The PedsQL™ Multidimensional Fatigue Scale in young adults: feasibility, reliability and validity in a University student population
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Background and objective
The PedsQL™ (Pediatric Quality of Life Inventory™) is a modular instrument designed to measure health-related quality of life (HRQOL) and disease-specific symptoms in children and adolescents ages 2–18. The PedsQL™ Multidimensional Fatigue Scale was designed as a generic symptom-specific instrument to measure fatigue in pediatric patients ages 2–18. Since a sizeable number of pediatric patients prefer to remain with their pediatric providers after age 18, the objective of the present study was to determine the feasibility, reliability, and validity of the PedsQL™ Multidimensional Fatigue Scale in young adults.
The 18-item PedsQL™ Multidimensional Fatigue Scale (General Fatigue, Sleep/Rest Fatigue, and Cognitive Fatigue domains), the PedsQL™ 4.0 Generic Core Scales Young Adult Version, and the SF-8™ Health Survey were completed by 423 university students ages 18–25.
The PedsQL™ Multidimensional Fatigue Scale evidenced minimal missing responses, achieved excellent reliability for the Total Scale Score (α = 0.90), distinguished between healthy young adults and young adults with chronic health conditions, was significantly correlated with the relevant PedsQL™ 4.0 Generic Core Scales and the SF-8™ standardized scores, and demonstrated a factor-derived structure largely consistent with the a priori conceptual model.
The results demonstrate the measurement properties of the PedsQL™ Multidimensional Fatigue Scale in a convenience sample of young adult university students. The findings suggest that the PedsQL™ Multidimensional Fatigue Scale may be utilized in the evaluation of fatigue for a broad age range.
KeywordsPedsQL™ Fatigue Young adults Self-report University students Patient-reported outcomes Health-related quality of life SF-8™ Health survey
Funding: This research was supported by an intramural grant from the Texas A&M University Research Foundation.
- 1.Varni, J. W., Burwinkle, T. M., & Lane, M. M. (2005). Health-related quality of life measurement in pediatric clinical practice: An appraisal and precept for future research and application. Health and Quality of Life Outcomes, 3(34), 1–9.Google Scholar
- 3.FDA: Guidance for industry (2006). Patient-reported outcome measures: Use in medical product development to support labeling claims. Rockville, MD: Center for drug evaluation and research, food and drug administration.Google Scholar
- 4.Razzouk, B. I., Hord, J. D., Hockenberry, M., Hinds, P. S., Feusner, J., Williams, D., & Rackoff, W. R. (2006). Double-blind, placebo-controlled study of quality of life, hematologic end points, and safety of weekly epoetin alfa in children with cancer receiving myelosuppressive chemotherapy. Journal of Clinical Oncology, 24, 3583–3589.PubMedCrossRefGoogle Scholar
- 12.Varni, J. W., Seid, M., Knight, T. S., Burwinkle, T. M., Brown, J., & Szer, I. S. (2002). The PedsQL™ in pediatric rheumatology: Reliability, validity, and responsiveness of the Pediatric Quality of Life Inventory™ Generic Core Scales and Rheumatology Module. Arthritis and Rheumatism, 46, 714–725.PubMedCrossRefGoogle Scholar
- 13.Varni, J. W., Burwinkle, T. M., Katz, E. R., Meeske, K., & Dickinson, P. (2002). The PedsQL™ in pediatric cancer: Reliability and validity of the Pediatric Quality of Life Inventory™ Generic Core Scales, Multidimensional Fatigue Scale, and Cancer Module. Cancer, 94, 2090–2106.PubMedCrossRefGoogle Scholar
- 14.Varni, J. W., Burwinkle, T. M., Berrin, S. J., Sherman, S. A., Artavia, K., Malcarne, V. L., & Chambers, H. G. (2006). The PedsQL™ in pediatric cerebral palsy: Reliability, validity, and sensitivity of the Generic Core Scales and Cerebral Palsy Module. Developmental Medicine and Child Neurology, 48, 442–449.PubMedCrossRefGoogle Scholar
