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The PedsQL™ Multidimensional Fatigue Scale in young adults: feasibility, reliability and validity in a University student population

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Abstract

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.

Method

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.

Results

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.

Conclusions

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.

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References

  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 

  2. Matza, L. S., Swensen, A. R., Flood, E. M., Secnik, K., & Leidy, N. K. (2004). Assessment of health-related quality of life in children: A review of conceptual, methodological, and regulatory issues. Value in Health, 7, 79–92.

    Article  PubMed  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.

  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.

    Article  PubMed  CAS  Google Scholar 

  5. Varni, J. W., Burwinkle, T. M., & Seid, M. (2005). The PedsQL™ as a pediatric patient-reported outcome: Reliability and validity of the PedsQL™ Measurement Model in 25,000 children. Expert Review of Pharmacoeconomics and Outcomes Research, 5, 705–719.

    Article  PubMed  Google Scholar 

  6. Schwimmer, J. B., Middleton, M. S., Deutsch, R., & Lavine, J. E. (2005). A phase 2 trial of metformin as a treatment for non-diabetic pediatric non-alcoholic steatohepatitis. Alimentary Pharmacology & Therapeutics, 21, 871–879.

    Article  CAS  Google Scholar 

  7. Connelly, M., & Rapoff, M. A. (2006). Assessing health-related quality of life in children with recurrent headache: Reliability and validity of the PedsQL™ 4.0 in a pediatric sample. Journal of Pediatric Psychology, 31, 698–702.

    Article  PubMed  Google Scholar 

  8. Varni, J. W., Seid, M., & Rode, C. A. (1999). The PedsQL™: Measurement model for the Pediatric Quality of Life Inventory. Medical Care, 37, 126–139.

    Article  PubMed  CAS  Google Scholar 

  9. Patrick, D. L., & Deyo, R. A. (1989). Generic and disease-specific measures in assessing health status and quality of life. Medical Care, 27, S217–S233.

    Article  PubMed  CAS  Google Scholar 

  10. Varni, J. W., Seid, M., & Kurtin, P. S. (2001). PedsQL™ 4.0: Reliability and validity of the Pediatric Quality of Life Inventory™ version 4.0 Generic Core Scales in healthy and patient populations. Medical Care, 39, 800–812.

    Article  PubMed  CAS  Google Scholar 

  11. Varni, J. W., Burwinkle, T. M., Rapoff, M. A., Kamps, J. L., & Olson, N. (2004). The PedsQL™ in pediatric asthma: Reliability and validity of the Pediatric Quality of Life Inventory™ Generic Core Scales and Asthma Module. Journal of Behavioral Medicine, 27, 297–318.

    Article  PubMed  Google 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.

    Article  PubMed  Google 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.

    Article  PubMed  Google 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.

    Article  PubMed  Google 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.

    Article  PubMed  Google Scholar 

  16. Palmer, S. N., Meeske, K. A., Katz, E. R., Burwinkle, T. M., & Varni, J. W. (2007). The PedsQL™ Brain Tumor Module: Initial reliability and validity. Pediatric Blood and Cancer, 49, 287–293.

    Article  PubMed  Google Scholar 

  17. Varni, J. W., Burwinkle, T. M., & Szer, I. S. (2004). The PedsQL™ Multidimensional Fatigue Scale in pediatric rheumatology: Reliability and validity. Journal of Rheumatology, 31, 2494–2500.

    PubMed  Google Scholar 

  18. Cella, D. (1997). The functional assessment of cancer therapy: Anemia (FACT–AN) scale: A new tool for the assessment of outcomes in cancer anemia and fatigue. Seminars in Hematology, 34, 13–19.

    PubMed  CAS  Google Scholar 

  19. Hann, D. M., Jacobsen, P. B., Azzarello, L. M., Martin, S. C., Curran, S. L., Fields, K. K., Greenberg, H., & Lyman, G. (1998). Measurement of fatigue in cancer patients: Development and validation of the fatigue symptom inventory. Quality of Life Research, 7, 301–310.

    Article  PubMed  CAS  Google Scholar 

  20. Belza, B. L. (1995). Comparison of self-reported fatigue in rheumatoid arthritis and controls. Journal of Rheumatology, 22, 639–643.

    PubMed  CAS  Google Scholar 

  21. 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, 315–325.

