scholarly journals Social Media Engagement and Influenza Vaccination During the COVID-19 Pandemic: Cross-sectional Survey Study (Preprint)

2020 ◽  
Author(s):  
Arriel Benis ◽  
Anna Khodos ◽  
Sivan Ran ◽  
Eugene Levner ◽  
Shai Ashkenazi
Keyword(s):  
Health Care ◽  
Social Media ◽  
Influenza Vaccination ◽  
Influenza Vaccines ◽  
Information Searching ◽  
Vaccination Rates ◽  
Media Usage ◽  
Related Information ◽  
Online Social Media ◽  
Social Media Engagement

BACKGROUND Vaccines are one of the most important achievements of modern medicine. However, their acceptance is only partial, with vaccine hesitancy and refusal representing a major health threat. Influenza vaccines have low compliance since repeated, annual vaccination is required. Influenza vaccines stimulate discussions both in the real world and online. Social media is currently a significant source of health and medical information. Elucidating the association between social media engagement and influenza vaccination is important and may be applicable to other vaccines, including ones against COVID-19. OBJECTIVE The goal of this study is to characterize profiles of social media engagement regarding the influenza vaccine and their association with knowledge and compliance in order to support improvement of future web-associated vaccination campaigns. METHODS A weblink to an online survey in Hebrew was disseminated over social media and messaging platforms. The survey answers were collected during April 2020. Anonymous and volunteer participants aged 21 years and over answered 30 questions related to sociodemographics; social media usage; influenza- and vaccine-related knowledge and behavior; health-related information searching, its reliability, and its influence; and COVID-19-related information searching. A univariate descriptive data analysis was performed, followed by multivariate analysis via building a decision tree to define the most important attributes associated with vaccination compliance. RESULTS A total of 213 subjects responded to the survey, of whom 207 were included in the analysis; the majority of the respondents were female, were aged 21 to 40 years, had 1 to 2 children, lived in central Israel, were secular Israeli natives, had higher education, and had a salary close to the national average. Most respondents (128/207, 61.8%) were not vaccinated against influenza in 2019 and used social media. Participants that used social media were younger, secular, and living in high-density agglomerations and had lower influenza vaccination rates. The perceived influence and reliability of the information on social media about COVID-19 were generally similar to those perceptions about influenza. CONCLUSIONS Using social media is negatively linked to compliance with seasonal influenza vaccination in this study. A high proportion of noncompliant individuals can lead to increased consumption of health care services and can, therefore, overload these health services. This is particularly crucial with a concomitant outbreak, such as COVID-19. Health care professionals should use improved and targeted health communication campaigns with the aid of experts in social media. Targeted communication, based on sociodemographic factors and personalized social media usage, might increase influenza vaccination rates and compliance with other vaccines as well.

scholarly journals Social Media Engagement and Influenza Vaccination During the COVID-19 Pandemic: Cross-sectional Survey Study

10.2196/25977 ◽  
2021 ◽  
Vol 23 (3) ◽  
pp. e25977 ◽  
Author(s):  
Arriel Benis ◽  
Anna Khodos ◽  
Sivan Ran ◽  
Eugene Levner ◽  
Shai Ashkenazi
Keyword(s):  
Health Care ◽  
Social Media ◽  
Influenza Vaccination ◽  
Influenza Vaccines ◽  
Information Searching ◽  
Vaccination Rates ◽  
Media Usage ◽  
Related Information ◽  
Online Social Media ◽  
Social Media Engagement

