| Literature DB >> 35206935 |
Cristian Lieneck1, Katharine Heinemann1, Janki Patel1, Hung Huynh1, Abigail Leafblad1, Emmanuel Moreno1, Claire Wingfield1.
Abstract
Background andEntities:
Keywords: COVID-19; Coronavirus; social media; vaccination
Year: 2022 PMID: 35206935 PMCID: PMC8871797 DOI: 10.3390/healthcare10020321
Source DB: PubMed Journal: Healthcare (Basel) ISSN: 2227-9032
Figure 1Research database search string and Boolean search operators that yielded the highest frequency of results in the search.
Figure 2Preferred reporting items for systematic reviews and meta-analysis (PRISMA) figure that demonstrates the study selection process.
Reviewer assignment of the initial database search findings (full article review).
| Article Assignment | Reviewer 1 | Reviewer 2 | Reviewer 3 | Reviewer 4 | Reviewer 5 | Reviewer 6 | Reviewer 7 |
|---|---|---|---|---|---|---|---|
| 1–10 | X | X | X | X | X | X | X |
| 11–20 | X | X | X | X | X | X | |
| 21–25 | X | X | X | X |
Summary of Findings (n = 25).
| Author(s) | Participant(s) | * JHNEBP Study Design | Facilitators of COVID-19 Vaccine Promotion on Social Media | Barriers to COVID-19 Vaccine Promotion on Social Media |
|---|---|---|---|---|
| Alshaabi et al. [ | Twitter users | 3 |
COVID has been heavily discussed among users of all languages Multiple peaks of attention/space/awareness identified to support vaccination |
Language barriers (to include health literacy challenges) Accessibility to accurate data cited as a challenge (ex. government websites not utilized/cited) Accessibility to vaccine itself in developing areas of the world |
| Bonnevie et al. [ | 1000 publicly available Twitter posts related to vaccine opposition and posts were categorized into themes | 3 |
Because of the debate, the topic is gaining more attention as the virus spreads Vaccine supporters might be more prone to getting vaccinated sooner |
Vaccine opposition increased by 80% based on thread comments 12 different conversation themes identified Mistrust in health authorities observed in many threads WHO classifies vaccine opposition as one of the largest threats to public health |
| Bonnevie et al. [ | 117 influencers generated 69,495 engagements | 3 |
Vaccination campaigns using a ground-up rather than top-down approach can feasibly reach at-risk groups with lower vaccination rates Shows the potentials of using an influencer-based model to communicate information about flu vaccination on a large scale |
Used micro-influencers only so less follows of these type of social media threads Not reaching as many people as major influencer (celebrity) threads |
| Brandt et al. [ | Two undergraduate classes ( | 2 |
College students are very active on social media Participants (97%) interacted on Facebook by “liking” a post or comment or posting a comment Participants demonstrated robust engagement and high treatment satisfaction Results suggests that social media is an effective platform to reach college students with health promotion interventions and increase HPV vaccination awareness in this important catch-up population. |
Facebook is not as widely used among younger crowd as other apps such as Instagram, Twitter, and Snapchat Harder to reach a large young crowd on Facebook |
| Broniatowski et al. [ | 288,175 posts from 204 Facebook pages | 3 |
Activity in pages promoting vaccine choice as a civil liberty increased in January 2015, April 2016, and January 2019 The 2019 increase was strongest in pages mentioning U.S. states |
Discussion about vaccine safety decreased while discussion about civil liberties increased The Disneyland measles outbreak drew vaccine opposition into the political mainstream, followed by promotional campaigns conducted in pages framing vaccine refusal as a civil right |
| Budenz et al. [ | Twitter messaging addressing gay, bisexual (GB) and other men who have sex with men (MSM) | 3 |
Prevention/protection messaging was prevalent only in MSM tweets (49%) HPV vaccine sentiment was positive in GB + MSM messaging, there were deficits in volume of messaging Opportunity to shape vaccine uptake through PH agenda setting using social media messaging that increases knowledge and minimizes HPV vaccine stigma |
There were deficits in volume of messaging, lack of focus on vaccination, and a proportion of negative tweets |
| Chan, et al. [ | Twitter users; geolocated tweets from U.S. counties (N = 115,330) | 3 |
Social media have demonstrated strong associations with vaccine patterns Programs to promote vaccination should encourage real-life conversations about vaccines |
When the associations are negative, discussions with family and friends appear to eliminate them |
| Dunn et al. [ | Sampled 53,188 U.S. Twitter users and examined who they follow and retweet across 21 million vaccine-related tweets | 3 |
36.7% users retweeted vaccine-related content Only a small proportion of vaccine-critical info that reaches active U.S. Twitter users comes from bots |
