Skip to main content

Advertisement

SpringerLink
Log in

Pain acts through fatigue to affect participation in individuals with multiple sclerosis

  • Published:
Quality of Life Research Aims and scope Submit manuscript

Abstract

Purpose

The symptoms of multiple sclerosis (MS) often cause physical and mental dysfunction, which interferes with a person’s ability to participate in life’s roles. Identification of the strength of the contributors to participation would help prioritize intervention approaches for its improvement. The objective of this study was to estimate the extent to which pain and other MS-related symptoms, physical function, psychological variables, and individual characteristics predict participation in people with MS.

Methods

This was a cross-sectional study. Study sample was a center-stratified random sample of 188 persons with MS. Subjects completed a battery of self-report and performance-based measures that assessed participation and domains affecting participation. To model the relationships among variables, a conceptual framework based on the Wilson and Cleary model was tested. Structural equation modeling aimed at identification of the predictors of participation within the hypothesized theoretical model.

Results

Fatigue (β = 0.63, p < 0.0001), physical function (β = 0.37, p < 0.0001), and psychological variables (β = 0.15, p = 0.04) were found to be as significant direct predictors of participation. Pain (β = 0.4, p < 0.0001) and age (β = 0.12, p < 0.0001) were significant indirect predictors through fatigue and physical function, respectively. Together these effects explained 88 % of the variance of participation, 35 % of the variance in psychological variables, and 29 % of the variance in physical function.

Conclusion

Fatigue, physical function, pain, and psychological variables were most important contributors for participation in persons with MS.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. Noseworthy, J. H., Lucchinetti, C., Rodriguez, M., & Weinshenker, B. G. (2000). Multiple sclerosis. New England Journal of Medicine, 343, 938–952.

    Article  CAS  PubMed  Google Scholar 

  2. O’Connor, P. (2009). Key issues in the diagnosis and treatment of multiple sclerosis: An overview. Neurology, 59, S1–S33.

    Article  Google Scholar 

  3. Richards, R. G., Sampson, F. C., Beard, S. M., & Tappenden, P. (2002). A review of the natural history and epidemiology of multiple sclerosis: Implications for resource allocation and health economic models. Health Technology Assessment, 6(10), 1–73.

    Article  CAS  PubMed  Google Scholar 

  4. Devins, G. M., Dion, R., Pelletier, L. G., Shapiro, C. M., Abbey, S., & Raiz, L. R. (2001). Structure of lifestyle disruptions in chronic disease, a confirmatory factor analysis of the Illness Intrusiveness Ratings Scale. Medical Care, 39(10), 1097–1104.

    Article  CAS  PubMed  Google Scholar 

  5. Neubeck, L., Freedman, S. B., Clark, A. M., Briffa, T., Bauman, A., & Redfern, J. (2012). Participating in cardiac rehabilitation, a systematic review and meta-synthesis of qualitative data. European Journal of Preventive Cardiology, 19(3), 494–503.

    Article  PubMed  Google Scholar 

  6. Barclay-Goddard, R., Ripat, J., & Mayo, N. (2012). Developing a model of participation post-stroke, a mixed-methods approach. Quality of Life Research, 21, 417–426.

    Article  PubMed Central  PubMed  Google Scholar 

  7. Mayo, N. E., Wood-Dauphinee, S., Cote, R., Durcan, L., & Carlton, J. (2002). Activity, participation, and quality of life six months post-stroke. Archives of Physical Medicine and Rehabilitation, 83, 1035–1042.

    Article  PubMed  Google Scholar 

  8. World Health Organization. (2001). International classification of functioning, disability and health (2nd revision ed.). http://www3.who.int/icf/icftemplate.cfm. Geneva.

  9. Salter, K., Jutai, J. W., Teasell, R., Foley, N. C., Bitensky, J., & Bayley, M. (2005). Issues for selection of outcome measures in stroke rehabilitation, ICF participation. Disability and Rehabilitation, 27(9), 507–528.

    Article  CAS  PubMed  Google Scholar 

  10. Johnston, M. V., & Miklos, C. S. (2002). Activity-related quality of life in rehabilitation and traumatic brain injury. Archives of Physical Medicine and Rehabilitation, 83(Suppl 2), S26–S38.

    Article  PubMed  Google Scholar 

  11. Whiteneck, G. G., Charliefue, S. W., & Gerhart, K. A. (1992). Quantifying handicap, a new measure of long-term rehabilitation outcomes. Archives of Physical Medicine and Rehabilitation, 73, 519–526.

    CAS  PubMed  Google Scholar 

  12. Phillips, L., & Stuifbergen, A. (2009). Structural equation modeling of disability in women with fibromyalgia or multiple sclerosis. Western Journal of Nursing Research, 31, 89–109.

