COVID-19 on Instagram: A content analysis of selected accounts

Text-Mining and Video Analytics of COVID-19 Narratives Shared by Patients on YouTube

This study explores how individuals who have experienced COVID-19 share their stories on YouTube, focusing on the nature of information disclosure, public engagement, and emotional impact pertaining to consumer health. Using a dataset of 186 YouTube videos, we used text mining and video analytics techniques to analyze textual transcripts and visual frames to identify themes, emotions, and their relationship with viewer engagement metrics. Findings reveal eight key themes: infection origins, symptoms, treatment, mental well-being, isolation, prevention, government directives, and vaccination. While viewers engaged most with videos about infection origins, treatment, and vaccination, fear and sadness in the text consistently drove views, likes, and comments. Visuals primarily conveyed happiness and sadness, but their influence on engagement varied. This research highlights the crucial role YouTube plays in disseminating COVID-19 patient narratives and suggests its potential for improving health communication strategies. By understanding how emotions and content influence viewer engagement, healthcare professionals and public health officials can tailor their messaging to better connect with the public and address pandemic-related anxieties.

COVID-19 information seeking and individuals' protective behaviors: examining the role of information sources and information content

BACKGROUND

Seeking COVID-19 information promotes individuals to adopt preventive behaviors, including wearing a mask, social distancing, staying away from risky places, and washing hands. This study aims to investigate which information and sources individuals relied on in seeking COVID-19 information and further examine their roles in individuals' adoption of preventive behaviors.

METHODS

Through a statistical analysis of 1027 valid responses from citizens in different Chinese cities in 2022 to the self-designed items in an online survey, this study identified individuals' preferred information sources and content on COVID-19. Regarding the information sources and content, the study used multiple regression analysis to examine their associations with individuals' preventive behaviors, and further applied fuzzy-set qualitative comparative analysis (fsQCA) to explore their configurations that increase the likelihood of individuals adopting preventive behaviors.

RESULTS

Individuals preferred information about the newest prevention and control policies, precautions and treatment, and symptoms from the sources of workplace and community, social media, and social live streaming services. Additionally, individuals' preventive behaviors were positively related to the workplace and community (β = 0.202, p <.001), social live streaming services (β = 0.089, p <.01), government department websites (β = 0.079, p <.05), television (β = 0.073, p <.05), and online news media (β = 0.069, p <.05), but were negatively associated with newspapers (β=-0.087, p <.05). Regarding information content, precautions and treatments (β = 0.211, p <.001), the newest prevention and control policies (β = 0.173, p <.001), symptoms (β = 0.152, p <.001), and official rumor-dispelling information (β = 0.082, p <.05) had a positive relationship with individuals' preventive behaviors. In addition, fsQCA results presented eight configurations that promote individuals to adopt preventive behaviors. The total coverage and solution consistency values were 0.869 and 0.987, respectively. Furthermore, COVID-19 information content, the sources of social media and interpersonal sources, and official news media played an essential role in increasing the likelihood of individuals adopting preventive behaviors.

CONCLUSIONS

Our findings demonstrated that individuals seek various COVID-19 information from multiple sources. The direct and degree of association of information sources and content with individuals' preventive behaviors vary from source to source and from content to content. Information sources and content could combinatorially promote individuals to adopt preventive behaviors through several configurations.

The Effect of COVID-19 on Middle-Aged Adults' Mental Health: A Mixed-Method Case-Control Study on the Moderating Effect of Cognitive Reserve

The COVID-19 pandemic has increased the vulnerability of adults to mental health effects, and the study of protective factors has become crucial. Cognitive reserve (CR) is a well-known protective factor against cognitive decline and several health factors; however, its protective effect on mental health during the pandemic has been rarely addressed. Thus, this study explored, through a mixed-method design, the effect of CR on perceived distress and PTSD-like symptoms in middle-aged participants who have survived severe COVID-19 and a matched control group. A total of 432 participants filled out self-report measures of CR, PTSD, depression, and anxiety, and were also asked to provide narration about their COVID-19-related experience. COVID-19 significantly affected the chances of reporting different mental health symptoms; levels of CR played a protective role in reducing their severity. Moreover, adults with higher CR seemed to be more realistic, focusing less on positive emotions, and elaborating more on the sense of anxiety when describing their experience: this might be an indication of a lower use of suppression to regulate emotions. Practical implications of these findings and future directions have been also discussed.

