What makes cancer information viral on social media?

Social Media Users' Engagement with Fear Appeal Elements in Government's Health Crisis Communication via State-Owned Media

Government health messaging is significant to the containment of public health crises. Such communication may benefit from using fear appeal, a message strategy for promoting health and preventing diseases. Yet little scholarly attention has been paid to how fear appeal is employed in government messaging to promote social media engagement through online actions including likes, shares, and comments. These actions play a meaningful role in addressing communication exigencies within the context of health crises. In this study, quantitative content analysis and corpus linguistics methods were employed to analyze fear appeal-related elements in COVID-19 messages sent by a state-owned media outlet on social media. The results show that when compared to messages without threat, messages conveying threat elicited significantly more comments, in which emotions and perceptions to threat and efficacy were exhibited, while messages containing both threat and efficacy generated more engagement in comparison to messages with threat alone. Moreover, while subdimensions under efficacy were positive predictors of engagement, those under threat were primarily found to have exerted negative effects. The findings provide insights into how fear appeal elements can be employed in government health crisis communication to engage the public.

How Visual Aesthetics and Calorie Density Predict Food Image Popularity on Instagram: A Computer Vision Analysis

Social media have become an important source where people are exposed to visual representations of foods. This study aims to understand what content factors contribute to the popularity of food images on Instagram. We collected 53,894 images from 90 popular food influencer accounts on Instagram over two years. Applying computer vision methods, we investigated the effects of visual aesthetics and calorie density of foods on audience engagement (i.e. likes, comments) as well as if the effects of visual aesthetics varied by calorie density. Our results showed that both visual aesthetics and calorie density were important predictors of image popularity. The use of arousing, warm colors such as red, orange, and yellow, feature complexity, and repetition predicted higher likes, whereas brightness, colorfulness, and compositional complexity acted reversely. A similar pattern was observed for comments. The calorie density of foods in images positively predicted likes and comments. Also, the effects of visual aesthetics varied by calorie content and were more pronounced for low-calorie images. Health practitioners who plan to harness the power of social media to encourage certain dietary behaviors should take visual aesthetics into account when designing persuasive messages and campaigns.

A multidimensional comparative study of help-seeking messages on Weibo under different stages of COVID-19 pandemic in China

Objective

During the COVID-19 pandemic, people posted help-seeking messages on Weibo, a mainstream social media in China, to solve practical problems. As viruses, policies, and perceptions have all changed, help-seeking behavior on Weibo has been shown to evolve in this paper.

Methods

We compare and analyze the help-seeking messages from three dimensions: content categories, time distribution, and retweeting influencing factors. First, we crawled the help-seeking messages from Weibo, and successively used CNN and xlm-roberta-large models for text classification to analyze the changes of help-seeking messages in different stages from the content categories dimension. Subsequently, we studied the time distribution of help-seeking messages and calculated the time lag using TLCC algorithm. Finally, we analyze the changes of the retweeting influencing factors of help-seeking messages in different stages by negative binomial regression.

Results

(1) Help-seekers in different periods have different emphasis on content. (2) There is a significant correlation between new daily help-seeking messages and new confirmed cases in the middle stage (1/1/2022-5/20/2022), with a 16-day time lag, but there is no correlation in the latter stage (12/10/2022-2/25/2023). (3) In all the periods, pictures or videos, and the length of the text have a significant positive effect on the number of retweets of help-seeking messages, but other factors do not have exactly the same effect on the retweeting volume.

Conclusion

This paper demonstrates the evolution of help-seeking messages during different stages of the COVID-19 pandemic in three dimensions: content categories, time distribution, and retweeting influencing factors, which are worthy of reference for decision-makers and help-seekers, as well as provide thinking for subsequent studies.

Exploring the impact of sentiment on multi-dimensional information dissemination using COVID-19 data in China

The outbreak of information epidemic in crisis events, with the channel effect of social media, has brought severe challenges to global public health. Combining information, users and environment, understanding how emotional information spreads on social media plays a vital role in public opinion governance and affective comfort, preventing mass incidents and stabilizing the network order. Therefore, from the perspective of the information ecology and elaboration likelihood model (ELM), this study conducted a comparative analysis based on two large-scale datasets related to COVID-19 to explore the influence mechanism of sentiment on the forwarding volume, spreading depth and network influence of information dissemination. Based on machine learning and social network methods, topics, sentiments, and network variables are extracted from large-scale text data, and the dissemination characteristics and evolution rules of online public opinions in crisis events are further analyzed. The results show that negative sentiment positively affects the volume, depth, and influence compared with positive sentiment. In addition, information characteristics such as richness, authority, and topic influence moderate the relationship between sentiment and information dissemination. Therefore, the research can build a more comprehensive connection between the emotional reaction of network users and information dissemination and analyze the internal characteristics and evolution trend of online public opinion. Then it can help sentiment management and information release strategy when emergencies occur.

