiological processes. Sensory Integration, 23, 1–4.
27.
MillsR. J.YoungC. A.PallantJ. F.TennantA. (2010). Rasch analysis of the Modified Fatigue Impact Scale (MFIS) in multiple sclerosis. Journal of Neurology, Neurosurgery & Psychiatry, 81, 1049–1051. doi:10.1136/jnnp.2008.151340
28.
MinagarA.BarnettM. H.BenedictR. H B.PelletierD.PirkoI.SahraianM. A.…ZivadinovR. (2013). The thalamus and multiple sclerosis. Neurology, 80, 210–219. doi:10.1212/WNL.0b013e31827b910b
29.
MitchellA. J.Benito-LeónJ.MoralesJ. M.Rivera-NavarroJ. (2005). Quality of life and its assessment in multiple sclerosis: Integrating physical and psychological components of wellbeing. Lancet Neurology, 4, 556–566. doi:10.1016/S1474-4422(05)70166-6
30.
PolmanC. H.ReingoldS. C.BanwellB.ClanetM.CohenJ. A.FilippiM.…WolinskyJ. S. (2011). Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. American Neurological Association, 69, 292–302. doi:10.1002/ana.22366
31.
RudroffT.KindredJ. H.KetelhutN. B. (2016). Fatigue in multiple sclerosis: Misconceptions and future research directions. Frontiers in Neurology, 7, Article 122. doi:10.3389/fneur.2016.00122
32.
WhelanR.LonegranR.KiiskiH.NolanH.KinsellaK.HutchisonM.…ReillyR. B. (2010). Impaired information processing speed and attention allocation in multiple sclerosis patients versus controls: A high-density EEG study. Journal of Neurological Sciences, 293, 45–50. doi:10.1016/j.jns.2010.03.010
