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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.v11i5.3528</article-id>
<article-id pub-id-type="publisher-id">11:5:3528</article-id>
<article-id pub-id-type="pii">S239949082103528X</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Population Data Science</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>Longitudinal analysis of school absence of pupils with and without Additional Support Needs in Scotland</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author"><name><surname>Behrens</surname><given-names initials="S">Silvia</given-names></name><xref ref-type="aff" rid="affil-1"><sup>1</sup></xref></contrib>
<contrib contrib-type="author"><name><surname>Treanor</surname><given-names initials="M">Morag</given-names></name><xref ref-type="aff" rid="affil-1"><sup>1</sup></xref></contrib>
<contrib contrib-type="author"><name><surname>Troncoso</surname><given-names initials="P">Patricio</given-names></name><xref ref-type="aff" rid="affil-2"><sup>2</sup></xref></contrib>
<contrib contrib-type="author"><name><surname>Russell</surname><given-names initials="E">Emma</given-names></name><xref ref-type="aff" rid="affil-1"><sup>1</sup></xref></contrib>
<contrib contrib-type="author"><name><surname>Lee-Shield</surname><given-names initials="B">Bethany</given-names></name><xref ref-type="aff" rid="affil-2"><sup>2</sup></xref></contrib>
<contrib contrib-type="author"><name><surname>Williamson</surname><given-names initials="L">Lee</given-names></name><xref ref-type="aff" rid="affil-2"><sup>2</sup></xref></contrib>
<contrib contrib-type="author"><name><surname>Macintyre</surname><given-names initials="C">Cecilia</given-names></name><xref ref-type="aff" rid="affil-3"><sup>3</sup></xref></contrib>
<aff id="affil-1"><label>1</label><institution>University of Glasgow, Glasgow, United Kingdom</institution></aff>
<aff id="affil-2"><label>2</label><institution>The University of Edinburgh, Edinburgh, United Kingdom</institution></aff>
<aff id="affil-3"><label>3</label><institution>Scottish Government, Edinburgh, United Kingdom</institution></aff>
</contrib-group>
<pub-date date-type="pub" publication-format="electronic"><day></day><month></month><year></year></pub-date>
<pub-date date-type="collection" publication-format="electronic"><year></year></pub-date>
<volume>11</volume>
<issue>5</issue>
<elocation-id>3528</elocation-id>
<permissions>
<license license-type="open-access" xlink:href="https://creativecommons.org/licenses/by-nc-nd/4.0/">
<license-p>This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.</license-p>
</license>
</permissions>
<self-uri xlink:href="https://ijpds.org/article/view/3528">This article is available from the IJPDS website at: https://ijpds.org/article/view/3528</self-uri>
<abstract>
<p>Children with special educational needs and disabilities (SEND) are more likely to be absent from school. In Scotland, SEND are referred to as additional support needs (ASN) and include needs resulting from health and disabilities but also extend to family circumstances, the learning environment, and social-emotional needs. This paper analyses the trajectories of school absence of pupils with and without ASN. Using linked administrative data from the Scottish context, the paper follows a cohort of 49,180 pupils at publicly funded schools who started school in 2008/09 to the end of mandatory education at secondary stage S4. Multilevel modelling and zero-inflated beta regression models are used to investigate the longitudinal association between ASN and school absence, controlling for school and local authority clustering. For modelling ASN as a binary category, using a cubic time term with a random pupil-level time slope provided the best fit overall, indicating a non-linear relationship between ASN status and absence over time. A subsequent model differentiating between ASN categories was best captured using a linear time term. The results confirmed a persistent attendance gap between pupils with and without ASN. This gap is present during primary school but widens during secondary school. This widening is particularly driven by social-emotional needs, family circumstances, and other non-specified needs. Variation in absence by ASN is greatest at primary-school level, followed by secondary-school and local authority-level. These findings can inform targeted and school-stage specific support to mitigate disparities in attendance among heterogeneous groups of pupils with ASN.</p>
</abstract>
</article-meta>
</front>
</article>