Interdisciplinary Approach to Identify and Characterize COVID-19 Misinformation on Twitter: Mixed Methods Study

BACKGROUND

Studying COVID-19 misinformation on Twitter presents methodological challenges. A computational approach can analyze large data sets but is limited when interpreting context. A qualitative approach allows deeper analysis of content, but is labor-intensive and feasible only for smaller data sets.

OBJECTIVE

Identify and characterize tweets containing COVID-19 misinformation.

METHODS

Tweets geolocated to the Philippines (1 January to 21 March 2020) containing the words coronavirus, covid, and ncov, were mined using GetOldTweets3 Python library. This primary corpus (N=12,631) was subjected to biterm topic modeling (BTM). Key informant interviews (KII) were conducted to elicit examples of COVID-19 misinformation and determine keywords. Using nVivo and a combination of word frequency and text search using KII keywords, subcorpus A (n=5,881) was constituted and manually coded to identify misinformation. Constant comparative, iterative, and consensual analysis were used to further characterize these tweets. Tweets containing KII keywords were extracted from the primary corpus and processed to constitute subcorpus B (n=4,634), of which 506 tweets were manually labeled as misinformation. This training set was subjected to natural language processing to identify tweets with misinformation in the primary corpus. These tweets were further manually coded to confirm labeling.

RESULTS

BTM of the primary corpus revealed the following topics: uncertainty, lawmakers' response, safety measures, testing, loved ones, health standards, panic buying, tragedies other than COVID-19, economy, COVID-19 statistics, precautions, health measures, international issues, adherence to guidelines, and front-liners. These were categorized into four major topics: nature of COVID, contexts and consequences, people and agents of COVID, and COVID prevention and management. Manual coding of subcorpus A identified 398 tweets with misinformation in these formats: misleading content (n=179), satire and/or parody (n=77), false connection (n=53), conspiracy (n=47) and false context (n=42). Discursive strategies identified were humor (n=109), fear mongering (n=67), anger and disgust (n=59), political commentary (n=59), performing credibility (n=45), over-positivity (n=32) and marketing (n=27) . NLP identified 165 tweets with misinformation. However, manual review of these tweets showed that 115 tweets (69.7%) did not contain misinformation. .

CONCLUSIONS

An interdisciplinary approach was used to identify tweets with COVID-19 misinformation. NLP mislabeled tweets, likely due to tweets written in Filipino or a combination of Filipino and English languages. Identifying formats and discursive strategies of tweets with misinformation required iterative, manual, and emergent coding by human coders with experiential and cultural knowledge of Twitter. An interdisciplinary team composed of experts in health, health informatics, social science, and computer science, combined computational and qualitative methods to gain a better understanding of COVID-19 misinformation on Twitter. .

CLINICALTRIAL

Recommending Breast Cancer Screening to My Mum: Examining the Interplay of Threat, Efficacy, and Virality on Recommendation Intention in the Chinese Context

The burgeoning eHealth campaigns and the emerging daughter-to-mother health communication necessitate a close examination of the intricate mechanism behind recommending preventive behaviors in online settings. The present study addresses existing gaps by investigating how message characteristics and platform-generated virality cues jointly influence younger females' intention to recommend breast cancer screening to their mothers. Drawing on the extended parallel process model (EPPM) as the theoretical basis, a 2 (threat: low vs. high) × 2 (efficacy: low vs. high) × 2 (virality: low vs. high) randomized between-subjects experiment (n = 269) was performed. Results revealed a three-way interaction effect between threat, efficacy, and virality on message involvement. Message involvement was positively associated with recommendation intention and mediated the three-way interaction effect on recommendation intention. This study demonstrates that a high threat can initiate message involvement but fail to trigger recommendation intention. In contrast, a low-threat, high-efficacy, high-virality combination would yield a salutary outcome. Besides, the indispensable role of message involvement in the underlying psychological mechanism behind recommending preventive behaviors was reaffirmed. Theoretical and practical implications are further discussed.

