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Designing Health Recommender Systems to Promote Health Equity: A Socioecological Perspective.
J Med Internet Res
January 2025
Department High-Tech Business and Entrepreneurship Section, Industrial Engineering and Business Information Systems, University of Twente, Enschede, Overijssel, Netherlands.
Health recommender systems (HRS) have the capability to improve human-centered care and prevention by personalizing content, such as health interventions or health information. HRS, an emerging and developing field, can play a unique role in the digital health field as they can offer relevant recommendations, not only based on what users themselves prefer and may be receptive to, but also using data about wider spheres of influence over human behavior, including peers, families, communities, and societies. We identify and discuss how HRS could play a unique role in decreasing health inequities.
View Article and Find Full Text PDFCo-Designing a Digital Brief Intervention to Reduce the Risk of Prescription Opioid-Related Harm Among People With Chronic Noncancer Pain: Qualitative Analysis of Patient Lived Experiences.
JMIR Form Res
January 2025
Faculty of Medicine, The University of Queensland, Brisbane, Australia.
Background: Opioid medications are important for pain management, but many patients progress to unsafe medication use. With few personalized and accessible behavioral treatment options to reduce potential opioid-related harm, new and innovative patient-centered approaches are urgently needed to fill this gap.
Objective: This study involved the first phase of co-designing a digital brief intervention to reduce the risk of opioid-related harm by investigating the lived experience of chronic noncancer pain (CNCP) in treatment-seeking patients, with a particular focus on opioid therapy experiences.
Assessing the Adherence of ChatGPT Chatbots to Public Health Guidelines for Smoking Cessation: Content Analysis.
J Med Internet Res
January 2025
Department of Engineering Management and Systems Engineering, George Washington University, Washington, DC, United States.
Background: Large language model (LLM) artificial intelligence chatbots using generative language can offer smoking cessation information and advice. However, little is known about the reliability of the information provided to users.
Objective: This study aims to examine whether 3 ChatGPT chatbots-the World Health Organization's Sarah, BeFreeGPT, and BasicGPT-provide reliable information on how to quit smoking.
Transforming RN-Baccalaureate Education Using Insights From a National Faculty Needs Assessment.
Nurse Educ
January 2025
Author Affiliations: Arizona State University Edson College of Nursing and Health Innovation, Phoenix, Arizona (Dr Heywood); Wichita State University School of Nursing, Wichita, Kansas (Dr Williams); Southern New Hampshire University Nursing and Health Professions Department, Manchester, New Hampshire (Dr Blackwell); Bemidji State University Department of Nursing, Bemidji, Minnesota (Dr Hommes); University of Mississippi Medical Center School of Nursing, Jackson, Mississippi (Professor Franklin); and Boise State University School of Nursing, Boise, Idaho (Dr Nichols).
Background: The recent American Association of Colleges of Nursing (AACN) Essentials revision emphasizes direct clinical experiences across 4 spheres of care in RN-Baccalaureate (RN-B) education, creating challenges for online, asynchronous programs. Differentiating between prelicensure and postlicensure education complicates the integration of these requirements. Understanding RN-B faculty needs is critical for curricular transformation.
View Article and Find Full Text PDFRevised Process for ACNS Guidelines Development.
J Clin Neurophysiol
February 2025
Division of Child Neurology, Department of Neurology, Stanford University, Palo Alto, California, U.S.A.
The development of clinical practice guidelines is an evolving field. In response to the need for consistent, evidence-based medical practice, the American Clinical Neurophysiology Society identified the need to update the Society's guideline development process. The American Clinical Neurophysiology Society Guidelines Committee created an action plan with the goal of improving transparency and rigor for future guidelines and bringing existing guidelines to current standards.
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