Skip to main content
SpringerLink
Log in

Psychometric properties of the PROMIS® Fatigue Short Form 7a among adults with myalgic encephalomyelitis/chronic fatigue syndrome

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

Abstract

Purpose

To evaluate the psychometric properties of the Patient-Reported Outcome Measurement Information System® Fatigue Short Form 7a (PROMIS F-SF) among people with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS).

Methods

Analyses were conducted using data from the Multi-Site Clinical Assessment of ME/CFS study, which recruited participants from seven ME/CFS specialty clinics across the US. Baseline and follow-up data from ME/CFS participants and healthy controls were used. Ceiling/Floor effects, internal consistency reliability, differential item functioning (DIF), known-groups validity, and responsiveness were examined.

Results

The final sample comprised 549 ME/CFS participants at baseline, 386 of whom also had follow-up. At baseline, the sample mean of PROMIS F-SF T-score was 68.6 (US general population mean T-score of 50 and standard deviation of 10). The PROMIS F-SF demonstrated good internal consistency reliability (Cronbach’s α = 0.84) and minimal floor/ceiling effects. No DIF was detected by age or sex for any item. This instrument also showed good known-groups validity with medium-to-large effect sizes (η2 = 0.08–0.69), with a monotonic increase of the fatigue T-score across ME/CFS participant groups with low, medium, and high functional impairment as measured by three different variables (p < 0.01), and with significantly higher fatigue T-scores among ME/CFS participants than healthy controls (p < 0.0001). Acceptable responsiveness was found with small-to-medium effect sizes (Guyatt’s Responsiveness Statistic = 0.28–0.54).

Conclusions

Study findings support the reliability and validity of PROMIS F-SF as a measure of fatigue for ME/CFS and lend support to the drug development tool submission for qualifying this measure to evaluate therapeutic effect in ME/CFS clinical trials.

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

Similar content being viewed by others

References

  1. Clayton, E. W. (2015). Beyond myalgic encephalomyelitis/chronic fatigue syndrome: An IOM report on redefining an illness. JAMA,313(11), 1101–1102. https://doi.org/10.1001/jama.2015.1346.

    Article  CAS  PubMed  Google Scholar 

  2. United States Food and Drug Administration. (2013). The voice of the patient: Chronic fatigue syndrome and myalgic encephalomyelitis. Bethesda: United States Food and Drug Administration.

    Google Scholar 

  3. Afari, N., & Buchwald, D. (2003). Chronic fatigue syndrome: A review. American Journal of Psychiatry,160(2), 221–236. https://doi.org/10.1176/appi.ajp.160.2.221.

    Article  PubMed  Google Scholar 

  4. Jason, L. A., Richman, J. A., Rademaker, A. W., Jordan, K. M., Plioplys, A. V., Taylor, R. R., et al. (1999). A community-based study of chronic fatigue syndrome. Archives of Internal Medicine,159(18), 2129–2137.

    Article  CAS  PubMed  Google Scholar 

  5. Reyes, M., Nisenbaum, R., Hoaglin, D. C., et al. (2003). Prevalence and incidence of chronic fatigue syndrome in Wichita, Kansas. Archives of Internal Medicine,163(13), 1530–1536. https://doi.org/10.1001/archinte.163.13.1530.

    Article  PubMed  Google Scholar 

  6. Reeves, W. C., Jones, J. F., Maloney, E., Heim, C., Hoaglin, D. C., Boneva, R. S., et al. (2007). Prevalence of chronic fatigue syndrome in metropolitan, urban, and rural Georgia. Popul Health Metr,5, 5. https://doi.org/10.1186/1478-7954-5-5.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Lin, J. S., Resch, S. C., Brimmer, D. J., Johnson, A., Kennedy, S., Burstein, N., et al. (2011). The economic impact of chronic fatigue syndrome in Georgia: Direct and indirect costs. Cost Effectiveness and Resource Allocation,9(1), 1. https://doi.org/10.1186/1478-7547-9-1.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Reynolds, K. J., Vernon, S. D., Bouchery, E., & Reeves, W. C. (2004). The economic impact of chronic fatigue syndrome. Cost Effectiveness and Resource Allocation,2, 4. https://doi.org/10.1186/1478-7547-2-4.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Jason, L. A., Benton, M. C., Valentine, L., Johnson, A., & Torres-Harding, S. (2008). The economic impact of ME/CFS: Individual and societal costs. Dynamic Medicine,7, 6. https://doi.org/10.1186/1476-5918-7-6.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Fukuda, K., Straus, S. E., Hickie, I., Sharpe, M. C., Dobbins, J. G., & Komaroff, A. (1994). The chronic fatigue syndrome: A comprehensive approach to its definition and study International. Chronic Fatigue Syndrome Study Group. Annals of Internal Medicine,121(12), 953–959.