Background Vaccines are one of the most important achievements of modern medicine. However, their acceptance is only partial, with vaccine hesitancy and refusal representing a major health threat. Influenza vaccines have low compliance since repeated, annual vaccination is required. Influenza vaccines stimulate discussions both in the real world and online. Social media is currently a significant source of health and medical information. Elucidating the association between social media engagement and influenza vaccination is important and may be applicable to other vaccines, including ones against COVID-19. Objective The goal of this study is to characterize profiles of social media engagement regarding the influenza vaccine and their association with knowledge and compliance in order to support improvement of future web-associated vaccination campaigns. Methods A weblink to an online survey in Hebrew was disseminated over social media and messaging platforms. The survey answers were collected during April 2020. Anonymous and volunteer participants aged 21 years and over answered 30 questions related to sociodemographics; social media usage; influenza- and vaccine-related knowledge and behavior; health-related information searching, its reliability, and its influence; and COVID-19-related information searching. A univariate descriptive data analysis was performed, followed by multivariate analysis via building a decision tree to define the most important attributes associated with vaccination compliance. Results A total of 213 subjects responded to the survey, of whom 207 were included in the analysis; the majority of the respondents were female, were aged 21 to 40 years, had 1 to 2 children, lived in central Israel, were secular Israeli natives, had higher education, and had a salary close to the national average. Most respondents (128/207, 61.8%) were not vaccinated against influenza in 2019 and used social media. Participants that used social media were younger, secular, and living in high-density agglomerations and had lower influenza vaccination rates. The perceived influence and reliability of the information on social media about COVID-19 were generally similar to those perceptions about influenza. Conclusions Using social media is negatively linked to compliance with seasonal influenza vaccination in this study. A high proportion of noncompliant individuals can lead to increased consumption of health care services and can, therefore, overload these health services. This is particularly crucial with a concomitant outbreak, such as COVID-19. Health care professionals should use improved and targeted health communication campaigns with the aid of experts in social media. Targeted communication, based on sociodemographic factors and personalized social media usage, might increase influenza vaccination rates and compliance with other vaccines as well.

scholarly journals Change in Threads on Twitter Regarding Influenza, Vaccines, and Vaccination During the COVID-19 Pandemic: Artificial Intelligence–Based Infodemiology Study

10.2196/31983 ◽  
2021 ◽  
Vol 1 (1) ◽  
pp. e31983
Author(s):  
Arriel Benis ◽  
Anat Chatsubi ◽  
Eugene Levner ◽  
Shai Ashkenazi
Keyword(s):  
Artificial Intelligence ◽  
United States ◽  
Machine Learning ◽  
Health Care ◽  
Social Media ◽  
Influenza Vaccination ◽  
Information Source ◽  
The United States ◽  
Influenza Vaccines ◽  
Clinical Aspects

Background Discussions of health issues on social media are a crucial information source reflecting real-world responses regarding events and opinions. They are often important in public health care, since these are influencing pathways that affect vaccination decision-making by hesitant individuals. Artificial intelligence methodologies based on internet search engine queries have been suggested to detect disease outbreaks and population behavior. Among social media, Twitter is a common platform of choice to search and share opinions and (mis)information about health care issues, including vaccination and vaccines. Objective Our primary objective was to support the design and implementation of future eHealth strategies and interventions on social media to increase the quality of targeted communication campaigns and therefore increase influenza vaccination rates. Our goal was to define an artificial intelligence–based approach to elucidate how threads in Twitter on influenza vaccination changed during the COVID-19 pandemic. Such findings may support adapted vaccination campaigns and could be generalized to other health-related mass communications. Methods The study comprised the following 5 stages: (1) collecting tweets from Twitter related to influenza, vaccines, and vaccination in the United States; (2) data cleansing and storage using machine learning techniques; (3) identifying terms, hashtags, and topics related to influenza, vaccines, and vaccination; (4) building a dynamic folksonomy of the previously defined vocabulary (terms and topics) to support the understanding of its trends; and (5) labeling and evaluating the folksonomy. Results We collected and analyzed 2,782,720 tweets of 420,617 unique users between December 30, 2019, and April 30, 2021. These tweets were in English, were from the United States, and included at least one of the following terms: “flu,” “influenza,” “vaccination,” “vaccine,” and “vaxx.” We noticed that the prevalence of the terms vaccine and vaccination increased over 2020, and that “flu” and “covid” occurrences were inversely correlated as “flu” disappeared over time from the tweets. By combining word embedding and clustering, we then identified a folksonomy built around the following 3 topics dominating the content of the collected tweets: “health and medicine (biological and clinical aspects),” “protection and responsibility,” and “politics.” By analyzing terms frequently appearing together, we noticed that the tweets were related mainly to COVID-19 pandemic events. Conclusions This study focused initially on vaccination against influenza and moved to vaccination against COVID-19. Infoveillance supported by machine learning on Twitter and other social media about topics related to vaccines and vaccination against communicable diseases and their trends can lead to the design of personalized messages encouraging targeted subpopulations’ engagement in vaccination. A greater likelihood that a targeted population receives a personalized message is associated with higher response, engagement, and proactiveness of the target population for the vaccination process.

