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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.v9i5.1681</article-id>
      <article-id pub-id-type="publisher-id">9:5:193</article-id>
      <title-group>
        <article-title>An innovative approach to developing practice informed evidence in the absence of RCTs for a Family-led peer to peer support program</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Montgomerie</surname>
            <given-names initials="A">Alicia</given-names>
          </name>
          <xref ref-type="aff" rid="affil-1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Maiorano</surname>
            <given-names initials="V">Vita</given-names>
          </name>
          <xref ref-type="aff" rid="affil-2">2</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Abbott</surname>
            <given-names initials="D">Danielle</given-names>
          </name>
          <xref ref-type="aff" rid="affil-2">2</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Lynch</surname>
            <given-names initials="J">John</given-names>
          </name>
          <xref ref-type="aff" rid="affil-3">3</xref>
          <xref ref-type="aff" rid="affil-4">4</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Pilkington</surname>
            <given-names initials="R">Rhiannon</given-names>
          </name>
          <xref ref-type="aff" rid="affil-3">3</xref>
        </contrib>
      </contrib-group>
      <aff id="affil-1"><label>1</label><institution>School of Public Health, The University of Adelaide</institution></aff>
      <aff id="affil-2"><label>2</label><institution>The Australian Centre for Social Innovation</institution></aff>
      <aff id="affil-3"><label>3</label><institution>School of Public Health, The University of Adelaide</institution></aff>
      <aff id="affil-4"><label>4</label><institution>School of Population Health Sciences, University of Bristol</institution></aff>
      <pub-date date-type="pub" publication-format="electronic">
        <day>18</day>
        <month>09</month>
        <year>2024</year>
      </pub-date>
      <pub-date date-type="collection" publication-format="electronic">
        <year>2024</year>
      </pub-date>
      <volume>9</volume>
      <issue>5</issue>
      <elocation-id>1681</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/1681">This article is available from the IJPDS website at: https://ijpds.org/article/view/1681</self-uri>
    </article-meta>
  </front>
  <body>
    <sec>
      <title>Objective</title>
      <p>To illustrate how whole-population linked data can be used to understand a system perspective of client complexity, and build robust evidence of Family by Family program impact.</p>
    </sec>
    <sec>
      <title>Methods</title>
      <p>Family by Family program (the program) participant data were linked into the Better Evidence Better Outcomes Linked Data (BEBOLD) Platform. BEBOLD is a whole-of-population linked de-identified administrative data platform for all South Australian children born 1991 onwards (n~500,000), as well as their parents including data spanning health, education, and social services.</p>
      <p>We descriptively analysed parental child protection history, emergency department presentations, hospitalisations, homelessness and justice system contact in the 24 months prior to and post program commencement. We emulate a trial using the ‘target trial’ causal inference framework to evaluate the program effect on a range of child outcomes using targeted maximum likelihood with a set of over 20 confounders.</p>
    </sec>
    <sec>
      <title>Results</title>
      <p>There were 361 families and 841 children in the program included in analysis. Selected results follow: Prior to the program, 35.8% of children were in a family where at least one parent had their own child protection history and 8% had a parent who experienced out-of-home care. Nearly 40% of children had at least one parent with a mental health related emergency department and/or hospitalisation, while 22% of children were in a family with specialist homelessness service contact. Program impact results will be presented at the conference.</p>
    </sec>
    <sec>
      <title>Conclusion</title>
      <p>This research-practice partnership illustrates how bringing together program and linked-administrative data generates new evidence about client complexity and program impact.</p>
    </sec>
  </body>
</article>