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Childhood Community Risk Factors on Intimate Partner Violence Perpetration and Victimization Among College Students.

Hyesu YeoY Joon ChoiEsther SonHyunkag ChoSung Hyun YunJungeun Olivia Lee
Published in: Journal of interpersonal violence (2021)
The study examined the effect of community environments, such as community cohesion, community safety, and community poverty, in childhood on the likelihood of Intimate Partner Violence (IPV) perpetration and victimization in young adulthood. The study used the cross-sectional survey data of 2,082 college students collected in 2016-2017 from six universities in the U.S. and the data for the childhood community environment from the 2007-2011 American Community Survey. Hierarchical regressions were performed separately by gender to 1) assess the effects of community factors in addition to individual factors for IPV perpetration and victimization, and to 2) identify the interaction effect of community cohesion with community poverty on IPV perpetration and victimization. Community factors of community cohesion and community poverty were significantly correlated to different types of IPV. For IPV perpetration, only community cohesion was significant for, the interaction effect between community cohesion and poverty showed that higher community cohesion lowered the risk of community poverty on later IPV perpetration in both genders. For IPV victimization, only female students were affected by community poverty, whereas none of the community factors had an impact on male students. The findings imply the significance of early interventions and policies strengthening the community environment, especially community cohesion, for preventing IPV. The findings also suggest that assessing risk and protective factors on IPV in multiple contexts during childhood is important to develop effective programs preventing IPV.
Keyphrases
  • intimate partner violence
  • mental health
  • healthcare
  • risk factors
  • public health
  • physical activity
  • artificial intelligence
  • big data
  • data analysis