Quality of Life Research

, Volume 20, Issue 6, pp 913–921 | Cite as

PedsQL™ Cognitive Functioning Scale in pediatric liver transplant recipients: feasibility, reliability, and validity

  • James W. VarniEmail author
  • Christine A. Limbers
  • Lisa G. Sorensen
  • Katie Neighbors
  • Karen Martz
  • John C. Bucuvalas
  • Estella M. Alonso



The PedsQL™ (Pediatric Quality of Life Inventory™) is a modular instrument designed to measure health-related quality of life and disease-specific symptoms. The PedsQL™ Cognitive Functioning Scale was developed as a brief generic symptom-specific instrument to measure cognitive functioning. The objective of the present study was to determine the feasibility, reliability, and validity of the PedsQL™ Cognitive Functioning Scale in pediatric liver transplant recipients.


The 6-item PedsQL™ Cognitive Functioning Scale and the PedsQL™ 4.0 Generic Core Scales were completed by pediatric liver transplant recipients ages 8–18 years (n = 215) and parents of pediatric liver transplant recipients ages 2–18 years (n = 502). Both patient self-report and parent proxy-report were available for 212 cases. The 72-item Behavior Rating Inventory of Executive Function (BRIEF), a widely validated measure of executive functioning, was completed by 100 parents and 56 teachers on a subset of patients.


The PedsQL™ Cognitive Functioning Scale demonstrated minimal missing responses (0.0%, child report, 0.67%, parent report), achieved excellent reliability (α = 0.88 child report, 0.94 parent report), distinguished between pediatric patients with liver transplants and healthy children supporting discriminant validity, and was significantly correlated with the PedsQL™ 4.0 Generic Core Scales and the BRIEF supporting construct and concurrent validity, respectively. Pediatric liver transplants recipients experienced cognitive functioning comparable to long-term pediatric cancer survivors.


The results demonstrate the feasibility, reliability, discriminant, construct, and concurrent validity of the PedsQL™ Cognitive Functioning Scale in pediatric liver transplant recipients.


Cognitive functioning PedsQL™ Liver transplant Pediatrics Executive functioning Quality of life 



Studies of Pediatric Liver Transplantation Functional Outcomes Group: University of California, Los Angeles (Sue McDiarmid, MD), Cincinnati Children’s Hospital Medical Center (John Bucuvalas, MD), The Children’s Hospital, Denver (Ronald Sokol, MD), Children’s Medical Center, Dallas (Jami Gross, MD), Hospital for Sick Children, Toronto (Vicky Ng, MD), University of Nebraska (Alan Langnas, DO), Mount Sinai Medical Center (Nanda Kerkar, MD), University of Alberta, Edmonton (Susan Gilmour, MD), Children’s Memorial Hospital (Estella Alonso, MD), Children’s Hospital of Philadelphia (Barbara Haber, MD), University of Miami/Jackson Memorial (Andreas Tzakis, MD), University of California, San Francisco (Philip Rosenthal, MD), Johns Hopkins University (Wikrom Karnsakul, MD), Children’s Mercy Hospital, Kansas City (James F. Daniel, MD), St. Louis Children’s Hospital (Yumirle Turmelle, MD), Texas Children’s Hospital (Saul Karpen, MD, PhD), University of Minnesota (Abhi Humar, MD), Children’s Hospital of Pittsburgh (George Mazariegos, MD), University of North Carolina, Chapel Hill (Jeffrey Fair, MD), University of California, San Diego (Joel E. Lavine, MD), Alfred I. DuPont Hospital for Children (Stephen Dunn, MD), Boston Children’s Hospital (Maureen Jonas, MD), University of Michigan (Emily Fredericks, PhD).


This project was supported by grant number R01 HD045694 of the National Institute of Child Health and Human Development and grant number U01 DK061693 of the National Institute of Diabetes and Digestive and Kidney Diseases at the National Institutes of Health. The sponsoring agency was not involved in the collection, analysis, or interpretation of data or the generation of the report.

