Background: Although most needlestick/sharps injuries (NSIs/SIs) research focuses on health care workers (HCWs), students in hospital internships are also at risk. Investigations that examined NSIsS/SIs in student populations generally studied medical rather than nursing students (NSs). In 1999, approximately 17,000 Taiwanese nursing graduates were exposed to the hazard of NSIs/SIs. We examined the frequency and mechanism of NSIs/SIs among vocational school NSs in southern Taiwan.
Methods: Between July and December of 1999, within 1 week after the NSs completed their internship training, one of the researchers, who was a teacher in this vocational school, asked them to fill out questionnaires.
Results: Five hundred twenty-seven of 550 (92.6%) questionnaires were considered valid. Two hundred sixty-four of 527 (50.1%) responders sustained one or more NSIs/SIs. Ninety-six of 527 (18.2%) responders suffered contaminated NSIs/SIs. The average number of NSIs/SIs per student was 8.0 times/year (4.9 times/student/year for NSIs and 3.1 times/student/year for SIs). NSIs/SIs rates for NSs in 10-week and 4-week internships were significantly different ( P = .039): 53.3% versus 43.7%, respectively. The NSIs/SIs frequencies were influenced by length of internship: 7.3 times/student/year in 10-week internship and 11.7 times/student/year in 4-week internship. Logistic regression analysis indicated that length of internship rotation was statistically significant with respect to contaminated NSIs/SIs (OR = 1.682; 95% CI: 1.005-2.81; P = .048).
Conclusions: The NSIs/SIs frequencies of NSs were higher than those for HCWs. We found that frequency of NSIs/SIs for vocational school NSs is above average. Whether the young age of these NSs put them at greater risk for NSIs/SIs warrants further inquiry.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.ajic.2004.02.007 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Human Brucellosis in the Rural and Urban Population of Pakistan: Seroprevalence, Risk Factors, and Clinical Manifestations.
Curr Microbiol
January 2025
Razi Vaccine and Serum Research Institute (RVSRI), Agricultural Research, Education and Organization (AREEO), Karaj, Iran.
Brucella spp. is the bacterium responsible for brucellosis, a zoonotic infection that affects humans. This disease poses significant health challenges and contributes to poverty, particularly in developing countries.
View Article and Find Full Text PDFEffects of grape seed proanthocyanidin on emulsifying capacity of soy protein isolate in extrusion field and its underlying mechanism.
J Sci Food Agric
January 2025
College of Food Science and Technology, Bohai University, Jinzhou, China.
Background: Soy protein isolate (SPI) has poor emulsifying ability because of its low molecular flexibility and compact structure, limiting its application in extruded protein-based foods. Extrusion technology has emerged as a promising way to alter the structural properties of proteins. Therefore, the impacts of grape seed proanthocyanidin (GSP) on structural and emulsifying characteristics of SPI in extrusion field were explored in this study.
View Article and Find Full Text PDFSocioeconomic Trends in Outcomes of Rehabilitation Among Patients With Systemic Connective Tissue Disorders in Germany: A Cross-Sectional Analysis of Routine Data.
Int J Rheum Dis
January 2025
Health Services Research, Faculty of Health, School of Medicine, Witten/Herdecke University, Witten, Germany.
Objective: Various demographic factors, including sex, socioeconomic status, and immigration status, have been linked to disparities in healthcare outcomes. Despite efforts by healthcare providers to address these inequities, interventions are not always effective. The present investigation provides empirical insights from Germany focusing on patients with systemic connective tissue disorders, highlighting the need for evaluated strategies to mitigate healthcare disparities.
View Article and Find Full Text PDFRisk Assessment for Preeclampsia in the Preconception Period Based on Maternal Clinical History via Machine Learning Methods.
J Clin Med
December 2024
Health Services Vocational School, Ankara Medipol University, Ankara 06050, Türkiye.
: This study was aimed to identify the most effective machine learning (ML) algorithm for predicting preeclampsia based on sociodemographic and obstetric factors during the preconception period. : Data from pregnant women admitted to the obstetric clinic during their first trimester were analyzed, focusing on maternal age, body mass index (BMI), smoking status, history of diabetes mellitus, gestational diabetes mellitus, and mean arterial pressure. The women were grouped by whether they had a preeclampsia diagnosis and by whether they had one or two live births.
View Article and Find Full Text PDFA Survey of Deep Anomaly Detection in Multivariate Time Series: Taxonomy, Applications, and Directions.
Sensors (Basel)
January 2025
School of Computer Science, South China Normal University, Guangzhou 510555, China.
Multivariate time series anomaly detection (MTSAD) can effectively identify and analyze anomalous behavior in complex systems, which is particularly important in fields such as financial monitoring, industrial equipment fault detection, and cybersecurity. MTSAD requires simultaneously analyze temporal dependencies and inter-variable relationships have prompted researchers to develop specialized deep learning models to detect anomalous patterns. In this paper, we conducted a structured and comprehensive overview of the latest techniques in deep learning for multivariate time series anomaly detection methods.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!