    Article  CAS  PubMed  Google Scholar 

  11. Carruthers, B. M., Jain, A. K., De Meirleir, K. L., Peterson, D. L., Klimas, N. G., Lerner, A. M., et al. (2003). Myalgic encephalomyelitis/chronic fatigue syndrome: Clinical working case definition, diagnostic and treatment protocols. Journla of Chronic Fatigue Syndrome,11(1), 7–115.

    Article  Google Scholar 

  12. Carruthers, B. M., van de Sande, M. I., De Meirleir, K. L., Klimas, N. G., Broderick, G., Mitchell, T., et al. (2011). Myalgic encephalomyelitis: International consensus criteria. Journal of Internal Medicine,270(4), 327–338. https://doi.org/10.1111/j.1365-2796.2011.02428.x.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Lai, J.-S., Cella, D., Choi, S., Junghaenel, D. U., Christodoulou, C., Gershon, R., et al. (2011). How item banks and their application can influence measurement practice in rehabilitation medicine: A PROMIS fatigue item bank example. Archives of Physical Medicine and Rehabilitation,92(10.0), S20–S27. https://doi.org/10.1016/j.apmr.2010.08.033.

    Article  PubMed  PubMed Central  Google Scholar 

  14. National Institutes of Health (2007). PROMIS domain framework/definitions. http://www.nihpromis.org/measures/domainframework.

  15. Smets, E. M. A., Garssen, B., Bonke, B., & De Haes, J. C. J. M. (1995). The Multidimensional Fatigue Inventory (MFI) Psychometric Qualities of an Instrument to Assess Fatigue. Journal of Psychosomatic Research,39(3), 315–325. https://doi.org/10.1016/0022-3999(94)00125-O.

    Article  CAS  PubMed  Google Scholar 

  16. Chalder, T., Berelowitz, G., Pawlikowska, T., Watts, L., Wessely, S., Wright, D., et al. (1993). Development of a fatigue scale. Journal of Psychosomatic Research,37(2), 147–153.

    Article  CAS  PubMed  Google Scholar 

  17. Khanna, D., Maranian, P., Rothrock, N., Cella, D., Gershon, R., Khanna, P. P., et al. (2012). Feasibility and construct validity of PROMIS and legacy Instruments in an Academic Scleroderma Clinic—Analysis from the UCLA Scleroderma Quality of Life Study. Value Health,15(1), 128–134. https://doi.org/10.1016/j.jval.2011.08.006.

    Article  PubMed  Google Scholar 

  18. US Department of Health and Human Services Food and Drug Administration. (2009). Guidance for industry: Patient-reported outcome measures: Use in medical product development to support labeling claims. https://www.fda.gov/regulatory-information/search-fda-guidance-documents/patient-reported-outcome-measures-use-medical-product-development-support-labeling-claims.

  19. Unger, E. R., Lin, J.-M. S., Tian, H., Natelson, B. H., Lange, G., Vu, D., et al. (2017). Multi-site clinical assessment of myalgic encephalomyelitis/chronic fatigue syndrome (MCAM): Design and Implementation of a prospective/retrospective rolling cohort study. American Journal of Epidemiology,185(8), 617–626. https://doi.org/10.1093/aje/kwx029.

    Article  PubMed  Google Scholar 

  20. Bjorner, J. B., Rose, M., Gandek, B., Stone, A. A., Junghaenel, D. U., & Ware, J. E., Jr. (2014). Method of administration of PROMIS scales did not significantly impact score level, reliability, or validity. Journal of Clinical Epidemiology,67(1), 108–113. https://doi.org/10.1016/j.jclinepi.2013.07.016.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Embretson, S. E., & Reise, S. P. (2013). Item response theory. Rotterdam: Psychology Press.

