Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 20 de 1.278
Filter
Add filters

Document Type
Year range
2.
Int J Environ Res Public Health ; 18(24)2021 12 09.
Article in English | MEDLINE | ID: covidwho-1613808

ABSTRACT

During the recent COVID-19 pandemic, people have, in many cases, acquired information primarily from social media. Users' need to stay informed and the intensive circulation of news has led to the spread of misinformation. As they have engaged in news, it has raised the question of trust. This study provides a model on how news trust can be explained through a need for cognition and news engagement. Accordingly, 433 Slovenian social media users participated in our survey. Structural equation modeling revealed that (1) the lower the need for cognition and the more prior knowledge about COVID-19 users have, the more they believe that social media news comprises all facts about the disease; (2) the more users believe that news comprises all essential facts, the more they trust that the news depicts the actual situation about COVID-19 accurately; (3) the more users are interested in engaging with social media news, the more they trust that the actual situation about COVID-19 is depicted accurately. These findings may help authorities to frame messages about COVID-19 effectively. We suggest investing more effort in disseminating new scientific evidence about the disease to contribute to the accurate shaping of knowledge about COVID-19 among social media users.


Subject(s)
COVID-19 , Social Media , Cognition , Humans , Pandemics , SARS-CoV-2 , Trust
3.
Int J Environ Res Public Health ; 19(1)2022 Jan 05.
Article in English | MEDLINE | ID: covidwho-1613773

ABSTRACT

The development of health sciences researchers has immense significance during a pandemic to control, manage, and prevent future outbreaks of the disease. This study focused on the use of social media tools (SMT) among pre-service health sciences researchers to complement their research competencies (RCT) and research completion levels (RC) during COVID-19. This study used the Vitae research development framework (RDF) to measure research competencies as a mediator between the use of social media tools and research completion levels among post-graduate health sciences students. A cross-section survey research approach was adopted to collect data from the post-graduate students (n = 410) enrolled in health sciences departments at universities in Pakistan. The SmartPLS 3.3.8 software was used to analyze data through Partial least square structural equation modeling (PLS-SEM). The results revealed that different social media tools such as communication, information management, and multimedia have a direct influence on the research competencies of the pre-service researchers and have an indirect effect on the research completion levels. Health sciences institutions may devise social-media-based instructional strategies to develop post-graduate students' research competencies, such as personal effectiveness, research governance, and research engagement, to help them compile their research and complete their degree program in time during an emergency.


Subject(s)
COVID-19 , Social Media , Humans , Pakistan , Pandemics , SARS-CoV-2
5.
Philos Trans A Math Phys Eng Sci ; 380(2214): 20210125, 2022 Jan 10.
Article in English | MEDLINE | ID: covidwho-1605660

ABSTRACT

The outbreak of the novel coronavirus, COVID-19, has become one of the most severe pandemics in human history. In this paper, we propose to leverage social media users as social sensors to simultaneously predict the pandemic trends and suggest potential risk factors for public health experts to understand spread situations and recommend proper interventions. More precisely, we develop novel deep learning models to recognize important entities and their relations over time, thereby establishing dynamic heterogeneous graphs to describe the observations of social media users. A dynamic graph neural network model can then forecast the trends (e.g. newly diagnosed cases and death rates) and identify high-risk events from social media. Based on the proposed computational method, we also develop a web-based system for domain experts without any computer science background to easily interact with. We conduct extensive experiments on large-scale datasets of COVID-19 related tweets provided by Twitter, which show that our method can precisely predict the new cases and death rates. We also demonstrate the robustness of our web-based pandemic surveillance system and its ability to retrieve essential knowledge and derive accurate predictions across a variety of circumstances. Our system is also available at http://scaiweb.cs.ucla.edu/covidsurveiller/. This article is part of the theme issue 'Data science approachs to infectious disease surveillance'.