An exploratory content and sentiment analysis of the guardian metaverse articles using leximancer and natural language processing

The metaverse has become one of the most popular concepts of recent times. Companies and entrepreneurs are fiercely competing to invest and take part in this virtual world. Millions of people globally are anticipated to spend much of their time in the metaverse, regardless of their age, gender, ethnicity, or culture. There are few comprehensive studies on the positive/negative sentiment and effect of the newly identified, but not well defined, metaverse concept that is already fast evolving the digital landscape. Thereby, this study aimed to better understand the metaverse concept, by, firstly, identifying the positive and negative sentiment characteristics and, secondly, by revealing the associations between the metaverse concept and other related concepts. To do so, this study used Natural Language Processing (NLP) methods, specifically Artificial Intelligence (AI) with computational qualitative analysis. The data comprised metaverse articles from 2021 to 2022 published on The Guardian website, a key global mainstream media outlet. To perform thematic content analysis of the qualitative data, this research used the Leximancer software, and the The Natural Language Toolkit (NLTK) from NLP libraries were used to identify sentiment. Further, an AI-based Monkeylearn API was used to make sectoral classifications of the main topics that emerged in the Leximancer analysis. The key themes which emerged in the Leximancer analysis, included "metaverse", "Facebook", "games" and "platforms". The sentiment analysis revealed that of all articles published in the period of 2021-2022 about the metaverse, 61% (n = 622) were positive, 30% (n = 311) were negative, and 9% (n = 90) were neutral. Positive discourses about the metaverse were found to concern key innovations that the virtual experiences brought to users and companies with the support of the technological infrastructure of blockchain, algorithms, NFTs, led by the gaming world. Negative discourse was found to evidence various problems (misinformation, harmful content, algorithms, data, and equipment) that occur during the use of Facebook and other social media platforms, and that individuals encountered harm in the metaverse or that the metaverse produces new problems. Monkeylearn findings revealed "marketing/advertising/PR" role, "Recreational" business, "Science & Technology" events as the key content topics. This study's contribution is twofold: first, it showcases a novel way to triangulate qualitative data analysis of large unstructured textual data as a method in exploring the metaverse concept; and second, the study reveals the characteristics of the metaverse as a concept, as well as its association with other related concepts. Given that the topic of the metaverse is new, this is the first study, to our knowledge, to do both.

Use of YouTube by academic medical centres during the COVID-19 pandemic: an observational study in Taiwan

OBJECTIVES

YouTube has been of immense importance in conveying essential information on COVID-19 and promoting the latest healthcare policies during the outbreak. However, there have been few studies that have focused on how healthcare organisations have used YouTube to communicate with the public and increase their awareness during the pandemic, as well as its effectiveness.

DESIGN

A nationwide observational study.

SETTINGS

We analysed all YouTube video posts culled from the official accounts of all medical centres in Taiwan from December 2019 to August 2021.

PARTICIPANTS

All YouTube videos were categorised as either COVID-19 or non-COVID-19 related. The COVID-19-related videos were divided into five categories, and detailed metrics for each video were recorded. For comparison, we also surveyed all YouTube video posts placed by the Ministry of Health and Welfare and the Taiwan Centers for Disease Control (TCDC).

RESULTS

We analysed official YouTube channels from 17 academic medical centres, involving a total of 943 videos. We found a relationship between the quantity of YouTube videos uploaded by the TCDC and the trend of confirmed cases (Pearson's correlation coefficient was 0.25, p=0.02). Data from private hospitals revealed that they posted more COVID-19 videos (103 vs 56) when compared with public hospitals. In addition, multivariate linear regression showed that more 'likes' (estimate 41.1, 95% CI 38.8 to 43.5) and longer lengths (estimate 10 800, 95% CI 6968.0 to 14 632.0) of COVID-19-related videos correlated significantly with an increased number of 'views'.

CONCLUSIONS

This nationwide observational study, performed in Taiwan, demonstrates well the trend and effectiveness of academic medical centres in promoting sound healthcare advice regarding COVID-19 through YouTube due to the channel's easy accessibility and usability.

Predicting Fact-Checking Health Information Before Sharing Among People with Different Levels of Altruism: Based on the Influence of Presumed Media Influence

Background

Pervasive health misinformation on social media affects people's health. Fact-checking health information before it is shared is an altruistic behavior that effectively addresses health misinformation on social media.

Purpose

Based on the influence of presumed media influence (IPMI), this study serves two purposes: The first is to investigate factors that influence social media users' decisions to fact-check health information before sharing it in accordance with the IPMI model. The second is to explore different predictive powers of the IPMI model for individuals with different levels of altruism.

Methods

This study conducted a questionnaire survey of 1045 Chinese adults. Participants were divided into either a low-altruism group (n = 545) or a high-altruism group (n = 500) at the median value of altruism. A multigroup analysis was conducted with R Lavaan package (Version 0.6-15).

