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The Child Health Utility 9D (CHU9D), a new generic preference-based health-related quality of life (HRQoL) instrument, was developed specifically for the application in cost-effectiveness analyses of treatments and interventions for children and adolescents. The main objective of this study was to examine the psychometric property of the Chinese version of CHU9D (CHU9D-CHN) in a large school-based sample in China.
Data were collected using a multi-stage sampling method from third-to-ninth-grade students in Shaanxi Province, China. Participants self-completed a hard-copy questionnaire including the CHU9D-CHN instrument, the Pediatric Quality of Life Inventory™ 4.0 Generic Core Scales (PedsQL), information on socio-demographic characteristics and self-reported health status. The psychometric properties of the CHU9D-CHN, including the internal consistency, 2-week test–retest reliability, convergent and known-groups validity were studied.
A total of 1912 students participated in the survey. The CHU9D-CHN internal consistency and test–retest reliability were good to excellent with a Cronbach’s alpha of 0.77 and an intra-class correlation coefficient of 0.65, respectively. The CHU9D utility scores moderately correlated with the PedsQL total scores (r = .57, P < .001), demonstrating good convergent validity. Difference of the CHU9D utility scores among the different participants with levels of self-reported general health, health services utilisation and left-behind status demonstrated good construct validity.
The findings demonstrated adequate psychometric performance for the CHU9D-CHN. The CHU9D-CHN was a satisfactory, reliable and valid instrument to measure and value HRQoL for children and adolescents in China.
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Williams, P. G., Holmbeck, G. N., & Greenley, R. N. (2002). Adolescent health psychology. Journal of Consulting and Clinical Psychology, 70, 828–842. CrossRef
Sawyer, S. M., Afifi, R. A., Bearinger, L. H., Blakemore, S. J., Dick, B., Ezeh, A. C., & Patton, G. C. (2012). Adolescence: A foundation for future health. Lancet, 379, 1630–1640. https://doi.org/10.1016/s0140-6736(12)60072-5. CrossRef
Kleinert, S. (2007). Adolescent health: An opportunity not to be missed. Lancet, 369, 1057–1058. https://doi.org/10.1016/s0140-6736(07)60374-2. CrossRef
Morris, J., Perez, D., & McNoe, B. (1998). The use of quality of life data in clinical practice. Quality of Life Research, 7, 85–91. CrossRef
Lehnert, T., Sonntag, D., Konnopka, A., Riedel-Heller, S., & Konig, H. H. (2012). The long-term cost-effectiveness of obesity prevention interventions: Systematic literature review. Obesity Reviews, 13, 537–553. https://doi.org/10.1111/j.1467-789X.2011.00980.x. CrossRef
Ratcliffe, J., Flynn, T., Terlich, F., Stevens, K., Brazier, J., & Sawyer, M. (2012). Developing adolescent-specific health state values for economic evaluation: An application of profile case best-worst scaling to the Child Health Utility 9D. Pharmacoeconomics, 30, 713–727. https://doi.org/10.2165/11597900-000000000-00000. CrossRef
Stevens, K., & Ratcliffe, J. (2012). Measuring and valuing health benefits for economic evaluation in adolescence: An assessment of the practicality and validity of the child health utility 9D in the Australian adolescent population. Value Health, 15, 1092–1099. https://doi.org/10.1016/j.jval.2012.07.011. CrossRef
Chen, G., Flynn, T., Stevens, K., Brazier, J., Huynh, E., Sawyer, M., Roberts, R., & Ratcliffe, J. (2015). Assessing the health-related quality of life of Australian adolescents: An empirical comparison of the Child Health Utility 9D and EQ-5D-Y instruments. Value Health, 18, 432–438. https://doi.org/10.1016/j.jval.2015.02.014. CrossRef
Blake, H., Quirk, H., Leighton, P., Randell, T., Greening, J., Guo, B., et al. (2016). Feasibility of an online intervention (STAK-D) to promote physical activity in children with type 1 diabetes: Protocol for a randomised controlled trial. Trials, 17(1), 583. https://doi.org/10.1186/s13063-016-1719-0. CrossRefPubMedCentral
Xu, F., Chen, G., Stevens, K., Zhou, H., Qi, S., Wang, Z., Hong, X., Chen, X., Yang, H., Wang, C., & Ratcliffe, J. (2014). Measuring and valuing health-related quality of life among children and adolescents in mainland China—A pilot study. PLoS ONE, 9, e89222. https://doi.org/10.1371/journal.pone.0089222. CrossRefPubMedCentral
Wild, D., Grove, A., Martin, M., Eremenco, S., McElroy, S., Verjee-Lorenz, A., et al. (2005). Principles of good practice for the translation and cultural adaptation process for patient-reported outcomes (PRO) measures: Report of the ISPOR task force for translation and cultural adaptation. Value Health, 8(2), 94–104. https://doi.org/10.1111/j.1524-4733.2005.04054.x. CrossRef
Ratcliffe, J., Huynh, E., Chen, G., Stevens, K., Swait, J., Brazier, J., Sawyer, M., Roberts, R., & Flynn, T. (2016). Valuing the Child Health Utility 9D: Using profile case best worst scaling methods to develop a new adolescent specific scoring algorithm. Social Science and Medicine, 157, 48–59. https://doi.org/10.1016/j.socscimed.2016.03.042. CrossRef
Chen, G., Xu, F., Huynh, E., Wang, Z., Li, C., Stevens, K., & Ratcliffe, J. (2016). Scoring the Child Health Utility 9D instrument. Estimation of a Chinese adolescent-specific tariff. Quality of Life Research, 25(S1), 23–24.
