<?xml version="1.0"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.2 20190208//EN" "JATS-journalpublishing1.dtd" [
]>
<article xml:lang="en" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
  xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML"
  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.v10i3.3186</article-id>
      <article-id pub-id-type="publisher-id">10:3:137</article-id>
      <title-group>
        <article-title>Primary school attainment outcomes in children with neurodisability: A
          population-based cohort study using linked education and health data from England.</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Munnery</surname>
            <given-names initials="K">Kim</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Shepherd</surname>
            <given-names initials="V">Victoria</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Lugg-Widger</surname>
            <given-names initials="F">Fiona</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Dibigbo</surname>
            <given-names initials="A">Amaka</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Lloyd</surname>
            <given-names initials="C">Christopher</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Trubey</surname>
            <given-names initials="R">Rob</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Ahmed</surname>
            <given-names initials="N">Nageen</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Hood</surname>
            <given-names initials="K">Kerenza</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Cannings-John</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>Murray</surname>
            <given-names initials="M">Macey L</given-names>
          </name>
          <xref ref-type="aff" rid="affil-2">2</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Mafham</surname>
            <given-names initials="M">Marion</given-names>
          </name>
          <xref ref-type="aff" rid="affil-3">3</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Robling</surname>
            <given-names initials="M">Mike</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
          <xref ref-type="aff" rid="affil-4">4</xref>
        </contrib>
      </contrib-group>
      <aff id="affil-1"><label>1</label><institution>Centre for Trials Research, Cardiff University,
        Cardiff, United Kingdom</institution></aff>
      <aff id="affil-2"><label>2</label><institution>MRC Clinical Trials Unit at UCL, London, United
        Kingdom</institution></aff>
      <aff id="affil-3"><label>3</label><institution>Clinical Trials Service Unit, Oxford Population
        Health, University of Oxford, Oxford, United Kingdom</institution></aff>
      <aff id="affil-4"><label>4</label><institution>Decipher, Cardiff University, Cardiff, United
        Kingdom</institution></aff>
      <pub-date>
        <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>3186</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/3186">This article is available from the
        IJPDS website at: https://ijpds.org/article/view/3186</self-uri>
    </article-meta>
  </front>
  <body>
    <sec>
      <title>Objectives</title>
      <p>The aim of the scoping review was to identify the existing literature on public and
        professional’s perspectives about inclusivity and diversity in trials that use routinely
        collected data. The review will inform the development of training for researchers to
        promote best practice for inclusive trial design.</p>
    </sec>
    <sec>
      <title>Methods</title>
      <p>The scoping review followed the 6-stage Arksey and O'Malley methodology framework,
        involving a systematic search of relevant databases and selection of publications based on
        predefined criteria. Those included were collated, summarised and reported using a thematic
        approach. The review included international publications to ensure a global perspective. The
        findings have been discussed in consultation with the HDR UK-funded Transforming Data for
        Trials’ public advisory group and key messages have been embedded into a training module to
        ensure its relevance and applicability. This module specifically focusses on equity insights
        for those that work on trials that use health systems data (HSD).</p>
    </sec>
    <sec>
      <title>Results</title>
      <p>We will present the results of the scoping review, including how the use of HSD can enhance
        inclusive trial design and areas where it does not. Preliminary results from 47 publications
        to date indicate a range of views from under-served groups toward the use of this data in
        trials from both public and professional opinion. The review has also identified
        data-enabled strategies and challenges related to inclusivity and diversity in trials. A
        training module is in development to begin to address these challenges, providing practical
        guidance and resources to enhance trialist’s best practice knowledge around inclusive trial
        design using HSD. The public voice is represented in the interpretation of the scoping
        review findings and content of the training, including key quotes and discussions from
        workshops.</p>
    </sec>
    <sec>
      <title>Conclusion</title>
      <p>This work explores ways to make trials more inclusive and diverse when using HSD and will
        contribute to building capacity in the field of real-world data research. The training will
        offer valuable insights into different research partners perspectives, guiding future
        inclusive trials and training initiatives.</p>
    </sec>
  </body>
</article>