Burnout among surgeons before and during the SARS-CoV-2 pandemic: an international survey

Background: SARS-CoV-2 pandemic has had many significant impacts within the surgical realm, and surgeons have been obligated to reconsider almost every aspect of daily clinical practice. Methods: This is a cross-sectional study reported in compliance with the CHERRIES guidelines and conducted through an online platform from June 14th to July 15th, 2020. The primary outcome was the burden of burnout during the pandemic indicated by the validated Shirom-Melamed Burnout Measure. Results: Nine hundred fifty-four surgeons completed the survey. The median length of practice was 10 years; 78.2% included were male with a median age of 37 years old, 39.5% were consultants, 68.9% were general surgeons, and 55.7% were affiliated with an academic institution. Overall, there was a significant increase in the mean burnout score during the pandemic; longer years of practice and older age were significantly associated with less burnout. There were significant reductions in the median number of outpatient visits, operated cases, on-call hours, emergency visits, and research work, so, 48.2% of respondents felt that the training resources were insufficient. The majority (81.3%) of respondents reported that their hospitals were included in the management of COVID-19, 66.5% felt their roles had been minimized; 41% were asked to assist in non-surgical medical practices, and 37.6% of respondents were included in COVID-19 management. Conclusions: There was a significant burnout among trainees. Almost all aspects of clinical and research activities were affected with a significant reduction in the volume of research, outpatient clinic visits, surgical procedures, on-call hours, and emergency cases hindering the training. Trial registration: The study was registered on clicaltrials.gov "NCT04433286" on 16/06/2020

SICLOP : simulateur de commande logique et de procedes

SIGLECNRS T 57740 / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc

Proceedings of the International Conference on Natural Language Processing, Signal and Speech Processing

International audienceThis book is a collection of the articles accepted in the conference ICNLSSP 2017. The objective of this is to create a synergy between different areas related to language processing: Speech Recognition, Social Network, Opinion mining, Images, Videos,...The conference highlights new approaches related to the language from basic theories to applications. ICNLSSP is an international conference dedicated to Natural Language Processing and Speech recognition (https://isga.ma/icnlsp_web/index.php). It is a technical conference not only proposing new researches on the concerned topics but also permits exchanging ideas between researchers from the world that will be very useful for PhD students and developers in this area