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      Internet and Pornography Use During the COVID-19 Pandemic: Presumed Impact and What Can Be Done

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          Abstract

          The COVID-19 pandemic continues to cause an immense psychosocial strain worldwide. Excessive use of the internet during these psychologically trying times, fueled by physical isolation as a result of lockdowns, has translated into dysfunctional behaviors. A growing body of evidence suggests an unprecedented increase in internet use and consumption of online pornography during the pandemic, and possibly even directly caused by it. In this review, the authors report data from relevant sources to show the rise in pornography use during lockdowns in different countries worldwide. In addition to a brief overview of the neurobiology of internet addiction broadly and problematic online pornography use specifically, similarities with substance use disorders are explained. Further, the current status of the debate about defining diagnostic criteria is discussed. Finally, the review sheds light on the potential detrimental outcomes during the future post-pandemic “re-adaptation,” while simultaneously offering preventative and management strategies for harm reduction. The authors conclude that foresightedness with utilizing existing tools and therapies and exercising appropriate amounts of caution could go a long way in addressing the challenges that lie ahead in the post-pandemic era.

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          Most cited references72

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          An interactive web-based dashboard to track COVID-19 in real time

          In December, 2019, a local outbreak of pneumonia of initially unknown cause was detected in Wuhan (Hubei, China), and was quickly determined to be caused by a novel coronavirus, 1 namely severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The outbreak has since spread to every province of mainland China as well as 27 other countries and regions, with more than 70 000 confirmed cases as of Feb 17, 2020. 2 In response to this ongoing public health emergency, we developed an online interactive dashboard, hosted by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University, Baltimore, MD, USA, to visualise and track reported cases of coronavirus disease 2019 (COVID-19) in real time. The dashboard, first shared publicly on Jan 22, illustrates the location and number of confirmed COVID-19 cases, deaths, and recoveries for all affected countries. It was developed to provide researchers, public health authorities, and the general public with a user-friendly tool to track the outbreak as it unfolds. All data collected and displayed are made freely available, initially through Google Sheets and now through a GitHub repository, along with the feature layers of the dashboard, which are now included in the Esri Living Atlas. The dashboard reports cases at the province level in China; at the city level in the USA, Australia, and Canada; and at the country level otherwise. During Jan 22–31, all data collection and processing were done manually, and updates were typically done twice a day, morning and night (US Eastern Time). As the outbreak evolved, the manual reporting process became unsustainable; therefore, on Feb 1, we adopted a semi-automated living data stream strategy. Our primary data source is DXY, an online platform run by members of the Chinese medical community, which aggregates local media and government reports to provide cumulative totals of COVID-19 cases in near real time at the province level in China and at the country level otherwise. Every 15 min, the cumulative case counts are updated from DXY for all provinces in China and for other affected countries and regions. For countries and regions outside mainland China (including Hong Kong, Macau, and Taiwan), we found DXY cumulative case counts to frequently lag behind other sources; we therefore manually update these case numbers throughout the day when new cases are identified. To identify new cases, we monitor various Twitter feeds, online news services, and direct communication sent through the dashboard. Before manually updating the dashboard, we confirm the case numbers with regional and local health departments, including the respective centres for disease control and prevention (CDC) of China, Taiwan, and Europe, the Hong Kong Department of Health, the Macau Government, and WHO, as well as city-level and state-level health authorities. For city-level case reports in the USA, Australia, and Canada, which we began reporting on Feb 1, we rely on the US CDC, the government of Canada, the Australian Government Department of Health, and various state or territory health authorities. All manual updates (for countries and regions outside mainland China) are coordinated by a team at Johns Hopkins University. The case data reported on the dashboard aligns with the daily Chinese CDC 3 and WHO situation reports 2 for within and outside of mainland China, respectively (figure ). Furthermore, the dashboard is particularly effective at capturing the timing of the first reported case of COVID-19 in new countries or regions (appendix). With the exception of Australia, Hong Kong, and Italy, the CSSE at Johns Hopkins University has reported newly infected countries ahead of WHO, with Hong Kong and Italy reported within hours of the corresponding WHO situation report. Figure Comparison of COVID-19 case reporting from different sources Daily cumulative case numbers (starting Jan 22, 2020) reported by the Johns Hopkins University Center for Systems Science and Engineering (CSSE), WHO situation reports, and the Chinese Center for Disease Control and Prevention (Chinese CDC) for within (A) and outside (B) mainland China. Given the popularity and impact of the dashboard to date, we plan to continue hosting and managing the tool throughout the entirety of the COVID-19 outbreak and to build out its capabilities to establish a standing tool to monitor and report on future outbreaks. We believe our efforts are crucial to help inform modelling efforts and control measures during the earliest stages of the outbreak.
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            Prevalence of Depression Symptoms in US Adults Before and During the COVID-19 Pandemic

