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  1. Mustafa HMJ, Ayob M, Albashish D, Abu-Taleb S
    PLoS One, 2020;15(6):e0232816.
    PMID: 32525869 DOI: 10.1371/journal.pone.0232816
    The text clustering is considered as one of the most effective text document analysis methods, which is applied to cluster documents as a consequence of the expanded big data and online information. Based on the review of the related work of the text clustering algorithms, these algorithms achieved reasonable clustering results for some datasets, while they failed on a wide variety of benchmark datasets. Furthermore, the performance of these algorithms was not robust due to the inefficient balance between the exploitation and exploration capabilities of the clustering algorithm. Accordingly, this research proposes a Memetic Differential Evolution algorithm (MDETC) to solve the text clustering problem, which aims to address the effect of the hybridization between the differential evolution (DE) mutation strategy with the memetic algorithm (MA). This hybridization intends to enhance the quality of text clustering and improve the exploitation and exploration capabilities of the algorithm. Our experimental results based on six standard text clustering benchmark datasets (i.e. the Laboratory of Computational Intelligence (LABIC)) have shown that the MDETC algorithm outperformed other compared clustering algorithms based on AUC metric, F-measure, and the statistical analysis. Furthermore, the MDETC is compared with the state of art text clustering algorithms and obtained almost the best results for the standard benchmark datasets.
  2. Taleb S, Vahedian-Azimi A, Karimi L, Salim S, Mohammad F, Samhadaneh D, et al.
    BMC Psychiatry, 2024 Jan 22;24(1):61.
    PMID: 38254016 DOI: 10.1186/s12888-023-05088-x
    BACKGROUND: In light of several recent studies, there is evidence that the coronavirus disease 2019 (COVID-19) pandemic has caused various mental health concerns in the general population, as well as among healthcare workers (HCWs). The main aim of this study was to assess the psychological distress, burnout and structural empowerment status of HCWs during the COVID-19 outbreak, and to evaluate its predictors.

    METHODS: This multi-center, cross-sectional web-based questionnaire survey was conducted on HCWs during the outbreak of COVID-19 from August 2020 to January 2021. HCWs working in hospitals from 48 different countries were invited to participate in an online anonymous survey that investigated sociodemographic data, psychological distress, burnout and structural empowerment (SE) based on Depression Anxiety and Stress Scale 21 (DASS-21), Maslach Burnout Inventory (MBI) and Conditions for work effectiveness questionnaire (CWEQ_II), respectively. Predictors of the total scores of DASS-21, MBI and CWEQ-II were assessed using unadjusted and adjusted binary logistic regression analysis.

    RESULTS: Out of the 1030 HCWs enrolled in this survey, all completed the sociodemographic section (response rate 100%) A total of 730 (70.9%) HCWs completed the DASS-21 questionnaire, 852 (82.6%) completed the MBI questionnaire, and 712 (69.1%) completed the CWEQ-II questionnaire. The results indicate that 360 out of 730 responders (49.3%) reported severe or extremely severe levels of stress, anxiety, and depression. Additionally, 422 out of 851 responders (49.6%) reported a high level of burnout, while 268 out of 712 responders (37.6%) reported a high level of structural empowerment based on the DASS-21, MBI, and CWEQ-II scales, respectively. In addition, the analysis showed that HCWs working in the COVID-19 areas experienced significantly higher symptoms of severe stress, anxiety, depression and higher levels of burnout compared to those working in other areas. The results also revealed that direct work with COVID-19 patients, lower work experience, and high workload during the outbreak of COVID-19 increase the risks of negative psychological consequences.

    CONCLUSION: Health professionals had high levels of burnout and psychological symptoms during the COVID-19 emergency. Monitoring and timely treatment of these conditions is needed.

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