| Autor: |
Trigo TR; Laboratory of Neuro Imaging (LIM-21), Department and Institute of Psychiatry, Clinics Hospital, University of São Paulo School of Medicine, São Paulo, Brazil., de Freitas CCS; Laboratory of Neuro Imaging (LIM-21), Department and Institute of Psychiatry, Clinics Hospital, University of São Paulo School of Medicine, São Paulo, Brazil., Wang YP; Section of Psychiatric Epidemiology (LIM-23), Department and Institute of Psychiatry, Clinics Hospital, University of São Paulo School of Medicine, São Paulo, Brazil., Ribeiro FG; Technical Advisory Office-State Department of Health-São Paulo State Government, São Paulo, Brazil., de Lucia MCS; Division of Psychology, Central Institute, Clinics Hospital, University of São Paulo School of Medicine, São Paulo, Brazil., Siqueira JO; Department of Pathology, University of São Paulo School of Medicine, São Paulo, Brazil.; Department of Experimental Psychology, Institute of Psychology, University of São Paulo, São Paulo, Brazil., Iosifescu DV; Department of Psychiatry, New York University School of Medicine, New York, NY, United States., Hallak JEC; Department of Neurosciences and Behavior, University of São Paulo School of Medicine, São Paulo, Brazil., Fraguas R; Laboratory of Neuro Imaging (LIM-21), Department and Institute of Psychiatry, Clinics Hospital, University of São Paulo School of Medicine, São Paulo, Brazil. |
| Abstrakt: |
Background: The Maslach Burnout Inventory-Human Services Survey (MBI-HSS) is the most commonly used instrument to assess burnout. Although various factors have been reported to influence its validity, the influence of major depressive disorder (MDD) has not been previously considered. We developed this study to investigate the influence of MDD on the psychometric properties of the MBI-HSS in nursing assistants. Results: From a sample of 521 nursing assistants, we found in those with MDD ( n = 138, 24.56%) a degree of data misfit into the model, revealed by non-acceptable values for the root mean square error of approximation (RMSEA; 0.073; p = 0.004) and for the comparative fit index (CFI; 0.912), while in the non-MDD group these indices were acceptable and good, respectively, for RMSEA (0.048; p = 0.639) and for CFI (0.951). Also, we found higher coefficients of correlation among MBI-HSS factors and less items loading properly in their respective factors in the MDD subset, when compared to the non-MDD subset. For the total sample, while original 3-factor solution was an acceptable model, the bifactor model fitted data better. Conclusions: MDD may impair the construct validity of MBI-HSS subscales, by increasing measurement error and decreasing model fitness. Therefore, researchers and health professionals should be aware of potential changes in the psychometric properties of the MBI-HSS when applied in subjects with depression. |
