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http://dx.doi.org/10.1136/bmj.d592 | DOI Listing |
Aust N Z J Public Health
December 2024
Curtin School of Population Health, Faculty of Health Sciences, Curtin University, Bentley, WA, 6102, Australia.
Objective: Globally, funding 'good causes' is a legitimation tactic for gambling operations. This research aimed to determine if an Australian system allowing tax concessions to not-for-profits (NFPs) meets its primary intention of funding community purpose.
Methods: Not-for-profit (NFP) venues operating electronic gaming machines (EGMs) in the state of Victoria must submit records to the gambling regulator showing contribution to community purposes.
Cent Eur J Public Health
December 2024
Department of Public Health and Hygiene, Faculty of Medicine, Pavol Jozef Safarik University in Kosice, Kosice, Slovak Republic.
Objectives: Overweight and obesity are important concerns for global health. They are characterized by excessive fat accumulation that can harm health. Childhood obesity has reached alarming levels around the world due to urbanization and changes in lifestyle.
View Article and Find Full Text PDFAlcohol Res
January 2025
Prevention Research Center, Pacific Institute for Research and Evaluation, Berkeley, California.
Purpose: Sociocultural characteristics, including race/ethnicity and socioeconomic status (SES), may affect individuals' attitudes and norms regarding alcohol use and treatment as well as their access to emerging health knowledge, innovative technologies, and general resources for improving health. As a result of these differences, as well as social determinants of health such as stigma and uneven enforcement, alcohol policies may not benefit all population subgroups equally. This review addresses research conducted within the last decade that examined differential effects of alcohol policies on alcohol consumption, alcohol harm, and alcohol treatment admissions across racial/ethnic and socioeconomic groups.
View Article and Find Full Text PDFNPJ Digit Med
January 2025
Laboratory for Computational Physiology, Massachusetts Institute of Technology, Cambridge, MA, USA.
The integration of large language models (LLMs) into electronic health records offers potential benefits but raises significant ethical, legal, and operational concerns, including unconsented data use, lack of governance, and AI-related malpractice accountability. Sycophancy, feedback loop bias, and data reuse risk amplifying errors without proper oversight. To safeguard patients, especially the vulnerable, clinicians must advocate for patient-centered education, ethical practices, and robust oversight to prevent harm.
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