COVID-19 topics and emotional frames in vaccine hesitation: A social media text and sentiment analysis.

Objective: Addressing gaps in COVID-19 vaccine-hesitancy research, the current study aimed to add depth and nuance to the exploratory research examining vaccine-hesitant groups. Using a larger, but more focused conversation occurring on social media, the results can be used by health communicators to frame emotionally resonant messaging to improve COVID-19 vaccine advocacy while also mitigating negative concerns for vaccine-hesitant individuals. Methods: Social media mentions were collected using a social media listening software, Brandwatch, to examine topics and sentiments in COVID-19 hesitancy discourse during a period of September 1, 2020, through December 31, 2020. The results from this query included publicly available mentions on two popular social media sites, Twitter and Reddit. The dataset of 14,901 global, English language messages were analyzed using a computer-assisted process in SAS text-mining and Brandwatch software. The data revealed eight unique topics before being analyzed by sentiment. Results: Among the COVID-19 hesitancy data, trust-related topics emerged that included declining vaccine acceptance, a parallel pandemic of distrust, and a call for politicians to let the scientific process work, among others. Positive sentiment revealed interest in the sources which included healthcare professionals, doctors, and government organizations. Pfizer was found to elicit both positive and negative emotions in the vaccine-hesitancy data. The negative sentiment tended to dominate the hesitancy conversation, accelerating once vaccines hit the market. Conclusions: Relevant topics were identified to help support targeted communication, strategically accelerate vaccine acceptance, and mitigate COVID-19 vaccine hesitancy among the public. Strategic methods of online and offline messaging tactics are suggested to reach diverse, malleable populations of interest. Topics of personal anecdotes of safety, effectiveness, and recommendations among families are identified as persuasive communication opportunities.

A Text-Mining Analysis to Examine Dominant Sources of Online Information and Content on Continuous Glucose Monitors.

PURPOSE: The purpose of this study is to use text-mining methods to examine the dominant sources of online information and content about continuous glucose monitors (CGMs). Because the internet is the most popular source for health information, it is important to understand what is being said about CGMs in online sources of information. METHODS: A text miner, algorithmic-driven statistical program was used to identify the main sources of online information and topics on CGMs. Content was limited to English and was posted from August 1, 2020, to August 4, 2022. Using Brandwatch software, 17 940 messages were identified. After cleaning, there were 10 677 messages in final analyses conducted using SAS Text Miner V.12.1 software. RESULTS: The analysis identified 20 topics that formed 7 themes. Results show that most online information comes from news sources and focuses on the general benefits of CGM use. Beneficial aspects ranged from improvements in self-management behaviors, cost, and glucose levels. None of the themes mentioned changes to practice, research, or policies related to CGM. CONCLUSIONS: To improve diffusion of information and innovations going forward, novel ways of information sharing should be explored, such as diabetes specialist, provider, and researcher engagement in social media and digital storytelling.

Web-Based Conversations Regarding Fathers Before and During the COVID-19 Pandemic: Qualitative Content Analysis.

BACKGROUND: Studies of new and expecting parents largely focus on the mother, leaving a gap in knowledge about fathers. OBJECTIVE: This study aimed to understand web-based conversations regarding new and expecting fathers on social media and to explore whether the COVID-19 pandemic has changed the web-based conversation. METHODS: A social media analysis was conducted. Brandwatch (Cision) captured social posts related to new and expecting fathers between February 1, 2019, and February 12, 2021. Overall, 2 periods were studied: 1 year before and 1 year during the pandemic. SAS Text Miner analyzed the data and produced 47% (9/19) of the topics in the first period and 53% (10/19) of the topics in the second period. The 19 topics were organized into 6 broad themes. RESULTS: Overall, 26% (5/19) of the topics obtained during each period were the same, showing consistency in conversation. In total, 6 broad themes were created: fatherhood thoughts, fatherhood celebrations, advice seeking, fatherhood announcements, external parties targeting fathers, and miscellaneous. CONCLUSIONS: Fathers use social media to make announcements, celebrate fatherhood, seek advice, and interact with other fathers. Others used social media to advertise baby products and promote baby-related resources for fathers. Overall, the arrival of the COVID-19 pandemic appeared to have little impact on the excitement and resiliency of new fathers as they transition to parenthood. Altogether, these findings provide insight and guidance on the ways in which public health professionals can rapidly gather information about special populations-such as new and expecting fathers via the web-to monitor their beliefs, attitudes, emotional reactions, and unique lived experiences in context (ie, throughout a global pandemic).

