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Estimating prevalence of child and youth mental disorder and mental health-related service contacts: a comparison of survey data and linked administrative health data

AIMS: Prevalence estimates of child and youth mental disorder and mental health-related service contacts are needed for policy formulation, research, advocacy and resource allocation. Our aim is to compare prevalence estimates of child and youth mental disorder and mental health-related service cont...

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Autores principales: Duncan, L., Georgiades, K., Wang, L., Edwards, J., Comeau, J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cambridge University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9121846/
https://www.ncbi.nlm.nih.gov/pubmed/35586920
http://dx.doi.org/10.1017/S204579602200018X
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author Duncan, L.
Georgiades, K.
Wang, L.
Edwards, J.
Comeau, J.
author_facet Duncan, L.
Georgiades, K.
Wang, L.
Edwards, J.
Comeau, J.
author_sort Duncan, L.
collection PubMed
description AIMS: Prevalence estimates of child and youth mental disorder and mental health-related service contacts are needed for policy formulation, research, advocacy and resource allocation. Our aim is to compare prevalence estimates of child and youth mental disorder and mental health-related service contacts derived from general population survey data v. linked administrative health data. METHODS: Provincially representative 2014 Ontario Child Health Study data were linked to administrative health records for 5563 children and youth aged 4–17 in Ontario. Emotional disorders (mood and anxiety) and attention-deficit/hyperactivity disorder were assessed using a standardised diagnostic interview in the survey and using diagnostic codes in administrative health data. Physician-based mental health-related service contacts were assessed using parent self-reports from the survey and administrative data related to mental health-related diagnostic codes. Prevalence estimates were calculated and compared based on one-sample z-tests and ratios of survey data to administrative data-based prevalence. Sensitivity, specificity and agreement between classifications were compared using κ. Prevalence estimates were calculated by age, sex and geography sub-groups and consistent group differences across data source were counted. RESULTS: Disorder prevalence and service contact estimates were significantly higher in survey data in all cases, except for mood disorder. Ratios of survey data to administrative data-based prevalence varied, ranging from 0.80 (mood) to 11.01 (attention-deficit/hyperactivity disorder). Specificity was high (0.98–1.00), sensitivity was low (0.07–0.41) and agreement ranged from slight (κ = 0.13) to moderate (κ = 0.46). Out of 18 sub-group difference comparisons, half were non-significant in either data source. In the remaining nine comparisons, the only significant differences between groups that were consistent across data source were for sex-based differences (attention-deficit/hyperactivity disorder and service contacts). There were no consistent age- or geography-based differences in prevalence across data sources. CONCLUSIONS: Our findings suggest that conclusions drawn about prevalence, service contacts and sub-group differences in these estimates are dependent on data source. Further research is needed to understand who and what is being captured by each source. Researchers should conduct data linkage where possible to access and compare multiple sources of information.
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spelling pubmed-91218462022-06-01 Estimating prevalence of child and youth mental disorder and mental health-related service contacts: a comparison of survey data and linked administrative health data Duncan, L. Georgiades, K. Wang, L. Edwards, J. Comeau, J. Epidemiol Psychiatr Sci Original Article AIMS: Prevalence estimates of child and youth mental disorder and mental health-related service contacts are needed for policy formulation, research, advocacy and resource allocation. Our aim is to compare prevalence estimates of child and youth mental disorder and mental health-related service contacts derived from general population survey data v. linked administrative health data. METHODS: Provincially representative 2014 Ontario Child Health Study data were linked to administrative health records for 5563 children and youth aged 4–17 in Ontario. Emotional disorders (mood and anxiety) and attention-deficit/hyperactivity disorder were assessed using a standardised diagnostic interview in the survey and using diagnostic codes in administrative health data. Physician-based mental health-related service contacts were assessed using parent self-reports from the survey and administrative data related to mental health-related diagnostic codes. Prevalence estimates were calculated and compared based on one-sample z-tests and ratios of survey data to administrative data-based prevalence. Sensitivity, specificity and agreement between classifications were compared using κ. Prevalence estimates were calculated by age, sex and geography sub-groups and consistent group differences across data source were counted. RESULTS: Disorder prevalence and service contact estimates were significantly higher in survey data in all cases, except for mood disorder. Ratios of survey data to administrative data-based prevalence varied, ranging from 0.80 (mood) to 11.01 (attention-deficit/hyperactivity disorder). Specificity was high (0.98–1.00), sensitivity was low (0.07–0.41) and agreement ranged from slight (κ = 0.13) to moderate (κ = 0.46). Out of 18 sub-group difference comparisons, half were non-significant in either data source. In the remaining nine comparisons, the only significant differences between groups that were consistent across data source were for sex-based differences (attention-deficit/hyperactivity disorder and service contacts). There were no consistent age- or geography-based differences in prevalence across data sources. CONCLUSIONS: Our findings suggest that conclusions drawn about prevalence, service contacts and sub-group differences in these estimates are dependent on data source. Further research is needed to understand who and what is being captured by each source. Researchers should conduct data linkage where possible to access and compare multiple sources of information. Cambridge University Press 2022-05-19 /pmc/articles/PMC9121846/ /pubmed/35586920 http://dx.doi.org/10.1017/S204579602200018X Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
spellingShingle Original Article
Duncan, L.
Georgiades, K.
Wang, L.
Edwards, J.
Comeau, J.
Estimating prevalence of child and youth mental disorder and mental health-related service contacts: a comparison of survey data and linked administrative health data
title Estimating prevalence of child and youth mental disorder and mental health-related service contacts: a comparison of survey data and linked administrative health data
title_full Estimating prevalence of child and youth mental disorder and mental health-related service contacts: a comparison of survey data and linked administrative health data
title_fullStr Estimating prevalence of child and youth mental disorder and mental health-related service contacts: a comparison of survey data and linked administrative health data
title_full_unstemmed Estimating prevalence of child and youth mental disorder and mental health-related service contacts: a comparison of survey data and linked administrative health data
title_short Estimating prevalence of child and youth mental disorder and mental health-related service contacts: a comparison of survey data and linked administrative health data
title_sort estimating prevalence of child and youth mental disorder and mental health-related service contacts: a comparison of survey data and linked administrative health data
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9121846/
https://www.ncbi.nlm.nih.gov/pubmed/35586920
http://dx.doi.org/10.1017/S204579602200018X
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