scholarly journals Change in Threads on Twitter Regarding Influenza, Vaccines, and Vaccination During the COVID-19 Pandemic: Artificial Intelligence–Based Infodemiology Study (Preprint)

2021 ◽  
Author(s):  
Arriel Benis ◽  
Anat Chatsubi ◽  
Eugene Levner ◽  
Shai Ashkenazi
Keyword(s):  
Artificial Intelligence ◽  
United States ◽  
Machine Learning ◽  
Health Care ◽  
Social Media ◽  
Influenza Vaccination ◽  
Information Source ◽  
The United States ◽  
Influenza Vaccines ◽  
Clinical Aspects

BACKGROUND Discussions of health issues on social media are a crucial information source reflecting real-world responses regarding events and opinions. They are often important in public health care, since these are influencing pathways that affect vaccination decision-making by hesitant individuals. Artificial intelligence methodologies based on internet search engine queries have been suggested to detect disease outbreaks and population behavior. Among social media, Twitter is a common platform of choice to search and share opinions and (mis)information about health care issues, including vaccination and vaccines. OBJECTIVE Our primary objective was to support the design and implementation of future eHealth strategies and interventions on social media to increase the quality of targeted communication campaigns and therefore increase influenza vaccination rates. Our goal was to define an artificial intelligence–based approach to elucidate how threads in Twitter on influenza vaccination changed during the COVID-19 pandemic. Such findings may support adapted vaccination campaigns and could be generalized to other health-related mass communications. METHODS The study comprised the following 5 stages: (1) collecting tweets from Twitter related to influenza, vaccines, and vaccination in the United States; (2) data cleansing and storage using machine learning techniques; (3) identifying terms, hashtags, and topics related to influenza, vaccines, and vaccination; (4) building a dynamic folksonomy of the previously defined vocabulary (terms and topics) to support the understanding of its trends; and (5) labeling and evaluating the folksonomy. RESULTS We collected and analyzed 2,782,720 tweets of 420,617 unique users between December 30, 2019, and April 30, 2021. These tweets were in English, were from the United States, and included at least one of the following terms: “flu,” “influenza,” “vaccination,” “vaccine,” and “vaxx.” We noticed that the prevalence of the terms vaccine and vaccination increased over 2020, and that “flu” and “covid” occurrences were inversely correlated as “flu” disappeared over time from the tweets. By combining word embedding and clustering, we then identified a folksonomy built around the following 3 topics dominating the content of the collected tweets: “health and medicine (biological and clinical aspects),” “protection and responsibility,” and “politics.” By analyzing terms frequently appearing together, we noticed that the tweets were related mainly to COVID-19 pandemic events. CONCLUSIONS This study focused initially on vaccination against influenza and moved to vaccination against COVID-19. Infoveillance supported by machine learning on Twitter and other social media about topics related to vaccines and vaccination against communicable diseases and their trends can lead to the design of personalized messages encouraging targeted subpopulations’ engagement in vaccination. A greater likelihood that a targeted population receives a personalized message is associated with higher response, engagement, and proactiveness of the target population for the vaccination process.

