Journal of Behavioral Medicine

, Volume 27, Issue 3, pp 297–318 | Cite as

The PedsQL™ in Pediatric Asthma: Reliability and Validity of the Pediatric Quality of Life Inventory™ Generic Core Scales and Asthma Module

  • James W. Varni
  • Tasha M. Burwinkle
  • Michael A. Rapoff
  • Jodi L. Kamps
  • Nancy Olson

Abstract

The PedsQL™ is a modular instrument designed to measure health-related quality of life (HRQOL) in children and adolescents ages 2–18. The PedsQL™ 4.0 Generic Core Scales were developed to be integrated with the PedsQL™ Disease-Specific Modules. The PedsQL™ 3.0 Asthma Module was designed to measure pediatric asthma-specific HRQOL. The PedsQL™ was administered to 529 families. Internal consistency reliability was demonstrated for the PedsQL™ 4.0 Total Score (α = 0.90 child, 0.91 parent report) and Asthma Module (average α = 0.71 child, 0.86 parent report). The PedsQL™ 4.0 distinguished between healthy children and children with asthma. The validity of the PedsQL™ Asthma Module was demonstrated through intercorrelations with a previously standardized asthma disease- specific instrument. Responsiveness was demonstrated through patient change over time as a result of clinical intervention. The results demonstrate the reliability, validity, and responsiveness of the PedsQL™ required for an outcome measure in pediatric asthma clinical trials and research.

