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Journal of Neurology

, 257:103 | Cite as

Characterization of functioning in multiple sclerosis using the ICF

  • Lisa Holper
  • Michaela Coenen
  • Andrea Weise
  • Gerold Stucki
  • Alarcos Cieza
  • Jürg Kesselring
Original Communication

Abstract

The objective of this study was to explore whether it is possible to describe based on the International Classification of Functioning, Disability and Health (ICF) relevant aspects of functioning and disability affected in multiple sclerosis (MS) as well as environmental factors relevant to persons with MS. The specific aim was to identify most relevant ‘Body functions’, ‘Body structures’, ‘Activities and participation’, as well as ‘Environmental factors’ in patients with MS using the ICF. Additionally, different MS forms were compared with respect to the identified problems. A multi-centre study was conducted in an empirical cross-sectional design. Data from 205 individuals with MS were collected in rehabilitation centres: disease related data, socio-demographic data, single interviews based on the Extended ICF Checklist and a patient questionnaire including ratings on general health and functioning status, Beck Depression Inventory II (BDI-II) and Comorbidity Questionnaire (SCQ). The 129 ICF categories identified represent a comprehensive classification of functioning in MS from the clinical perspective. Differences between MS forms were observed for several ICF categories, EDSS, general health and functioning status, but not for BDI and SCQ. The study showed that it is possible to describe based on the ICF the spectrum in functioning and disability affected in MS as well as environmental factors relevant to persons with MS.

Keywords

Multiple sclerosis Rehabilitation Relapsing Remitting Progressive Empirical study Clinical perspective International Classification of Functioning, Disability and Health (ICF) 

Notes

Acknowledgment

The project was supported by the Hertie Foundation (“Gemeinnützige Hertie-Stiftung”) as a cooperative project between the Classification, Terminology and Standards (CTS) Team of WHO, Department of Neurorehabilitation, Valens Rehabilitation Centre, Valens (Switzerland), the Institute for Health and Rehabilitation Sciences, ICF Research Branch of WHO at the Ludwig-Maximilian University Munich (Germany), the Multiple Sclerosis International Federation (MSIF), and the International Society of Physical Medicine and Rehabilitation (ISPMR). For the conduction of the statistical analysis the authors thank Cornelia Oberhauser, Institute for Health and Rehabilitation Sciences (IHRS), ICF Research Branch of WHO at the Ludwig-Maximilian University, Munich (Germany). The authors further thank all participating clinics and rehabilitation centers involved in data collection, the University Hospital Zurich (Switzerland), the Swiss Multiple Sclerosis Society, Zurich (Switzerland) and the Neurological Rehabilitation Center Quellenhof, Bad Wildbad (Germany).

Conflict of interest statement

None.