How did Chinese public health authorities promote COVID-19 vaccination on social media? A content analysis of the vaccination promotion posts

Objective

Drawing upon the health belief model, this study aims to analyze the message characteristics of coronavirus disease 2019 (COVID-19) vaccination promotion messages posted by influential Chinese public health institutions and how those characteristics affect audiences' participative engagement on Weibo, which is a popular social media site in China.

Methods

Two Chinese phrases for the COVID-19 vaccine were adopted as search terms to retrieve qualified posts on Weibo from 1 December 2019 to 18 March 2023. A total of 2546 posts by the top nine most impactful public health institutions were retained for quantitative content analysis. Message characteristics derived from the health belief model and participative engagement indicators were coded by the authors.

Results

Among health belief model constructs, the collective-oriented constructs (i.e., benefits, cues to action, and susceptibility) appeared in almost half of the posts, while the individual-oriented constructs (i.e., barriers, self-efficacy, and severity) were mentioned less. Moreover, negative binomial regression models revealed that collective-oriented constructs and self-efficacy facilitated engagement, while other constructs played impeding roles.

Conclusions

Appearances and functions of the health belief model's constructs in the COVID-19 vaccination promotion context are closely associated with China's collectivistic culture. Furthermore, constructs conforming to people's psychological traits are likely to promote public engagement and may facilitate vaccination behavior.

Social media in health communication: A literature review of information quality

BACKGROUND

Social media is used in health communication by individuals, health professionals, disease centres and other health regulatory bodies. However, varying degrees of information quality are churned out daily on social media. This review is concerned with the quality of Social Media Health Information (SMHI).

OBJECTIVE

The review sought to understand how SMHI quality issues have been framed and addressed in the literature. Health topics, users and social media platforms that have raised health information quality concerns are reviewed. The review also looked at the suitability of existing criteria and instruments used in evaluating SMHI and identified gaps for future research.

METHOD

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses and the forward chaining strategy were used in the document search. Data were sourced according to inclusion criteria from five academic databases, namely Scopus, Web of Science, Cochrane Library, PubMed and MEDLINE.

RESULTS

A total of 93 articles published between 2000 and 2019 were used in the review. The review revealed a worrying trend of health content and communication on social media, especially of cancer, dental care and diabetes information on YouTube. The review further discovered that the Journal of the American Medical Association, the DISCERN and the Health on the Net Foundation, which were designed before the advent of social media, continue to be used as quality evaluation instruments for SMHI, even though technical and user characteristics of social media differ from traditional portals such as websites.

CONCLUSION

The study synthesises varied opinions on SMHI quality in the literature and recommends that future research proposes quality evaluation criteria and instruments specifically for SMHI.

Development and validation of a quality assessment tool to assess online nutrition information

Setting

The internet is an important source of health information but is unregulated. Little research has focused on the assessment of digital information related to nutrition.

Aim

To develop and validate a novel online quality assessment tool (OQAT) for quality assessment of online nutrition information.

Method

The OQAT was developed and validated in six distinct stages. After reviewing the literature, a framework and criteria were developed and formalised. Next, the quality assessment criteria were piloted on a subset of data and criteria refined. The established criteria were then validated against a previously validated assessment tool, and reliability was tested. Finally, the validated OQAT was used to assess the quality of articles from a 24-h collection period, 19 April 2021.

Results

The final OQAT consisted of 10 key questions. Twenty-six news articles were assessed independently by two raters. Comparison of scores found moderate internal consistency (α = 0.382). Cohen's Kappa coefficient demonstrated high interrater agreement (k = 0.653, p < 0.001). The OQAT was tested on 291 relevant Uniform Resource Locators (URLs), which were determined to be either poor 3% (n = 9), satisfactory 49% (n = 144), or high-quality 48% (n = 139) articles. There was a statistically significant difference in OQAT scores between blogs, news articles, and press releases, χ2(2) = 23.22, p < 0.001, with a mean rank OQAT score of 138.2 for blogs, 216.6 for news articles, and 188.7 for press releases.

Conclusion

This novel tool provides a reliable and objective method for assessing the quality of nutrition content online. It could potentially be used by researchers to assess the quality of online information in different settings and by organisations to inform readers of the quality of information being accessed.