Chen, G., Huynh, E., Xu, F., Stevens, K., Brazier, J., Swait, J., & Ratcliffe, J. (2017). OP55 Health technology assessment in children and adolescents: Adolescent preferences for Child Health Utility 9D health states. International Journal of Technology Assessment in Health Care, 33(S1), 24–25. https://doi.org/10.1017/s026646231700143x. CrossRef
Chen, G., Xu, F., Huynh, E., Wang, Z., Li, C., Stevens, K., & Ratcliffe, J. (2018). Developing a Chinese-specific adolescent tariff for the Child Health Utility 9D instrument. Melbourne: Centre for Health Economics Research Paper 96, Monash University.
Huang, Y., Zhong, X. N., Li, Q. Y., Xu, D., Zhang, X. L., Feng, C., Yang, G. X., Bo, Y. Y., & Deng, B. (2015). Health-related quality of life of the rural-China left-behind children or adolescents and influential factors: A cross-sectional study. Health and Quality Life Outcomes, 13, 29. https://doi.org/10.1186/s12955-015-0220-x. CrossRef
Hofsteenge, G. H., Weijs, P. J., Delemarre-van de Waal, H. A., de Wit, M., & Chinapaw, M. J. (2013). Effect of the Go4it multidisciplinary group treatment for obese adolescents on health related quality of life: A randomised controlled trial. BMC Public Health, 13, 939. https://doi.org/10.1186/1471-2458-13-939. CrossRefPubMedCentral
Varni, J. W., Seid, M., & Kurtin, P. S. (2001). PedsQL™ 4.0: Reliability and validity of the Pediatric Quality of Life Inventory™ version 4.0 generic core scales in healthy and patient populations. Medical Care, 39, 800–812. CrossRef
Field, A. (2013). Discovering statistics using IBM SPSS statistics. London: Sage. Publications Ltd.
Fayers, P. M., & Machin, D. (2007). Quality of Life: The assessment, analysis and interpretation of patient-reported outcomes (2nd ed). Chichester: Wiley. CrossRef
Conner-Spady, B. L., Marshall, D. A., Bohm, E., Dunbar, M. J., Loucks, L., Khudairy, A. A., et al. (2015). Reliability and validity of the EQ-5D-5L compared to the EQ-5D-3L in patients with osteoarthritis referred for hip and knee replacement. Quality of Life Research, 24(7), 1775–1784. https://doi.org/10.1007/s11136-014-0910-6. CrossRef
Cheung, P. W. H., Wong, C. K. H., Samartzis, D., Luk, K. D. K., Lam, C. L. K., Cheung, K. M. C., et al. (2016). Psychometric validation of the EuroQoL 5-Dimension 5-Level (EQ-5D-5L) in Chinese patients with adolescent idiopathic scoliosis. Scoliosis Spinal Disorders, 11, 19. https://doi.org/10.1186/s13013-016-0083-x. CrossRefPubMedCentral
Cohen, J. (1968). Weighted kappa: Nominal scale agreement with provision for scaled disagreement or partial credit. Psychological Bulletin, 70, 213–220. CrossRef
Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33(1), 159–174. CrossRef
Anderson, T. W., & Finn, J. (1996). The new statistical analysis of data. New York: Springer. CrossRef
Man, Y., Mengmeng, L., Lezhi, L., Ting, M., & Jingping, Z. (2017). The psychological problems and related influential factors of left-behind adolescents (LBA) in Hunan, China: A cross sectional study. International Journal of Equity in Health, 16(1), 163. https://doi.org/10.1186/s12939-017-0639-2. CrossRef
Qu, G. B., Wu, W., Wang, L. L., Tang, X., Sun, Y. H., Li, J., et al. (2017). Systematic review and meta-analysis found higher levels of behavioural problems in male left-behind children aged 6–11 years. Acta Paediatrica. https://doi.org/10.1111/apa.14199.
Petersen, K. D., Chen, G., Mpundu-Kaambwa, C., Stevens, K., Brazier, J., & Ratcliffe, J. (2018). Measuring health-related quality of life in adolescent populations: An empirical comparison of the CHU9D and the PedsQL™ 4.0 Short Form 15. Patient, 11(1), 29–37. https://doi.org/10.1007/s40271-017-0265-5. CrossRef
- Psychometric evaluation of the Chinese version of the Child Health Utility 9D (CHU9D-CHN): a school-based study in China
- Springer International Publishing