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<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Psychiatry</journal-id>
<journal-title-group>
<journal-title>Frontiers in Psychiatry</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Psychiatry</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">1664-0640</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
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<article-meta>
<article-id pub-id-type="doi">10.3389/fpsyt.2025.1667612</article-id>
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<article-categories>
<subj-group subj-group-type="heading">
<subject>Original Research</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>Factorial invariance of the Spanish version of the PHQ-9 by gender and country in Latin America and the Caribbean</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name><surname>Caldichoury</surname><given-names>Nicole</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
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<name><surname>Morales-Asencio</surname><given-names>Breiner</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
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<name><surname>Castellanos-Alvarenga</surname><given-names>Luis Mario</given-names></name>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
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<contrib contrib-type="author">
<name><surname>Coronado</surname><given-names>Juan-Carlos</given-names></name>
<xref ref-type="aff" rid="aff4"><sup>4</sup></xref>
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<name><surname>Quispe-Ayala</surname><given-names>C&#xe9;sar</given-names></name>
<xref ref-type="aff" rid="aff5"><sup>5</sup></xref>
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<contrib contrib-type="author">
<name><surname>Ripoll-C&#xf3;rdoba</surname><given-names>Daniela</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
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<contrib contrib-type="author">
<name><surname>Sald&#xed;as</surname><given-names>Carol</given-names></name>
<xref ref-type="aff" rid="aff6"><sup>6</sup></xref>
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<name><surname>Bada</surname><given-names>Wendy</given-names></name>
<xref ref-type="aff" rid="aff7"><sup>7</sup></xref>
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<name><surname>Alcos-Flores</surname><given-names>Karen</given-names></name>
<xref ref-type="aff" rid="aff5"><sup>5</sup></xref>
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<name><surname>Zurita-Cueva</surname><given-names>Boris</given-names></name>
<xref ref-type="aff" rid="aff8"><sup>8</sup></xref>
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<name><surname>Duhalde-Sanhueza</surname><given-names>Rodrigo</given-names></name>
<xref ref-type="aff" rid="aff6"><sup>6</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/3137190/overview"/>
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<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="software" vocab-term-identifier="https://credit.niso.org/contributor-roles/software/">Software</role>
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<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; original draft" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-original-draft/">Writing &#x2013; original draft</role>
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<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="visualization" vocab-term-identifier="https://credit.niso.org/contributor-roles/visualization/">Visualization</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Data curation" vocab-term-identifier="https://credit.niso.org/contributor-roles/data-curation/">Data curation</role>
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</contrib>
<contrib contrib-type="author">
<name><surname>Romo</surname><given-names>Cristian</given-names></name>
<xref ref-type="aff" rid="aff9"><sup>9</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/2927073/overview"/>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; original draft" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-original-draft/">Writing &#x2013; original draft</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="visualization" vocab-term-identifier="https://credit.niso.org/contributor-roles/visualization/">Visualization</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Formal analysis" vocab-term-identifier="https://credit.niso.org/contributor-roles/formal-analysis/">Formal analysis</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="software" vocab-term-identifier="https://credit.niso.org/contributor-roles/software/">Software</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="validation" vocab-term-identifier="https://credit.niso.org/contributor-roles/validation/">Validation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="supervision" vocab-term-identifier="https://credit.niso.org/contributor-roles/supervision/">Supervision</role>
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<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &amp; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-review-editing/">Writing &#x2013; review &amp; editing</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Data curation" vocab-term-identifier="https://credit.niso.org/contributor-roles/data-curation/">Data curation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="investigation" vocab-term-identifier="https://credit.niso.org/contributor-roles/investigation/">Investigation</role>
</contrib>
<contrib contrib-type="author">
<name><surname>Quincho-Apumayta</surname><given-names>Ra&#xfa;l</given-names></name>
<xref ref-type="aff" rid="aff5"><sup>5</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/2899308/overview"/>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="software" vocab-term-identifier="https://credit.niso.org/contributor-roles/software/">Software</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; original draft" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-original-draft/">Writing &#x2013; original draft</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &amp; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-review-editing/">Writing &#x2013; review &amp; editing</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="investigation" vocab-term-identifier="https://credit.niso.org/contributor-roles/investigation/">Investigation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="visualization" vocab-term-identifier="https://credit.niso.org/contributor-roles/visualization/">Visualization</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="validation" vocab-term-identifier="https://credit.niso.org/contributor-roles/validation/">Validation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Formal analysis" vocab-term-identifier="https://credit.niso.org/contributor-roles/formal-analysis/">Formal analysis</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="methodology" vocab-term-identifier="https://credit.niso.org/contributor-roles/methodology/">Methodology</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="supervision" vocab-term-identifier="https://credit.niso.org/contributor-roles/supervision/">Supervision</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Data curation" vocab-term-identifier="https://credit.niso.org/contributor-roles/data-curation/">Data curation</role>
</contrib>
<contrib contrib-type="author">
<name><surname>Salazar</surname><given-names>David</given-names></name>
<xref ref-type="aff" rid="aff10"><sup>10</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/2948254/overview"/>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="resources" vocab-term-identifier="https://credit.niso.org/contributor-roles/resources/">Resources</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="software" vocab-term-identifier="https://credit.niso.org/contributor-roles/software/">Software</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; original draft" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-original-draft/">Writing &#x2013; original draft</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="visualization" vocab-term-identifier="https://credit.niso.org/contributor-roles/visualization/">Visualization</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="methodology" vocab-term-identifier="https://credit.niso.org/contributor-roles/methodology/">Methodology</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &amp; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-review-editing/">Writing &#x2013; review &amp; editing</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="validation" vocab-term-identifier="https://credit.niso.org/contributor-roles/validation/">Validation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Formal analysis" vocab-term-identifier="https://credit.niso.org/contributor-roles/formal-analysis/">Formal analysis</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="supervision" vocab-term-identifier="https://credit.niso.org/contributor-roles/supervision/">Supervision</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Data curation" vocab-term-identifier="https://credit.niso.org/contributor-roles/data-curation/">Data curation</role>
</contrib>
<contrib contrib-type="author">
<name><surname>Florez</surname><given-names>Yuliana</given-names></name>
