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      Anxiety and Panic Buying Behaviour during COVID-19 Pandemic—A Qualitative Analysis of Toilet Paper Hoarding Contents on Twitter

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          Abstract

          Background: The coronavirus disease 2019 (COVID-19) pandemic had increased population-level anxiety and had elicited panic buying behaviour across the world. The over-hoarding of toilet paper has received a lot of negative public attention. In this work, we used Twitter data to qualitatively analyse tweets related to panic buying of toilet paper during the crisis. Methods: A total of 255,171 tweets were collected. Of these 4081 met our inclusion criteria and 100 tweets were randomly selected to develop a coding scheme in the initial phase. Random samples of tweets in folds of 100 were then qualitatively analysed in the focused coding phase until saturation was met at 500 tweets analysed. Results: Five key themes emerged: (1) humour or sarcasm, (2) marketing or profiteering, (3) opinion and emotions, (4) personal experience, and (5) support or information. About half of the tweets carried negative sentiments, expressing anger or frustration towards the deficiency of toilet paper and the frantic situation of toilet paper hoarding, which were among the most influential tweets. Discussion: Panic buying of toilet paper was seen during the 2020 pandemic period with a mass amount of related content spread across social media. The spontaneous contagion of fear and panic through social media could fuel psychological reactions in midst of crises. The high level of negative social media posts regarding the toilet paper crisis acts as an emotional trigger of public anxiety and panic. Conclusions: Social media data can provide rapid infodemiology of public mental health. In a pandemic or crisis situation, real-time data could be monitored and content-analysed for authorities to promptly address public concerns.

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          The novel coronavirus (COVID-2019) outbreak: Amplification of public health consequences by media exposure.

          The 2019 novel coronavirus (COVID-2019) has led to a serious outbreak of often severe respiratory disease, which originated in China and has quickly become a global pandemic, with far-reaching consequences that are unprecedented in the modern era. As public health officials seek to contain the virus and mitigate the deleterious effects on worldwide population health, a related threat has emerged: global media exposure to the crisis. We review research suggesting that repeated media exposure to community crisis can lead to increased anxiety, heightened stress responses that can lead to downstream effects on health, and misplaced health-protective and help-seeking behaviors that can overburden health care facilities and tax available resources. We draw from work on previous public health crises (i.e., Ebola and H1N1 outbreaks) and other collective trauma (e.g., terrorist attacks) where media coverage of events had unintended consequences for those at relatively low risk for direct exposure, leading to potentially severe public health repercussions. We conclude with recommendations for individuals, researchers, and public health officials with respect to receiving and providing effective communications during a public health crisis. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
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            A simple method to assess and report thematic saturation in qualitative research

            Data saturation is the most commonly employed concept for estimating sample sizes in qualitative research. Over the past 20 years, scholars using both empirical research and mathematical/statistical models have made significant contributions to the question: How many qualitative interviews are enough? This body of work has advanced the evidence base for sample size estimation in qualitative inquiry during the design phase of a study, prior to data collection, but it does not provide qualitative researchers with a simple and reliable way to determine the adequacy of sample sizes during and/or after data collection. Using the principle of saturation as a foundation, we describe and validate a simple-to-apply method for assessing and reporting on saturation in the context of inductive thematic analyses. Following a review of the empirical research on data saturation and sample size estimation in qualitative research, we propose an alternative way to evaluate saturation that overcomes the shortcomings and challenges associated with existing methods identified in our review. Our approach includes three primary elements in its calculation and assessment: Base Size, Run Length, and New Information Threshold. We additionally propose a more flexible approach to reporting saturation. To validate our method, we use a bootstrapping technique on three existing thematically coded qualitative datasets generated from in-depth interviews. Results from this analysis indicate the method we propose to assess and report on saturation is feasible and congruent with findings from earlier studies.
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              Pandemics in the Age of Twitter: Content Analysis of Tweets during the 2009 H1N1 Outbreak

              Background Surveys are popular methods to measure public perceptions in emergencies but can be costly and time consuming. We suggest and evaluate a complementary “infoveillance” approach using Twitter during the 2009 H1N1 pandemic. Our study aimed to: 1) monitor the use of the terms “H1N1” versus “swine flu” over time; 2) conduct a content analysis of “tweets”; and 3) validate Twitter as a real-time content, sentiment, and public attention trend-tracking tool. Methodology/Principal Findings Between May 1 and December 31, 2009, we archived over 2 million Twitter posts containing keywords “swine flu,” “swineflu,” and/or “H1N1.” using Infovigil, an infoveillance system. Tweets using “H1N1” increased from 8.8% to 40.5% (R 2 = .788; p<.001), indicating a gradual adoption of World Health Organization-recommended terminology. 5,395 tweets were randomly selected from 9 days, 4 weeks apart and coded using a tri-axial coding scheme. To track tweet content and to test the feasibility of automated coding, we created database queries for keywords and correlated these results with manual coding. Content analysis indicated resource-related posts were most commonly shared (52.6%). 4.5% of cases were identified as misinformation. News websites were the most popular sources (23.2%), while government and health agencies were linked only 1.5% of the time. 7/10 automated queries correlated with manual coding. Several Twitter activity peaks coincided with major news stories. Our results correlated well with H1N1 incidence data. Conclusions This study illustrates the potential of using social media to conduct “infodemiology” studies for public health. 2009 H1N1-related tweets were primarily used to disseminate information from credible sources, but were also a source of opinions and experiences. Tweets can be used for real-time content analysis and knowledge translation research, allowing health authorities to respond to public concerns.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                Int J Environ Res Public Health
                Int J Environ Res Public Health
                ijerph
                International Journal of Environmental Research and Public Health
                MDPI
                1661-7827
                1660-4601
                27 January 2021
                February 2021
                : 18
                : 3
                : 1127
                Affiliations
                [1 ]National Centre for Youth Substance Use Research, The University of Queensland, Brisbane, QLD 4072, Australia; j.leung1@ 123456uq.edu.au (J.L.); c.tisdale@ 123456uq.edu.au (C.T.); vivian.chiu@ 123456uq.net.au (V.C.); c.lim2@ 123456uq.net.au (C.C.W.L.); c.chan4@ 123456uq.edu.au (G.C.)
                [2 ]School of Psychology, The University of Queensland, Brisbane, QLD 4072, Australia
                Author notes
                Author information
                https://orcid.org/0000-0001-5816-2959
                https://orcid.org/0000-0003-3142-3316
                https://orcid.org/0000-0002-8729-3330
                https://orcid.org/0000-0003-1595-6307
                https://orcid.org/0000-0002-7569-1948
                Article
                ijerph-18-01127
                10.3390/ijerph18031127
                7908195
                33514049
                09145d63-7a27-45dd-bb46-b396c8b0b9ed
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 31 December 2020
                : 22 January 2021
                Categories
                Article

                Public health
                covid-19,pandemic,anxiety,panic buying,social media,psychological phenomena,snowball effect
                Public health
                covid-19, pandemic, anxiety, panic buying, social media, psychological phenomena, snowball effect

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