Bullshit can be harmful to your health: Bullibility as a precursor to poor decision--making

Bullshitting is characterized by sharing information with little to no regard for truth, established knowledge, or genuine evidence. It involves the use of various rhetorical strategies to make one's statements sound knowledgeable, impressive, persuasive, influential, or confusing in order to aid bullshitters in explaining things in areas where their obligations to provide opinions exceed their actual knowledge in those domains. Distinct from gullibility (i.e., a propensity to accept a false premise in the presence of untrustworthiness cues), we highlight the research on bullibility (i.e., believing bullshit even in the face of social cues that signal something is bullshit) and its links to erroneous judgments and decisions. A deeper understanding of bullibility is critical to identifying and correcting poor decision-making.

A reassessment of the Resistance to Framing scale

Risky-choice and attribute framing effects are well-known cognitive biases, where choices are influenced by the way information is presented. To assess susceptibility to these framing types, the Resistance to Framing scale is often used, although its performance has rarely been extensively tested. In an online survey among university students from Bulgaria (N = 245) and North America (N = 261), we planned to examine the scale's psychometric properties, structural validity, and measurement invariance. However, some of these examinations were not possible because the scale displayed low and mostly non-significant inter-item correlations as well as low item-total correlations. Followingly, exploratory item response theory analyses indicated that the scale's reliability was low, especially for high levels of resistance to framing. This suggests problems with the scale at a basic level of conceptualization, namely that the items may not represent the same content domain. Overall, the scale in its current version is of limited use, at least in university student samples, due to the identified problems. We discuss potential remedies to these problems, as well as provide open code and data ( https://osf.io/j5n6f ) which facilitates testing the scale in other samples (e.g., general population, different languages and countries) to obtain a comprehensive picture of its performance.

Individual differences moderate effects in an Unusual Disease paradigm: A psychophysical data collection lab approach and an online experiment

We report two studies investigating individual intuitive-deliberative cognitive-styles and risk-styles as moderators of the framing effect in Tversky and Kahneman's famous Unusual Disease problem setting. We examined framing effects in two ways: counting the number of frame-inconsistent choices and comparing the proportions of risky choices depending on gain-loss framing. Moreover, in addition to gain-loss frames, we systematically varied the number of affected people, probabilities of surviving/dying, type of disease, and response deadlines. Study 1 used a psychophysical data collection approach and a sample of 43 undergraduate students, each performing 480 trials. Study 2 was an online study incorporating psychophysical elements in a social science approach using a larger and more heterogeneous sample, i.e., 262 participants performed 80 trials each. In both studies, the effect of framing on risky choice proportions was moderated by risk-styles. Cognitive-styles measured on different scales moderated the framing effect only in study 2. The effects of disease type, probability of surviving/dying, and number of affected people on risky choice frequencies were also affected by cognitive-styles and risk-styles but different for both studies and to different extents. We found no relationship between the number of frame-inconsistent choices and cognitive-styles or risk-styles, respectively.