<xref ref-type="aff" rid="aff11"><sup>11</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/2877153/overview"/>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; original draft" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-original-draft/">Writing &#x2013; original draft</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &amp; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-review-editing/">Writing &#x2013; review &amp; editing</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="supervision" vocab-term-identifier="https://credit.niso.org/contributor-roles/supervision/">Supervision</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Formal analysis" vocab-term-identifier="https://credit.niso.org/contributor-roles/formal-analysis/">Formal analysis</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="visualization" vocab-term-identifier="https://credit.niso.org/contributor-roles/visualization/">Visualization</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="methodology" vocab-term-identifier="https://credit.niso.org/contributor-roles/methodology/">Methodology</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="software" vocab-term-identifier="https://credit.niso.org/contributor-roles/software/">Software</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="validation" vocab-term-identifier="https://credit.niso.org/contributor-roles/validation/">Validation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="investigation" vocab-term-identifier="https://credit.niso.org/contributor-roles/investigation/">Investigation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Data curation" vocab-term-identifier="https://credit.niso.org/contributor-roles/data-curation/">Data curation</role>
</contrib>
<contrib contrib-type="author">
<name><surname>C&#xe1;rdenas</surname><given-names>Juan</given-names></name>
<xref ref-type="aff" rid="aff12"><sup>12</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/2947483/overview"/>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="methodology" vocab-term-identifier="https://credit.niso.org/contributor-roles/methodology/">Methodology</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="visualization" vocab-term-identifier="https://credit.niso.org/contributor-roles/visualization/">Visualization</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="investigation" vocab-term-identifier="https://credit.niso.org/contributor-roles/investigation/">Investigation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="validation" vocab-term-identifier="https://credit.niso.org/contributor-roles/validation/">Validation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="software" vocab-term-identifier="https://credit.niso.org/contributor-roles/software/">Software</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="supervision" vocab-term-identifier="https://credit.niso.org/contributor-roles/supervision/">Supervision</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Data curation" vocab-term-identifier="https://credit.niso.org/contributor-roles/data-curation/">Data curation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &amp; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-review-editing/">Writing &#x2013; review &amp; editing</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Formal analysis" vocab-term-identifier="https://credit.niso.org/contributor-roles/formal-analysis/">Formal analysis</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; original draft" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-original-draft/">Writing &#x2013; original draft</role>
</contrib>
<contrib contrib-type="author">
<name><surname>Ardila-Duarte</surname><given-names>Carlos</given-names></name>
<xref ref-type="aff" rid="aff13"><sup>13</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/3089451/overview"/>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="methodology" vocab-term-identifier="https://credit.niso.org/contributor-roles/methodology/">Methodology</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="supervision" vocab-term-identifier="https://credit.niso.org/contributor-roles/supervision/">Supervision</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &amp; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-review-editing/">Writing &#x2013; review &amp; editing</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="conceptualization" vocab-term-identifier="https://credit.niso.org/contributor-roles/conceptualization/">Conceptualization</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Data curation" vocab-term-identifier="https://credit.niso.org/contributor-roles/data-curation/">Data curation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="validation" vocab-term-identifier="https://credit.niso.org/contributor-roles/validation/">Validation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; original draft" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-original-draft/">Writing &#x2013; original draft</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Formal analysis" vocab-term-identifier="https://credit.niso.org/contributor-roles/formal-analysis/">Formal analysis</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="software" vocab-term-identifier="https://credit.niso.org/contributor-roles/software/">Software</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="visualization" vocab-term-identifier="https://credit.niso.org/contributor-roles/visualization/">Visualization</role>
</contrib>
<contrib contrib-type="author">
<name><surname>Mart&#xed;nez</surname><given-names>Juan</given-names></name>
<xref ref-type="aff" rid="aff14"><sup>14</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/2951610/overview"/>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="resources" vocab-term-identifier="https://credit.niso.org/contributor-roles/resources/">Resources</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="conceptualization" vocab-term-identifier="https://credit.niso.org/contributor-roles/conceptualization/">Conceptualization</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="visualization" vocab-term-identifier="https://credit.niso.org/contributor-roles/visualization/">Visualization</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="validation" vocab-term-identifier="https://credit.niso.org/contributor-roles/validation/">Validation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Formal analysis" vocab-term-identifier="https://credit.niso.org/contributor-roles/formal-analysis/">Formal analysis</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; original draft" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-original-draft/">Writing &#x2013; original draft</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="supervision" vocab-term-identifier="https://credit.niso.org/contributor-roles/supervision/">Supervision</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Data curation" vocab-term-identifier="https://credit.niso.org/contributor-roles/data-curation/">Data curation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &amp; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-review-editing/">Writing &#x2013; review &amp; editing</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="software" vocab-term-identifier="https://credit.niso.org/contributor-roles/software/">Software</role>
</contrib>
<contrib contrib-type="author">
<name><surname>Castellanos</surname><given-names>Cesar</given-names></name>
<xref ref-type="aff" rid="aff15"><sup>15</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/2949267/overview"/>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Data curation" vocab-term-identifier="https://credit.niso.org/contributor-roles/data-curation/">Data curation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; original draft" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-original-draft/">Writing &#x2013; original draft</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Formal analysis" vocab-term-identifier="https://credit.niso.org/contributor-roles/formal-analysis/">Formal analysis</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="software" vocab-term-identifier="https://credit.niso.org/contributor-roles/software/">Software</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="supervision" vocab-term-identifier="https://credit.niso.org/contributor-roles/supervision/">Supervision</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="validation" vocab-term-identifier="https://credit.niso.org/contributor-roles/validation/">Validation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="resources" vocab-term-identifier="https://credit.niso.org/contributor-roles/resources/">Resources</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="visualization" vocab-term-identifier="https://credit.niso.org/contributor-roles/visualization/">Visualization</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &amp; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-review-editing/">Writing &#x2013; review &amp; editing</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="investigation" vocab-term-identifier="https://credit.niso.org/contributor-roles/investigation/">Investigation</role>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name><surname>L&#xf3;pez</surname><given-names>Norman</given-names></name>
<xref ref-type="aff" rid="aff6"><sup>6</sup></xref>
