TY - JOUR T1 - Sampling design and methodology of the Violence Against Children and Youth Surveys JF - Injury Prevention JO - Inj Prev SP - 321 LP - 327 DO - 10.1136/injuryprev-2018-042916 VL - 25 IS - 4 AU - Kimberly H Nguyen AU - Howard Kress AU - Andres Villaveces AU - Greta M Massetti Y1 - 2019/08/01 UR - http://injuryprevention.bmj.com/content/25/4/321.abstract N2 - Introduction Globally 1 billion children are exposed to violence every year. The Violence Against Children Surveys (VACS) are nationally representative surveys of males and females ages 13–24 that are intended to measure the burden of sexual, physical and emotional violence experienced in childhood, adolescence and young adulthood. It is important to document the methodological approach and design of the VACS to better understand the national estimates that are produced in each country, which are used to drive violence prevention efforts.Methods This study describes the surveys’ target population, sampling design, statistical considerations, data collection process, priority violence indicators and data dissemination.Results Twenty-four national household surveys have been completed or are being planned in countries across Africa, Asia, the Caribbean, Central and South America, and Eastern Europe. The sample sizes range from 891 to 7912 among females (72%–98% response rate) and 803–2717 among males (66%–98% response rate). Two face-to-face interviews are conducted: a Household and an Individual Questionnaire. A standard set of core priority indicators are generated for each country that range from prevalence of different types of violence, contexts, risk and protective factors, and health consequences. Results are disseminated through various platforms to expand the reach and impact of the survey results.Conclusion Data obtained through VACS can inform development and implementation of effective prevention strategies and improve health service provision for all who experience violence. VACS serves as a standardised tool to inform and drive prevention through high-quality, comprehensive data. ER -