health-related quality of life asthma pediatrics children PedsQL™ 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Aday, L. A. (1996). Designing and Conducting Health Surveys: A Comprehensive Guide 2nd ed.,, Jossey-Bass, San Francisco.Google Scholar
  2. Campbell, D. T., and Fiske, D. W. (1959). Convergent and discriminant validation by the multitrait–multimethod matrix. Psychol. Bull. 56: 81-105.Google Scholar
  3. Campo, J. V., Comer, D. M., Jansen-McWilliams, L., Gardner, W., and Kelleher, K. J. (2002). Recurrent pain, emotional distress, and health service use in childhood. J. Pediatr. 141: 76-83.Google Scholar
  4. Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences, 2nd ed., Erlbaum, Hillsdale, NJ.Google Scholar
  5. Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika 16: 297-334.Google Scholar
  6. Drotar, D. (Ed.). (1998). Measuring Health-Related Quality of Life in Children and Adolescents, Erlbaum, Mahwah, NJ.Google Scholar
  7. Fairclough, D. L. (2002). Design and Analysis of Quality of Life Studies in Clinical Trials: Interdisciplinary Statistics, Chapman & Hall/CRC, New York.Google Scholar
  8. Fayers, P. M., and Machin, D. (2000). Quality of Life: Assessment, Analysis, and Interpretation, Wiley, New York.Google Scholar
  9. Feeny, D. H., Juniper, E. F., Ferrie, P. J., Griffith, L. E., and Guyatt, G. H. (1998). Why not just ask the kids? Health-related quality of life in children with asthma. In Drotar, D. (Ed.), Measuring Health-Related Quality of Life in Children and Adolescents: Implications for Research and Practice, Erlbaum, Mahwah, NJ, pp. 171-185.Google Scholar
  10. Fowler, F. J., Jr. (1995). Improving Survey Questions: Design and Evaluation,2nd ed., Sage, Thousand Oaks, CA.Google Scholar
  11. French, D. J. (2001). Asthma. In Koot, H. M., and Wallander, J. L. (Eds.), Quality of Life in Child and Adolescent Illness: Concepts, Methods and Findings, Brunner-Routledge, East Sussex, UK, pp. 241-265.Google Scholar
  12. Janicke, D. M., Finney, J. W., and Riley, A. W. (2001). Children's health care use: A prospective investigation of factors related to care-seeking. Med. Care 39: 990-1001.Google Scholar
  13. Juniper, E. F., Guyatt, G. H., Feeny, D. H., Ferrie, P. J., Griffith, L. E., and Townsend, M. (1996). Measuring quality of life in children with asthma. Qual. Life Res. 5: 35-46.Google Scholar
  14. Kazis, L. E., Anderson, J. J., and Meenan, R. F. (1989). Effect sizes for interpreting changes in health status. Med. Care 27: 178-189.Google Scholar
  15. Koot, H. M., and Wallander, J. L. (Eds.). (2001). Quality of Life in Child and Adolescent Illness: Concepts, Methods and Findings, Brunner-Routledge, East Sussex, UK.Google Scholar
  16. McHorney, C. A., Ware, J. E., Lu, J. F. R., and 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. Med. Care 32: 40-66.Google Scholar
  17. McHorney, C. A., Ware, J. E., and 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. Med. Care 31: 247-263.Google Scholar
  18. McHorney, C. A., Ware, J. E., Rogers, W., Raczek, A. E., and Lu, J. F. R. (1992). The validity and relative precision of MOS short-and long-form health status scales and Dartmouth COOP charts: Results from the Medical Outcomes Study. Med. Care 30: MS253-MS265.Google Scholar
  19. National Institutes of Health (1997). Expert Panel Report 2: Guidelines for the diagnosis and management of asthma. NIH Publication No. 97-4051.Google Scholar
  20. Novick, M., and Lewis, G. (1967). Coefficient alpha and the reliability of composite measurements. Psychometrika 32: 1-13.Google Scholar
  21. Nunnally, J. C., and Bernstein, I. R. (1994). Psychometric Theory, 3rd ed., McGraw-Hill, New York.Google Scholar
  22. Pedhazur, E. J., and Schmelkin, L. P. (1991). Measurement, Design, and Analysis: An Integrated Approach, Erlbaum, Hillsdale, NJ.Google Scholar
  23. Schwarz, N., and Sudman, N. (Eds.). (1996). Answering Questions: Methodology for Determining Cognitive and Communicative Processes in Survey Research, Jossey-Bass, San Francisco.Google Scholar
  24. Smith, K. W., Avis, N. E., and Assmann, S. F. (1999). Distinguishing between quality of life and health status in quality of life research: A meta-analysis. Qual. Life Res. 8: 447-459.Google Scholar
  25. Spilker, B. (1996). Quality of Life and Pharmacoeconomics in Clinical Trials, 2nd ed., Lippincott-Raven, Philadelphia.Google Scholar
  26. Sprangers, M. A. G., Cull, A., Bjordal, K., Groenvold, M., and Aaronson, N. K. (1993). The European Organization for Research and Treatment of Cancer approach to quality of life assessment: Guidelines for developing questionnaire modules. Qual. Life Res. 2: 287-295.Google Scholar