New interventions to increase influenza vaccination rates in health care workers

2010 ◽  
Vol 38 (6) ◽  
pp. 476-481 ◽  
Author(s):  
Anna Llupià ◽  
Alberto L. García-Basteiro ◽  
Victoria Olivé ◽  
Laura Costas ◽  
Jose Ríos ◽  
...  
Keyword(s):  
Health Care ◽  
Influenza Vaccination ◽  
Health Care Workers ◽  
Vaccination Rates ◽  
Care Workers

Private club members’ perceptions of social media

2017 ◽  
Vol 8 (1) ◽  
pp. 119-132 ◽  
Author(s):  
MiRan Kim ◽  
Ronald Cichy
Keyword(s):  
Social Media ◽  
Ease Of Use ◽  
Perceived Usefulness ◽  
Perceived Ease Of Use ◽  
Content Type ◽  
Media Usage ◽  
Online Social Media ◽  
Usage Behavior ◽  
Perceived Enjoyment ◽  
Beliefs And Attitudes

Purpose Private club members belong to an organization where people with common interests, experiences, backgrounds and professions meet for social and recreational purposes. This study aims to examine the relationships among private club members’ perceptions of social media regarding perceived ease of use, perceived usefulness, perceived enjoyment, attitude toward social media involvement and behavioral intention toward social media usage. Design/methodology/approach An online survey was conducted among private club members across the USA (n = 571). The data were analyzed using structural equation modeling. Findings The findings of this study center on the perceptions of club members and their beliefs and attitudes associated with their social media usage behavior. This study extends the social media literature by supporting previous studies that suggest a causal flow from perceived ease of use to intrinsic and extrinsic motivations (perceived usefulness, perceived enjoyment) based on a motivational model. Research limitations/implications This study is meaningful for revealing the perceptions of private club members and their beliefs and attitudes associated with their social media usage behavior. It is untested whether this study’s model applies to other hospitality businesses. Future research could examine other segments and add other variables such as perceived security and trust. Practical implications This study can provide private club managers, and the members of the clubs that they lead, with a better understanding of online social media. Originality/value This study is one of a few empirical online social media studies in the area of the private club industry. This study seeks to provide baselines regarding social media perceptions and usage in the hospitality literature by providing a comprehensive model.

scholarly journals Learning Social Media Content Optimization: How Can SMEs Draw the Users' Attention on Official WeChat Accounts?

2022 ◽  
Vol 12 ◽  
Author(s):  
Xueyun Zeng ◽  
Xuening Xu ◽  
Yenchun Jim Wu
Keyword(s):  
Artificial Intelligence ◽  
Social Media ◽  
Psychological Needs ◽  
Media Content ◽  
Media Usage ◽  
Knowledge Based ◽  
Related Information ◽  
Artificial Intelligence Technology ◽  
Positive Effect ◽  
Content Optimization

Application of artificial intelligence is accelerating the digital transformation of enterprises, and digital content optimization is crucial to take the users' attention in social media usage. The purpose of this work is to demonstrate how social media content reaches and impresses more users. Using a sample of 345 articles released by Chinese small and medium-sized enterprises (SMEs) on their official WeChat accounts, we employ the self-determination theory to analyze the effects of content optimization strategies on social media visibility. It is found that articles with enterprise-related information optimized for content related to users' psychological needs (heart-based content optimization, mind-based content optimization, and knowledge-based content optimization) achieved higher visibility than that of sheer enterprise-related information, whereas the enterprise-related information embedded with material incentive (benefits-based content optimization) brings lower visibility. The results confirm the positive effect of psychological needs on the diffusion of enterprise-related information, and provide guidance for SMEs to apply artificial intelligence technology to social media practice.

scholarly journals Pregnancy-Related Information Seeking and Sharing in the Social Media Era Among Expectant Mothers: Qualitative Study (Preprint)

2019 ◽  
Author(s):  
Chengyan Zhu ◽  
Runxi Zeng ◽  
Wei Zhang ◽  
Richard Evans ◽  
Rongrong He
Keyword(s):  
Social Media ◽  
Pregnant Women ◽  
Information Seeking ◽  
Chinese Culture ◽  
Instant Messaging ◽  
Media Usage ◽  
Related Information ◽  
Expectant Mothers ◽  
Media Channels ◽  
The Impact

