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  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">IJPDS</journal-id>
      <journal-title-group>
        <journal-title>International Journal of Population Data Science</journal-title>
        <abbrev-journal-title>IJPDS</abbrev-journal-title>
      </journal-title-group>
      <issn pub-type="epub">2399-4908</issn>
      <publisher>
        <publisher-name>Swansea University</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.23889/ijpds.v10i3.3162</article-id>
      <article-id pub-id-type="publisher-id">10:3:130</article-id>
      <title-group>
        <article-title>An overview of the Northern Ireland Education Outcomes Linkage (EOL) (2018/2019) database</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Skripkauskaite</surname>
            <given-names initials="S">Simona</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
      </contrib-group>
      <aff id="affil-1"><label>1</label><institution>University of Oxford, Oxford, United Kingdom</institution></aff>
      <pub-date date-type="pub" publication-format="electronic">
        <day>01</day>
        <month>06</month>
        <year>2025</year>
      </pub-date>
      <pub-date date-type="collection" publication-format="electronic">
        <year>2025</year>
      </pub-date>
      <volume>8</volume>
      <issue>4</issue>
      <elocation-id>3162</elocation-id>
      <permissions>
        <license license-type="open-access"
          xlink:href="https://creativecommons.org/licences/by/4.0/">
          <license-p>This work is licenced under a Creative Commons Attribution 4.0 International License.</license-p>
        </license>
      </permissions>
      <self-uri xlink:href="https://ijpds.org/article/view/3162">This article is available from the IJPDS website at: https://ijpds.org/article/view/3162</self-uri>
    </article-meta>
  </front>
  <body>
    <sec>
      <title>Objectives</title>
      <p>The 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.</p>
    </sec>
    <sec>
      <title>Methods</title>
      <p>The 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.</p>
    </sec>
    <sec>
      <title>Results</title>
      <p>The 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.</p>
    </sec>
    <sec>
      <title>Conclusion</title>
      <p>Administrative 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.</p>
    </sec>
  </body>
</article>