    Article  PubMed  Google Scholar 

  13. Yorkston, K., Johnson, K., & Klasner, E. (2005). Taking part in life, enhancing participation in multiple sclerosis. Physical Medicine & Rehabilitation Clinics of North America, 16, 583–594.

    Article  Google Scholar 

  14. Shahrbanian, S., Auais, M., Duquette, P., Andersen, K., & Mayo, N. E. (2013). Does pain in individuals with multiple sclerosis affect employment? A systematic review and meta-analysis. Pain Research & Management, 18(5), e94–e100.

    Google Scholar 

  15. Ehde, D. M., Osborne, T. L., & Jensen, M. P. (2005). Chronic pain in persons with multiple sclerosis. Physical Medicine & Rehabilitation Clinics of North America, 16, 503–512.

    Article  Google Scholar 

  16. Archibald, C. J., McGrath, P. J., & Ritvo, P. G. (1994). Pain prevalence, severity and impact in a clinic sample of multiple sclerosis patients. Pain, 58, 89–93.

    Article  CAS  PubMed  Google Scholar 

  17. Hadjimichael, O., Kerns, R. D., Rizzo, M. A., Cutter, G., & Vollmer, T. (2007). Persistent pain and uncomfortable sensations in persons with multiple sclerosis. Pain, 127, 35–41.

    Article  PubMed  Google Scholar 

  18. Warnell, P. (1991). The pain experience of a multiple sclerosis population, a descriptive study. Axon, 13, 26–28.

    CAS  PubMed  Google Scholar 

  19. Kerns, R., Kassirer, M., & Otis, J. (2002). Pain in multiple sclerosis, a biopsychosocial perspective. Journal of Rehabilitation Research and Development, 39, 225–232.

    PubMed  Google Scholar 

  20. Wilson, I. B., & Cleary, P. D. (1995). Linking clinical variables with health-related quality of life. A conceptual model of patient outcomes. JAMA, 273(1), 59–65.

    Article  CAS  PubMed  Google Scholar 

  21. Kurtzke, J. F. (1983). Rating neurologic impairment in multiple sclerosis, an expanded disability status scale (EDSS). Neurology, 33(11), 1444–1452.

    Article  CAS  PubMed  Google Scholar 

  22. Ng, P., Finch, L., Hum, S., & Mayo, N. E. (2013). The path to work capacity in people with multiple sclerosis. Dissertation, McGill University.

  23. Jensen, M. P., Turner, J. A., & Romano, J. M. (1999). Comparative reliability and validity of chronic pain intensity measures. Pain, 83, 157–162.

    Article  CAS  PubMed  Google Scholar 

  24. Margolis, R. B., Tait, R. C., & Krause, S. J. (1986). A rating system for use with patient pain drawings. Pain, 24, 57–65.

    Article  CAS  PubMed  Google Scholar 

  25. Hays, R. D., Sherbourne, C. D., & Mazel, R. M. (1993). The RAND 36-item health survey 1.0. Health Economics, 2(3), 217–227.

    Article  CAS  PubMed  Google Scholar 

  26. Ware, J. E, Jr. (1987). Standards for validating health measures: Definition and content. Journal of Chronic Diseases, 40(6), 473–480.

    Article  PubMed  Google Scholar 

  27. Bjelland, I., Dahl, A. A., Haug, T. T., & Neckelmann, D. (2002). The validity of the hospital anxiety and depression scale, an updated literature review. Journal of Psychosomatic Research, 52, 69–77.

    Article  PubMed  Google Scholar 

  28. Illfeld, F. W. (1976). Further validation of a psychiatric symptom index in a normal population. Psychological Reports, 39, 1215–1228.

    Article  Google Scholar 

  29. Sullivan, J. L., Edgley, K., & Dehoux, E. (1990). A survey of multiple sclerosis. Part 1: Perceived cognitive problems and compensatory strategy use. Canadian Journal of Rehabilitation, 4(2), 99–105.

    Google Scholar 

  30. Gronwall, D. M. (1977). Paced auditory serial-addition task, a measure of recovery from concussion. Perceptual and Motor Skills, 44(2), 367–373.

    Article  CAS  PubMed  Google Scholar 

  31. Cella, D. F., Dineen, K., Arnason, B., Reder, A., Webster, K. A., & Karabatsos, G. (1996). Validation of the functional assessment of multiple sclerosis quality of life instrument. Neurology, 47, 129–139.

