Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress 2023 EHA Congress 2023 ASCO Annual Meeting
Clinical Collections
Advances in Alzheimer’s

ACC 2024 Congress

Catch up on all the top stories and latest evidence in cardiology research with our ACC 2024 Congress hub page.
ADVANCED SEARCH
Log in
Top
Health and Quality of Life Outcomes
Published in: Health and Quality of Life Outcomes 1/2015

Open Access 01-12-2015 | Research

The validity of the Child Health Utility instrument (CHU9D) as a routine outcome measure for use in child and adolescent mental health services

Authors: Gareth Furber, Leonie Segal

Published in: Health and Quality of Life Outcomes | Issue 1/2015

Login to get access

Abstract

Background

Few cost-utility studies of child and adolescent mental health services (CAMHS) use quality adjusted life years (a combination of utility weights and time in health state) as the outcome to enable comparison across disparate programs and modalities. Part of the solution to this problem involves embedding preference-based health-related quality of life (PBHRQOL) utility instruments, which generate utility weights, in clinical practice and research. The Child Health Utility (CHU9D) is a generic PBHRQOL instrument developed specifically for use in young people. The purpose of this study was to assess the suitability of the CHU9D as a routine outcome measure in CAMHS clinical practice.

Methods

Two hundred caregivers of children receiving community mental health services completed the CHU9D alongside a standardised child and adolescent mental health measure (the Strengths and Difficulties Questionnaire – SDQ) during a telephone interview. We investigated face validity, practicality, internal consistency, and convergent validity of the CHU9D. In addition, we compared the utility weights obtained in this group with utility weights from other studies of child and adolescent mental health populations.

Results

Participants found the CHU9D easy and quick to complete. It demonstrated acceptable internal consistency, and correlated moderately with the SDQ. It was able to discriminate between children in the abnormal range and those in the non-clinical/borderline range as measured by the SDQ. Three CHU9D items without corollaries in the SDQ (sleep, schoolwork, daily routine) were found to be significant predictors of the SDQ total score and may be useful clinical metrics. The mean utility weight of this sample was comparable with clinical subsamples from other CHU9D studies, but was significantly higher than mean utility weights noted in other child and adolescent mental health samples.

