As part of our continuing effort to highlight innovative approaches to improving the health and environment of communities, the is pleased to publish a bimonthly column from the Agency for Toxic Substances and Disease Registry (ATSDR). ATSDR is a federal public health agency of the U.S. Department of Health and Human Services (HHS) and shares a common office of the Director with the National Center for Environmental Health (NCEH) at the Centers for Disease Control and Prevention (CDC). ATSDR serves the public by using the best science, taking responsive public health actions, and providing trusted health information to prevent harmful exposures and diseases related to toxic substances. The purpose of this column is to inform readers of ATSDR's activities and initiatives to better understand the relationship between exposure to hazardous substances in the environment and their impact on human health and how to protect public health. We believe that the column will provide a valuable resource to our readership by helping to make known the considerable resources and expertise that ATSDR has available to assist communities, states, and others to assure good environmental health practice for all is served. The conclusions of this column are those of the author(s) and do not necessarily represent the views of ATSDR, CDC, or HHS. Kevin Horton is chief of the Environmental Health Surveillance Branch within the Division of Toxicology and Human Health Sciences at ATSDR. Wendy Kaye is a senior epidemiologist at McKing Consulting Corporation. Laurie Wagner is a research associate at McKing Consulting Corporation.
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J Med Internet Res
January 2025
Department of Clinical Pharmacy, College of Pharmacy, University of Michigan, Ann Arbor, MI, United States.
Background: Clinical decision support systems leveraging artificial intelligence (AI) are increasingly integrated into health care practices, including pharmacy medication verification. Communicating uncertainty in an AI prediction is viewed as an important mechanism for boosting human collaboration and trust. Yet, little is known about the effects on human cognition as a result of interacting with such types of AI advice.
View Article and Find Full Text PDFJMIR Res Protoc
January 2025
University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States.
Background: Black adults in the United States experience disproportionately high rates of tobacco- and obesity-related diseases, driven in part by disparities in smoking cessation and physical activity. Smartphone-based interventions with financial incentives offer a scalable solution to address these health disparities.
Objective: This study aims to assess the feasibility and preliminary efficacy of a mobile health intervention that provides financial incentives for smoking cessation and physical activity among Black adults.
J Med Internet Res
January 2025
NORC at the University of Chicago, Chicago, IL, United States.
Background: Poor health outcomes are well documented among patients with a non-English language preference (NELP). The use of interpreters can improve the quality of care for patients with NELP. Despite a growing and unmet need for interpretation services in the US health care system, rates of interpreter use in the care setting are consistently low.
View Article and Find Full Text PDFStress Health
February 2025
Collaborative Innovation Center of Assessment Toward Basic Education Quality, Beijing Normal University, Beijing, China.
This study explored the structure and temporal evolution of the relationship among depression, maladaptive cognition, and internet addiction (DMI) among university students by focusing on topological and dynamic properties in a network analysis. A 3-year longitudinal survey was conducted with 873 university students (M = 18.32, SD = 0.
View Article and Find Full Text PDFJAMA Health Forum
January 2025
Department of Health Policy and Management, Harvard T. H. Chan School of Public Health, Boston, Massachusetts.
Importance: Skilled nursing facilities (SNFs) experienced high mortality during the COVID-19 pandemic, leading them to adopt preventive measures to counteract viral spread. A critical appraisal of these measures is essential to support SNFs in managing future infectious disease outbreaks.
Objective: To perform a scoping review of data and evidence on the use and effectiveness of preventive measures implemented from 2020 to 2024 to prevent COVID-19 infection in SNFs in the US.
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