<xref ref-type="aff" rid="aff11"><sup>11</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>*</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/1150398/overview"/>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Data curation" vocab-term-identifier="https://credit.niso.org/contributor-roles/data-curation/">Data curation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="supervision" vocab-term-identifier="https://credit.niso.org/contributor-roles/supervision/">Supervision</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="methodology" vocab-term-identifier="https://credit.niso.org/contributor-roles/methodology/">Methodology</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &amp; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-review-editing/">Writing &#x2013; review &amp; editing</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="software" vocab-term-identifier="https://credit.niso.org/contributor-roles/software/">Software</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; original draft" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-original-draft/">Writing &#x2013; original draft</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="investigation" vocab-term-identifier="https://credit.niso.org/contributor-roles/investigation/">Investigation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="visualization" vocab-term-identifier="https://credit.niso.org/contributor-roles/visualization/">Visualization</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Funding acquisition" vocab-term-identifier="https://credit.niso.org/contributor-roles/funding-acquisition/">Funding acquisition</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="validation" vocab-term-identifier="https://credit.niso.org/contributor-roles/validation/">Validation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Formal analysis" vocab-term-identifier="https://credit.niso.org/contributor-roles/formal-analysis/">Formal analysis</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="resources" vocab-term-identifier="https://credit.niso.org/contributor-roles/resources/">Resources</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Project-administration" vocab-term-identifier="https://credit.niso.org/contributor-roles/project-administration/">Project administration</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="conceptualization" vocab-term-identifier="https://credit.niso.org/contributor-roles/conceptualization/">Conceptualization</role>
</contrib>
</contrib-group>
<aff id="aff1"><label>1</label><institution>Departamento de Ciencias Sociales, Universidad de Los Lagos</institution>, <city>Osorno</city>,&#xa0;<country country="cl">Chile</country></aff>
<aff id="aff2"><label>2</label><institution>Consorcio Latinoamericano de Investigaci&#xf3;n (CLATI)</institution>, <city>Temuco</city>,&#xa0;<country country="cl">Chile</country></aff>
<aff id="aff3"><label>3</label><institution>Escuela de Psicolog&#xed;a, Facultad de Ciencias Sociales y Comunicaciones, Universidad Santo Tom&#xe1;s</institution>, <city>Temuco</city>,&#xa0;<country country="cl">Chile</country></aff>
<aff id="aff4"><label>4</label><institution>Departamento de Procesos Terap&#xe9;uticos, Facultad de Ciencias de la Salud, Universidad Cat&#xf3;lica de Temuco</institution>, <city>Temuco</city>,&#xa0;<country country="cl">Chile</country></aff>
<aff id="aff5"><label>5</label><institution>Universidad Nacional de Huancavelica</institution>, <city>Huancavelica</city>,&#xa0;<country country="pe">Peru</country></aff>
<aff id="aff6"><label>6</label><institution>Escuela de Kinesiolog&#xed;a, Facultad de Salud, Universidad Santo Tomas</institution>, <city>Temuco</city>,&#xa0;<country country="cl">Chile</country></aff>
<aff id="aff7"><label>7</label><institution>Universidad Nacional Intercultural de la Amazonia</institution>, <city>Pucallpa</city>,&#xa0;<country country="pe">Peru</country></aff>
<aff id="aff8"><label>8</label><institution>Departamento de Neurocirug&#xed;a, Omni Hospital</institution>, <city>Guayaquil</city>,&#xa0;<country country="ec">Ecuador</country></aff>
<aff id="aff9"><label>9</label><institution>Departamento de Ciencias Exactas, Universidad de Los Lagos</institution>, <city>Osorno</city>,&#xa0;<country country="cl">Chile</country></aff>
<aff id="aff10"><label>10</label><institution>Universidad Nacional Daniel Alcides Carri&#xf3;n</institution>, <city>Cerro de Pasco</city>,&#xa0;<country country="pe">Peru</country></aff>
<aff id="aff11"><label>11</label><institution>Departamento de Ciencias Sociales, Universidad de la Costa</institution>, <city>Barranquilla</city>,&#xa0;<country country="co">Colombia</country></aff>
<aff id="aff12"><label>12</label><institution>Universidad Nacional Aut&#xf3;noma Altoandina de Tarma</institution>, <city>Tarma</city>,&#xa0;<country country="pe">Peru</country></aff>
<aff id="aff13"><label>13</label><institution>Departamento de Ciencias B&#xe1;sicas, Universidad Metropolitana</institution>, <city>Barranquilla</city>,&#xa0;<country country="co">Colombia</country></aff>
<aff id="aff14"><label>14</label><institution>Graduate School of Education, Ana G. Mendez University</institution>, <city>San Juan</city>,&#xa0;<country country="pr">Puerto Rico</country></aff>
<aff id="aff15"><label>15</label><institution>Instituto Dominicano para el Estudio de la Salud Integral y la Psicolog&#xed;a Aplicada (IDESIP)</institution>, <city>Santo Domingo</city>,&#xa0;<country country="dm">Dominican Republic</country></aff>
<author-notes>
<corresp id="c001"><label>*</label>Correspondence: Norman L&#xf3;pez, <email xlink:href="mailto:normanlopezve@santotomas.cl">normanlopezve@santotomas.cl</email></corresp>
</author-notes>
<pub-date publication-format="electronic" date-type="pub" iso-8601-date="2025-11-19">
<day>19</day>
<month>11</month>
<year>2025</year>
</pub-date>
<pub-date publication-format="electronic" date-type="collection">
<year>2025</year>
</pub-date>
<volume>16</volume>
<elocation-id>1667612</elocation-id>
<history>
<date date-type="received">
<day>16</day>
<month>07</month>
<year>2025</year>
</date>
<date date-type="accepted">
<day>28</day>
<month>10</month>
<year>2025</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2025 Caldichoury, Morales-Asencio, Castellanos-Alvarenga, Coronado, Quispe-Ayala, Ripoll-C&#xf3;rdoba, Sald&#xed;as, Bada, Alcos-Flores, Zurita-Cueva, Duhalde-Sanhueza, Romo, Quincho-Apumayta, Salazar, Florez, C&#xe1;rdenas, Ardila-Duarte, Mart&#xed;nez, Castellanos and L&#xf3;pez.</copyright-statement>
<copyright-year>2025</copyright-year>
<copyright-holder>Caldichoury, Morales-Asencio, Castellanos-Alvarenga, Coronado, Quispe-Ayala, Ripoll-C&#xf3;rdoba, Sald&#xed;as, Bada, Alcos-Flores, Zurita-Cueva, Duhalde-Sanhueza, Romo, Quincho-Apumayta, Salazar, Florez, C&#xe1;rdenas, Ardila-Duarte, Mart&#xed;nez, Castellanos and L&#xf3;pez</copyright-holder>
<license>
<ali:license_ref start_date="2025-11-19">https://creativecommons.org/licenses/by/4.0/</ali:license_ref>
<license-p>This is an open-access article distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution License (CC BY)</ext-link>. The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</license-p>
</license>
</permissions>
<abstract>
<sec>
<title>Introduction</title>
<p>Depression is one of the leading causes of global disease burden, particularly in regions with high inequality such as Latin America and the Caribbean (LAC). The Patient Health Questionnaire-9 (PHQ-9) is one of the most widely used instruments internationally for screening depressive symptoms, although its structural validity and diagnostic comparability in LAC still require further evidence.</p>
</sec>
<sec>
<title>Objective</title>
<p>To examine the factorial structure, invariance by sex and country, internal consistency, and concurrent validity of the PHQ-9 in a multinational sample of Latin American adults.</p>
</sec>
<sec>
<title>Method</title>
<p>Data from 12,124 participants across 15 LAC countries were analyzed, collected through an online form using snowball sampling. Confirmatory factor analysis (CFA) and multigroup invariance analysis were applied, along with Omega coefficient and correlations with GAD-7 and Mini-Z.</p>
</sec>
<sec>
<title>Results</title>
<p>The PHQ-9 showed a unidimensional structure with excellent fit (CFI = .989; RMSEA = .075), adequate internal consistency (&#x3a9; = .89), and evidence of configural, metric, scalar, and strict invariance by sex and country. High correlation with GAD-7 (r = .79) and moderate correlation with Mini-Z (r = .64) supported its concurrent validity.</p>
</sec>
<sec>
<title>Conclusion</title>
<p>The PHQ-9 demonstrated robust psychometric properties and diagnostic comparability across countries and sexes in LAC. These findings reinforce its utility as a standardized and culturally adaptable tool for screening depressive symptoms in clinical and community settings in the region.</p>
</sec>
</abstract>
<kwd-group>
<kwd>PHQ-9</kwd>
<kwd>depression</kwd>
<kwd>factorial invariance</kwd>
<kwd>Latin America</kwd>
<kwd>structural validity</kwd>
<kwd>screening</kwd>
</kwd-group>
<funding-group>
<award-group id="gs1">
<funding-source id="sp1">
<institution-wrap>
<institution>Universidad de la Costa</institution>
<institution-id institution-id-type="doi" vocab="open-funder-registry" vocab-identifier="10.13039/open_funder_registry">10.13039/100031577</institution-id>
</institution-wrap>
</funding-source>
</award-group>
<funding-statement>The author(s) declare financial support was received for the research and/or publication of this article. This study was approved and funded by the Universidad de la Costa. Project reference: INV. 140-03-001-18.</funding-statement>
</funding-group>
<counts>
<fig-count count="1"/>
<table-count count="3"/>
<equation-count count="0"/>
<ref-count count="71"/>
<page-count count="10"/>
<word-count count="4699"/>
</counts>
<custom-meta-group>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Mood Disorders</meta-value>
</custom-meta>
</custom-meta-group>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<label>1</label>
<title>Introduction</title>
<p>Depression is a mental disorder characterized by a persistently sad or irritable mood, loss of interest or pleasure, decreased energy, sleep or appetite disturbances, concentration difficulties, and feelings of worthlessness or guilt, lasting at least two weeks, with a significant impact on daily functioning (<xref ref-type="bibr" rid="B1">1</xref>&#x2013;<xref ref-type="bibr" rid="B3">3</xref>).The COVID-19 pandemic exacerbated the burden of emotional disorders across all regions, with an increase in cases of major depressive disorder in the general population (<xref ref-type="bibr" rid="B4">4</xref>, <xref ref-type="bibr" rid="B5">5</xref>). In Latin America, these effects were intensified due to inequity in access to healthcare, unemployment, food insecurity, and pressure on health systems (<xref ref-type="bibr" rid="B6">6</xref>).</p>
