Memory Activation and the Availability of Explanations in Sequential Diagnostic Reasoning

Article (PDF Available)inJournal of Experimental Psychology Learning Memory and Cognition 37(6):1391-411 · June 2011with33 Reads
DOI: 10.1037/a0023920 · Source: PubMed
In the field of diagnostic reasoning, it has been argued that memory activation can provide the reasoner with a subset of possible explanations from memory that are highly adaptive for the task at hand. However, few studies have experimentally tested this assumption. Even less empirical and theoretical work has investigated how newly incoming observations affect the availability of explanations in memory over time. In this article we present the results of 2 experiments in which we address these questions. While participants diagnosed sequentially presented medical symptoms, the availability of potential explanations in memory was measured with an implicit probe reaction time task. The results of the experiments were used to test 4 quantitative cognitive models. The models share the general assumption that observations can activate and inhibit explanations in memory. They vary with respect to how newly incoming observations affect the availability of explanations over time. The data of both experiments were predicted best by a model in which all observations in working memory have the same potential to activate explanations from long-term memory and in which these observations do not decay. The results illustrate the power of memory activation processes and show where additional deliberate reasoning strategies might come into play.
    • "For instance, in the medical context, a complete understanding of diagnostic reasoning can help to save lives by improving the process of forming the right diagnosis (Mehlhorn, Taatgen, Lebiere, & Krems, 2011). But there are more applications such as finding the error in a technical system like a car or a computer (Johnson & Krems, 2001; Krems & Zierer, 1994; Mehlhorn et al., 2011). For instance, imagine you experience a loss in power of your car. "
    [Show abstract] [Hide abstract] ABSTRACT: When finding a best explanation for observed symptoms a multitude of information has to be integrated and matched against explanations stored in memory. Although assumptions about ongoing memory processes can be derived from the process models, little process data exists that would allow to sufficiently test these assumptions. In order to explore memory processes in diagnostic reasoning, 29 participants were asked to solve a visual reasoning task (the Black Box paradigm) where critical information had to be retrieved from memory. This study focused on differentiating between processes that take place during the encoding and the evaluation of symptom information by comparing eye movement measures (the number of fixation and fixation duration per dwell). Results will be discussed in light of existing theories on sequential diagnostic reasoning. Further, it will be discussed to which extent eye movements can be informative about memory processes underlying sequential diagnostic reasoning.
    Full-text · Conference Paper · Aug 2016 · Journal of Cognitive Engineering and Decision Making
    • "To provide a thorough assessment of internal and external validity and evidence for the alignment of the theories of reasoning and cognition to elements of the theory-integrated ADS depicting the medical diagnostician's work domain (Figures 2 and 3), the cognitive architecture (Byrne, 2005) provided by the ADS model should be implemented as a simulated computer program. This will allow researchers to compare results from the simulated ADS model of diagnosis to diagnostic performance of practicing clinicians (e.g., see Mehlhorn, Taatgen, Lebiere, & Krems, 2011). If the computer-simulated ADS model is able to predict the diagnostic performance resulting from practicing clinicians, this will provide substantial evidence favoring the ADS model as a valid depiction of medical diagnosis. "
    [Show abstract] [Hide abstract] ABSTRACT: Recent research investigating diagnosis has generally relied upon one of two approaches to categorize and assess the antecedents of diagnostic error: (a) describing diagnostic error as a result of flaws in human cognition or (b) explaining diagnostic error as a result of working with complex health information systems. Each approach has uncovered important features that promote diagnostic error. However, each approach has inherent limitations, and integrating results from one approach to the other has proved difficult. In the current study, a cognitive engineering technique known as work domain analysis was implemented to provide a framework for uncovering the relationship between diagnosis, complex health systems, and theories of cognition and reasoning. The resulting model of diagnosis provides a comprehensive, novel perspective of the diagnostic process that offers a new foundation to formulate empirical inquiries about diagnosis and provides new avenues for the design and development of health information technologies, assessment strategies, and diagnosis-centered simulation paradigms.
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    • "The reasoning task was to determine the most likely cause of a patient's symptoms. The patients were workers in a chemical plant that produces four chemicals and each worker was affected by exactly one of those chemicals (Mehlhorn, Taatgen, Lebiere, & Krems, 2011). "
    Full-text · Conference Paper · Apr 2015 · Journal of Cognitive Engineering and Decision Making
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