The Mediating Role of Cognitive Fatigue on the Relationship between Anxiety and Illness Intrusiveness

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The Mediating Role of Cognitive Fatigue on the Relationship between Anxiety and Illness Intrusiveness CAROLINE ALTARAS, B.S., NICHOLAS A VISSICCHIO, B.A., SHONNA SCHNEIDER, B.A., SHAINA SHAGALOW, B.A., AMANDA A PARKER, B.S., JENNIFER MILLER, B.A., AND FREDERICK W FOLEY, PH.D. FERKAUF GRADUATE SCHOOL OF PSYCHOLOGY, YESHIVA UNIVERSITY, BRONX, NY HOLY NAME MEDICAL CENTER, MS CENTER, TEANECK, NJ

Learning Objectives Better understand the impact of anxiety of the degree to which MS patients perceive their MS as intrusive Examine the mediating role of cognitive fatigue on the association between anxiety and illness intrusiveness

Illness Intrusiveness Illness intrusiveness refers to the degree to which an individual perceives his/her illness as interfering with valued aspects of life, such as ongoing activities and interests 1,2 Impacts well-being via two pathways 2-4 1) Reduced availability and participation of valued activities 2) Reduced perception of control Associated with: 2 Poor quality of life 5,6 Psychological distress and mental health (depression and anxiety) 1,2,5,7 Fatigue 6,7 Physical disability 6,7 Sleep quality 4

Anxiety Unpleasant state of fear associated with an anticipation of a future threat Prevalence: 19.3-44.5% 8 Factors: 9-11 Uncertainty, unpredictability, physical and psychological limitations, social and financial strains, exacerbations, and complexities of treatment Some researchers have suggested that some anxiety may be due to the direct effects of physiological changes in MS (e.g. cerebral atrophy) MS patients with higher levels of anxiety were more likely to perceive their MS as intrusive than those with lower anxiety 12 Cognitive distortions Impact of anxiety on disease factors

Cognitive Fatigue Cognitive fatigue is a component of central fatigue characterized as a decline in the ability to sustain concentration and endure mental tasks 13,14 Fatigue has prevalence of 60 95% in MS Associated with: 10, 17, 18 Anxiety and depression Self-efficacy Stress Sleep quality Quality of life 15, 16 Relation of anxiety and cognitive fatigue 19,20 Interplay of biological, cognitive, emotional, and behavioral factors

Objective Examine the relationship between anxiety and illness intrusiveness, and evaluate cognitive fatigue as a mediator 1-4 Disease Factors Illness Intrusiveness Subjective Well- Being Psychological Factors

Methods and Demographics Participants recruited from ongoing study at the MS Center at Holy Name Hospital in Teaneck, NJ Data analysis is based on 60 participants Statistical Analysis- SPSS 24.0, Process Macro Preacher and Hayes bootstrapping approach 21 Series of OLS regressions Characteristics M SD Age 47.91 12.36 Years of Education 14.98 3.90 ISS Total Score 13.13 6.91 Gender Female Male Race/Ethnicity Caucasian Black Hispanic Employment Status Unemployed Part-time Full-time 77.3% 22.7% 75.8% 15.2% 9.1% 69.7% 4.5% 25.8%

Instruments Illness Intrusiveness Rating Scale (IIRS) 22 13 item, 7-point scale Total score range= 13-91 Subscales: 1) Instrumental; 2) Intimacy; 3) Relationship/Personal Development Fatigue Scale for Motor and Cognitive Functions (FSMCC) 23 20 item, 5 point scale Ranges= Mild: 22-27, Moderate: 28-33 and Severe: 34 Subscales: 1) Motor Fatigue; 2) Cognitive Fatigue Scale M (N) SD (%) HADS Anxiety No Anxiety Anxiety 8.80 23 37 4.05 38.3% 61.7% FSMC Cognitive None Mild Moderate Severe 37.14 4 5 14 37 9.06 6.7% 8.3% 23.3% 61.7% IIRS Total Score 52.55 20.12 Hospital Anxiety and Depression Scale (HADS) 24 14 item, 4 point scale Range=0- no symptoms to 21- most severe symptoms Subscales: 1) Anxiety; 2) Depression

Mediational Model a Cognitive Fatigue b Anxiety c direct effect c total effect Illness Intrusiveness

Mediational Model a Cognitive Fatigue b Anxiety ab indirect effect Illness Intrusiveness

a FSMCC Model 1- Pathway a HADSA FSMCC (Cognitive Fatigue) B SE B 95% CI Intercept 17.776* 7.760 (2.218, 33.333) HADSA (Anxiety) 1.318***.243 (.831, 1.806) Age.042.080 (-.118,.202) Gender 1.549 2.340 (-3.143, 6.240) Years of Education -.010.445 (-.902,.881) ISS Total.222.160 (-.099,.543) R 2 =.455, F(5, 54)=9.011, p<.001 Path a

Model 2- Pathway c HADSA IIRS (Illness Intrusiveness) B SE B 95% CI Intercept 31.534 17.409 (-3.369, 66.437) HADSA (Anxiety) 1.799**.546 (.705, 2.892) Age -.236.179 (-.595,.123) Gender 10.531* 5.250 (.006, 21.056) Years of Education -1.102.997 (-3.101,.898) ISS Total 1.097**.359 (.377, 1.817) R 2 =.423, F(5, 54)=7.932, p<.001 c IIRS Path c

