Pathways through support services in neurodivergent children and young people who develop mental health conditions: preliminary findings and challenges using administrative data from the ECHILD project

ObjectivesThe prevalence of mental health (MH) disorders in neurodivergent (e.g., autistic or ADHD) children and young people (CYP) is high. Many neurodivergent CYP, at some point, engage with educational support, social care, and health services, each contact representing an opportunity for unmet MH support needs to be identified and addressed. MethodThe current research leverages the rich administrative data linkage by the Education and Child Health Insights from Linked Data (ECHILD) project in the UK. It assesses whether, when, and where neurodivergent CYP who develop MH conditions engage with educational support, social care, and health services from birth until 12 years of age (focusing on CYP born in or after 2011). I will also assess how their pathways of service contact may differ from those of their peers, including neurodivergent CYP without a diagnosis of MH conditions and neurotypical CYP who have a diagnosis of a MH condition. ResultsThe current presentation will provide a first insight into the data and preliminary comparisons across the quasi-experimental groups including a general overview of differences in the type of services CYP are in contact with and how that varies based on demographic characteristic (gender and ethnicity). It will also discuss the benefits and challenges of making use of administrative data information on mental health diagnoses linked to educational, social care, and hospital episode data. ConclusionAdministrative data linkage provides an excellent opportunity to conduct careful longitudinal assessment of temporal precedence for first contact with different services in a large-scale dataset of service users.

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Publication Details

Journal
International Journal for Population Data Science
Published
2025-08-28
DOI
https://doi.org/10.23889/ijpds.v10i4.3162
Primary Topic
demographic modeling and climate adaptation
Type
article
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article

Pathways through support services in neurodivergent children and young people who develop mental health conditions: preliminary findings and challenges using administrative data from the ECHILD project

Simona Skripkauskaitė
International Journal for Population Data Science
demographic modeling and climate adaptation
article

Pathways through support services in neurodivergent children and young people who develop mental health conditions: preliminary findings and challenges using administrative data from the ECHILD project

Simona Skripkauskaitė
article en

Abstract

ObjectivesThe prevalence of mental health (MH) disorders in neurodivergent (e.g., autistic or ADHD) children and young people (CYP) is high. Many neurodivergent CYP, at some point, engage with educational support, social care, and health services, each contact representing an opportunity for unmet MH support needs to be identified and addressed. MethodThe current research leverages the rich administrative data linkage by the Education and Child Health Insights from Linked Data (ECHILD) project in the UK. It assesses whether, when, and where neurodivergent CYP who develop MH conditions engage with educational support, social care, and health services from birth until 12 years of age (focusing on CYP born in or after 2011). I will also assess how their pathways of service contact may differ from those of their peers, including neurodivergent CYP without a diagnosis of MH conditions and neurotypical CYP who have a diagnosis of a MH condition. ResultsThe current presentation will provide a first insight into the data and preliminary comparisons across the quasi-experimental groups including a general overview of differences in the type of services CYP are in contact with and how that varies based on demographic characteristic (gender and ethnicity). It will also discuss the benefits and challenges of making use of administrative data information on mental health diagnoses linked to educational, social care, and hospital episode data. ConclusionAdministrative data linkage provides an excellent opportunity to conduct careful longitudinal assessment of temporal precedence for first contact with different services in a large-scale dataset of service users.

International Journal for Population Data ScienceVol. 10(4)
University of Oxford (GB)
Openalex Percentile: Top 73%
demographic modeling and climate adaptation
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