Results

All of the hypotheses were supported, which confirms the applicability of the IPMI model in the context of fact-checking health information on social media before sharing. Notably, the IPMI model yielded different results for the low- and high-altruism groups.

Conclusion

This study confirmed the IPMI model can be employed in the context of fact-checking health information. Paying attention to health misinformation can indirectly affect an individual's intention to fact-check health information before they share it on social media. Furthermore, this study demonstrated the IPMI model's varying predictive powers for individuals with different altruism levels and recommended specific strategies health-promotion officials can take to encourage others to fact-check health information.

Unravelling the truth: Examining the evidence for health-related claims made by naturopathic influencers on social media - a retrospective analysis

Background: Social media platforms are frequently used by the general public to access health information, including information relating to complementary and alternative medicine (CAM). The aim of this study was to measure how often naturopathic influencers make evidence-informed recommendations on Instagram, and to examine associations between the level of evidence available or presented, and user engagement. Methods: A retrospective observational study using quantitative content analysis on health-related claims made by naturopathic influencers with 30000 or more followers on Instagram was conducted. Linear regression was used to measure the association between health-related posts and the number of Likes, and Comments. Results: A total of 494 health claims were extracted from eight Instagram accounts, of which 242 (49.0%) were supported by evidence and 34 (6.9%) included a link to evidence supporting the claim. Three naturopathic influencers did not provide any evidence to support the health claims they made on Instagram. Posts with links to evidence had fewer Likes (B=-1343.9, 95% CI=-2424.4 to -263.4, X=-0.1, P=0.02) and fewer Comments (B=-82.0, 95% CI=-145.9 to -18.2, X=-0.2, P=0.01), compared to posts without links to evidence. The most common areas of health were claims relating to 'women's health' (n=94; 19.0%), and 'hair, nail and skin' (n=74; 15.0%). Conclusion: This study is one of the first to look at the evidence available to support health-related claims by naturopathic influencers on Instagram. Our findings indicate that around half of Instagram posts from popular naturopathic influencers with health claims are supported by high-quality evidence.

Religiousness in the first year of COVID-19: A systematic review of empirical research

The COVID-19 pandemic emerged suddenly in early 2020, posing a serious health threat and creating tremendous stress and distress across the world. Religion has been shown to play important and varied roles in previous disasters and health crises, but its roles in the pandemic have yet to be outlined. We aimed to summarize the research conducted on religion and COVID-19 in the first year of the pandemic with a systematic review of studies that specifically involved individual-level religiousness and COVID-19. Searches were conducted in PubMed, Scopus, CINAHL, and PsycINFO covering a one-year period from the first published mention of the novel coronavirus (Jan. 5, 2020) through January 4, 2021. We included articles about COVID-19 that were peer-reviewed and empirical, measured and reported results on religion on an individual level, and were available in English. Our search produced 137 empirical articles that met the inclusion criteria. In the course of sorting studies by their primary focus, eight categories of empirical findings emerged: general distress and wellbeing (53 articles), COVID-19-specific stress (24 articles), beliefs in science, conspiracies, and misinformation (15 articles), COVID-19 public health behaviors (12 articles), perceived risk of COVID-19 (10 articles), perceived growth or positive changes taking place during the pandemic (nine articles), health behaviors (three articles), and consumer behavior (three articles). Findings indicated that religiousness was associated with both unique benefits and challenges and played a significant role in the pandemic. Religiousness was associated with a broad range of outcomes across geographical regions and populations during the first year of COVID-19. It was a commonly reported coping mechanism with varying levels of favorable associations with mental health and COVID-19-related behaviors.

Everyday life information seeking in South Korea during the COVID-19 pandemic: daily topics of information needs in social Q&A

Purpose

This study investigated information needs on COVID-19 by identifying topics discussed on social questions and answers (Q&A) about daily routines, problems, and health issues for survival. A layered model of contexts for everyday life information seeking (ELIS) was adapted for interpreting topics to better understand the contexts in which users could relate information needs.

Design/methodology/approach

Questions and answers posted on Naver Knowledge-iN were collected and analyzed during the first nine months following the outbreak. Time distribution, topic modeling, and association rule mining were applied to examine the topics on COVID-19 and their temporal variation.

Findings

Numerous topics related to the cognitive context (symptoms and masks) and situational contexts (international affairs, financial support, study, and work) were discovered. Topics related to social context were discussed moderately, but the number of questions on this topic increased with time. Strong associations were observed between terms related to symptoms, indicating their importance as a COVID-19 topic in health.

Originality/value

This study investigated topics of information needs using social Q&A data in which not only information inquiry but also information sharing coexist. The findings can help bridge the theory of ELIS to topic modeling in practice. The insights gained from this study can be used by information service providers for developing guidance and programs about how to survive during a pandemic.