2.1% users retweeted vaccine content from bots 4.5% of users retweeted vaccine-critical to herd immunity comments |
| Dyer [ | Eligible COVID-19 vaccine recipients | 5 |
A proper compensation program may be a cheap and straight-forward solution to neutralizing vaccine hesitancy and bring the pandemic to an early end |
Social media posts play into existing concerns that many people might not accept the vaccine, as surveys indicate |
| Featherstone & Zhang [ | Sampled 609 U.S. adult participants with 5 message conditions (2 misinformation messages, 2 corresponding two-sided refutational messages, and 1 control group) | 2 |
Two-sided refutational messages can be a promising strategy to combat vaccine misinformation |
Conspiracy and uncertainty framed misinformation messages decreased pro-vaccination attitude Effects were further mediated by emotions of anger Parental status and conspiracy beliefs did not moderate effects of the messages on vaccination attitude |
| Hussain et al. [ | Over 300,000 social media posts related to COVID-19 vaccines | 3 |
Used AI to analyze the public sentiments toward the COVID-19 vaccine Social media is where the data comes from; researchers can tell the response of the public based on these apps By knowing public sentiments, policy makers are more informed when making decisions |
Significant amount of this article is not about promoting the vaccine; it’s about finding out the how the public feels about the vaccine Public confidence can be shaken by misinformation about vaccine safety |
| Hwang [ | 48,600 people/random sample | 3 |
Vaccinations were more likely if friends or families vaccinate their children |
Misinformation online produces skepticism The more trust people put in social media, the more it will skew their view of vaccines |
| Jang et al. [ | Canada vs. the U.S surveys on vaccination perceptions | 3 |
This information can assist public health authorities in the monitoring and surveillance of health information, concerns, and behaviors, and can help tailor the public health strategy to the population Public health interventions on social media can break up the misinformation |
Misinformation on social medial regarding vaccines beyond public health organizations’ controls |
| Khubchandani et al. [ | Individuals were asked about their likelihood of getting the COVID-19 vaccine (asked before the vaccines came out). | 3 |
Questionnaires and information can be shared on social media easily and disseminate quickly |
Conspiracy theories and misinformation able to be identified/coded |
| Latkin et al. [ | Study participants were recruited through Amazon’s Mechanical Turk (Mturk) service. | 3 |
In-person communication is risky so more social media communication is encouraged Encourage a collective social identity around COVID-19 prevention, which may influence behavior change and increase vaccine acceptance among friends and family |
Contradictory messages from the CDC and White House |
| Lin et al. [ | 515 valid cases from a sample of undergraduate students from a class at a large Northeastern University | 3 |
The more college students rely on social media for H1N1 information, the more likely they are to be vaccinated When online news is not the dominant information source, dependence on social media sources is a significant variable in explaining potential vaccine uptake |
Better understanding of the H1N1 threat does not necessarily motivate a stronger risk-prevention commitment |
| Nowak et al. [ | 716 members of the RAND American life panel with children under the age of 21 years were invited to take the survey. | 3 |
A lot of information is out there on social media. Participants asked about knowledge and beliefs on 35 categories, political conspiracies, health conspiracies, putative vaccine side effects, gestalt vaccine endorsements, vaccine biology/epidemiology Twitter data was pulled related to the 35 categories |
Prevalent misinformation on vaccines The people who post about issues on twitter are the ones who care about specific issues, causing polarization on the subject of vaccines |
| Oehler [ | n/a | 4 |
To counter social media misinformation, we need to develop or enlist “social media influencers” for medicine in the same ways that corporations and other groups promote their celebrities, products, and services so successfully Communicating on healthcare topics via a practice Facebook page, starting a twitter feed, posting, or sharing accurate health-related information to a professional Instagram account, and volunteering medical interviews to local broadcast and print media can all improve our footprint as medically trained “influencers” and can bolster respect for our practices as well |
