Publication Details

Al Mutair, A., Mutairi, A., Chagla, H., Alawam, K., Alsalman, K. & Ali, A. (2020). Examining and adapting the psychometric properties of the maslach burnout inventory-health services survey (MBI-HSS) among healthcare professionals. Applied Sciences, 10 (5), 1890-1-1890-11.


Burnout is known to negatively impact healthcare providers both physically and mentally and is assessed using the Maslach Burnout Inventory-Human Services Survey (MBI-HSS). Many versions of this tool have been developed for different parts of the world, but there is currently no valid version specifically designed for use in the Gulf Cooperation Council Region. This study aims to use data collected across six different regions in the Gulf Cooperation Council Region to assess the validity and reliability of the MBI-HSS model and develop a version of the MBI-HSS best suited for evaluating burnout levels among the healthcare providers in this region. The MBI-HSS questionnaire adapted by Maslach was distributed to 888 healthcare providers aged 32 years ± 7 years, 231 (26.1%) of whom were males and 651 (73.9%) of whom were females, between 2017 and 2018. The data collected were randomly divided into two subsamples, resulting in a sample with the data of 300 healthcare professionals for exploratory factor analysis (EFA) and 588 healthcare professionals for confirmatory factor analysis (CFA). The CFA of the original version of the MBI-HSS yielded a chi-square value of 1897 (p < 0.001), indicating the need for revision. EFA was then used to construct a new model of the MBI-HSS, and a CFA was performed on the second subsample to evaluate the model fit to the data. The EFA produced a 3-factor version that accounted for 56.3% of the total variance, with item 11 of the MBI moved to the Emotional Exhaustion (EE) subscale and item 16 loaded onto Depersonalisation (DP) instead of EE. Additionally, items 18 and 20 were omitted. The reconstructed version had a Root Mean Square Error of Approximation (RMSEA) value of 0.065 (0.90) and an adjusted goodness of fit index (AGFI) value of 0.893 (>0.8). These results when compared to the CFA of the original model, which produced a GFI value of 0.79, an AGFI value of 0.74 and an RMSEA value of 0.09 (>0.08), indicate that this new version has a more satisfactory fit to the data and should be used when assessing burnout in the Gulf Cooperation Council Region.



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