PedsQL™ 4.0: Reliability and Validity of the Pediatric Quality of Life Inventory™ Version 4.0 Generic Core Scales in Healthy and Patient Populations

Background.The PedsQL (Pediatric Quality of Life Inventory) (Children’s Hospital and Health Center, San Diego, California) is a modular instrument for measuring health-related quality of life (HRQOL) in children and adolescents ages 2 to 18. The PedsQL 4.0 Generic Core Scales are multidimensional child self-report and parent proxy-report scales developed as the generic core measure to be integrated with the PedsQL Disease-Specific Modules. The PedsQL 4.0 Generic Core Scales consist of 23 items applicable for healthy school and community populations, as well as pediatric populations with acute and chronic health conditions. Methods.The 4 PedsQL 4.0 Generic Core Scales (Physical, Emotional, Social, School) were administered to 963 children and 1,629 parents (1,677 subjects accrued overall) recruited from pediatric health care settings. Item-level and scale-level measurement properties were computed. Results.Internal consistency reliability for the Total Scale Score (&agr; = 0.88 child, 0.90 parent report), Physical Health Summary Score (&agr; = 0.80 child, 0.88 parent), and Psychosocial Health Summary Score (&agr; = 0.83 child, 0.86 parent) were acceptable for group comparisons. Validity was demonstrated using the known-groups method, correlations with indicators of morbidity and illness burden, and factor analysis. The PedsQL distinguished between healthy children and pediatric patients with acute or chronic health conditions, was related to indicators of morbidity and illness burden, and displayed a factor-derived solution largely consistent with the a priori conceptually-derived scales. Conclusion.The results demonstrate the reliability and validity of the PedsQL 4.0 Generic Core Scales. The PedsQL 4.0 Generic Core Scales may be applicable in clinical trials, research, clinical practice, school health settings, and community populations.

[1]  J. Varni,et al.  The PedsQL: measurement model for the pediatric quality of life inventory. , 1999, Medical care.

[2]  J. Ware,et al.  Testing the equivalence of translations of widely used response choice labels: results from the IQOLA Project. International Quality of Life Assessment. , 1998, Journal of clinical epidemiology.

[3]  J. Varni,et al.  The pediatric cancer quality of life inventory‐32 (PCQL‐32) , 1998, Cancer.

[4]  J. Varni,et al.  Effects of pediatric chronic physical disorders on child and family adjustment. , 1998, Journal of child psychology and psychiatry, and allied disciplines.

[5]  G. Guyatt,et al.  Children and adult perceptions of childhood asthma. , 1997, Pediatrics.

[6]  D. Mark,et al.  Medical care costs and quality of life after randomization to coronary angioplasty or coronary bypass surgery. Bypass Angioplasty Revascularization Investigation (BARI) Investigators. , 1997, The New England journal of medicine.

[7]  J. Pater Quality of life and pharmacoeconomics in clinical trials , 1996 .

[8]  J. Varni,et al.  Development of the Waldron/Varni Pediatric Pain Coping Inventory , 1996, PAIN.

[9]  J. Varni,et al.  Chronic Pain and Emotional Distress in Children and Adolescents , 1996, Journal of developmental and behavioral pediatrics : JDBP.

[10]  J. Varni,et al.  Adjustment of Children with Newly Diagnosed Cancer: Cross-Informant Variance , 1996 .

[11]  J. Passchier,et al.  A Quality of Life Instrument for Adolescents with Chronic Headache , 1996, Cephalalgia : an international journal of headache.

[12]  M. Gold,et al.  Assessing the health of the nation. The predictive validity of a preference-based measure and self-rated health. , 1996, Medical care.

[13]  P. Ganz Impact of quality of life outcomes on clinical practice. , 1995, Oncology.

[14]  M. Bullinger German translation and psychometric testing of the SF-36 Health Survey: preliminary results from the IQOLA Project. International Quality of Life Assessment. , 1995, Social science & medicine.

[15]  S. Peskin Applications of QOL measurements: a managed care perspective. , 1995, Oncology.

[16]  J. Farndon,et al.  Observer variation in assessment of quality of life in patients with oesophageal cancer , 1995, The British journal of surgery.

[17]  Stefaan Decoene,et al.  Measurement, design, and analysis - an integrated approach - pedhazur,ej, schmelkin,lp , 1995 .

[18]  F. Floyd,et al.  Factor analysis in the development and refinement of clinical assessment instruments. , 1995 .

[19]  L. K. Bartholomew,et al.  Measurement of quality of well being in a child and adolescent cystic fibrosis population. , 1994, Medical care.

[20]  C. Sherbourne,et al.  The MOS 36-item Short-Form Health Survey (SF-36): III. Tests of data quality, scaling assumptions, and reliability across diverse patient groups. , 1994 .

[21]  C. McHorney,et al.  The MOS 36‐Item Short‐Form Health Survey (SF‐36): II. Psychometric and Clinical Tests of Validity in Measuring Physical and Mental Health Constructs , 1993, Medical care.

[22]  N. Aaronson,et al.  The role of health care providers and significant others in evaluating the quality of life of patients with chronic disease: A review , 1992 .

[23]  C. Sherbourne,et al.  The MOS 36-Item Short-Form Health Survey (SF-36) , 1992 .

[24]  Anastasia E. Raczek,et al.  The validity and relative precision of MOS short- and long-form health status scales and Dartmouth COOP charts. Results from the Medical Outcomes Study. , 1992, Medical care.

[25]  N. Aaronson,et al.  The role of health care providers and significant others in evaluating the quality of life of patients with chronic disease: a review. , 1992, Journal of clinical epidemiology.

[26]  J. Varni,et al.  Screening for behavioral and emotional problems in children and adolescents with congenital or acquired limb deficiencies. , 1992, American journal of diseases of children.

[27]  Elazar J. Pedhazur,et al.  Measurement, Design, and Analysis: An Integrated Approach , 1994 .

[28]  G. Guyatt,et al.  Issues in quality-of-life measurement in clinical trials. , 1991, Controlled clinical trials.

[29]  Ron D. Hays,et al.  Beyond internal consistency reliability: Rationale and user’s guide for Multitrait Analysis Program on the microcomputer , 1990 .

[30]  P. Lachenbruch Statistical Power Analysis for the Behavioral Sciences (2nd ed.) , 1989 .

[31]  R. Deyo,et al.  Generic and Disease-Specific Measures in Assessing Health Status and Quality of Life , 1989, Medical care.

[32]  J. Varni,et al.  Chronic musculoskeletal pain and functional status in juvenile rheumatoid arthritis: an empirical model , 1988, Pain.

[33]  R. Hays,et al.  A microcomputer program for analyzing multitrait-multimethod matrices , 1987 .

[34]  K L Thompson,et al.  The Varni/Thompson Pediatrie Pain Questionnaire. I. Chronic musculoskeletal pain in juvenile rheumatoid arthritis , 1987, Pain.

[35]  T. Achenbach,et al.  Child/adolescent behavioral and emotional problems: implications of cross-informant correlations for situational specificity. , 1987, Psychological bulletin.

[36]  J. Varni,et al.  A developmental cognitive-biobehavioral approach to pediatric pain assessment , 1986, Pain.

[37]  L. Cronbach Coefficient alpha and the internal structure of tests , 1951 .