    Article  PubMed  CAS  Google Scholar 

  22. Stein, K. D., Martin, S. C., Hann, D. M., & Jacobsen, P. B. (1998). A multidimensional measure of fatigue for use with cancer patients. Cancer Practice, 6, 143–152.

    Article  PubMed  CAS  Google 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.

    Article  PubMed  CAS  Google Scholar 

  24. Varni, J. W., Wilcox, K. T., Hanson, V., & Brik, R. (1988). Chronic musculoskeletal pain and functional status in juvenile rheumatoid arthritis: An empirical model. Pain, 32, 1–7.

    Article  PubMed  CAS  Google Scholar 

  25. Varni, J. W., Burwinkle, T. M., & Katz, E. R. (2004). The PedsQL™ in pediatric cancer pain: A prospective longitudinal analysis of pain and emotional distress. Journal of Developmental and Behavioral Pediatrics, 25, 1–8.

    Article  Google Scholar 

  26. Berrin, S. J., Malcarne, V. L., Varni, J. W., Burwinkle, T., Sherman, S. A., Artavia, K. A., & Chambers, H. G. (2007). Pain, fatigue, and school functioning in children with cerebral palsy: A path-analytic model. Journal of Pediatric Psychology, 32, 330–337.

    Article  PubMed  Google 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.

  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 

  29. Zullig, K. J. (2005). Using CDC’s health-related quality of life scale on a college campus. American Journal of Health Behavior, 29, 569–578.

    PubMed  Google Scholar 

  30. Robins, R. W., Noftle, E. E., Trzesniewski, K. H., & Roberts, B. W. (2005). Do people know how their personality has change?: Correlates of perceived and actual personality change in young adulthood. Journal of Personality, 73, 489–522.

    Article  PubMed  Google Scholar 

  31. Yang, C. M., Wu, C. H., Hsieh, M. H., Lui, M. H., & Lu, F. H. (2003). Coping with sleep disturbances among young adults: A survey of first-year college students in Taiwan. Behavioral Medicine, 29, 133–138.

    Article  PubMed  Google Scholar 

  32. Vaez, M., & Laflamme, L. (2003). Health behaviors, self-rated health, and quality of life: A study among first-year Swedish university students. Journal of American College Health, 51, 156–162.

    PubMed  Google Scholar 

  33. Vaez, M., Ponce de Leon, A., & Laflamme, L. (2006). Health-related determinants of perceived quality of life: A comparison between first-year university students and their working peers. Work, 26, 167–177.

    PubMed  Google Scholar 

  34. Bovier, P. A., Chamot, E., & Perneger, T. V. (2004). Perceived stress, internal resources, and social support as determinants of mental health among young adults. Quality of Life Research, 13, 161–170.

    Article  PubMed  Google Scholar 

  35. Khawaja, N. G., & Bryden, K. J. (2006). The development and psychometric investigation of the university student depression inventory. Journal of Affective Disorders, 96, 21–29.

    Article  PubMed  Google Scholar 

  36. Stewart-Brown, S., Evan, J., Patterson, J., Petersen, S., Doll, H., Balding, J., & Regis, D. (2000). The health of students in institutes of higher education: An important and neglected public health problem? Journal of Public Health Medicine, 22, 492–499.

    Article  PubMed  CAS  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).

  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.

  39. Fayers, P. M., & Hand, D. J. (1997). Factor analysis, causal indicators and quality of life. Quality of Life Research, 6, 139–150.

    PubMed  CAS  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 

  43. Varni, J. W., Thompson, K. L., & Hanson, V. (1987). The Varni/Thompson Pediatric Pain Questionnaire: I. Chronic musculoskeletal pain in juvenile rheumatoid arthritis. Pain, 28, 27–38.

    Article  PubMed  CAS  Google Scholar 

  44. Varni, J. W., Waldron, S. A., Gragg, R. A., Rapoff, M. A., Bernstein, B. H., Lindsley, C. B., & Newcomb, M. D. (1996). Development of the Waldron/Varni Pediatric Pain Coping Inventory. Pain, 67, 141–150.

    Article  PubMed  CAS  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 

  46. Varni, J. W., Burwinkle, T. M., Seid, M., & Skarr, D. (2003). The PedsQL™ 4.0 as a pediatric population health measure: Feasibility, reliability, and validity. Ambulatory Pediatrics, 3, 329–341.

