4 research outputs found

    THE EFFECTS OF WORK STRESS ON JOB SATISFACTION OF HEALTHCARE WORKERS IN A PUBLIC SECTOR HOSPITAL IN ALDAKHLIYA, OMAN

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    The role of healthcare workers is central to the modern healthcare system and was further highlighted during the COVID-19 pandemic situation. However, the healthcare workers did face a lot of work pressure during the pandemic which also had some negative consequences. In the present study, we investigated the effects of work stress and its five dimensions including the availability of resources, work environment, reward and incentive, functional relationship, and fear of catching COVID-19 on employee job satisfaction in the context of the public healthcare system in Oman. The sample is selected from a selected healthcare unit and data is collected using the survey-based method. The findings show that there are significant effects of two dimensions including functional relationships and work environments on healthcare job satisfaction. Based on the findings, it can be concluded that healthcare workers facing a lot of stress and this issue need greater managerial attention. Keywords: Work Stress, Job Satisfaction, Healthcare Workers, COVID-19 Pandemic

    Forecasting the SARS COVID-19 pandemic and critical care resources threshold in the Gulf Cooperation Council (GCC) countries: population analysis of aggregate data

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    ObjectiveTo generate cross-national forecasts of COVID-19 trajectories and quantify the associated impact on essential critical care resources for disease management in Gulf Cooperation Council (GCC) countries.Design Population-level aggregate analysis.Setting Bahrain, Kuwait, Oman, Qatar, United Arab Emirates (UAE) and Saudi Arabia.MethodsWe applied an extended time-dependent SEICRD compartmental model to predict the flow of people between six states, susceptible–exposed–infected–critical–recovery–death, accounting for community mitigation strategies and the latent period between exposure and infected and contagious states. Then, we used the WHO Adaptt Surge Planning Tool to predict intensive care unit (ICU) and human resources capacity based on predicted daily active and cumulative infections from the SEICRD model.Main outcome measuresPredicted COVID-19 infections, deaths, and ICU and human resources capacity for disease management.Results COVID-19 infections vary daily from 498 per million in Bahrain to over 300 per million in UAE and Qatar, to 9 per million in Saudi Arabia. The cumulative number of deaths varies from 302 per million in Oman to 89 in Qatar. UAE attained its first peak as early as 21 April 2020, whereas Oman had its peak on 29 August 2020. In absolute terms, Saudi Arabia is predicted to have the highest COVID-19 mortality burden, followed by UAE and Oman. The predicted maximum number of COVID-19-infected patients in need of oxygen therapy during the peak of emergency admissions varies between 690 in Bahrain, 1440 in Oman and over 10 000 in Saudi Arabia.Conclusion Although most GCC countries have managed to flatten the epidemiological curve by August 2020, trends since November 2020 show potential increase in new infections. The pandemic is predicted to recede by August 2021, provided the existing infection control measures continue effectively and consistently across all countries. Current health infrastructure including the provision of ICUs and nursing staff seem adequate, but health systems should keep ICUs ready to manage critically ill patients

    External validation of a cardiovascular risk model for Omani patients with type 2 diabetes mellitus: a retrospective cohort study

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    Objectives To externally validate a recently developed cardiovascular disease (CVD) risk model for Omanis with type 2 diabetes mellitus (T2DM).Design Retrospective cohort study.Setting Nine primary care centres in Muscat Governorate, Oman.Participants A total of 809 male and female adult Omani patients with T2DM free of CVD at baseline were selected using a systematic random sampling strategy.Outcome measures Data regarding CVD risk factors and outcomes were collected from the patients’ electronic medical records between 29 August 2020 and 2 May 2021. The ability of the model to discriminate CVD risk was assessed by calculating the area under the curve (AUC) of the receiver-operating characteristic curve. Calibration of the model was evaluated using a Hosmer-Lemeshow χ2 test and the Brier score.Results The incidence of CVD events over the 5-year follow-up period was 4.6%, with myocardial infarction being most frequent (48.6%), followed by peripheral arterial disease (27%) and non-fatal stroke (21.6%). A cut-off risk value of 11.8% demonstrated good sensitivity (67.6%) and specificity (66.5%). The area under the curve (AUC) was 0.7 (95% CI 0.60 to 0.78) and the Brier score was 0.01. However, the overall mean predicted risk was greater than the overall observed risk (11.8% vs 4.6%) and the calibration graph showed a relatively significant difference between predicted and observed risk levels in different subgroups.Conclusions Although the model slightly overestimated the CVD risk, it demonstrated good discrimination. Recalibration of the model is required, after which it has the potential to be applied to patients presenting to diabetic care centres elsewhere in Oman
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