Objectives: To compare the proportional representation of healthcare workers in receipt of New Year honours (NYHs) with workers in other industries and to determine whether the NYH system has gender or geographical biases.
Design: Observational study of the UK honours system with a comparative analysis of proportional representation of the UK workforce and subgroup analyses of gender and geographical representations.
Participants: Recipients of NYHs from 2009 to 2018.
Main Outcome Measures: Absolute risk of receiving an NYH based on industry, gender, or region of the UK. Relative risk of receiving an NYH for services to healthcare compared with other industries.
Results: 10 989 NYHs were bestowed from 2009 to 2018, 47% of which were awarded to women. 832 awards (7.6%) were for services to healthcare. People working in sport and in the arts and media were more likely to receive NYHs than those working in healthcare (relative risks of 22.01 (95% confidence interval 19.91 to 24.34) and 5.84 (5.31 to 6.44), respectively). There was no significant difference between the rate of receiving honours for healthcare and for science and technology (P=0.22). 34% (3741) of awards were issued to people living in London and in the southeast of England, and only 496 of 1447 (34%) higher order awards (knighthoods, damehoods, companions of honour, and commanders of the order of the British empire) were received by women.
Conclusions: In relation to the size of its workforce, a career in healthcare is not as "honourable" as careers in certain other industries. Geographical and gender biases might exist in the honours system.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7190067 | PMC |
http://dx.doi.org/10.1136/bmj.l6721 | DOI Listing |
Sensors (Basel)
January 2025
School of Information and Communication Engineering, Beijing Information Science and Technology University, Beijing 100101, China.
Human activity recognition by radar sensors plays an important role in healthcare and smart homes. However, labeling a large number of radar datasets is difficult and time-consuming, and it is difficult for models trained on insufficient labeled data to obtain exact classification results. In this paper, we propose a multiscale residual weighted classification network with large-scale, medium-scale, and small-scale residual networks.
View Article and Find Full Text PDFIsr J Health Policy Res
January 2025
Ruth and Bruce Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, POB 9907, Haifa, Israel.
Background: Workforce diversity in healthcare has been shown to improve the quality of patient care. A paucity of data exists globally on this subject in ophthalmology. The purpose of this study was to analyze nationwide trends in gender-, ethnic- and country of graduation disparities among ophthalmologists in Israel.
View Article and Find Full Text PDFSci Rep
January 2025
School of Mathematics and Systems Science, Guangdong Polytechnic Normal University, No. 293, Zhongshan Avenue West, Tianhe District, Guangzhou, 510665, China.
Due to the lack of efficient mpox diagnostic technology, mpox cases continue to increase. Recently, the great potential of deep learning models in detecting mpox and non-mpox has been proven. However, existing methods are susceptible to interference from various noises in real-world settings, require diverse non-mpox images, and fail to detect abnormal input, which makes them unsuitable for practical deployment and application.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
January 2025
Department of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125.
Cognition relies on transforming sensory inputs into a generalizable understanding of the world. Mirror neurons have been proposed to underlie this process, mapping visual representations of others' actions and sensations onto neurons that mediate our own, providing a conduit for understanding. However, this theory has limitations.
View Article and Find Full Text PDFJAMA Netw Open
January 2025
Department of Pediatrics, University of Minnesota, Minneapolis.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!