Áreas da vida no trabalho como preditoras da síndrome de burnout: tradução, adaptação transcultural e validação do modelo AWS-MBIGS

Abstract

The instrument Areas of Worklife Scale AWS is configured as an instrument for organizational assessment and intervention, structured as a model that relates six measures to the context and content of work - workload, control, reward, community, fairness and values - with three dimensions of burnout - exhaustion, cynicism and professional efficacy (LEITER; MASLACH, 2011). AWS concentrates the degree of congruence between the individual and the six domains of their work environment (MASLACH; LEITER, 1997), proposing that the greater the perceived gap between person and work, the greater the likelihood of burnout, conversely, the greater the consistency, the greater is the likelihood of commitment to work. Thus, considering the relevance of the model of areas of professional life that allows not only the measurement of burnout, but the identification of component areas of the organizational context that may be predictors of diseases, the following research issue appears: “do the six areas of work life by Leiter and Maslach (2011) confirm themselves as organizational predictors of burnout in the Brazilian context? " In order to find an answer to this problem, we present a proposal to analyze if the factors of six areas of worklife present in the instrument Areas of Worklife Scale AWS (LEITER; MASLACH, 2011) - workload, control, reward, community, fairness and values - confirm themselves as organizational predictors for three dimensions of burnout components of the instrument Maslach MBI-GS General Burnout Inventory Survey (MASLACH; JACKSON; LEITER, 2016) - exhaustion, cynicism and professional efficacy – from the translation and transcultural adaptation to the Brazilian context. In order to achieve the proposed objective, we propose a methodological approach with a qualitative approach to the translation and adaptation stage of the AWS and MBI-GS instruments using the transcultural adaptation process (BEATON et al., 2000) and quantitative approach to the validation step of the integrated AWS-MBIGS model using the structural equation modelling with partial least squares (HAIR Jr. et al., 2017). The results allow us to infer that the relationships between the six areas of work life and the three dimensions of burnout are supported in the model and the hypothesis “H1 Control directly and positively influences workload” has been accepted presenting internal coefficient of 0.359, t-test 8,723 and significance with p value less than 0.05. Hypothesis “H2 control influences directly and positively reward” has been accepted with internal coefficient of 0.554, t-test of 16.695 and significance with value less than 0.05. Hypothesis “H3 Control directly and positively influences the community” has also been accepted with an internal coefficient of 0.423, t- test 10.317 and significance with a value less than 0.05. Hypothesis “H4 Control directly and positively influences fairness” accepted with internal coefficient 0.517 and t-test value 15.138 and value less than 0.05. Hypothesis “H5 Reward directly and positively influences values” accepted the same way with internal coefficient value of 0.242 and t-test value 5.076 significant at 0.05. Hypothesis “H6 Community directly and positively influences values” with internal coefficient of 0.138 and t-test value 2.741 showing significance. Hypothesis “H7 Fairness directly and positively influences values” with a coefficient of 0.316 and t-test value of 6.602 and significant. The hypothesis “H8 Values influences directly and negatively exhaustion” with coefficient of -0.061 and t-test value 1.866 and p value = 0.062 leading to the rejection of the hypothesis. Hypothesis “H9 Values directly and negatively influences cynicism” with internal coefficient -0.343 and value for t-test 9.651 shows significance with value less than 0.05. Hypothesis “H10 Values influences directly and positively professional effectiveness” presents the internal coefficient value 0.141 and the t-test value of 3.323 being significant. Hypothesis “H11 Workload directly and negatively affects exhaustion” has internal coefficient value of -0.657, t-test value 25.524, significant 0.05. Hypothesis “H12 Exhaustion directly and positively influences cynicism” with an internal coefficient of 0.457 and a t-test value of 13.826, significant. Finally, hypothesis “H13 Cynicism influences directly and negatively professional effectiveness” has an internal coefficient of -0.397 and a test value of 10.062, being significant at 0.05. We have accepted the model hypotheses except for H8 which has been rejected. Confirming, this way, the areas of worklife as predictors of burnout syndrome, enabling us to use the model as a diagnostic and intervention instrument to minimize or eliminate elements that may cause imbalance in the individual-work relationship.