References

  1. 1.
    Amato MP, Zipoli V, Portaccio E (2006) Multiple sclerosis-related cognitive changes: a review of cross-sectional and longitudinal studies. J Neurol Sci 245:41–46CrossRefPubMedGoogle Scholar
  2. 2.
    Avasarala J, Cross A, Trinkaus K (2003) Comparative assessment of yale single question and beck depression inventory scale in screening for depression in multiple sclerosis. Multiple Scler 9:307–310CrossRefGoogle Scholar
  3. 3.
    Beck A, Steer R, Brown G (1996) Manual for beck depression inventory-II—manual. The Psychological Corporation, San AntonioGoogle Scholar
  4. 4.
    Beck A, Ward C, Mendelson M, Mock J, Erbaugh J (1961) An inventory for measuring depression. Arch Gen Psychia 4:53–63Google Scholar
  5. 5.
    Beiske A, Svensson E, Sandanger I, Czujko B, Pedersen E, Aarseth J, Myhr K (2008) Depression and anxiety amongst multiple sclerosis patients. Eur J Neurol 15:329–345CrossRefGoogle Scholar
  6. 6.
    Clingerman E, Stuifbergen A, Becker H (2004) The influence of resources on perceived functional limitations among women with multiple sclerosis. J Neurosci Nurs 36:312–321CrossRefPubMedGoogle Scholar
  7. 7.
    Ewert T, Fuessl M, Cieza A, Anderson C (2004) Identification of the most common problems in patients with chronic conditions using the ICF checklist. J Rehabil Med Suppl 44:22–29CrossRefGoogle Scholar
  8. 8.
    Flachenecker P, Rieckmann P (2004) Health outcome in multiple sclerosis. Curr Opin Neurol 17:257–261CrossRefPubMedGoogle Scholar
  9. 9.
    Fraser C, Polito S (2007) A comparative study of self-efficacy in men and women with multiple sclerosis. J Neurosci Nurs 39:102–106CrossRefPubMedGoogle Scholar
  10. 10.
    Green G, Todd J, Pevalin D (2007) Biographical disruption associated with multiple sclerosis: using propensity scoring to assess the impact. Soc Sci Med 65:524–535CrossRefPubMedGoogle Scholar
  11. 11.
    Hastie T, Tibshirani R, Friedman J (2008) The elements of statistical learning: data mining, inference, and prediction. New YorkGoogle Scholar
  12. 12.
    Hautzinger M, Keller F, Kühner C (2006) BDI-II—beck depressions-inventar 2. Auflage Harcourt Test Services, Frankfurt/MainGoogle Scholar
  13. 13.
    Heesen C, Böhm J, Reich C, Kasper J, Goebel M, Gold S (2008) Patient perception of bodily functions in multiple sclerosis: gait and visual function are the most valuable. Multiple Scler 14:988–991CrossRefGoogle Scholar
  14. 14.
    Johansson S, Ytterberg C, Claesson I, Lindberg J, Hillert J, Andresson M, Widén Holmqvist L, von Koch L (2007) High concurrent presence of disability in multiple sclerosis. J Neurol 254:767–773CrossRefPubMedGoogle Scholar
  15. 15.
    Julian L, Merluzzi N, Mohr D (2007) The relationship among depression, subjective cognitive impairment, and neuropsychological performance in multiple sclerosis. Multiple Scler 13:81–86CrossRefGoogle Scholar
  16. 16.
    Kesselring J, Beer S (2005) Symptomatic therapy and neurorehabilitation in multiple sclerosis. Lancet Neurol 4:643–652CrossRefPubMedGoogle Scholar
  17. 17.
    Kira J, Tobimatsu S, Goto I, Hasuo K (1993) Primary progressive versus relapsing remitting multiple sclerosis in Japanese patients: a combined clinical, magnetic resonance imaging and multimodality evoked potential study. J Neurol Sci 117:179–185CrossRefPubMedGoogle Scholar
  18. 18.
    Kobelt G, Berg J, Lindgren P, Fredrikson S, Jönsson B (2006) Costs and quality of life of patients with multiple sclerosis in Europe. J Neurol Neurosurg Psychiatry 77:918–926CrossRefPubMedGoogle Scholar
  19. 19.
    Lobentanz I, Asenbaum S, Vaas K, Sauter C, Klösch G, Kollegger H, Kristoferitsch W, Zeitlhofer J (2004) Factors influencing quality of life in multiple sclerosis patients: disability, depressive mood, fatique and sleep quality. Acta Neurol Scand 110:6–13CrossRefPubMedGoogle Scholar
  20. 20.
    MacAllister W, Krupp L (2005) Multiple sclerosis-related fatique. Phys Med Rehabil Clin N Am 16:483–502PubMedGoogle Scholar
  21. 21.
    Marrow T (2007) The costs and consequences of multiple sclerosis relapses: a managed care perspective. J Neurol Sci 15:S39–S44CrossRefGoogle Scholar
  22. 22.
    Nortvedt M, Riise T, Fruqård J, Mohn J, Bakke A, Skår A, Nyland H, Glad S, Myhr K (2007) Prevalence of bladder, bowel and sexual problems among multiple sclerosis patients two to five years after diagnosis. Multiple Scler 13:106–112CrossRefGoogle Scholar
  23. 23.