Understanding Melanoma Talk on Twitter: The Lessons Learned and Missed Opportunities

BACKGROUND

Melanoma is the third most common cause of cancer and the deadliest form of skin cancer among 17-39 year-olds in the United States. Melanoma is a critical public health issue with a substantial economic burden. Cases and associated burdens, however, could be prevented with a greater awareness of, and interventions related to, skin cancer and melanoma-related preventive behaviors. In fact, as social media use is close to ubiquitous, it represents a potential communication modality. However, more research is needed to understand the current state of melanoma-related information exchanged between Twitter users. This study aimed to understand the different types of users controlling the melanoma-related information diffusion and conversation themes on Twitter.

METHODS

Tweets (n = 692) were imported from Twitter between 1 and 31 May 2021 using the Twitter public API; and uploaded to NodeXL to conduct a social network analysis.

RESULTS

Health professionals and organizations with medical backgrounds were the main content producers, disseminators, and top influencers. However, information diffusion is slow and uneven among users. Additionally, conversations lacked a focus on preventive behaviors.

CONCLUSION

Twitter is a potential platform for the targeted outreach of individuals in melanoma awareness campaigns. This study provides insights maximizing the effectiveness of Twitter as a communication modality. Our findings can help guide the development of customized content and interventions during melanoma awareness campaigns.

Insights and Strategies to Revive Brachytherapy Using Social Media: A Google Trends Analysis

Introduction: The utilization and public awareness of brachytherapy are both declining. Social media has an increasing presence in health promotions. As regards cancer care, social media has been successfully used as a platform for information dissemination, psychosocial support, and patient engagement and empowerment.

Methods and materials: Using Google Trends (Google LLC, Mountain View, CA, USA), we analyzed the impacts on the public interest of three brachytherapy-related social media campaigns/publicity events and compared and contrasted them with three other campaigns/publicity events. We used descriptive statistics (mean ± standard deviation (SD)) to describe the search results, independent t-tests to compare means before and after campaigns/announcements for short-term effects, and one-way ANOVA (or Kruskal-Wallis test when appropriate) to compare mean values across distinct time periods for long-term effects.

Results: We identified three major types of social media campaigns/events: those that have a short-term impact but little long-term impact, those that have both short-term and long-term impacts, and those with little short-term or long-term impact. We examined campaigns with significant and lasting impacts and noticed that they tend to be celebrity-related/celebrity-endorsed, focused on sharing personal experiences, and occur with regular frequency.

Conclusions: To increase public awareness of brachytherapy, the American Brachytherapy Society (ABS) can consider tie-ins with events and people with high search traffic (such as Breast Cancer Awareness Month), having celebrities/influencers who were treated with brachytherapy to provide testimonials, encouraging patient engagement and sharing of their experiences with brachytherapy on social media, and setting up recurring brachytherapy publicity events.

Passengers’ Sensitivity and Adaptive Behaviors to Health Risks in the Subway Microenvironment: A Case Study in Nanjing, China

Passenger behavior in subways has recently become a matter of great concern, with more attention being paid to the health risks of the subway microenvironment (sub-ME). This paper aimed to provide guidance for subway passengers on better adapting to the health risks presented by the sub-ME. A questionnaire-based survey was conducted in Nanjing, China, and descriptive analysis and a one-way analysis of variance were performed to understand the sensitivity levels of subway passengers and analyze their adaptive behaviors, based on their sensitivity to sub-ME health risks. The results showed that passengers over 66 years old and those who are frequently sick are more sensitive to the presented health risks. Additionally, passengers traveling for longer and those traveling in rush hours are more sensitive to sub-ME health risks. We also found that individual characteristics, knowledge structure, and information communication all influence passengers’ adaptive behaviors. It was ascertained that those with a positive attitude and those who had previously suffered from environmentally influenced diseases, as well as those who studied an environment-related subject, tended to demonstrate more adaptive behaviors. Moreover, passengers who are very familiar with the subway information communication channels and the related information adapted better to the health risks of the sub-ME. Our findings are beneficial for improving passengers’ adaptability to the health risks presented by the sub-ME and for promoting the sustainable operation of subway systems.

