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Frontline Workers' Response to Harmful Sexual Behavior: Building Blocks For Promising Practice.

Gemma McKibbinCathy Humphreys
Published in: Trauma, violence & abuse (2021)
Frontline workers, including educators and health practitioners, play an important role in identifying and responding to harmful sexual behavior (HSB) carried out by children and young people. Despite this, there have been no reviews of the evidence about promising practice for how frontline workers could best manage this behavior. This article presents a scoping review of evidence exploring the research question: How can frontline professionals be trained and supported to better manage HSB carried out by children and young people? Multiple databases were searched in July 2020. Inclusion criteria included a focus on professional development or practice relating to children and young people displaying inappropriate sexual behavior or HSB; a population of frontline workers (teachers, health practitioners, coaches, childcare workers); and all study types, including gray literature. Two reviewers screened the articles, and findings from included papers were synthesized according to the method of thematic synthesis. Thirty-one papers were included in the review. Five themes were identified in response to the research question: process of identification and response, knowledge required to identify and respond, skills needed to identify and respond, organization-level supports, and system-level supports. The authors propose the "building blocks" for a promising practice model, which sets out the process of identification and response to HSB, and the knowledge required by frontline workers to support that process. Further, the model identifies the skills required by frontline workers to undertake the process of identification and response, as well as the organization-level and system-level scaffolding needed for good practice.
Keyphrases
  • healthcare
  • primary care
  • mental health
  • young adults
  • public health
  • systematic review
  • quality improvement
  • gene expression
  • genome wide
  • social media
  • artificial intelligence
  • big data