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Factorial invariance of child self-report across socioeconomic status groups: a multigroup confirmatory factor analysis utilizing the PedsQLTM 4.0 Generic Core Scales

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Abstract

The measurement of health-related quality of life (HRQOL) in pediatric medicine and health services research has grown significantly over the past decade. Socioeconomic status (SES) differences in health outcomes have been extensively documented in adult and child populations. In order for HRQOL comparisons to be meaningful across different socioeconomic status (SES) groups, items on a HRQOL measure must have equivalent meaning across the SES subpopulations being compared. That is, they must demonstrate factorial invariance. This study examined factorial invariance of child self-report for ages 5–18 across SES groups in 453 children utilizing the PedsQLTM 4.0 Generic Core Scales. Multigroup Confirmatory Factor Analysis was performed specifying a five-factor model across two SES groups. SES groupings were assigned according to the Hollingshead Index of Social Status. Factorial invariance across socioeconomic status groups was demonstrated based on stability of the Comparative Fit Index (CFI) between the models, and several additional indices of practical fit including the Root Mean Squared Error of Approximation (RMSEA), the Non-Normed Fit Index (NNFI), and the Parsimony Normed Fit Index (PNFI). The findings support an equivalent five-factor structure of child self-report on the PedsQLTM across the two SES groups studied. Based on these data, it can be concluded that children across SES groups interpreted items on the PedsQLTM in a similar manner.

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References

  • Acquadro, C., Berzon, R., Dubois, D., Leidy, N. K., Marquis, P., Revicki, D., et al. (2003). 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, 6, 522–531. doi:10.1046/j.1524-4733.2003.65309.x.

    Article  PubMed  Google Scholar 

  • Barrett, R. J., Harlan, L. C., Wesley, M. N., Hill, H. A., Chen, V. W., Clayton, L. A., et al. (1995). Endometrial cancer: Stage at diagnosis and associated factors in black and white patients. American Journal of Obstetrics and Gynecology, 173, 414–422. doi:10.1016/0002-9378(95)90261-9.

    Article  PubMed  Google Scholar 

  • Bentler, P. (1990). Comparative fit indixes in structural models. Psychological Bulletin, 107, 238–246. doi:10.1037/0033-2909.107.2.238.

    Article  PubMed  Google Scholar 

  • Berrin, S. J., Malcarne, V. L., Varni, J. W., Burwinkle, T., Sherman, S. A., Artavia, K. A., et al. (2007). Pain, fatigue, and school functioning in children with cerebral palsy: A path-analytic model. Journal of Pediatric Psychology, 32, 330–337. doi:10.1093/jpepsy/jsl017.

    Article  PubMed  Google Scholar 

  • Bradley, R. H., & Corwyn, R. F. (2002). Socioeconomic status and child development. Annual Review of Psychology, 53, 371–399. doi:10.1146/annurev.psych.53.100901.135233.

    Article  PubMed  Google Scholar 

  • Browne, M. W., & Cudeck, R. (1992). Alternative ways of assessing model fit. Sociological Methods & Research, 21, 230–258. doi:10.1177/0049124192021002005.

    Article  Google Scholar 

  • Campbell, D. T., & Fiske, D. W. (1959). Convergent and discriminant validation by the multitrait-multimethod matrix. Psychological Bulletin, 56, 81–105. doi:10.1037/h0046016.

    Article  PubMed  Google Scholar 

  • Chen, E., Matthews, K. A., & Boyce, W. T. (2002). Socioeconomic differences in children’s health: How and why do these relationships change with age? Psychological Bulletin, 128, 295–329. doi:10.1037/0033-2909.128.2.295.

    Article  PubMed  Google Scholar 

  • Cheung, G. W., & Rensvold, R. B. (1999). What constitutes significant differences in evaluating measurement invariance? Conference of the Academy of Management, Chicago.

  • Cheung, G. W., Rensvold, R. B. (2002). Evaluating goodness-of-fit indexes for testing measurement invariance. Strctural Equation Modeling, 9, 233–255.

    Article  Google Scholar 

  • Cirino, P. T., Chin, C. E., Sevcik, R. A., Wolf, M., & Morris, R. D. (2002). Measuring socioeconomic status: Reliability and preliminary validity for different approaches. Assessment, 9, 145–155. doi:10.1177/10791102009002005.

    Article  PubMed  Google Scholar 

  • Clarke, S. A., & Eiser, C. (2004). The measurement of health-related quality of life in pediatric clinical trials: A systematic review. Health and Quality of Life Outcomes, 2(66), 1–5.