Spread of misinformation amongst specific groups on social media platforms. Similarly, accurate public health information gets pushed behind unwarranted rumors Shared online testimonials about adverse reactions to vaccines. Sharing of misinformation undermining physician recommendations or health information Lack of peer-review standards on social media platforms Ability for anti-vaccination groups to spread misinformation to a broad audience Intentional use of medical product marketing to mislead consumers to believe misinformation Weaponization of anti-vaccination messages by “bots” Social media platforms unwilling to take action/responsibility for misinformation. Almost 90% of older adults (ages 50 years or older) have used social media to find and share health information Major medical organizations have placed very low priority in developing their social media presence |
| Piltch-Loeb et al. [ | Random mobile application users | 3 |
A majority of participants reported hearing positive information about the COVID-19 vaccine, primarily from local TV |
Public Health information shared by credible, evidence-based sources compete with unverified sources on the largest internet platforms There was a statistically significant difference in vaccine acceptance among those who had exclusively gotten information only from traditional media (46.9%), only from social media (29.3%), or both types of channels (37.1%) Those who are less likely to get the vaccine are using social media as their sole source of information, or as at least one of their sources of information Vulnerability of social media channels to exploitation by bad actors |
| Raghupathi et al. [ | 9581 vaccine-related tweets | 3 |
Talks about measles vaccine by tracking sentiment (not necessarily topical) The positive sentiments related to the existence of a vaccine for measles, the vaccine being effective and the vaccine actually saving lives |
Higher percentage of negative tweets about vaccines compared to positive tweets A strong misinformation study In an empirical study of Facebook users, it was demonstrated that positive information gets disseminated fast but does not sustain as long as negative information |
| Romer & Jamieson [ | U.S. residents ( | 3 |
A recent survey of content on Twitter concluded that despite the large amount of misinformation on social media There is also a great amount of science-based information that circulates on those sites |
Use of social media in March was also predictive of vaccination in July, with an overall negative indirect relation of −0.041 (2020) |
| Rosenbaum [ | Opinion/discussion article. | 4 |
In response to these dangerous disinformation campaigns, social media companies have intensified efforts to label falsehoods and eliminate them |
While people firmly opposed to all vaccines may be relatively few in number, they wield outsized influence, particularly on social media, over the undecideds A recent study of expressions of vaccine-related sentiments by 100 million Facebook users found that antivaccine clusters of people, though less numerous than pro-vaccine clusters, have a more central presence in large networks and interact with more undecided clusters |
| Ruiz & Bell [ | 804 adults compensated English-speaking adults living in the U.S. | 3 |
n/a |
Respondents relying on social media for information about COVID-19 anticipated a lower likelihood of COVID-19 vaccine acceptance People are increasingly turning to social media for information expanding the potential for disseminating harmful health-related information |
| Speaker & Moffatt [ | Article described the scope of a National Library of Medicine Global Health Events web archive | 4 |
n/a |
Social media provides a wealth of misinformation and conspiracy theories |
| Zhang et al. [ | 2,598,033 tweets from 3 Twitter datasets | 3 |
Social media platforms such as Facebook can be important tools of information regarding effectiveness of the HPV vaccine Same as above except this article analyzes tweets |
Twitter algorithm investigation and discussion provides detailed insight into public responses to posts/tweets regarding vaccinations |
* Johns Hopkins Nursing Evidence-Based Practice (JHNEBP) levels of strength of evidence: Level 1, experimental study/randomized control trial (RCT); Level 2, quasi-experimental study; Level 3, non-experimental, qualitative, or meta-synthesis study; Level 4, opinion of nationally recognized experts based on research evidence/consensus panels; Level 5, opinions of industry experts not based on research evidence.
Summary of Quality Assessments.
| Strength of Evidence | Frequency |
|---|---|
| II | 2 (8%) |
| III | 19 (76%) |
| IV | 3 (12%) |
| V | 1 (4%) |
Figure 3Occurrences of underlying themes identified as barriers to COVID-19 vaccine promotion in social media as observed in the literature.
Figure 4Occurrences of underlying themes identified as facilitators to COVID-19 vaccine promotion in social media as observed in the literature.