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Australian adolescent population norms for the child health utility index 9D-results from the young minds matter survey.
Le, Long Khanh-Dao; Richards-Jones, Scott; Chatterton, Mary Lou; Engel, Lidia; Lawrence, David; Stevenson, Chris; Pepin, Genevieve; Ratcliffe, Julie; Sawyer, Michael; Mihalopoulos, Cathrine.
Affiliation
  • Le LK; Deakin Health Economics, Faculty of Health, Institute for Health Transformation, School of Health and Social Development, Deakin University, Geelong, Australia. long.le@deakin.edu.au.
  • Richards-Jones S; School of Health and Social Development, Deakin University, Geelong, Victoria, Australia. long.le@deakin.edu.au.
  • Chatterton ML; Deakin Health Economics, Faculty of Health, Institute for Health Transformation, School of Health and Social Development, Deakin University, Geelong, Australia.
  • Engel L; Deakin Health Economics, Faculty of Health, Institute for Health Transformation, School of Health and Social Development, Deakin University, Geelong, Australia.
  • Lawrence D; Deakin Health Economics, Faculty of Health, Institute for Health Transformation, School of Health and Social Development, Deakin University, Geelong, Australia.
  • Stevenson C; Graduate School of Education, The University of Western Australia, Perth, Australia.
  • Pepin G; Faculty of Health, School of Health and Social Development, Deakin University, Geelong, Australia.
  • Ratcliffe J; Faculty of Health, School of Health and Social Development, Deakin University, Geelong, Australia.
  • Sawyer M; Health and Social Care Economics Group, Caring Futures Institute, Flinders University, Adelaide, Australia.
  • Mihalopoulos C; School of Psychology and Adelaide Medical School, University of Adelaide, Adelaide, SA, Australia.
Qual Life Res ; 30(10): 2895-2906, 2021 Oct.
Article in En | MEDLINE | ID: mdl-33999321
OBJECTIVE: Patient-reported outcomes of health-related quality-of-life (HRQoL) are important descriptors of population health. A recent Australian adolescent population survey provided a unique opportunity to derive preference-based HRQoL. METHODS: Data from 2967 adolescents aged 11-17 years were analysed. An interviewer-led parent/carer questionnaire was administered for demographic variables and mental disorders of adolescents during previous 12 months using the Diagnostic Interview Schedule for Children. A self-report survey was administered to derive HRQoL using the child health utility nine-dimensions instrument (CHU-9D). Weighted HRQoL was derived for several demographic groups, mental disorder diagnosis, and youth risk behaviours. RESULTS: The total population had a mean utility of 0.78 [standard deviation (SD): 0.20]. Males had a significantly higher mean utility (0.81, SD 0.18) than females (0.76, SD: 0.21) (Cohen's d = 0.23, p < 0.001), and utility decreased with age for both males and females (p < 0.001). Family type and some parent/carer variables were associated with significant lower HRQoL scores with small effect size. Youth risk behaviours were associated with reduced HRQoL with moderate effect sizes. Adolescents who self-harmed, had suicidal ideation, or had a mental disorder had significantly lower utilities scores with moderate to large effect sizes compared to those who did not have such conditions. CONCLUSIONS: This study has provided contemporary Australian population norms for HRQoL in adolescents that may be used as cross comparison between studies as well as indicators allowing estimation of population health (e.g. estimation of the burden of disease) and can be used to populate future economic models.
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Full text: 1 Database: MEDLINE Main subject: Quality of Life / Child Health Type of study: Prognostic_studies Limits: Adolescent / Child / Female / Humans / Male Country/Region as subject: Oceania Language: En Year: 2021 Type: Article

Full text: 1 Database: MEDLINE Main subject: Quality of Life / Child Health Type of study: Prognostic_studies Limits: Adolescent / Child / Female / Humans / Male Country/Region as subject: Oceania Language: En Year: 2021 Type: Article