Subject(s)
COVID-19 , Social Media , Data Mining , Humans , Pandemics , SARS-CoV-2
6.
Front Public Health ; 9: 788848, 2021.
Article in English | MEDLINE | ID: covidwho-1608692

ABSTRACT

The capturing of social opinions, especially rumors, is a crucial issue in digital public health. With the outbreak of the COVID-19 pandemic, the discussions of related topics have increased exponentially in social media, with a large number of rumors on the Internet, which highly impede the harmony and sustainable development of society. As human health has never suffered a threat of this magnitude since the Internet era, past studies have lacked in-depth analysis of rumors regarding such a globally sweeping pandemic. This text-based analysis explores the dynamic features of Internet rumors during the COVID-19 pandemic considering the progress of the pandemic as time-series. Specifically, a Latent Dirichlet Allocation (LDA) model is used to extract rumor topics that spread widely during the pandemic, and the extracted six rumor topics, i.e., "Human Immunity," "Technology R&D," "Virus Protection," "People's Livelihood," "Virus Spreading," and "Psychosomatic Health" are found to show a certain degree of concentrated distribution at different stages of the pandemic. Linguistic Inquiry and Word Count (LIWC) is used to statistically test the psychosocial dynamics reflected in the rumor texts, and the results show differences in psychosocial characteristics of rumors at different stages of the pandemic progression. There are also differences in the indicators of psychosocial characteristics between truth and disinformation. Our results reveal which topics of rumors and which psychosocial characteristics are more likely to spread at each stage of progress of the pandemic. The findings contribute to a comprehensive understanding of the changing public opinions and psychological dynamics during the pandemic, and also provide reference for public opinion responses to major public health emergencies that may arise in the future.


Subject(s)
COVID-19 , Social Media , Humans , Pandemics , SARS-CoV-2
8.
Int J Environ Res Public Health ; 18(24)2021 12 16.
Article in English | MEDLINE | ID: covidwho-1593389

ABSTRACT

Neglecting oral hygiene in adolescents negatively affects dental caries and periodontal diseases, in addition to social and emotional well-being. Thus, the TikTok platform (ByteDance, Beijing, China)as a social media could be a powerful channel to provide health-related information and educational content. This study aims to assess the quality of the TikTok videos corresponding to #oralhealtheducation. Sixty-nine videos were identified. Three oral health professionals (OHP), three health education professionals (HEP), and ten of TikTok's target audience watched and evaluated the videos from a qualitative questionnaire. OHP detected false or incorrect information in 11.6% (8/69) of the videos. At least two HEPs reported being unable to detect this type of content or whether the video met dental ethics standards in both the videos. Disagreement was observed among the professionals themselves. The evaluation indicated that TikTok's target audience was satisfied with the products viewed with an average score of >2.5, unlike the professionals, whose average score was <2.5 on a scale of 0 to 5. Users are advised to think critically and to consider the content of TikTok oral health videos with caution. The involvement of health professionals in the writing and validation of the videos could be an added value to positively respond to the needs of the adolescents.


Subject(s)
COVID-19 , Dental Caries , Social Media , Adolescent , Health Education , Health Education, Dental , Humans , Video Recording
9.
J Med Internet Res ; 23(12): e30753, 2021 12 22.
Article in English | MEDLINE | ID: covidwho-1593102

ABSTRACT

BACKGROUND: Expanding access to and use of medication for opioid use disorder (MOUD) is a key component of overdose prevention. An important barrier to the uptake of MOUD is exposure to inaccurate and potentially harmful health misinformation on social media or web-based forums where individuals commonly seek information. There is a significant need to devise computational techniques to describe the prevalence of web-based health misinformation related to MOUD to facilitate mitigation efforts. OBJECTIVE: By adopting a multidisciplinary, mixed methods strategy, this paper aims to present machine learning and natural language analysis approaches to identify the characteristics and prevalence of web-based misinformation related to MOUD to inform future prevention, treatment, and response efforts. METHODS: The team harnessed public social media posts and comments in the English language from Twitter (6,365,245 posts), YouTube (99,386 posts), Reddit (13,483,419 posts), and Drugs-Forum (5549 posts). Leveraging public health expert annotations on a sample of 2400 of these social media posts that were found to be semantically most similar to a variety of prevailing opioid use disorder-related myths based on representational learning, the team developed a supervised machine learning classifier. This classifier identified whether a post's language promoted one of the leading myths challenging addiction treatment: that the use of agonist therapy for MOUD is simply replacing one drug with another. Platform-level prevalence was calculated thereafter by machine labeling all unannotated posts with the classifier and noting the proportion of myth-indicative posts over all posts. RESULTS: Our results demonstrate promise in identifying social media postings that center on treatment myths about opioid use disorder with an accuracy of 91% and an area under the curve of 0.9, including how these discussions vary across platforms in terms of prevalence and linguistic characteristics, with the lowest prevalence on web-based health communities such as Reddit and Drugs-Forum and the highest on Twitter. Specifically, the prevalence of the stated MOUD myth ranged from 0.4% on web-based health communities to 0.9% on Twitter. CONCLUSIONS: This work provides one of the first large-scale assessments of a key MOUD-related myth across multiple social media platforms and highlights the feasibility and importance of ongoing assessment of health misinformation related to addiction treatment.


