A systematic method for hypothesis synthesis and conceptual model development

Abstract

Abstract Conceptual models are necessary to synthesize what is known about a topic, identify gaps in knowledge and improve understanding. The process of developing conceptual models that summarize the literature using ad hoc approaches has high potential to be incomplete due to the challenges of tracking information and hypotheses across the literature. We present a novel, systematic approach to conceptual model development through qualitative synthesis and graphical analysis of hypotheses already present in the scientific literature. Our approach has five stages: researchers explicitly define the scope of the question, conduct a systematic review, extract hypotheses from prior studies, assemble hypotheses into a single network model and analyse trends in the model through network analysis. The resulting network can be analysed to identify shifts in thinking over time, variation in the application of ideas over different axes of investigation (e.g. geography, taxonomy, ecosystem type) and the most important hypotheses based on the network structure. To illustrate the approach, we present examples from a case study that applied the method to synthesize decades of research on the effects of forest fragmentation on birds. This approach can be used to synthesize scientific thinking across any field of research, guide future research to fill knowledge gaps efficiently and help researchers systematically build conceptual models representing alternative hypotheses.