Telehealth adoption during the COVID-19 pandemic: A social media textual and network analysis.

Objective: The telemedicine industry has rapidly grown during the COVID-19 pandemic, and telemedicine has become a common form of care. The present study looks at the online conversation regarding telemedicine at the beginning of the pandemic and one year later. The Technology Acceptance Model is utilized to explain the findings. Methods: Brandwatch and NUVI software captured social mentions on Twitter regarding telemedicine during the beginning of the pandemic (March 15, 2020-April 20, 2020) and one year later (March 12, 2021-April 19, 2021). SAS text-mining software analyzed the social mentions and organized them into ten unique topics for each time period. The research team analyzed the topics and organized them into themes. A network analysis was also performed to examine structure and influence within the network. Results: In March-April 2020, the themes focused on the use of telehealth in general, telehealth for mental health applications, and Medicare covering telehealth services. In March-April 2021, the themes focused on news events regarding telehealth and the rise in prominence of telehealth services. The network analysis shows a shift in the distribution of telehealth information among influential accounts and reveals that the network became more connected, with a change in the control of information spread. Conclusions: Technology Acceptance Model explains the social acceptance and spread of telemedicine. The transition in the conversation about telemedicine suggests a pattern of greater system use consistent with the Technology Acceptance Model. Telemedicine may have greatly increased in use because of the pandemic, but data suggests that its use may persist after the pandemic subsides.

Promoting support for community water fluoridation: Testing message effects and the role of normative beliefs.

BACKGROUND: Despite evidence that community water fluoridation (CWF) protects oral health, improves health equity, is safe and cost-effective, and contributes to social well-being, little is known regarding which of these benefits should be highlighted to effectively influence support for CWF. METHODS: This within-participants study examines differences in CWF support in response to pro-CWF messages reflecting themes of oral health, health equity, CWF safety, cost-effectiveness, or social well-being among a sample of parents. Prior belief that CWF has health benefits, worry about potential health risks, and normative beliefs were also examined as independent predictors of support for each theme. RESULTS: Oral health, health equity, and safety messages significantly increased support in comparison with social well-being messages (P < .05). Oral health messages also produced greater support than cost-savings messages. Belief that CWF has health benefits positively predicted support, as did normative beliefs that one's family and physician approve of CWF. Worry about health risks and community and dentist norms were not significant predictors of support. There were no interaction effects of message themes and prior beliefs. CONCLUSIONS: Messaging focused on oral health, health equity, and the safety of CWF may be the most effective at influencing support for CWF. Preexisting personal beliefs about CWF benefits significantly predict support, but so do normative beliefs-family and physician norms in particular. PRACTICAL IMPLICATIONS: Findings suggest dental health educators should emphasize CWF's oral health benefits, such as preventing caries, over cost-saving and social well-being outcomes. They should also consider collaborating with family physicians to promote CWF and referencing other groups that may positively influence beliefs that CWF is beneficial.

Social media conversations about community water fluoridation: formative research to guide health communication.

OBJECTIVES: Community water fluoridation (CWF) is one of the greatest public health achievements of the 20th century. Despite this achievement, there are still misunderstandings about the safety of water fluoridation. Previous communication campaigns advocating CWF have been unsuccessful in combating these misunderstandings, suggesting a need for a new way to promote CWF. The goal of this article is to guide research for future campaigns by analyzing the digital conversation regarding community water fluoridation and other forms of fluoride in the state of Texas. METHODS: NUVI software extracted tweets from Twitter, and SAS Text Miner 12.1 software revealed topics related to water fluoridation. RESULTS: The results uncovered eight topics related to water fluoridation. Overall, the analysis showed mixed reactions toward water fluoridation, fluoride toothpaste, and children's dental health. CONCLUSIONS: The findings of the text analysis will guide future research, with the goal of building a pro-CWF effort in Texas.

Identifying #addiction concerns on twitter during the COVID-19 pandemic: A text mining analysis.