<p>From a clinical and public health perspective, depression is associated with multiple comorbid conditions such as insomnia (<xref ref-type="bibr" rid="B7">7</xref>), anxiety (<xref ref-type="bibr" rid="B8">8</xref>), eating problems, and suicide (<xref ref-type="bibr" rid="B9">9</xref>), which increase the severity of the condition and reduce therapeutic effectiveness if not detected in a timely manner (<xref ref-type="bibr" rid="B10">10</xref>). In addition, depression may coexist with conditions such as burnout and chronic stress, especially in contexts of work overload and lack of institutional support (<xref ref-type="bibr" rid="B11">11</xref>, <xref ref-type="bibr" rid="B12">12</xref>). It also negatively impacts quality of life and life satisfaction, work performance, and overall individual functioning, becoming a key determinant of global disease burden (<xref ref-type="bibr" rid="B13">13</xref>, <xref ref-type="bibr" rid="B14">14</xref>).</p>
<p>In this context, early detection of depression is a priority in clinical, community, and epidemiological settings. Rapid screening instruments, such as the Patient Health Questionnaire-9 (PHQ-9), have proven to be effective, valid, and low-cost tools for identifying depressive symptoms in accordance with DSM-5. criterio (<xref ref-type="bibr" rid="B15">15</xref>, <xref ref-type="bibr" rid="B16">16</xref>). This questionnaire has become one of the most widely used tools globally due to its brevity, ease of administration, and usefulness in resource-limited settings (<xref ref-type="bibr" rid="B17">17</xref>, <xref ref-type="bibr" rid="B18">18</xref>).</p>
<p>In Latin America, various studies have supported the validity and reliability of the PHQ-9. In Colombia, among a university population, adequate internal consistencies were reported (&#x3b1; = 0.80; &#x3c9; = 0.81) and concurrent validity with the HADS-D (&#x3c1; = 0.64) and PHQ-2 (&#x3c1; = 0.70) (<xref ref-type="bibr" rid="B9">9</xref>). In Peru, a large-scale population study confirmed a unidimensional structure with good fit (CFI = 0.936; RMSEA = 0.089; SRMR = 0.039), high reliability (&#x3b1; = &#x3c9; = 0.87), and invariance by sex and age groups (<xref ref-type="bibr" rid="B19">19</xref>). In Argentina, high internal consistencies were observed (&#x3b1; = 0.87) and adequate diagnostic accuracy (AUC = 0.87) in primary care (<xref ref-type="bibr" rid="B20">20</xref>, <xref ref-type="bibr" rid="B21">21</xref>). In Mexico and Chile, stable performance of the PHQ-9 has been documented in the general population and clinical samples, with good internal consistency and validity in local contexts (<xref ref-type="bibr" rid="B6">6</xref>, <xref ref-type="bibr" rid="B22">22</xref>). In Puerto Rico, although two-dimensional and bifactor models were explored, the authors concluded that the most parsimonious interpretation of the scores is unidimensional, also confirming its invariance by sex (<xref ref-type="bibr" rid="B23">23</xref>). Additionally, in Spain, high internal consistency has been reported (&#x3c9; = 0.89), good sensitivity (88%) and specificity (80%), as well as factorial stability in primary care; although both unifactorial and two-dimensional models showed acceptable fit (CFI = 0.95; RMSEA = 0.08), the high correlation between factors (r = 0.86) supported the parsimony of the unidimensional model, which also demonstrated invariance by sex, age, marital status, educational level, employment status, and over time (<xref ref-type="bibr" rid="B24">24</xref>).</p>
<p>Although some studies have explored alternative models to the unifactorial structure, including two-factor structures (<xref ref-type="bibr" rid="B25">25</xref>), bifactor models in Spanish-speaking university populations (<xref ref-type="bibr" rid="B21">21</xref>), and even four-factor solutions in community samples (<xref ref-type="bibr" rid="B26">26</xref>), the accumulated evidence indicates that such configurations tend to show very high correlations between factors and low reliability in the subfactors. The most recent meta-analysis (<xref ref-type="bibr" rid="B10">10</xref>) integrated the available evidence and confirmed that, although two-factor or bifactor models may show acceptable fit, the high correlation between factors and low subfactor reliability limit their usefulness; in contrast, the unidimensional model proves to be more parsimonious and stable, consolidating itself as the most robust option for clinical practice and cross-cultural research.</p>
<p>In this regard, the present study is based on the hypothesis that the PHQ-9 assesses a predominantly unidimensional construct, allowing the total score to be interpreted as a global measure of depressive symptoms and enabling the evaluation of its metric equivalence across countries and sexes. This is particularly relevant in Latin America and the Caribbean, where studies on the factorial invariance of the PHQ-9 remain scarce (<xref ref-type="bibr" rid="B16">16</xref>, <xref ref-type="bibr" rid="B23">23</xref>). Therefore, the aim of this study was to assess the structural consistency and comparability of the PHQ-9 in a multinational sample of adults from the region, in order to provide evidence supporting its clinical and epidemiological use in diverse contexts.</p>
</sec>
<sec id="s2" sec-type="materials|methods">
<label>2</label>
<title>Materials and method</title>
<sec id="s2_1">
<label>2.1</label>
<title>Participants</title>
<p>The present study is part of a regional digital mental health monitoring strategy (<xref ref-type="bibr" rid="B27">27</xref>), coordinated across multiple countries in Latin America and the Caribbean. A non-probabilistic snowball sampling method was used, with a dissemination process structured in several stages. First, meetings were held with representatives of professional associations, educational, health, and community institutions, who were invited to participate and to disseminate the initiative within their networks. Subsequently, official invitations were sent through the human resources offices of universities, hospitals, clinics, and professional associations, accompanied by mass institutional emails. Finally, dissemination was carried out through institutional messaging groups (WhatsApp), managed by universities, hospitals, and professional associations, asking their members to share the invitation with their peers and local communities; this helped expand the coverage to new participants. This strategy combined formal and informal channels, reducing the risk of sample homogeneity and ensuring the inclusion of diverse profiles.</p>
<p>A self-administered online form was designed, available in linguistically and culturally adapted versions. The instrument included an introductory section with informed consent and guidelines to facilitate item comprehension. Dissemination was reinforced through local campaigns coordinated by technical teams previously trained in each participating country. Data collection was carried out between May 12, 2022, and November 27, 2023.</p>
<p>Initially, 14,842 participants were assessed; however, 2,718 cases were excluded for not completing the questionnaire, not accepting the informed consent, or selecting countries with low response volumes. The final sample consisted of 12,124 valid forms (54.32% women and 45.68% men), originating from Argentina (7.3%), Bolivia (6.7%), Colombia (10.3%), Chile (6.9%), Costa Rica (4.9%), El Salvador (5.7%), Ecuador (7.2%), Guatemala (4.7%), Panama (5.1%), Paraguay (5.7%), Peru (8.6%), Puerto Rico (5.8%), the Dominican Republic (6.6%), Uruguay (6.3%), and Venezuela (8.2%). The mean age was 31.14 years (SD = 18.78). The sample included professionals in health (12.5%), engineering and exact sciences (9.3%), social sciences (8.2%), legal, accounting, and administrative sciences (10.3%), education (11.4%), university students (14.2%), and individuals from the general community (34.1%). (see <xref ref-type="supplementary-material" rid="SM1"><bold>Supplementary Participant Data</bold></xref>). In all included countries, the Spanish version of the PHQ-9 was administered. In the case of Puerto Rico, although it is legally a territory of the United States, Spanish is the predominant language spoken by the population, which justifies its use in this sample.</p>
<p><xref ref-type="table" rid="T1"><bold>Table&#xa0;1</bold></xref> presents the sociodemographic distribution of the sample (N = 12,124) by country, mean age, age range, and sex. Overall, the sample reflected early and middle adulthood, with a slight female majority (54.3%).</p>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>Descriptive statistics for the PHQ-9 items.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="left">&#xed;tem</th>
<th valign="middle" align="center"><italic>M</italic></th>
<th valign="middle" align="center"><italic>SD</italic></th>
<th valign="middle" align="center">Skew</th>
<th valign="middle" align="center">Kurt.</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" align="left">1. Little interest or pleasure in doing things.</td>
<td valign="middle" align="center">1.04</td>
<td valign="middle" align="center">0.81</td>
<td valign="middle" align="center">0.58</td>
<td valign="middle" align="center">-0.01</td>
</tr>
<tr>
<td valign="middle" align="left">2. Feeling down, depressed, or hopeless.</td>
<td valign="middle" align="center">0.99</td>
<td valign="middle" align="center">0.87</td>
<td valign="middle" align="center">0.69</td>
<td valign="middle" align="center">-0.09</td>
</tr>
<tr>
<td valign="middle" align="left">3. Trouble falling or staying asleep or sleeping too much.</td>
<td valign="middle" align="center">1.32</td>
<td valign="middle" align="center">0.99</td>
<td valign="middle" align="center">0.34</td>
<td valign="middle" align="center">-0.90</td>
</tr>
<tr>
<td valign="middle" align="left">4. Feeling tired or having little energy.</td>
<td valign="middle" align="center">1.40</td>
<td valign="middle" align="center">0.91</td>
<td valign="middle" align="center">0.40</td>
<td valign="middle" align="center">-0.66</td>
</tr>
<tr>
<td valign="middle" align="left">5. Poor appetite or overeating.</td>
