[Preparation of a questionnaire to detect cases of hate violence in emergency rooms]

Gac Sanit. 2020 Mar-Apr;34(2):166-170. doi: 10.1016/j.gaceta.2019.01.006. Epub 2019 May 14.
[Article in Spanish]

Abstract

Objective: In the context of the SIVIVO project, the development of a tool to facilitate the detection, recording and description of cases of hate violence and its consequences on health was proposed.

Method: A two-round Delphi method was used with experts from clinical-care, public health, epidemiological, academic, administration and non-governmental organizations to assess the relevance of different items using a Likert scale, presenting the results with medians and coefficients of variation.

Results: The best evaluated questions, with scores equal to or greater than 4, and which make up the final version of the questionnaire are the relative socio-demographic characteristics of the victim, the injuries, description of the incident, the motivations perceived by the aggrieved person, possible evidence of hatred, the intention to denounce and the perception of the health personnel of the motive for the aggression. The piloting showed the adequacy of the questions that were finally selected.

Conclusions: The systematic incorporation of this tool can help us to learn the magnitude and characteristics of hate violence and its impact on health. This information would allow the elaboration of prevention and intervention strategies aimed, specifically, at the sectors of the population most exposed to this type of violence.

Keywords: Diagnosis; Diagnóstico; Encuestas y cuestionarios; Surveys and questionnaires; Violence; Violencia.

MeSH terms

  • Adult
  • Delphi Technique
  • Emergency Service, Hospital*
  • Ethnicity
  • Exposure to Violence
  • Female
  • Gender Identity
  • Hate*
  • Humans
  • Male
  • Motivation
  • Pilot Projects
  • Prejudice
  • Sex
  • Socioeconomic Factors
  • Surveys and Questionnaires*
  • Violence* / prevention & control
  • Violence* / psychology
  • Violence* / statistics & numerical data