Abstract
Focus of Presentation
Most researchers do not use causal diagrams, in this case meaning directed acyclic graphs (DAGs), despite being widely recommended in epidemiology. They can help to identify the biases that might lead to faulty conclusions or suggest variables for which data should be collected and included in a model. Seeking to understand this reluctance and develop alternative strategies that might increase the use of causal diagrams, we searched the cognitive science literature for potential reasons and suggestions.
Findings
Insights from cognitive psychology led to a better understanding of the barriers that might underlie the reluctance to use causal diagrams. This includes our built-in desire for cognitive ease and suggests that strategies which lower the effort required to create a diagram may help. We explain these findings using example projects from neuropsychiatry big data research and describe how an online resource we have created has helped.
Conclusions/Implications
A causal diagram website has been created that aims to lower the effort needed to create a diagram for a study. It contains tutorials and a terminology guide, as well as links to other tutorials; a guide to software and other resources that might be used; and a searchable database of example causal diagrams with links to published articles that include them.
Key messages
A website has been developed to help overcome barriers to the use of causal diagrams. With contributions welcome.
1070An online searchable database of example causal diagrams to make them easier to construct