<td valign="middle" align="center">1.30</td>
<td valign="middle" align="center">1.00</td>
<td valign="middle" align="center">0.32</td>
<td valign="middle" align="center">-0.94</td>
</tr>
<tr>
<td valign="middle" align="left">6. Feeling bad about yourself &#x2013; or that you are a failure or have let yourself or your family down.</td>
<td valign="middle" align="center">0.80</td>
<td valign="middle" align="center">0.93</td>
<td valign="middle" align="center">0.97</td>
<td valign="middle" align="center">-0.02</td>
</tr>
<tr>
<td valign="middle" align="left">7. Trouble concentrating on things, such as reading the newspaper or watching television.</td>
<td valign="middle" align="center">0.96</td>
<td valign="middle" align="center">0.88</td>
<td valign="middle" align="center">0.71</td>
<td valign="middle" align="center">-0.16</td>
</tr>
<tr>
<td valign="middle" align="left">8. Moving or speaking so slowly that other people could have noticed. Or the opposite &#x2013; being so fidgety or restless that you have been moving around a lot more than usual.</td>
<td valign="middle" align="center">0.68</td>
<td valign="middle" align="center">0.82</td>
<td valign="middle" align="center">1.12</td>
<td valign="middle" align="center">0.63</td>
</tr>
<tr>
<td valign="middle" align="left">9. Thoughts that you would be better off dead or of hurting yourself in some way</td>
<td valign="middle" align="center">0.28</td>
<td valign="middle" align="center">0.63</td>
<td valign="middle" align="center">2.51</td>
<td valign="middle" align="center">6.20</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec id="s2_2">
<label>2.2</label>
<title>Instrument</title>
<p>The Patient Health Questionnaire-9 (PHQ-9) was used, a self-report test designed to assess the presence and severity of depressive symptoms over the past two weeks. This instrument was developed by Spitzer et&#xa0;al. (<xref ref-type="bibr" rid="B28">28</xref>), as part of the Primary Care Evaluation of Mental Disorders (PRIME-MD). It consists of 9 items based on the DSM-5 diagnostic criteria for major depressive disorder, scored on a Likert scale from 0 (&#x201c;not at all&#x201d;) to 3 (&#x201c;nearly every day&#x201d;), with a total score ranging from 0 to 27. A cutoff score of &#x2265;10 has demonstrated sensitivity and specificity greater than 80% in various studies. The PHQ-9 is a brief, sensitive, and easy-to-administer tool, with strong international empirical support confirming its unidimensionality, reliability, and cross-cultural equivalence across multiple countries and languages (<xref ref-type="bibr" rid="B29">29</xref>, <xref ref-type="bibr" rid="B30">30</xref>). In this study, the Spanish version adapted for the general Spanish-speaking population was used (<xref ref-type="bibr" rid="B19">19</xref>, <xref ref-type="bibr" rid="B23">23</xref>).</p>
<p>Additionally, for the analysis of concurrent validity, the Generalized Anxiety Disorder-7 (GAD-7) was used; it is a 7-item test that assesses generalized anxiety symptoms over the past two weeks. Each item is rated on a scale from 0 (&#x201c;not at all&#x201d;) to 3 (&#x201c;nearly every day&#x201d;), with a total score ranging from 0 to 21. A score of &#x2265;10 is considered indicative of moderate to severe anxiety. The version used was validated in the general Spanish-speaking population by our group (L&#xf3;pez, N, et&#xa0;al., 2025; L&#xf3;pez, N, et&#xa0;al., 2025) (<xref ref-type="bibr" rid="B31">31</xref>) showing adequate validity and usefulness for screening in community settings.</p>
<p>Finally, Mini-Z 2.0 was used, a 10-item scale designed to assess burnout symptoms and associated psychosocial factors, including job satisfaction, workload, perceived control, stress, and alignment with institutional values. Item 1 specifically measures emotional exhaustion and is considered the primary indicator of burnout, with scores &#x2265;3 suggesting clinical risk. Items are answered using either Likert or dichotomous formats, depending on their content. The version used was recently adapted and validated in a Spanish-speaking population (<xref ref-type="bibr" rid="B33">33</xref>). This instrument was applied only to participants who reported being actively employed in the online form; this condition was later randomly verified through confirmation emails. The purpose of its inclusion in this study was to examine the concurrent validity of the PHQ-9 in relation to burnout, a related but distinct construct from depression; in order to verify that the expected associations were maintained without compromising the specificity of the screening.</p>
</sec>
<sec id="s2_3">
<label>2.3</label>
<title>Data analysis</title>
<p>Data were digitized through the use of forms in a Google Sheets spreadsheet. The database was downloaded as an.xlsx file and imported into R software version 4.0.2, within the RStudio programming environment version 1.3.595 (<xref ref-type="bibr" rid="B34">34</xref>). The openxlsx package (<xref ref-type="bibr" rid="B35">35</xref>) was used for data import, tidyverse (<xref ref-type="bibr" rid="B36">36</xref>) and psych (<xref ref-type="bibr" rid="B37">37</xref>) for data preparation and analysis; lavaan (<xref ref-type="bibr" rid="B38">38</xref>), semPlot (<xref ref-type="bibr" rid="B39">39</xref>), and sem Tools (<xref ref-type="bibr" rid="B40">40</xref>) for confirmatory factor analysis (CFA) and measurement invariance; MBESS (<xref ref-type="bibr" rid="B41">41</xref>) for the calculation of the Omega coefficient and its confidence intervals, and WRS2 (<xref ref-type="bibr" rid="B42">42</xref>) for the computation of the winsorized correlation coefficient (tr. = 0.10). For the CFA, the robust Weighted Least Squares Mean and Variance adjusted (WLSMV) method was used as the estimator, and unidimensional structures were evaluated for both instruments. The following criteria were considered for assessing model fit: values &#x2265;.90 and &#x2265;.95 for the CFI and TLI were interpreted as acceptable and good fit, respectively; values &#x2264;.08 and &#x2264;.05 for the RMSEA as acceptable and good fit, respectively; and for the SRMR, values &#x2264;.08 and &#x2264;.06 were considered good and ideal fit, respectively. For the evaluation of measurement invariance, the procedure developed by Wu &amp; Estabrook (<xref ref-type="bibr" rid="B43">43</xref>), was applied. Invariance assessment considered a sample size &gt;300 and potential non-invariance was established when &#x394;CFI &lt;.010, &#x394;TLI &lt;.010, &#x394;SRMR &lt;.030 y &#x394;RMSEA &lt;.015 (<xref ref-type="bibr" rid="B44">44</xref>&#x2013;<xref ref-type="bibr" rid="B46">46</xref>).</p>
</sec>
<sec id="s2_4">
<label>2.4</label>
<title>Ethical considerations</title>
<p>The study was conducted in accordance with the ethical principles established by the relevant institutional and national committees, as well as the guidelines of the Declaration of Helsinki (1975), updated in 2008. All participants provided informed consent through an online form prior to the start of the study. Upon completion of their participation, each received an individual report with their results, accompanied by relevant psychological and clinical recommendations. The research protocol was duly approved by the Ethics Committee of the Universidad de La Costa, under file No. 173 dated May 27, 2024, and registered under code INV.140-03-001-18.</p>
</sec>
</sec>
<sec id="s3" sec-type="results">
<label>3</label>
<title>Results</title>
<p><xref ref-type="table" rid="T1"><bold>Table&#xa0;1</bold></xref> shows the descriptive statistics of the PHQ-9 items. Item 9 has the lowest mean value, while item 4 has the highest. Regarding skewness and kurtosis values, the vast majority are close to 0, with the exception of item 9, which presents the highest skewness and kurtosis values. Considering the content of this item, which reflects thoughts of self-harm, the high positive skewness and leptokurtic kurtosis indicate that the vast majority of respondents fall into the &#x201c;not at all&#x201d; category.</p>
<p>Confirmatory factor analysis was then conducted to examine the internal structure of the test. The models analyzed and their fit indices are presented in <xref ref-type="table" rid="T2"><bold>Table&#xa0;2</bold></xref>. For the PHQ-9, the unidimensional structure without correlated errors (Model 0) showed adequate fit indices according to the CFI, TLI, and SRMR; although the RMSEA presented a value close to the threshold of poor fit. Given the content overlap among somatic items (sleep&#x2013;energy&#x2013;appetite) and the modification indices, a minimal set of residual covariances was allowed (<xref ref-type="bibr" rid="B3">3</xref>, <xref ref-type="bibr" rid="B4">4</xref>, <xref ref-type="bibr" rid="B5">5</xref>). This decision is methodologically acceptable when local dependence is documented and there is theoretical justification (<xref ref-type="bibr" rid="B47">47</xref>, <xref ref-type="bibr" rid="B48">48</xref>). Comparability by sex and country was assessed through multigroup CFA.</p>
<table-wrap id="T2" position="float">
<label>Table&#xa0;2</label>
<caption>
<p>Analyzed models and goodness-of-fit &#xed;ndices.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="center">Modelos</th>
<th valign="middle" align="center">&#x3c7;&#xb2;</th>
<th valign="middle" align="center">gl</th>
<th valign="middle" align="center">CFI</th>
<th valign="middle" align="center">TLI</th>
<th valign="middle" align="center">RMSEA</th>
<th valign="middle" align="center">SRMR</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" align="left">Modelo 0</td>
<td valign="middle" align="center">42,822.39</td>
<td valign="middle" align="center">36</td>
<td valign="middle" align="center">.978</td>
<td valign="middle" align="center">.971</td>
<td valign="middle" align="center">.098</td>
<td valign="middle" align="center">.047</td>
</tr>
<tr>
<td valign="middle" align="left">Model with covariance of error items: 4 and 5</td>
