A Review of the Psychometric Performance of Selected Child and Adolescent Preference-Based Measures Used to Produce Utilities for Child and Adolescent Health

Abstract

This review examined the psychometric performance of 4 generic child-and adolescent-specific preference-based measures that can be used to produce utilities for child and adolescent health. Methods: A systematic search was undertaken to identify studies reporting the psychometric performance of the Child Health Utility (CHU9D), EQ-5D-Y (3L or 5L), and Health Utilities Index Mark 2 (HUI2) or Mark 3 (HUI3) in children and/or adolescents. Data were extracted to assess known-group validity, convergent validity, responsiveness, reliability, acceptability, and feasibility. Data were extracted separately for the dimensions and utility index where this was reported. Results: The review included 76 studies (CHU9D n = 12, EQ-5D-Y-3L n = 20, HUI2 n = 26,HUI3 n = 43), which varied considerably across conditions and sample size. EQ-5D-Y-3L had the largest amount of evidence of good psychometric performance in proportion to the number of studies examining performance. The majority of the evidence related to EQ-5D-Y-3L was based on dimensions. CHU9D was assessed in fewer studies, but the majority of studies found evidence of good psychometric performance. Evidence for HUI2 and HUI3 was more mixed, but the studies were more limited in sample size and statistical power, which was likely to have affected performance. Conclusions: The heterogeneity of published studies means that the evidence is based on studies across a range of countries, populations and conditions, using different study designs, different languages, different value sets and different statistical techniques. Evidence for CHU9D in particular is based on a limited number of studies. The findings raise concerns about the comparability of self-report and proxy-report responses to generate utility values for children and adolescents.

Psychometric Performance of HRQoL Measures: An Australian Paediatric Multi-Instrument Comparison Study Protocol (P-MIC)

“…Future work from this study could look at international extensions and the development of psychometric testing protocols. Our work will allow for clear comparison of evidence across instruments [13] and will be of national and international significance. are members of the EuroQol Group.…”

“…A sensitivity calculation was completed using the PedsQL self-report scores and it was determined that a sample of 128 (64 per group) would give statistical power of 0.9 to detect a difference between healthy children and children with a chronic condition on the total score of the PedsQL self-report using a one-sided test with type I error of 1% [16]. Additional information on sample size calculations is available in Appendix D. The total sample size of 6100 was estimated from a similar adult study and a review of previous pediatric HRQoL studies [13,17]. Although the overall sample size is greater than the outcome specific sample sizes estimated above, this larger total sample is required to complete further item level analysis such as Item Response Theory (IRT) and factor analysis in addition to subgroup analysis, such as by disease group and child age.…”

“…The EQ-5D-Y-3L was identified as priority for inclusion as it is a generic instrument widely used in pediatric populations with good evidence for performance, but requiring more [13]. The EQ-5D-Y-5L was identified as priority for inclusion because it is a promising new instrument that requires further validation work.…”

“…Identified as priority for inclusion as it is a generic instrument widely used in pediatric populations with good evidence for performance, but requiring more [13].…”

“…Additionally, a 2021 systematic review examining the psychometric performance of key generic pediatric preference-based instruments (CHU9D, EQ-5D-Y-3L, HUI2, and HUI3) also identified gaps in evidence on the psychometric performance of pediatric HRQoL instruments. Key limitations in the currently available literature include the small sample size of some studies, wide variation in methods, a focus on single instruments, limited coverage and heterogeneity of disease conditions or age groups, meaning that broad synthesis of evidence is challenging [13]. These limitations have resulted in ambiguity regarding which pediatric HRQoL instruments are most appropriate for which context, inhibiting clinicians in instrument use for clinical care, researchers in evidence collection and decision makers in evidence appraisal.…”