    Article  PubMed  Google Scholar 

  47. Hollingshead, A. B. (1975). Four Factor Index of Social Status. New Haven, CT: Yale University.

    Google Scholar 

  48. McHorney, C. A., Ware, J. E., Lu, J. F. R., & Sherbourne, C. D. (1994). The MOS 36-item short-form health survey (SF-36): III. Tests of data quality, scaling assumptions, and reliability across diverse patient groups. Medical Care, 32, 40–66.

    Article  PubMed  CAS  Google Scholar 

  49. Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16, 297–334.

    Article  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 

  52. McHorney, C. A., Ware, J. E., & Raczek, A. E. (1993). The MOS 36-item short-form health survey (SF-36): II. Psychometric and clinical tests of validity in measuring physical and mental health constructs. Medical Care, 31, 247–263.

    Article  PubMed  CAS  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 

  56. Floyd, F. J., & Widaman, K. F. (1995). Factor analysis in the development and refinement of clinical assessment instruments. Psychological Assessment, 7, 286–299.

    Article  Google Scholar 

  57. Cella, D., Lai, J. S., Chang, C. H., Peterman, A., & Slavin, M. (2002). Fatigue in cancer patients compared with fatigue in the general United States population. Cancer, 94, 528–538.

    Article  PubMed  Google Scholar 

  58. Wolfe, F., Hawley, D. J., & Wilson, K. (1996). The prevalence and meaning of fatigue in rheumatic disease. Journal of Rheumatology, 23, 1407–1417.

    PubMed  CAS  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).

  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.

    Article  PubMed  Google 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.

    Article  PubMed  CAS  Google Scholar 

  62. Bower, J. E., Ganz, P. A., Desmond, K. A., Rowland, J. H., Meyerowitz, B. E., & Belin, T. R. (2000). Fatigue in breast cancer survivors: Occurrence, correlates, and impact on quality of life. Journal of Clinical Oncology, 18, 743–753.

    PubMed  CAS  Google Scholar 

  63. Gaston-Johansson F, Fall-Dickson, J. M., Bakos, A. B., & Kennedy, M. J. (1999). Fatigue, pain, and depression in pre-autotransplant breast cancer patients. Cancer Practice, 7, 240–247.

    Article  PubMed  CAS  Google Scholar 

  64. Akechi, T., Kugaya, A., Okamura, H., Yamawaki, S., Uchitomi, Y. (1999). Fatigue and its associated factors in ambulatory cancer patients: A preliminary study. Journal of Pain and Symptom Management, 17, 42–48.

    Article  PubMed  CAS  Google Scholar 

  65. Donovan, K. A., Andrykowski, M. A., Small, B. J., Munster, P., & Jacobsen, P. B. (2007). Utility of a cognitive-behavioral model to predict fatigue following breast cancer treatment. Health Psychology, 26, 464–472.

    Article  PubMed  Google 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 

  67. Oginska, H., & Pokorski, J. (2006). Fatigue and mood correlates of sleep length in three age-social groups: School children, students, and employees. Chronobiology International, 23, 1317–1328.

    Article  PubMed  Google Scholar 

  68. Lavidor, M., Weller, A., & Babkoff, H. (2002). Multidimensional fatigue, somatic symptoms and depression. British Journal of Health Psychology, 7, 67–75.

    Article  PubMed  Google Scholar 

  69. ter Wolbeek, M., van Doornen, L. J. P., Kavelaars, A., & Heijnen, C. J. (2006). Severe fatigue in adolescents: A common phenomenon? Pediatrics, 117, e1078–e1086.

    Article  PubMed  Google Scholar 

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Acknowledgements

Funding: This research was supported by an intramural grant from the Texas A&M University Research Foundation.

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Correspondence to James W. Varni.

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Competing Interests: Dr. Varni holds the copyright and the trademark for the PedsQL™ and receives financial compensation from the Mapi Research Trust, which is a nonprofit research institute that charges distribution fees to for-profit companies that use the Pediatric Quality of Life Inventory™. The PedsQL is available at http://www.pedsql.org.

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Varni, J.W., Limbers, C.A. The PedsQL™ Multidimensional Fatigue Scale in young adults: feasibility, reliability and validity in a University student population. Qual Life Res 17, 105–114 (2008). https://doi.org/10.1007/s11136-007-9282-5

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