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

ABSTRACT: In addition to affecting people's bodily and mental health, the Covid-19 epidemic has also altered the emotional and mental well-being of many workers. Especially in the realm of institutions and privately held enterprises, which encountered a plethora of constraints due to the peculiar circumstances of the epidemic. It was thus anticipated that the present study would use a group method of data handling (GMDH) neural network for analyzing the relationship of demographic factors, Coronavirus, resilience, and the burnout in startups. The test methodology was quantitative. The research examined 384 startup directors and representatives, which is a sizable proportion of the limitless community. The BRCS, the MBI-GS, and custom-made assessments of stress due to the Coronavirus were all used to

SUBMITTER: Fan T 

PROVIDER: S-EPMC10627462 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature