<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Traumatic Brain Injury | ISSUES | The Ohio State University</title><link>https://issues-osu.github.io/ISSUESlab/tag/traumatic-brain-injury/</link><atom:link href="https://issues-osu.github.io/ISSUESlab/tag/traumatic-brain-injury/index.xml" rel="self" type="application/rss+xml"/><description>Traumatic Brain Injury</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Mon, 24 Aug 2026 00:00:00 +0000</lastBuildDate><image><url>https://issues-osu.github.io/ISSUESlab/media/logo_hu2fedd529b9d9d7008e9f6968cd645fa1_199187_300x300_fit_lanczos_3.png</url><title>Traumatic Brain Injury</title><link>https://issues-osu.github.io/ISSUESlab/tag/traumatic-brain-injury/</link></image><item><title>Detecting Hidden Mechanisms of Abuse-Related Injury in Children: Structured Topic Modeling of Clinical Death Reviews and Legal Opinions</title><link>https://issues-osu.github.io/ISSUESlab/presentations/ispcan-melbourne-2026/</link><pubDate>Mon, 24 Aug 2026 00:00:00 +0000</pubDate><guid>https://issues-osu.github.io/ISSUESlab/presentations/ispcan-melbourne-2026/</guid><description>&lt;p>&lt;strong>Presented at the ISPCAN World Congress on Child Abuse and Neglect&lt;/strong>, Melbourne, Australia, August 2426, 2026.&lt;/p>
&lt;p>&lt;strong>Full title:&lt;/strong> &lt;em>Detecting Hidden Mechanisms of Abuse-Related Injury in Children: Structured Topic Modeling of Clinical Death Reviews and Legal Opinions Triangulating Multidisciplinary Child Fatality Reviews with Factual and Procedural Narratives from Case Law&lt;/em>&lt;/p>
&lt;h2 id="abstract">Abstract&lt;/h2>
&lt;p>Existing child maltreatment surveillance systems miss or misclassify between 8090% of maltreatment deaths, and CPS records undercount fatalities by 5576%. Unstructured narrative text clinical death reviews, court opinions, and social work records accounts for 8090% of all organizational data produced, yet it is rarely leveraged for injury surveillance.&lt;/p>
&lt;p>This presentation introduces a two-study AI + Structured Topic Modeling (STM) pipeline that integrates two distinct narrative corpora to recover latent, abuse-related injury mechanisms that structured administrative codes routinely obscure.&lt;/p>
&lt;h2 id="study-design">Study Design&lt;/h2>
&lt;table>
&lt;thead>
&lt;tr>
&lt;th>&lt;/th>
&lt;th>Study 1: CFRT Death Reviews&lt;/th>
&lt;th>Study 2: CourtListener Case Law&lt;/th>
&lt;/tr>
&lt;/thead>
&lt;tbody>
&lt;tr>
&lt;td>&lt;strong>Source&lt;/strong>&lt;/td>
&lt;td>Colorado Child Fatality Review Team reports&lt;/td>
&lt;td>Appellate opinions retrieved from CourtListener&lt;/td>
&lt;/tr>
&lt;tr>
&lt;td>&lt;strong>Documents&lt;/strong>&lt;/td>
&lt;td>223 child-level narrative records&lt;/td>
&lt;td>751 opinions → 335 confirmed cases from Ohio&lt;/td>
&lt;/tr>
&lt;tr>
&lt;td>&lt;strong>Text&lt;/strong>&lt;/td>
&lt;td>Two free-text fields per report (clinical + administrative)&lt;/td>
&lt;td>Facts + procedural history&lt;/td>
&lt;/tr>
&lt;tr>
&lt;td>&lt;strong>LLM Extraction&lt;/strong>&lt;/td>
&lt;td>GPT-4o-mini: caregiver behavior, injury mechanism, setting, diagnosis&lt;/td>
&lt;td>GPT-4o-mini: 9 structured fields including perpetrator, victim type, legal outcome&lt;/td>
&lt;/tr>
&lt;tr>
&lt;td>&lt;strong>STM Models&lt;/strong>&lt;/td>
&lt;td>Risk &amp;amp; Contributing Factors; Circumstances&lt;/td>
&lt;td>Injury Mechanism; Long-Term Consequences&lt;/td>
&lt;/tr>
&lt;tr>
&lt;td>&lt;strong>Covariate&lt;/strong>&lt;/td>