BACKGROUND Social media has become the most popular communication tool used by Chinese citizens, including expectant mothers. An increasing number of women have adopted various forms of social media channels, such as interactive websites, instant messaging, and mobile apps, to solve problems and obtain answers to queries during pregnancy. Although the use of the internet by pregnant women has been studied extensively worldwide, limited research exists that explores the changing social media usage habits in China, where the 1 child policy ended in 2015. OBJECTIVE This study aimed to (1) present the status quo of pregnancy-related information seeking and sharing via social media among Chinese expectant mothers, (2) reveal the impact of social media usage, and (3) shed light on pregnancy-related health services delivered via social media channels. METHODS A qualitative approach was employed to examine social media usage and its consequences on pregnant women. A total of 20 women who had conceived and were at various stages of pregnancy were interviewed from July 20 to August 10, 2017. Thematic analysis was conducted on the collected data to identify patterns in usage. RESULTS Overall, 80% (16/20) of participants were aged in their 20s (mean 28.5 years [SD 4.3]). All had used social media for pregnancy-related purposes. For the seeking behavior, 18 codes were merged into 4 themes, namely, gravida, fetus, delivery, and the postpartum period; whereas for sharing behaviors, 10 codes were merged into 4 themes, namely, gravida, fetus, delivery, and caretaker. Lurking, small group sharing, bad news avoidance, and cross-checking were identified as the preferred patterns for using social media. Overall, 95% (19/20) of participants reported a positive mental impact from using social media during their pregnancy. CONCLUSIONS It is indisputable that social media has played an increasingly important role in supporting expectant mothers in China. The specific seeking and sharing patterns identified in this study indicate that the general quality of pregnancy-related information on social media, as well as Chinese culture toward pregnancy, is improving. The new themes that merge in pregnancy-related social media use represent a shift toward safe pregnancy and the promotion of a more enjoyable pregnancy. Future prenatal care should provide further information on services related to being comfortable during pregnancy and reducing the inequality of social media–based services caused by the digital divide.

Influenza Vaccination in Massachusetts Jails: A Mixed-Methods Analysis

2021 ◽  
pp. 003335492110416
Author(s):  
Sarah Khorasani ◽  
Julia Zubiago ◽  
Jac Carreiro ◽  
Rubeen Guardado ◽  
Alysse G. Wurcel
Keyword(s):  
Public Health ◽  
Health Care ◽  
Influenza Vaccine ◽  
Influenza Vaccination ◽  
Summary Statistics ◽  
Vaccination Rates ◽  
Delivery Practices ◽  
County Jails ◽  
Influenza Vaccinations ◽  
Health Administrators

Objectives Influenza infects millions of people each year and contributes to tens of thousands of deaths annually despite the availability of vaccines. People most at risk of influenza complications are disproportionately represented in people incarcerated in US prisons and jails. The objectives of this study were to survey health administrators in Massachusetts county jails about institutional influenza vaccine policies and practices and estimate influenza vaccination rates in Massachusetts jails from 2013 to 2020. Methods In April 2020, we administered surveys to the health services administrators in Massachusetts’ 14 county jails to gather information about influenza vaccination policies and delivery practices. To calculate influenza vaccination rates for each facility, we obtained data on influenza vaccine orders from the Massachusetts Department of Public Health for each county in Massachusetts for influenza seasons 2013-2020. We calculated summary statistics for each reporting facility and each year, conducted a Kruskal–Wallis analysis to compare vaccination rates between years, and used a linear regression model to identify predictors of vaccination rates. Results Influenza vaccination rates in Massachusetts jails ranged from 1.9% to 11.8%. We found no significant differences in vaccination rates between years. Influenza vaccine ordering and delivery practices varied by jail, and respondents had high levels of confidence in influenza policies and vaccine delivery practices. Conclusions Influenza vaccination rates in Massachusetts jails are low, and delivery practices in jails vary. Lack of influenza vaccinations in jails is a gap in health care that needs to be prioritized, especially considering the current COVID-19 pandemic. Further investigations for effective and equitable vaccination in this population should involve people who are incarcerated and people who make influenza vaccine policies in jails.

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