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 (<0.08), a goodness of fit index (GFI) value of 0.915 (>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.
Background
Dengue is a mosquito-borne viral disease that is mainly spread by Aedes aegypti. It is prevalent on five continents, predominantly in tropical and sub-tropical zones across the world. Wolbachia bacteria have been extensively used in vector control strategies worldwide. The focus of the current study was to obtain a natural population of Ae. aegypti harbouring Wolbachia and to determine the impact of this bacteria on the new host in a semi-field environment.
Methods
Wolbachia-infected Aedes albopictus was collected from the city of Lahore, Punjab, Pakistan, and Wolbachia were successfully introduced into laboratory-reared Ae. aegypti via embryonic microinjection. The stable vertical transmission of wAlbB in the host population was observed for eight generations, and the impact of Wolbachia on the general fitness of the host was evaluated in semi-field conditions.
Results
In the laboratory and semi-field experiments, wAlbB Wolbachia presented a strong cytoplasmic incompatibility (CI) effect, evidenced as zero egg hatching, in crosses between Wolbachia-infected males and wild (uninfected) females of Ae. aegypti. Wolbachia infection had no noticeable impact on the general fitness (P > 0.05), fecundity, body size (females and males) and mating competitiveness of the new host, Ae. aegypti. However, there was a significant decrease in female fertility (egg hatch) (P < 0.001). In addition, under starvation conditions, there was a remarkable decrease (P < 0.0001) in the life span of Wolbachia-infected females compared to uninfected females (4 vs. > 5 days, respectively).
Conclusions
Wolbachia strain wAlbB has a great potential to control the dengue vector in Ae. aegypti populations by producing 100% CI with a limited burden on its host in natural field conditions. This strain can be used as a biological tool against vector-borne diseases.
Graphical Abstract
We propose herein a six-parameter McDonald modified Burr-III distribution. This distribution contains several special cases, including the modified Burr-III, Burr-III, Beta Burr-III, and Kum Burr-III distributions. Accordingly, we obtained its hazard function, survival function, moments, Renyi's entropy, β-entropy, and mean deviation. We also used the method of maximum likelihood to estimate the parameters of our proposed distribution. Simulation studies were also performed for different values of sample sizes. The proposed model is applied on real-life datasets and shows that our proposed distribution yields better fits than other existing models.
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