Contextualizing Engagement With Health Information on Facebook: Using the Social Media Content and Context Elicitation Method

Background

Most of what is known regarding health information engagement on social media stems from quantitative methodologies. Public health literature often quantifies engagement by measuring likes, comments, and/or shares of posts within health organizations’ Facebook pages. However, this content may not represent the health information (and misinformation) generally available to and consumed by platform users. Furthermore, some individuals may prefer to engage with information without leaving quantifiable digital traces. Mixed methods approaches may provide a way of surpassing the constraints of assessing engagement with health information by using only currently available social media metrics.

Objective

This study aims to discuss the limitations of current approaches in assessing health information engagement on Facebook and presents the social media content and context elicitation method, a qualitatively driven, mixed methods approach to understanding engagement with health information and how engagement may lead to subsequent actions.

Methods

Data collection, management, and analysis using the social media content and context elicitation method are presented. This method was developed for a broader study exploring how and why US Latinos and Latinas engage with cancer prevention and screening information on Facebook. The study included 20 participants aged between 40 and 75 years without cancer who participated in semistructured, in-depth interviews to discuss their Facebook use and engagement with cancer information on the platform. Participants accessed their Facebook account alongside the researcher, typed cancer in the search bar, and discussed cancer-related posts they engaged with during the previous 12 months. Engagement was defined as liking, commenting, and/or sharing a post; clicking on a post link; reading an article in a post; and/or watching a video within a post. Content engagement prompted questions regarding the reasons for engagement and whether engagement triggered further action. Data were managed using MAXQDA (VERBI GmbH) and analyzed using thematic and content analyses.

Results

Data emerging from the social media content and context elicitation method demonstrated that participants mainly engaged with cancer prevention and screening information by viewing and/or reading content (48/66, 73%) without liking, commenting, or sharing it. This method provided rich content regarding how US Latinos and Latinas engage with and act upon cancer prevention and screening information on Facebook. We present 2 emblematic cases from the main study to exemplify the additional information and context elicited from this methodology, which is currently lacking from quantitative approaches.

Conclusions

The social media content and context elicitation method allows a better representation and deeper contextualization of how people engage with and act upon health information and misinformation encountered on social media. This method may be applied to future studies regarding how to best communicate health information on social media, including how these affect assessments of message credibility and accuracy, which can influence health outcomes.

Harnessing Artificial Intelligence for Health Message Generation: The Folic Acid Message Engine

Background

Communication campaigns using social media can raise public awareness; however, they are difficult to sustain. A barrier is the need to generate and constantly post novel but on-topic messages, which creates a resource-intensive bottleneck.

Objective

In this study, we aim to harness the latest advances in artificial intelligence (AI) to build a pilot system that can generate many candidate messages, which could be used for a campaign to suggest novel, on-topic candidate messages. The issue of folic acid, a B-vitamin that helps prevent major birth defects, serves as an example; however, the system can work with other issues that could benefit from higher levels of public awareness.

Methods

We used the Generative Pretrained Transformer-2 architecture, a machine learning model trained on a large natural language corpus, and fine-tuned it using a data set of autodownloaded tweets about #folicacid. The fine-tuned model was then used as a message engine, that is, to create new messages about this topic. We conducted a web-based study to gauge how human raters evaluate AI-generated tweet messages compared with original, human-crafted messages.

Results

We found that the Folic Acid Message Engine can easily create several hundreds of new messages that appear natural to humans. Web-based raters evaluated the clarity and quality of a human-curated sample of AI-generated messages as on par with human-generated ones. Overall, these results showed that it is feasible to use such a message engine to suggest messages for web-based campaigns that focus on promoting awareness.

Conclusions

The message engine can serve as a starting point for more sophisticated AI-guided message creation systems for health communication. Beyond the practical potential of such systems for campaigns in the age of social media, they also hold great scientific potential for the quantitative analysis of message characteristics that promote successful communication. We discuss future developments and obvious ethical challenges that need to be addressed as AI technologies for health persuasion enter the stage.