- 15.Varni, J. W., Burwinkle, T. M., Jacobs, J. R., Gottschalk, M., Kaufman, F., & Jones, K. L. (2003). The PedsQL™ in Type 1 and Type 2 diabetes: Reliability and validity of the Pediatric Quality of Life Inventory™ Generic Core Scales and Type 1 Diabetes Module. Diabetes Care, 26, 631–637.PubMedCrossRefGoogle Scholar
- 23.Okuyama, T., Akechi, T., Kugaya, A., Okamura, H., Shima, Y., Maruguchi, M., Hosaka, T., & Uchitomi, Y. (2000). Development and validation of the cancer fatigue scale: A brief, three-dimensional, self-rating scale for assessment of fatigue in cancer patients. Journal of Pain and Symptom Management, 19, 5–14.PubMedCrossRefGoogle Scholar
- 27.Katz, E. R., Burwinkle, T. M., Varni, J. W., & Barr, R. D (2007). Health-related quality of life in adolescents and young adults with cancer. In Cancer in Adolescents and Young Adults. A. Bleyer, R. Barr, K. Albritton, M. Phillips, & S. Siegel (Eds.) New York: Springer Verlag.Google Scholar
- 28.Varni, J. W., Burwinkle, T. M., Limbers, C. A., & Szer, I. S. (2007). The PedsQL™ as a patient-reported outcome in children and adolescents with fibromyalgia: An analysis of OMERACT domains. Health and Quality of Life Outcomes, 5(9), 1–12.Google Scholar
- 37.Varni, J. W., & Limbers, C. A. (2007). The PedsQL™ 4.0 Generic Core Scales Young Adult Version: Feasibility, reliability and validity in a university student population. (Unpublished manuscript).Google Scholar
- 38.Ware, J. E., Kosinski, M., Dewey, J. E., Gandek, B. (2001). How to Score and Interpret Single-Item Health Status Measures: A Manual for Users of the SF-8™ Health Survey. Lincoln, RI: QualityMetric Incorporated.Google Scholar
- 40.Aday, L. A. (1996). Designing and conducting health surveys: A comprehensive guide, 2nd edn. San Francisco: Jossey-Bass.Google Scholar
- 41.Fowler, F. J., Jr. (1995). Improving survey questions: Design and evaluation. Thousand Oaks, CA: Sage.Google Scholar
- 42.Schwarz, N., Sudman N. (eds.) (1996). Answering questions: Methodology for determining cognitive and communicative processes in survey research. San Francisco: Jossey-Bass.Google Scholar
- 45.Fairclough, D. L. (2002). Design and analysis of quality of life studies in clinical trials: Interdisciplinary statistics. New York: Chapman & Hall/CRC.Google Scholar
- 47.Hollingshead, A. B. (1975). Four Factor Index of Social Status. New Haven, CT: Yale University.Google Scholar
- 50.Nunnally, J. C., & Bernstein, I. R. (1994). Psychometric theory (3rd ed.). New York: McGraw-Hill.Google Scholar
- 51.Pedhazur, E. J., & Schmelkin, L. P. (1991). Measurement, design, and analysis: An integrated approach. Hillsdale, NJ: Erlbaum.Google Scholar
- 53.Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Hillsdale, NJ: Erlbaum.Google Scholar
- 54.Fayers, P. M., & Machin, D. (2000). Quality of life: Assessment, analysis, and interpretation. New York: Wiley.Google Scholar
- 55.SPSS (2005). SPSS 14.0 for Windows. Chicago: SPSS, Inc.Google Scholar
- 59.Banthia, R., Malcarne, V. L., Ko, C. M., Varni, J. W., & Sadler, G. R. Fatigued breast cancer survivors: The role of sleep quality, depressed mood, stage, and age. Psychology and Health (in press).Google Scholar
- 60.Anderson, K. O., Getto, C. J., Mendoza, T. R., Palmer, S. N., Wang, X. S., Reyes-Gibby, C. C., & Cleeland, C. S. (2003). Fatigue and sleep disturbance in patients with cancer, patients with clinical depression, and community-dwelling adults. Journal of Pain and Symptom Management, 25, 307–318.PubMedCrossRefGoogle Scholar
- 61.Okuyama, T., Akechi, T., Kugaya, A., Okamura, H., Imoto, S., Nakanon, T., Mikami, I., Hosaka, T., & Uchitomi, Y. (2000). Factors correlated with fatigue in disease-free breast cancer patients: Application of the Cancer Fatigue Scale. Supportive Care in Cancer, 8, 215–222.PubMedCrossRefGoogle Scholar
- 66.Lee, Y. C., Chien, K. L., & Chen, H. H. (2007). Lifestyle risk factors associated with fatigue in graduate students. Journal of Formosan Medical Association, 106, 565–572.Google Scholar