Semantic Coherence and Inconsistency in Estimating Conditional Probabilities

Two studies examined semantic coherence and internal inconsistency fallacies in conditional probability estimation. Problems reflected five distinct relationships between two sets: identical sets, mutually exclusive sets, subsets, overlapping sets, and independent sets (a special case of overlapping sets). Participants estimated P(A), P(B), P(A|B), and P(B|A). Inconsistency occurs when this constellation of estimates does not conform to Bayes' theorem. Semantic coherence occurs when this constellation of estimates is consistent with the depicted relationship among sets. Fuzzy‐trace theory predicts that people have difficulty with overlapping sets and subsets because they require class‐inclusion reasoning. On these problems, people are vulnerable to denominator neglect, the tendency to ignore relevant denominators, making the gist more difficult to discern. Independent sets are simplified by the gist understanding that P(A) provides no information about P(B), and thus, P(A|B) = P(A). The gist for identical sets is that P(A|B) = 1.0, and the gist of mutually exclusive sets is that P(A|B) = 0. In Study 1, identical, mutually exclusive, and independent sets yielded superior performance (in internal inconsistency and semantic coherence) than subsets and overlapping sets. For subsets and overlapping sets, interventions clarifying appropriate denominators generally improved semantic coherence and inconsistency, including teaching people to use Euler diagrams, 2 × 2 tables, or relative frequencies. In Study 2, with problems about breast cancer and BRCA mutations, there was a strong correlation between inconsistency in conditional probability estimation and conjunction fallacies of joint probability estimation, suggesting that similar fallacious reasoning processes produce these errors. Copyright © 2012 John Wiley & Sons, Ltd.     

Internet Safety and the Silver Surfer: The Relationship Between Gist Reasoning and Adults' Risky Online Behavior

Currently, fewer older adults are online compared with younger generations. However, with many new initiatives aiming to significantly increase the number of older internet users, they will increasingly be exposed to potential victimisation from internet fraud, a fundamental issue affecting all adult internet users. Despite this, little research has examined online risk‐taking across the adult lifespan or adults' reasoning about risky online behaviors. Using fuzzy trace theory, we investigated adults' online risk‐taking behavior and intentions, and whether these behaviors were related to different ways of reasoning about risk, namely, gist reasoning (using qualitative, intuitive knowledge) and verbatim reasoning (using quantitative, specific knowledge). Participants (326 adults, 18–79 years old, M_age = 49.54 years) reported their past risk‐taking behavior, future online risk intentions, gist and verbatim reasoning about online risk, sensation seeking, and time spent online. Age was negatively correlated with past risk‐taking, time online, future risk intentions, and sensation seeking. However, time spent online was positively related to future risk intentions, suggesting that spending more time using the internet could lead individuals to take more risks. Increased verbatim reasoning predicted increased intentions to take online risks, while gist reasoning predicted reduced intentions to take risks online. Our findings extend online risk research applying fuzzy trace theory to adolescents and young adults and suggest that online safety training incorporating gist‐based reasoning strategies could benefit all adults and, in particular, older generations. Copyright © 2017 John Wiley & Sons, Ltd.     

Coherence and correspondence criteria for rationality: experts' estimation of risks of sexually transmitted infections

The aim of this study is to examine both coherence and correspondence criteria for rationality in experts' judgments of risk. We investigated biases in risk estimation for sexually transmitted infections (STIs) predicted by fuzzy‐trace theory, i.e., that specific errors would occur despite experts' knowledge of correct responses. One hundred twenty professionals with specific knowledge of STI risks in adolescents were administered a survey questionnaire to test predictions concerning: knowledge deficits (producing underestimation of risks); gist‐based representation of risk categories (producing overestimation of condom effectiveness); retrieval failure for risk knowledge (producing lower risk estimates); and processing interference in combining risk estimates (producing biases in post‐test diagnosis of infection). Retrieval was manipulated by asking estimation questions that “unpacked” the STI category into infection types or did not specify infection types. Other questions differentiated processing biases from knowledge deficits or retrieval failure by directly providing requisite knowledge. Experts' knowledge of STI transmission and infection risks was verified empirically. Nevertheless, under predictable conditions, they misestimated risk, overestimated the effectiveness of condoms, and also suffered from processing biases. When questions provided better retrieval supports (unpacked format), risk estimates improved. Biases were linked to gist representations, retrieval failures, and processing errors, as opposed to knowledge about STIs. Results support fuzzy‐trace theory's dual‐process assumptions that different types of errors are dissociated from one another, and separate failures of coherence and correspondence among the same sample of experts. Copyright © 2005 John Wiley & Sons, Ltd.