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Ann Intern Med
January 2025
959 Medical Operations Squadron, U.S. Air Force, Department of Neurology, Brooke Army Medical Center, San Antonio, Texas (T.K.).
Description: In July 2024, the U.S. Department of Veterans Affairs (VA) and U.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Division of Nephrology and Endocrinology, The University of Tokyo, Tokyo, Japan.
JMIR Form Res
January 2025
Division of Psychology, School of Health, Care and Social Welfare, Mälardalen University, Västerås/Eskilstuna, Sweden.
Background: Having a great amount of sedentary time is common among older adults and increases with age. There is a strong need for tools to reduce sedentary time and promote adherence to reduced sedentary time, for which eHealth interventions have the potential to be useful. Interventions for reducing sedentary time in older adults have been found to be more effective when elements of self-management are included.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, ON, Canada.
Current literature is unclear on the safety and optimal timing of delivery for pregnant individuals with gestational diabetes mellitus, which inspired our study team to conduct a web-based survey study exploring patient and provider opinions on delivery options. However, an incident of fraudulent activity with survey responses prompted a shift in the focus of the research project. Unfortunately, despite the significant rise of web-based surveys used in medical research, there remains very limited evidence on the implications of and optimal methods to handle fraudulent web-based survey responses.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
School of Computer Science, University of Technology Sydney, Sydney, Australia.
The integration of artificial intelligence (AI) into health communication systems has introduced a transformative approach to public health management, particularly during public health emergencies, capable of reaching billions through familiar digital channels. This paper explores the utility and implications of generalist conversational artificial intelligence (CAI) advanced AI systems trained on extensive datasets to handle a wide range of conversational tasks across various domains with human-like responsiveness. The specific focus is on the application of generalist CAI within messaging services, emphasizing its potential to enhance public health communication.
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