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Comparing Generic Paediatric Health-Related Quality-of-Life Instruments: A Dimensionality Assessment Using Factor Analysis.
Bahrampour, Mina; Jones, Renee; Dalziel, Kim; Devlin, Nancy; Mulhern, Brendan.
Afiliación
  • Bahrampour M; Centre for Health Economics Research and Evaluation (CHERE), University of Technology Sydney, Sydney, NSW, Australia. mina.bahrampour@uts.edu.au.
  • Jones R; Health Economics Unit, School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia.
  • Dalziel K; Health Economics Unit, School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia.
  • Devlin N; Health Economics Unit, School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia.
  • Mulhern B; Centre for Health Economics Research and Evaluation (CHERE), University of Technology Sydney, Sydney, NSW, Australia.
Pharmacoeconomics ; 42(Suppl 1): 81-94, 2024 Jun.
Article en En | MEDLINE | ID: mdl-38819719
ABSTRACT

BACKGROUND:

Widely used generic instruments to measure paediatric health-related quality of life (HRQoL) include the EQ-5D-Y-5L, Child Health Utility 9 Dimension (CHU-9D), Paediatric Quality of Life Inventory (PedsQL) and Health Utilities Index (HUI). There are similarities and differences in the content of these instruments, but there is little empirical evidence on how the items they contain relate to each other, and to an overarching model of HRQoL derived from their content.

OBJECTIVE:

This study aimed to explore the dimensionality of the instruments using exploratory factor analysis (EFA).

METHODS:

Data from the Australian Paediatric Multi-Instrument Comparison (P-MIC) Study were used. EQ-5D-Y-5L, CHU-9D, PedsQL and HUI data were collected via proxy or child self-report data. EFA was used to investigate the underlying domain structure and measurement relationship. Items from the four instruments were pooled and domain models were identified for self- and proxy-reported data. The number of factors was determined based on eigenvalues greater than 1. A correlation cut-off of 0.32 was used to determine item loading on a given factor, with cross-loading also considered. Oblique rotation was used.

RESULTS:

Results suggest a six-factor structure for the proxy-reported data, including emotional functioning, pain, daily activities, physical functioning, school functioning, and senses, while the self-report data revealed a similar seven-factor structure, with social functioning emerging as an additional factor.

CONCLUSION:

We provide evidence of differences and similarities between paediatric HRQoL instruments and the aspects of health being measured by these instruments. The results identified slight differences between self- and proxy-reported data in the relationships among items within the resulting domains.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Calidad de Vida Límite: Adolescent / Child / Child, preschool / Female / Humans / Male País/Región como asunto: Oceania Idioma: En Revista: Pharmacoeconomics Asunto de la revista: FARMACOLOGIA / TERAPIA POR MEDICAMENTOS Año: 2024 Tipo del documento: Article País de afiliación: Australia

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Calidad de Vida Límite: Adolescent / Child / Child, preschool / Female / Humans / Male País/Región como asunto: Oceania Idioma: En Revista: Pharmacoeconomics Asunto de la revista: FARMACOLOGIA / TERAPIA POR MEDICAMENTOS Año: 2024 Tipo del documento: Article País de afiliación: Australia