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      Substance use and abuse, COVID-19-related distress, and disregard for social distancing: A network analysis

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          Abstract

          Research shows that there has been a substantial increase in substance use and abuse during the COVID-19 pandemic, and that substance use/abuse is a commonly reported way of coping with anxiety concerning COVID-19. Anxiety about COVID-19 is more than simply worry about infection. Research provides evidence of a COVID Stress Syndrome characterized by (1) worry about the dangers of COVID-19 and worry about coming into contact with coronavirus contaminated objects or surfaces, (2) worry about the personal socioeconomic impact of COVID-19, (3) xenophobic worries that foreigners are spreading COVID-19, (4) COVID-19-related traumatic stress symptoms (e.g., nightmares), and (5) COVID-19-related compulsive checking and reassurance-seeking. These form a network of interrelated nodes. Research also provides evidence of another constellation or “syndrome”, characterized by (1) belief that one has robust physical health against COVID-19, (2) belief that the threat of COVID-19 has been exaggerated, and (3) disregard for social distancing. These also form a network of nodes known as a COVID-19 Disregard Syndrome. The present study, based on a population-representative sample of 3075 American and Canadian adults, sought to investigate how these syndromes are related to substance use and abuse. We found substantial COVID-19-related increases in alcohol and drug use. Network analyses indicated that although the two syndromes are negatively correlated with one another, they both have positive links to alcohol and drug abuse. More specifically, COVID-19-related traumatic stress symptoms and the tendency to disregard social distancing were both linked to substance abuse. Clinical and public health implications are discussed.

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          Most cited references31

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          Estimating psychological networks and their accuracy: A tutorial paper

          The usage of psychological networks that conceptualize behavior as a complex interplay of psychological and other components has gained increasing popularity in various research fields. While prior publications have tackled the topics of estimating and interpreting such networks, little work has been conducted to check how accurate (i.e., prone to sampling variation) networks are estimated, and how stable (i.e., interpretation remains similar with less observations) inferences from the network structure (such as centrality indices) are. In this tutorial paper, we aim to introduce the reader to this field and tackle the problem of accuracy under sampling variation. We first introduce the current state-of-the-art of network estimation. Second, we provide a rationale why researchers should investigate the accuracy of psychological networks. Third, we describe how bootstrap routines can be used to (A) assess the accuracy of estimated network connections, (B) investigate the stability of centrality indices, and (C) test whether network connections and centrality estimates for different variables differ from each other. We introduce two novel statistical methods: for (B) the correlation stability coefficient, and for (C) the bootstrapped difference test for edge-weights and centrality indices. We conducted and present simulation studies to assess the performance of both methods. Finally, we developed the free R-package bootnet that allows for estimating psychological networks in a generalized framework in addition to the proposed bootstrap methods. We showcase bootnet in a tutorial, accompanied by R syntax, in which we analyze a dataset of 359 women with posttraumatic stress disorder available online. Electronic supplementary material The online version of this article (doi:10.3758/s13428-017-0862-1) contains supplementary material, which is available to authorized users.
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            Thanks Coefficient Alpha, We’ll Take It From Here.

            Empirical studies in psychology commonly report Cronbach's alpha as a measure of internal consistency reliability despite the fact that many methodological studies have shown that Cronbach's alpha is riddled with problems stemming from unrealistic assumptions. In many circumstances, violating these assumptions yields estimates of reliability that are too small, making measures look less reliable than they actually are. Although methodological critiques of Cronbach's alpha are being cited with increasing frequency in empirical studies, in this tutorial we discuss how the trend is not necessarily improving methodology used in the literature. That is, many studies continue to use Cronbach's alpha without regard for its assumptions or merely cite methodological articles advising against its use to rationalize unfavorable Cronbach's alpha estimates. This tutorial first provides evidence that recommendations against Cronbach's alpha have not appreciably changed how empirical studies report reliability. Then, we summarize the drawbacks of Cronbach's alpha conceptually without relying on mathematical or simulation-based arguments so that these arguments are accessible to a broad audience. We continue by discussing several alternative measures that make less rigid assumptions which provide justifiably higher estimates of reliability compared to Cronbach's alpha. We conclude with empirical examples to illustrate advantages of alternative measures of reliability including omega total, Revelle's omega total, the greatest lower bound, and Coefficient H. A detailed software appendix is also provided to help researchers implement alternative methods. (PsycINFO Database Record
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              Development and Initial Validation of the COVID Stress Scales

              Highlights • A large population-representative was surveyed to better understand COVID-19-related psychopathology. • We developed and validated the COVID Stress Scales, comprising 36 items on 5 scales. • The COVID Stress Scales offer promise for identifying people in need of pandemic-related mental health services.
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                Author and article information

                Journal
                Addict Behav
                Addict Behav
                Addictive Behaviors
                Elsevier Ltd.
                0306-4603
                1873-6327
                3 December 2020
                March 2021
                3 December 2020
                : 114
                : 106754
                Affiliations
                [a ]Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
                [b ]Department of Psychology, University of Regina, Regina, SK, Canada
                [c ]Department of Psychology, Fordham University of Regina, NY, USA
                Author notes
                [* ]Corresponding author at: Department of Psychiatry, University of British Columbia, Vancouver V6E 2A1, Canada.
                Article
                S0306-4603(20)30883-2 106754
                10.1016/j.addbeh.2020.106754
                8164919
                33310690
                716463f9-d57a-43a4-b23d-1fe56ab5d3da
                © 2020 Elsevier Ltd. All rights reserved.

                Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

                History
                : 30 September 2020
                : 22 November 2020
                : 23 November 2020
                Categories
                Article

                Clinical Psychology & Psychiatry
                covid-19,covid stress syndrome,social distancing,alcohol abuse,drug abuse,network analysis

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