Subject(s)
Opioid-Related Disorders , Social Media , Communication , Humans , Machine Learning , Opioid-Related Disorders/drug therapy , Opioid-Related Disorders/epidemiology , Prevalence
10.
Sensors (Basel) ; 21(24)2021 Dec 08.
Article in English | MEDLINE | ID: covidwho-1592974

ABSTRACT

The encroachment of wild boars into urban areas is a growing problem. The occurrence of wild boars in cities leads to conflict situations. Socio-spatial conflicts can escalate to a varied degree. Assessments of these conflicts can be performed by analyzing spatial data concerning the affected locations and wild boar behaviors. The collection of spatial data is a laborious and costly process that requires access to urban surveillance systems, in addition to regular analyses of intervention reports. A supporting method for assessing the risk of wild boar encroachment and socio-spatial conflict in cities was proposed in the present study. The developed approach relies on big data, namely, multimedia and descriptive data that are on social media. The proposed method was tested in the city of Olsztyn in Poland. The main aim of this study was to evaluate the applicability of data crowdsourced from a popular social networking site for determining the location and severity of conflicts. A photointerpretation method and the kernel density estimation (KDE) tool implemented in ArcGIS Desktop 10.7.1 software were applied in the study. The proposed approach fills a gap in the application of crowdsourcing data to identify types of socio-spatial conflicts involving wild boars in urban areas. Validation of the results with reports of calls to intervention services showed the high coverage of this approach and thus the usefulness of crowdsourcing data.


Subject(s)
Social Media , Sus scrofa , Animals , Cities , Humans , Poland , Spatial Analysis , Swine
11.
J Med Internet Res ; 23(12): e27599, 2021 12 20.
Article in English | MEDLINE | ID: covidwho-1598927

ABSTRACT

BACKGROUND: eHealth and social media could be of particular benefit to adults with hearing impairment, but it is unknown whether their use of smart devices, apps, and social media is similar to that of the general population. OBJECTIVE: Our aim is to study whether adults with normal hearing and those with impaired hearing differ in their weekly use of smart devices, apps, and social media; reasons for using social media; and benefits from using social media. METHODS: We used data from a Dutch cohort, the National Longitudinal Study on Hearing. Data were collected from September 2016 to April 2020 using a web-based questionnaire and speech-in-noise test. The results from this test were used to categorize normal hearing and hearing impairment. Outcomes were compared using (multiple) logistic regression models. RESULTS: Adults with impaired hearing (n=384) did not differ from normal hearing adults (n=341) in their use of a smartphone or tablet. They were less likely to make use of social media apps on a smartphone, tablet, or smartwatch (age-adjusted odds ratio [OR] 0.67, 95% CI 0.48-0.92; P=.02). Use of social media on all devices and use of other apps did not differ. Adults with hearing impairment were more likely to agree with using social media to stay in touch with family members (OR 1.54, 95% CI 1.16-2.07; P=.003) and friends (age-adjusted OR 1.35, 95% CI 1.01-1.81; P=.046). Furthermore, they were more likely to agree with using social media to perform their work (age-adjusted OR 1.51, 95% CI 1.04-2.18; P=.03). There were no differences in the experienced benefits from social media. CONCLUSIONS: The potential for eHealth is confirmed because adults with hearing impairment are not less likely to use smart devices than their normal hearing peers. Adults with hearing impairment are less likely to use social media apps on a smart device but not less likely to use social media on all types of internet-connected devices. This warrants further research on the types of social media platforms that adults with hearing impairment use and on the type of device on which they prefer to use social media. Given that participants with hearing impairment are more likely than their normal hearing peers to use social media to perform their work, use of social media may be seen as an opportunity to enhance vocational rehabilitation services for persons with hearing impairment.