    Article  CAS  PubMed  Google Scholar 

  32. Ritvo, P., Fischer, J. S., Miller, D., Andrews, H., Paty, D., & LaRocca, N. G. (1997). Multiple sclerosis quality of life, A user’s manual. Denver: National Multiple Sclerosis Society.

    Google Scholar 

  33. Weinshenker, B. G., Bass, B., Rice, G. P. A., Noseworthy, J., Carriere, W., Baskerville, J., et al. (1989). The natural history of multiple sclerosis: A geographically based study. Brain, 112, 133–146.

    Article  PubMed  Google Scholar 

  34. Becker, H., Stuifbergen, A. K., & Sands, D. (1991). Development of a scale to measure barriers to health promotion activities among persons with disabilities. American Journal of Health Promotion, 5(6), 44–454.

    Article  Google Scholar 

  35. Poissant, L., Mayo, N. E., Wood-Dauphinee, S., & Clarke, A. E. (2003). The development and preliminary validation of a preference-based stroke index (PBSI). Health and Quality of Life Outcomes, 1, 15–43.

    Article  Google Scholar 

  36. Devins, G. M. (2010). Using the illness intrusiveness ratings scale to understand health-related quality of life in chronic disease. Journal of Psychosomatic Research, 68(6), 591–602.

    Article  PubMed  Google Scholar 

  37. Goldman, M. D., Marrie, R. A., & Cohen, J. A. (2008). Evaluation of the six-minute walk in multiple sclerosis subjects and healthy controls. Multiple Sclerosis Journal, 14(3), 383–390.

    Article  PubMed  Google Scholar 

  38. Tyson, S., & Connell, L. (2009). The psychometric properties and clinical utility of measures of walking and mobility in neurological conditions, a systematic review. Clinical Rehabilitation, 23(11), 1018–1033.

    Article  PubMed  Google Scholar 

  39. Tesio, L., Perucca, L., Franchignoni, F. P., & Battaglia, M. A. (1997). A short measure of balance in multiple sclerosis, validation through Rasch analysis. Functional Neurology, 12(5), 255–265.

    CAS  PubMed  Google Scholar 

  40. Bohannon, R. W., & Smith, M. B. (1987). Interrater reliability of a modified Ashworth scale of muscle spasticity. Physical Therapy, 67(2), 206–207.

    CAS  PubMed  Google Scholar 

  41. Health, C. S. E. P., Appraisal, F. P. H.-R., & Strategy, C. (2004). The Canadian physical activity, fitness and lifestyle approach (3rd ed.). Ontario: Canadian Society for Exercise Physiology.

    Google Scholar 

  42. Markovic, G., Dizdar, D., Jukic, I., & Cardinale, M. (2004). Reliability and factorial validity of squat and countermovement jump tests. Journal of Strength and Conditioning Research, 18(3), 551–555.

    PubMed  Google Scholar 

  43. Mathiowetz, V., Weber, K., Volland, G., & Kashman, N. (1984). Reliability and validity of grip and pinch strength evaluations. Journal of Hand Surgery. American Volume, 9(2), 222–226.

    Article  CAS  Google Scholar 

  44. Cano, S., Barrett, L., Zajicek, J., & Hobart, J. (2011). Beyond the reach of traditional analyses, using Rasch to evaluate the dash in people with multiple sclerosis. Multiple Sclerosis Journal, 17, 214–222.

    Article  CAS  PubMed  Google Scholar 

  45. Kline, R. B. (2011). Principles and practice of structural equation modeling (3rd ed.). New York: Guilford.

    Google Scholar 

  46. Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis, conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1–55.

    Article  Google Scholar 

  47. MacCallum, R. C., Browne, M. W., & Sugawara, H. M. (1996). Power analysis and determination of sample size for covariance structure modeling. Psychological Methods, 1, 130–149.

    Article  Google Scholar 

  48. Muthén, L. K., & Muthén, B. O. (1998–2012). Mplus User’s Guide (7th ed.). Los Angeles, CA: Muthén & Muthén.

  49. SAS 9.2 (computer program). (2008). Version 9.2. Cary, NC, SAS Institute Inc.

  50. Kempen, J. C. E., de Groot, V., Knol, D. L., Lankhorst, G. J., & Beckerman, H. (2012). Self-reported fatigue and energy cost during walking are not related in patients with multiple sclerosis. Archives of Physical Medicine and Rehabilitation, 93(5), 889–895.

    Article  PubMed  Google Scholar 

  51. Khan, F., Amatya, B., & Galea, M. (2014). Management of fatigue in persons with multiple sclerosis. Frontiers in Neurology, 15(5), 177.

