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INTRODUCTION: Depression in the elderly constitutes 7.3% of the total Malaysian national prevalence of depression. However, depression is commonly underdiagnosed by primary care physicians, which may impact coexisting comorbid conditions and general well-being. As depression in the elderly increases with age, its prevalence is expected to become even more significant due to the increased life expectancy and isolation during the pandemic. This study aims to determine the perceptions, views and barriers encountered among primary care physicians on screening for depression among the elderly. MATERIALS AND METHODS: This qualitative study involved five public healthcare clinics in the Kuching district with indepth interviews (IDI) conducted on 14 primary care doctors (PCDs). Semi-structured interviews and in-depth discussions were conducted via videoconferencing. One representative was selected from each clinic at initiation, followed by snowball method for subsequent subject selection until saturation of themes. Interviews were transcribed verbatim, and analysis based on framework analysis principles via NVivo software. Themes were analysed deductively according to study objectives and evidence from literature. RESULTS: Three main themes emerged from the IDI: (1) The perception of depression in elderly patients, (2) The perceived barriers to screening, and (3) The screening processes. Majority of the PCDs perceived depression as part of ageing process. Time constraints, lack of privacy in consultation rooms, dominant caregivers and failure to recognise recurrent somatic symptoms as part of depression influenced PCDs decision to screen. Screening was technically challenging for PCDs to use the DASS-21, which was not socio-culturally validated for local native population. Only 21.4% of respondents (3/14) reported screening at least three out 10 elderly patients seen over 1- month period. During the covid pandemic, due to the same human resource support and practices, most participants thought their screening for depression in elderlies had not changed. CONCLUSION: Awareness of depression among PCDs needs to be re-enforced via continuous medical education programs to use appropriate screening tools, address infrastructure related barriers to optimise screening practices. The use of appropriate locally validated and socio-culturally adapted tool is vital to correctly interpret the screening test for patients.
Subject(s)
COVID-19 , Depression , Humans , Aged , Depression/diagnosis , Depression/epidemiology , COVID-19/diagnosis , COVID-19/epidemiology , Primary Health Care , Delivery of Health Care , PerceptionABSTRACT
COVID-19 pandemic is a major worldwide health disaster firstly reported in December 2019. The Food and Drug Administration (FDA) has offered the public hope of halting it, authorizing vaccinations for emergency use with more than 85% efficacy against serious acute respiratory syndrome (SARS-CoV-2). Recent outbreaks of SARS-CoV-2 variations including spike-protein mutations, the key vaccines viral target for immune response, have prompted a thorough investigation into the vaccine's long-term effectiveness. Consequently, this review assayed the details on SARS-CoV-2 infection mechanism and how to control the infection by different types of SARS-CoV-2 vaccines, and their effectiveness against other mutant strains. Additionally, the review summarized the different complaints which have been recorded after vaccination. In conclusion, these negative effects must be constantly weighed against the predicted advantages in terms of disease prevention. Although COVID-19 vaccination is recommended for everyone aged 5 years and older, SARS-CoV-2 is high likely to continue to be a pandemic infectious as a result of the broadcasting of variants of the virus. Therefore, a booster vaccination, wearing a mask, and social distancing should be maintained. © 2023 Global NEST.
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Visually impaired people require support with regular tasks including navigating, detecting obstacles, and maintaining safety, especially in both indoor and outdoor environments. As a result of the advancement of assistive technology, their lives have become substantially more convenient. Here, cutting-edge assistive devices and technologies for the visually impaired are reviewed, along with a chronology of their evolution. These methodologies are classified according to their intended applications. The taxonomy is combined with a description of the tests and experiments that can be used to examine the characteristics and assessments of assistive technology. In addition, the algorithms used in assistive devices are examined. This paper looks at solar industry innovations and promotes using renewable energy sources to create assistive devices, as well as, addresses the sudden advent of COVID-19 and the shift in the development of assistive devices. This review can serve as a stepping stone for further research on the topic. Copyright © 2022 The Author(s)
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In the last year, the outbreak of COVID-19 has deployed computer vision and machine learning algorithms in various fields to enhance human life interactions. COVID-19 is a highly contaminated disease that affects mainly the respiratory organs of the human body. We must wear a mask in this situation as the virus can be contaminated through the air and a non-masked person can be affected. Our proposal deploys a computer vision and deep learning framework to recognize face masks from images or videos. We have implemented a Boundary dependent face cut recognition algorithm that can cut the face from the image using 27 landmarks and then the preprocessed image can further be sent to the deep learning ResNet50 model. The experimental result shows a significant advancement of 3.4 percent compared to the YOLOV3 mask recognition architecture in just 10 epochs. © 2021 IEEE.
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COVID-19 is the virus that engulfed the globe in the year 2020 that caused many deaths and disrupted countries' economies. In this report, we reviewed all aspects to explain the subjects, where we performed a systematic and thorough report of the Covid-19 outbreak, its medical conditions, its sources, diagnosis and prevention mechanisms and available methods of treatment. This also discussed the epidemiological situation in Iraq and the distribution of the province of Anbar as a sample for the report. Overall, from all of this analysis we conclude that epidemiology, virology, COVID-19 clinical is still enigmatic and that (viral) epidemics occasionally kill humanity, so we need a broader understanding of viruses.
