98%
921
2 minutes
20
Introduction: The physical and mental health of nurses may significantly impact the entire medical care group and directly affect the quality of medical services. Due to the intense emotional involvement and often problematic working conditions that characterise their profession, nurses appear to be especially susceptible to a complex set of stressors with repercussions to their health. Several landmark studies of nurses have provided an abundance of evidence on risk factors that influence the health status of nurses. However, few studies have investigated the health status of nurses who work in high-intensity work environments in China. The National Nurse Health Study (NNHS) objective is to build an ambispective cohort to gather web-based information on early-life events, daily habits, occupational and environmental risk factors, and health outcomes of a specific subset of healthcare professionals of Chinese nurses.
Methods And Analysis: NNHS, which was developed at a tertiary hospital in Beijing, China, is a research initiative that enrolls registered nurses working at Peking University Third Hospital. A web-based self-administered system was designed to collect health-related data and link them with previous physical examination data. During the study period, participants with signed informed consent will be invited to annually repeat a similar procedure.
Ethics And Dissemination: The NNHS research protocol was approved by the Institutional Ethics Committee and provides promising data that contribute to the understanding of pathophysiological links between early-life events, body composition, gut microbiota, and inflammatory and metabolic risk profiles. Moreover, the combination of a user-friendly tool with the innovative purposes of the NNHS offers a remarkable resource to test hypotheses about mechanisms of diseases, including work stress, and further plan preventive programmes in public health.
Trial Registration Number: The study was registered on Clinicaltrials.gov (https://clinicaltrials.gov/ct2/show/NCT04572347) and the China Cohort Consortium (http://chinacohort.bjmu.edu.cn/project/102/).
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8378396 | PMC |
http://dx.doi.org/10.1136/bmjopen-2021-049958 | DOI Listing |
J Hosp Adm
January 2025
Department of Population Health, University of Cincinnati, Cincinnati, United States.
Objective: Occupational sharps and needlestick injuries (SNSI) are a significant and persistent challenge in the U.S. healthcare work environment.
View Article and Find Full Text PDFIndoor Air
January 2025
National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
Background/objectives: Respiratory viruses circulate year-round and can spread indoors via inhalation of airborne particles. Effective ventilation and filtration may reduce transmission, particularly in school settings where children and staff spend significant time. This study examines the impact of indoor air quality (IAQ) and ventilation in schools on respiratory virus detection.
View Article and Find Full Text PDFHeart Lung
September 2025
Department of Nursing, College of Medicine, National Cheng Kung University, No. 1, University Road, East District, Tainan City 70101, Taiwan. Electronic address:
Background: In-hospital mortality in patients with acute myocardial infarction (AMI) following primary percutaneous coronary intervention (pPCI) remains a significant concern. Developing a predictive model of in-hospital mortality is crucial for identifying high-risk patients, guiding clinical decisions, and preventing in-hospital mortality. Machine learning (ML) may analyze patterns in large datasets and provide accurate predictions of in-hospital mortality in AMI patients following pPCI.
View Article and Find Full Text PDFArch Cardiovasc Dis
September 2025
CIC INSERM 1410, 97410 Saint-Pierre, France; Department of Cardiology, La Réunion University Hospital, 97400 Saint-Denis, France. Electronic address:
Background: Artificial intelligence has emerged as a promising tool to optimize patient care in the field of cardiovascular medicine. However, data on its adoption and utilization by healthcare professionals are scarce.
Aim: To explore the factors that support or hinder the adoption of artificial intelligence in cardiology in France.
Nurse Educ Pract
September 2025
Department of Allied Health Education and Digital Learning, National Taipei University of Nursing and Health Sciences, Taipei, Taiwan, ROC. Electronic address:
Aim: To evaluate the effectiveness of the CARES-MFW (Clinical Augmented Reality Education Simulation for Malignant Fungating Wounds) app in enhancing nurses' knowledge and clinical reasoning in the care of MFWs.
Background: Malignant fungating wounds (MFWs) affect many patients with advanced cancer, with nearly 50 % dying within six months of diagnosis. These wounds often present with heavy exudate, pain, malodor and bleeding, leading to profound physical and psychosocial distress.