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Understanding the Components and Determinants of Police Attitudes Toward Intervention in Intimate Partner Violence Against Women: A Systematic Review.

Celia Serrano-MontillaLuis M LozanoMaría Alonso-FerresInmaculada Valor-SeguraJose-Luis Padilla
Published in: Trauma, violence & abuse (2021)
Police officers are society's first interveners in intimate partner violence against women (IPVAW) and are essential for victim safety. Despite IPVAW laws, police attitudes influence their real actions during IPVAW intervention. However, the fuzzy conceptualization of the construct deters the pursuit of conclusive evidence. This systematic review sought to identify the components of police attitudes toward intervention in IPVAW and their determinants. A search was conducted through several databases (e.g., Web of Science). Papers were included if they (a) provided original empirical findings or were review studies, (b) were published between 1990 and 2019, (c) were written in Spanish or English, (d) alluded to police officers, and (e) focused on police attitudes toward intervention in IPVAW or their determinants. Fifty-seven papers were included. The studied components of police attitudes toward intervention in IPVAW extracted from the literature were tolerance of IPVAW, minimal police involvement, unsupportive and supportive attitudes toward the legal system and legislation against IPVAW, understanding of the complex nature of abuse, and IPVAW intervention as an important police task. Moreover, the central role of individual and situational determinants in police attitudes toward intervention in IPVAW was confirmed, whereas organizational and societal determinants were studied scarcely. This review proposes a framework upon which to build operational definition of police attitudes toward intervention in IPVAW and includes remarks on police backgrounds and the situational characteristics of IPVAW events that are essential in shaping police procedures for managing them. Empirical evidence should be transferred to police training and standard operating procedures.
Keyphrases
  • randomized controlled trial
  • systematic review
  • intimate partner violence
  • public health
  • mental health
  • meta analyses
  • type diabetes
  • machine learning
  • pregnant women
  • metabolic syndrome
  • deep learning
  • breast cancer risk