BACKGROUND: The 2019 Novel Coronavirus (COVID-19) is responsible for thousands of deaths and hospitalizations. To curb the spread of this highly transmissible disease, governments enacted protective guidelines for its citizens, including social distancing and stay-at-home orders. These restrictions on social interactions can be especially problematic for individuals managing or recovering from addiction given that treatment often involves access to services and resources that became limited or even unavailable at this time. Social media sites like Twitter serve as a space for users to post questions and concerns about timely topics and allow for researchers to track common themes among the public. The goal of this study was to identify how the public was discussing addiction on Twitter during the COVID pandemic. Methods: We performed a text mining analysis to analyze tweets that contained "addiction" and "covid" to capture posts from the public that illustrated comments and concerns about addiction during the COVID-19 pandemic. We report on 3,301 tweets captured between January 31 and April 23, 2020. The study was conducted in the United States, but contained tweets from multiple countries. Results: The most prevalent topics had to do with services offered by Acadia Healthcare and Serenity Healthcare Centers, attempts to manage time while home, difficulties of coping with alcoholism amidst rising sales of alcohol, and attention to ongoing health crises (e.g.,., opioids, vaping). Additional topics included affordable telehealth services, research from France on the relationship between nicotine and COVID-19, concerns about gambling addiction, and changing patterns in substance misuse as drug availability varies. Conclusions: Analyzing Twitter content enables health professionals to identify the public's concerns about addiction during the COVID-19 pandemic. Findings from text mining studies addressing timely health topics can serve as preliminary analyses for building more comprehensive models, which can then be used to generate recommendations for the larger public and inform policy.

Reactions to the opioid epidemic: A text-mining analysis of tweets.

OBJECTIVE: This study analyzed public reactions to the opioid epidemic using Twitter discourse. Methods: One month of unique tweets (n = 26,079) from July 23, 2018 to August 22, 2018 were identified using the keyword "opioid" in conjunction with the words "crisis, epidemic, misuse, prescription, and death." Twelve topics, each representing more than 1% of all tweets, together accounted for 17,206 (66%) of identified tweets. Results: The top four tweet topics (representing 38% of the total) addressed lawsuits and public policy, people who use opioids to treat persistent pain, programs to alleviate the opioid epidemic, and one specific initiative, the "#onelesspill" movement. The next seven topics (representing 27% of the total) addressed news articles relating to the opioid epidemic. The 12th topic was a book about the opioid crisis (1.7% of the total tweets). Conclusions: These tweets exhibited polarization of opinions with some people calling for tighter restrictions on opioids and others desperate to preserve their daily use of opioids for alleviation of illnesses characterized by persistent pain. Social media posts can help inform efforts to craft public policy and communication strategies to support optimal opioid stewardship.

Development of a health communication campaign to promote the Texas prescription monitoring program.

Given the role opioid overprescribing has played in the current overdose crisis, reducing the supply of prescription opioids available for misuse has gained widespread support. Prescription monitoring programs (PMPs) have been identified as a tool for achieving this goal, but little is known about how to promote PMP use to prescribers. This paper describes the process of developing a health communication campaign to support the adoption of the Texas PMP. After formative research, message development and concept testing, a range of campaign concepts and messages were tested and final recommendations determined. The messages and lessons learned have utility beyond Texas.

Reactions to foodborne Escherichia coli outbreaks: A text-mining analysis of the public's response.

Foodborne illnesses caused by bacteria are being reported at an increasing rate in the United States. We performed a text-mining analysis to look at nearly 13,000 tweets from two foodborne Escherichia coli outbreaks in 2018. Concerns from the public included staying informed about contaminated lettuce, recognizing signs of infection, and holding responsible farms accountable. At the end of the second outbreak, comments were focused on assessing symptoms, using the traceback process to locate outbreak sources, and calling for better food labeling practices.

Sudden Infant Death Syndrome and Safe Sleep on Twitter: Analysis of Influences and Themes to Guide Health Promotion Efforts.