Subject(s)
Hearing Loss , Mobile Applications , Social Media , Adult , Cross-Sectional Studies , Humans , Longitudinal Studies , Smartphone
12.
J Med Internet Res ; 23(12): e28318, 2021 12 20.
Article in English | MEDLINE | ID: covidwho-1598280

ABSTRACT

BACKGROUND: Chronic obstructive pulmonary disease (COPD) has become one of the most critical public health problems worldwide. Because many COPD patients are using video-based social media to search for health information, there is an urgent need to assess the information quality of COPD videos on social media. Recently, the short-video app TikTok has demonstrated huge potential in disseminating health information and there are currently many COPD videos available on TikTok; however, the information quality of these videos remains unknown. OBJECTIVE: The aim of this study was to investigate the information quality of COPD videos on TikTok. METHODS: In December 2020, we retrieved and screened 300 videos from TikTok and collected a sample of 199 COPD-related videos in Chinese for data extraction. We extracted the basic video information, coded the content, and identified the video sources. Two independent raters assessed the information quality of each video using the DISCERN instrument. RESULTS: COPD videos on TikTok came mainly from two types of sources: individual users (n=168) and organizational users (n=31). The individual users included health professionals, individual science communicators, and general TikTok users, whereas the organizational users consisted of for-profit organizations, nonprofit organizations, and news agencies. For the 199 videos, the mean scores of the DISCERN items ranged from 3.42 to 4.46, with a total mean score of 3.75. Publication reliability (P=.04) and overall quality (P=.02) showed significant differences across the six types of sources, whereas the quality of treatment choices showed only a marginally significant difference (P=.053) across the different sources. CONCLUSIONS: The overall information quality of COPD videos on TikTok is satisfactory, although the quality varies across different sources and according to specific quality dimensions. Patients should be selective and cautious when watching COPD videos on TikTok.


Subject(s)
COVID-19 , Pulmonary Disease, Chronic Obstructive , Social Media , Humans , Information Dissemination , Public Health , Pulmonary Disease, Chronic Obstructive/therapy , Reproducibility of Results , Video Recording
13.
BMC Res Notes ; 14(1): 463, 2021 Dec 20.
Article in English | MEDLINE | ID: covidwho-1582019

ABSTRACT

OBJECTIVES: During the COVID-19 pandemic, most countries implemented lockdowns that motivated changes in the dietary patterns, physical activity, and body mass index (BMI) of consumers worldwide, as well as the emergence of new food marketing strategies in social media. We sought to design and validate a methodology for monitoring and evaluating the Facebook marketing strategies of multinational fast-food chains in response to the COVID-19 pandemic. DATA DESCRIPTION: We developed three datasets. First, a dataset with the Uniform Resource Locators (URLs) of 1015 Facebook posts of five fast-food chains present in Argentina, Bolivia, Guatemala, and Peru. Second, a dataset of 106 content-analyzed posts we used in a pilot to determine intercoder reliability using statistical tests. Third, a dataset of a final sample of the 1015 content-analyzed posts that we used to determine the variables most frequently used. Following a mixed-methods approach, we developed 29 variables that recorded general information, as well as the marketing strategies we identified in the posts, including 14 COVID-19 specific variables. These data should help to monitor the social media marketing strategies that fast-food chains have introduced during the COVID-19 lockdowns, thus providing initial evidence about how they could be contributing to an unhealthy food environment.


Subject(s)
COVID-19 , Social Media , Communicable Disease Control , Humans , Latin America , Marketing , Pandemics , Reproducibility of Results , SARS-CoV-2
14.
PLoS One ; 16(12): e0259882, 2021.
Article in English | MEDLINE | ID: covidwho-1581788

ABSTRACT

COVID-19 has ruptured routines and caused breakdowns in what had been conventional practice and custom: everything from going to work and school and shopping in the supermarket to socializing with friends and taking holidays. Nonetheless, COVID-19 does provide an opportunity to study how people make sense of radically changing circumstances over time. In this paper we demonstrate how Twitter affords this opportunity by providing data in real time, and over time. In the present research, we collect a large pool of COVID-19 related tweets posted by New Zealanders-citizens of a country successful in containing the coronavirus-from the moment COVID-19 became evident to the world in the last days of 2019 until 19 August 2020. We undertake topic modeling on the tweets to foster understanding and sensemaking of the COVID-19 tweet landscape in New Zealand and its temporal development and evolution over time. This information can be valuable for those interested in how people react to emergent events, including researchers, governments, and policy makers.


