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5.2: How to transform social science data and evidence into actionable findings

5.2: How to transform social science data and evidence into actionable findings

This session teaches how to effectively design research and transform social science data and evidence into findings that can be used to influence policy and practice relevant.

Learning outcomes

  • Be able to transform data into useful knowledge and actionable recommendations.
  • Know how to draw out what research findings actually mean in a way that is helpful to community engagement and/or communications activities.
  • Be able to design research that lays the foundation for actionable findings.

Related resources

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Module structure

1.1: Introduction to social science – definition, approaches and role in broader humanitarian action
1.2: Operational social science research in the humanitarian programme cycle
1.3: Advocating for the inclusion of social science in emergency response activities that engage communities
2.1: Understanding context, vulnerability and inequality in public health and humanitarian emergencie
2.2: Understanding behaviour in public health and humanitarian emergencies – models and theories
2.3: Rapid strategies to understand the political, socio-cultural, and economic factors that increase vulnerability
2.4: Understanding the importance of language in social science research
3.1: Ethical principles and approvals for social science research in a humanitarian context
3.2: Promoting the meaningful translation and application of ethical principles
4.1: Localised research: designing operational social science research that is responsive to communities
4.2: Quantitative and qualitative approaches to generate data in operational social science research
4.3: Quantitative data collection methods: knowledge, attitudes and practice / perceptions surveys
4.4: Qualitative data collection methods: in-depths interviews, observation, and focus group discussions
4.5: Quantitative data analysis in operational social science research
4.6: Qualitative data analysis in operational social science research
4.7: Mixing different methods to produce quality evidence
4.8: Triangulation of data: why it is important and how does it work?
5.1: Evidence synthesis for social and behavioural data
5.2: How to transform social science data and evidence into actionable findings
5.3: How to communicate and present research outputs to different audiences
5.4: Feeding back to communities and using findings to support community-level solutions and actions
6.1: Translating social science research into
6.2: Enabling environments for the uptake of social science evidence in emergency response
7.1: Tracking the use or ‘application’ of integrated operational social science outputs: Integrated Outbreaks Analytics and MONITO

Session type

90-120 minutes
Online and offline