Advertisement

Quality of Life Research

, Volume 21, Issue 6, pp 1021–1030 | Cite as

A PROMIS fatigue short form for use by individuals who have multiple sclerosis

  • Karon F. Cook
  • Alyssa M. Bamer
  • Toni S. Roddey
  • George H. Kraft
  • Jiseon Kim
  • Dagmar Amtmann
Original Paper

Abstract

Purpose

To derive from the Patient Reported Outcomes Measurement Information System (PROMIS) fatigue item bank, a short form for individuals with multiple sclerosis (MS), the PROMIS-FatigueMS.

Methods

A panel of 37 clinicians and 46 individuals with MS ranked the relevance of PROMIS fatigue items to persons with MS. Eight items were selected for the PROMIS-FatigueMS that maximized relevance rankings, content coverage, and item discrimination. The PROMIS-FatigueMS and an existing, 7-item PROMIS fatigue short form (PROMIS-FatigueSFv1.0) were administered to a new sample of 231 individuals with MS. Known groups and content validity were assessed.

Results

Scores from the short forms were highly correlated (r = 0.92). Discriminant validity of the PROMIS-FatigueMS scores was supported in known groups comparisons. Scores of neither short form exhibited an advantage in quantitative analyses. The PROMIS-FatigueMS targeted more of the content included in participants’ responses to open-ended questions than did the PROMIS-FatigueSFv1.0.

Conclusions

The PROMIS-FatigueMS was derived to have content validity in MS samples. The validity of the measure was further supported by the ability of PROMIS-FatigueMS items to discriminate among groups expected to differ in levels of fatigue. We recommend its use in measuring the fatigue of individuals with MS.

Keywords

Multiple sclerosis Fatigue Outcomes assessment Psychometrics 

Abbreviations

MS

Multiple sclerosis

PROMIS-Fatigue SFv1.0

PROMIS 7-item fatigue short form, Version 1.0

PROMIS

Patient Reported Outcome Measurement Information System

U.S.

