Cargando…
How do common conditions impact health-related quality of life for children? Providing guidance for validating pediatric preference-based measures
BACKGROUND: There is increasing interest in the validation of pediatric preference-based health-related quality of life measurement instruments. It is critical that children with various degrees of health-related quality of life (HRQoL) impact are included in validation studies. To inform patient sa...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9878815/ https://www.ncbi.nlm.nih.gov/pubmed/36698179 http://dx.doi.org/10.1186/s12955-023-02091-4 |
_version_ | 1784878569233580032 |
---|---|
author | Xiong, Xiuqin Dalziel, Kim Huang, Li Mulhern, Brendan Carvalho, Natalie |
author_facet | Xiong, Xiuqin Dalziel, Kim Huang, Li Mulhern, Brendan Carvalho, Natalie |
author_sort | Xiong, Xiuqin |
collection | PubMed |
description | BACKGROUND: There is increasing interest in the validation of pediatric preference-based health-related quality of life measurement instruments. It is critical that children with various degrees of health-related quality of life (HRQoL) impact are included in validation studies. To inform patient sample selection for validation studies from a pragmatic perspective, this study explored HRQoL impairments between known-groups and HRQoL changes over time across 27 common chronic child health conditions and identified conditions with the largest impact on HRQoL. METHODS: The health dimensions of two common preference-based HRQoL measures, the EQ-5D-Y and CHU9D, were constructed using Pediatric Quality of Life Inventory items that overlap conceptually. Data was from the Longitudinal Study of Australian Children, a nationally representative sample with over 10,000 children at baseline. Seven waves of data were included for the analysis, with child age ranging from 2 to18 years. Impacts to specific health dimensions and overall HRQoL between those having a specific condition versus not were compared using linear mixed effects models. HRQoL changes over time were obtained by calculating the HRQoL differences between two consecutive time points, grouped by “Improved” and “Worsened” health status. Comparison among various health conditions and different age groups (2–4 years, 5–12 years and 13–18 years) were made. RESULTS: Conditions with the largest statistically significant total HRQoL impairments of having a specific condition compared with not having the condition were recurrent chest pain, autism, epilepsy, anxiety/depression, irritable bowel, recurrent back pain, recurrent abdominal pain, and attention deficit hyperactivity disorder (ADHD) for the total sample (2–18 years). Conditions with largest HRQoL improvement over time were anxiety/depression, ADHD, autism, bone/joint/muscle problem, recurrent abdominal pain, recurrent pain in other part, frequent headache, diarrhea and day-wetting. The dimensions included in EQ-5D-Y and CHU9D can generally reflect HRQoL differences and changes. The HRQoL impacts to specific health dimensions differed by condition in the expected direction. The conditions with largest HRQoL impacts differed by age group. CONCLUSIONS: The conditions with largest HRQoL impact were identified. This information is likely to be valuable for recruiting patient samples when validating pediatric preference-based HRQoL instruments pragmatically. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12955-023-02091-4. |
format | Online Article Text |
id | pubmed-9878815 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-98788152023-01-27 How do common conditions impact health-related quality of life for children? Providing guidance for validating pediatric preference-based measures Xiong, Xiuqin Dalziel, Kim Huang, Li Mulhern, Brendan Carvalho, Natalie Health Qual Life Outcomes Research BACKGROUND: There is increasing interest in the validation of pediatric preference-based health-related quality of life measurement instruments. It is critical that children with various degrees of health-related quality of life (HRQoL) impact are included in validation studies. To inform patient sample selection for validation studies from a pragmatic perspective, this study explored HRQoL impairments between known-groups and HRQoL changes over time across 27 common chronic child health conditions and identified conditions with the largest impact on HRQoL. METHODS: The health dimensions of two common preference-based HRQoL measures, the EQ-5D-Y and CHU9D, were constructed using Pediatric Quality of Life Inventory items that overlap conceptually. Data was from the Longitudinal Study of Australian Children, a nationally representative sample with over 10,000 children at baseline. Seven waves of data were included for the analysis, with child age ranging from 2 to18 years. Impacts to specific health dimensions and overall HRQoL between those having a specific condition versus not were compared using linear mixed effects models. HRQoL changes over time were obtained by calculating the HRQoL differences between two consecutive time points, grouped by “Improved” and “Worsened” health status. Comparison among various health conditions and different age groups (2–4 years, 5–12 years and 13–18 years) were made. RESULTS: Conditions with the largest statistically significant total HRQoL impairments of having a specific condition compared with not having the condition were recurrent chest pain, autism, epilepsy, anxiety/depression, irritable bowel, recurrent back pain, recurrent abdominal pain, and attention deficit hyperactivity disorder (ADHD) for the total sample (2–18 years). Conditions with largest HRQoL improvement over time were anxiety/depression, ADHD, autism, bone/joint/muscle problem, recurrent abdominal pain, recurrent pain in other part, frequent headache, diarrhea and day-wetting. The dimensions included in EQ-5D-Y and CHU9D can generally reflect HRQoL differences and changes. The HRQoL impacts to specific health dimensions differed by condition in the expected direction. The conditions with largest HRQoL impacts differed by age group. CONCLUSIONS: The conditions with largest HRQoL impact were identified. This information is likely to be valuable for recruiting patient samples when validating pediatric preference-based HRQoL instruments pragmatically. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12955-023-02091-4. BioMed Central 2023-01-25 /pmc/articles/PMC9878815/ /pubmed/36698179 http://dx.doi.org/10.1186/s12955-023-02091-4 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Xiong, Xiuqin Dalziel, Kim Huang, Li Mulhern, Brendan Carvalho, Natalie How do common conditions impact health-related quality of life for children? Providing guidance for validating pediatric preference-based measures |
title | How do common conditions impact health-related quality of life for children? Providing guidance for validating pediatric preference-based measures |
title_full | How do common conditions impact health-related quality of life for children? Providing guidance for validating pediatric preference-based measures |
title_fullStr | How do common conditions impact health-related quality of life for children? Providing guidance for validating pediatric preference-based measures |
title_full_unstemmed | How do common conditions impact health-related quality of life for children? Providing guidance for validating pediatric preference-based measures |
title_short | How do common conditions impact health-related quality of life for children? Providing guidance for validating pediatric preference-based measures |
title_sort | how do common conditions impact health-related quality of life for children? providing guidance for validating pediatric preference-based measures |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9878815/ https://www.ncbi.nlm.nih.gov/pubmed/36698179 http://dx.doi.org/10.1186/s12955-023-02091-4 |
work_keys_str_mv | AT xiongxiuqin howdocommonconditionsimpacthealthrelatedqualityoflifeforchildrenprovidingguidanceforvalidatingpediatricpreferencebasedmeasures AT dalzielkim howdocommonconditionsimpacthealthrelatedqualityoflifeforchildrenprovidingguidanceforvalidatingpediatricpreferencebasedmeasures AT huangli howdocommonconditionsimpacthealthrelatedqualityoflifeforchildrenprovidingguidanceforvalidatingpediatricpreferencebasedmeasures AT mulhernbrendan howdocommonconditionsimpacthealthrelatedqualityoflifeforchildrenprovidingguidanceforvalidatingpediatricpreferencebasedmeasures AT carvalhonatalie howdocommonconditionsimpacthealthrelatedqualityoflifeforchildrenprovidingguidanceforvalidatingpediatricpreferencebasedmeasures |