Development of a Health-State Classification System for the Pediatric Quality-of-Life Inventory Version 4.0 Generic Core Scales for Preference-Based Valuation in Australia

被引:1
作者
Kwon, Joseph [1 ]
Raghunandan, Rakhee [2 ]
Nghiem, Son Hong [3 ]
Howard, Kirsten [2 ]
Lancsar, Emily [3 ]
Huynh, Elisabeth [3 ]
Howell, Martin [2 ]
Petrou, Stavros [1 ]
Smith, Sarah [4 ]
机构
[1] Univ Oxford, Nuffield Dept Primary Care Hlth Sci, Oxford, England
[2] Univ Sydney, Menzies Ctr Hlth Policy & Econ, Sydney, NSW, Australia
[3] Australian Natl Univ, Dept Hlth Econ Wellbeing & Soc, Canberra, NSW, Australia
[4] London Sch Hyg & Trop Med, Dept Hlth Serv Res & Policy, London, England
关键词
health-state classification system; health utility; item set selection; Pediatric Quality of Life Inventory Version 4.0 Generic Core Scales; psychometric evaluation; PSYCHOMETRIC PROPERTIES; MEASUREMENT MODEL; VALIDITY; CHILDREN; INDEX; ADOLESCENCE; UTILITIES; INSTRUMENTS; RELIABILITY; PERFORMANCE;
D O I
10.1016/j.jval.2024.08.005
中图分类号
F [经济];
学科分类号
02 ;
摘要
Objectives: Pediatric Quality-of-Life Inventory Version 4.0 Generic Core Scales (PedsQL GCS), comprising 23 items covering 4 subscales (physical, emotional, social, and school functioning), is a widely applied generic measure of childhood health-related quality of life but does not provide health utilities for cost-effectiveness-based decision making. This study aimed to develop a reduced item version of PedsQL GCS amenable to health utility derivation in Australia. Methods: Data sources were 2 cohorts of the Longitudinal Study of Australian Children, including proxy responses for all PedsQL GCS versions (Toddlers, Young Children, Children, and Teens), and the CheckPoint sample containing child self-report to the Children version. Three analytic samples were CheckPoint sample (n = 1874); Mallinson sample containing 1 measurement per child from one of the Young Children, Children, or Teens versions (n = 7855); and Toddlers sample (n = 7401). Exploratory and confirmatory factor analyses assessed dimensionality. Psychometric analyses used Rasch and classical criteria on 3 randomly selected subsamples (n = 500) per sample. Item selection prioritized psychometric performance in the CheckPoint sample, also considering performance in other samples and conceptual content. Results: Dimensionality assessments did not generate an alternative empirical structure for the measure, and psychometric analyses were conducted on the original 4 subscales. The selected items were: "Get aches and pains" for physical functioning; "Feel sad/blue" for emotional functioning; "Other kids not friends" for social functioning; and "Keeping up with school work" for school functioning. Conclusions: The final 4-item set, pending further psychometric validation and valuation, can generate health utilities from the widely used PedsQL GCS to inform cost-effectiveness-based decision making.
引用
收藏
页码:88 / 98
页数:11
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