    Osborne T, Jensen M, Ehde D, Hanley M, Kraft G (2007) Psychological factors associated with pain intensity, pain-related interference, and psychological functioning in persons with multiple sclerosis and pain. Pain 127:52–62CrossRefPubMedGoogle Scholar
  24. 24.
    Polman C, Reingold S, Edan G, Filippi M, Hartung H-P, Kappos L, Lublin F, Metz L, McFarland H, O’Connor P, Sandberg-Wollheim M, Thompson A, Weinshenker B, Wolinsky J (2005) Diagnostic criteria for multiple sclerosis: 2005 revisions to the “McDonald criteria”. Ann Neurol 58:840–846CrossRefPubMedGoogle Scholar
  25. 25.
    Poser C, Paty D, Scheinberg L, McDonald W, Davis F, Ebers G, Johnson K, Sibley W, Silberberg D, Tourtellotte W (1983) New diagnostic criteria for multiple sclerosis: guidelines for research protocols. Ann Neurol 13:227–231CrossRefPubMedGoogle Scholar
  26. 26.
    Potagas C, Giogkaraki E, Koutsis G, Mandellos D, Tsirempolou E, Sfagos C, Vassilopoulos D (2008) Cognitive impairment in different MS subtypes and clinically isolated syndromes. J Neurol Sci 267:100–106CrossRefPubMedGoogle Scholar
  27. 27.
    Putzki N, Katsarava Z, Vago S, Diener H, Limmroth V (2008) Prevalence and severity of multiple-sclerosis-associated fatigue in treated and untreated patients. Eur Neurol 59:136–142CrossRefPubMedGoogle Scholar
  28. 28.
    Rashid W, Hadjiprocopis A, Davies G, Griffin C, Chard D, Tiberio M, Altmann D, Wheeler-Kingshott C, Tozer D, Thompson A, Miller D (2008) Longitudinal evaluation of clinically early relapsing-remitting multiple sclerosis with diffusion tensor imaging. J Neurol 255:390–397CrossRefPubMedGoogle Scholar
  29. 29.
    Rot U, Mesec A (2006) Clinical, MRI, CSF and electrophysiological findings in different stages of multiple sclerosis. Clin Neurol Neurosurg 108:271–274CrossRefPubMedGoogle Scholar
  30. 30.
    Sá M (2007) Psychological aspects of multiple sclerosis. Clin Neurol Neurosurg (in press)Google Scholar
  31. 31.
    Sangha O, Stucki G, Liang M, Fossel A, Katz J (2003) The self-administered comorbidity questionnaire: a new method to assess comorbidity for clinical and health services research. Arthritis Rheum 49:156–163CrossRefPubMedGoogle Scholar
  32. 32.
    Simioni S, Ruffieux C, Bruggimann L, Annoni J, Schluep M (2007) Cognition, mood and fatigue in patients in the early stage of multiple sclerosis. Swiss Med Wkly 137:496–501PubMedGoogle Scholar
  33. 33.
    Thompson A (2004) Overview of primary progressive multiple sclerosis (PPMS): similarities and differences from other forms of MS, diagnostic criteria, pros and cons of progressive diagnosis. Multiple Scler 10:S2–S7CrossRefGoogle Scholar
  34. 34.
    Turpin K, Carroll L, Cassidy J, Hader W (2007) Deterioration in the health-related quality of life of persons with multiple sclerosis: the possible warning signs. Multiple Scler 13:1038–1045CrossRefGoogle Scholar
  35. 35.
    Ustun B, Chatterji S, Bickenbach J, Konstansjek N, Schneider M (2001) The World Health Classification, ICIDH-2 checklist 2.1a clinical form for international classification of functioning, disability and health. ICF, GenevaGoogle Scholar
  36. 36.
    Vleugels L, Pfennings L, Pouwer F, Cohen L, Ketelaer P, Polman C, Lankhorst G, van der Ploeg H (1998) Psychological functioning in primary progressive versus secondary progressive multiple sclerosis. Br J Med Psychol 71:99–106PubMedGoogle Scholar
  37. 37.
    WHO (2004) Atlas: country resources for neurological disorders. WHO, GenevaGoogle Scholar
  38. 38.
    WHO (2001) International Classification of Functioning, Disability and Health: ICF. WHO, GenevaGoogle Scholar
  39. 39.
    Yuan M, Lin Y (2006) Model selection and estimation in regression with grouped variables. J R Stat Soc B 68:49–67CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2009

Authors and Affiliations

  • Lisa Holper
    • 1
  • Michaela Coenen
    • 2
  • Andrea Weise
    • 1
  • Gerold Stucki
    • 3
    • 4
    • 5
  • Alarcos Cieza
    • 2
    • 5
  • Jürg Kesselring
    • 1
  1. 1.Department of Neurology and NeurorehabilitationRehabilitation Centre ValensValensSwitzerland
  2. 2.Institute for Health and Rehabilitation Sciences (IHRS), ICF Research Branch, WHO FIC Collaborating Center (DIMDI)Ludwig-Maximilian UniversityMunichGermany
  3. 3.ICF Research Branch of WHO FIC CC (DIMDI) at SPF Nottwil, Switzerland and at IHRSLudwig Maximilian UniversityMunichGermany
  4. 4.Seminar of Health Sciences and Health PolicyUniversity of LucerneLucerneSwitzerland
  5. 5.Swiss Paraplegic ResearchNottwilSwitzerland

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