Aims: To investigate the cognitive processing of emotive pictorial warnings intended to curb alcohol misuse, using novel methodologies adapted from the reasoning literature to assess whether emotive pictorial warnings alter reasoning.
Method: In Study 1, individuals completed a version of the Wason selection task-evaluating warnings in which content type (Alcohol and Non-Alcohol) and emotional valence (Positive and Negative) were manipulated through imagery. In Study 2, people evaluated the certainty of outcomes described by alcohol-related and non-alcohol-related warnings in the form of If-Then statements.
Results: Study 1 found that in alcohol-related warnings, there was no difference in reasoning accuracy between positive and negative content. However, fewer correct responses followed exposure to negative general-health messages. Study 2 suggested that when a warning involves the potential consequences of drinking alcohol, accuracy is improved when the content is negative. However, when considering the consequences of abstinence, accuracy was greatest when the content was positive. This was supported by an inference by content interaction.
Conclusion: In conclusion, negative imagery should be used with caution in health warnings, and goals carefully considered. In some cases imagery of negative outcomes may improve reasoning, however, its use in alcohol-related messages does not appear to be consistently beneficial.
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http://dx.doi.org/10.1093/alcalc/agv029 | DOI Listing |
Sci Rep
January 2025
School of Computer Science and Technology, Donghua University, Shanghai, 201620, China.
Extracting high-order abstract patterns from complex high-dimensional data forms the foundation of human cognitive abilities. Abstract visual reasoning involves identifying abstract patterns embedded within composite images, considered a core competency of machine intelligence. Traditional neuro-symbolic methods often infer unknown objects through data fitting, without fully exploring the abstract patterns within composite images and the sequential sensitivity of visual sequences.
View Article and Find Full Text PDFSci Rep
January 2025
Harbin Normal University, Harbin, 150025, China.
The health status of aerospace equipment directly affects the operational capability of the entire system. Belief rule base (BRB) is an effective method for assessing health status that combines expert knowledge and historical data. However, in the actual assessment, the data provided by experts only form the basic framework of the model.
View Article and Find Full Text PDFBackgrounds: Biomedical research requires sophisticated understanding and reasoning across multiple specializations. While large language models (LLMs) show promise in scientific applications, their capability to safely and accurately support complex biomedical research remains uncertain.
Methods: We present , a novel question-and-answer benchmark for evaluating LLMs in biomedical research.
J Med Ethics
January 2025
Warren Alpert Medical School, Brown University, Providence, Rhode Island, USA.
Introduction: The integration of artificial intelligence (AI) into healthcare introduces innovative possibilities but raises ethical, legal and professional concerns. Assessing the performance of AI in core components of the United States Medical Licensing Examination (USMLE), such as communication skills, ethics, empathy and professionalism, is crucial. This study evaluates how well ChatGPT versions 3.
View Article and Find Full Text PDFJ Exp Child Psychol
January 2025
Technical University of Munich, TUM School of Social Sciences and Technology, Department of Educational Sciences, Germany. Electronic address:
Understanding fraction magnitudes is crucial for mathematical development but is challenging for many children. Visualizations, such as tape diagrams, are thought to leverage children's early proportional reasoning skills. However, depending on children's prior knowledge, these visualizations may encourage various strategies.
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