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Background: Many surgeons report passion for their work, but not all tasks are likely to be satisfying. Little is known about how hospital surgeons spend their days, how they like specific tasks, and the role of core tasks (i.e. surgery-related tasks) versus tasks that may keep them from core tasks (e.g., administrative work). This study aimed at a more detailed picture of hospital surgeons' daily work - how much time they spend with different tasks, how they like them, and associations with satisfaction.
Methods: Hospital surgeons (N = 105) responded to a general survey, and 81 of these provided up to five daily questionnaires concerning daily activities and their attractiveness, as well as their job satisfaction. The data were analyzed using t-tests, analysis of variance, as well as analysis of covariance and repeated measures analysis of variance for comparing means across tasks.
Results: Among 14 tasks, surgery-related tasks took 21.2%, patient-related tasks 21.7% of the surgeons' time; 10.4% entailed meetings and communicating about patients, and 18.6% documentation and administration. The remaining time was spent with teaching, research, leadership and management, and not task-related activities (e.g. walking between rooms). Surgery was rated as most (4.25; SD = .66), administration as least attractive (2.63; SD = .78). A higher percentage of administration predicted lower perceived legitimacy; perceived legitimacy of administrative work predicted job satisfaction (r = .47). Residents were least satisfied; there were few gender differences.
Conclusions: Surgeons seem to thrive on their core tasks, most notably surgery. By contrast, administrative duties are likely perceived as keeping them from their core medical tasks. Increasing the percentage of medical tasks proper, notably surgery, and reducing administrative duties may contribute to hospital surgeons' job satisfaction.
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http://dx.doi.org/10.1186/s12893-019-0570-0 | DOI Listing |
Neural Netw
September 2025
Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen, China. Electronic address:
Automatic segmentation of retinal vessels from retinography images is crucial for timely clinical diagnosis. However, the high cost and specialized expertise required for annotating medical images often result in limited labeled datasets, which constrains the full potential of deep learning methods. Recent advances in self-supervised pretraining using unlabeled data have shown significant benefits for downstream tasks.
View Article and Find Full Text PDFRev Neurol
August 2025
Servicio de Neurología, Hospital Universitario 12 de Octubre, 28041 Madrid, Español.
Introduction: The advancement of artificial intelligence (AI), particularly generative AI, has significantly transformed the field of medicine, impacting healthcare delivery, medical education, and research. While the opportunities are substantial, the implementation of AI also raises important ethical and technical challenges, including risks related to data bias, the potential erosion of clinical skills, and concerns about information privacy.
Development: AI has demonstrated great potential in optimizing both clinical and educational processes.
J Healthc Qual Res
September 2025
Master's Program in Preventive Medicine and Public Health, Department of Preventive Medicine and Public Health, University of Granada, 18016 Granada, Spain; Biosanitary Research Institute, Ibs.Granada, 18012 Granada, Spain; Consortium for Biomedical Research in Epidemiology and Public Health (CIBERE
Background And Objective: Float nurses are frequently assigned to unfamiliar settings where they must perform a wide range of tasks, often without prior orientation, specific training, or knowledge of local protocols and equipment. Given the widespread use of floating as a staffing strategy, it is essential to allocate resources that support their integration while prioritising patient safety. This study aimed to develop a self-administered Integration Checklist for float nurses, highlighting key aspects to address before delivering direct patient care.
View Article and Find Full Text PDFOlder adulthood is associated with declines across a wide range of cognitive functions, limiting the ability to perform tasks necessary for independent living. Changes in cognitive flexibility are a promising candidate mechanism underlying age-related changes in cognition, but the causes of inflexibility in older adulthood remain elusive. Here we focus on a core feature of flexible cognition: the ability to rapidly transition between different cognitive states when required to do so by changes in the environment or our goals (e.
View Article and Find Full Text PDFLight Sci Appl
September 2025
Institute of Intelligent Photonics, Nankai University, Tianjin, China.
The rapidly growing computational demands of artificial intelligence (AI) and complex optimization tasks are increasingly straining conventional electronic architectures, driving the search for novel, energy-efficient processing paradigms. Photonic computing, which harnesses the unique properties of light to perform computation, has emerged as a compelling alternative. This perspective highlights a key advancement: a versatile nonlinear optoelectronic engine based on integrated photodetectors and micro-ring modulators (PD + MRM).
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