Valerie F. Reyna

Fuzzy-trace theory: An interim synthesis

Abstract We review the current status of fuzzy-trace theory. The presentation is organized around five topics. First, theoretical ideas that immediately preceded the development of fuzzy-trace theory are sketched. Second, experimental findings that challenged those ideas (e.g., memory-reasoning independence, the intuitive nature of mature reasoning) are summarized. Third, the core assumptions that comprised the initial version of fuzzy-trace theory are described. Fourth, some modifications to those assumptions are explored that were necessitated by subsequent experimental findings. Fifth, four areas of experimentation are considered in which research under the aegis of fuzzy-trace theory is in progress: (a) suggestibility and false memories; (b) judgment and decision making; (c) the development of forgetting; and (d) the development of retrieval.

How Numeracy Influences Risk Comprehension and Medical Decision Making

We review the growing literature on health numeracy, the ability to understand and use numerical information, and its relation to cognition, health behaviors, and medical outcomes. Despite the surfeit of health information from commercial and noncommercial sources, national and international surveys show that many people lack basic numerical skills that are essential to maintain their health and make informed medical decisions. Low numeracy distorts perceptions of risks and benefits of screening, reduces medication compliance, impedes access to treatments, impairs risk communication (limiting prevention efforts among the most vulnerable), and, based on the scant research conducted on outcomes, appears to adversely affect medical outcomes. Low numeracy is also associated with greater susceptibility to extraneous factors (i.e., factors that do not change the objective numerical information). That is, low numeracy increases susceptibility to effects of mood or how information is presented (e.g., as frequencies vs. percentages) and to biases in judgment and decision making (e.g., framing and ratio bias effects). Much of this research is not grounded in empirically supported theories of numeracy or mathematical cognition, which are crucial for designing evidence-based policies and interventions that are effective in reducing risk and improving medical decision making. To address this gap, we outline four theoretical approaches (psychophysical, computational, standard dual-process, and fuzzy trace theory), review their implications for numeracy, and point to avenues for future research.

How People Make Decisions That Involve Risk A Dual-Processes Approach

Many health and safety problems, including war and terrorism, are by-products of how people reason about risk. I describe a new approach to reasoning about risk that implements a modern dual-process model of memory called fuzzy-trace theory. This approach posits encoding of both verbatim and gist representations, with reliance on the latter whenever possible; dependence of reasoning on retrieval cues that access stored values and principles; and vulnerability of reasoning to processing interference from overlapping classes of events, which causes denominator neglect in risk or probability judgments. These simple principles explain classic and new findings, for example, the finding that people overestimate small risks but ignore very small risks. Fuzzy-trace theory differs from other dual-process approaches to reasoning in that it places intuition at the apex of development, considering fuzzy intuitive processing more advanced than precise computational processing (e.g., trading off risks and rewards). The theory supplies a conception of rationality that distinguishes degrees of severity of errors in reasoning. It also includes a mechanism for achieving consistency in reasoning, a hallmark of rationality, by explaining how a person can treat superficially different reasoning problems in the same way if the problems share an underlying gist.

Fuzzy-Trace Theory and False Memory

A key problem confronting theories of false memory is that false-memory phenomena are so diverse: Some are characteristic of controlled laboratory tasks, others of everyday life; some occur for traumatic events with legal consequences, others for innocuous events; some are characteristic of one developmental level, others of another developmental level. Fuzzy-trace theory explains false memories via a small set of principles that implement a single representational distinction. Those principles generate new predictions, some of which are counterintuitive.

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

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.

Gist is the grist: Fuzzy-trace theory and the new intuitionism☆

Abstract Fuzzy-trace theory is a gist-driven interpretation of cognitive development that has descended from, but is distinctly different than, the Piagetian and information-processing traditions. Intuition, rather than deductive logic or computing machinery, is taken as the operative metaphor for cognition, where intuition is defined as it is in the foundations of mathematics—namely, as a fuzzy concept in combination with a construction rule. The theory is orchestrated around seven basic principles: (a) gist extraction; (b) fuzzy-to-verbatim continua; (c) the fuzzy-processing preference (intuition); (d) reconstruction in short- and long-term memory; (e) output interference; (f) resource freedom; and (g) ontogenesis. These principles are illustrated with developmental findings from such familiar reasoning paradigms as class inclusion, framing, mental arithmetic, probability judgment, and transitive inference.

