Improving infection control competency through an online learning course.

Nurs Times

School of Community and Health Studies, Centennial College, Toronto, Canada.

Published: April 2009

Background: While most staff are aware of the basics of infection prevention and control, this can be eroded over time. In addition, it is difficult to keep up with emerging best practices.

Aim: To develop an online course to improve infection prevention and control competency and access to training.

Method: Surveys were conducted with 76 healthcare professionals, most of whom were nurses, before and after the course.

Results: Participants made significant increases in competency scores, and satisfaction with the course was high.

Discussion: A number of barriers to online learning in the workplace were identified. Organisational support in terms of protected training time, computers and internet access are essential.

Conclusion: Online learning can be an effective way for nurses to learn or refresh their skills and knowledge but needs employer support to be successful.

Download full-text PDF

Source

Publication Analysis

Top Keywords

online learning
12
control competency
8
infection prevention
8
prevention control
8
improving infection
4
infection control
4
online
4
competency online
4
learning course
4
course background
4

Similar Publications

JC polyomavirus (JCPyV) establishes a persistent, asymptomatic kidney infection in most of the population. However, JCPyV can reactivate in immunocompromised individuals and cause progressive multifocal leukoencephalopathy (PML), a fatal demyelinating disease with no approved treatment. Mutations in the hypervariable non-coding control region (NCCR) of the JCPyV genome have been linked to disease outcomes and neuropathogenesis, yet few metanalyses document these associations.

View Article and Find Full Text PDF

: Proper nutrition and hydration are essential for the health, growth, and athletic performance of student-athletes. Adequate energy availability and sufficient intake of macro- and micronutrients support adolescent development, prevent nutrient deficiencies, and reduce the risk of disordered eating. These challenges are particularly relevant to student-athletes, who are vulnerable to nutrition misinformation and often exhibit limited nutrition knowledge.

View Article and Find Full Text PDF

Higher education institutions and public health agencies in the United States (US) have recognized that food insecurity is pervasive and interferes with student learning on multiple levels. However, less research has examined food insecurity among culturally diverse college students. A cross-sectional online survey was conducted to estimate the prevalence and predictors of food insecurity for US-born White, US-born Multicultural, and International students aged 18-34 at a Midwest university.

View Article and Find Full Text PDF

Rapid heating cycle molding technology has recently emerged as a novel injection molding technique, with the uniformity of temperature distribution on the mold cavity surface being a critical factor influencing product quality. A numerical simulation method is employed to investigate the rapid heating process of molds and optimize heating power, with the positions of heating rods as variables. The temperature uniformity coefficient is an indicator used to assess the uniformity of temperature distribution within a system or process, while the thermal response rate plays a crucial role in evaluating the heating efficiency of a heating system.

View Article and Find Full Text PDF

Improving Industrial Quality Control: A Transfer Learning Approach to Surface Defect Detection.

Sensors (Basel)

January 2025

Centre of Mechanical Technology and Automation (TEMA), Department of Mechanical Engineering, University of Aveiro, 3810-193 Aveiro, Portugal.

To automate the quality control of painted surfaces of heating devices, an automatic defect detection and classification system was developed by combining deflectometry and bright light-based illumination on the image acquisition, deep learning models for the classification of non-defective (OK) and defective (NOK) surfaces that fused dual-modal information at the decision level, and an online network for information dispatching and visualization. Three decision-making algorithms were tested for implementation: a new model built and trained from scratch and transfer learning of pre-trained networks (ResNet-50 and Inception V3). The results revealed that the two illumination modes employed widened the type of defects that could be identified with this system, while maintaining its lower computational complexity by performing multi-modal fusion at the decision level.

View Article and Find Full Text PDF

Want 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!