How young can children reliably and validly self-report their health-related quality of life?: an analysis of 8,591 children across age subgroups with the PedsQL 4.0 Generic Core Scales

James W Varni, Christine A Limbers, Tasha M Burwinkle, James W Varni, Christine A Limbers, Tasha M Burwinkle

Abstract

Background: The last decade has evidenced a dramatic increase in the development and utilization of pediatric health-related quality of life (HRQOL) measures in an effort to improve pediatric patient health and well-being and determine the value of healthcare services. The emerging paradigm shift toward patient-reported outcomes (PROs) in clinical trials has provided the opportunity to further emphasize the value and essential need for pediatric patient self-reported outcomes measurement. Data from the PedsQL DatabaseSM were utilized to test the hypothesis that children as young as 5 years of age can reliably and validly report their HRQOL.

Methods: The sample analyzed represented child self-report age data on 8,591 children ages 5 to 16 years from the PedsQL 4.0 Generic Core Scales DatabaseSM. Participants were recruited from general pediatric clinics, subspecialty clinics, and hospitals in which children were being seen for well-child checks, mild acute illness, or chronic illness care (n = 2,603, 30.3%), and from a State Children's Health Insurance Program (SCHIP) in California (n = 5,988, 69.7%).

Results: Items on the PedsQL 4.0 Generic Core Scales had minimal missing responses for children as young as 5 years old, supporting feasibility. The majority of the child self-report scales across the age subgroups, including for children as young as 5 years, exceeded the minimum internal consistency reliability standard of 0.70 required for group comparisons, while the Total Scale Scores across the age subgroups approached or exceeded the reliability criterion of 0.90 recommended for analyzing individual patient scale scores. Construct validity was demonstrated utilizing the known groups approach. For each PedsQL scale and summary score, across age subgroups, including children as young as 5 years, healthy children demonstrated a statistically significant difference in HRQOL (better HRQOL) than children with a known chronic health condition, with most effect sizes in the medium to large effect size range.

Conclusion: The results demonstrate that children as young as the 5 year old age subgroup can reliably and validly self-report their HRQOL when given the opportunity to do so with an age-appropriate instrument. These analyses are consistent with recent FDA guidelines which require instrument development and validation testing for children and adolescents within fairly narrow age groupings and which determine the lower age limit at which children can provide reliable and valid responses across age categories.

