DFG: Diagnostic Reasoning with Causal Models

The project 'Order Effects in Diagnostic Reasoning' with Georg Jahn and Felix Rebitschek consisted of a series of studies concerning diagnostic reasoning. Thereby, diagnostic reasoning is defined as the process of finding the best possible explanation for a set of symptoms. This process is predominantly based on causal knowledge. Especially symptoms supporting only one cause are seen as strong predictors for this cause. However, symptoms support usually more than one cause. This project investigated the processing and sequential integration of ambigous symptoms and their causal strenght and diversity . The way hypotheses are generated and kept active in working memory is hugely infuenced by these factors.

Diagnostic judgements and process data were compared with normative solutions and simaltions of cognitive processes. The results of this projects allow a better understanding of the sequential symptom integration during diagnostic reasoning and enable us to draft assistance meassures to improve the process of finding the best possible diagnosis.

References

• Jahn, G., Renkewitz, F., & Kunze, S. (2007). Heuristics in multi-attribute decision making: effects of representation format. In D. S. McNamara & J. G. Trafton (Hrsg.), Proceedings of the 29th Annual Cognitive Science Society (pp. 383-388). Austin, TX: Cognitive Science Society.

• Rebitschek, F. G., Bocklisch, F., Scholz, A., Krems, J. F. & Jahn G. (2015). Biased processing of ambiguous symptoms favors the initially leading hypothesis in sequential diagnostic reasoning. Experimental Psychology, 62(5), 287-305. doi:10.1027/1618-3169/a000298