Abstract: The Potential Influences of COVID-19 and Social Vulnerability Measures on Child Maltreatment: Spatial Temporal Cluster Analysis and Negative Binormial Regression (Society for Social Work and Research 28th Annual Conference - Recentering & Democratizing Knowledge: The Next 30 Years of Social Work Science)

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681P The Potential Influences of COVID-19 and Social Vulnerability Measures on Child Maltreatment: Spatial Temporal Cluster Analysis and Negative Binormial Regression

Schedule:
Sunday, January 14, 2024
Marquis BR Salon 6, ML 2 (Marriott Marquis Washington DC)
* noted as presenting author
Tae Kyung Park, PhD, Assistant Professor, University of Colorado, Colorado Springs, Colorado Springs, CO
Hui Liew, PhD, Associate Professor, University of Nebraska, Kearney, NE
Background and Purpose

During the public health crises such as COVID-19, parents can experience high stress driven by drastically changed social environments. Parental stress can weaken child care capacity and associate with child abuse and neglect (CAN). For appropriate responses to CAN during public health crises, it is important to understand the patterns of CAN and association between CAN cases with the number of confirmed COVID-19 cases and social vulnerability measures. This study used spatial-temporal clustering and negative binomial regression (NBR) to examine how child removal due to physical abuse and neglect prevalence differs by the magnitudes of COVID-19 cases across counties in the U.S. We also examined the impact of COVID-19 and social vulnerability measures on physical abuse and neglect.

Methods

This study utilized secondary data sets obtained from Adoption and Foster Care Analysis and Reporting of the National Data Archive on Child Abuse and Neglect for child maltreatment, USA Facts for COVID-19 confirmed cases, and the Agency for Toxic Substances and Disease Registry’s Geospatial Research, Analysis & Services Program for social vulnerability measures. The 2020 data were selected for the analysis due to its availability. Child maltreatment was estimated using the negative binomial regression (NBR) because the of the over-dispersion of the outcome variable, CAN. Two NBR models was estimated. The analysis began in Model 1 by including the spatial temporal cluster of COVID-19 cases by county in the U.S. as an independent variable. Model 2 added measures of social vulnerability such as percentages of unemployed population, persons with no high school diploma, persons below 150% poverty estimate, population in mobile homes, households living in crowded housing situations.

Results

Results in Model 1 revealed that the number of child removal due to parental physical abuse and neglect was significantly higher in counties characterized by moderately severe increases (b=.1016, p<.0001), very severe increases (b=1.5779, p<.0001), and drastic increases (b=2.8995, p<.0001) in Covid-19 cases when compared to counties characterized by plateau or mild increases in Covid-19 cases. These spatial temporal clusters of COVID-19 cases continued to have a significant effect on the number of child removal due to parental physical abuse due to parental physical abuse and neglect was significantly higher in counties characterized by moderately severe increases (b=.9696, p<.001), very severe increases (b=1.5003, p<.0001), and drastic increases (b=2.6990, p<.0001) in COVID-19 cases when compared to counties characterized by plateau or mild increases even with the addition of the social vulnerability measures in Model 2. However, Model 2 revealed that social vulnerability measures had no significant effects on child removal after controlling for spatial-temporal clusters of COVID-19.

Conclusion and Implication

Our study was able to identify that child removal due to physical abuse and neglect was more prevalent in the counties that experienced severe and drastic increase of confirmed COVID-19 cases. The findings requires cautious interpretation given complicating nature of child maltreatment. Further research will guide child welfare policy makers to develop prevention programs for more vulnerable communities during public health crises.