United States

IRT

Item response theory

UW

University of Washington, Seattle

RI

Relevance index

RI-MS20

RI value based on participant rankings of 20 PROMIS items

RI-EX44

RI value based on expert clinician rankings of 44 PROMIS items

EDSS

Expanded Disability Status Scores

SF8

8-item Health Survey Short Form

References

  1. 1.
    National Multiple Sclerosis Society (2008). Clinical study measures: Mental health inventory. [cited June 27, 2008]; Available from: http://www.nationalmssociety.org/for-professionals/researchers/clinical-study-measures/mhi/index.Aspx. National Multiple Sclerosis Society.
  2. 2.
    Chwastiak, L. A., Gibbons, L. E., Ehde, D. M., Sullivan, M., Bowen, J. D., Bombardier, C. H., et al. (2005). Fatigue and psychiatric illness in a large community sample of persons with multiple sclerosis. Journal of Psychosomatic Research, 59(5), 291–298.PubMedCrossRefGoogle Scholar
  3. 3.
    Kraft, G. H., Freal, J. E., & Coryell, J. K. (1986). Disability, disease duration, and rehabilitation service needs in multiple sclerosis: Patient perspectives. Archives of Physical Medicine and Rehabilitation, 67(3), 164–168.PubMedCrossRefGoogle Scholar
  4. 4.
    Amato, M. P., Ponziani, G., Rossi, F., Liedl, C. L., Stefanile, C., & Rossi, L. (2001). Quality of life in multiple sclerosis: The impact of depression, fatigue and disability. Multiple Sclerosis, 7(5), 340–344.PubMedGoogle Scholar
  5. 5.
    Johnson, S. L. (2008). The concept of fatigue in multiple sclerosis. The Journal of Neuroscience Nursing, 40(2), 72–77.PubMedCrossRefGoogle Scholar
  6. 6.
    Fisk, J. D., Pontefract, A., Ritvo, P. G., Archibald, C. J., & Murray, T. J. (1994). The impact of fatigue on patients with multiple sclerosis. Canadian Journal of Neurological Sciences, 21(1), 9–14.PubMedGoogle Scholar
  7. 7.
    O’Connor, A. B., Schwid, S. R., Herrmann, D. N., Markman, J. D., & Dworkin, R. H. (2008). Pain associated with multiple sclerosis: Systematic review and proposed classification. Pain, 137(1), 96–111.PubMedCrossRefGoogle Scholar
  8. 8.
    Pompeii, L. A., Moon, S. D., & McCrory, D. C. (2005). Measures of physical and cognitive function and work status among individuals with multiple sclerosis: A review of the literature. Journal of Occupational Rehabilitation, 15(1), 69–84.PubMedCrossRefGoogle Scholar
  9. 9.
    Hubsky, E. P., & Sears, J. H. (1992). Fatigue in multiple sclerosis: Guidelines for nursing care. Rehabilitation Nursing, 17(4), 176–180.PubMedGoogle Scholar
  10. 10.
    Cook, K. F., O’Malley, K. J., & Roddey, T. S. (2005). Dynamic assessment of health outcomes: Time to let the cat out of the bag? Health Services Research, 40(5 Pt 2), 1694–1711.PubMedCrossRefGoogle Scholar
  11. 11.
    Cella, D., Yount, S., Rothrock, N., Gershon, R., Cook, K., Reeve, B., et al. (2007). The patient-reported outcomes measurement information system (PROMIS): Progress of an NIH roadmap cooperative group during its first two years. Medical Care, 45(5 Suppl 1), S3–S11.PubMedCrossRefGoogle Scholar
  12. 12.
    Rothrock, N., Hays, R. D., Spritzer, K., Yount, S. E., Riley, W., & Cella, D. (2010). Relative to the general us population, chronic diseases are associated with poorer health-related quality of life as measured by the patient-reported outcomes measurement information system (PROMIS). Journal of Clinical Epidemiology, 63(11), 1195–1204.PubMedCrossRefGoogle Scholar
  13. 13.
    Riley, W. T., Rothrock, N., Bruce, B., Christodolou, C., Cook, K., Hahn, E. A., et al. (2010). Patient-reported outcomes measurement information system (PROMIS) domain names and definitions revisions: Further evaluation of content validity in irt-derived item banks. Quality of Life Research, 19(9), 1311–1321.PubMedCrossRefGoogle Scholar
  14. 14.
    Lai, J.-S., Cella, D., Choi, S., Junghaenel, D. U., Christodoulou, C., Gershon, R., et al. (in press). How item banks and their applications can influence measurement practice in rehabilitation medicine: A PROMIS fatigue item bank example. Archives of Physical Medicine and Rehabilitation.Google Scholar
  15. 15.
    U.S. Department of Health and Human Services Food and Drug Administration. (2009). http://www.fda.gov/downloads/drugs/guidancecomplianceregulatoryinformation/guidances/ucm193282.pdf.
  16. 16.
    Yellen, S. B., Cella, D. F., Webster, K., Blendowski, C., & Kaplan, E. (1997). Measuring fatigue and other anemia-related symptoms with the functional assessment of cancer therapy (FACT) measurement system. Journal of Pain and Symptom Management, 13(2), 63–74.PubMedCrossRefGoogle Scholar
  17. 17.
    Amtmann, D., Cook, K. F., Johnson, K. L., Cella, D. (in press). The PROMIS initiative: Examples of applications in rehabilitation. Archives of Physical and Medical Rehabilitation.Google Scholar
  18. 18.
    Bamer, A. M., Johnson, K. L., Amtmann, D. A., & Kraft, G. H. (2010). Beyond fatigue: Assessing variables associated with sleep problems and use of sleep medications in multiple sclerosis. Clinical Epidemiology, 2010(2), 99–106.PubMedCrossRefGoogle Scholar
  19. 19.
    Belza, B. L., Henke, C. J., Yelin, E. H., Epstein, W. V., & Gilliss, C. L. (1993). Correlates of fatigue in older adults with rheumatoid arthritis. Nursing Research, 42(2), 93–99.PubMedCrossRefGoogle Scholar
  20. 20.
    Bowen, J., Gibbons, L., Gianas, A., & Kraft, G. H. (2001). Self-administered expanded disability status scale with functional system scores correlates well with a physician-administered test. Multiple Sclerosis, 7(3), 201–206.PubMedGoogle Scholar
  21. 21.
    Ware, J. E., Kosinski, M., Dewey, J. E., & Gandek, B. (2001). A manual for users of the sf-8 health survey. Lincoln, RI: Quality Metric Incorporated.Google Scholar
  22. 22.
    Flora, D. B., Thissen, D. (2002). User’s guide for IRTScore: Item response theory score approximation Software. Electronic Research Memorandum #2002-1. Chapel Hill, NC: University of North Carolina, L.L. Thurstone Psychometric Laboratory.Google Scholar
  23. 23.
    Bland, J. M., & Altman, D. G. (1986). Statistical methods for assessing agreement between two methods of clinical measurement. Lancet, 1(8476), 307–310.PubMedCrossRefGoogle Scholar
  24. 24.
    Given, B., Given, C. W., Sikorskii, A., Jeon, S., McCorkle, R., Champion, V., et al. (2008). Establishing mild, moderate, and severe scores for cancer-related symptoms: How consistent and clinically meaningful are interference-based severity cut-points? Journal of Pain and Symptom Management, 35(2), 126–135.PubMedCrossRefGoogle Scholar
  25. 25.
    Cella, D., Riley, W., Stone, A., Rothrock, N., Reeve, B., Yount, S., et al. (2010). The patient-reported outcomes measurement information system (PROMIS) developed and tested its first wave of adult self-reported health outcome item banks: 2005–2008. Journal of Clinical Epidemiology, 63(11), 1179–1194.PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Karon F. Cook
    • 1
  • Alyssa M. Bamer
    • 2
  • Toni S. Roddey
    • 3
  • George H. Kraft
    • 2
  • Jiseon Kim
    • 2
  • Dagmar Amtmann
    • 2
  1. 1.Northwestern UniversityChicagoUSA
  2. 2.University of WashingtonSeattleUSA
  3. 3.Texas Woman’s UniversityHoustonUSA

Personalised recommendations