Constructing causal loop diagrams from large interview data sets

Who it's for: Ideal for learners with a basic understanding of systems dynamics or a background in public health, seeking methodologies to analyze systems with interview data sets.

Why we love it: By analyzing over 100 interviews, the authors of this study explore manual and semi-automated techniques for constructing causal loop diagrams. The study highlights the intricacies of data interpretation and the importance of context when studying systems. This methodological paper offers practical insights and recommendations for researchers seeking to use large qualitative datasets for systemic analysis, particularly for intervention design in the field of public health.

Citation: Newberry, P., & Carhart, N. (2024). Constructing causal loop diagrams from large interview data sets. System Dynamics Review, 40(1), e1745. https://doi.org/10.1002/sdr.1745