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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.v10i3.3177</article-id>
      <article-id pub-id-type="publisher-id">10:3:145</article-id>
      <title-group>
        <article-title>Building Research Capacity for Data-Enabled Trials: Embedding Public
          Perspectives</article-title>
      </title-group>
      <contrib-group>
        <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>Nollett</surname>
            <given-names initials="C">Claire</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Stock</surname>
            <given-names initials="J">Joshua</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Fitzgibbon</surname>
            <given-names initials="J">Jim</given-names>
          </name>
          <xref ref-type="aff" rid="affil-2">2</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Yameen</surname>
            <given-names initials="F">Farheen</given-names>
          </name>
          <xref ref-type="aff" rid="affil-2">2</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Brookes-Howell</surname>
            <given-names initials="L">Lucy</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</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-3">3</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-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>Public Member, Cardiff, United Kingdom</institution></aff>
      <aff id="affil-3"><label>3</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>3177</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/3177">This article is available from the
        IJPDS website at: https://ijpds.org/article/view/3177</self-uri>
    </article-meta>
  </front>
  <body>
    <p>This project aimed to establish recommendations for data owners on the production, release,
      and public communication of synthetic data. By engaging members of the UK public in
      facilitated discussions, we explored perceptions of synthetic data use in research and
      identified strategies to enhance transparency, trust, and responsible data management.</p>
    <p>We worked with community engagement specialists to recruit a diverse group of 39 public
      members from across the UK. Members took part in four deliberative workshops, held online, to
      co-develop recommendations for data owners. They heard from subject matter experts and engaged
      in structured discussions on synthetic data, its applications, and ethical considerations. Key
      concerns and priorities were identified through analysis of workshop notes, with public
      feedback incorporated iteratively throughout the process to ensure recommendations aligned
      with public expectations. The workshops facilitated an in-depth exploration of transparency,
      accessibility, and governance surrounding synthetic data, highlighting the importance of clear
      public communication.</p>
    <p>Ten key recommendations were developed, categorised into five thematic areas: (1) Introducing
      synthetic data and its distinction from real data; (2) Clarifying its purpose and role in
      research; (3) Guidelines for dataset creation and validation; (4) Managing access, usage, and
      potential misuse; and (5) Strategies for effective public communication and trust-building.
      Public members emphasised the need for accessible explanations, governance measures, and
      ongoing engagement to ensure ethical use. Iterative refinement of recommendations in the final
      workshop highlighted public concerns about data misuse and the importance of organisation’s
      accountability. These findings provide a framework for responsible synthetic data creation and
      improved public engagement strategies.</p>
    <p>This project provides valuable insight into public attitudes towards synthetic data in
      research, emphasising transparency and trust. The recommendations offer guidance for UK data
      owners in responsibly managing synthetic datasets. Ongoing research is needed to monitor
      evolving public perspectives as synthetic data use expands across research domains.</p>
  </body>
</article>