Conclusions

Initial validation suggests further investigation of the CHU9D as a routine outcome measure in CAMHS is warranted. Further investigation should explore test-retest reliability, sensitivity to change, concordance between caregiver and child-completed forms, and the calibration of the utility weights. Differences between utility weights generated by the CHU9D and other utility instruments in this population should be further examined by administering a range of PBHRQOL instruments concurrently in a mental health group.
Literature
1.
Hall CL, Moldavsky M, Taylor J, Sayal K, Marriott M, Batty MJ, et al. Implementation of routine outcome measurement in child and adolescent mental health services in the United Kingdom: a critical perspective. Eur Child Adolesc Psychiatry. 2013;23:239–42.CrossRefPubMedCentral
2.
Duncan EAS, Murray J. The barriers and facilitators to routine outcome measurement by allied health professionals in practice: A systematic review. BMC Health Serv Res. 2012;12:96.CrossRefPubMedCentralPubMed
3.
McKay R, Coombs T. An exploration of the ability of routine outcome measurement to represent clinically meaningful information regarding individual consumers. Australas Psychiatry. 2012;20:433–7.CrossRefPubMed
4.
Coombs T, Stapley K, Pirkis J. The multiple uses of routine mental health outcome measures in Australia and New Zealand: Experiences from the field. Australas Psychiatry. 2011;19:247–53.CrossRefPubMed
5.
Gowers SG, Harrington RC, Whitton A, Lelliott P, Beevor A, Wing J, et al. Brief scale for measuring the outcomes of emotional and behavioural disorders in children. Health of the Nation Outcome Scales for Children and Adolescents (HoNOSCA). Br J Psychiatry. 1999;174(MAY):413–6.CrossRefPubMed
6.
Goodman R. The strengths and difficulties questionnaire: a research note. J Child Psychol Psychiatry. 1997;38:581–6.CrossRefPubMed
7.
Furber G, Segal L. Give your child and adolescent mental health service a health economics makeover. Child Youth Serv Rev. 2011;34:71–5.CrossRef
8.
Green C, Brazier J, Deverill M. Valuing health-related quality of life. Pharmacoeconomics. 2000;17:151–65.CrossRefPubMed
9.
10.
Ratcliffe J, Flynn T, Terlich F, Stevens K, Brazier J, Sawyer M. Developing adolescent-specific health state values for economic evaluation: an application of profile case best-worst scaling to the Child Health Utility 9D. Pharmacoeconomics. 2012;30:713–27.CrossRefPubMed
11.
Furlong WJ, Feeny DH, Torrance GW, Barr RD. The Health Utilities Index (HUI) system for assessing health-related quality of life in clinical studies. Ann Med. 2001;33:375–84.CrossRefPubMed
12.
Apajasalo M, Sintonen H, Holmberg C, Sinkkonen J, Aalberg V, Pihko H, et al. Quality of life in early adolescence: a sixteen-dimensional health-related measure (16D). Qual Life Res. 1996;5:205–11.CrossRefPubMed
13.
Apajasalo M, Rautonen J, Holmberg C, Sinkkonen J, Aalberg V, Pihko H, et al. Quality of life in pre-adolescence: A 17-dimensional health-related measure (17D). Qual Life Res. 1996;5:532–8.CrossRefPubMed
14.
Wille N, Badia X, Bonsel G, Burström K, Cavrini G, Devlin N, et al. Development of the EQ-5D-Y: a child-friendly version of the EQ-5D. Qual Life Res. 2010;19:875–86.CrossRefPubMedCentralPubMed
15.
Beusterien KM, Yeung J-E, Pang F, Brazier J. Development of the multi-attribute Adolescent Health Utility Measure (AHUM). Health Qual Life Outcomes. 2012;10:102.CrossRefPubMedCentralPubMed
16.
Mihalopolous C, Richardson J, Iezzi A, Khan M. The assessment of Quality of Life Eight Dimension Scale (AQoL-8D) - How does it compare to commonly used mental health outcomes instruments? J Ment Health Policy Econ. 2013;16:S25–6.
17.
Stevens K. The development of a preference based paediatric health related quality of life measure for use in economic evaluation. PhD thesis. Sheffield: The University of Sheffield; 2008.
18.
19.
Stevens K. Developing a descriptive system for a new preference-based measure of health-related quality of life for children. Qual Life Res. 2009;18:1105–13.CrossRefPubMed
20.
Stevens K. 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. Appl Health Econ Health Policy. 2011;9:157–69.CrossRefPubMed
21.
Canaway AG, Frew EJ. 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. Qual Life Res. 2013;22:173–83.CrossRefPubMed
22.
Stevens K, Ratcliffe J. 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. 2012;15:1092–9.CrossRefPubMed
23.
Ratcliffe J, Couzner L, Flynn T, Sawyer M, Stevens K, Brazier J, et al. Valuing Child Health Utility 9D health states with a young adolescent sample: a feasibility study to compare best-worst scaling discrete-choice experiment, standard gamble and time trade-off methods. Appl Health Econ Health Policy. 2011;9:15–27.CrossRefPubMed
24.
Ratcliffe J, Stevens K, Flynn T, Brazier J, Sawyer M. An assessment of the construct validity of the CHU9D in the Australian adolescent general population. Qual Life Res. 2012;21:717–25.CrossRefPubMed
25.
Furber GV, Segal L, Leach MJ, Cocks J. Mapping scores from the Strengths and Difficulties Questionnaire (SDQ) to preference-based utility values. Qual Life Res. 2013;23:403–11.CrossRefPubMed
26.
Rutter M. A children’s behaviour questionnaire for completion by teachers: preliminary findings. J Child Psychol Psychiatry. 1967;8:1–11.CrossRefPubMed
27.