References

    1. Varni JW, Burwinkle TM, Lane MM. 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. 2005;3:34:1–9.
    1. Matza LS, Swensen AR, Flood EM, Secnik K, Leidy NK. Assessment of health-related quality of life in children: A review of conceptual, methodological, and regulatory issues. Value in Health. 2004;7:79–92. doi: 10.1111/j.1524-4733.2004.71273.x.
    1. Fayers PM, Machin D. Quality of life: Assessment, analysis, and interpretation. New York , Wiley; 2000.
    1. Spilker B. Quality of life and pharmacoeconomics in clinical trials. 2nd. Philadelphia , Lippincott-Raven; 1996.
    1. Varni JW, Seid M, Kurtin PS. Pediatric health-related quality of life measurement technology: A guide for health care decision makers. Journal of Clinical Outcomes Management. 1999;6:33–40.
    1. World Health Organization . Constitution of the World Health Organization: Basic Document. Geneva, Switzerland , World Health Organization; 1948.
    1. FDA . Guidance for Industry: Patient-reported outcome measures: Use in medical product development to support labeling claims. Center for Drug Evaluation and Research, Food and Drug Administration, Rockville, MD; 2006.
    1. Eiser C. Use of quality of life measures in clinical trials. Ambulatory Pediatrics. 2004;4:395–399. doi: 10.1367/A03-112R.1.
    1. Razzouk BI, Hord JD, Hockenberry M, Hinds PS, Feusner J, Williams D, Rackoff WR. 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. 2006;24:3583–3589. doi: 10.1200/JCO.2005.03.4371.
    1. Varni JW, Burwinkle TM, Seid M. 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. 2005;5:705–719. doi: 10.1586/14737167.5.6.705.
    1. Schwimmer JB, Middleton MS, Deutsch R, Lavine JE. A phase 2 trial of metformin as a treatment for non-diabetic pediatric non-alcoholic steatohepatitis. Alimentary Pharmacology & Therapeutics. 2005;21:871–879. doi: 10.1111/j.1365-2036.2005.02420.x.
    1. Connelly M, Rapoff MA. 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. 2006;31:698–702. doi: 10.1093/jpepsy/jsj063.
    1. Clarke SA, Eiser C. The measurement of health-related quality of life in pediatric clinical trials: A systematic review. Health and Quality of Life Outcomes. 2004;2:66:1–5.
    1. Acquadro C, Berzon R, Dubois D, Leidy NK, Marquis P, Revicki D, Rothman M. Incorporating the patient's perspective into drug development and communication: An ad hoc task force report of the patient-reported outcomes (PRO) harmonization group meeting at the Food and Drug Administration, February 16, 2001. Value in Health. 2003;6:522–531. doi: 10.1046/j.1524-4733.2003.65309.x.
    1. Willke RJ, Burke LB, Erickson P. Measuring treatment impact: A review of patient-reported outcomes and other efficacy endpoints in approved product labels. Controlled Clinical Trials. 2004;25:535–552. doi: 10.1016/j.cct.2004.09.003.
    1. Sherman SA, Eisen S, Burwinkle TM, Varni JW. The PedsQL™ Present Functioning Visual Analogue Scales: Preliminary reliability and validity. Health and Quality of Life Outcomes. 2006;4:75:1–10.
    1. McGrath PA. Pain in children: Nature, assessment, and treatment. New York , Guilford; 1990.
    1. Varni JW, Thompson KL, Hanson V. The Varni/Thompson Pediatric Pain Questionnaire: I. Chronic musculoskeletal pain in juvenile rheumatoid arthritis. Pain. 1987;28:27–38. doi: 10.1016/0304-3959(87)91056-6.
    1. Varni JW, Bernstein BH. Evaluation and management of pain in children with rheumatic diseases. Rheumatic Disease Clinics of North America. 1991;17:985–1000.
    1. Sprangers MAG, Aaronson NK. The role of health care providers and significant others in evaluating the quality of life of patients with chronic disease: A review. Journal of Clinical Epidemiology. 1992;45:743–760. doi: 10.1016/0895-4356(92)90052-O.
    1. Achenbach TM, McConaughy SH, Howell CT. Child/adolescent behavioral and emotional problems: Implications of cross-informant correlations for situational specificity. Psychological Bulletin. 1987;101:213–232. doi: 10.1037/0033-2909.101.2.213.
    1. Varni JW, Katz ER, Colegrove R, Dolgin M. Adjustment of children with newly diagnosed cancer: Cross-informant variance. Journal of Psychosocial Oncology. 1995;13:23–38. doi: 10.1300/J077V13N04_02.
    1. Varni JW, Katz ER, Seid M, Quiggins DJL, Friedman-Bender A, Castro CM. The Pediatric Cancer Quality of Life Inventory (PCQL): I. Instrument development, descriptive statistics, and cross-informant variance. Journal of Behavioral Medicine. 1998;21:179–204. doi: 10.1023/A:1018779908502.
    1. Varni JW, Seid M, Rode CA. The PedsQL™: Measurement model for the Pediatric Quality of Life Inventory. Medical Care. 1999;37:126–139. doi: 10.1097/00005650-199902000-00003.
    1. Levi RB, Drotar D. Health-related quality of life in childhood cancer: Discrepancy in parent–child reports. International Journal of Cancer. 1999;12:58–64. doi: 10.1002/(SICI)1097-0215(1999)83:12+<58::AID-IJC11>;2-A.
    1. Clancy C, McGrath P, Oddson B. Pain in children and adolescents with spina bifida. Developmental Medicine and Child Neurology. 2005;47:27–34. doi: 10.1017/S0012162205000058.