    Book  Google Scholar 

  22. Liu, H., Cella, D., Gershon, R., Shen, J., Morales, L. S., Riley, W., et al. (2010). Representativeness of the PROMIS Internet Panel. Journal of Clinical Epidemiology,63(11), 1169–1178. https://doi.org/10.1016/j.jclinepi.2009.11.021.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Cai, L., Thissen, D., & du Toit, S. H. C. (2011). IRTPRO: Flexible, multidimensional, multiple categorical IRT modeling. Lincolnwood, IL: Scientific Software International.

    Google Scholar 

  24. SAS Institute Inc. (2002–2014). SAS®9.4 Help and Documentation. Cary, NC: SAS Institute Inc.

  25. Wang, L., Zhang, Z., McArdle, J. J., & Salthouse, T. A. (2009). Investigating ceiling effects in longitudinal data analysis. Multivariate Behav Res,43(3), 476–496. https://doi.org/10.1080/00273170802285941.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Terwee, C. B., Bot, S. D., de Boer, M. R., van der Windt, D. A., Knol, D. L., Dekker, J., et al. (2007). Quality criteria were proposed for measurement properties of health status questionnaires.,60(1), 34–42.

    Google Scholar 

  27. Nunnally, J., & Bernstein, I. (1978). Psychometric Theory McGraw-Hill New York Google Scholar.

  28. Lohr, K N J Qo L R. (2002). Assessing health status and quality-of-life instruments: Attributes and review criteria. Quality of Life,11(3), 193–205.

    Article  Google Scholar 

  29. Bartlett, S. J., Orbai, A.-M., Duncan, T., DeLeon, E., Ruffing, V., Clegg-Smith, K., et al. (2015). Reliability and validity of selected PROMIS measures in people with rheumatoid arthritis. PLoS ONE,10(9), e0138543.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Yost, K. J., Eton, D. T., Garcia, S. F., & Cella, D. J. J. O. C. E. (2011). Minimally important differences were estimated for six Patient-Reported Outcomes Measurement Information System-Cancer scales in advanced-stage cancer patients. Journal of Clinical Epidemiology,64(5), 507–516.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Lord, F. M. (1980). Applications of item response theory to practical testing problems. Hillsdale, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  32. Langer, M. M. (2008). A Reexamination of Lord’s Wald Test for Differential Item Functioning Using Item Response Theory and Modern Error Estimation. Doctoral Dissertation, University of North Carolina at Chapel Hill.

  33. Rusu, C., Gee, M. E., Lagacé, C., & Parlor, M. (2015). Chronic fatigue syndrome and fibromyalgia in Canada: Prevalence and associations with six health status indicators. Health Promotion and Chronic Disease Prevention in Canada: Research, Policy and Practice,35(1), 3–11.

    Article  CAS  Google Scholar 

  34. Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society. Series B (Methodological),57(1), 289–300.

    Article  Google Scholar 

  35. Thissen, D., Steinberg, L., & Kuang, D. (2002). Quick and easy implementation of the Benjamini-Hochberg procedure for controlling the false positive rate in multiple comparisons. Journal of Educational and Behavioral Statistics,27(1), 77–83. https://doi.org/10.3102/10769986027001077.

    Article  Google Scholar 

  36. Tukey, J. W. (1949). Comparing individual means in the analysis of variance. Biometrics,5(2), 99–114. https://doi.org/10.2307/3001913.

    Article  CAS  PubMed  Google Scholar 

  37. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  38. Miles, J., & Shevlin, M. (2001). Applying regression & correlation: A guide for students and researchers (1st ed.). Thousand Oaks, CA: Sage.

    Google Scholar 

  39. Badhiwala, J. H., Witiw, C. D., Nassiri, F., Akbar, M. A., Jaja, B., Wilson, J. R., et al. (2018). Minimum clinically important difference in SF-36 scores for use in degenerative cervical myelopathy. Spine. https://doi.org/10.1097/brs.0000000000002684.

    Article  PubMed  Google Scholar 

  40. Swigris, J. J., Brown, K. K., Behr, J., du Bois, R. M., King, T. E., Raghu, G., et al. (2010). The SF-36 and SGRQ: Validity and first look at minimum important differences in IPF. Respiratory Medicine,104(2), 296–304. https://doi.org/10.1016/j.rmed.2009.09.006.

