Ethnographic research is perhaps the most common applicable type of qualitative research method in psychology and medicine. In ethnography studies, the researcher immerses himself in the environment of participants to understand the cultures, challenges, motivations, and topics that arise between them by investigating the environment directly. This type of research method can last for a few days to a few years because it involves in-depth monitoring and data collection based on these foundations. For this reason, the findings of the current study stimuli the researchers in psychology and medicine to conduct studies by applying ethnographic research method to investigate the common cultural patterns language, thinking, beliefs, and behavior for groups of addicts, the bullies and their bullies, hospitalized psychiatric patients, psychiatric nursing groups, psychologists, counselors and psychotherapists, elderly residents of care homes, abused persons, orphans, persons with special needs, groups of gifted students in gifted schools and centers, and family with special needs children. The ethnographic approach is a very important method in medicine to investigate the health case of the patients with chronic diseases, such as heart diseases, cancer, diabetes, blood pressure, and others. And examine the effectiveness of the treatment plan and take a decision to continue this plan, or change it, in the treatment of a particular disease group. As well as detection of the side effects of drugs and treatment plan for certain groups of patients, and learning about the common culture of pregnant women about the process of pregnancy and childbirth.
Background: The COVID-19 infection is a more recent pandemic disease all over the world and studying the pulmonary findings on survivors of this disease has lately commenced.
Objective: We aimed to estimate the cumulative percentage of whole radiological resolution after 3 months from recovery and to define the residual chest CT findings and exploring the relevant affecting factors.
Subjects and Methods: Patients who had been previously diagnosed with COVID-19 pneumonia confirmed by RT-PCR test and had radiological evidence of pulmonary involvement by Chest CT during the acute illness were included in the present study. The radiol
... Show MoreBackground: Asthma is one of the most common chronic respiratory diseases in the world, standing for the most frequent cause for hospitalization and emergency cases. Respiratory viruses are the most triggering cause. Aim: To assess the role of viral infections, especially COVID-19, in the pathogenesis of asthma initiation and exacerbations. Method: Electronic search was done for the manuscripts focusing on asthma as a risk factor for complications after COVID-19 infection. The outcomes were titles, materials, methods and classified studies related or not related to the review study. Three hundred publications were identified and only ten studies were selected for analysis. Seven studies were review, one retrospective, one longitudin
... Show MoreThe most common cause of upper respiratory tract infection is coronavirus, which has a crown appearance due to the existence of spikes on its envelope. D-dimer levels in the plasma have been considered a prognostic factor for COVID-19 patients.
The aim of the study is to demonstrate the role of COVID-19 on coagulation parameters D-dimer and ferritin with their association with COVID-19 severity and disease progression in a single-center study.
Background: the coronavirus leads to upper respiratory tract-associated manifestations like nasal congestion, sore throat, and smell disorder
Objectives: To reveal the impact of COVID-19 pandemic on otolaryngology symptoms using our daily medical practice.
Subject and Methods: A cross-sectional study that was carried on in the isolation wards at Al-Kindy and Al-Nu’man Teaching Hospitals during three months from the 1st of Jun. till the end of Aug. 2020. It included 1270 patients who were diagnosed with COVID-19 infection seen in the ENT consultation clinic and admitted to the isolation wards.
Results: Otolaryngological manifestations were shown
... Show MoreBackground: since December 2019, China and in particularly Wuhan, faced an unprecedented an outbreak challenge of coronavirus disease 2019, caused by the severe acute respiratory syndrome coronavirus 2. Clinical characteristics of Iraqi patients with COVID-19 and risk factors for mortality needed to be shared with the health care providers to improve the overall disease experience. Methods: prospective, single-center study recruited patients with confirmed SARS-CoV-2 infection who were admitted to Al-Shifaa Isolation Center / Baghdad Medical City between the mid of March and the end of April 2020 until had been discharged or had died. Demographic data, information on clinical signs, symptoms, at presentation, treatment, have been collected
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Theoretical spectroscopic studies of beryllium oxide has been carried out, potential energy curves for ground states X1Σ+ and exited states A1Π , B1Σ+ by using two functions Morse and and Varshni compared with experimental results. The potentials of this molecule are agreement with experimental results. The Fortrat Parabola corrcponding to and branches were determind in the range 1<J<20 for the (0-0) band. It was found that for electronic transition A1Π- X1Σ+ the bands head lies in branche of Fortrat p |
The aim of the present study is to compare the biochemical action of the three vaccines taken in Iraq: Pfizer Biontech, AstraZeneca Oxford and Sinopharm based on biochemical parameters. Seventy COVID-19 Iraqi patients ( males and females ) were participated in the present study and classified into 7 groups : Gc : COVID-19 patients ( without vaccine ) , Gp1: COVID-19 patients took one dose of Pfizer Biontech, Gp2 : COVID-19 patients took two doses of Pfizer Biontech, Ga1 : patients took one dose of AstraZeneca Oxford vaccine , Ga2: patients took two doses of AstraZeneca Oxford vaccine , Gs1 : patients took one dose of Sinopharm vaccine and Gs2:
... Show MoreBy March 2020, a pandemic had been emerged Corona Virus Infection in 2019 (COVID-19), which was triggered through the sensitive pulmonary syndrome (SARS disease corona virus- 2 (SARS COV-2). Overall precise path physiology of SARS COV-2 still unknown, as does the involvement of every element of the acute or adaptable immunity systems. Additionally, evidence from additional corona virus groups, including SARS COV as well as the Middle East pulmonary disease, besides that, fresh discoveries might help researchers fully comprehend SARS CoV-2. Toll-like receptors (TLRs) serve a critical part in both detection of viral particles as well as the stimulation of the body's immune response. When TLR systems are activated, pro-inflammatory cy
... Show MoreBackground: Coronavirus, which causes respiratory illness, has been a public health issue in recent decades. Because the clinical symptoms of infection are not always specific, it is difficult to expose all suspects to qualitative testing in order to confirm or rule out infection as a test. Methods: According to the scientific studies and investigations, seventy-three results of scientific articles and research were obtained using PubMed, Medline, Research gate and Google Scholar. The research keywords used were COVID-19, coronavirus, blood parameters, and saliva. Results: This review provides a report on the changes in the blood and saliva tests of those who are infected with the COVID-19.COVID-19 is a systemic infection that has
... Show MoreAfter the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings
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