Peer review

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-10-2021-0547.

The information‐seeking behavior of medical sciences students toward COVID‐19 in mass and social media: A cross‐sectional study

Background and Aims

During the COVID‐19 pandemic, college students can access health‐related information on the Internet to improve preventative behaviors, but they often judge the merits of such information and create challenges in the community. The aim of this study was to investigate information‐seeking behaviors in regard to COVID‐19 among students at Kerman University of Medical Sciences (KUMS) with the help of mass and social media.

Methods

The present study is a cross‐sectional study, which was conducted using an online researcher‐made questionnaire. An invitation to participate in the study was sent to 500 students at KUMS, of which 203 were selected according to the inclusion criteria and completed the questionnaire. Descriptive statistics were used to analyze the data.

Results

COVID‐19 news was mostly obtained through social media platforms such as WhatsApp, Telegram, Instagram, radio, and television, as well as online publications and news agencies. Social media platforms such as WhatsApp, Telegram, Instagram, and satellite networks such as BBC contained the most rumors about COVID‐19. Some of the most common misconceptions regarding COVID‐19 were as follows: “COVID‐19 is the deadliest disease in the world,” “COVID‐19 is a biological attack,” and “COVID‐19 disappears as the air temperature rises.” In addition, most of the virtual training provided through mass media focused on “refraining from visiting holy places and crowded locations such as markets,” “observing personal hygiene and refraining from touching the eyes, nose, and mouth with infected hands,” and “the role of quarantine in reducing the incidence of COVID‐19.”

Conclusion

Our findings demonstrated that during the pandemic, students used social media platforms the most to obtain health‐related information and these media have a significant impact on their willingness to engage in preventative behaviors and take the COVID‐19 risk seriously.

Characterization of misleading fluoride information on Instagram: An infodemiology study (Preprint)

Background

Online false or misleading oral health–related content has been propagated on social media to deceive people against fluoride’s economic and health benefits to prevent dental caries.

Objective

The aim of this study was to characterize the false or misleading fluoride-related content on Instagram.

Methods

A total of 3863 posts ranked by users’ total interaction and published between August 2016 and August 2021 were retrieved by CrowdTangle, of which 641 were screened to obtain 500 final posts. Subsequently, two independent investigators analyzed posts qualitatively to define their authors’ interests, profile characteristics, content type, and sentiment. Latent Dirichlet allocation analysis topic modeling was then applied to find salient terms and topics related to false or misleading content, and their similarity was calculated through an intertopic distance map. Data were evaluated by descriptive analysis, the Mann-Whitney U test, the Cramer V test, and multiple logistic regression models.

Results

Most of the posts were categorized as misinformation and political misinformation. The overperforming score was positively associated with older messages (odds ratio [OR]=3.293, P<.001) and professional/political misinformation (OR=1.944, P=.05). In this context, time from publication, negative/neutral sentiment, author’s profile linked to business/dental office/news agency, and social and political interests were related to the increment of performance of messages. Although political misinformation with negative/neutral sentiments was typically published by regular users, misinformation was linked to positive commercial posts. Overall messages focused on improving oral health habits, side effects, dentifrice containing natural ingredients, and fluoride-free products propaganda.

Conclusions

False or misleading fluoride-related content found on Instagram was predominantly produced by regular users motivated by social, psychological, and/or financial interests. However, higher engagement and spreading metrics were associated with political misinformation. Most of the posts were related to the toxicity of fluoridated water and products frequently motivated by financial interests.

Exploring nurses' online perspectives and social networks during a global pandemic COVID-19

Objectives

Examine the online interactions, social networks, and perspectives of nursing actors on COVID‐19 from conversations on Twitter to understand how the profession responded to this global pandemic.

Design

Mixed methods.

Sample

Ten‐thousand five‐hundred and seventy‐four tweets by 2790 individuals and organizations.

Measurements

NodeXL software was used for social network analysis to produce a network visualization. The betweenness centrality algorithm identified key users who were influential in COVID‐19 related conversations on Twitter. Inductive content analysis enabled exploration of tweet content. A communicative figurations framework guided the study.

Results

Nursing actors formed different social groupings, and communicated with one another across groups. Tweets covered four themes; (1) outbreak and clinical management of the infectious disease, (2) education and information sharing, (3) social, economic, and political context, and (4) working together and supporting each other.

Conclusion

In addition to spreading knowledge, nurses tried to reach out through social media to political and healthcare leaders to advocate for improvements needed to address COVID‐19. However, they primarily conversed within their own professional community. Action is needed to better understand how social media is and can be used by nurses for health communication, and to improve their preparedness to be influential on social media beyond the nursing community.