Moving from thematic to causal analysis: research into how asylum seekers perceive the impact of social protection on their wellbeing

This case study draws on innovative, collaborative research to demonstrate the benefits and limitations of using mixed methods data collection, including peer-led Qualitative Impact Protocol (QuIP) interviews and Photovoice, and causal analysis. We illustrate how the methodological design addressed the needs of research participants, policy-makers, and wider stakeholders and was more incisive than general thematic analysis in assessing how different forms of social protection were perceived to mediate or hinder UK asylum seekers’ wellbeing. Despite challenges in adopting a peer-researcher model, the QuIP was effective in drawing out detailed stories of change in participants’ lives while mitigating potential response bias. The use of peer researchers from the refugee community encouraged open, frank conversations and empathic listening and sup-ported both interviewee and peer researcher wellbeing. The Causal Map (v2) software successfully analysed and visualised complex causal relationships in the mixed, textual data, producing top-level quantitative visualisations linked clearly to underlying quali-tative evidence.