Structured Topic Modeling of Child Fatal Injury Narratives Using Machine Learning with County-Level Demographic Indicators to Strengthen Prevention Strategies

Wed, 01 Jan 2025 00:00:00 +0000

Plain-Language Summary

This study applies machine learning and natural language processing to analyze child fatality reports in Pennsylvania from 2016 to 2023. Unstructured text narratives from child death investigations were combined with census data to identify recurring themes and environmental factors surrounding child neglect and traumatic injuries.

Using structured topic modeling, the researchers identified 11 distinct circumstances of death, including substance misuse, sleep-related deaths, firearms, and supervisory neglect. The analysis showed that counties with higher poverty levels and larger non-White populations experienced a higher prevalence of firearm-related and severe traumatic injuries. The findings demonstrate how combining clinical narratives with machine learning can strengthen fatality surveillance and help construct more effective, targeted prevention programs.

Examining the Interplay Between the Natural and Socio-physical Environment Using Machine Learning Algorithms

Thu, 01 Aug 2024 00:00:00 +0000

Plain-Language Summary

This research presentation examines the interplay between the built, natural, and social environments in predicting the risk of child abuse and neglect (CAN). By utilizing machine learning algorithms, the study categorizes environmental determinants of child well-being into key dimensions including urban design, environmental contaminants, and neighborhood socioeconomic conditions.

The study demonstrates that characteristics of the physical and natural environment, such as neighborhood walkability, lighting, and greenness, interact with social vulnerabilities to shape family stress and safety. This work highlights the value of using computational models to translate physical streetscape characteristics into policy-relevant indicators for child maltreatment prevention.

Sharefa A. Duhaney | ISSUES | The Ohio State University

Structured Topic Modeling of Child Fatal Injury Narratives Using Machine Learning with County-Level Demographic Indicators to Strengthen Prevention Strategies

Plain-Language Summary

Examining the Interplay Between the Natural and Socio-physical Environment Using Machine Learning Algorithms

Plain-Language Summary