Subject(s)
COVID-19 , Communication , Humans , Social Media
16.
Front Public Health ; 9: 756360, 2021.
Article in English | MEDLINE | ID: covidwho-1581117

ABSTRACT

Suicide events may have a negative impact on all of society. The media plays a significant role in suicide prevention. Therefore, the aims of this study are (a) to understand the association between characteristics of suicide events and characteristics of who committed suicide, and event impact indexes (EIIs) of suicide reported on the internet; (b) to analyze violation of recommendations for reporting suicide by Weibo, and (c) to investigate the effect of online reports of suicide on public opinion. We carried out a content analysis of online reports of suicide. This study analyzed 113 suicide events, 300 news reports of suicide, and 2,654 Weibo comments about suicide collected from the WeiboReach between 2015 and 2020. We used a t-test and analysis of variance (ANOVA) to explore the potential factors associated with the EIIs of suicide events. The results found that (a) The suicide events reported on the internet during COVID-19 and those related to celebrities and students tend to have higher EIIs; (b) suicide reports on Weibo frequently violated WHO recommendations for suicide reporting in the media; and (c) public opinion of suicide reporting in the online media was mostly emotional and irrational, which is not beneficial for public mental health and suicide prevention. In conclusion, first, the situation of many people working from home or studying from home and spreading more time online during COVID-19 may lead to suicide events obtain more public attention. Online media could further improve public responsible reporting and daily media-content surveillance, especially taking particular care in those suicide events during COVID-19, and related to celebrities and students, which may have a higher event impact on the internet. Second, health managers should regular assessment of observance of the WHO recommendations for suicide reporting by online social media to prevent suicide. Third, health communication managers should use big data to identify, assess, and manage harmful information about suicide; and track anyone affected by suicide-related reports on social media to reduce the negative impact of public opinion to intervene suicide in the early stage of suicide.


Subject(s)
COVID-19 , Social Media , Suicide , Humans , Public Opinion , SARS-CoV-2 , Suicide/prevention & control
17.
Front Public Health ; 9: 770111, 2021.
Article in English | MEDLINE | ID: covidwho-1581113

ABSTRACT

Background: The spread of rumors related to COVID-19 on social media has posed substantial challenges to public health governance, and thus exposing rumors and curbing their spread quickly and effectively has become an urgent task. This study aimed to assist in formulating effective strategies to debunk rumors and curb their spread on social media. Methods: A total of 2,053 original postings and 100,348 comments that replied to the postings of five false rumors related to COVID-19 (dated from January 20, 2020, to June 28, 2020) belonging to three categories, authoritative, social, and political, on Sina Weibo in China were randomly selected. To study the effectiveness of different debunking methods, a new annotation scheme was proposed that divides debunking methods into six categories: denial, further fact-checking, refutation, person response, organization response, and combination methods. Text classifiers using deep learning methods were built to automatically identify four user stances in comments that replied to debunking postings: supporting, denying, querying, and commenting stances. Then, based on stance responses, a debunking effectiveness index (DEI) was developed to measure the effectiveness of different debunking methods. Results: The refutation method with cited evidence has the best debunking effect, whether used alone or in combination with other debunking methods. For the social category of Car rumor and political category of Russia rumor, using the refutation method alone can achieve the optimal debunking effect. For authoritative rumors, a combination method has the optimal debunking effect, but the most effective combination method requires avoiding the use of a combination of a debunking method where the person or organization defamed by the authoritative rumor responds personally and the refutation method. Conclusion: The findings provide relevant insights into ways to debunk rumors effectively, support crisis management of false information, and take necessary actions in response to rumors amid public health emergencies.