FSMCC b Model 3- Pathways b and c HADSA IIRS (Illness Intrusiveness) B SE B 95% CI Intercept 17.730 17.268 (-16.906, 52.366) FSMC (Cognitive Fatigue).777**.289 (.197, 1.357) HADSA (Anxiety).775.642 (-.513, 2.062) Age -.269.170 (-.610,.072) Gender 9.328 4.992 (-.684, 19.340) Years of Education -1.094.945 (-2.988,.801) ISS Total.924**.346 (.230, 1.618) R 2 =.493, F(6, 53)=8.573, p<.001 c IIRS Path b Path c

a FSMCC b Indirect Effect- Pathway ab HADSA ab IIRS Total. Direct, and Indirect Effects Effect SE 95% CI p Total effect: c 1.799.546 (.705, 2.892).0017 Direct effect: c.775.6420 (-.513, 2.062).2330 Indirect effect: ab 1.024.439 (.311, 2.037) * Sobel Test 1.024.4312.0176 * The 95% CI does not include zero suggesting the mediation effect is significant at p <.05

Conclusion Cognitive Fatigue a= 1.318, SE=.243*** b=.777, SE=.2891** Anxiety ab = 1.024, SE=.439 95% CI (.311, 2.037)* Illness Intrusiveness

Conclusion and Future Directions Findings indicate that the positive association between anxiety and the degree to which an individual perceives their MS as intrusive is mediated by the individual's perception of cognitive fatigue Anxiety was no longer a significant predictor of illness intrusiveness after controlling for cognitive fatigue Cross-Sectional Design Examine individual subscales, motor fatigue, and depression

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References 7. Shahrbanian, S., et al., Contribution of symptom clusters to multiple sclerosis consequences. Quality of Life Research, 2015. 24(3): p. 617-629. 8. Marrie, R.A., et al., The incidence and prevalence of psychiatric disorders in multiple sclerosis: a systematic review. Multiple Sclerosis Journal, 2015. 21(3): p. 305-317. 9. Giesser, B.S., Primer on multiple sclerosis. 2015: Oxford University Press. 10. Hartoonian, N., et al., Predictors of anxiety in multiple sclerosis. Rehabilitation Psychology, 2015. 60(1): p. 91-98. 11. Garfield, A.C. and N.B. Lincoln, Factors affecting anxiety in multiple sclerosis. Disability and Rehabilitation: An International, Multidisciplinary Journal, 2012. 34(24): p. 2047-2052. 12. Snyder, S., et al., Psychological and physical predictors of illness intrusiveness in patients with multiple sclerosis. Journal of the neurological sciences, 2013. 332(1): p. 41-44. 13. Chaudhuri, A. and P.O. Behan, Fatigue in neurological disorders. The lancet, 2004. 363(9413): p. 978-988. 14. Cantor, F., Central and peripheral fatigue: exemplified by multiple sclerosis and myasthenia gravis. PM&R, 2010. 2(5): p. 399-405.

References 15. Nagaraj, K., et al., Prevalence of fatigue in patients with multiple sclerosis and its effect on the quality of life. Journal of neurosciences in rural practice, 2013. 4(3): p. 278. 16. Hadjimichael, O., T. Vollmer, and M. Oleen-Burkey, Fatigue characteristics in multiple sclerosis: the North American Research Committee on Multiple Sclerosis (NARCOMS) survey. Health and Quality of Life Outcomes, 2008. 6(1): p. 100. 17. Trojan, D.A., et al., Fatigue in multiple sclerosis: association with disease-related, behavioural and psychosocial factors. Multiple Sclerosis Journal, 2007. 13(8): p. 985-995. 18. Pardini, M., et al., Frontal networks play a role in fatigue perception in multiple sclerosis. Behavioral neuroscience, 2010. 124(3): p. 329. 19. Van Kessel, K. and R. Moss-Morris, Understanding multiple sclerosis fatigue: A synthesis of biological and psychological factors. 2006, Elsevier Science: Netherlands. p. 583-585. 20. Knoop, H., K. Van Kessel, and R. Moss-Morris, Which cognitions and behaviours mediate the positive effect of cognitive behavioural therapy on fatigue in patients with multiple sclerosis? Psychological medicine, 2012. 42(01): p. 205-213.

References 21. Preacher, K.J. and A.F. Hayes, SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behavior research methods, 2004. 36(4): p. 717-731. 22. Devins, G.M., et al., The emotional impact of end-stage renal disease: Importance of patients' perceptions of intrusiveness and control. International Journal of Psychiatry in Medicine, 1983. 13(4): p. 327-343. 23. Penner, I., et al., The Fatigue Scale for Motor and Cognitive Functions (FSMC): validation of a new instrument to assess multiple sclerosis-related fatigue. Multiple sclerosis, 2009. 15(12): p. 1509-1517. 24. Zigmond, A.S. and R.P. Snaith, The Hospital Anxiety and Depression Scale. 1983, Blackwell Publishing: United Kingdom. p. 361-370.