Corpus overview


MeSH Disease

Human Phenotype


    displaying 1 - 2 records in total 2
    records per page

    Associating Unemployment with Panic Attack HP Using Stacked-RNN Model During COVID-19

    Authors: Samir Bandyopadhyay; SHAWNI DUTTA

    id:10.20944/preprints202006.0242.v1 Date: 2020-06-19 Source:

    Corona Virus Infectious Disease MESHD (COVID-19) is newly emerging infectious disease MESHD. This disease MESHD is known to the globe in early 2019. Poor status of mental health is often caused by unemployment, ongoing socio-economic condition. Poor mental health may even accelerate the process of panic attack HP. It has been happening rapidly during COVID-19. It has a great effect on human health. This paper utilizes multiple related factors those have impact on causing panic attack HP. Recurrent Neural Network (RNN) based framework is utilized in this paper that assembles multiple RNN layers along with other parameters into a single platform. This method is implemented by capturing interfering factors and predicts panic attack HP tendency of people during COVID-19. Early prediction of panic attacks HP may assist in saving life from unwanted circumstances.

    Compare the severity of psychological distress among four groups of Iranian society in COVID-19 pandemic

    Authors: Amir Vahedian-Azimi; Malihe Sadat Moayed; Farshid Rahimibashar; Sajad Shojaei; Sara Ashtari; Mohamad Amin Pourhoseingholi

    doi:10.21203/ Date: 2020-04-19 Source: ResearchSquare

    Background: Coronavirus Disease MESHD 2019 (COVID-19) pandemic has caused serious psychological problems, such as panic attack HP, anxiety HP, stress and depression. The main objective of this study was to measure the prevalence SERO and compare the severity of this psychological distress among four groups of Iranian population.Method: In cross-sectional survey, the mental health status of four groups of Iranian society such as community population, patients with COVID-19, medical staff and medical students were investigated by self-report questionnaire Depression, Anxiety HP and Stress Scale (DASS). DASS-21 questionnaire and the demographic data sheet were filled in by all participants. All statistical analyses were done using SPSS version 21.0. P-values less than 0.05 were considered statistically significant.Results: Of the 886 participants in this survey, 554 (62.5%) were male TRANS and 332 (37.5%) were female TRANS, and the mean ± standard division (SD) age TRANS of subjects was 40.91±10.7 years. Among these participants, 241 (27.2%) were selected from community population, 221 (24.9%) were patients with COVID-19, 217 (24.5%) were medical staff and 207 (23.4%) were medical students. The mean score of stress, anxiety HP and depression in medical students and patients with COVID-19 was significantly higher than medical staff and community population (P<0.05). In overall, the score of anxiety HP level in male TRANS was higher than that in female TRANS (27.4±4.6 vs. 26.48±4.8, P=0.006), and the score of depression in unmarried participants was significantly higher than that in married group (27.5±4.8 vs. 26.7±4.6, P=0.023). In addition, the score of depression in female TRANS medical staff (27.08±4.6 vs. 25.33±4.3, P=0.011) and community population (26.6±4.3 vs. 25.3±4.3, P=0.02) was higher than that in male TRANS.Conclusion: In COVID-19 pandemic, the severity of anxiety HP, stress and depression was high among Iranian population. Patients with COVID-19 and medical students who spent time with patients with COVID-19, with low experience than professional medical staff and community population were at high risk for mental illness. Continuous surveillance and monitoring of psychological distress for outbreaks should become routine as part of preparedness efforts worldwide. 

The ZB MED preprint Viewer preVIEW includes all COVID-19 related preprints from medRxiv and bioRxiv, from ChemRxiv, from ResearchSquare, from arXiv and from and is updated on a daily basis (7am CET/CEST).



MeSH Disease
Human Phenotype

Export subcorpus as Endnote

This service is developed in the project nfdi4health task force covid-19 which is a part of nfdi4health.

nfdi4health is one of the funded consortia of the National Research Data Infrastructure programme of the DFG.