Research suggests that individuals with conduct disorder (CD) are marked by social impairments, such as difficulties in processing the affective reactions of others. Little is known, though, about how they make decisions during social interactions in response to emotional expressions of others. In this study, we therefore investigated the neural mechanisms underlying fairness decisions in response to communicated emotions of others in aggressive, criminal justice-involved boys with CD (N = 32) compared with typically developing (TD) boys (N = 33), aged 15-19 years. Participants received written emotional responses (angry, disappointed or happy) from peers in response to a previous offer and then had to make fairness decisions in a version of the Dictator Game. Behavioral results showed that CD boys did not make differential fairness decisions in response to the emotions, whereas the TD boys did show a differentiation and also responded more unfair to happy reactions than the CD boys. Neuroimaging results revealed that when receiving happy vs disappointed and angry reactions, the CD boys showed less activation than the TD boys in the temporoparietal junction and supramarginal gyrus, regions involved in perspective taking and attention. These results suggest that boys with CD have difficulties with processing explicit emotional cues from others on behavioral and neural levels.
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http://dx.doi.org/10.1093/scan/nsv150 | DOI Listing |
Health Sci Rep
January 2025
Department of Research The Medical Research Circle (MedReC) Goma Democratic Republic of the Congo.
Background And Aim: Epilepsy is a major neurological challenge, especially for pediatric populations. It profoundly impacts both developmental progress and quality of life in affected children. With the advent of artificial intelligence (AI), there's a growing interest in leveraging its capabilities to improve the diagnosis and management of pediatric epilepsy.
View Article and Find Full Text PDFBMC Med Inform Decis Mak
January 2025
Department of Clinical Pharmacy and Translational Science, The University of Tennessee Health Science Center, Memphis, TN, USA.
Background: The COVID-19 pandemic has highlighted the crucial role of artificial intelligence (AI) in predicting mortality and guiding healthcare decisions. However, AI models may perpetuate or exacerbate existing health disparities due to demographic biases, particularly affecting racial and ethnic minorities. The objective of this study is to investigate the demographic biases in AI models predicting COVID-19 mortality and to assess the effectiveness of transfer learning in improving model fairness across diverse demographic groups.
View Article and Find Full Text PDFHealth Econ Policy Law
January 2025
Health Systems Program, Department of International Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.
The framework presented in the World Bank report Open and Inclusive: Fair processes for Financing Universal Health Coverage effectively connects proposed decision-making principles with practical examples that country governments can use to pursue greater fairness. In this commentary, we consider the suggestion that international development partners might use the report's criteria to examine their own processes. We consider what the report's primary Fair Process principles - equality, impartiality and consistency - imply for development partners.
View Article and Find Full Text PDFHealth Econ Policy Law
January 2025
Norwegian Institute of Public Health, Oslo, Norway.
In response to our critics, we clarify and defend key ideas in the report . First, we argue that procedural fairness has greater value than Dan Hausman allows. Second, we argue that the Report aligns with John Kinuthia's view that a knowledgeable public and a capable civil society, alongside good facilitation, are important for effective public deliberation.
View Article and Find Full Text PDFJ Public Health Policy
January 2025
Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Australia.
Evidence-informed policymaking emphasizes that policy decisions should be informed by the best available evidence from research and follow a systematic and transparent approach. For public health policymaking we can learn from existing practices of transparent, evidence-informed decision-making for clinical practice, medicines, and medical technology. We review existing evidence-to-decision frameworks, as well as frameworks and theories for policymaking to address the political dimension of policymaking, and use this analysis to propose an integrated framework to guide evidence-informed policymaking.
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