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ionals safeguard the psychological well-being of students facing an expanding COVID-19 pandemic.
PRR1-10.2196/28757.
PRR1-10.2196/28757.
Since the beginning of the COVID-19 pandemic, a great number of papers have been published in the pediatric field.
We aimed to assess research around the globe on COVID-19 in the pediatric field by bibliometric analysis, identifying publication trends and topic dissemination and showing the relevance of publishing authors, institutions, and countries.
The Scopus database was comprehensively searched for all indexed documents published between January 1, 2020, and June 11, 2020, dealing with COVID-19 in the pediatric population (0-18 years). A machine learning bibliometric methodology was applied to evaluate the total number of papers and citations, journal and publication types, the top productive institutions and countries and their scientific collaboration, and core keywords.
A total of 2301 papers were retrieved, with an average of 4.8 citations per article. Of this, 1078 (46.9%) were research articles, 436 (18.9%) were reviews, 363 (15.8%) were letters, 186 (8.1%) were editorials, 7 (0.3%) were co large number of articles were published within a limited period on COVID-19, testifying to the rush to spread new findings on the topic in a timely manner. The leading authors, countries, and institutions evidently belonged to the most impacted geographical areas. A focus on the pediatric population was often included in general articles, and pediatric research about COVID-19 mainly focused on the clinical features, public health issues, and psychological impact of the disease.
Digital technology use is nearly ubiquitous among young adults, this use provides both benefits and risks. Risks of technology use include maladaptive technology use or technology addiction. Several conceptualizations of these addictions have emerged, each with their own assessment tools. These conditions include Problematic Internet Use (PIU), Internet Gaming Disorder (IGD) and Social Media Addiction (SMA). These conditions have been associated with health outcomes such as problematic alcohol use, sleep disorders and mental illness. These maladaptive technology conditions have most commonly been studied in isolation from each other.
The purpose of this study was to examine PIU, IGD and SMA together to better inform future research approaches and provider screening practices for young adults.
This cross-sectional survey study was conducted using Qualtrics panel-based recruitment and survey hosting. We recruited US young adults ages 18-25 years. Selleckchem PF-05221304 The survey assessed PIU, IGD and SMA. Survey measures also demographic variables and similar overlap with health outcomes. The sensitivity of PIU screening to detect IGD was 82%, and to detect SMA was 93%, while the specificity and positive predictive value were much lower (37-54% specificity, 6-37% positive predictive value).
This cross-sectional survey screened a large national sample of AYAs for PIU, IGD and SMA to determine prevalence and overlap, demographic associations with each, and associations between these technology-related conditions and health outcomes. There was overlap across PIU, IGD and SMA in some associated demographic variables as well as health outcomes. However, the patterns in associated variables demonstrated unique qualities of each of these conditions.
A disproportionate number of COVID-19 cases affect older, minority populations. Obese older adults are at higher risk for severe COVID-19 complications and lower survival rates; minority older adults often experience higher rates of obesity. A plant-based diet intervention may improve COVID-19 obesity modifiable risk factors. Encouraging the consumption plant-based diets consisting of vegetables, fruits, whole grains, legumes, seeds, and nuts utilizing community outreach strategies and digital technology can contribute to improving COVID-19 risk factors.
A disproportionate number of COVID-19 cases affect older, minority populations. Obese older adults are at higher risk for severe COVID-19 complications and lower survival rates; minority older adults often experience higher rates of obesity. A plant-based diet intervention may improve COVID-19 obesity modifiable risk factors. Encouraging the consumption plant-based diets consisting of vegetables, fruits, whole grains, legumes, seeds, and nuts utilizing community outreach strategies and digital technology can contribute to improving COVID-19 risk factors.
The COVID-19 pandemic has had enormous impacts on people's lives, including disruptions to their normal ways of behaving, working, and interacting with others. Understanding and documenting these experiences is important to inform the ongoing response to COVID-19 and disaster preparedness efforts.
The aim of this study was to examine the psychosocial impacts of COVID-19 on a sample of Australian adults.
The data analyzed were derived from a larger cross-sectional survey of Australian adults that was administered during the month of May 2020. Participants (N=3483) were asked in which ways COVID-19 had most greatly impacted them; the responses produced a text data set containing 1 COVID-19 impact story for each participant, totaling 86,642 words. Participants also completed assessments of their sociodemographic characteristics (sex, age, financial stress), level of concern related to COVID-19, personality trait profile, and satisfaction with life. Impact stories were analyzed using sentiment analysis and Findings may inform the development of mental health and social support resources and interventions to help alleviate the psychosocial consequences of disaster response measures.