    Google Scholar 

  • Connelly, M., & Rapoff, M. A. (2006). Assessing health-related quality of life in children with recurrent headache: Reliability and validity of the PedsQLTM 4.0 in a pediatric sample. Journal of Pediatric Psychology, 31, 698–702. doi:10.1093/jpepsy/jsj063

    Google Scholar 

  • Denvir, M. A., Lee, A. J., Rysdale, J., Walker, A., Eteiba, H., Starkey, I. R., et al. (2006). Influence of socioeconomic status on clinical outcomes and quality of life after percutaneous coronary intervention. Journal of Epidemiology and Community Health, 60, 1085–1088. doi:10.1136/jech.2005.044255.

    Article  PubMed  Google Scholar 

  • Eiser, C. (2004). Use of quality of life measures in clinical trials. Ambulatory Pediatrics, 4, 395–399. doi:10.1367/A03-112R.1.

    Article  PubMed  Google Scholar 

  • FDA. (2006). Guidance for industry: Patient-reported outcome measures: Use in medical product development to support labeling claims. Rockville, MD: Center for Drug Evaluation and Research, Food and Drug Administration.

    Google Scholar 

  • Felder-Puig, R., Topf, R., Gadner, H., & Formann, A.K. (in press) Measuring health-related quality of life in children from different perspectives using the Pediatric Quality of Life InventoryTM (PedsQLTM) and teachers’ ratings. Journal of Public Health.

  • French, B., & Finch, W. (2006). Confirmatory factor analytic procedures for the determination of measurement invariance. Structural Equation Modeling, 13, 378–402. doi:10.1207/s15328007sem1303_3.

    Article  Google Scholar 

  • Gregorich, S. E. (2006). Do self-report instruments allow meaningful comparisons across diverse population groups?: Testing measurement invariance using the confirmatory factor analysis framework. Medical Care, 44, S78–S94. doi:10.1097/01.mlr.0000245454.12228.8f.

    Article  PubMed  Google Scholar 

  • Guilford, J. P. (1954). Psychometric methods. New York: McGraw-Hill.

    Google Scholar 

  • Hassan, K., Loar, R., Anderson, B. J., & Heptulla, R. A. (2006). The role of socioeconomic status, depression, quality of life, and glycemic control in Type 1 diabetes mellitus. The Journal of Pediatrics, 149, 526–531. doi:10.1016/j.jpeds.2006.05.039.

    Article  PubMed  Google Scholar 

  • Hollingshead, A. B. (1975). Four factor index of social status. New Haven, CT: Yale University.

    Google Scholar 

  • Horn, J. L., & McArdle, J. J. (1992). A practical and theoretical guide to measurement invariance in aging research. Experimental Aging Research, 18, 117–144.

    PubMed  Google Scholar 

  • Hu, L., & Bentler, P. M. (1995). Evaluating model fit. In R. H. Hoyle (Ed.), Structural equation modeling: Concepts, issues and applications. Thousand Oaks: Sage.

    Google Scholar 

  • Huguet, A., & Miro, J. (2008). Development and psychometric evaluation of a Catalan self- and interviewer-administered version of the Pediatric Quality of Life InventoryTM Version 4.0. Journal of Pediatric Psychology, 33, 63–79. doi:10.1093/jpepsy/jsm040.

    Article  PubMed  Google Scholar 

  • James, L. R., Mulaik, S. A., & Brett, J. M. (1982). Causal analysis: Models, assumptions, and data. Beverly Hills: Sage.

    Google Scholar 

  • Joreskog, K. G., & Sorbom, D. (1996). Lisrel 8: User’s Reference Guide. Chicago, IL: Scientific Software International.

    Google Scholar 

  • Joreskog, K. G., & Sorbom, D. (2003). LISREL 8.5. Lincolwood, IL: Scientific Software International, Inc.

    Google Scholar 

  • Kline, R. B. (2005). Principles and practice of structural equation modeling. New York: Guilford.

    Google Scholar 

  • Laaksonen, C., Aromaa, M., Heinonen, O. J., Heinonen, S., & Salantera, S. (2007). Pediatric health-related quality of life instrument for primary school children: Cross-cultural validation. Journal of Advanced Nursing, 59, 542–550. doi:10.1111/j.1365-2648.2007.04347.x.

    Article  PubMed  Google Scholar 

  • Limbers, C. A., Newman, D. A., & Varni, J. W. (in press). Factorial invariance of child self-report across age subgroups: A confirmatory factor analysis of ages 5 to 16 years utilizing the PedsQLTM 4.0 Generic Core Scales. Value in Health.

