Mapping scores from the Strengths and Difficulties Questionnaire (SDQ) to preference-based utility values

详细信息    查看全文

• 作者：Gareth Furber (1)
  Leonie Segal (1)
  Matthew Leach (2)
  Jane Cocks (3)
  
• 关键词：Utility ; Mapping ; Mental health ; Child and adolescent
• 刊名：Quality of Life Research
• 出版年：2014
• 出版时间：March 2014
• 年：2014
• 卷：23
• 期：2
• 页码：403-411
• 全文大小：201 KB
• 参考文献：1. Department of Health & Ageing. (2012). Guidelines for preparing submissions to the Pharmaceutical Benefits Advisory Committee. / Pharmaceutical Benefits Advisory Committee. Accessed January 10, 2013, from http://www.pbs.gov.au/industry/listing/elements/pbac-guidelines/PBAC4.3.2.pdf.
  2. Rabin, R., & De Charro, F. (2001). EQ-5D: A measure of health status from the EuroQol group. / Annals of Medicine, / 33(5), 337-43. CrossRef
  3. Ungar, W. J. (2011). Challenges in health state valuation in paediatric economic evaluation: Are QALYs contraindicated? / PharmacoEconomics, / 29(8), 641-52. CrossRef
  4. Romeo, R., Byford, S., & Knapp, M. (2005). Annotation: Economic evaluations of child and adolescent mental health interventions: a systematic review. / Journal of Child Psychology and Psychiatry and Allied Disciplines, / 46(9), 919-30. CrossRef
  5. Hsia, R. Y., & Belfer, M. L. (2008). A framework for the economic analysis of child and adolescent mental disorders. / International Review of Psychiatry, / 20(3), 251-59. CrossRef
  6. Kilian, R., Losert, C., Park, A.-L., McDaid, D., & Knapp, M. (2010). Cost-effectiveness analysis in child and adolescent mental health problems: An updated review of literature. / International Journal of Mental Health Promotion, / 12(4), 45-7. CrossRef
  7. Dalziel, K., & Segal, L. (2009). Economic evaluation in child protection: What are the special challenges? In W. Ungar (Ed.), / Economic evaluation in child health (pp. 133-64). London: Oxford Press.
  8. Kromm, S. K., Bethell, J., Kraglund, F., Edwards, S. A., Laporte, A., Coyte, P. C., et al. (2012). Characteristics and quality of pediatric cost-utility analyses. / Quality of Life Research, / 21(8), 1315-325. CrossRef
  9. Petrou, S., Johnson, S., Wolke, D., Hollis, C., Kochhar, P., & Marlow, N. (2010). Economic costs and preference-based health-related quality of life outcomes associated with childhood psychiatric disorders. / The British Journal of Psychiatry, / 197, 395-04. CrossRef
  10. Petrou, S., & Kupek, E. (2009). Estimating preference-based Health Utilities Index mark 3 utility scores for childhood conditions in England and Scotland. / Medical Decision Making, / 29(3), 291-03. CrossRef
  11. Mortimer, D., & Segal, L. (2008). Comparing the incomparable? A systematic review of competing techniques for converting descriptive measures of health status into QALY-weights. / Medical Decision Making, / 28(1), 66-9. CrossRef
  12. Petrillo, J., & Cairns, J. (2008). Converting condition-specific measures into preference-based outcomes for use in economic evaluation. / Expert Review of Pharmacoeconomics and Outcomes Research, / 8(5), 453-61. CrossRef
  13. Brazier, J. E., Yang, Y., Tsuchiya, A., & Rowen, D. L. (2010). A review of studies mapping (or cross walking) non-preference based measures of health to generic preference-based measures. / The European Journal of Health Economics, / 11(2), 215-25. CrossRef
  14. Chuang, L. H., & Whitehead, S. J. (2012). Mapping for economic evaluation. / British Medical Bulletin, / 101(1), 1-5. CrossRef
  15. National Institute for Health and Clinical Excellence. (2008). / Guide to the methods of technology appraisal. London: National Institute for Health and Clinical Excellence.
  16. Segal, L., Day, S. E., Chapman, A. B., & Osborne, R. H. (2004). Can we reduce disease burden from osteoarthritis? / The Medical Journal of Australia, / 180(5 Suppl), S11–S17.
  17. Goodman, R. (2007). The Strengths and Difficulties Questionnaire: A research note. / Journal of Child Psychology and Psychiatry and Allied Disciplines, / 38(5), 581-86. CrossRef
  18. Stevens, K. J. (2008). / Working with children to develop dimensions for a preference based generic paediatric health related quality of life measure. Health Economics and Decision Science Discussion Paper 08/04. http://www.shef.ac.uk/scharr/sections/heds/discussion.html.
  19. Faul, F., Erdfelder, E., Buchner, A., & Lang, A. G. (2009). Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses. / Behavior Research Methods, / 41, 1149-160. CrossRef
  20. Rutter, M. (1967). A children’s behaviour questionnaire for completion by teachers: Preliminary findings. / Journal of Child Psychology and Psychiatry, / 8, 1-1. CrossRef
  21. Goodman, R. (2001). Psychometric properties of the strengths and difficulties questionnaire. / Journal of the American Academy of Child and Adolescent Psychiatry, / 40(11), 1337-345. CrossRef
  22. Hawes, D. J., & Dadds, M. R. (2004). Australian data and psychometric properties of the Strengths and Difficulties Questionnaire. / Australian and New Zealand Journal of Psychiatry, / 38, 644-51. CrossRef
  23. Goodman, A., & Goodman, R. (2009). Strengths and Difficulties Questionnaire as a dimensional measure of child mental health. / Journal of the American Academy of Child and Adolescent Psychiatry, / 48(4), 400-03. CrossRef
  24. 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(8), 1105-113. CrossRef
  25. Stevens, K. (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, / 9(3), 157-69. CrossRef
  26. Stevens, K. (2012). Valuation of the child health utility 9D index. / PharmacoEconomics, / 30(8), 729-47. CrossRef
  27. Ratcliffe, J., Flynn, T., Terlich, F., Brazier, J., Stevens, K., & 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, 713-27.
  28. Ratcliffe, J., Stevens, K., Flynn, T., Brazier, J., & Sawyer, M. (2012). An assessment of the construct validity of the CHU9D in the Australian adolescent general population. / Quality of Life Research, / 21(4), 717-25. CrossRef
  29. Ratcliffe, J., Stevens, K., Flynn, T., Brazier, J., & Sawyer, M. (2012). Whose values in health? An empirical comparison of the application of adolescent and adult values for the CHU-9D and AQOL-6D in the Australian adolescent general population. / Value in Health, / 15(5), 730-36. CrossRef
  30. Drummond, M. (2001). Introducing economic and quality of life measurements into clinical studies. / Annals of Medicine, / 33(5), 344-49. CrossRef
  31. Canaway, A. G., & Frew, E. J. (2012). Measuring preference-based quality of life in children aged 6-?years: A comparison of the performance of the CHU-9D and EQ-5D-Y-the WAVES Pilot Study. / Quality of Life Research, 22(1), 173-83.
  32. Ratcliffe, J., Couzner, L., Flynn, T., Sawyer, M., Stevens, K., Brazier, J., et al. (2011). Valuing Child Health Utility 9D health states with a young adolescent sample: A feasibility study to compare best-worst discrete choice experiment, standard gamble and time trade off methods. / Applied Health Economics and Health Policy, / 9(1), 15-7. CrossRef
  
