Making data on violence publicly available is a crucial first step to ensuring their use. However, more researchers and practitioners should be able to access opportunities to learn how to use and analyse these data. Efforts to expand the accessibility of violence data should be paired with efforts to support the use, analysis and interpretation of these data. Such efforts could include publicly available courses, video tutorials, statistical code, online discussion forums.

Analysing quantitative data and generating violence statistics is a responsibility. How statistics are generated and what they say have implications on the lives of young people in many countries. Four points are salient here. First, teach students that the rows in a VACS dataset are young people who have shared their lived experiences with a researcher and violence statistics come from real people.

Secondly, training on how to code and analyse data on violence, and generate violence statistics should be inseparable from training on how to develop a conceptual and theoretical approach to the analysis of data on violence with a focus on how violence is structurally produced, the interplay between individual and societal factors*, and the role of power and gender. The framing of the analysis shapes recommendations and policy implications: no analysis is neutral or apolitical.

Thirdly, contextualising the VACS as a survey program is also important to ensure students understand how data are collected, the sampling strategy, the safety protocols, and the ethical approaches used to keep participants safe. Encourage students to ask questions about where the data came from, who collected it, and what was done to prevent harm.

Finally, analyses of a dataset should be accompanied by a commitment to understanding the historical and social context of the statistics generated: encourage students to study the policy context of violence prevention and response and of youth health and wellbeing more broadly. This will require engaging with the social, political and economic context in which a violence survey was conducted and situating quantitative findings within this broader context.

Combining empathy for research participants, theory and context, allows students to engage more deeply with the statistics they are generating and engage with the implications of their analyses in a contextually relevant way.

* For more information on socio-ecological approaches to violence research see A socioecological approach to children’s experiences of violence: Evidence from Young Lives

Develop training on the analysis of violence data using models of co-teaching and co-learning. Collaborations with global north and south institutions and with researchers and practitioners will offer richer pedagogy. Work to decolonise the curriculum. Have conversations within the teaching team about the power hierarchies embedded in the course and which ones can be challenged. Ensure reading lists, guest speakers and mentors do not come from a single discipline, and represent a range of expertise and experiences. Create spaces of learning which do not privilege a single way of speaking English and collaborate to offer multilingual educational resources where possible.

For students, data on violence, which provides information on experiences of trauma, are not always easy to confront or analyse. The high prevalence of violence globally means that both instructors and students are often living with their own histories of violence. Support the teaching team and students to look after themselves and each other, discuss how to do this at the start of the course and re-visit regularly. Work to avoid platitudes about self-care but centre a focus on collective care.

Encourage students to think about the audiences for their data analysis and research – NGOs, government, INGOs, academic organisations, activists. Spend time exploring with students how these audiences might relate to their research findings, what the facilitators and barriers are to research uptake and how students can communicate with these audiences. Practice science communication, data visualisation, and data interpretation throughout the course. When students report data on violence in academic publications or policy briefs, encourage them to reflect on the key elements of ethical reporting.

Show students how quantitative data analyses can inform programming and policy from the beginning of the course. This will help students design and develop their own analyses. Often this content is included at the end of a course, or all together excluded from statistics and epidemiology training on violence.

A multi-session course is often not enough. When possible, offer students support to organize webinars, attend conferences, develop peer-reviewed publications, or generate other outputs to share findings and learnings. Create opportunities in the course where students can learn from and help each other. Connect students to researchers and invite them into the global community of violence researchers. Signpost existing communities of practice for students (e.g., SVRI or ISPCAN) or encourage them to set up their own in their contexts and institutions. For early career researchers this is particularly important and could shape career trajectories.