<td valign="middle" align="center">42,350.15</td>
<td valign="middle" align="center">35</td>
<td valign="middle" align="center">.982</td>
<td valign="middle" align="center">.976</td>
<td valign="middle" align="center">.090</td>
<td valign="middle" align="center">.043</td>
</tr>
<tr>
<td valign="middle" align="left">Model with covariance of error items: 4 and 5, 3 and 4</td>
<td valign="middle" align="center">41,975.62</td>
<td valign="middle" align="center">34</td>
<td valign="middle" align="center">.986</td>
<td valign="middle" align="center">.980</td>
<td valign="middle" align="center">.082</td>
<td valign="middle" align="center">.039</td>
</tr>
<tr>
<td valign="middle" align="left">Model with covariance of error items: 4 and 5, 3 and 4, 3 and 5</td>
<td valign="middle" align="center">41,650.48</td>
<td valign="middle" align="center">33</td>
<td valign="middle" align="center">.989</td>
<td valign="middle" align="center">.983</td>
<td valign="middle" align="center">.075</td>
<td valign="middle" align="center">.035</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>CFI, Comparative Fit Index; TLI, Tucker-Lewis Index; RMSEA, Root Mean Square Error of Approximation; SRMR, Standardized Root Mean Square Residual.</p></fn>
</table-wrap-foot>
</table-wrap>
<p><xref ref-type="fig" rid="f1"><bold>Figure&#xa0;1</bold></xref> presents the factor loadings of the model that showed the best fit for the PHQ-9. The factor loadings were greater than.68, and the values of the correlated errors ranged from.23 to.37.</p>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>Factor loadings and correlated errors of the PHQ-9.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fpsyt-16-1667612-g001.tif">
<alt-text content-type="machine-generated">Diagram displaying a path model for PHQ-9, showing nine items linked from a central oval labeled &#x201c;PHQ-9&#x201d; with various coefficients. Item correlations are represented with arrows and respective values, such as 0.80 for Item 1, 0.85 for Item 2, and so on. Arrows between Item 3 and Item 4 show additional correlations, including values 0.32, 0.23, and 0.37. Each item ends with an oval containing a number indicating factor loadings.</alt-text>
</graphic></fig>
<p>In addition, the equivalence of the PHQ-9 factor structure was evaluated by sex and country. The results are presented in <xref ref-type="table" rid="T3"><bold>Table&#xa0;3</bold></xref>. In the measurement invariance analyses of the PHQ-9 factor structure, the fit indices ranged from good to adequate across all levels examined (configural, threshold, metric, scalar, and strict). Furthermore, the differences between the fit indices were below the threshold established in the data analysis section, indicating that the factor structure of the instrument demonstrates measurement invariance and is equivalent for both groups (men and women). The same applies when using country as the comparison variable. The structure (configural), thresholds, factor loadings (metric), intercepts (scalar), and residuals (strict) are equivalent across groups.</p>
<table-wrap id="T3" position="float">
<label>Table&#xa0;3</label>
<caption>
<p>Measurement invariance by sex and country.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="center"/>
<th valign="middle" align="center">Model</th>
<th valign="middle" align="center">X<sup>2</sup></th>
<th valign="middle" align="center">Gl</th>
<th valign="middle" align="center">CFI</th>
<th valign="middle" align="center">TLI</th>
<th valign="middle" align="center">RMSEA</th>
<th valign="middle" align="center">SRMR</th>
<th valign="middle" align="center">&#x394;CFI</th>
<th valign="middle" align="center">&#x394;TLI</th>
<th valign="middle" align="center">&#x394;RMSEA</th>
<th valign="middle" align="center">&#x394;SRMR</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" rowspan="12" align="center" style="background-color:#7f7f7f">PHQ-9</td>
<th valign="middle" colspan="11" align="left">Sex</th>
</tr>
<tr>
<td valign="middle" align="left">Configural</td>
<td valign="middle" align="center">538.029</td>
<td valign="middle" align="center">48</td>
<td valign="middle" align="center">.989</td>
<td valign="middle" align="center">.983</td>
<td valign="middle" align="center">.076</td>
<td valign="middle" align="center">.037</td>
<td valign="middle" align="center">&#x2013;</td>
<td valign="middle" align="center">&#x2013;</td>
<td valign="middle" align="center">&#x2013;</td>
<td valign="middle" align="center">&#x2013;</td>
</tr>
<tr>
<td valign="middle" align="left">Threshold</td>
<td valign="middle" align="center">586.372</td>
<td valign="middle" align="center">57</td>
<td valign="middle" align="center">.988</td>
<td valign="middle" align="center">.985</td>
<td valign="middle" align="center">.072</td>
<td valign="middle" align="center">.037</td>
<td valign="middle" align="center">-.001</td>
<td valign="middle" align="center">.002</td>
<td valign="middle" align="center">-.003</td>
<td valign="middle" align="center">.000</td>
</tr>
<tr>
<td valign="middle" align="left">Metric</td>
<td valign="middle" align="center">559.509</td>
<td valign="middle" align="center">65</td>
<td valign="middle" align="center">.989</td>
<td valign="middle" align="center">.987</td>
<td valign="middle" align="center">.065</td>
<td valign="middle" align="center">.037</td>
<td valign="middle" align="center">.001</td>
<td valign="middle" align="center">.003</td>
<td valign="middle" align="center">-.007</td>
<td valign="middle" align="center">.000</td>
</tr>
<tr>
<td valign="middle" align="left">Scalar</td>
<td valign="middle" align="center">540.200</td>
<td valign="middle" align="center">73</td>
<td valign="middle" align="center">.989</td>
<td valign="middle" align="center">.989</td>
<td valign="middle" align="center">.060</td>
<td valign="middle" align="center">.037</td>
<td valign="middle" align="center">.001</td>
<td valign="middle" align="center">.002</td>
<td valign="middle" align="center">-.005</td>
<td valign="middle" align="center">.000</td>
</tr>
<tr>
<td valign="middle" align="left">Strict</td>
<td valign="middle" align="center">561.721</td>
<td valign="middle" align="center">82</td>
<td valign="middle" align="center">.989</td>
<td valign="middle" align="center">.990</td>
<td valign="middle" align="center">.057</td>
<td valign="middle" align="center">.039</td>
<td valign="middle" align="center">.000</td>
<td valign="middle" align="center">.001</td>
<td valign="middle" align="center">-.003</td>
<td valign="middle" align="center">.002</td>
</tr>
<tr>
<th valign="middle" colspan="11" align="left">Country</th>
</tr>
<tr>
<td valign="middle" align="left">Configural</td>
<td valign="middle" align="center">647.417</td>
<td valign="middle" align="center">144</td>
<td valign="middle" align="center">.989</td>
<td valign="middle" align="center">.983</td>
<td valign="middle" align="center">.077</td>
<td valign="middle" align="center">.041</td>
<td valign="middle" align="center">&#x2013;</td>
<td valign="middle" align="center">&#x2013;</td>
<td valign="middle" align="center">&#x2013;</td>
<td valign="middle" align="center">&#x2013;</td>
</tr>
<tr>
<td valign="middle" align="left">Threshold</td>
<td valign="middle" align="center">722.529</td>
<td valign="middle" align="center">189</td>
<td valign="middle" align="center">.988</td>
<td valign="middle" align="center">.986</td>
<td valign="middle" align="center">.069</td>
<td valign="middle" align="center">.041</td>
<td valign="middle" align="center">-.001</td>
<td valign="middle" align="center">.003</td>
<td valign="middle" align="center">-.008</td>
<td valign="middle" align="center">.000</td>
</tr>
<tr>
<td valign="middle" align="left">Metric</td>
<td valign="middle" align="center">685.194</td>
<td valign="middle" align="center">229</td>
<td valign="middle" align="center">.990</td>
<td valign="middle" align="center">.990</td>
<td valign="middle" align="center">.058</td>
<td valign="middle" align="center">.041</td>
<td valign="middle" align="center">.002</td>
<td valign="middle" align="center">.004</td>
<td valign="middle" align="center">-.011</td>
<td valign="middle" align="center">.001</td>
</tr>
<tr>
<td valign="middle" align="left">Scalar</td>
<td valign="middle" align="center">719.451</td>
<td valign="middle" align="center">269</td>
<td valign="middle" align="center">.990</td>
<td valign="middle" align="center">.992</td>
<td valign="middle" align="center">.053</td>
<td valign="middle" align="center">.042</td>
<td valign="middle" align="center">.000</td>
<td valign="middle" align="center">.002</td>
<td valign="middle" align="center">-.005</td>
<td valign="middle" align="center">.001</td>
</tr>
<tr>
<td valign="middle" align="left">Strict</td>
<td valign="middle" align="center">803.723</td>
<td valign="middle" align="center">314</td>
<td valign="middle" align="center">.989</td>
<td valign="middle" align="center">.992</td>
<td valign="middle" align="center">.051</td>
<td valign="middle" align="center">.048</td>
<td valign="middle" align="center">-.001</td>
<td valign="middle" align="center">.001</td>
<td valign="middle" align="center">.002</td>
<td valign="middle" align="center">.006</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>Concurrent validity analysis was conducted by correlating the PHQ-9 with two measures related to depressive symptomatology: occupational burnout, assessed through the Mini-Z, and generalized anxiety symptoms, measured with the GAD-7. To interpret the correlations, the following thresholds were considered: r = .20 as weak, r = .50 as moderate, and.50&#x2013;.80 as high (<xref ref-type="bibr" rid="B49">49</xref>). The results show a high positive correlation between the PHQ-9 and the GAD-7 (r = 0.792, p &lt; 0.01), which supports that both instruments measure related but distinguishable constructs, as anxiety and depression often present comorbidly. Likewise, a high correlation was observed between the PHQ-9 and the Mini-Z (r = 0.635, p &lt; 0.01), suggesting that high levels of occupational burnout are related to higher levels of depressive symptoms. (see <xref ref-type="supplementary-material" rid="SM1"><bold>Supplementary Data 3</bold></xref>: Correlation Matrix).</p>