    Article  PubMed  Google Scholar 

  41. Ward, M. M., Guthrie, L. C., & Alba, M. I. (2014). Clinically important chances in short form-36 scales for use in rheumatoid arthritis clinical trials: The impact of low responsiveness. Arthritis Care & Research,66(12), 1783–1789. https://doi.org/10.1002/acr.22392.

    Article  Google Scholar 

  42. Norman, G. R., Sloan, J. A., & Wyrwich, K. W. (2003). Interpretation of changes in health-related quality of life: The remarkable universality of half a standard deviation. Medical Care,41(5), 582–592. https://doi.org/10.1097/01.mlr.0000062554.74615.4c.

    Article  PubMed  Google Scholar 

  43. Guyatt, G., Walter, S., & Norman, G. (1987). Measuring change over time: Assessing the usefulness of evaluative instruments. Journal of Chronic Diseases,40(2), 171–178. https://doi.org/10.1016/0021-9681(87)90069-5.

    Article  CAS  PubMed  Google Scholar 

  44. Cook, K. F., Bamer, A. M., Roddey, T. S., Kraft, G. H., Kim, J., & Amtmann, D. (2012). A PROMIS fatigue short form for use by individuals who have multiple sclerosis. Quality of Life Research,21(6), 1021–1030. https://doi.org/10.1007/s11136-011-0011-8.

    Article  PubMed  Google Scholar 

  45. Ameringer, S., Elswick, R. K., Jr., Menzies, V., Robins, J. L., Starkweather, A., Walter, J., et al. (2016). Psychometric evaluation of the patient-reported outcomes measurement information system fatigue-short form across diverse populations. Nursing Research,65(4), 279–289. https://doi.org/10.1097/nnr.0000000000000162.

    Article  PubMed  PubMed Central  Google Scholar 

  46. DeWalt, D. A., Rothrock, N., Yount, S., & Stone, A. A. (2007). Evaluation of item candidates: The PROMIS qualitative item review. Medical Care,45(5 Suppl 1), S12–S21. https://doi.org/10.1097/01.mlr.0000254567.79743.e2.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We would like to thank the Multi-Site Clinical Assessment of ME/CFS (MCAM) study group who made the data sets available through Research Collaboration Agreement. The group included: Division of High-Consequence, Pathogens and Pathology, Centers for Disease Control and Prevention, Atlanta, Georgia: Elizabeth R. Unger, Britany Helton, Yang Chen, and Monica Cornelius; Open Medicine Institute Consortium, Mountain View, CA: Andreas Kogelnik, Catt Phan, Joan Danver, Lucinda Bateman, Jennifer Bland, Charles Lapp, Wendy Springs, Richard Podell, Trisha Fitzpatrick, Daniel Peterson, and Marco Maynard; Institute for Neuro Immune Medicine, Miami, Florida: Nancy Klimas, Elizabeth Balbin, Precious Leaks-Gutierrez, and Shuntae Parnell; and Mount Sinai Beth Israel, New York, New York: Benjamin Natelson and Diana Vu.

Disclaimer

The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.

Funding

Manshu Yang (MY) and San Keller (SK) were supported by a National Institutes of Health (NIH) Grant Award (U2CCA186878). Jin-Mann S. Lin (JML) was supported by the Centers for Disease Control and Prevention (CDC).

Author information

Authors and Affiliations

  1. Department of Psychology, University of Rhode Island, 142 Flagg Road, Kingston, RI, 02881, USA

    Manshu Yang

  2. American Institutes for Research, Chapel Hill, NC, USA

    Manshu Yang & San Keller

  3. Centers for Disease Control and Prevention, Atlanta, GA, USA

    Jin-Mann S. Lin

Authors
  1. Manshu Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. San Keller
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jin-Mann S. Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Manshu Yang.

Ethics declarations

Conflict of interest

The authors declare no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yang, M., Keller, S. & Lin, JM.S. Psychometric properties of the PROMIS® Fatigue Short Form 7a among adults with myalgic encephalomyelitis/chronic fatigue syndrome. Qual Life Res 28, 3375–3384 (2019). https://doi.org/10.1007/s11136-019-02289-4

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11136-019-02289-4

Keywords

Search

Navigation