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Children Witnessing Domestic Violence in the Voice of Health and Social Professionals Dealing with Contrasting Gender Violence.

Stefania CarnevaleImmacolata Di NapoliCiro EspositoCaterina ArcidiaconoFortuna Procentese
Published in: International journal of environmental research and public health (2020)
Witnessing domestic violence (WDV) is recognized by the Istanbul Convention as psychological abuse that has dramatic consequences on the psychophysical health of children. Therefore, professionals who form the support network for WDV victims play a very fundamental role. In order to draw up useful guidelines for services dealing with WDV, and to give children more awareness of supportive settings, this study analyzes WDV in the perception of health and welfare professionals to enhance their skills and strategies for contrasting gender violence. Sixteen Neapolitan specialists dealing with WDV children were interviewed. A theoretical intentional sampling was used. Narrative focused interviews were carried out, transcribed verbatim and analyzed through the grounded theory methodology, using the ATLAS.ti 8 software (Scientific Software Development GmbH, Berlin, Germany). We assigned 319 codes and grouped these into 10 categories and 4 macro-categories. The analysis of the texts led to the definition of the core category as "The Crystal Fortress". It summarizes the image of the WDV children as described by the professionals working in contrasting domestic violence. In this structure the parental roles of protection and care (fortress) are suspended and everything is extremely rigid, fragile and always at risk of a catastrophe. It also symbolizes the difficult role of health professionals in dealing with such children and their families. For WDV children, protective factors guarantee solid development and supportive settings help them to learn proper emotional responsiveness and expressiveness and to develop their skills in talking with adults while avoiding negative consequences.
Keyphrases
  • mental health
  • young adults
  • healthcare
  • public health
  • depressive symptoms
  • risk assessment
  • single cell
  • palliative care
  • health information
  • deep learning
  • network analysis
  • clinical practice
  • pain management