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Determinants of Referral Outcomes for Victim-Survivors Accessing Specialist Sexual Violence and Abuse Support Services.

Annie BunceNiels BlomEstela Capelas Barbosa
Published in: Journal of child sexual abuse (2024)
Sexual violence and abuse (SVA) is highly prevalent globally, has devastating and wide-ranging effects on victim-survivors, and demands the provision of accessible specialist support services. In the UK, Rape Crisis England & Wales (RCEW), a voluntary third sector organization, is the main provider of specialist SVA services. Understanding the profile of victim-survivors who are referred to RCEW and their referral outcomes is important for the effective allocation of services. Using administrative data collected by three Rape Crisis Centres in England between April 2016 and March 2020, this study used multinomial regression analysis to examine the determinants of victim-survivors' referral outcomes, controlling for a wide range of potentially confounding variables. The findings demonstrate that support needs, more so than the type of abuse experienced, predicted whether victim-survivors were engaged with services. Particularly, the presence of mental health, substance misuse and social, emotional, and behavioral needs were important for referral outcomes. The referral source also influenced referral outcomes, and there were some differences according to demographic characteristics and socioeconomic factors. The research was co-produced with stakeholders from RCEW, who informed interpretation of these findings. That victim-survivors' engagement with services was determined by their support needs, over and above demographic characteristics or the type of abuse they had experienced, demonstrates the needs-led approach to service provision adopted by RCEW, whereby resources are allocated effectively to those who need them most.
Keyphrases
  • mental health
  • primary care
  • healthcare
  • young adults
  • palliative care
  • public health
  • mental illness
  • intimate partner violence
  • chronic pain
  • social media
  • big data
  • adipose tissue
  • cross sectional