Who is the expert? A process guide to incorporate lived/living experience into directed acyclic graphs: an applied example from HIV research

AIM: Causal inference relies on correct background knowledge, which epidemiologists generally understand to come from academic experts. Our community-engaged study augments scientific domain knowledge with lived/living experience to co-construct the directed acyclic graph (DAG) underpinning our team's research question about ageing and HIV. We outline our team's process for co-creating the community-based DAG and describe qualitative reflections from team members regarding these methods. Our overarching goal was to expand expert knowledge to include community expertise by engaging peer researchers in DAG co-development. METHODS: We assembled a team of quantitative and qualitative researchers, including a diverse group of peer researchers living with HIV. The team co-constructed a DAG, illustrated by a peer researcher-artist, combining the lived/living experience of peer researchers with subject-matter expertise from academic researchers. The DAG was refined with input from epidemiologists. Qualitative researchers transcribed DAG co-development sessions to understand how peer researchers engaged with this tool. RESULTS: Qualitative reflections allowed the study team to critically analyse our process. Peer researchers found drawing the DAG intuitive. Having a visual representation of causal relationships led to active discussion and greater understanding. The complexity of the DAG enmeshed with temporal ordering humanised the research; seeing the web of covariates resonated as a reflection of a person's life journey. One peer researcher found that incorporating diverse perspectives meant upholding unique expertise and not only platforming academic expertise. CONCLUSIONS: Co-constructing DAGs incorporating lived/living experience is reasonable and possible. Co-constructing DAGs may strengthen epidemiologic studies by reconceptualising the traditional epidemiologic definition of expert knowledge.