Quality of Life Research

, Volume 27, Issue 7, pp 1921–1931 | Cite as

Psychometric evaluation of the Chinese version of the Child Health Utility 9D (CHU9D-CHN): a school-based study in China

  • Peirong Yang
  • Gang Chen
  • Peng Wang
  • Kejian Zhang
  • Feng Deng
  • Haifeng Yang
  • Guihua Zhuang



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.


Health-related quality of life Utility CHU9D Children Adolescents China 


Compliance with ethical standards

Conflict of interest

GC was involved in the development of the Chinese version of CHU9D instrument. All other authors declare that they have no conflict of interest.

Ethical Approval

Ethical approval was granted by the Ethics Committee of Baoji Center for Disease Control and Prevention (Project No. 201601). All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Informed consent

Written informed consent was obtained from both parents or caregivers and all individual students included in the study.


  1. 1.
    Williams, P. G., Holmbeck, G. N., & Greenley, R. N. (2002). Adolescent health psychology. Journal of Consulting and Clinical Psychology, 70, 828–842.CrossRefPubMedGoogle Scholar
  2. 2.
    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. Scholar
  3. 3.
    Kleinert, S. (2007). Adolescent health: An opportunity not to be missed. Lancet, 369, 1057–1058. Scholar
  4. 4.
    Morris, J., Perez, D., & McNoe, B. (1998). The use of quality of life data in clinical practice. Quality of Life Research, 7, 85–91.CrossRefPubMedGoogle Scholar
  5. 5.
    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. Scholar
  6. 6.
    Chen, G., & Ratcliffe, J. (2015). A review of the development and application of generic multi-attribute utility instruments for paediatric populations. Pharmacoeconomics, 33, 1013–1028. Scholar
  7. 7.
    Stevens, K. J. (2010). Working with children to develop dimensions for a preference-based, generic, pediatric, health-related quality-of-life measure. Qualitative Health Research, 20, 340–351. Scholar
  8. 8.
    Stevens, K. (2009). Developing a descriptive system for a new preference-based measure of health-related quality of life for children. Quality of Life Research, 18, 1105–1113. Scholar
  9. 9.
    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. Scholar
  10. 10.
    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. Scholar
  11. 11.
    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. Scholar
  12. 12.
    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. Scholar
  13. 13.
    Furber, G., & Segal, L. (2015). The validity of the Child Health Utility instrument (CHU9D) as a routine outcome measure for use in child and adolescent mental health services. Health and Quality of Life Outcomes, 13(1), 22. Scholar
  14. 14.
    Frew, E. J., Pallan, M., Lancashire, E., Hemming, K., & Adab, P. (2015). Is utility-based quality of life associated with overweight in children? Evidence from the UK WAVES randomised controlled study. BMC Pediatrics, 15(1), 211. Scholar
  15. 15.
    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. Scholar
  16. 16.
    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. Scholar
  17. 17.
    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. Scholar
  18. 18.
    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.Google Scholar
  19. 19.
    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. Scholar
  20. 20.
    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.Google Scholar
  21. 21.
    Hao, Y., Tian, Q., Lu, Y., Chai, Y., & Rao, S. (2010). Psychometric properties of the Chinese version of the Pediatric Quality of Life Inventory 4.0 generic core scales. Quality of Life Research, 19, 1229–1233. Scholar
  22. 22.
    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. Scholar
  23. 23.
    Wu, H. H., Li, H., & Gao, Q. (2013). Psychometric properties of the Chinese version of the pediatric quality of life inventory 4.0 generic core scales among children with short stature. Health and Quality Life Outcomes, 11, 87. Scholar
  24. 24.
    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. Scholar
  25. 25.
    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.CrossRefPubMedGoogle Scholar
  26. 26.
    Fleiss, J. L., & Cohen, J. (1973). The equivalence of weighted kappa and the intraclass correlation coefficient as measures of reliability. Educational and Psychological Measurement, 33, 613–619. Scholar
  27. 27.
    Field, A. (2013). Discovering statistics using IBM SPSS statistics. London: Sage. Publications Ltd.Google Scholar
  28. 28.
    Fayers, P. M., & Machin, D. (2007). Quality of Life: The assessment, analysis and interpretation of patient-reported outcomes (2nd ed). Chichester: Wiley.CrossRefGoogle Scholar
  29. 29.
    Wang, H. M., Patrick, D. L., Edwards, T. C., Skalicky, A. M., Zeng, H. Y., & Gu, W. W. (2012). Validation of the EQ-5D in a general population sample in urban China. Quality of Life Research, 21(1), 155–160. Scholar
  30. 30.
    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. Scholar
  31. 31.
    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. Scholar
  32. 32.
    Cohen, J. (1968). Weighted kappa: Nominal scale agreement with provision for scaled disagreement or partial credit. Psychological Bulletin, 70, 213–220.CrossRefPubMedGoogle Scholar
  33. 33.
    Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33(1), 159–174.CrossRefPubMedGoogle Scholar
  34. 34.
    Anderson, T. W., & Finn, J. (1996). The new statistical analysis of data. New York: Springer.CrossRefGoogle Scholar
  35. 35.
    Fan, F., Su, L. Y., Gill, M. K., & Birmaher, B. (2010). Emotional and behavioral problems of Chinese left-behind children: A preliminary study. Social Psychiatry Psychiatric Epidemiology, 45(6), 655–664. Scholar
  36. 36.
    Ding, G., & Bao, Y. (2014). Editorial perspective: Assessing developmental risk in cultural context: The case of ‘left behind’ children in rural China. Journal of Child Psychology and Psychiatry, 55(4), 411–412. Scholar
  37. 37.
    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. Scholar
  38. 38.
    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. Scholar
  39. 39.
    Xing, H., Yu, W., Xu, F., & Chen, S. (2017). Influence of social support and rearing behavior on psychosocial health in left-behind children. Health Quality Life Outcomes, 15(1), 13. Scholar
  40. 40.
    Furber, G., & Segal, L. (2015). The validity of the Child Health Utility instrument (CHU9D) as a routine outcome measure for use in child and adolescent mental health services. Health Quality Life Outcomes, 13, 22. Scholar
  41. 41.
    Canaway, A. G., & Frew, E. J. (2013). Measuring preference-based quality of life in children aged 6–7 years: A comparison of the performance of the CHU-9D and EQ-5D-Y—the WAVES pilot study. Quality of Life Research, 22(1), 173–183. Scholar
  42. 42.
    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. Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Epidemiology and Biostatistics, School of Public HealthXi’an Jiaotong University Health Science CenterXi’anChina
  2. 2.Baoji Center for Disease Control and PreventionBaojiChina
  3. 3.Centre for Health EconomicsMonash UniversityMelbourneAustralia
  4. 4.College of Foreign LanguageBaoji University of Arts and SciencesBaojiChina

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