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10.4415/ANN_21_01_01 http://scihub22266oqcxt.onion/10.4415/ANN_21_01_01 33797398!ä!33797398 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 298.79999999999995 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Ann+Ist+Super+Sanita 2021 ; 57 (1): 1-6 Nephropedia Template TP {{tp|p=33797398|t=2021. COVID-19 and digital competencies among young physicians: are we (really) ready for the new era? A national survey of the Italian Young Medical Doctors Association |pdf=|usr=}}{{33797398}} gab.com Text COVID-19 and digital competencies among young physicians: are we (really) ready for the new era A national survey of the Italian Young Medical Doctors Association JO: Ann Ist Super Sanita http://www.kidney.de/pget.php?&tw=1&pmid=33797398 #FOAvip BACKGROUND: Digital health (DH) is nowadays fundamental for physicians. Despite the improvement of information and communications technology (ICT), Italian medical doctors' (MDs) education system seems inadequate in this area. Moreover, due to the COVID-19 pandemic, societies are waking up to their limitations. The aim of this paper is to analyze the Italian status quo in DH. METHODS: The Italian Young Medical Doctors Association (Segretariato Italiano Giovani Medici - SIGM) proposed a web-based survey to assess DH awareness and previous knowledge among young doctors. Investigated areas were: big data, -omics technology and predictive models, artificial intelligence (AI), internet of things, telemedicine, social media, blockchain and clinical-data storage. RESULTS: A total of 362 participants answered to the survey. Only 13% had experience in big data during clinical or research activities, 13% in -omics technology and predictive models, 13% in AI, 6% had experience in internet of things, 22% experienced at least one telemedicine tool and 23% of the participants declared that during their clinical activities data collection was paper-driven. CONCLUSIONS: Three categories of MDs, high-tech, low-tech and no-tech, can be identified from the survey-based investigation. Our survey's results indicate an urgent need for integration of pre- and post-graduation training in digital health to provide adequate medical education. Twit Text FOAVip COVID-19 and digital competencies among young physicians: are we (really) ready for the new era A national survey of the Italian Young Medical Doctors Association ????Ann Ist Super Sanita http://www.kidney.de/pget.php?&tw=1&pmid=33797398 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33797398 #FOAvip English Wikipedia <ref>{{Cite pmid|33797398}}</ref> COVID-19 and digital competencies among young physicians: are we (really) ready for the new era? A national survey of the Italian Young Medical Doctors Association #MMPMID33797398 Casa C; Marotta C; Di Pumpo M; Cozzolino A; D'Aviero A; Frisicale EM; Silenzi A; Gabbrielli F; Bertinato L; Brusaferro S Ann Ist Super Sanita 2021[Jan]; 57 (1): 1-6 PMID33797398show ga BACKGROUND: Digital health (DH) is nowadays fundamental for physicians. Despite the improvement of information and communications technology (ICT), Italian medical doctors' (MDs) education system seems inadequate in this area. Moreover, due to the COVID-19 pandemic, societies are waking up to their limitations. The aim of this paper is to analyze the Italian status quo in DH. METHODS: The Italian Young Medical Doctors Association (Segretariato Italiano Giovani Medici - SIGM) proposed a web-based survey to assess DH awareness and previous knowledge among young doctors. Investigated areas were: big data, -omics technology and predictive models, artificial intelligence (AI), internet of things, telemedicine, social media, blockchain and clinical-data storage. RESULTS: A total of 362 participants answered to the survey. Only 13% had experience in big data during clinical or research activities, 13% in -omics technology and predictive models, 13% in AI, 6% had experience in internet of things, 22% experienced at least one telemedicine tool and 23% of the participants declared that during their clinical activities data collection was paper-driven. CONCLUSIONS: Three categories of MDs, high-tech, low-tech and no-tech, can be identified from the survey-based investigation. Our survey's results indicate an urgent need for integration of pre- and post-graduation training in digital health to provide adequate medical education. |*COVID-19[MESH] |*Digital Technology/education[MESH] |*Health Knowledge, Attitudes, Practice[MESH] |*Physicians[MESH] |Cross-Sectional Studies[MESH] |Education, Medical[MESH] |Humans[MESH] |Italy[MESH] |Societies, Medical[MESH]COVID-19 and digital competencies among young physicians: are we (real(epmc).pdf DeepDyve Pubget Overpricing