            Key Points Question What is the burden of depression symptoms among US adults during the coronavirus disease 2019 (COVID-19) pandemic compared with before COVID-19, and what are the risk factors associated with depression symptoms? Findings In this survey study that included 1441 respondents from during the COVID-19 pandemic and 5065 respondents from before the pandemic, depression symptom prevalence was more than 3-fold higher during the COVID-19 pandemic than before. Lower income, having less than $5000 in savings, and having exposure to more stressors were associated with greater risk of depression symptoms during COVID-19. Meaning These findings suggest that there is a high burden of depression symptoms in the US associated with the COVID-19 pandemic and that this burden falls disproportionately on individuals who are already at increased risk.
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              A cognitive-behavioral model of pathological Internet use

              R.A. Davis (2001)
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                Author and article information

                Contributors
                Journal
                Front Psychiatry
                Front Psychiatry
                Front. Psychiatry
                Frontiers in Psychiatry
                Frontiers Media S.A.
                1664-0640
                16 March 2021
                2021
                16 March 2021
                : 12
                : 623508
                Affiliations
                [1] 1Dow University of Health Sciences , Karachi, Pakistan
                [2] 2Kabir Medical College, Gandhara University , Peshawar, Pakistan
                [3] 3Department of Child and Adolescent Psychiatry, School of Medicine, New York University , New York, NY, United States
                [4] 4Department of Social and Community Health, School of Population Health, University of Auckland , Auckland, New Zealand
                [5] 5Unit of Clinical Psychiatry, Department of Neurosciences/DIMSC, School of Medicine and Surgery, Polytechnic University of Marche , Ancona, Italy
                [6] 6Psychiatry Unit, Department of Health Sciences, University Magna Graecia of Catanzaro , Catanzaro, Italy
                [7] 7Department of Psychiatry, Jos University Teaching Hospital , Jos, Nigeria
                [8] 8Bhaktshreshtha Kamalakarpant Laxman Walawalkar Rural Medical College , Kasarwadi, India
                [9] 9Smt. Kashibai Navale Medical College and General Hospital , Pune, India
                [10] 10Veterans Affairs Connecticut Healthcare System, Yale University School of Medicine , West Haven, CT, United States
                [11] 11School of Medicine Yale University , New Haven, CT, United States
                Author notes

                Edited by: Hironobu Fujiwara, Kyoto University Hospital, Japan

                Reviewed by: Orsolya Király, Eötvös Loránd University, Hungary; Biljana Gjoneska, Macedonian Academy of Sciences and Arts, North Macedonia

                *Correspondence: Sanya Virani sanya.virani@ 123456yale.edu

                This article was submitted to Addictive Disorders, a section of the journal Frontiers in Psychiatry

                Article
                10.3389/fpsyt.2021.623508
                8007884
                33796031
                12ed2f31-f48e-4f86-b12d-cce756c88786
                Copyright © 2021 Awan, Aamir, Diwan, Ullah, Pereira-Sanchez, Ramalho, Orsolini, de Filippis, Ojeahere, Ransing, Vadsaria and Virani.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 30 October 2020
                : 08 February 2021
                Page count
                Figures: 1, Tables: 1, Equations: 0, References: 78, Pages: 8, Words: 6664
                Categories
                Psychiatry
                Mini Review

                Clinical Psychology & Psychiatry
                covid-19,problematic internet use,pornography,behavioral addictions,mental health

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