  • Limbers, C. A., Newman, D. A., & Varni, J. W. (2008). Factorial invariance of child self-report across healthy and chronic health condition groups: A confirmatory factor analysis of ages 5 to 18 years utilizing the PedsQLTM 4.0 Generic Core Scales. Journal of Pediatric Psychology, 33, 630–639. doi:10.1093/jpepsy/jsm131.

    Article  PubMed  Google Scholar 

  • Little, T. (1997). Mean and covariance structures (MACS) analyses of cross-cultural data: Practical and theoretical issues. Multivariate Behavioral Research, 31, 53–76. doi:10.1207/s15327906mbr3201_3.

    Article  Google Scholar 

  • MacCallum, R. C., Widaman, K. F., Preacher, K. J., & Hong, S. (2001). Sample size in factor analysis: The role of model error. Multivariate Behavioral Research, 36, 611–637. doi:10.1207/S15327906MBR3604_06.

    Article  Google Scholar 

  • Makari, J., Zaborskis, A., Labanauskas, L., & Rageliene, L. (2007). The quality of life of children suffering from oncologic diseases in Lithuania. Medicina, 43, 726–735.

    PubMed  Google Scholar 

  • Matza, L. S., Swensen, A. R., Flood, E. M., Secnik, K., & Leidy, N. K. (2004). Assessment of health-related quality of life in children: A review of conceptual, methodological, and regulatory issues. Value in Health, 7, 79–92. doi:10.1111/j.1524-4733.2004.71273.x.

    Article  PubMed  Google Scholar 

  • Maydeu-Olivares, A., & D’Zurilla, T. J. (1996). A factor-analytic study of the Social Problem-Solving Inventory: An integration of theory and data. Cognitive Therapy and Research, 20, 115–133. doi:10.1007/BF02228030.

    Article  Google Scholar 

  • Meredith, W., & Teresi, J. A. (2006). An essay on measurement and factorial invariance. Medical Care, 44, S69–S77. doi:10.1097/01.mlr.0000245438.73837.89.

    Article  PubMed  Google Scholar 

  • Montazeri, A., Hole, D. J., Milroy, R., McEwen, J., & Gillis, C. R. (2003). Quality of life in lung cancer patients: Does socioeconomic status matter? Health and Quality of Life Outcomes, 1, 1–6. doi:10.1186/1477-7525-1-1.

    Article  Google Scholar 

  • 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. doi:10.1037/0033-2909.105.3.430.

    Article  Google Scholar 

  • Nguyen, H. T., Kitner-Triolo, M., Evans, M. K., & Zonderman, A. B. (2004). Factorial invariance of the CES-D in low socioeconomic status African Americans compared with a nationally representative sample. Psychiatry Research, 126, 177–187. doi:10.1016/j.psychres.2004.02.004.

    Article  PubMed  Google Scholar 

  • O’Brien, P. C. (1992). Robust procedures for testing equality of covariance matrices. Biometrics, 48, 819–827. doi:10.2307/2532347.

    Article  Google Scholar 

  • Olson, L. M., Lara, M., & Frintner, M. P. (2004). Measuring health status and quality of life for US children: Relationship to race, ethnicity, and income status. Ambulatory Pediatrics, 4, 377–386. doi:10.1367/A03-156.1.

    Article  PubMed  Google Scholar 

  • Patrick, D. L., & Deyo, R. A. (1989). Generic and disease-specific measures in assessing health status and quality of life. Medical Care, 27, S217–S233. doi:10.1097/00005650-198903001-00018.

    Article  PubMed  Google Scholar 

  • Razzouk, B. I., Hord, J. D., Hockenberry, M., Hinds, P. S., Feusner, J., Williams, D., et al. (2006). 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, 24, 3583–3589. doi:10.1200/JCO.2005.03.4371.

    Article  PubMed  Google Scholar 

  • Reinfjell, T., Diseth, T. H., Veenstra, M., & Vikan, A. (2006). Measuring health-related quality of life in young adolescents: Reliability and validity in the Norwegian version of the Pediatric Quality of Life InventoryTM 4.0 (PedsQLTM) Generic Core Scales. Health and Quality of Life Outcomes, 4(61), 1–9.

    Google Scholar 

  • Schwimmer, J. B., Middleton, M. S., Deutsch, R., & Lavine, J. E. (2005). A phase 2 trial of metformin as a treatment for non-diabetic pediatric non-alcoholic steatohepatitis. Alimentary Pharmacology & Therapeutics, 21, 871–879. doi:10.1111/j.1365-2036.2005.02420.x.