BACKGROUND: In the United States, sudden infant death syndrome (SIDS) is the leading cause of death in infants aged 1 month to 1 year. Approximately 3500 infants die from SIDS and sleep-related reasons on a yearly basis. Unintentional sleep-related deaths and bed sharing, a known risk factor for SIDS, are on the rise. Furthermore, ethnic disparities exist among those most affected by SIDS. Despite public health campaigns, infant mortality persists. Given the popularity of social media, understanding social media conversations around SIDS and safe sleep may assist the medical and public health communities with information needed to spread, reinforce, or counteract false information regarding SIDS and safe sleep. OBJECTIVE: The objective of our study was to investigate the social media conversation around SIDS and safe sleep to understand the possible influences and guide health promotion efforts and public health research as well as enable health professionals to engage in directed communication regarding this topic. METHODS: We used textual analytics to identify topics and extract meanings contained in unstructured textual data. Twitter messages were captured during September, October, and November in 2017. Tweets and retweets were collected using NUVI software in conjunction with Twitter's search API using the keywords: "sids," "infant death syndrome," "sudden infant death syndrome," and "safe sleep." This returned a total of 41,358 messages, which were analyzed using text mining and social media monitoring software. RESULTS: Multiple themes were identified, including recommendations for safe sleep to prevent SIDS, safe sleep devices, the potential causes of SIDS, and how breastfeeding reduces SIDS. Compared with September and November, more personal and specific stories of infant loss were demonstrated in October (Pregnancy and Infant Loss Awareness Month). The top influencers were news organizations, universities, and health-related organizations. CONCLUSIONS: We identified valuable topics discussed and shared on Twitter regarding SIDS and safe sleep. The study results highlight the contradicting information a subset of the population is exposed to regarding SIDS and the continued controversy over vaccines. In addition, this analysis emphasizes the lack of public health organizations' presence on Twitter compared with the influence of universities and news media organizations. The results also demonstrate the prevalence of safe sleep products that are embedded in safe sleep messaging. These findings can assist providers in speaking about relevant topics when engaging in conversations about the prevention of SIDS and the promotion of safe sleep. Furthermore, public health agencies and advocates should utilize social media and Twitter to better communicate accurate health information as well as continue to combat the spread of false information.

A text-mining analysis of the public's reactions to the opioid crisis.

BACKGROUND: Opioid abuse has become an epidemic in the United States. On August 25, 2016, the former Surgeon General of the United States sent an open letter to care providers asking for their help with combatting this growing health crisis. Social media forums like Twitter allow for open discussions among the public and up-to-date exchanges of information about timely topics like opioids. Therefore, the goal of the current study is to identify the public's reactions to the opioid epidemic by identifying the most popular topics tweeted by users. METHODS: We used a text-miner, algorithmic-driven statistical program to capture 73,235 original tweets and retweets posted within a two-month time span (August 15, 2016 through October 15, 2016). All tweets contained references to "opioids," "turnthetide," or similar keywords. We then analyzed the sets of tweets to identify the most prevalent topics. RESULTS: The most discussed topics had to do with public figures addressing opioid abuse, creating better treatment options for teen addicts, using marijuana as an alternative for managing pain, holding foreign and domestic drug makers accountable for the epidemic, promoting the "Rx for Change" campaign, addressing double-standards in the perceptions and treatment of Black and White opioid users, and advertising opioid recovery programs. CONCLUSIONS: Twitter allows users to find current information, voice their concerns, and share calls for action in response to the opioid epidemic. Monitoring the conversations about opioids that are taking place on social media forums like Twitter can help public health officials and care providers better understand how the public is responding to this health crisis.

Public reactions to e-cigarette regulations on Twitter: a text mining analysis.

BACKGROUND: In May 2016, the Food and Drug Administration (FDA) issued a final rule that deemed e-cigarettes to be within their regulatory authority as a tobacco product. News and opinions about the regulation were shared on social media platforms, such as Twitter, which can play an important role in shaping the public's attitudes. We analysed information shared on Twitter for insights into initial public reactions. METHODS: A text mining approach was used to uncover important topics among reactions to the e-cigarette regulations on Twitter. SAS Text Miner V.12.1 software was used for descriptive text mining to uncover the primary topics from tweets collected from May 1 to May 17 2016 using NUVI software to gather the data. RESULTS: A total of nine topics were generated. These topics reveal initial reactions to whether the FDA's e-cigarette regulations will benefit or harm public health, how the regulations will impact the emerging e-cigarette market and efforts to share the news. The topics were dominated by negative or mixed reactions. CONCLUSIONS: In the days following the FDA's announcement of the new deeming regulations, the public reaction on Twitter was largely negative. Public health advocates should consider using social media outlets to better communicate the policy's intentions, reach and potential impact for public good to create a more balanced conversation.

E-Cigarette Topics Shared by Medical Professionals: A Comparison of Tweets from the United States and United Kingdom.