<p>Finally, McDonald&#x2019;s Omega coefficient was used to assess the internal consistency of the instrument, yielding a value of 0.89, which indicates an adequate level of reliability.</p>
</sec>
<sec id="s4" sec-type="discussion">
<label>4</label>
<title>Discussion</title>
<p>The findings of this study strengthen the psychometric evidence supporting the PHQ-9 as a clinically valid, robust, and culturally adaptable tool for assessing depressive symptoms across a broad sample of countries in Latin America and the Caribbean. Consistent with previous global research (<xref ref-type="bibr" rid="B50">50</xref>&#x2013;<xref ref-type="bibr" rid="B52">52</xref>), our results confirm a unidimensional structure of the instrument, aligned with DSM-5 criteria. This configuration enables a concise and effective evaluation of depressive symptomatology without compromising diagnostic sensitivity.</p>
<p>The factorial stability of the unidimensional PHQ-9 model across the 15 included countries is particularly noteworthy. Despite cultural, linguistic, and socioeconomic differences among these contexts, the instrument demonstrated excellent fit, supporting its structural robustness and comparative utility across countries. This finding is consistent with multicultural studies that have consistently reported a predominant unidimensional structure (<xref ref-type="bibr" rid="B6">6</xref>, <xref ref-type="bibr" rid="B21">21</xref>). However, some research has proposed alternative models with bifactorial or bidimensional configurations (<xref ref-type="bibr" rid="B23">23</xref>, <xref ref-type="bibr" rid="B53">53</xref>). Although these approaches aim to capture structural variations in specific contexts, their results present relevant limitations.</p>
<p>In the study by Costantini et&#xa0;al. (<xref ref-type="bibr" rid="B53">53</xref>), the factor loadings associated with the specific factors were weak and inconsistent, which reduced the interpretability of the bifactor model. Similarly, Rosario-Hern&#xe1;ndez et&#xa0;al. (<xref ref-type="bibr" rid="B23">23</xref>) identified an acceptable fit for the two-dimensional model in Puerto Rican workers; however, the low loadings on the subfactors and the risk of overfitting limited its applicability, partly due to the reduced sociodemographic diversity of the sample. Other studies have also explored alternative models with heterogeneous results. Yu et&#xa0;al. (<xref ref-type="bibr" rid="B54">54</xref>) reported marginal fit for the unidimensional model (RMSEA = 0.122), which partially improved when allowing for error covariances; whereas Doi et&#xa0;al. (<xref ref-type="bibr" rid="B55">55</xref>), found that the bifactor model achieved superior fit indices (CFI = 0.980; RMSEA = 0.083) compared to the unidimensional model; although the subfactors showed weak loadings and the sample was recruited online without clinical diagnostic verification.</p>
<p>In contrast, our results consistently supported the unidimensional structure, reinforcing its practical utility for screening, without ruling out that alternative models may provide complementary information in specific contexts. Unlike the aforementioned studies, our work was based on a large and heterogeneous sample from Latin America and the Caribbean, which allowed us to confirm a stable unidimensional structure, with excellent fit and adequate cross-cultural validity. These findings are consistent with the most recent meta-analysis (<xref ref-type="bibr" rid="B10">10</xref>), which integrated evidence from 40 countries and demonstrated that, although bifactor or two-dimensional models may show statistically acceptable fit, the high correlations between factors and the low reliability of subfactors limit their practical usefulness.</p>
<p>Moreover, previous evidence indicates that the instrument with a unidimensional structure has demonstrated invariance across sociodemographic variables such as age, sex, educational level, and socioeconomic status (<xref ref-type="bibr" rid="B19">19</xref>). Therefore, the accumulated evidence supports the parsimony, stability, and invariance of the unidimensional model, confirming that the PHQ-9 should be interpreted primarily as a global measure of depressive symptoms. Thus, the alignment between our findings and the strongest international evidence helps close the conceptual debate, consolidating the unifactorial model as the most robust solution for research and screening in Latin America and the Caribbean.</p>
<p>It is worth noting that, like other studies using non-probabilistic sampling, our work is subject to the limitation of selection bias. However, unlike those investigations, the factorial structure and multigroup invariance were empirically evaluated using the dataset itself, which provides additional evidence of structural stability and comparability across countries and sexes. This approach partially mitigates concerns about the influence of such bias on the main results.</p>
<p>On the other hand, the high reliability coefficients observed both at the global level and within country and sex subgroups support the internal consistency of the PHQ-9 in LAC. These values exceed international standards established for brief screening scales (<xref ref-type="bibr" rid="B25">25</xref>, <xref ref-type="bibr" rid="B56">56</xref>) and are consistent with studies conducted in various countries, including those in Asia, Europe, and the Americas (<xref ref-type="bibr" rid="B10">10</xref>, <xref ref-type="bibr" rid="B14">14</xref>, <xref ref-type="bibr" rid="B57">57</xref>, <xref ref-type="bibr" rid="B58">58</xref>), The consistency of these results supports the psychometric stability of the instrument across diverse sociocultural contexts.</p>
<p>On the other hand, the multigroup invariance analysis represents a significant contribution. The results show that the PHQ-9 meets the criteria for configural, metric, and scalar invariance by both gender and country. These levels of invariance, which are not always achieved in comparative studies (<xref ref-type="bibr" rid="B59">59</xref>), allow for valid comparisons between groups and support its use in multicenter research. The ability to assess depressive symptoms equivalently across diverse populations is essential for advancing global mental health research and for the development of evidence-based public policies.</p>
<p>Compared to these findings, international evidence on the cultural invariance of the PHQ-9 remains limited in many regions. In Africa, for example (<xref ref-type="bibr" rid="B60">60</xref>),, found configural and metric invariance across samples from South Africa, Ghana, and Kenya, supporting its cross-cultural equivalence. Similarly, in rural areas of Asia (<xref ref-type="bibr" rid="B61">61</xref>),, reported a stable factor structure and good internal consistency in impoverished populations in India. In Europe (<xref ref-type="bibr" rid="B24">24</xref>),, documented invariance by age, sex, and educational level in a Spanish population.</p>
<p>These findings reinforce the need for culturally validated instruments in regions such as Latin America and the Caribbean, where mental health inequities and limited resource availability hinder access to timely diagnostic evaluations (<xref ref-type="bibr" rid="B22">22</xref>, <xref ref-type="bibr" rid="B62">62</xref>). In this context, the PHQ-9 stands out as a useful tool due to its brevity, reliability, and ease of use-even in high-demand services with limited technical capacity. Its implementation is feasible in primary care, community programs, schools, correctional facilities, and public health campaigns, and it is particularly relevant for vulnerable populations such as migrants, individuals with chronic illnesses, workers exposed to stress, and rural communities, where early diagnosis and preventive interventions are a priority (<xref ref-type="bibr" rid="B63">63</xref>&#x2013;<xref ref-type="bibr" rid="B65">65</xref>).</p>
<p>Beyond its clinical applicability, the confirmation of PHQ-9 invariance supports its usefulness for multicenter, longitudinal, and clinical studies in the region. This finding aligns with international evidence on its cross-cultural validity (<xref ref-type="bibr" rid="B51">51</xref>, <xref ref-type="bibr" rid="B59">59</xref>) and is complemented by studies in Indigenous populations of Peru and Bolivia, where it has demonstrated strong properties in intercultural contexts (<xref ref-type="bibr" rid="B65">65</xref>, <xref ref-type="bibr" rid="B66">66</xref>). The present work, along with previous research conducted by our team in clinical, general, and Indigenous samples (<xref ref-type="bibr" rid="B32">32</xref>, <xref ref-type="bibr" rid="B67">67</xref>, <xref ref-type="bibr" rid="B68">68</xref>), contributes to strengthening a regional diagnostic validation agenda aimed at mental health equity.</p>
<p>Finally, the results show that the PHQ-9 demonstrates concurrent validity with other scales measuring constructs related to depressive symptomatology, such as anxiety and occupational burnout. Its strong correlation with the GAD-7 replicates previous findings in multicultural contexts, which have documented consistent associations between depressive and anxious symptoms (<xref ref-type="bibr" rid="B69">69</xref>, <xref ref-type="bibr" rid="B70">70</xref>). Complementarily, its moderate correlation with the Mini-Z supports its utility in identifying psychosocial distress in the workplace. In a study involving intensive care unit staff, Jackson et&#xa0;al. (<xref ref-type="bibr" rid="B71">71</xref>) reported that higher PHQ-9 scores were significantly associated with elevated levels of burnout (&#x3b2; = &#x2013;0.32), confirming its sensitivity to occupational stress. Taken together, these findings reinforce the value of the PHQ-9 as a reliable tool for comprehensive mental health screening in clinical and workplace settings.</p>
