McLay Molly M
Brown School, Washington University in St. Louis, Campus Box 1196, One Brookings Drive, Saint Louis, MO 63130 USA.
J Fam Violence. 2022;37(6):861-870. doi: 10.1007/s10896-020-00225-6. Epub 2021 Jan 7.
This study explored the COVID-19 pandemic's impacts on domestic violence (DV) with the following research questions: 1) Did DV occurring during the pandemic differ on certain variables from cases occurring on a typical day the previous year? 2) Did DV occurring after the implementation of shelter-in-place orders differ (on these same variables) from cases occurring prior to shelter-in-place orders? Two logistic regression models were developed to predict DV case differences before and during the pandemic. DV reports ( = 4618) were collected from the Chicago Police Department. Cases from March 2019 and March 2020 were analyzed based on multiple variables. One model was set to predict case differences since the pandemic began, and another model was set to predict case differences during the shelter-in-place period later that month. Both models were significant with multiple significant predictors. During the pandemic period, cases with arrests were 20% less likely to have occurred, and cases at residential locations were 22% more likely to have occurred. During the shelter-in-place period, cases at residential locations were 64% more likely to have occurred, and cases with child victims were 67% less likely to have occurred. This study offers a rapid analysis of DV case differences since the pandemic and shelter-in-place began. Additional variables and data sources could improve model explanatory power. Research, policy, and practice in this area must pivot to focus on protecting children whose access to mandated reporters has decreased and moving victims out of dangerous living situations into safe spaces.
本研究通过以下研究问题探讨了新冠疫情对家庭暴力(DV)的影响:1)疫情期间发生的家庭暴力在某些变量上与上一年正常日子里发生的案件有何不同?2)实施就地避难令后发生的家庭暴力(在这些相同变量上)与就地避难令实施前发生的案件有何不同?开发了两个逻辑回归模型来预测疫情之前和期间家庭暴力案件的差异。从芝加哥警察局收集了家庭暴力报告(n = 4618)。基于多个变量对2019年3月和2020年3月的案件进行了分析。一个模型用于预测自疫情开始以来的案件差异,另一个模型用于预测当月晚些时候就地避难期间的案件差异。两个模型都具有显著性,且有多个显著预测因素。在疫情期间,有逮捕情况的案件发生可能性降低了20%,发生在居住场所的案件发生可能性增加了22%。在就地避难期间,发生在居住场所的案件发生可能性增加了64%,有儿童受害者的案件发生可能性降低了67%。本研究对自疫情和就地避难开始以来的家庭暴力案件差异进行了快速分析。其他变量和数据源可以提高模型的解释力。该领域的研究、政策和实践必须转向关注保护那些向法定报告人求助机会减少的儿童,并将受害者从危险的生活环境转移到安全的空间。