Subject(s)
COVID-19 , Social Media , Humans , Pandemics/prevention & control , Public Health , SARS-CoV-2
18.
Front Public Health ; 9: 798905, 2021.
Article in English | MEDLINE | ID: covidwho-1581098

ABSTRACT

The exponential growth of social media users has changed the dynamics of retrieving the potential information from user-generated content and transformed the paradigm of information-retrieval mechanism with the novel developments on the concept of "web of data". In this regard, our proposed Ontology-Based Sentiment Analysis provides two novel approaches: First, the emotion extraction on tweets related to COVID-19 is carried out by a well-formed taxonomy that comprises possible emotional concepts with fine-grained properties and polarized values. Second, the potential entities present in the tweet can be analyzed for semantic associativity. The extraction of emotions can be performed in two cases: (i) words directly associated with the emotional concepts present in the taxonomy and (ii) words indirectly present in the emotional concepts. Though the latter case is very challenging in processing the tweets to find the hidden patterns and extract the meaningful facts associated with it, our proposed work is able to extract and detect almost 81% of true positives and considerably able to detect the false negatives. Finally, the proposed approach's superior performance is witnessed from its comparison with other peer-level approaches.


Subject(s)
COVID-19 , Social Media , Emotions , Humans , Pandemics , SARS-CoV-2
19.
Int J Environ Res Public Health ; 19(1)2021 12 26.
Article in English | MEDLINE | ID: covidwho-1580811

ABSTRACT

In July 2021, breakthrough cases were reported in the outbreak of COVID-19 in Nanjing, sparking concern and discussion about the vaccine's effectiveness and becoming a trending topic on Sina Weibo. In order to explore public attitudes towards the COVID-19 vaccine and their emotional orientations, we collected 1542 posts under the trending topic through data mining. We set up four categories of attitudes towards COVID-19 vaccines, and used a big data analysis tool to code and manually checked the coding results to complete the content analysis. The results showed that 45.14% of the Weibo posts (n = 1542) supported the COVID-19 vaccine, 12.97% were neutral, and 7.26% were doubtful, which indicated that the public did not question the vaccine's effectiveness due to the breakthrough cases in Nanjing. There were 66.47% posts that reflected significant negative emotions. Among these, 50.44% of posts with negative emotions were directed towards the media, 25.07% towards the posting users, and 11.51% towards the public, which indicated that the negative emotions were not directed towards the COVID-19 vaccine. External sources outside the vaccine might cause vaccine hesitancy. Public opinions expressed in online media reflect the public's cognition and attitude towards vaccines and their core needs in terms of information. Therefore, online public opinion monitoring could be an essential way to understand the opinions and attitudes towards public health issues.


Subject(s)
COVID-19 , Social Media , COVID-19 Vaccines , Disease Outbreaks/prevention & control , Humans , SARS-CoV-2
20.
Int J Environ Res Public Health ; 19(1)2021 12 30.
Article in English | MEDLINE | ID: covidwho-1580784

ABSTRACT

There is increasing evidence of the psychological impact of COVID-19 on various population groups, with concern particularly focused on young people's mental health. However, few papers have engaged with the views of young people themselves. We present findings from a study into young people's discussions on social media about the impact of COVID-19 on their mental health. Real-time, multi-platform online ethnography was used to collect social media posts by young people in the United Kingdom (UK), March 2020-March 2021, 1033 original posts and 13,860 associated comments were analysed thematically. Mental health difficulties that were described as arising from, or exacerbated by, school closures, lost opportunities or fraught family environments included depression, anxiety and suicidality. Yet, some also described improvements to their mental health, away from prior stressors, such as school. Young people also recounted anxiety at the ramifications of the virus on others. The complexities of the psychological impact of COVID-19 on young people, and how this impact is situated in their pre-existing social worlds, need recognising. Forging appropriate support necessitates looking beyond an individualised conceptualisation of young people's mental health that sets this apart from broader societal concerns. Instead, both research and practice need to take a systemic approach, recognising young people's societal belonging and social contexts.


Subject(s)
COVID-19 , Social Media , Adolescent , Anthropology, Cultural , Humans , Mental Health , SARS-CoV-2
SELECTION OF CITATIONS
SEARCH DETAIL
...