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Prevalence, increase and predictors of family violence during the COVID-19 pandemic, using modern machine learning
Kristina Todorovic1, Erin O'Leary2, Kaitlin P Ward3
1Department of Psychology, University of Toledo, Toledo, OH, United States.
Insights
Parental empathy and well-being reduce child maltreatment risk during the COVID-19 pandemic. Family violence, including physical punishment and partner altercations, significantly increased, highlighting the need for mental health support and parenting programs.
Area of Science:
- Psychology
- Public Health
- Data Science
Background:
- The COVID-19 pandemic has negatively impacted mental health, leading to increased child maltreatment and intimate partner violence.
- Family violence poses a significant public health concern, exacerbated by pandemic-related stressors.
Purpose of the Study:
- To identify key predictors of child maltreatment and intimate partner violence during the COVID-19 pandemic using machine learning.
- To analyze the prevalence of family violence at different stages of the pandemic.
Main Methods:
- Machine learning models, including random forest and SHAP values, were employed to analyze data from 380 participants.
- Data included COVID-19 related factors, parental psychological distress, personality traits, and relationship dynamics.
- A longitudinal cohort study assessed family violence across three time points between March and June 2020.
Main Results:
- Parental affective empathy, psychological well-being, and engaging in outdoor activities with children were associated with a lower risk of child maltreatment.
- A reduction in physical altercations between partners also predicted decreased child maltreatment.
- Significant increases in physical punishment of children and physical/verbal altercations between partners were observed during the pandemic.
Conclusions:
- Predictive algorithms can identify crucial factors influencing child maltreatment.
- Raising awareness of family violence and implementing mental health-focused parenting programs are essential for mitigation efforts.
Background:
We are facing an ongoing pandemic of coronavirus disease 2019 (COVID-19), which is causing detrimental effects on mental health, including disturbing consequences on child maltreatment and intimate partner violence.
Methods:
We sought to identify predictors of child maltreatment and intimate partner violence from 380 participants (mean age 36.67 ± 10.61, 63.2% male; Time 3: June 2020) using modern machine learning analysis (random forest and SHAP values). We predicted that COVID-related factors (such as days in lockdown), parents' psychological distress during the pandemic (anxiety, depression), their personality traits, and their intimate partner relationship will be key contributors to child maltreatment. We also examined if there is an increase in family violence during the pandemic by using an additional cohort at two time points (Time 1: March 2020, N = 434; mean age 35.67 ± 9.85, 41.69% male; and Time 2: April 2020, N = 515; mean age 35.3 ± 9.5, 34.33%).
Results:
Feature importance analysis revealed that parents' affective empathy, psychological well-being, outdoor activities with children as well as a reduction in physical fights between partners are strong predictors of a reduced risk of child maltreatment. We also found a significant increase in physical punishment (Time 3: 66.26%) toward children, as well as in physical (Time 3: 36.24%) and verbal fights (Time 3: 41.08%) among partners between different times.
Conclusion:
Using modernized predictive algorithms, we present a spectrum of features that can have influential weight on prediction of child maltreatment. Increasing awareness about family violence consequences and promoting parenting programs centered around mental health are imperative.
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