Measuring fatigue in persons with multiple sclerosis: creating a crosswalk between the Modified Fatigue Impact Scale and the PROMIS Fatigue Short Form
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To create cross-walk tables to associate scores for the Modified Fatigue Impact Scale (MFIS) with scores for the Patient Reported Outcome Measurement Information System (PROMIS) Fatigue Short Form (SF) in persons with Multiple Sclerosis (MS).
Cross-walk tables were created using equipercentile linking and based on data collected at one time point in a longitudinal study of persons with MS (N = 458). Validation of the tables was conducted using data collected at a subsequent time point (N = 444). Deviations between estimates and actual scores were compared across levels of fatigue. The impact of sample size on the precision of sample mean estimates was evaluated using bootstrapping.
Correlations between deviations and fatigue level for the PROMIS Fatigue SF and MFIS were (−0.31) and (−0.30), respectively, indicating moderately greater deviations with lower fatigue scores. Estimated sample means were impacted by sample size.
Cross-walk tables allow data from studies using different measures of fatigue to be combined to achieve larger sample sizes and to compare results. These tables are valid for group-level analyses with sample sizes of 150 or greater.
KeywordsFatigue Multiple sclerosis Outcome assessment Questionnaires
The contents of this manuscript were developed under grants from the Department of Education, National Institute on Disability and Rehabilitation Research grant numbers H133B031129 and H133B080025, and the National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institute of Health (Grant 5U01AR052171). However, these contents do not necessarily represent the policy of the Department of Education, and you should not assume endorsement by the Federal Government.
- 1.World Health Organization, & Multiple Sclerosis International Federation. (2008). Atlas multiple sclerosis resources in the world 2008. Geneva, Switzerland: World Health Organization.Google Scholar
- 3.Multiple Sclerosis Council for Clinical Practice Guidelines. (1998). Fatigue and multiple sclerosis: Evidence-based management strategies for fatigue in multiple sclerosis. Washington, DC: Paralyzed Veterans of America.Google Scholar
- 4.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, 1179–1194.PubMedCrossRefGoogle Scholar
- 5.Patient Reported Outcomes Measurement Information System (PROMIS). PROMIS. http://www.nihpromis.org. Accessed 20 May 2011.
- 6.Holland, P.W. (2007). Chapter 2. A framework and history for score linking. In N.J. Dorans, M. Pommerich, & P. W. Holland (Eds.), In Linking and Aligning Scores and Scales (pp. 5–30) Springer, New York.Google Scholar
- 14.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, 1311–1321.PubMedCrossRefGoogle Scholar
- 15.Christodoulou, C., Junghaenel, D. U., DeWalt, D. A., Rothrock, N., & Stone, A. A. (2008). Cognitive interviewing in the evaluation of fatigue items: Results from the Patient-Reported Outcomes Measurement Information System (PROMIS). Quality of Life Research, 17, 1239–1246.PubMedCrossRefGoogle Scholar
- 16.Lai, J. S., Cella, D., Choi, S., Junghaenel, D. U., Gershon, R., & Stone, A. (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, S20–S27.Google Scholar
- 22.Muthén, L. K., & Muthén, B. O. (2009). Mplus: statistical software version 5.21. Los Angeles, CA: Muthén & Muthén.Google Scholar
- 23.Reeve, B. B., Hays, R. D., Bjorner, J. B., Cook, K. F., Crane, P. K., Teresi, J. A., et al. (2007). Psychometric evaluation and calibration of health-related quality of life item banks: Plans for the Patient-Reported Outcomes Measurement Information System (PROMIS). Medical Care, 45, S22–S31.PubMedCrossRefGoogle Scholar
- 24.Yu, C. Y. (2002). Evaluating cutoff criteria of model fit indices for latent variable models with binary and continuous outcomes. Doctor of Philosophy in Education. Los Angeles: University of California.Google Scholar