Top

Gepubliceerd in:

01-10-2013 | Brief Communication

Confirmatory factor analysis of the PedsQL among youth in a residential treatment setting

Auteurs: Steven Hoffman, Matthew C. Lambert, Timothy D. Nelson, Alexandra L. Trout, Michael H. Epstein, Robert Pick

Gepubliceerd in: Quality of Life Research | Uitgave 8/2013

Abstract

Purpose

The Pediatric Quality of Life assessment (PedsQL™) is the most widely used measure for assessing adolescent health-related quality of life (HRQoL). While youth in residential treatment facilities face many physical and mental health, behavioral, education, and familial challenges that could impact their HRQoL, no research has sought to assess the factor structure of the PedsQL™ among youth receiving residential care.

Methods

High school–aged youth (N = 229) attending a large residential treatment center in Omaha, NE were recruited to complete a data collection packet comprised of various health assessments including the PedsQL. Four competing confirmatory factor analysis models were used to test the hypothesized internal structure of the PedsQL™ 4.0 Teen Report.

Results

Models A, B, and C had acceptable CFI (≥.90), TLI (≥.90), and RMSEA (≤.08) fit indicators. However, factor loadings for items 5 and 6 were problematic. After removing the two problematic items, Model D was fit to the data and proved to be the superior of the four models. This model included two first-order factors (physical health problems; school attendance problems) and one second-order factor (psychological health problems).

Conclusions

The findings suggest that researchers and practitioners studying youth in residential settings can reliably use the PedsQL™ to assess their HRQoL.

vorige artikel Prognostic value of patient-reported symptom interference in patients with late-stage lung cancer

volgende artikel Exposure to traumatic events and health-related quality of life in preschool-aged children

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.PubMedCrossRef

Dalmida, S. G. (2006). Spirituality, mental health, physical health, and health-related quality of life among women with HIV/AIDS: Integrating spirituality into mental health care. Issues in Mental Health Nursing, 27, 185–198.PubMedCrossRef

Eton, D. T., & Lepore, S. J. (2002). Prostate cancer and health-related quality of life: A review of the literature. Psychooncology, 11, 307–326.PubMedCrossRef

Eisenman, D. P., Gelberg, L., Liu, H., & Shapiro, M. F. (2003). Mental health and health-related quality of life among adult Latino primary care patients living in the United States with previous exposure to political violence. The Journal of the American Medical Association, 290, 627–634.CrossRef

Institute of Medicine. (2012). Living well with chronic illness: A call for public health action. Washington, DC: The National Academics Press.

Asarnow, J. R., Aoki, W., & Elson, S. (1996). Children in residential treatment: A follow-up study. Journal of Clinical Child Psychology, 25, 209–214.CrossRef

Drais-Parrillo, A. A., Baker, A., Fojaz, S., Gunn, S., Kurland, D., & Schnur, E. (2005). The Odyssey project: A descriptive and prospective study of children and youth in residential group care and therapeutic foster care. Washington, DC: Child Welfare League of America.

Nelson, T. D., Smith, T. R., Thompson, R. W., Epstein, M. H., Griffith, A. K., Duppong Hurley, K., et al. (2011). Prevalence of physical health problems among youth entering residential treatment. Pediatrics, 128, e1226–e1232.PubMedCrossRef

Varni, J. W. (2012). About the model. The PedsQL™ Measurement Model for the Pediatric Quality of Life Inventory. http://www.pedsql.org/about_pedsql.html. Accessed June 28, 2012.

10.

Hao, Y., Tian, Q., Lu, Y., Chai, Y., & Rao, S. (2010). Psychometric properties of the Chinese version of the Pediatric Quality of Life Inventory 4.0 generic core scales. Quality of Life Research, 19, 1229–1233.PubMedCrossRef

11.

Lin, C. Y., Luh, W. M., Yang, A. L., Su, C. T., Wang, J. D., & Ma, J. I. (2012). Psychometric properties and gender invariance of the Chinese version of the self-report Pediatric Quality of Life Inventory version 4.0: Short form is acceptable. Quality of Life Research, 21, 177–182.PubMedCrossRef

12.

Panepinto, J. A., Hoffmann, R. G., & Pajewski, N. M. (2009). A psychometric evaluation of the PedsQL™ family impact module in parents of children with sickle cell disease. Health and Quality of Life Outcomes, 7, 1–11.

13.

Perrin, J. M., Kuhlthau, K., Chughtai, A., Romm, D., Kirschener, B. S., Ferry, G. D., et al. (2008). Measuring quality of life in pediatric patients with inflammatory bowel disease: Psychometric and clinical characteristics. Journal of Pediatric Gastroenterology and Nutrition, 46, 164–171.PubMedCrossRef

14.

Muthén, L. K., & Muthén, B. O. (1998–2009). Mplus user’s guide (6th ed.). Los Angeles, CA: Muthén & Muthén.

15.

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 utilizing the PedsQL 4.0 Generic Core Scales. Journal of Pediatric Psychology, 33, 630–639.PubMedCrossRef

16.

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.PubMedCrossRef

17.

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.PubMedCrossRef

18.

Varni, J. W. (2010). Scaling and scoring of the Pediatric Quality of Life Inventory™ (PedsQL™). France: Mapi Research Trust.

19.

Little, T. D., Slegers, D. W., & Card, N. A. (2006). A non-arbitrary method of identifying and scaling latent variables in SEM and MACS models. Structural Equation Modeling, 13(1), 59–72.CrossRef

20.

Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107(2), 238–246.PubMedCrossRef

21.

Tucker, L., & Lewis, C. (1973). A reliability coefficient for maximum likelihood factor analysis. Psychometrika, 38(1), 1–10.CrossRef

22.

Steiger, J. H., & Lind, J. C. (1980, May). Statistically based tests for the number of common factors. Paper presented at the annual meeting of the Psychometric Society, Iowa City, IA.

23.

Browne, M. W., & Cudeck, R. (1993). Alternative ways of accessing model fit. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models (pp. 136–162). Newbury Park, CA: Sage.

24.

Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1–55.CrossRef

Titel: Confirmatory factor analysis of the PedsQL among youth in a residential treatment setting
Auteurs: Steven Hoffman
Matthew C. Lambert
Timothy D. Nelson
Alexandra L. Trout
Michael H. Epstein
Robert Pick
Publicatiedatum: 01-10-2013
Uitgeverij: Springer Netherlands
Gepubliceerd in: Quality of Life Research / Uitgave 8/2013
Print ISSN: 0962-9343
Elektronisch ISSN: 1573-2649
DOI: https://doi.org/10.1007/s11136-012-0327-z

Bohn Stafleu van Loghum

Deel dit onderdeel of sectie (kopieer de link)

Abstract

Purpose

Methods

Results

Conclusions

Log in om toegang te krijgen

Andere artikelen Uitgave 8/2013

Evaluation of the Social Participation Questionnaire in adult patients with depressive symptoms using Rasch analysis

A comparison of the scaling properties of the English, Spanish, French, and Chinese EQ-5D descriptive systems

Condition-specific quality of life questionnaires for caregivers of children with pediatric conditions: a systematic review

Health-related quality of life improvement via telemedicine for epilepsy: printed versus SMS-based education intervention

Factor structure of the Child Health Questionnaire Parent Form-50 and predictors of health-related quality of life in children with epilepsy

SF-36v2 norms and its’ discriminative properties among healthy households of tuberculosis patients in Malaysia