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™.


  1. 1.
    Weissberg-Benchell, J., Zielinski, T. E., Rodgers, S., Greenley, R. N., Askenazi, D., Goldstein, S. L., et al. (2010). Pediatric health-related quality of life: Feasibility, reliability and validity of the PedsQL™ Transplant Module. American Journal of Transplantation, 10, 1677–1685.PubMedCrossRefGoogle Scholar
  2. 2.
    Alonso, E. M., Limbers, C. A., Neighbors, K., Martz, K., Bucuvalas, J. C., Webb, T., et al. (2010). Cross-sectional analysis of health-related quality of life in pediatric liver transplant recipients. Journal of Pediatrics, 156, 270–276.PubMedCrossRefGoogle Scholar
  3. 3.
    Gilmour, S., Adkinsb, R., Liddellb, G. A., Jhangric, G., & Robertsond, C. M. (2009). Assessment of psychoeducational outcomes after pediatric liver transplant. American Journal of Transplantation, 9, 294–300.PubMedCrossRefGoogle Scholar
  4. 4.
    Krull, K., Fuchs, C., Yurk, H., Boone, P., & Alonso, E. M. (2003). Neurocognitive outcome in pediatric liver transplant recipients. Pediatric Transplantation, 7, 111–118.PubMedCrossRefGoogle Scholar
  5. 5.
    Adeback, A., Nemeth, A., & Fischler, B. (2003). Cognitive and emotional outcome after pediatric liver transplantation. Pediatric Transplantation, 7, 385–389.PubMedCrossRefGoogle Scholar
  6. 6.
    Kaller, T., Schulz, K., Sander, K., Boeck, A., Rogiers, X., & Burdelski, M. (2005). Cognitive abilities in children after liver transplantation. Transplantation, 79, 1252–1256.PubMedCrossRefGoogle Scholar
  7. 7.
    Sorensen, L. G., Neighbors, K., Martz, K., Zelko, F., Bucuvalas, J. C., & Alonso, E. M. (in press). Cognitive and academic outcomes after pediatric liver transplantation: Functional outcomes group (FOG) results. American Journal of Transplantation.Google Scholar
  8. 8.
    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
  9. 9.
    McCarthy, M. L., MacKenzie, E. J., Durbin, D. R., Aitken, M. E., Jaffe, K. M., Paidas, C. N., et al. (2005). The Pediatric Quality of Life Inventory: An evaluation of its reliability and validity for children with traumatic brain injury. Archives of Physical Medicine and Rehabilitation, 86, 1901–1909.PubMedCrossRefGoogle Scholar
  10. 10.
    Suchy, Y. (2009). Executive functioning: Overview, assessment, and research issues for non-neuropsychologists. Annals of Behavioral Medicine, 37, 106–116.PubMedCrossRefGoogle Scholar
  11. 11.
    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.PubMedGoogle Scholar
  12. 12.
    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 & Cancer, 49, 287–293.CrossRefGoogle Scholar
  13. 13.
    Gold, J. I., Mahrer, N. E., Yee, J., & Palermo, T. M. (2009). Pain, fatigue, and health-related quality of life in children and adolescents with chronic pain. Clinical Journal of Pain, 25, 407–412.PubMedCrossRefGoogle Scholar
  14. 14.
    Varni, J. W., Limbers, C. A., Bryant, W. P., & Wilson, D. P. (2009). The PedsQL™ Multidimensional Fatigue Scale in type 1 diabetes: Feasibility, reliability, and validity. Pediatric Diabetes, 10, 321–328.PubMedCrossRefGoogle Scholar
  15. 15.
    Varni, J. W., Limbers, C. A., Bryant, W. P., & Wilson, D. P. (2010). The PedsQL™ Multidimensional Fatigue Scale in pediatric obesity: Feasibility, reliability, and validity. International Journal of Pediatric Obesity, 5, 34–42.PubMedCrossRefGoogle Scholar
  16. 16.
    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.PubMedCrossRefGoogle Scholar
