Introducing effective parameters for predicting job burnout using a self-organizing method based on group method of data handling neural network

Improved Artificial Neural Network with High Precision for Predicting Burnout among Managers and Employees of Start-Ups during COVID-19 Pandemic

(2023) Sutrisno Sutrisno et al.   Electronics

Burnout of Healthcare Workers amid the COVID-19 Pandemic: A Japanese Cross-Sectional Survey

(2021) Yoshito Nishimura et al.   International Journal of Environmental Research and Public Health

Burnout Impact of COVID-19 Pandemic on Health-Care Professionals at Assiut University Hospitals, 2020

(2021) Shimaa A. Elghazally et al.   International Journal of Environmental Research and Public Health

Predictors of Occupational Burnout: A Systematic Review

(2021) Yara Shoman et al.   International Journal of Environmental Research and Public Health

Resilience of nurses at the epicenter of the COVID-19 pandemic in Lebanon

(2021) Mohamad Alameddine et al.   International Journal of Nursing Sciences

Occurrence, prevention, and management of the psychological effects of emerging virus outbreaks on healthcare workers: rapid review and meta-analysis

(2020) Steve Kisely et al.   BMJ-British Medical Journal

Assessment of pre and post-disaster supply chain resilience based on network structural parameters with CVaR as a risk measure

(2020) Vijaya Dixit et al.   INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS

Ripple effect in the supply chain: an analysis and recent literature

(2017) Alexandre Dolgui et al.   INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH

Examining Factors That Increase and Decrease Stress in Adolescent Community College Students

(2010) Nancy R. Ahern et al.   Journal of Pediatric Nursing-Nursing Care of Children & Families

The importance of teaching and learning resilience in the health disciplines: A critical review of the literature

(2008) Margaret McAllister et al.   NURSE EDUCATION TODAY