Qualidade de vida profissional em trabalhadores da saúde: fatores associados

Abstract

Professional quality of life refers to how well the individual feels at work and is determined by the ability of the workers to manage their responses to labor demands. It is determined by positive aspects, called Compassion Satisfaction, and by negative aspects, called Compassion Fatigue. The present study aimed to analyze the quality of professional life of health workers who work in critical care services in the northern region of Minas Gerais, Brazil, resulting in three scientific articles. Study 1 aimed to analyze what is available in literature about factors associated with compassion fatigue among health professionals working in hospital services. It was an integrative review of the literature, with the inclusion of Portuguese, Spanish and English scientific articles published in the databases: SciELO, LILACS and Medline in the period from 2013 to 2017. The descriptors used were " Compassion Fatigue" and "Fadiga por Compaixão" (In Portuguese). The search resulted in 12 articles that were included. The results demonstrated that the syndrome is related to working conditions, emotional state, psychological and sociodemographic characteristics. Study 2 aimed to verify the factors associated with professional quality of life and its dimensions. 469 participating workers in the sectors of oncology, neonatal intensive care, nephrology and first aid, were selected through a simple random sample with replacement. The data were collected using two instruments: a questionnaire, referring to the characterization of the subjects, and the professional quality of life scale in its version 5, which verified the dimensions that make up the professional quality of life, being: Compassion Satisfaction, Burnout, and Secondary Traumatic Stress. The results showed that work time in health, work sector, function, use of sleeping medication, type of employment relationship and self-perception of health status were related to professional quality of life. Study 3 sought to build a prediction model for Compassion Satisfaction among workers working in hospital sectors that serve critical patients through an Artificial Neural Network. The simulations were performed using MATLAB® software in its R2017a version and the Non-dominant Classification Genetic Algorithm was adopted in its second version, in order to maximize the hit rate and minimize the number of variables in the model. The neural network resulting has seven layers with 12 neurons in the input layer, represented by sociodemographic, labor and health characteristics; and 1 neuron in the output layer, represented by " Compassion Satisfaction". The study showed that the best result was presented by the inclusion of 12 variables, with a final accuracy of 94.5%. The data of the present thesis can serve as support for the health promotion of the workers in hospital sectors that attend critical patients. Knowing and analyzing the factors that influence positively and negatively the professional quality of life allows better management of the conditions that can lead to Compassion Satisfaction and Compassion Fatigue.