&lt;td>Incident year (temporal prevalence)&lt;/td>
&lt;td>Judicial ruling (affirmed / reversed)&lt;/td>
&lt;/tr>
&lt;/tbody>
&lt;/table>
&lt;h2 id="research-questions">Research Questions&lt;/h2>
&lt;ol>
&lt;li>Can large language models transform unstructured child fatality narratives into standardized semantic features caregiver behavior, injury mechanism, setting, diagnosis?&lt;/li>
&lt;li>What latent themes emerge, and what typology of risk and incident circumstances do they suggest?&lt;/li>
&lt;li>Do the recovered themes reveal recurring patterns of head and neck trauma consistent with abuse-related injury?&lt;/li>
&lt;li>How does the prevalence of these themes shift across incident years (20202025)?&lt;/li>
&lt;/ol>
&lt;h2 id="key-findings">Key Findings&lt;/h2>
&lt;ul>
&lt;li>Both corpora converge on &lt;strong>craniofacial injury&lt;/strong> as the dominant mechanism routinely undercounted by ICD codes.&lt;/li>
&lt;li>&lt;strong>Strangulation&lt;/strong> emerged as a critical lethality predictor; soft-tissue damage can surface 23 days post-injury, requiring clinician and court training on delayed sequelae.&lt;/li>
&lt;li>Records document &lt;strong>long-term neurological harm&lt;/strong> (cerebral palsy, pituitary damage, blindness) in children often years before clinical follow-up.&lt;/li>
&lt;li>&lt;strong>Children represent a structurally distinct injury profile&lt;/strong> in both datasets, warranting specialized clinical and legal protocols.&lt;/li>
&lt;li>&amp;ldquo;Accidental&amp;rdquo; injuries (falls, environmental contact) are frequently embedded in an abuse context screening for &lt;strong>mechanism&lt;/strong>, not just diagnosis, is essential.&lt;/li>
&lt;li>Appellate opinions and death reviews function as &lt;strong>injury-surveillance sources&lt;/strong> beyond structured administrative fields.&lt;/li>
&lt;/ul>
&lt;h2 id="methodology">Methodology&lt;/h2>
&lt;p>The pipeline applies:&lt;/p>
&lt;ul>
&lt;li>&lt;strong>PDF parsing&lt;/strong> (pdftools) and regex isolation of narrative fields&lt;/li>
&lt;li>&lt;strong>GPT-4o-mini&lt;/strong> for LLM-based structured field extraction&lt;/li>
&lt;li>&lt;strong>Structured Topic Modeling (STM)&lt;/strong> with incident year or judicial ruling as a prevalence covariate&lt;/li>
&lt;li>&lt;strong>BART zero-shot classification&lt;/strong> as an independent supervised-style validation check&lt;/li>
&lt;li>&lt;strong>FREX word scoring&lt;/strong> (frequency � exclusivity) for topic labeling&lt;/li>
&lt;/ul>
&lt;h2 id="lab-members">Lab Members&lt;/h2>
&lt;p>This presentation was developed by the ISSUES Lab team at The Ohio State University:&lt;/p>
&lt;p>&lt;strong>Dr. Gia E. Barboza-Salerno&lt;/strong> (Founding Director), &lt;strong>Dr. Henriikka Weir&lt;/strong>, &lt;strong>Malcolm McCarthy&lt;/strong>, &lt;strong>Dr. Karla Shockley McCarthy&lt;/strong>, &lt;strong>Dr. Amy Watson-Grace&lt;/strong>, &lt;strong>Dr. Keith Warren&lt;/strong>, &lt;strong>Esenia Cassidy&lt;/strong>, and &lt;strong>Olivia McLucas&lt;/strong> with collaborators &lt;strong>Scottye Cash&lt;/strong> and &lt;strong>Suzanne Perkins&lt;/strong>.&lt;/p>
&lt;h3 id="-presentation">📄 Presentation&lt;/h3>
&lt;p>
&lt;i class="fas fa-download pr-1 fa-fw">&lt;/i> Download the
&lt;a href="https://issues-osu.github.io/ISSUESlab/ISSUESlab/uploads/ISPCAN_Melbourne_2026_ISSUES_Lab.pptx" target="_blank">presentation slides here&lt;/a>
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