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Patterns and Usefulness of Safety Behaviors Among Community-Based Women Survivors of Intimate Partner Violence.

Ginger C HansonJill Theresa MessingJocelyn C AndersonJonel ThallerNancy A PerrinNancy E Glass
Published in: Journal of interpersonal violence (2019)
Women who experience intimate partner violence (IPV) use a variety of safety strategies to reduce the frequency and severity of violence, including both informal and formal help-seeking. The purpose of this study was to identifying patterns of engagement in safety behaviors by U.S. women from outside of formal service settings, examine which factors are associated with different patterns of use, and examine the perceived usefulness of safety strategies among women who used them. Cross-sectional data from 725 women experiencing IPV were used for these analyses. A cluster analysis revealed three clusters of safety behavior use among the IPV survivors: Exploring Safety Options, Avoiding the Justice System, and Trying Everything. The trying everything cluster had high rates of use across all of the safety behaviors; they also reported the highest levels of physical, sexual, and psychological IPV. The exploring safety options cluster used the fewest safety behaviors and had the lowest level of IPV. Higher violence was related to a higher likelihood of finding safety planning helpful and a lower likelihood of finding leaving home helpful. Women who were currently living with their partner were less likely to find talking with a professional, making a safety plan, or leaving home helpful. Higher decisional conflict-uncertainty about what safety decisions would be best-was almost universally related to greater likelihood of not finding safety behaviors helpful. The study findings reinforce the importance of working with survivors to tailor safety plans with strategies that reflect their situation, and provide insights into for which tailoring of resource recommendations may be made.
Keyphrases
  • intimate partner violence
  • mental health
  • polycystic ovary syndrome
  • healthcare
  • physical activity
  • social media
  • pregnancy outcomes
  • insulin resistance
  • machine learning
  • deep learning
  • single cell