Introduction: Discrimination toward ethnic minorities is a persistent societal problem. One reason behind this is a bias in trust: people tend to trust their ingroup and comparatively distrust outgroups.
Methods: In this study, we investigated whether and how people change their explicit trust bias with respect to ethnicity based on behavioral interactions with in- and outgroup members in a modified Trust Game.
Results: Subjects' initial explicit trust bias disappeared after the game. The change was largest for ingroup members who behaved unfairly, and the reduction of trust bias generalized to a small sample of new in- and outgroup members. Reinforcement learning models showed subjects' learning was best explained by a model with only one learning rate, indicating that subjects learned from trial outcomes and partner types equally during investment.
Discussion: We conclude that subjects can reduce bias through simple learning, in particular by learning that ingroup members can behave unfairly.
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http://dx.doi.org/10.3389/fpsyg.2023.1139128 | DOI Listing |
J Pediatr Surg
December 2024
Pediatric Surgery, Dipartimento di Medicina di Precisione e Rigenerativa a Area Jonica, Azienda Ospedaliera-Universitaria Consorziale Ospedale Pediatrico Giovanni XXIII, Bari, Italy.
Background And Aims: Image Defined Risk Factors (IDRFs) assess surgical risk in neuroblastoma (NB) and guide neoadjuvant therapy. Despite chemotherapy IDRFs may persist in 70 % of cases. Several studies have suggested that not all IDRFs hold equal significance and that the presence of an IDRF does not inherently signify unresectability.
View Article and Find Full Text PDFJ Pers Med
December 2024
Department of Medical Education, Catolica Medical School, Universidade Católica Portuguesa, 1649-023 Oeiras, Portugal.
Transcranial Magnetic Stimulation-Electroencephalography (TMS-EEG) is a non-operative technique that allows for magnetic cortical stimulation (TMS) and analysis of the electrical currents generated in the brain (EEG). Despite the regular utilization of both techniques independently, little is known about the potential impact of their combination in neurosurgical practice. This scoping review, conducted following PRISMA guidelines, focused on TMS-EEG in epilepsy, neuro-oncology, and general neurosurgery.
View Article and Find Full Text PDFFront Psychol
December 2024
Department of Communication and Media, University of Liverpool, Liverpool, United Kingdom.
In the fast-paced, densely populated information landscape shaped by digitization, distinguishing information from misinformation is critical. Fact-checkers are effective in fighting fake news but face challenges such as cognitive overload and time pressure, which increase susceptibility to cognitive biases. Establishing standards to mitigate these biases can improve the quality of fact-checks, bolster audience trust, and protect against reputation attacks from disinformation actors.
View Article and Find Full Text PDFCureus
November 2024
Cardiology, University of Arizona College of Medicine, Phoenix, USA.
Artificial intelligence (AI) and machine learning (ML) have become critical components in the transformation of healthcare. They offer enhanced diagnostic accuracy, personalized treatment plans, and support for clinical decision-making. However, with these advancements come significant ethical challenges, including concerns around transparency, bias, data privacy, and the potential displacement of healthcare professionals.
View Article and Find Full Text PDFTransfusion
December 2024
Department of Cardiovascular Sciences, Unit Anesthesiology and Algology, Biomedical Sciences Group, University of Leuven (KU Leuven), Leuven, Belgium.
Objectives: Identifying cardiac surgical patients at risk of requiring red blood cell (RBC) transfusion is crucial for optimizing their outcome. We critically appraised prognostic models preoperatively predicting perioperative exposure to RBC transfusion in adult cardiac surgery and summarized model performance.
Methods: Design: Systematic review and meta-analysis.
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