A Theory of Medical Decision Making and Health: Fuzzy Trace Theory

Departments of Human Development and Psychology, Cornell University, Ithaca, New York 14850, USA.
Medical Decision Making (Impact Factor: 3.24). 11/2008; 28(6):850-65. DOI: 10.1177/0272989X08327066
Source: PubMed


The tenets of fuzzy trace theory are summarized with respect to their relevance to health and medical decision making. Illustrations are given for HIV prevention, cardiovascular disease, surgical risk, genetic risk, and cancer prevention and control. A core idea of fuzzy trace theory is that people rely on the gist of information, its bottom-line meaning, as opposed to verbatim details in judgment and decision making. This idea explains why precise information (e.g., about risk) is not necessarily effective in encouraging prevention behaviors or in supporting medical decision making. People can get the facts right, and still not derive the proper meaning, which is key to informed decision making. Getting the gist is not sufficient, however. Retrieval (e.g., of health-related values) and processing interference brought on by thinking about nested or overlapping classes (e.g., in ratio concepts, such as probability) are also important. Theory-based interventions that work (and why they work) are presented, ranging from specific techniques aimed at enhancing representation, retrieval, and processing to a comprehensive intervention that integrates these components.

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    • "However, this account suggests that changing the absolute number of narratives reporting the occurrence of a focal event while keeping their relative proportion constant will affect judgments or decisions. A similar notion can be found in research on the ratio-bias or denominator neglect—i.e., the phenomenon that individuals tend to prefer a gamble with a 9 100 likelihood of winning over a gamble with a 1 10 likelihood, because they tend to ignore the denominator (Denes-Raj & Epstein, 1994; Reyna & Brainerd, 2008). Thus, the second goal of this paper is to clarify whether the narrative bias relies on the relative or absolute number of narratives reporting the critical event. "
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    ABSTRACT: When people judge risk or the probability of a risky prospect, single case narratives can bias judgments when a statistical base-rate is also provided. In this work we investigate various methodological and procedural factors that may influence this narrative bias. We found that narratives had the strongest effect on a non-numerical risk measure, which was also the best predictor of behavioral intentions. In contrast, two scales for subjective probability reflected primarily statistical variations. We observed a negativity bias on the risk measure, such that the narratives increased rather than decreased risk perceptions, whereas the effect on probability judgments was symmetric. Additionally, we found no evidence that the narrative bias is solely produced by adherence to conversational norms. Finally, changing the absolute number of narratives reporting the focal event, while keeping their relative frequency constant, had no effect. Thus, individuals extract a representation of likelihood from a sample of single-case narratives, which drives the bias. These results show that the narrative bias is in part dependent on the measure used to assess it and underline the conceptual distinction between subjective probability and perceived risk.
    Judgment and decision making 05/2015; 10(3):241-264. · 2.62 Impact Factor
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    • ", details ) . That is , an individual with higher gist rea - soning skills may encode details more efficiently when compared to an individual with lower gist reasoning ability ( Reyna , 2008 ) . Empirically , distinctions between higher - order and lower - level language skills have proven to be clinically informative when elucidating impair - ments in TBI ( Gamino et al . "
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    ABSTRACT: Often, standard aphasia batteries do not fully characterize higher-order cognitive-linguistic sequelae associated with a traumatic brain injury (TBI). Limited understanding and detection of complex linguistic deficits have thwarted efforts to comprehensively remediate higher-order language deficits that persist even in chronic stages of recovery post-TBI. This chapter reviews key precursor metrics that have motivated efforts to elucidate higher-order language proficiencies after a TBI. The chapter further expounds on a paradigmatic shift away from sole focus on lower level basic skills, towards a more top-down cognitive control approach to measure, retrain, and strengthen complex language abilities in TBI. The intricate relations between complex language abilities and cognitive control functions are also discussed. The concluding section offers promising directions for future research and clinical management based on new discoveries of higher-order language impairments and their modifiability in TBI populations. © 2015 Elsevier B.V. All rights reserved.
    Handbook of Clinical Neurology 02/2015; 128:497-510. DOI:10.1016/B978-0-444-63521-1.00031-5
    • "Thus , PE ratings obtained by measures consistent with our proposed definition are not affected by the depth of processing implied by some currently available measures , such as items asking how plausible a message is . For exam ple , heuristic processing can lead people to get the gist of a message , but they would not be able to comment on the plau sibility of the message ( as that would have required deeper message scrutiny ; Reyna , 2008 ) . In contrast , asking directly about likely effects on themselves would be possible . "
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    ABSTRACT: Health message quality is best understood in terms of a message's ability to effectively produce change in the variables that it was designed to change. The importance of determining a message's effectiveness in producing change prior to implementation is clear: The better a message's potential effectiveness is understood, the better able interventionists are to distinguish effective from ineffective messages before allocating scarce resources to message implementation. For this purpose, research has relied on perceived message effectiveness measures as a proxy of a message's potential effectiveness. Remarkably, however, very little conceptual work has been done on perceived message effectiveness, which renders its measures underinformed and inconsistent across studies. To encourage greater conceptual work on this important construct, we review several threats to the validity of existing measures and consider strategies for improving our understanding of perceived message effectiveness.
    Health Communication 02/2015; 30(2):125-34. DOI:10.1080/10410236.2014.974131 · 0.97 Impact Factor
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