Background: Previous studies of face trustworthiness have often examined isolated face stimulus, ignoring the role of context.
Purpose: The current study used mouse-tracking technique and the seven-point Likert scale to examine the effect of emotional visual context on face trustworthiness judgment at the levels of the early evaluation process and final evaluation result.
Methods: Experiment 1 used mouse-tracking technique to study the impact of different contexts on the judgment of face trustworthiness at the early evaluation process. Experiment 2 used the seven-point Likert scale to study the effect of different contexts on the judgment of face trustworthiness at the final evaluation result.
Results: Experiment 1 found that when faces are embedded in threatening negative contexts, the mouse trajectories are more tortuous for trustworthy responses and straighter for untrustworthy responses than in neutral contexts. When faces are embedded in non-threatening negative contexts, the mouse trajectories are more tortuous for trustworthy responses but did not significantly differ for untrustworthy responses than in neutral contexts. When faces are embedded in positive contexts, the mouse trajectories are straighter for trustworthy responses and more tortuous for untrustworthy responses than in neutral contexts. Experiment 2 found that faces embedded in threatening and non-threatening negative contexts have lower scores and faces embedded in positive contexts have higher scores than in neutral contexts.
Conclusion: The results show that the emotional visual context significantly influences the judgment of face trustworthiness both at the levels of the early evaluation process and final evaluation result.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7667160 | PMC |
http://dx.doi.org/10.2147/PRBM.S269543 | DOI Listing |
J Exp Psychol Gen
January 2025
Department of Cognitive and Psychological Sciences, Brown University.
Faces-the most common and complex stimuli in our daily lives-contain multidimensional information used to infer social attributes that guide consequential behaviors, such as deciding who to trust. Decades of research illustrates that perceptual information from faces is processed holistically. An open question, however, is whether goals might impact this perceptual process, influencing the encoding and representation of the complex social information embedded in faces.
View Article and Find Full Text PDFBMC Pediatr
January 2025
School of Public Health, College Of Health Sciences and Medicine, Dilla University, Dilla, Ethiopia.
Nat Commun
January 2025
Department of Chemistry, Theoretical Chemistry Institute, University of Wisconsin-Madison, Madison, WI, 53706, USA.
Identifying transitional states is crucial for understanding protein conformational changes that underlie numerous biological processes. Markov state models (MSMs), built from Molecular Dynamics (MD) simulations, capture these dynamics through transitions among metastable conformational states, and have demonstrated success in studying protein conformational changes. However, MSMs face challenges in identifying transition states, as they partition MD conformations into discrete metastable states (or free energy minima), lacking description of transition states located at the free energy barriers.
View Article and Find Full Text PDFJ Med Radiat Sci
December 2024
Department of Radiography, School of Allied Health Sciences, Faculty of Health Sciences and Veterinary Medicine, University of Namibia, Windhoek, Namibia.
Introduction: Clinical training is crucial for diagnostic radiography students, bridging theoretical knowledge with practical skills. In resource-constrained settings, this training may face unique challenges that might significantly impact learning outcomes and future practice. Despite its importance, the experiences of diagnostic radiography students during clinical placements remain understudied, particularly in Sub-Saharan Africa.
View Article and Find Full Text PDFJ Pers Med
November 2024
Department of Radiation Oncology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea.
Large language models (LLMs) show promise in healthcare but face challenges with hallucinations, particularly in rapidly evolving fields like diabetes management. Traditional LLM updating methods are resource-intensive, necessitating new approaches for delivering reliable, current medical information. This study aimed to develop and evaluate a novel retrieval system to enhance LLM reliability in diabetes management across different languages and guidelines.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!