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  dtd-version="1.2" article-type="abstract">
  <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.v10i3.3269</article-id>
      <article-id pub-id-type="publisher-id">10:3:234</article-id>
      <title-group>
        <article-title>Pathways to legal permanence for a cohort of care experienced children in
          Scotland</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Ward</surname>
            <given-names initials="R">Rebecca</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Rawlings</surname>
            <given-names initials="A">Anna</given-names>
          </name>
          <xref ref-type="aff" rid="affil-2">2</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>May</surname>
            <given-names initials="R">Richard</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Turner-Evans</surname>
            <given-names initials="H">Hywel</given-names>
          </name>
          <xref ref-type="aff" rid="affil-2">2</xref>
        </contrib>
      </contrib-group>
      <aff id="affil-1"><label>1</label><institution>University of South Wales, Pontypridd, United
        Kingdom</institution></aff>
      <aff id="affil-2"><label>2</label><institution>Swansea University, Swansea, 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>3269</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/3269">This article is available from the
        IJPDS website at: https://ijpds.org/article/view/3269</self-uri>
    </article-meta>
  </front>
  <body>
    <sec>
      <title>Objectives</title>
      <p>There are many challenges in identifying children with language and communication delays,
        including autism, from bilingual backgrounds. This study is the first to investigate
        disparities in autism diagnosis rates and age of diagnosis among multilingual children in
        the UK. It explores how language background, ethnicity, sex, and deprivation influence
        diagnostic patterns.</p>
    </sec>
    <sec>
      <title>Methods</title>
      <p>A retrospective cross-sectional study examined population-level data within the Secure
        Anonymised Information Linkage (SAIL) Databank to analyse trends in autism diagnosis in
        Wales, UK. Using routinely collected health, education, and Office for National Statistics
        Census 2011 data, we analysed diagnostic patterns of autism in children (aged ≤ 18 years)
        over a 20-year period (1999 – 2019). We report the association of language background,
        ethnicity, area-based relative deprivation level, educational attainment, and sex with
        autism diagnosis rates and age.</p>
    </sec>
    <sec>
      <title>Results</title>
      <p>Descriptive statistics were used to compare autism diagnoses between different language
        backgrounds (mono vs multilingual). Logistic regression models investigated the impact of
        language background on referral rates and age at diagnosis. Subgroup analyses were conducted
        to explore variations in diagnostic patterns by sex, ethnicity, and geographical location.
        Finally, hierarchical linear models were employed to explore whether specific factors,
        including level of relative deprivation and sex, contribute to disparities in neurodiversity
        diagnoses amongst multilingual children. Educational outcomes were also analysed whilst
        assessing the impact of age at diagnosis and language background. Statistical significance
        was assessed using 95% confidence intervals.</p>
    </sec>
    <sec>
      <title>Conclusion</title>
      <p>These findings will be crucial for identifying systemic barriers in autism diagnosis among
        multilingual children. By utilising data-driven insights, policymakers can guide
        improvements in autism screening, promoting equitable access to neurodiversity services.
        International efforts to improve autism identification and support services for multilingual
        populations can now be better informed.</p>
    </sec>
  </body>
</article>