Background: There is a lack of psychometric evidence about pediatric health-related quality of life (HRQoL) instruments. Evidence on cost effectiveness, involving the measurement of HRQoL, is used in many countries to make decisions about pharmaceuticals, technologies, and health services for children. Additionally, valid instruments are required to facilitate accurate outcome measurement and clinical decision making. A pediatric multi instrument comparison (P-MIC) study is planned to compare the psychometric performance and measurement characteristics of pediatric HRQoL instruments. Methods: The planned P-MIC study will collect data on approximately 6100 Australian children and adolescents aged 2–18 years via The Royal Children’s Hospital Melbourne and online survey panels. Participants will complete an initial survey, involving the concurrent collection of a range of pediatric HRQoL instruments, followed by a shorter survey 2–8 weeks later, involving the collection of a subset of instruments from the initial survey. Children aged ≥7 years will be asked to self-report HRQoL. Psychometric performance will be assessed at the instrument, domain, and item level. Conclusions: This paper describes the methodology of the planned P-MIC study, including benefits, limitations, and likely challenges. Evidence from this study will guide the choice of HRQoL measures used in clinical trials, economic evaluation, and other applications.

Background: Collecting data using paediatric health-related quality of life (HRQoL) instruments is complex, and there is a paucity of evidence regarding the comparative performance of paediatric HRQoL instruments. The Australian Paediatric Multi-Instrument Comparison (P-MIC) study was conducted to address this paucity of evidence. This study aims to understand the (1) feasibility of collecting data using paediatric HRQoL instruments in a research setting and (2) acceptability and feasibility for children and their caregivers to complete common paediatric HRQoL instruments using data from the Australian P-MIC study. Methods: Data were from children aged 5–18 years from the Australian P-MIC study. Demographics, cost and time for data collection, dropout rates, and inconsistent responses were used to assess Aim 1. Participant-reported difficulty and completion time were used to assess Aim 2. Subgroup analyses included child age, report type (self/proxy), sample recruitment pathway (hospital/online), and online panel sample type (general population/condition groups). Results: Overall, 5945 P-MIC participants aged 5–18 years completed an initial survey, of these, 2346 also completed the follow-up survey (39.5% response rate). Compared with online panel recruitment, hospital recruitment was more costly and time-consuming and had higher follow-up completion (33.5% versus 80.4%) (Aim 1). Data were of similar good quality (based on inconsistent responses) for both recruitment pathways (Aim 1). Participants completed each instrument in 70% reported each instrument as easy to complete (Aim 2). Conclusions: The Australian P-MIC study was able to collect good-quality data using both online panel and hospital recruitment pathways. All instruments were acceptable and feasible to children and their caregivers.