Achenbach TM, Rescorla LA. Manual for the ASEBA preschool forms & profiles. Burlington, VT: University of Vermont, Research Center for Children, Youth, & Families; 2000.
28.
Achenbach TM, Rescorla LA. Manual for the ASEBA school-Age forms & profiles. Burlington, VT: University of Vermont, Research Center for Children, Youth, & Families; 2001.
29.
Goodman R. Psychometric properties of the strengths and difficulties questionnaire. J Am Acad Child Adolesc Psychiatry. 2001;40:1337–45.CrossRefPubMed
30.
Hawes DJ, Dadds MR. Australian data and psychometric properties of the Strengths and Difficulties Questionnaire. Aust N Z J Psychiatry. 2004;38:644–51.CrossRefPubMed
31.
Goodman A, Goodman R. Strengths and difficulties questionnaire as a dimensional measure of child mental health. J Am Acad Child Adolesc Psychiatry. 2009;48:400–3.CrossRefPubMed
32.
Department of Health, Canberra. Mental Health National Outcomes and Casemix Collection. Technical specification of state and territory reporting requirements, version 1.70. Canberra: Department of Health; 2013.
33.
34.
35.
Field A. Discovering statistics using IBM SPSS statistics. London: Sage Publications Ltd; 2013.
36.
Cohen J. Statistical power analysis for the behavioral sciences (2nd edition). New Jersey: Lawrence Erlbaum; 1988.
37.
Drummond M. Introducing economic and quality of life measurements into clinical studies. Ann Med. 2001;33:344–9.CrossRefPubMed
38.
39.
40.
Petrou S, Johnson S, Wolke D, Hollis C, Kochhar P, Marlow N. Economic costs and preference-based health-related quality of life outcomes associated with childhood psychiatric disorders. Br J Psychiatry. 2010;197:395–404.CrossRefPubMed
41.
Petrou S, Kupek E. Estimating preference-based health utilities index mark 3 utility scores for childhood conditions in England and Scotland. Med Decis Making. 2009;29:291–303.CrossRefPubMed
42.
Goodyer IM, Dubicka B, Wilkinson P, Kelvin R, Roberts C, Byford S, et al. A randomised controlled trial of cognitive behaviour therapy in adolescents with major depression treated by selective serotonin reuptake inhibitors. The ADAPT trial. Health Technol Assess. 2008;12(14):iii-iv, ix-60.CrossRefPubMed
43.
Bodden DHM, Dirksen CD, Bögels SM, Nauta MH, De Haan E, Ringrose J, et al. Costs and cost-effectiveness of family CBT versus individual CBT in clinically anxious children. Clin Child Psychol Psychiatry. 2008;13:543–64.CrossRefPubMed
44.
Kind P, Lafata JE, Matuszewski K, Raisch D. The use of QALYs in clinical and patient decision-making: issues and prospects. Value Health. 2009;12 Suppl 1:S27–30.CrossRefPubMed
45.
46.
47.
Batty MJ, Moldavsky M, Foroushani PS, Pass S, Marriott M, Sayal K, et al. Implementing routine outcome measures in child and adolescent mental health services: from present to future practice. Child Adolesc Ment Health. 2013;18:82–7.CrossRef
48.
Page LAF, Thomson WM, Marshman Z, Stevens KJ. The potential of the Child Health Utility 9D Index as an outcome measure for child dental health. BMC Oral Health. 2014;14:90.CrossRefPubMed
49.
Grieve R, Grishchenko M, Cairns J. SF-6D versus EQ-5D: reasons for differences in utility scores and impact on reported cost-utility. Eur J Health Econ. 2009;10:15–23.CrossRefPubMed
50.
Sach TH, Barton GR, Jenkinson C, Doherty M, Avery AJ, Muir KR. Comparing cost-utility estimates: does the choice of EQ-5D or SF-6D matter? Med Care. 2009;47:889–94.CrossRefPubMed
51.
52.
Brazier J, Roberts J, Deverill M. The estimation of a preference-based measure of health from the SF-36. J Health Econ. 2002;21:271–92.CrossRefPubMed
53.
Lamers LM, Bouwmans CAM, van Straten A, Donker MCH, Hakkaart L. Comparison of EQ-5D and SF-6D utilities in mental health patients. Health Econ. 2006;15:1229–36.CrossRefPubMed
54.
Ferreira LN, Ferreira PL, Pereira LN, Rowen D. Reducing the floor effect in the SF-6D: a feasibility study. Appl Res Qual Life. 2011;7:193–208.CrossRef
55.
Ungar WJ. Challenges in health state valuation in paediatric economic evaluation: are QALYs contraindicated? Pharmacoeconomics. 2011;29:641–52.CrossRefPubMed
56.
Metadata
Title
The validity of the Child Health Utility instrument (CHU9D) as a routine outcome measure for use in child and adolescent mental health services
Authors
Gareth Furber
Leonie Segal
Publication date
01-12-2015
Publisher
BioMed Central
Published in
Health and Quality of Life Outcomes / Issue 1/2015
Electronic ISSN: 1477-7525
DOI
https://doi.org/10.1186/s12955-015-0218-4

Other articles of this Issue 1/2015

Health and Quality of Life Outcomes 1/2015 Go to the issue

Research

Quality of life and its association with direct medical costs for COPD in urban China

Research

Predictors of health-related quality of life in stroke patients after neurological inpatient rehabilitation: a prospective study

Research

Translation, cross-cultural adaptation and psychometric evaluation of yoruba version of the short-form 36 health survey

Research

The effect of subjective and objective social class on health-related quality of life: new paradigm using longitudinal analysis

Research

Psychometric properties of the incontinence utility index among patients with idiopathic overactive bladder: data from two multicenter, double-blind, randomized, Phase 3, placebo-controlled clinical trials

Research

Construction of quality of life change patterns: example in oncology in a phase III therapeutic trial (FFCD 0307)