COVID-19 transmission rates in South Asia initially were under control when governments implemented health policies aimed at controlling the pandemic such as quarantines, travel bans, and border, business, and school closures. Governments have since relaxed public health restrictions, which resulted in significant outbreaks, shifting the global epicenter of COVID-19 to India. Ongoing systematic public health surveillance of the COVID-19 pandemic is needed to inform disease prevention policy to re-establish control over the pandemic within South Asia.
This study aimed to inform public health leaders about the state of the COVID-19 pandemic, how South Asia displays differences within and among countries and other global regions, and where immediate action is needed to control the outbreaks.
We extracted COVID-19 data spanning 62 days from public health registries and calculated traditional and enhanced surveillance metrics. We use an empirical difference equation to measure the daily number of cases in Sor 100,000 population, which constitutes an increased outbreak.
Relaxation of public health restrictions and the spread of novel variants fueled the second wave of the COVID-19 pandemic in South Asia. Public health surveillance indicates that shifts in policy and the spread of new variants correlate with a drastic expansion in the pandemic, requiring immediate action to mitigate the spread of COVID-19. Surveillance is needed to inform leaders whether policies help control the pandemic.
Relaxation of public health restrictions and the spread of novel variants fueled the second wave of the COVID-19 pandemic in South Asia. Public health surveillance indicates that shifts in policy and the spread of new variants correlate with a drastic expansion in the pandemic, requiring immediate action to mitigate the spread of COVID-19. Surveillance is needed to inform leaders whether policies help control the pandemic.
COVID-19 has created serious mental health consequences for people who are designated as essential workers or have become unemployed as a result of the pandemic. Digital mental health tools have the potential to address this problem in a timely and efficient manner.
The purpose of this study was to document the extent of digital mental health tool use (DMHT) by essential workers and those unemployed due to COVID-19, including asking participants to rate the usability and user burden of the DMHT they used most to cope. We also explored which tools and features of DMHTs were seen as necessary for managing stress during a pandemic through the design their own ideal DMHT.
Two thousand people were recruited from an online research community (Prolific) and completed a one-time survey about mental health symptoms, digital mental health use and preferred digital mental health features.
The final sample included 1,987 United States residents that identified as either an essential worker or someone who was unemchology (1131/1986, 56.9%). Subgroups by employment, distress, and previous DMHT use status had varied preferences. Of those who did not use a DMHT to cope with COVID-19, most indicated that they did not consider looking for such a tool to cope (1179/1710, 68.9%).
Despite potential need for DMHTs, this study found that use of such tools remains like pre-pandemic levels. This study also found that regardless of level of distress or even past experience using an app to cope with COVID-19, it is possible to develop a COVID-19 coping app that would appeal to a majority of essential workers and unemployed persons.
Despite potential need for DMHTs, this study found that use of such tools remains like pre-pandemic levels. This study also found that regardless of level of distress or even past experience using an app to cope with COVID-19, it is possible to develop a COVID-19 coping app that would appeal to a majority of essential workers and unemployed persons.
COVID-19 testing remains an essential element of a comprehensive strategy for community mitigation. Social media is a popular source of information about health, including COVID-19 and testing information. One of the most popular communication channels used by adolescents and young adults who search for health information is TikTok-an emerging social media platform.
The purpose of this study was to describe TikTok videos related to COVID-19 testing.
The hashtag #covidtesting was searched, and the first 100 videos were included in the study sample. At the time the sample was drawn, these 100 videos garnered more than 50% of the views for all videos cataloged under the hashtag #covidtesting. The content characteristics that were coded included mentions, displays, or suggestions of anxiety, COVID-19 symptoms, quarantine, types of tests, results of test, and disgust/unpleasantness. Additional data that were coded included the number and percentage of views, likes, and comments and the use of music, dance, aeed for public health agencies to recognize and address connotations of COVID-19 testing on social media.
Our finding of an association between TikTok videos that mentioned or suggested that COVID-19 tests were disgusting/unpleasant and these videos' propensity to garner views and likes is of concern. There is a need for public health agencies to recognize and address connotations of COVID-19 testing on social media.Deep learning-based methods have achieved notable progress in removing blocking artifacts caused by lossy JPEG compression on images. However, most deep learning-based methods handle this task by designing black-box network architectures to directly learn the relationships between the compressed images and their clean versions. These network architectures are always lack of sufficient interpretability, which limits their further improvements in deblocking performance. To address this issue, in this article, we propose a model-driven deep unfolding method for JPEG artifacts removal, with interpretable network structures. First, we build a maximum posterior (MAP) model for deblocking using convolutional dictionary learning and design an iterative optimization algorithm using proximal operators. Second, we unfold this iterative algorithm into a learnable deep network structure, where each module corresponds to a specific operation of the iterative algorithm. In this way, our network inherits the benefits of both the powerful model ability of data-driven deep learning method and the interpretability of traditional model-driven method.