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Systematic Review of the Psychometric Performance of Generic Childhood Multi-attribute Utility Instruments

Author

Listed:
  • Joseph Kwon

    (University of Oxford)

  • Sarah Smith

    (London School of Hygiene and Tropical Medicine)

  • Rakhee Raghunandan

    (University of Sydney)

  • Martin Howell

    (University of Sydney)

  • Elisabeth Huynh

    (Australian National University)

  • Sungwook Kim

    (University of Oxford)

  • Thomas Bentley

    (University of Oxford)

  • Nia Roberts

    (University of Oxford)

  • Emily Lancsar

    (Australian National University)

  • Kirsten Howard

    (University of Sydney)

  • Germaine Wong

    (University of Sydney)

  • Jonathan Craig

    (Flinders University)

  • Stavros Petrou

    (University of Oxford)

Abstract

Background Childhood multi-attribute utility instruments (MAUIs) can be used to measure health utilities in children (aged ≤ 18 years) for economic evaluation. Systematic review methods can generate a psychometric evidence base that informs their selection for application. Previous reviews focused on limited sets of MAUIs and psychometric properties, and only on evidence from studies that directly aimed to conduct psychometric assessments. Objective This study aimed to conduct a systematic review of psychometric evidence for generic childhood MAUIs and to meet three objectives: (1) create a comprehensive catalogue of evaluated psychometric evidence; (2) identify psychometric evidence gaps; and (3) summarise the psychometric assessment methods and performance by property. Methods A review protocol was registered with the Prospective Register of Systematic Reviews (PROSPERO; CRD42021295959); reporting followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guideline. The searches covered seven academic databases, and included studies that provided psychometric evidence for one or more of the following generic childhood MAUIs designed to be accompanied by a preference-based value set (any language version): 16D, 17D, AHUM, AQoL-6D, CH-6D, CHSCS-PS, CHU9D, EQ-5D-Y-3L, EQ-5D-Y-5L, HUI2, HUI3, IQI, QWB, and TANDI; used data derived from general and/or clinical childhood populations and from children and/or proxy respondents; and were published in English. The review included ‘direct studies’ that aimed to assess psychometric properties and ‘indirect studies’ that generated psychometric evidence without this explicit aim. Eighteen properties were evaluated using a four-part criteria rating developed from established standards in the literature. Data syntheses identified psychometric evidence gaps and summarised the psychometric assessment methods/results by property. Results Overall, 372 studies were included, generating a catalogue of 2153 criteria rating outputs across 14 instruments covering all properties except predictive validity. The number of outputs varied markedly by instrument and property, ranging from 1 for IQI to 623 for HUI3, and from zero for predictive validity to 500 for known-group validity. The more recently developed instruments targeting preschool children (CHSCS-PS, IQI, TANDI) have greater evidence gaps (lack of any evidence) than longer established instruments such as EQ-5D-Y, HUI2/3, and CHU9D. The gaps were prominent for reliability (test–retest, inter-proxy-rater, inter-modal, internal consistency) and proxy-child agreement. The inclusion of indirect studies (n = 209 studies; n = 900 outputs) increased the number of properties with at least one output of acceptable performance. Common methodological issues in psychometric assessment were identified, e.g., lack of reference measures to help interpret associations and changes. No instrument consistently outperformed others across all properties. Conclusion This review provides comprehensive evidence on the psychometric performance of generic childhood MAUIs. It assists analysts involved in cost-effectiveness-based evaluation to select instruments based on the application-specific minimum standards of scientific rigour. The identified evidence gaps and methodological issues also motivate and inform future psychometric studies and their methods, particularly those assessing reliability, proxy-child agreement, and MAUIs targeting preschool children.

Suggested Citation

  • Joseph Kwon & Sarah Smith & Rakhee Raghunandan & Martin Howell & Elisabeth Huynh & Sungwook Kim & Thomas Bentley & Nia Roberts & Emily Lancsar & Kirsten Howard & Germaine Wong & Jonathan Craig & Stavr, 2023. "Systematic Review of the Psychometric Performance of Generic Childhood Multi-attribute Utility Instruments," Applied Health Economics and Health Policy, Springer, vol. 21(4), pages 559-584, July.
  • Handle: RePEc:spr:aphecp:v:21:y:2023:i:4:d:10.1007_s40258-023-00806-8
    DOI: 10.1007/s40258-023-00806-8
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    References listed on IDEAS

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    1. John Brazier & Mark Deverill, 1999. "A checklist for judging preference‐based measures of health related quality of life: Learning from psychometrics," Health Economics, John Wiley & Sons, Ltd., vol. 8(1), pages 41-51, February.
    2. Katherine Stevens, 2011. "Assessing the performance of a new generic measure of health-related quality of life for children and refining it for use in health state valuation," Applied Health Economics and Health Policy, Springer, vol. 9(3), pages 157-169, May.
    3. Drummond, Michael F. & Sculpher, Mark J. & Claxton, Karl & Stoddart, Greg L. & Torrance, George W., 2015. "Methods for the Economic Evaluation of Health Care Programmes," OUP Catalogue, Oxford University Press, edition 4, number 9780199665884.
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