• 作者单位：Gareth Furber (1)
  Leonie Segal (1)
  Matthew Leach (2)
  Jane Cocks (3)
  
  1. Health Economics and Social Policy Group, University of South Australia, Playford Building, City East Campus, North Terrace, Adelaide, SA, 5000, Australia
  2. School of Nursing and Midwifery, University of South Australia, Centenary Building, City East Campus, North Terrace, Adelaide, SA, 5000, Australia
  3. Social Epidemiology and Evaluation Research Group, University of South Australia, Playford Building, City East Campus, North Terrace, Adelaide, SA, 5000, Australia
  
• ISSN：1573-2649

文摘

Purpose Quality of life mapping methods such as “Transfer to Utility-can be used to translate scores on disease-specific measures to utility values, when traditional utility measurement methods (e.g. standard gamble, time trade-off, preference-based multi-attribute instruments) have not been used. The aim of this study was to generate preliminary ordinary least squares (OLS) regression-based algorithms to transform scores from the Strengths and Difficulties Questionnaires (SDQ), a widely used measure of mental health in children and adolescents, to utility values obtained using the preference-based Child Health Utility (CHU9D) instrument. Methods Two hundred caregivers of children receiving community mental health services completed the SDQ and CHU9D during a telephone interview. Two OLS regressions were run with the CHU9D utility value as the dependent variable and SDQ subscales as predictors. Resulting algorithms were validated by comparing predicted and observed group mean utility values in randomly selected subsamples. Results Preliminary validation was obtained for two algorithms, utilising five and three subscales of the SDQ, respectively. Root mean square error values (.124) for both models suggested poor fit at an individual level, but both algorithms performed well in predicting mean group observed utility values. Conclusion This research generated algorithms for translating SDQ scores to utility values and providing researchers with an additional tool for conducting health economic evaluations with child and adolescent mental health data.