Medical professionals are now relying on social media platforms like Twitter to express their recommendations for the use or avoidance of products like electronic cigarettes (e-cigs), which may have long-term health consequences for users. The goal of this study is to compare how physicians from the United States and the United Kingdom talk about e-cigs on Twitter and identify the topics that these groups perceive as salient. Comparing tweets from the U.S. and U.K. will allow for a better understanding of how medical professionals from these countries differ in their attitudes toward e-cigs. This information can be also used to inform policies designed to regulate the use of e-cigs. Using a text-mining program, we analyzed approximately 3,800 original tweets sent by physicians from the U.S. and the U.K. within a 1-year time span (June 2015 through June 2016). The program clustered the tweets by topics, which allowed us to categorize the topics by importance. Both sets of tweets contained debates about the degree to which e-cigs pose a threat to health, but the U.S. tweets emphasized the dangers of e-cig use for teens, while the U.K. tweets focused more on the potential that e-cigs have to be used as a smoking cessation aid. Doctors are using Twitter to share timely information about the potential risks, benefits, and regulations associated with e-cigs. Evaluating these tweets allows researchers to collect information about topics that doctors find important and make comparisons about how medical professionals from the U.S. and the U.K. regard e-cigs.

Exploring gender and identity issues among female adolescent and young adults who connect in an anonymous platform.

There has been an increased usage of online cancer support groups as a resource for health-related information and social support. This work analyzes message blog posts from an anonymous online support community to better understand issues related to gender and identity among female adolescent and young adults. This work sheds further light into the nuances of gender and identity issues including motherhood and reproductive issues, physical appearance, and romantic relationships. Specifically, findings reveal that female adolescent and young adults experience issues pertaining to infertility, feeling like a bad mom, hair loss, scarring, dating, and intimacy. These findings of this work offer further guidance about how healthcare providers and caregivers can attempt to meet the needs of female adolescent and young adults.

E-Cigarette Social Media Messages: A Text Mining Analysis of Marketing and Consumer Conversations on Twitter.

BACKGROUND: As the use of electronic cigarettes (e-cigarettes) rises, social media likely influences public awareness and perception of this emerging tobacco product. OBJECTIVE: This study examined the public conversation on Twitter to determine overarching themes and insights for trending topics from commercial and consumer users. METHODS: Text mining uncovered key patterns and important topics for e-cigarettes on Twitter. SAS Text Miner 12.1 software (SAS Institute Inc) was used for descriptive text mining to reveal the primary topics from tweets collected from March 24, 2015, to July 3, 2015, using a Python script in conjunction with Twitter's streaming application programming interface. A total of 18 keywords related to e-cigarettes were used and resulted in a total of 872,544 tweets that were sorted into overarching themes through a text topic node for tweets (126,127) and retweets (114,451) that represented more than 1% of the conversation. RESULTS: While some of the final themes were marketing-focused, many topics represented diverse proponent and user conversations that included discussion of policies, personal experiences, and the differentiation of e-cigarettes from traditional tobacco, often by pointing to the lack of evidence for the harm or risks of e-cigarettes or taking the position that e-cigarettes should be promoted as smoking cessation devices. CONCLUSIONS: These findings reveal that unique, large-scale public conversations are occurring on Twitter alongside e-cigarette advertising and promotion. Proponents and users are turning to social media to share knowledge, experience, and questions about e-cigarette use. Future research should focus on these unique conversations to understand how they influence attitudes towards and use of e-cigarettes.

Identifying the public's concerns and the Centers for Disease Control and Prevention's reactions during a health crisis: An analysis of a Zika live Twitter chat.

The arrival of the Zika virus in the United States caused much concern among the public because of its ease of transmission and serious consequences for pregnant women and their newborns. We conducted a text analysis to examine original tweets from the public and responses from the Centers for Disease Control and Prevention (CDC) during a live Twitter chat hosted by the CDC. Both the public and the CDC expressed concern about the spread of Zika virus, but the public showed more concern about the consequences it had for women and babies, whereas the CDC focused more on symptoms and education.

Detecting themes of public concern: a text mining analysis of the Centers for Disease Control and Prevention's Ebola live Twitter chat.

A diagnosis of Ebola on US soil triggered widespread panic. In response, the Centers for Disease Control and Prevention held a live Twitter chat to address public concerns. This study applied a textual analytics method to reveal insights from these tweets that can inform communication strategies. User-generated tweets were collected, sorted, and analyzed to reveal major themes. The public was concerned with symptoms and lifespan of the virus, disease transfer and contraction, safe travel, and protection of one's body.