Developmental Reversals in False Memory: A Review of Data and Theory

Can susceptibility to false memory and suggestion increase dramatically with age? The authors review the theoretical and empirical literatures on this counterintuitive possibility. Until recently, the well-documented pattern was that susceptibility to memory distortion had been found to decline between early childhood and young adulthood. That pattern is the centerpiece of much expert testimony in legal cases involving child witnesses and victims. During the past 5 years, however, several experiments have been published that test fuzzy-trace theorys prediction that some of the most powerful forms of false memory in adults will be greatly attenuated in children. Those experiments show that in some common domains of experience, in which false memories are rooted in meaning connections among events, age increases in false memory are the rule and are sometimes accompanied by net declines in the accuracy of memory. As these experiments are strongly theory-driven, they have established that developmental improvements in the formation of meaning connections are necessary and sufficient to produce age increases in false memory.

Clinical Implications of Numeracy: Theory and Practice

BackgroundLow numeracy is pervasive and constrains informed patient choice, reduces medication compliance, limits access to treatments, impairs risk communication, and affects medical outcomes; therefore, it is incumbent upon providers to minimize its adverse effects.PurposeWe provide an overview of research on health numeracy and discuss its implications in clinical contexts.ConclusionsLow numeracy cannot be reliably inferred on the basis of patients’ education, intelligence, or other observable characteristics. Objective and subjective assessments of numeracy are available in short forms and could be used to tailor health communication. Low scorers on these assessments are subject to cognitive biases, irrelevant cues (e.g., mood), and sharper temporal discounting. Because prevention of the leading causes of death (e.g., cancer and cardiovascular disease) depends on taking action now to prevent serious consequences later, those low in numeracy are likely to require more explanation of risk to engage in prevention behaviors. Visual displays can be used to make numerical relations more transparent, and different types of displays have different effects (e.g., greater risk avoidance). Ironically, superior quantitative processing seems to be achieved by focusing on qualitative gist and affective meaning, which has important implications for empowering patients to take advantage of the evidence in evidence-based medicine.

The Development of forgetting and reminiscence

Many theoretical positions on memory development anticipate that forgetting rates should vary substantially with age. The nature of these age variations is also relevant to many applied questions about child development that have major social policy implications, such as the veracity of childrens eyewitness testimony and the long-term effectiveness of classroom instruction. Surprisingly, developmental studies of long-term retention have repeatedly produced the puzzling finding that forgetting rates are age invariant. It now seems, however, that these null age trends may have been artifacts of variables such as measurement insensitivity, floor effects, and stages-of-learning confounds. Assuming, as some later studies suggest, that forgetting rates vary with age when these factors are controlled, there are three overriding questions that must be dealt with in the developmental analysis of forgetting: the relative importance of storage failure versus retrieval failure, the relative importance of true forgetting processes versus test-induced processes, and the relative importance of storage-based reminiscence versus retrieval-based reminiscence. We describe a framework (disintegration/redintegation theory) that provides a conceptual environment within which research on these questions can progress. This framework, which evolved from fuzzy-trace theory, reinterprets processes such as storage failure, retrieval failure, restorage, and retrieval relearning in terms of levels of featural integration in traces (i.e., the extent to which contextual information is integrated with core semantic gist to produce a coherent representation). The theory is implemented in a mathematical model (the trace-integrity model) whose parameters deliver measurements of relevant memory processes on a common ratio scale. In a series of experiments, the model was used to study the theorys predictions about the contributions of these memory processes to long-term retention in subjects between the ages of 7 and 70. All the experiments were standard long-term retention designs (an initial acquisition session, followed by a 1-2-week forgetting interval, followed by a series of retention tests).(ABSTRACT TRUNCATED AT 400 WORDS)

Physician decision making and cardiac risk: Effects of knowledge, risk perception, risk tolerance, and fuzzy processing

Despite training, professionals sometimes make serious errors in risky decision making. The authors investigated judgments and decisions for 9 hypothetical patients at 3 levels of cardiac risk, comparing student and physician groups varying in domain-specific knowledge. Decisions were examined regarding whether they deviated from guidelines, how risk perceptions and risk tolerances determined decisions, and how the latter differed for knowledge groups. More knowledgeable professionals were better at discriminating levels of risk according to external correspondence criteria but committed similar errors in disjunctive probability judgments, violating internal coherence criteria. Also, higher knowledge groups relied on fewer dimensions of information than did lower knowledge groups. Consistent with fuzzy-trace theory, experts achieved better discrimination by processing less information and made sharper all-or-none distinctions among decision categories.