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

Abstract

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.