What makes an online help-seeking message go far during the COVID-19 crisis in mainland China? A multilevel regression analysis

Various studies have explored the underlying mechanisms that enhance the overall reach of a support-seeking message on social media networks. However, little attention has been paid to an under-examined structural feature of help-seeking message diffusion, information diffusion depth, and how support-seeking messages can traverse vertically into social media networks to reach other users who are not directly connected to the help-seeker. Using the multilevel regression to analyze 705 help-seeking posts regarding COVID-19 on Sina Weibo, we examined sender, content, and environmental factors to investigate what makes help-seeking messages traverse deeply into social media networks. Results suggested that bandwagon cues, anger, instrumental appeal, and intermediate self-disclosure facilitate the diffusion depth of help-seeking messages. However, the effects of these factors were moderated by the epidemic severity. Implications of the findings on support-seeking behavior and narrative strategies on social media were also discussed.

Understanding terror states of online users in the context of COVID-19: An application of Terror Management Theory

The COVID-19 pandemic has provided psych challenges for many in society. One such challenge is the anxiety that is created in many people faced with the risk of death from the disease. Another issue is understanding how individuals cope psychologically with the threat of death from the disease. In this study we examine the manifestation of death anxiety and various coping mechanisms through the lens of terror management theory (TMT) and online platforms. We take a novel approach to testing the theory using big data analytics and machine learning, focusing on the user-generated content of Twitter users. Based on a sample of all tweets in the UK mentioning COVID-19 terms over a 5-month period, we evaluate dictionary mentions of anxiety and death, and various TMT defense mechanisms, and calculate the pattern of latent death anxiety or ‘terror’ states of Twitter users via Hidden Markov Models. The research identifies four online ‘terror’ states, with high death and anxiety mentions during the peak of the pandemic. Further we examine various TMT defense mechanisms that have been proposed in the literature for coping with death anxiety and find that online social connection, achievement and religion all play important roles in improving the model and explaining movement between states. The paper concludes with various implications of the study for future research and practice.

Cancer Communication and User Engagement on Chinese Social Media: Content Analysis and Topic Modeling Study

Background

Cancer ranks among the most serious public health challenges worldwide. In China—the world’s most populous country—about one-quarter of the population consists of people with cancer. Social media has become an important platform that the Chinese public uses to express opinions.

Objective

We investigated cancer-related discussions on the Chinese social media platform Weibo (Sina Corporation) to identify cancer topics that generate the highest levels of user engagement.

Methods

We conducted topic modeling and regression analyses to analyze and visualize cancer-related messages on Weibo and to examine the relationships between different cancer topics and user engagement (ie, the number of retweets, comments, and likes).

Results

Our results revealed that cancer communication on Weibo has generally focused on the following six topics: social support, cancer treatment, cancer prevention, women’s cancers, smoking and skin cancer, and other topics. Discussions about social support and cancer treatment attracted the highest number of users and received the greatest numbers of retweets, comments, and likes.

Conclusions

Our investigation of cancer-related communication on Weibo provides valuable insights into public concerns about cancer and can help guide the development of health campaigns in social media.

Promoting HPV vaccination on social media: interactive effects of threat, efficacy and social cues

BACKGROUND

Women are currently facing a tremendous threat of cervical cancer globally. Social media health campaigns have the potential to shape public health behaviors. This study explores the effects of cervical-cancer-related fear appeal messages with social cues on social media using the extended parallel processing model (EPPM).

METHOD

We use a 2 (threat: present vs. absent) × 2 (efficacy: present vs. absent) × 2 (social cues: high vs. low) factorial experimental design to examine the effects of fear appeal messages with social cues on behavioral intention to receive the human papillomavirus (HPV) vaccination.

RESULTS

There was a significant main effect of threat on the intention to receive HPV vaccination. Additionally, a significant three-way interactive effect among threat, efficacy, and social cues was detected.

CONCLUSION

Women exposed to threat messages had a higher intention of HPV vaccination compared to those who were exposed to non-threat messages. Furthermore, with the low number of likes, women who were exposed to messages containing both threat and efficacy tended to have the highest intention of HPV vaccination.

PRACTICE IMPLICATIONS

When conducting fear appeal campaigns on social media, the side effects of number of likes should be recognized. For vaccination promotion campaigns, the efficacy information should be more specific and audience-centered.

Factors Influencing the Popularity of a Health-Related Answer on a Chinese Question-and-Answer Website: Case Study

BACKGROUND

Social question-and-answer (Q&A) sites have become an important venue for individuals to obtain and share human papillomavirus (HPV) vaccine knowledge.

OBJECTIVE

This study aims to examine how different features of an HPV vaccine-related answer are associated with users' response behaviors on social Q&A websites.