  27. SPSS. (1998). SPSS 8.0 for Windows, SPSS, Inc., Chicago.Google Scholar
  28. Thompson, K. L., and Varni, J. W. (1986). A developmental cognitive–biobehavioral approach to pediatric pain assessment. Pain 25: 282-296.Google Scholar
  29. Uzark, K., Jones, K., Burwinkle, T. M., and Varni, J. W. (2003). The Pediatric Quality of Life Inventory™ in children with heart disease. Prog. Pediatr. Cardiol. 18: 141-148.Google Scholar
  30. Varni, J. W., Burwinkle, T. M., Jacobs, J. R., Gottschalk, M., Kaufman, F., and Jones, K. L. (2003a). 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.Google Scholar
  31. Varni, J. W., Burwinkle, T. M., Katz, E. R., Meeske, K., and Dickinson, P. (2002a). 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.Google Scholar
  32. Varni, J. W., Burwinkle, T. M., Seid, M., and Skarr, D. (2003b). The PedsQL™ 4.0 as a pediatric population health measure: Feasibility, reliability, and validity. Ambul. Pediatr. 3: 329-341.Google Scholar
  33. Varni, J. W., Jacobs, J. R., and Seid, M. (2000). Treatment adherence as a predictor of health-related quality of life. In Drotar, D. (Ed.), Promoting Adherence to Medical Treatment in Chronic Childhood Illness: Concepts, Methods, and Interventions, Erlbaum, Mahwah, NJ, pp. 287-305.Google Scholar
  34. Varni, J. W., Katz, E. R., Colegrove, R., and Dolgin, M. (1995). Adjustment of children with newly diagnosed cancer: Cross-informant variance. J. Psychosoc. Oncol. 13: 23-38.Google Scholar
  35. Varni, J. W., Katz, E. R., Seid, M., Quiggins, D. J. L., and Friedman-Bender, A. (1998a). The Pediatric Cancer Quality of Life Inventory-32 (PCQL-32): I. Reliability and validity. Cancer 82: 1184-1196.Google Scholar
  36. Varni, J. W., Katz, E. R., Seid, M., Quiggins, D. J. L., Friedman-Bender, A., and Castro, C. M. (1998b). The Pediatric Cancer Quality of Life Inventory (PCQL): I. Instrument development, descriptive statistics, and cross-informant variance. J. Behav. Med. 21: 179-204.Google Scholar
  37. Varni, J. W., Seid, M., Knight, T. S., Burwinkle, T. M., Brown, J., and Szer, I. S. (2002b). The PedsQL™ in pediatric rheumatology: Reliability, validity, and responsiveness of the Pediatric Quality of Life Inventory™ Generic Core Scales and Rheumatology Module. Arthritis Rheum. 46: 714-725.Google Scholar
  38. Varni, J. W., Seid, M., Knight, T. S., Uzark, K., and Szer, I. S. (2002c). The PedsQL™ 4.0 Generic Core Scales: Sensitivity, responsiveness, and impact on clinical decision-making. J. Behav. Med. 25: 175-193.Google Scholar
  39. Varni, J. W., Seid, M., and Kurtin, P. S. (1999a). Pediatric health-related quality of life measurement technology: A guide for health care decision makers. J. Clin. Outcomes Manage. 6: 33-40.Google Scholar
  40. Varni, J. W., Seid, M., and Kurtin, P. S. (2001). The PedsQL™ 4.0: Reliability and validity of the Pediatric Quality of Life Inventory™ Version 4.0 Generic Core Scales in healthy and patient populations. Med. Care 39: 800-812.Google Scholar
  41. Varni, J. W., Seid, M., and Rode, C. A. (1999b). The PedsQL™: Measurement model for the Pediatric Quality of Life Inventory. Med. Care 37: 126-139.Google Scholar
  42. Varni, J. W., and Setoguchi, Y. (1992). Screening for behavioral and emotional problems in children and adolescents with congenital or acquired limb deficiencies. Am. J. Dis. Child. 146: 103-107.Google Scholar
  43. Varni, J. W., Thompson, K. L., and Hanson, V. (1987). The Varni/Thompson Pediatric Pain Questionnaire: I. Chronic musculoskeletal pain in juvenile rheumatoid arthritis. Pain 28: 27-38.Google Scholar
  44. Varni, J. W., Waldron, S. A., Gragg, R. A., Rapoff, M. A., Bernstein, B. H., Lindsley, C. B., and Newcomb, M. D. (1996). Development of the Waldron/Varni Pediatric Pain Coping Inventory. Pain 67: 141-150.Google Scholar
  45. Varni, J. W., Wilcox, K. T., Hanson, V., and Brik, R. (1988). Chronic musculoskeletal pain and functional status in juvenile rheumatoid arthritis: An empirical model. Pain 32: 1-7.Google Scholar
  46. World Health Organization. (1948). Constitution of the World Health Organization Basic Document, World Health Organization, Geneva, Switzerland.Google Scholar

Copyright information

© Plenum Publishing Corporation 2004

Authors and Affiliations

  • James W. Varni
    • 1
    • 3
  • Tasha M. Burwinkle
    • 2
  • Michael A. Rapoff
    • 3
  • Jodi L. Kamps
    • 3
  • Nancy Olson
    • 3
  1. 1.Department of Landscape Architecture and Urban Planning, College of ArchitectureTexas A&M UniversityCollege Station
  2. 2.Department of AnesthesiologyUniversity of WashingtonSeattle
  3. 3.Department of Pediatrics, College of MedicineTexas A&M UniversityCollege Station

Personalised recommendations