    Google Scholar 

  52. Lapierre, Y., & Hum, S. (2007). Treating fatigue. The International MS Journal, 14, 64–71.

    CAS  PubMed  Google Scholar 

  53. Asano, M., & Finlayson, M. L. (2014). Meta-analysis of three different types of fatigue management interventions for people with multiple sclerosis: Exercise, education, and medication. Multiple Sclerosis International,. doi:10.1155/2014/798285. (Epub 2014 May 14).

    PubMed Central  PubMed  Google Scholar 

  54. Asano, M., Berg, E., Johnson, K., Turpin, M., & Finlayson, M. L. (2014). A scoping review of rehabilitation interventions that reduce fatigue among adults with multiple sclerosis. Disability and Rehabilitation, 37(9), 729–738.

    Article  PubMed  Google Scholar 

  55. Skerrett, T. N., & Moss-Morris, R. (2006). Fatigue and social impairment in multiple sclerosis, the role of patients’ cognitive and behavioral responses to their symptoms. Journal of Psychosomatic Research, 61(5), 587–593.

    Article  PubMed  Google Scholar 

  56. Van Kessel, K., & Moss-Morris, R. (2006). Understanding multiple sclerosis fatigue, a synthesis of biological and psychological factors. Journal of Psychosomatic Research, 61(5), 583–585.

    Article  PubMed  Google Scholar 

  57. Motl, R. W., Snook, E. M., & Schapiro, R. T. (2008). Symptoms and physical activity behavior in individuals with multiple sclerosis. Research in Nursing & Health, 31, 466–475.

    Article  Google Scholar 

  58. Shahrbanian, S., Duquette, P., Kuspinar, A., & Mayo, N. E. (2015). Consequences of symptom cluster in individuals with multiple sclerosis. Quality of Life Research Journal, 24(3), 617–629.

    Article  Google Scholar 

  59. Lublin, F. D., & Reingold, S. C. (1996). Defining the clinical course of multiple sclerosis: results of an international survey. National multiple sclerosis society (USA) advisory committee on clinical trials of new agents in multiple sclerosis. Neurology, 46(4), 907–911.

    Article  CAS  PubMed  Google Scholar 

  60. Mayo, N. E., Scott, S. C., & Bayley, M. (2015). Modeling health-related quality of life in people recovering from stroke. Quality of Life Research, 24(1), 41–53.

    Article  PubMed  Google Scholar 

  61. Multiple Sclerosis Society of Canada. (2009). www.mssociety.ca. Canada, MS Society of Canada.

  62. Mayo, N. (2008). Setting the agenda for multiple sclerosis rehabilitation research. Multiple Sclerosis Journal, 14(9), 1154–1156.

    Article  PubMed  Google Scholar 

  63. Leary, S., & Thompson, A. (2000). Current management of multiple sclerosis. International Journal of Clinical Practice, 54, 161–169.

    CAS  PubMed  Google Scholar 

Download references

Acknowledgments

Shahrbanian was a recipient of the Canadian Institutes of Health Research Award (Grant No. 218665). Authors also acknowledge the contribution of Ayse Kuspinar, Shang Yuan Teng, and Elaine Roger, who recruited patients from MNH, CNRS, and CHUM, respectively.

Author information

Authors and Affiliations

  1. Faculty of Medicine, School of Physical and Occupational Therapy, McGill University Health Center, McGill University, Royal Victoria Hospital Site, Ross Pavilion R4.27, 687 Pine Ave W, Montreal, QC, H3A 1A1, Canada

    Shahnaz Shahrbanian, Sara Ahmed & Nancy E. Mayo

  2. Faculty of Physical Education and Sport Science, Buali Sina University, Hamedan, Iran

    Shahnaz Shahrbanian

  3. Notre-Dame Hospital (CHUM), University of Montreal, Montreal, Canada

    Pierre Duquette

  4. Division of Clinical Epidemiology, McGill University Health Center, Royal Victoria Hospital, Montreal, Canada

    Sara Ahmed & Nancy E. Mayo

Authors
  1. Shahnaz Shahrbanian
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Pierre Duquette
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sara Ahmed
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Nancy E. Mayo
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Shahnaz Shahrbanian.

Ethics declarations

Conflict of interest

The authors declare that there is no conflict of interest.

Ethical standard

Study protocol and procedures were approved by the ethics committee of each participating hospital, and informed consent was obtained and signed by all subjects on the day of testing.

Appendix

Appendix

See Table 7.

Table 7 Measures included in analyses
Full size table

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Shahrbanian, S., Duquette, P., Ahmed, S. et al. Pain acts through fatigue to affect participation in individuals with multiple sclerosis. Qual Life Res 25, 477–491 (2016). https://doi.org/10.1007/s11136-015-1098-0

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11136-015-1098-0

Keywords

Search

Navigation