METHODS

A total of 2953 answers and 270 corresponding questions regarding the HPV vaccine were collected from a leading Chinese social Q&A platform, Zhihu. Three types of key features, including content, context, and contributor, were extracted and coded. Negative binomial regression models were used to examine their impact on the vote and comment count of an HPV vaccine-related answer.

RESULTS

The findings showed that both content length and vividness were positively related to the response behaviors of HPV vaccine-related answers. In addition, compared with answers under the question theme benefits and risks, answers under the question theme vaccination experience received fewer votes and answers under the theme news opinions received more votes but fewer comments. The effects of characteristics of contributors were also supported, suggesting that answers from a male contributor with more followers and no professional identity would attract more votes and comments from community members. The significant interaction effect between content and context features further showed that long and vivid answers about HPV vaccination experience were more likely to receive votes and comments of users than those about benefits and risks.

CONCLUSIONS

The study provides a complete picture of the underlying mechanism behind response behaviors of users toward HPV vaccine-related answers on social Q&A websites. The results help health community organizers develop better strategies for building and maintaining a vibrant web-based community for communicating HPV vaccine knowledge.

Few changes shown in cancer information-seeking behaviour among young adults in China between 2012 and 2017

BACKGROUND

The increasing incidence of cancer among young adults (18-40 years old) is of concern in China.

OBJECTIVES

This study aims to examine the influence of cancer information-seeking behaviours (CISB) on young adults' worries about cancer and participation in screening.

METHODS

This study analysed data from two probability sample surveys conducted in 2012 and 2017 in China. The questions in the questionnaire remained the same for better comparison. The sample size was 1212 in the 2012 survey, and 2178 in the 2017 survey.

RESULTS

From 2012 to 2017, among young adults, there was a decline in cancer information seeking, diversity of cancer information sought and cancer worry, while an improvement in cancer information-seeking experience was found. Also, CISB had significant associations with cancer worry and health screening over the 5 years.

DISCUSSION

The level of young adults' cancer information seeking remains low in China, and this group is not fully aware of their potential risks of getting cancer.

CONCLUSION

Although young adults find the experience of looking for cancer information easier in 2017, health campaigns may be necessary to encourage young adults to find out more about their cancer risks, and to participate more in health screening.

What triggers online help-seeking retransmission during the COVID-19 period? Empirical evidence from Chinese social media

The past nine months witnessed COVID-19's fast-spreading at the global level. Limited by medical resources shortage and uneven facilities distribution, online help-seeking becomes an essential approach to cope with public health emergencies for many ordinaries. This study explores the driving forces behind the retransmission of online help-seeking posts. We built an analytical framework that emphasized content characteristics, including information completeness, proximity, support seeking type, disease severity, and emotion of help-seeking messages. A quantitative content analysis was conducted with a probability sample consisting of 727 posts. The results illustrate the importance of individual information completeness, high proximity, instrumental support seeking. This study also demonstrates slight inconformity with the severity principle but stresses the power of anger in help-seeking messages dissemination. As one of the first online help-seeking diffusion analyses in the COVID-19 period, our research provides a reference for constructing compelling and effective help-seeking posts during a particular period. It also reveals further possibilities for harnessing social media's power to promote reciprocal and cooperative actions as a response to this deepening global concern.

Internet as a context: Exploring its impacts on scientific optimism in China

The Internet brings new opportunities and challenges to scientific development and science communication. Previous studies overwhelmingly focused on individual-level Internet factors but overlooked the potential explanatory strength of Internet context. This study addresses the existing gap by examining how the Internet influences Chinese people’s scientific optimism from a comprehensive perspective (Internet as a medium and Internet as a context). Multilevel models were built based on individual-provincial merged data. The results indicate that (1) the Internet context impairs scientific optimism while Internet exposure has no significant effect. (2) The relationship between individual Internet exposure and scientific optimism varies by province. As a quantitative indicator of Internet context, Internet penetration mitigates the weakening effect of individual Internet exposure on scientific optimism. This research provides empirical evidence on scientific attitude formation in the non-Western environment and expands the analytic approach of public attitudes toward science.