ABSTRACT
COVID-19 is the virus that engulfed the globe in the year 2020 that caused many deaths and disrupted countries' economies. In this report, we reviewed all aspects to explain the subjects, where we performed a systematic and thorough report of the Covid-19 outbreak, its medical conditions, its sources, diagnosis, and prevention mechanisms and available methods of treatment. This also discussed the epidemiological situation in Iraq and the distribution of the province of Anbar as a sample for the report. Overall, from all of this analysis we conclude that epidemiology, virology, COVID-19 clinical is still enigmatic and that (viral) epidemics occasionally kill humanity, so we need a broader understanding of viruses.
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Prevention of the spread of disease is the most critical effort before the domino effect occurs. One way to prevent its spread is to practice social distancing. Prevention of the spread of covid-19 can be easier by doing Contact Tracing. Contact tracing is done to find out who is infected. This paper proposes an accurate and energy-efficient tracing system based on an android application by utilizing Bluetooth Low Energy (BLE) signals from smartphones to automatically detect possible contacts between users. Using BLE level signals, each app estimates its distance to its opponent. However, calculating the approximate distance with a BLE level signal cannot yield a sufficiently accurate number. Therefore, the prototype of the contact tracing system implements zoning based on the signal level. The results show that the Received Signal Strength Indicator (RSSI) threshold at one meter is accurate for tracing, provided that the devices share the same chipset. Moreover, it is pretty energy-efficient to be installed on a user's Android smartphone because it only requires 14.17 mAh for 6 hours of operation or the equivalent of 2.14 mAh per hour. © 2021 IEEE.
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Objective: To study the role for preoperative CT chest scans in suspected COVID-19 patients requiring emergent surgery. Design: Retrospective - observational. Participants: A total of 98 patients admitted for emergency surgery with COVID-19 infection and underwent preoperative CT chest scanning. Main outcome measurements: Incidence of clinical symptoms of COVID-19 infection upon presentation, imaging characteristics in chest CT and semi-quantitative CT severity score. Results: The median age of the study cohorts was 50 years (interquartile range (IQR): 40-60 years) and 52/98 (53.1%) were males. The most common symptoms were fever (80.6%) and cough (65.3%). 50/98 had positive severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RT-PCR test prior to CT scan, while 48/98 had positive reverse transcriptase-polymerase chain reaction (RT-PCR) result returned after imaging. The imaging characteristics were bilateral infiltrates on CT of 90/98, with 70/98 of infiltrates located peripherally and 28/98 located peripherally and centrally. The most common disease pattern was ground-glass opacities, observed in 95/98. The median total COVID-19 CT severity score was 7 (IQR: 4-14), corresponding to 5-25% global lung involvement. Conclusion: Patients with mild symptomatic COVID-19 in this study displayed CT evidence of SARS-CoV-2 infection. Preoperative CT imaging should be considered for identifying suspected active SARS-CoV-2 cases in resource limited environments with high community spread, to aid in resource allocation and personal protective equipment (PPE) rationing.
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People around the world have used social media extensively to communicate and express opinions especially during this time of the rapid spread of COVID-19. Nowadays, the various narratives of social media users are important that can be used in creating measures to curb the deadly disease. However, the manual collection of data from social media such as Facebook and its analysis can take time. Thus, this study attempted to use natural language processing (NLP) techniques such as topic modeling and word embedding to identify the concepts contained in the posts and comments of Facebook users in the Philippines regarding the pandemic. This study harvested posts and comments in Facebook groups that are primarily Filipino citizens that express opinions and suggestions in COVID-19 responses. Using Latent Dirichlet Allocation (LDA), this study was able to generate 10 topics related to the concepts of (1) self-discipline, (2) prayers for the frontliners, (3) total lockdown, (4) following government guidelines and protocols, and (5) flattening the curve of the disease. Meanwhile, word groups generated by Word2vec developed concepts such as (1) mass testing, (2) hope for faster recovery, and (3) expectation from the government. The average cosine similarity for word groups is 0.92, which implies strong relatedness of each word per group. This study proved that the use of NLP techniques helped in analyzing the themes of Facebook posts and comments related to the pandemic. © 2020 ACM.
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Media as the core source of information and knowledge disperse in the society, its effect on the learning, understanding and analysing about the society in the human minds and cognition is certainly impacted. In focal to the visual media such as advertisement, movies, video etc., it enunciates and indicates a high level of learning process and social learning. Media has a huge impact on the different aspects of cognition in the population, especially on the age category of teenagers and young adults. With the current situation of covid 19, there has been a paradigm shift within the educational sector, forcing visual media as the key source of education and learning, with many countries utilizing remote learning or digital learning to cope with the current educational crisis. This study therefore aims to investigate and understand the impact of the visual media and different video learning platforms in improvement of the social cognition and learning among student. Questionnaire survey method was employed as a tool to collect data from the sample of 250 students between the age group of 16 – 25 and a sample of 155 teachers with the experience of 1 -10 + years in the field of education across UAE and India. The result indicates that the student population showcase a keen interest and participation on the information and knowledge dispersed through screens such as movies and presentation rather than the content published such as newspaper and books. It helps students foster self-awareness, cultural value, cognitive skills and moral wellbeing with the help of visual media. © 2021 Institute of Physics Publishing. All rights reserved.