The links of stress, substance use and socio-demographic factors with domestic violence during the Covid-19 pandemic in Portugal
Authors & affiliation
Yilian M. Perez, Ana Gama, Ana R. Pedro, Maria J. L. de Carvalho, Ana E. Guerreiro, Vera Duarte, Jorge Quintas, Pedro Aguiar, Ines Keygnaert, Sonia Dias
Background Lockdown, as a measure implemented to combat the coronavirus disease 2019 (COVID-19) pandemic, left many domestic violence (DV) victims trapped with their abusers. This study intends to explore the links between perceived stress, substance use and socio-demographic factors with DV experiences during COVID-19 pandemic in Portugal. Methods A cross-sectional study was carried out on a sample of 1062 participants over 16 years old, residing in Portugal. Data were collected through an online survey conducted between April and October 2020. The associations between potential factors and DV were investigated using bivariable analysis and multivariable logistic regression. Results The prevalence of DV reported was 13.75% (n = 146), disaggregated into psychological violence (13%, n = 138), sexual violence (1.0%, n = 11) and physical violence (0.9%, n = 10). Multivariable analyses confirmed that perceived financial difficulties (OR = 1.608; P = 0.019), use of medications to sleep or calm down (OR = 1.851; P = 0.002) and perceived stress (OR = 2.443; P = 0.003) were responsible for DV exposure during COVID-19 pandemic. Younger age (<25 years old) and consumption of alcohol were associated with a higher risk of DV victimization. Conclusions Interventions aimed at preventing and confronting DV are necessary within the strategies to combat COVID-19 in Portugal, especially aimed at groups in vulnerable situations, during and after the pandemic.
Lotte De Schrijver, Ines Keygnaert, Anne Nobels2021 Eindrapport Onderzoek naar Relaties, Stress en Agressie in de eerste 12 maanden van COVID-19 in België
Lotte De Schrijver, Ines Keygnaert, Anne Nobels2021 Eerste bevindingen omtrent Seksueel Geweld en COVID-19 in 2020 in België : kan een voorspellingsmodel helpen in vergelijkbare lockdown-situaties?
Lotte De Schrijver, Ines Keygnaert, Anne Nobels