Re-written narrative: transformation of the image of Ivan-chaj in Eastern Europe

The aim of this study was to understand the role of viral narratives and the involvement of social media into the invention of tradition. We took as an example the recently highly promoted Ivan-chaj, a tea made from the fermented leaves of willowherb, a plant little known and used in Europe until a few years ago. Relying on a wide variety of sources circulating on the Internet (videos, various texts and visuals) and robust empirical field research results, we used mixed methods to analyze this specific case in order to understand if people adopt new teachings and if their acceptance leads to practical output. The results showed that the new teachings spread quickly, supported by narratives based on a wide variety of interaction points that viralized the message, also causing an economic impact. It is clear that the change of status and the economic success that Ivan-chaj now enjoys is due to the virality of the narrative, which has reshaped the image of Ivan-chaj from an "outcast" imitation and tea substitute into the national healthy drink. Having appeared in Russia, mostly as a Russian cultural marker, the narrative went viral and spread beyond its borders where neighbors have tried in turn to embrace Ivan-chaj as their own cultural marker by proclaiming it a local tradition. Indeed, narratives regarding Ivan-chaj spread easily in countries sharing some linguistic, historical and/or cultural elements with Russia (via the nexus of the Soviet Union).

Modeling Impact of Word of Mouth and E-Government on Online Social Presence during COVID-19 Outbreak: A Multi-Mediation Approach

Although social presence plays an essential role under general conditions, its role becomes significant for societal protection during the quarantine period in epidemic outbreak. In this study, we attempted to identify the role of E-government and COVID-19 word of mouth in terms of their direct impact on online social presence during the outbreak as well as their impacts mediated by epidemic protection and attitudes toward epidemic outbreaks. For this purpose, a unique multi-mediation model is proposed to provide a new direction for research in the field of epidemic outbreaks and their control. Through random sampling, an online survey was conducted and data from 683participants were analyzed. Partial least squares structural equation modeling was used to test the relationships between the variables of interest. The study results revealed that the roles of E-government and COVID-19 word of mouth are positively related to online social presence during the outbreak. Epidemic protection and attitude toward epidemic outbreak were found to positively moderate the impact of the role of E-government and COVID-19 word of mouth on online social presence during the outbreak. The key findings of this study have both practical and academic implications.

What Can Twitter Tell Us about Skin Cancer Communication and Prevention on Social Media?

BACKGROUND

Skin cancer places a substantial burden on the health system in Australia. The modernisation of skin cancer prevention interventions by using social media may enhance their contemporary reach and relevance, especially among the youth. This study aimed to analyse Twitter posts in Australia to establish a baseline of skin cancer and sun-related communication trends.

METHODS

Tweets posted over the summer of 2018/2019 relating to relevant keywords and hashtags such as "slipslopslap" and "sunscreen" were analysed using quantitative and qualitative methods. The number of tweets, related communication patterns, and possible factors for sudden changes in tweet volume were studied.

RESULTS

Results showed that Australians are using Twitter to communicate about their sun-related and skin cancer experiences and to share advice and information on this matter. Overall, Australians use Twitter more frequently to talk about sunscreen (number of tweets between December 2018 and February 2019 = 5,842) and/or skin cancer (n = 3,936), but not so often to communicate about other sun-protective behaviours (n = 1,972) or skin cancer prevention campaigns (n = 108). The number of tweets is greatly affected by the increase in temperature. Celebrities, non-health-related organisations with a high number of followers, and individuals sharing their own skin cancer experiences achieve a substantial number of likes and retweets and thus influence on Twitter regarding skin cancer-related communication.

CONCLUSIONS

The results allow deeper understanding of important determinants for effective social media use for health promotion and public health messaging in the future. Linking tweets with temperature, sharing by celebrities or non-health-related organisations and individuals with a high following can all contribute to greater spread of skin cancer and sun-related messages.

Opioids on Twitter: A Content Analysis of Conversations regarding Prescription Drugs on Social Media and Implications for Message Design

As many as 130 lives are lost every day in the United States due to prescription drug misuse. The opioid crisis is gripping the country and disrupting the lives of millions. Not surprisingly, health organizations are desperately seeking solutions to educate and inform people regarding the issue, often seeking the help of various social media platforms. In this study, we do a content analysis of Twitter messages related to opioids in order to understand the factors that are most likely to influence content sharing. Our findings indicate that structure, source, and the actual content of the post all influence the likelihood of the content's being shared. Specifically, certain types of content enhanced the likelihood of content sharing whereas use of the term "addiction" discouraged retweeting. Theoretical and practical implications for message design are discussed.