  17. 17.
    Marcus, S. B., Strople, J. A., Neighbors, K., Weissberg-Benchell, J., Nelson, S. P., Limbers, C. A., et al. (2009). Fatigue and health-related quality of life in pediatric inflammatory bowel disease. Clinical Gastroenterology and Hepatology, 7, 554–561.PubMedCrossRefGoogle Scholar
  18. 18.
    MacAllister, W. S., Christodoulou, C., Troxell, R., Milazzo, M., Block, P., Preston, T. E., et al. (2009). Fatigue and quality of life in pediatric multiple sclerosis. Multiple Sclerosis, 15, 1502–1508.PubMedCrossRefGoogle Scholar
  19. 19.
    Paulsen, E. K., Friedman, L. S., Myers, L. M., & Lynch, D. R. (2010). Health-related quality of life in children with Friedreich ataxia. Pediatric Neurology, 42, 335–337.PubMedCrossRefGoogle Scholar
  20. 20.
    Dampier, C., Lieff, S., Lebeau, P., Rhee, S., McMurray, M., Rogers, Z., et al. (2010). Health-related quality of life in children with sickle cell disease: A report from the comprehensive sickle cell centers clinical trial consortium. Pediatric Blood & Cancer, 55, 485–494.CrossRefGoogle Scholar
  21. 21.
    Limbers, C. A., Heffer, R. W., & Varni, J. W. (2009). Health-related quality of life and cognitive functioning from the perspective of parents of school-aged children with Asperger’s Syndrome utilizing the PedsQL™. Journal of Autism and Developmental Disorders, 39, 1529–1541.PubMedCrossRefGoogle Scholar
  22. 22.
    Fayers, P. M., & Hand, D. J. (1997). Factor analysis, causal indicators and quality of life. Quality of Life Research, 6, 139–150.PubMedGoogle Scholar
  23. 23.
    Rubenstein, C. L., Varni, J. W., & Katz, E. R. (1990). Cognitive functioning in long-term survivors of childhood leukemia: A prospective analysis. Journal of Developmental and Behavioral Pediatrics, 11, 301–305.PubMedCrossRefGoogle Scholar
  24. 24.
    Copeland, D. R. (1992). Neuropsychological and psychosocial effects of childhood leukemia and its treatment. CA-A Cancer Journal for Clinicians, 42, 283–295.PubMedCrossRefGoogle Scholar
  25. 25.
    Mulhern, R. K., Hancock, J., Fairclough, D., & Kun, L. (1992). Neuropsychological status of children treated for brain tumors: A critical review and integrative analysis. Medical and Pediatric Oncology, 20, 181–191.PubMedCrossRefGoogle Scholar
  26. 26.
    Meadows, A. T., Massari, D. J., & Fergusson, J. (1981). Declines in IQ scores and cognitive dysfunctions in children with acute lymphocytic leukemia treated with cranial irradiation. Lancet, 2, 1015–1018.PubMedCrossRefGoogle Scholar
  27. 27.
    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.PubMedCrossRefGoogle Scholar
  28. 28.
    McHorney, C. A., Kosinski, M., & Ware, J. E. (1994). Comparisons of the costs and quality of norms for the SF-36 Health Survey collected by mail versus telephone interview: Results from a national survey. Medical Care, 32, 551–567.PubMedCrossRefGoogle Scholar
  29. 29.
    Fairclough, D. L., & Cella, D. F. (1996). Functional assessment of cancer therapy (FACT-G): Non-response to individual questions. Quality of Life Research, 5, 321–329.PubMedCrossRefGoogle Scholar
  30. 30.
    Gioia, G. A., Isquith, P. K., Guy, S. C., & Kenworthy, L. (2000). Behavior rating inventory of executive function. Odessa, FL: Psychological Assessment Resources.Google Scholar
  31. 31.
    Sesma, H. W., Slomine, B. S., Ding, R., & McCarthy, M. L. (2008). Executive functioning in the first year after pediatric traumatic brain injury. Pediatrics, 121, e1686–e1695.PubMedCrossRefGoogle Scholar
