Stress, anxiety, and depression are some of the most important research and practice challenges for psychologists, psychiatrists, and behavioral scientists. Due to the importance of issue and the lack of general statistics on these disorders among the Hospital staff treating the COVID-19 patients, this study aims to systematically review and determine the prevalence of stress, anxiety and depression within front-line healthcare workers caring for COVID-19 patients. In this research work, the systematic review, meta-analysis and meta-regression approaches are used to approximate the prevalence of stress, anxiety and depression within front-line healthcare workers caring for COVID-19 patients. The keywords of prevalence, anxiety, stress, depression, psychopathy, mental illness, mental disorder, doctor, physician, nurse, hospital staff, 2019-nCoV, COVID-19, SARS-CoV-2 and Coronaviruses were used for searching the SID, MagIran, IranMedex, IranDoc, ScienceDirect, Embase, Scopus, PubMed, Web of Science (ISI) and Google Scholar databases. The search process was conducted in December 2019 to June 2020. In order to amalgamate and analyze the reported results within the collected studies, the random effects model is used. The heterogeneity of the studies is assessed using the I2 index. Lastly, the data analysis is performed within the Comprehensive Meta-Analysis software. Of the 29 studies with a total sample size of 22,380, 21 papers have reported the prevalence of depression, 23 have reported the prevalence of anxiety, and 9 studies have reported the prevalence of stress. The prevalence of depression is 24.3% (18% CI 18.2–31.6%), the prevalence of anxiety is 25.8% (95% CI 20.5–31.9%), and the prevalence of stress is 45% (95% CI 24.3–67.5%) among the hospitals’ Hospital staff caring for the COVID-19 patients. According to the results of meta-regression analysis, with increasing the sample size, the prevalence of depression and anxiety decreased, and this was statistically significant (P < 0.05), however, the prevalence of stress increased with increasing the sample size, yet this was not statistically significant (P = 0.829). The results of this study clearly demonstrate that the prevalence of stress, anxiety and depression within front-line healthcare workers caring for COVID-19 patients is high. Therefore, the health policy-makers should take measures to control and prevent mental disorders in the Hospital staff.

/pdf/the-prevalence-of-stress-anxiety-and-depression-within-front-288oedexyp.pdf

The prevalence of stress, anxiety and depression within front-line healthcare workers caring for COVID-19 patients: a systematic review and meta-regression.

Mental health issues are increasing in severity and number on college campuses. Improving adolescent mental well-being remains a challenge for most societies.The objectives of this study was to stu...

https://www.ajol.info/index.php/bafm/article/view/154055/143634

Prevalence and associated factors of stress, anxiety and depression among medical Fayoum University students

Prevalence of depression among nursing students: A systematic review and meta-analysis.

Harnessing the massively parallel architectures soon to become available into efficient algorithmic cooperation is one of the most important intellectual challenges facing Computer Science today. To the theoretician, the task seems similar to thiat of understanding the issues involved in the performance of sequential algorithms (which motivated Knuth’s books, among other important works), only mfinitely more complex. In sequential computation, th.e design process involves (a) choosing an algorithm and (b) analyzing it (mostly, counting its steps). In the parallel context, however, we have at least four stages: (1) Choose the algorithm (say, a directed acyclic graph (dag) indicating the elementary computations and their interdependence, a model in which evaluation of sequential performance is trivial). (2) Choose a particular multiprocessor architecture. (3) Find a schedule whereby the algorithm is executed on the processors (so that all necessary data a:re available at the appropriate processor at the time of each computation). (4) Only now can we talk about the performance of the algorithm, measured as the makespan of the schedule (elapsed time for computing the last result). In our opinion, it is this multi-layered nature of the problem that lies at the heart of the difficulties encountered in the development of the necessary ideas, principles, and tools for the design of parallel algorithms. Is there a way to shortcut the process, thus improving our chances of finally gaining some insight into parallel algorithms? It would be very interesting if we could combine stages (3) and (4) into a single step whereby the performance of the algorithm cho-

Towards an Architecture-Independent Analysis of Parallel Algorithms (Extended Abstract)

Aim: To estimate the prevalence of symptoms of depression, anxiety, stress and associated factors in a population of college students. Method: Cross-sectional study of psychological distress measured through the Depression, Anxiety and Stress Scale (DASS-21) in a sample of 1074 college students. Results: We found a moderate prevalence of depression (18.4%), anxiety (23.6%) and stress (34.5%) symptoms in our study population. Being <21, having problematic Internet use behavior, smoking, presenting insomnia and having a low self-esteem were independently associated with symptoms of depression, anxiety and stress. Being a woman, living with their family, having a stable partner, consuming alcohol frequently and having poor nutritional habits were significantly associated with symptoms of stress; lacking a stable partner was significantly associated with depressive symptoms; and frequent consumption of alcohol was significantly associated with symptoms of anxiety. Conclusion: We found a moderate prevalence of depression, anxiety and stress symptoms in our population. Interventions aimed at promoting mental health among college students should be implemented.

https://www.mdpi.com/1660-4601/17/19/7001/pdf

The prevalence of depression, anxiety and stress and their associated factors in college students

Introduction. Depression is one of the four major diseases in the world and is the most common cause of disability from diseases. The aim of this study is to estimate the prevalence of depression among Iranian university students using meta-analysis method. Materials and Methods. Keyword depression was searched in electronic databases such as PubMed, Scopus, MAGIran, Medlib, and SID. Data was analyzed using meta-analysis (random-effects model). Heterogeneity of studies was assessed using the index. Data was analyzed using STATA software Ver.10. Results. In 35 studies conducted in Iran from 1995 to 2012 with sample size of 9743, prevalence of depression in the university students was estimated to be 33% (95% CI: 32–34). The prevalence of depression among boys was estimated to be 28% (95% CI: 26–30), among girls 23% (95% CI: 22–24), single students 39% (95% CI: 37–41), and married students 20% (95% CI: 17–24). Metaregression model showed that the trend of depression among Iranian students was flat. Conclusions. On the whole, depression is common in university students with no preponderance between males and females and in single students is higher than married ones.

/pdf/prevalence-of-depression-among-university-students-a-4vficufcim.pdf

Prevalence of Depression among University Students: A Systematic Review and Meta-Analysis Study.

The architecture of a cloud includes several key modules user interaction interface, system resource management module with a services catalog, and resource provisioning module. The system resource management module manages a massive network of servers running in parallel. Often it also uses virtualization techniques to dynamically allocate computing resources. In a distributed system Timing and mapping the priority of tasks among processors is one of the issues attracted most of attention to itself. This issue consists of mapping a Direct Acyclic Graph with a set of tasks on a number of parallel processors and its purpose is allocating tasks to the available processors in order to satisfy the needs of priority and decency of tasks, and also to minimize the duration time of execution in total graph. In this article, we'll represent an algorithm that useful Servers Count and Branch Factoring Tasks of Workflow in distributed systems. Simulations is showed that we approach is better than about the list schedule algorithm.

https://textroad.com/pdf/JBASR/J.%20Basic.%20Appl.%20Sci.%20Res.,%202(11)11659-11667,%202012.pdf

Rohollah Esmaeli Manesh

Papers

Prevalence of Depression among University Students: A Systematic Review and Meta-Analysis Study.

A Study about Servers Count and Branch Factoring Tasks of Workflow in Cloud Computing