Article

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

ABSTRACT

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.

Full-text preview

Available from: ncbi.nlm.nih.gov
  • Source
    • "The approaches of fuzzy multi-criteria decision making have been tested successfully in many real life applications, including health sciences and sustainable human well-being. For example, the fuzzy approach has been applied in medical decision making (Reyna 2008;Toress & Nieto 2006;Phuonga & Kreinovich 2001) and also in measuring quality of life (Abdullah & Md Tap 2008;Abdullah & Md Tap 2009). The method of fuzzy decision making fuzzy simple additive weight was employed by Abdullah and Jamal (2011) to weight dimensions of HRQoL. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Health Related Quality of Life (HRQoL) is one of the escalating subjects used for assessing health condition among patients who suffer specific diseases or ailments. It has been known that dimensions of HRQoL are able to mirror one’s overall health condition using mainly standard statistical technique. However, devising the extent of contribution of multiple dimensions towards overall health conditions is not straight forward as the arbitrary nature of HRQoL dimensions. Therefore this paper aims to propose a model to explain the relationship between HRQoL dimensions and overall health condition using a matrix driven fuzzy linear regression. An experiment was conducted to measure the strength of the relationship among elderly people via judgment provided by ten decision makers. The health condition linguistic data and scaled data of regularity of experiencing health-related problems among elderly people were given by the decision makers. The five stepwise computations based on matrix-driven fuzzy linear regression were proposed to describe the relationship. It is found that nearly forty six percent variations in overall health condition of elder people were explained by the eights HRQoL dimensions. The employment of matrix-driven multivariate fuzzy linear regression model has successfully identified the strength of the relationship between multi dimensions of HRQoL and overall health condition in the case of elderly people.
    Preview · Article · Dec 2015 · Modern Applied Science
  • Source
    • "However, this approach has been criticized because accurate recall does not ensure that the information can be used effectively. Rather, decisions are typically made based on gist (see, e.g., Reyna, 2008; Timmermans et al., 2004; Weinstein, 1999; Wilhelms & Reyna, 2013; Wolfe, 2006; Zikmund-Fisher, 2013). Thus, it is important to include measures of gist along with measures of verbatim understanding (e.g., Feldman-Stewart, Brundage, & Zotov, 2007; Hawley et al., 2008; Wolfe, 2006). "
    [Show abstract] [Hide abstract]
    ABSTRACT: The aim of this work is to advance knowledge of how to measure gist and verbatim understanding of risk magnitude information and to apply this knowledge to address whether graphics that focus on the number of people affected (the numerator of the risk ratio, i.e., the foreground) are effective displays for increasing (a) understanding of absolute and relative risk magnitudes and (b) risk avoidance. In 2 experiments, the authors examined the effects of a graphical display that used icons to represent the foreground information on measures of understanding (Experiments 1 and 2) and on perceived risk, affect, and risk aversion (Experiment 2). Consistent with prior findings, this foreground-only graphical display increased perceived risk and risk aversion; however, it also led to decreased understanding of absolute (although not relative) risk magnitudes. Methodologically, this work shows the importance of distinguishing understanding of absolute risk from understanding of relative risk magnitudes, and the need to assess gist knowledge of both types of risk. Substantively, this work shows that although using foreground-only graphical displays is an appealing risk communication strategy to increase risk aversion, doing so comes at the cost of decreased understanding of absolute risk magnitudes.
    Full-text · Article · Jun 2015 · Journal of Health Communication
  • Source
    • "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. "
    [Show abstract] [Hide abstract]
    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.
    Full-text · Article · May 2015 · Judgment and decision making
Show more