  32. 32.
    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.PubMedCrossRefGoogle Scholar
  33. 33.
    Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16, 297–334.CrossRefGoogle Scholar
  34. 34.
    Nunnally, J. C., & Bernstein, I. R. (1994). Psychometric theory (3rd ed.). New York: McGraw-Hill.Google Scholar
  35. 35.
    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.PubMedCrossRefGoogle Scholar
  36. 36.
    Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Hillsdale, NJ: Erlbaum.Google Scholar
  37. 37.
    Pedhazur, E. J., & Schmelkin, L. P. (1991). Measurement, design, and analysis: An integrated approach. Hillsdale, NJ: Erlbaum.Google Scholar
  38. 38.
    McGraw, K. O., & Wong, S. P. (1996). Forming inferences about some intraclass correlation coefficients. Psychological Methods, 1, 30–46.CrossRefGoogle Scholar
  39. 39.
    Wilson, K. A., Dowling, A. J., Abdolell, M., & Tannock, I. F. (2001). Perception of quality of life by patients, partners and treating physicians. Quality of Life Research, 9, 1041–1052.CrossRefGoogle Scholar
  40. 40.
    SPSS. (2008). SPSS 16.0 for windows. Chicago: SPSS, Inc.Google Scholar
  41. 41.
    Upton, P., Lawford, J., & Eiser, C. (2008). Parent-child agreement across child health-related quality of life instruments: A review of the literature. Quality of Life Research, 17, 895–913.PubMedCrossRefGoogle Scholar
  42. 42.
    Eiser, C., & Morse, R. (2001). Can parents rate their child’s health-related quality of life?: Results from a systematic review. Quality of Life Research, 10, 347–357.PubMedCrossRefGoogle Scholar
  43. 43.
    Varni, J. W., Limbers, C. A., & Burwinkle, T. M. (2007). Parent proxy-report of their children’s health-related quality of life: An analysis of 13, 878 parents’ reliability and validity across age subgroups using the PedsQL™ 4.0 Generic Core Scales. Health and Quality of Life Outcomes, 5(2), 1–10.PubMedCrossRefGoogle Scholar
  44. 44.
    Varni, J. W., Burwinkle, T. M., & Seid, M. (2006). The PedsQL™ 4.0 as a school population health measure: Feasibility, reliability, and validity. Quality of Life Research, 15, 203–215.PubMedCrossRefGoogle Scholar
  45. 45.
    Newman, D. A., Limbers, C. A., & Varni, J. W. (2010). Factorial invariance of child self-report across English and Spanish language groups in a Hispanic population utilizing the PedsQL™ 4.0 Generic Core Scales. European Journal of Psychological Assessment, 26, 194–202.CrossRefGoogle Scholar
  46. 46.
    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.PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  • James W. Varni
    • 1
    Email author
  • Christine A. Limbers
    • 2
  • Lisa G. Sorensen
    • 3
  • Katie Neighbors
    • 4
  • Karen Martz
    • 5
  • John C. Bucuvalas
    • 6
  • Estella M. Alonso
    • 4
  1. 1.Department of Pediatrics, College of Medicine, Department of Landscape Architecture and Urban Planning, College of ArchitectureTexas A&M UniversityCollege StationUSA
  2. 2.Department of Psychology and NeuroscienceBaylor UniversityWacoUSA
  3. 3.Department of Child and Adolescent Psychiatry, Children’s Memorial HospitalNorthwestern UniversityChicagoUSA
  4. 4.Department of Pediatrics, Children’s Memorial HospitalNorthwestern UniversityChicagoUSA
  5. 5.EMMES CorporationRockvilleUSA
  6. 6.Department of PediatricsCincinnati Children’s Hospital Medical CenterCincinnatiUSA

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