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The Effects of Self-Monitoring Using a Smartwatch and Smartphone App on Stress Awareness, Self-Efficacy, and Well-Being-Related Outcomes in Police Officers: Longitudinal Mixed Design Study.
JMIR Mhealth Uhealth
January 2025
Department of Learning and Workforce Development, The Netherlands Organisation for Applied Scientific Research, Soesterberg, Netherlands.
Background: Wearable sensor technologies, often referred to as "wearables," have seen a rapid rise in consumer interest in recent years. Initially often seen as "activity trackers," wearables have gradually expanded to also estimate sleep, stress, and physiological recovery. In occupational settings, there is a growing interest in applying this technology to promote health and well-being, especially in professions with highly demanding working conditions such as first responders.
View Article and Find Full Text PDFEpidemiological Features, Clinical Symptoms, and Environmental Risk Factors for Notifiable Japanese Encephalitis in Taiwan From 2008 to 2020: Retrospective Study.
JMIR Public Health Surveill
January 2025
School of Public Health, National Defense Medical Center, Taipei City, Taiwan.
Background: Japanese encephalitis (JE) is a zoonotic parasitic disease caused by the Japanese encephalitis virus (JEV), and may cause fever, nausea, headache, or meningitis. It is currently unclear whether the epidemiological characteristics of the JEV have been affected by the extreme climatic conditions that have been observed in recent years.
Objective: This study aimed to examine the epidemiological characteristics, trends, and potential risk factors of JE in Taiwan from 2008 to 2020.
Use of the FHTHWA Index as a Novel Approach for Predicting the Incidence of Diabetes in a Japanese Population Without Diabetes: Data Analysis Study.
JMIR Med Inform
January 2025
Department of Endocrinology and Metabolism, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
Background: Many tools have been developed to predict the risk of diabetes in a population without diabetes; however, these tools have shortcomings that include the omission of race, inclusion of variables that are not readily available to patients, and low sensitivity or specificity.
Objective: We aimed to develop and validate an easy, systematic index for predicting diabetes risk in the Asian population.
Methods: We collected the data from the NAGALA (NAfld [nonalcoholic fatty liver disease] in the Gifu Area, Longitudinal Analysis) database.
Musculoskeletal adverse events associated with CDK4/6 inhibitors: a real-world study using FDA Adverse Event Reporting System (FAERS) database.
BMC Pharmacol Toxicol
January 2025
Department of Pharmacy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
Objective: Cyclin-dependent kinase (CDK)-4/6 inhibitors have significantly improved outcomes in several cancers but can also induce various organ system toxicities, including musculoskeletal disorders. This study aimed to comprehensively characterize the musculoskeletal adverse events (MSAEs) associated with CDK4/6 inhibitors based on real-world data.
Methods: Reports of MSAEs linked to CDK4/6 inhibitors from the first quarter (Q1) of 2015 and 2023 Q4 were extracted from the FAERS.
Evaluation of Lyso-Gb1 as a biomarker for Gaucher disease treatment outcomes using data from the Gaucher Outcome Survey.
Orphanet J Rare Dis
January 2025
Department of Gastroenterology, Hepatology and Infectious Diseases, University Hospital, Heinrich- Heine University, Düsseldorf, Germany.
Background: Patients with Gaucher disease (GD) require continual monitoring; however, lack of specific disease biomarkers was a significant challenge in the past. Glucosylsphingosine (lyso-Gb1) has been shown to be a reliable, key, specific, and sensitive biomarker for diagnosis, prognosis, and treatment response in clinical studies of patients with GD. We evaluated the change in lyso-Gb1 concentration over time following enzyme replacement therapy in patients with confirmed GD using real-world data from the Gaucher Outcome Survey disease registry.
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