Background: Certification in infection control (CIC) is a standardized indicator of the knowledge and competencies essential for effective infection prevention practice. Evidence measuring success of training programs for certfication in infection control is limited.
Methods: From 2017 through 2023, 51 novice infection preventionists (IPs) were enrolled in a training program that combined didactic learning, application of knowledge in practice, and mentorship from advanced-practice and near-peer IPs. Participants were tracked through completion of certification examination and pass rates were compared with rates for 2023 CIC candidates.
Results: All participants engaged in the training program attempted the CIC examination. The training group had a pass rate of 98%. This is 27% higher than the most recent rate published by Certification Board of Infection Control and Epidemiology (CBIC) of 71%.
Discussion: Participants were significantly more likely to pass the CIC exam on the first try, showing that a supported, competency-based training program can be successful in supporting novice IPs in certification success.
Conclusions: Building foundational knowledge on key concepts in infection prevention and control and enhancing learning through supervised, direct application of skills improves CIC certification exam pass rates and supports progression of early career IPs to more independent practice.
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http://dx.doi.org/10.1016/j.ajic.2024.07.015 | DOI Listing |
Sci Rep
December 2024
School of Physical Education, Southwest Petroleum University, Chengdu, 610500, China.
Stroke is one of the leading causes of death in developing countries, and China bears the largest global burden of stroke. This study aims to investigate the relationship between different dimensions of physical activity levels and stroke risk using a nationally representative database. We performed a cross-sectional analysis using data from the China Health and Retirement Longitudinal Study (CHARLS) 2020.
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December 2024
Merchant Marine College, Shanghai Maritime University, Shanghai, 201306, China.
The intelligent identification of wear particles in ferrography is a critical bottleneck that hampers the development and widespread adoption of ferrography technology. To address challenges such as false detection, missed detection of small wear particles, difficulty in distinguishing overlapping and similar abrasions, and handling complex image backgrounds, this paper proposes an algorithm called TCBGY-Net for detecting wear particles in ferrography images. The proposed TCBGY-Net uses YOLOv5s as the backbone network, which is enhanced with several advanced modules to improve detection performance.
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December 2024
Trauma Nursing Research Center, Kashan University of Medical Sciences, Kashan, Iran.
This study aimed to investigate comfort and its related factors in clinical nurses working in teaching hospitals of Kashan University of Medical Sciences in Iran. In this cross-sectional study, 300 nurses were selected by stratified random sampling method (2022). Data were collected using the Persian version of the nurse comfort questionnaire and a questionnaire of possible related factors.
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December 2024
Department of Production Engineering, KTH Royal Institute of Technology, 11428, Stockholm, Sweden.
This study investigates the implementation of collaborative route planning between trucks and drones within rural logistics to improve distribution efficiency and service quality. The paper commences with an analysis of the unique characteristics and challenges inherent in rural logistics, emphasizing the limitations of traditional methods while highlighting the advantages of integrating truck and drone technologies. It proceeds to review the current state of development for these two technologies and presents case studies that illustrate their application in rural logistics.
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December 2024
College of Mechanical and Electronic Engineering, Dalian Minzu University, Dalian, 116650, Liaoning, China.
The novel coronavirus (COVID-19) has affected more than two million people of the world, and far social distancing and segregated lifestyle have to be adopted as a common solution in recent years. To solve the problem of sanitation control and epidemic prevention in public places, in this paper, an intelligent disinfection control system based on the STM32 single-chip microprocessor was designed to realize intelligent closed-loop disinfection in local public places such as public toilets. The proposed system comprises seven modules: image acquisition, spraying control, disinfectant liquid level control, access control, voice broadcast, system display, and data storage.
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