COVID 19-related burnout among healthcare workers in India and ECG based predictive machine learning model: Insights from the BRUCEE- Li study

COVID 19-related burnout among healthcare workers in India and ECG based predictive machine learning model: Insights from the BRUCEE- Li study

Objectives: COVID-19 pandemic has led to unprecedented increase in rates of stress and burn out among healthcare workers (HCWs). Heart rate variability (HRV) has been shown to be reflective of stress and burnout. The present study evaluated the prevalence of burnout and attempted to develop a HRV ba...

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Auteurs principaux: Mohit D. Gupta, Manish Kumar Jha, Ankit Bansal, Rakesh Yadav, Sivasubramanian Ramakrishanan, M.P. Girish, Prattay G. Sarkar, Arman Qamar, Suresh Kumar, Satish Kumar, Ajeet Jain, Rajni Saijpaul, Vandana Gupta, Deepankar Kansal, Sandeep Garg, Sameer Arora, P.S. Biswas, Jamal Yusuf, Rajeev K. Malhotra, Vishal Batra, Sanjeev Kathuria, Vimal Mehta, Safal, Manu Kumar Shetty, Saibal Mukhopadhyay, Sanjay Tyagi, Anubha Gupta
Format: article
Langue:EN
Publié: Elsevier 2021
Sujets:
Burnout
Stress
COVID-19
Heart rate variability
Machine learning
Health care worker
Surgery
RD1-811
Diseases of the circulatory (Cardiovascular) system
RC666-701
Accès en ligne:https://doaj.org/article/b3b70a454f3644a1bc46789bb61656c4
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https://doaj.org/article/b3b70a454f3644a1bc46789bb61656c4

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