    Article  Google Scholar 

  • Seid, M., Varni, J. W., Cummings, L., & Schonlau, M. (2006). The impact of realized access to care on health-related quality of life: A two-year prospective cohort study of children in the California State Children’s Health Insurance Program. The Journal of Pediatrics, 149, 354–361. doi:10.1016/j.jpeds.2006.04.024.

    Article  PubMed  Google Scholar 

  • Sherman, S. A., Eisen, S., Burwinkle, T. M., & Varni, J. W. (2006). The PedsQLTM present functioning visual analogue scales: Preliminary reliability and validity. Health and Quality of Life Outcomes, 4(75), 1–10.

    Google Scholar 

  • Sivo, S. A., Fan, X., Witta, E. L., & Willse, J. T. (2006). The search for optimal cutoff properties: Fit index criteria in structural equation modeling. Journal of Experimental Education, 74, 267–288. doi:10.3200/JEXE.74.3.267-288.

    Article  Google Scholar 

  • SPSS. (2007). SPSS 15.0 for Windows. Chicago: SPSS, Inc.

    Google Scholar 

  • Steiger, J. H. (1989). EzPath: A supplementary module for SYSTAT and SYGRAPH. Evanston, IL: SYSTAT Inc.

    Google Scholar 

  • Steiger, J. H. (1990). Structural model evaluation and modification: An interval estimation approach. Multivariate Behavioral Research, 25, 173–180. doi:10.1207/s15327906mbr2502_4.

    Article  Google Scholar 

  • Stern, M., Mazzeo, S. E., Gerke, C. K., Porter, J. S., Bean, M. K., & Laver, J. H. (2007). Gender, ethnicity, psychosocial factors, and quality of life among severely overweight, treatment-seeking adolescents. Journal of Pediatric Psychology, 32, 90–94. doi:10.1093/jpepsy/jsl013.

    Article  PubMed  Google Scholar 

  • Tucker, L. R., & Lewis, C. (1973). A reliability coefficient for maximum likelihood factor analysis. Psychometrika, 38, 1–10. doi:10.1007/BF02291170.

    Article  Google Scholar 

  • Uzark, K., Jones, K., Slusher, J., Limbers, C. A., Burwinkle, T. M., & Varni, J. W. (2008). Quality of life in children with heart disease as perceived by children and parents. Pediatrics, 121, e1060–e1067. doi:10.1542/peds.2006-3778.

    Article  PubMed  Google Scholar 

  • Vandenberg, R., & Lance, C. (2000). A review and synthesis of the measurement invariance literature: Suggestions, practices, and recommendations for organizational research. Organizational Research Methods, 3, 4–70. doi:10.1177/109442810031002.

    Article  Google Scholar 

  • Varni, J. W., Burwinkle, T. M., Berrin, S. J., Sherman, S. A., Artavia, K., Malcarne, V. L., et al. (2006a). The PedsQLTM in pediatric cerebral palsy: Reliability, validity, and sensitivity of the Generic Core Scales and Cerebral Palsy Module. Developmental Medicine and Child Neurology, 48, 442–449. doi:10.1017/S001216220600096X.

    Article  PubMed  Google Scholar 

  • Varni, J. W., Burwinkle, T. M., Jacobs, J. R., Gottschalk, M., Kaufman, F., & Jones, K. L. (2003a). The PedsQLTM in Type 1 and Type 2 diabetes: Reliability and validity of the Pediatric Quality of Life InventoryTM Generic Core Scales and Type 1 Diabetes Module. Diabetes Care, 26, 631–637. doi:10.2337/diacare.26.3.631.

    Article  PubMed  Google Scholar 

  • Varni, J. W., Burwinkle, T. M., Katz, E. R., Meeske, K., & Dickinson, P. (2002a). The PedsQLTM in pediatric cancer: Reliability and validity of the Pediatric Quality of Life InventoryTM Generic Core Scales, Multidimensional Fatigue Scale, and Cancer Module. Cancer, 94, 2090–2106. doi:10.1002/cncr.10428.

    Article  PubMed  Google Scholar 

  • Varni, J. W., Burwinkle, T. M., Rapoff, M. A., Kamps, J. L., & Olson, N. (2004). The PedsQLTM in pediatric asthma: Reliability and validity of the Pediatric Quality of Life InventoryTM Generic Core Scales and Asthma Module. Journal of Behavioral Medicine, 27, 297–318. doi:10.1023/B:JOBM.0000028500.53608.2c.