<p>This study presents some limitations that should be considered when interpreting the findings. First, although participants from fifteen LAC countries were included, the sample is not representative of the entire region due to the non-probabilistic snowball sampling method. This limits the generalizability of the results to national or underrepresented rural populations. Nevertheless, the geographic breadth and sociodemographic heterogeneity of the sample provide a robust framework for regional interpretations. Likewise, the use of digital self-report sampling may have biased the sample toward individuals with greater technological access, higher educational levels, urban residence, and recruitment channels that may have varied between countries. This type of selection bias has also been noted in previous studies, reinforcing the need to interpret it as a shared limitation in the literature. While these characteristics limit population representativeness, the relative homogeneity of the sample, particularly regarding educational level and language proficiency, may have contributed to the internal consistency and invariance observed. Therefore, the diversity achieved and the robustness of the findings should be interpreted as evidence of internal validity within this sample, and their generalization to broader or less educated populations should be made with caution.</p>
<p>Second, the cross-sectional design prevents establishing causal relationships and assessing the temporal stability of the PHQ-9 or its sensitivity to change. These limitations could be addressed through longitudinal studies that examine its structural consistency and responsiveness to interventions. Additionally, the use of self-report measures may introduce biases, such as social desirability or comprehension difficulties, especially in contexts with low health literacy. Nevertheless, the brief format and accessible language of the PHQ-9 help mitigate these risks. Likewise, no formal diagnostic verification through clinical interviews was included, as the main objective was to assess the metric equivalence of the PHQ-9 across different countries and genders. The use of standardized self-reports such as the PHQ-9, which has been widely validated in population-based and cross-cultural studies, is an accepted strategy in this type of research. However, future studies should incorporate structured diagnostic interviews to complement self-reports and strengthen the clinical validity of the findings.</p>
<p>Third, although invariance by sex and country was confirmed, other dimensions of cultural diversity such as Indigenous populations, people of African descent, migrants, or individuals with low educational attainment were not explored. These groups require specific studies to assess the psychometric and cultural equivalence of the instrument.</p>
<p>Future research should incorporate qualitative or mixed-method approaches to explore the subjective meaning of the items, especially in contexts where somatic expressions of emotional distress are predominant. It is also essential to examine the instrument&#x2019;s performance in various clinical settings, such as primary care, prisons, rural communities, and populations with chronic illnesses.</p>
<p>The present study provides robust evidence on the structural validity, internal consistency, concurrent validity, and factorial invariance of the PHQ-9 in Latin America and the Caribbean. The results confirm a unidimensional structure with excellent fit, high reliability, and equivalence by sex and country, supporting its use as a comparative instrument in multicenter and transnational contexts. These findings consolidate the PHQ-9 as a psychometrically sound and culturally adaptable tool for assessing depressive symptoms in diverse populations across the region.</p>
</sec>
</body>
<back>
<sec id="s5" sec-type="data-availability">
<title>Data availability statement</title>
<p>The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.</p></sec>
<sec id="s6" sec-type="ethics-statement">
<title>Ethics statement</title>
<p>The research protocol was duly approved by the Ethics Committee of the Universidad de La Costa, under file number 173 dated May 27, 2024, and registered with code INV.140-03-001-18. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.</p></sec>
<sec id="s7" sec-type="author-contributions">
<title>Author contributions</title>
<p>NC: Methodology, Investigation, Software, Visualization, Conceptualization, Resources, Writing &#x2013; review &amp; editing, Project administration, Writing &#x2013; original draft, Funding acquisition, Formal Analysis. BM-A: Project administration, Validation, Formal Analysis, Writing &#x2013; review &amp; editing, Supervision, Data curation, Methodology, Conceptualization, Writing &#x2013; original draft, Software, Investigation. LC-A: Validation, Supervision, Data curation, Writing &#x2013; review &amp; editing, Writing &#x2013; original draft, Methodology, Software, Visualization, Formal Analysis, Investigation. J-CC: Supervision, Writing &#x2013; original draft, Writing &#x2013; review &amp; editing, Software, Formal Analysis, Validation, Data curation, Resources, Visualization, Methodology. CQ-A: Visualization, Formal Analysis, Validation, Data curation, Resources, Supervision, Software, Writing &#x2013; review &amp; editing, Methodology, Writing &#x2013; original draft. DR-C: Visualization, Investigation, Validation, Software, Writing &#x2013; review &amp; editing, Formal Analysis, Supervision, Writing &#x2013; original draft, Methodology, Data curation. CS: Conceptualization, Resources, Visualization, Investigation, Writing &#x2013; original draft, Methodology, Writing &#x2013; review &amp; editing, Validation, Formal Analysis, Data curation. WB: Validation, Data curation, Resources, Supervision, Writing &#x2013; original draft, Writing &#x2013; review &amp; editing, Software, Visualization, Investigation, Formal Analysis. KA-F: Formal Analysis, Validation, Supervision, Data curation, Software, Writing &#x2013; original draft, Investigation, Writing &#x2013; review &amp; editing, Resources, Visualization. BZ-C: Investigation, Visualization, Validation, Supervision, Formal Analysis, Writing &#x2013; original draft, Writing &#x2013; review &amp; editing, Methodology, Software, Data curation. RD-S: Writing &#x2013; review &amp; editing, Software, Investigation, Writing &#x2013; original draft, Supervision, Resources, Visualization, Data curation, Formal Analysis, Validation. CR: Writing &#x2013; original draft, Visualization, Formal Analysis, Software, Validation, Supervision, Methodology, Writing &#x2013; review &amp; editing, Data curation, Investigation. RQ-A: Software, Writing &#x2013; original draft, Writing &#x2013; review &amp; editing, Investigation, Visualization, Validation, Formal Analysis, Methodology, Supervision, Data curation. DS: Resources, Software, Writing &#x2013; original draft, Visualization, Methodology, Writing &#x2013; review &amp; editing, Validation, Formal Analysis, Supervision, Data curation. YF: Writing &#x2013; original draft, Writing &#x2013; review &amp; editing, Supervision, Formal Analysis, Visualization, Methodology, Software, Validation, Investigation, Data curation. JC: Methodology, Visualization, Investigation, Validation, Software, Supervision, Data curation, Writing &#x2013; review &amp; editing, Formal Analysis, Writing &#x2013; original draft. CA-D: Methodology, Supervision, Writing &#x2013; review &amp; editing, Conceptualization, Data curation, Validation, Writing &#x2013; original draft, Formal Analysis, Software, Visualization. JM: Resources, Conceptualization, Visualization, Validation, Formal Analysis, Writing &#x2013; original draft, Supervision, Data curation, Writing &#x2013; review &amp; editing, Software. CC: Data curation, Writing &#x2013; original draft, Formal Analysis, Software, Supervision, Validation, Resources, Visualization, Writing &#x2013; review &amp; editing, Investigation. NL: Data curation, Supervision, Methodology, Writing &#x2013; review &amp; editing, Software, Writing &#x2013; original draft, Investigation, Visualization, Funding acquisition, Validation, Formal Analysis, Resources, Project administration, Conceptualization.</p></sec>
<sec id="s9" sec-type="COI-statement">
<title>Conflict of interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p></sec>
<sec id="s10" sec-type="ai-statement">
<title>Generative AI statement</title>
<p>The author(s) declare that no Generative AI was used in the creation of this manuscript.</p>
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<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p></sec>
<sec id="s12" sec-type="supplementary-material">
<title>Supplementary material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fpsyt.2025.1667612/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fpsyt.2025.1667612/full#supplementary-material</ext-link></p>
<supplementary-material xlink:href="DataSheet1.docx" id="SM1" mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document"><label>Supplementary Table&#xa0;1</label>
<caption>
<p>Demographic information of the participants.</p>
</caption></supplementary-material>
<supplementary-material xlink:href="DataSheet1.docx" id="SM2" mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document"><label>Supplementary Table&#xa0;2</label>
<caption>
<p>Occupational distribution of participants by country.</p>
</caption></supplementary-material>
<supplementary-material xlink:href="DataSheet1.docx" id="SM3" mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document"><label>Supplementary Table&#xa0;3</label>
<caption>
<p>Partial correlations of the PHQ-9 with Mini-Z by country.</p>
</caption></supplementary-material></sec>
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