Swipe om te navigeren naar een ander artikel
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 new PedsQL™ Infant Scales were designed as a generic HRQOL instrument specifically for healthy and ill infants ages 1–24 months. The objective of this study was to report on the initial feasibility, internal consistency reliability, and validity of the PedsQL™ Infant Scales in healthy, acutely ill, and chronically ill infants.
The 36-item (ages 1–12 months) and 45-item (ages 13–24 months) PedsQL™ Infant Scales (Physical Functioning, Physical Symptoms, Emotional Functioning, Social Functioning, Cognitive Functioning) were completed by 683 parents of healthy, acutely ill, and chronically ill infants.
The PedsQL™ Infant Scales evidenced minimal missing responses, achieved excellent internal consistency reliability for the Total Scale Scores (α = 0.92), distinguished between healthy infants and acutely and chronically ill infants, and demonstrated a confirmatory factor structure largely consistent with the a priori conceptual model.
The results demonstrate the initial measurement properties of the PedsQL™ Infant Scales in healthy and ill infants. The findings suggest that the PedsQL™ Infant Scales may be utilized in the evaluation of generic HRQOL in infants ages 1–24 months.
Log in om toegang te krijgen
Met onderstaand(e) abonnement(en) heeft u direct toegang:
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.
Palermo, T. M., Long, A. C., Lewandowski, A. S., Drotar, D., Quittner, A. L., & Walker, L. S. (2008). Evidence-based assessment of health-related quality of life and functional impairment in pediatric psychology. Journal of Pediatric Psychology,33, 896–983. CrossRef
World Health Organization. (1948). Constitution of the World Health Organization: Basic document. Geneva, Switzerland: World Health Organization.
FDA. (2009). Guidance for Industry: Patient-reported outcome measures: Use in medical product development to support labeling claims. Rockville, MD: Food and Drug Administration, U.S. Department of Health and Human Services.
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. CrossRefPubMed
Aday, L. A. (1996). Designing and conducting health surveys: A comprehensive guide (2nd ed.). San Francisco: Jossey-Bass.
Fowler, F. J. (1995). Improving survey questions: Design and evaluation. Thousand Oaks, CA: Sage.
Schwarz, N., & Sudman, N. (Eds.). (1996). Answering questions: Methodology for determining cognitive and communicative processes in survey research. San Francisco: Jossey-Bass.
Fairclough, D. L. (2002). Design and analysis of quality of life studies in clinical trials: Interdisciplinary statistics. New York: Chapman & Hall/CRC.
Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika,16, 297–334. CrossRef
Nunnally, J. C., & Bernstein, I. R. (1994). Psychometric theory (3rd ed.). New York: McGraw-Hill.
Pedhazur, E. J., & Schmelkin, L. P. (1991). Measurement, design, and analysis: An integrated approach. Hillsdale, NJ: Erlbaum.
Fayers, P. M., & Machin, D. (2000). Quality of life: Assessment, analysis, and interpretation. New York: Wiley.
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. CrossRefPubMed
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Erlbaum.
SPSS. (2008). SPSS 16.0 for Windows. Chicago: SPSS, Inc.
Hurley, A. E., Scandura, T. A., Schriesheim, C. A., Brannick, M. T., Seers, A., Vandenberg, R. J., et al. (1997). Exploratory and confirmatory factor analysis: Guidelines, issues, and alternatives. Journal of Organizational Behavior,18, 667–683. CrossRef
Mulaik, S., James, L., Van Alstine, J., Bennett, N., Lind, S., & Stilwell, C. (1989). Evaluation of goodness-of-fit indices for structural equation models. Psychological Bulletin,105, 430–445. CrossRef
Steiger, J. H. (1990). Structural model evaluation and modification: An interval estimation approach. Multivariate Behavioral Research,25, 173–180. CrossRef
Tucker, L. R., & Lewis, C. (1973). A reliability coefficient for maximum likelihood factor analysis. Psychometrika,38, 1–10. CrossRef
Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indices in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling,6, 1–55. CrossRef
Browne, M. W., & Cudeck, R. (1992). Alternative ways of assessing model fit. Sociological Methods and Research,21, 230–258. CrossRef
Hu. L., & Bentler, P. M. (1995). Evaluating model fit. In Hoyle, R. H. (Ed.) Structural equation modeling: Concepts, issues and applications (pp. 76–99) . Thousand Oaks: Sage.
Joreskog, K. G., & Sorbom, D. (2003). LISREL 8.5. Lincolnwood, IL: Scientific Software International, Inc.
- The PedsQL™ Infant Scales: feasibility, internal consistency reliability, and validity in healthy and ill infants
James W. Varni
Christine A. Limbers
Judith E. C. Lieu
Robert W. Heffer
Jerry J. Zimmerman
Estella M. Alonso
- Springer Netherlands