    Article  PubMed  Google Scholar 

  • Varni, J. W., Burwinkle, T. M., & Seid, M. (2006b). The PedsQLTM 4.0 as a school population health measure: Feasibility, reliability, and validity. Quality of Life Research, 15, 203–215. doi:10.1007/s11136-005-1388-z.

    Article  PubMed  Google Scholar 

  • Varni, J. W., Burwinkle, T. M., Seid, M., & Skarr, D. (2003b). The PedsQLTM 4.0 as a pediatric population health measure: Feasibility, reliability, and validity. Ambulatory Pediatrics, 3, 329–341. doi :10.1367/1539-4409(2003)003<0329:TPAAPP>2.0.CO;2

    Article  PubMed  Google Scholar 

  • Varni, J. W., Limbers, C. A., & Burwinkle, T. M. (2007a). 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 PedsQLTM 4.0 Generic Core Scales. Health and Quality of Life Outcomes, 5(1), 1–13. doi:10.1186/1477-7525-5-1.

    Article  PubMed  Google Scholar 

  • Varni, J. W., Limbers, C. A., & Burwinkle, T. M. (2007b). 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 PedsQLTM 4.0 Generic Core Scales. Health and Quality of Life Outcomes, 5(2), 1–10. doi:10.1186/1477-7525-5-1.

    Article  PubMed  Google Scholar 

  • Varni, J. W., Seid, M., Knight, T. S., Burwinkle, T. M., Brown, J., & Szer, I. S. (2002b). The PedsQLTM in pediatric rheumatology: Reliability, validity, and responsiveness of the Pediatric Quality of Life InventoryTM Generic Core Scales and Rheumatology Module. Arthritis and Rheumatism, 46, 714–725. doi:10.1002/art.10095.

    Article  PubMed  Google Scholar 

  • Varni, J. W., Seid, M., & Kurtin, P. S. (2001). PedsQLTM 4.0: Reliability and validity of the Pediatric Quality of Life InventoryTM Version 4.0 Generic Core Scales in healthy and patient populations. Medical Care, 39, 800–812. doi:10.1097/00005650-200108000-00006.

    Article  PubMed  Google Scholar 

  • Varni, J. W., Seid, M., & Rode, C. A. (1999). The PedsQLTM: Measurement model for the Pediatric Quality of Life Inventory. Medical Care, 37, 126–139. doi:10.1097/00005650-199902000-00003.

    Article  PubMed  Google Scholar 

  • von Rueden, U., Gosch, A., Rajmil, L., Bisegger, C., & Ravens-Sieberer, U. (2006). Socioeconomic determinants of health-related quality of life in childhood and adolescence: Results from a European study. Journal of Epidemiology and Community Health, 60, 130–135. doi:10.1136/jech.2005.039792.

    Article  Google Scholar 

  • Widaman, K. F. (1985). Hierarchically nested covariance structure models for multitrait-multimethod data. Applied Psychological Measurement, 9, 1–26. doi:10.1177/014662168500900101.

    Article  Google Scholar 

  • Willke, R. J., Burke, L. B., & Erickson, P. (2004). Measuring treatment impact: A review of patient-reported outcomes and other efficacy endpoints in approved product labels. Controlled Clinical Trials, 25, 535–552. doi:10.1016/j.cct.2004.09.003.

    Article  PubMed  Google Scholar 

  • World Health Organization. (1948). Constitution of the World Health Organization: Basic Document. Geneva, Switzerland: World Health Organization.

    Google Scholar 

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Acknowledgement

Preparation of this manuscript was supported by an intramural grant from the Texas A&M University Research Foundation.

Competing Interests:

Dr. Varni holds the copyright and the trademark for the PedsQLTM 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 InventoryTM.

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Authors and Affiliations

  1. Department of Psychology, College of Liberal Arts, Texas A&M University, College Station, TX, USA

    Christine A. Limbers

  2. Department of Psychology, University of Illinois at Urbana-Champaign, 603 East Daniel St., Champaign, IL, USA

    Daniel A. Newman

  3. Department of Pediatrics, College of Medicine, Texas A&M University, College Station, TX, USA

    James W. Varni

  4. Department of Landscape Architecture and Urban Planning, College of Architecture,, Texas A&M University, 3137 TAMU, College Station, TX, 77843-3137, USA

    James W. Varni

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  1. Christine A. Limbers
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Limbers, C.A., Newman, D.A. & Varni, J.W. Factorial invariance of child self-report across socioeconomic status groups: a multigroup confirmatory factor analysis utilizing the PedsQLTM 4.0 Generic Core Scales. J Behav Med 31, 401–411 (2008). https://doi.org/10.1007/s10865-008-9166-3

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