Improving classification based on physical surface tension-neural net for the prediction of psychosocial-risk level in public school teachers.

ABSTRACT:

Background

Psychosocial risks, also present in educational processes, are stress factors particularly critical in state-schools, affecting the efficacy, stress, and job satisfaction of the teachers. This study proposes an intelligent algorithm to improve the prediction of psychosocial risk, as a tool for the generation of health and risk prevention assistance programs.

Methods

The proposed approach, Physical Surface Tension-Neural Net (PST-NN), applied the theory of superficial tension in liquids to an artificial neural network (ANN), in order to model four risk levels (low, medium, high and very high psychosocial risk). The model was trained and tested using the results of tests for measurement of the psychosocial risk levels of 5,443 teachers. Psychosocial, and also physio

SUBMITTER: Mosquera Navarro R 

PROVIDER: S-EPMC8176537 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature