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The impact of COVID-19 on child maltreatment-related medical encounters and system responses using linked administrative data
Investigator (PI): Rebbe, Rebecca
Performing Organization (PO): (Current): University of Southern California, Suzanne Dworak-Peck School of Social Work / (213) 740-8311
Supporting Agency (SA): National Institutes of Health (NIH), Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD)
Initial Year: 2021
Final Year: 2023
Record Source/Award ID: RePorter/ R21HD105907
Funding: 2021 Award Amount: $226,226
Award Type: Grant
Abstract: With schools and daycare facilities closed and unemployment rates soaring due to the COVID-19 pandemic, experts worry not only that the incidence of child maltreatment has increased but that that new or recurrent cases of maltreatment have gone undetected because two-thirds of reports to child protective services (CPS) are made by professionals. Linked administrative data (i.e., records collected for the provision of services, including health and child protection) can overcome the challenges of relying solely on CPS reports by joining the CPS database with medical records. Medical records have been identified as a useful data source for measuring child maltreatment. The objective of this application is to determine if and how the COVID-19 pandemic has impacted the incidence of child maltreatment-related medical encounters and the system responses to diagnosed cases of maltreatment. The rationale is maltreatment has significant identified impacts on children and if maltreatment has increased during this time, it will be important to allocate resources to address this detrimental form of trauma. The proposed study will take advantage of a natural experiment to focus on two specific aims: 1) compare the incidence rates of child maltreatment-related medical encounters, before and during COVID-19; and 2) determine the social and legal interventions/system responses to diagnosed medical encounters of child maltreatment before and during the pandemic. For the first aim, an interrupted time series will be used to identify the frequency of diagnosed maltreatment in primary care, emergency department, and hospitalization medical encounters. For the second aim, interrupted time series and logistic regression will be used to determine the percentage and likelihood of diagnosed maltreatment-related medical encounters being reported to CPS. The proposed research is innovative because it uses data from multiple sources and includes several types of medical encounters. The proposed research is significant because maltreatment is highly consequential but difficult to measure. Results will identify with robust empirical evidence if the pandemic COVID-19 has increased the incidence and severity of child maltreatment-related medical encounters and changed the social and legal interventions in response to such medical encounters. Ultimately, such knowledge has the potential to identify how community-level events impact child maltreatment, informing public policy, resource allocation, professional training, and future research.
MeSH Terms:
    Country: United States
    State: California
    Zip Code: 90089
    UI: 20214007
    Project Status: Ongoing