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Factors Influencing Telemedicine Adoption Among Health Care Professionals: Qualitative Interview Study.
JMIR Form Res
January 2025
Center for Management, University of Münster, Münster, Germany.
Background: Telemedicine is transforming health care by enabling remote diagnosis, consultation, and treatment. Despite rapid adoption during the COVID-19 pandemic, telemedicine uptake among health care professionals (HCPs) remains inconsistent due to perceived risks and lack of tailored policies. Existing studies focus on patient perspectives or general adoption factors, neglecting the complex interplay of contextual variables and trust constructs influencing HCPs' telemedicine adoption.
View Article and Find Full Text PDFThe Unrecognized Orthopedic Burden of COVID-19: Heterotopic Ossification of the Hip Joint.
Acta Orthop Belg
December 2024
COVID-19 has extensively affected the health-care organization with varying impact on different medical specialties. Long term ICU admission is associated with a less familiar complication: the formation of heterotopic ossifications (HO). In this case report we would like to emphasize the unrecognized burden of the coronavirus pandemic in patient care from the perspective of the orthopedic surgeon.
View Article and Find Full Text PDFEffectiveness of Frequent Point-of-Care Molecular COVID-19 Surveillance in a Rural Workplace: Nonrandomized Controlled Clinical Trial Among Miners.
JMIR Public Health Surveill
January 2025
Center for Global Health, University of New Mexico Health Sciences Center, Albuquerque, NM, United States.
Background: Numerous studies have assessed the risk of SARS-CoV-2 exposure and infection among health care workers during the pandemic. However, far fewer studies have investigated the impact of SARS-CoV-2 on essential workers in other sectors. Moreover, guidance for maintaining a safely operating workplace in sectors outside of health care remains limited.
View Article and Find Full Text PDFIn 2019, the novel coronavirus swept the world, exposing the monitoring and early warning problems of the medical system. Computer-aided diagnosis models based on deep learning have good universality and can well alleviate these problems. However, traditional image processing methods may lead to high false positive rates, which is unacceptable in disease monitoring and early warning.
View Article and Find Full Text PDFSurveillance of SARS-CoV-2 in Pets of Harris County, Texas, Revealed More Common Pet Infections in Households With Human COVID-19 Cases.
Vet Med Sci
March 2025
College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, Texas, USA.
Local health departments can play a critical role in zoonoses surveillance at the human-domestic animal interface, especially when existing public health services and close relationships with community groups can be leveraged. Investigators at Harris County Veterinary Public Health employed a community-based surveillance tool for identifying severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in dogs and cats in June--December 2021. Diagnosis was made using both RT-qPCR testing of oral and nasal swabs and plaque reduction neutralization testing of serum samples.
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