The present study made an attempt to induce fear-related reasoning biases by providing children with negative information about a novel stimulus. For this purpose, non-clinical children aged 9-12 years (N=318) were shown a picture of an unknown animal for which they received either negative, ambiguous, positive, or no information. Then children completed a series of tests for measuring various types of reasoning biases (i.e., confirmation bias and covariation bias) in relation to this animal. Results indicated that children in the negative and, to a lesser extent, the ambiguous information groups displayed higher scores on tests of fear-related reasoning biases than children in the positive and no information groups. Altogether, these results support the idea that learning via negatively tinted information plays a role in the development of fear-related cognitive distortions in youths.
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http://dx.doi.org/10.1016/j.brat.2008.12.002 | DOI Listing |
Cognition
January 2025
Minerva Fast Track Group Milestones of Early Cognitive Development, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1A, 04103 Leipzig, Saxony, Germany; Department of Liberal Arts and Sciences, University of Technology Nuremberg, Ulmenstraße 52i, 90443 Nuremberg, Germany. Electronic address:
As social beings, we excel at understanding what other people think or believe. We even seem to be influenced by the belief of others in situations where it is irrelevant to our current tasks. Such altercentric interference has been proposed to reflect implicit belief processing.
View Article and Find Full Text PDFPLoS One
January 2025
Academic Medicine Education Institute, Duke-NUS Medical School, Singapore, Singapore.
Introduction: Clinical medicine is becoming more complex and increasingly requires a team-based approach to deliver healthcare needs. This dispersion of cognitive reasoning across individuals, teams and systems (termed "distributed cognition") means that our understanding of cognitive biases and errors must expand beyond traditional "in-the-head" individual mental models and focus on a broader "out-in-the-world" context instead. To our knowledge, no qualitative studies thus far have examined cognitive biases in clinical settings from a team-based sociocultural perspective.
View Article and Find Full Text PDFSci Rep
December 2024
Potsdam University of Applied Sciences, Kiepenheuerallee 5, 14469, Potsdam, Germany.
Persuasive appeals frequently prove ineffective or produce unintended outcomes, due to the presence of motivated reasoning. Using the example of electric cars adoption, this research delves into the impact of emotional content, message valence, and the coherence of pre-existing attitudes on biased information evaluation. By conducting a factorial survey (N = 480) and incorporating a computational model of attitude formation, we aim to gain a deeper insight into the cognitive-affective mechanisms driving motivated reasoning.
View Article and Find Full Text PDFBMC Med Educ
December 2024
Department of Orthopedics, Guru Gobind Singh Medical College and Hospital, Faridkot, Punjab, 151203, India.
Generative Artificial Intelligence (AI), characterized by its ability to generate diverse forms of content including text, images, video and audio, has revolutionized many fields, including medical education. Generative AI leverages machine learning to create diverse content, enabling personalized learning, enhancing resource accessibility, and facilitating interactive case studies. This narrative review explores the integration of generative artificial intelligence (AI) into orthopedic education and training, highlighting its potential, current challenges, and future trajectory.
View Article and Find Full Text PDFPLoS One
December 2024
Département de Psychologie, Université de Montréal, Montréal, Québec, Canada.
Cognitive biases have been studied in relation to schizophrenia and psychosis for over 50 years. Yet, the quality of the evidence linking cognitive biases and psychosis is not entirely clear. This umbrella-review examines the quality of the evidence and summarizes the effect sizes of the reasoning and interpretation cognitive biases studied in relation to psychotic characteristics (psychotic disorders, psychotic symptoms, psychotic-like experiences or psychosis risk).
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