    1. Felder-Puig R, diGallo A, Waldenmair M, Norden P, Winter A, Gadner H, Topf R. Health-related quality of life of pediatric patients receiving allogeneic stem cell or bone marrow transplantation: Results of a longitudinal, multi-center study. Bone Marrow Transplantation. 2006;38:119–126. doi: 10.1038/sj.bmt.1705417.
    1. Vance YH, Morse RC, Jenney ME, Eiser C. Issues in measuring quality of life in childhood cancer: Measures, proxies, and parental mental health. Journal of Child Psychology and Psychiatry. 2001;42:661–667. doi: 10.1017/S0021963001007314.
    1. Chang P, Yeh C. Agreement between child self-report and parent proxy-report to evaluate quality of life in children with cancer. Psycho-Oncology. 2005;14:125–134. doi: 10.1002/pon.828.
    1. Yeh CH, Chang CW, Chang PC. Evaluating quality of life in children with cancer using children's self-reports and parent-proxy reports. Nursing Research. 2005;54:354–362. doi: 10.1097/00006199-200509000-00010.
    1. Eiser C, Morse R. Can parents rate their child's health-related quality of life?: Results from a systematic review. Quality of Life Research. 2001;10:347–357. doi: 10.1023/A:1012253723272.
    1. Theunissen NCM, Vogels TGC, Koopman HM, Verrips GHW, Zwinderman KAH, Verloove-Vanhorick SP, Wit JM. The proxy problem: Child report versus parent report in health-related quality of life research. Quality of Life Research. 1998;7:387–397. doi: 10.1023/A:1008801802877.
    1. De Los Reyes A, Kazdin AE. Measuring informant discrepancies in clinical child research. Psychological Assessment. 2004;16:330–334. doi: 10.1037/1040-3590.16.3.330.
    1. Richters JE. Depressed mothers as informants about their children: A critical review of the evidence for distortion. Psychological Bulletin. 1992;112:485–499. doi: 10.1037/0033-2909.112.3.485.
    1. Berg-Nielsen TS, Vika A, Dahl AA. When adolescents disagree with their mothers: CBCL-YSR discrepancies related to maternal depression and adolescent self-esteem. Child: Care, Health and Development. 2003;29:207–213. doi: 10.1046/j.1365-2214.2003.00332.x.
    1. Varni JW, Limbers CA, Burwinkle TM. 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. 2007.
    1. Varni JW, Seid M, Kurtin PS. 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. 2001;39:800–812. doi: 10.1097/00005650-200108000-00006.
    1. Varni JW, Burwinkle TM, Seid M, Skarr D. The PedsQL™ 4.0 as a pediatric population health measure: Feasibility, reliability, and validity. Ambulatory Pediatrics. 2003;3:329–341. doi: 10.1367/1539-4409(2003)003<0329:TPAAPP>;2.
    1. Varni JW, Waldron SA, Gragg RA, Rapoff MA, Bernstein BH, Lindsley CB, Newcomb MD. Development of the Waldron/Varni Pediatric Pain Coping Inventory. Pain. 1996;67:141–150. doi: 10.1016/0304-3959(96)03077-1.
    1. McHorney CA, Ware JE, Lu JFR, Sherbourne CD. 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. 1994;32:40–66. doi: 10.1097/00005650-199401000-00004.
    1. Fairclough DL, Cella DF. Functional Assessment of Cancer Therapy (FACT-G): Non-response to individual questions. Quality of Life Research. 1996;5:321–329. doi: 10.1007/BF00433916.
    1. Hollingshead AB. Four factor index of social status. New Haven, CT , Yale University; 1975.
    1. Cronbach LJ. Coefficient alpha and the internal structure of tests. Psychometrika. 1951;16:297–334. doi: 10.1007/BF02310555.
    1. Nunnally JC, Bernstein IR. Psychometric theory. 3rd. New York , McGraw-Hill; 1994.
    1. Pedhazur EJ, Schmelkin LP. Measurement, design, and analysis: An integrated approach. Hillsdale, NJ , Erlbaum; 1991.
    1. McHorney CA, Ware JE, Raczek AE. 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. 1993;31:247–263. doi: 10.1097/00005650-199303000-00006.
    1. Cohen J. Statistical power analysis for the behavioral sciences. 2nd. Hillsdale, NJ , Erlbaum; 1988.
    1. McGraw KO, Wong SP. Forming inferences about some Intraclass Correlation Coefficients. Psychological Methods. 1996;1:30–46. doi: 10.1037/1082-989X.1.1.30.
    1. Cremeens J, Eiser C, Blades M. Factors influencing agreement between child self-report and parent proxy-reports on the Pediatric Quality of Life Inventory™ 4.0 (PedsQL™) Generic Core Scales. Health and Quality of Life Outcomes. 2006;4:1–8.
    1. Bartko JJ. The intraclass correlation coefficient as a measure of reliability. Psychological Reports. 1966;19:3–11.
    1. Wilson KA, Dowling AJ, Abdolell M, Tannock IF. Perception of quality of life by patients, partners and treating physicians. Quality of Life Research. 2001;9:1041–1052. doi: 10.1023/A:1016647407161.
    1. Weng. Li-Jen Impact of the number of response categories and anchor labels on coefficient alpha and test-retest reliability. Educational and Psychological Measurement. 2004;64:956–972. doi: 10.1177/0013164404268674.
    1. Novick M, Lewis G. Coefficient alpha and the reliability of composite measurements. Psychometrika. 1967;32:1–13. doi: 10.1007/BF02289400.
    1. Eiser C, Morse R. Quality of life measures in chronic diseases of childhood. Health Technology Assessment. 2001;5:1–158.
    1. IOM . Crossing the quality chasm: A new health system for the 21st century. Washington, DC , National Academy of Sciences; 2001.
    1. Varni JW. PedsQL™ Website

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