e.g. mhealth
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In South Korea, individuals aged 65 years and older are classified as older populations and are considered particularly vulnerable, prompting targeted governmental support in the form of free influenza and SARS-Co V-2 vaccinations to address their specific health risks and needs. To delineate disparities in vaccination acceptance based on age-specific policies, we categorized the study population into 2 distinct age groups: younger (19-64 years) and older (≥65 years) populations.
JMIR Public Health Surveill 2024;10:e56989
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Throughout the COVID-19 pandemic up to 2022, HPV and MMR were the vaccines that maintained the greatest negative impact on routine vaccinations in the United States, suggesting a need for proactive efforts to increase vaccination coverage to prevent associated health complications and costs [49].
The overview of study design and classifications used to evaluate vaccine-related posts. 3 Cs: confidence, complacency, and convenience; ML: machine learning; WHO: World Health Organization.
JMIR Med Inform 2024;12:e57164
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The breadth and depth of COVID-19 misinformation expanded to include all vaccinations, such as human papillomavirus (HPV) vaccination, depressing already suboptimal vaccination uptake in the United States [1,2]. As HPV vaccination is critical to the prevention of various cancers, this could pose significant cancer control challenges in the future [2]. There is an urgent need to address HPV vaccination misinformation to increase HPV vaccination uptake [2].
JMIR Infodemiology 2024;4:e54000
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Upon enrollment, participants were asked to complete an initial intake questionnaire to collect demographic information (including race or ethnicity and zip code) and a health history survey to capture current health conditions (including anxiety or depression), vaccinations (including influenza or tetanus-diphtheria-pertussis [TDa P]), prescription medications (free-text response), over-the-counter medications (free-text response), and the use of prenatal vitamins (yes or no binary response; Multimedia Appendices
JMIR Form Res 2023;7:e50867
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While this method can be useful in many cases, it fails to account for other time-dependent factors that may also influence vaccinations. For example, the COVID-19 vaccine conversation on social media has been deemed an infodemic, with antivaccination misinformation spreading across social media platforms [7]. Researchers have found that the internet and social media both play a role in shaping personal or parental choices about vaccinations [8,9].
JMIR Infodemiology 2023;3:e43703
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Chatbots are used as a promising tool to promote COVID-19 vaccinations [1,2] as they offer the possibility of upscaled interactions with users. Chatbots can also support health communication by engaging users via social media channels [3]. Unfortunately, there is a considerable amount of resistance toward COVID-19 vaccinations in society [4,5], and chatbots themselves may evoke negative user responses (eg, [6]). Specifically, the effects of chatbot empathy have been found to be ambiguous.
JMIR Form Res 2023;7:e41148
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Investigating COVID-19 Vaccine Communication and Misinformation on TikTok: Cross-sectional Study
Future studies may benefit from comparing several cross-sectional studies and perform content analysis on how trends change over time as more vaccinations are rolled out globally. Our data extraction is also limited by Tik Tok’s algorithm, which is known to show users content related to their interests.
JMIR Infodemiology 2022;2(2):e38316
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This is a peer-review report submitted for the paper “Google Trends as a Predictive Tool for COVID-19 Vaccinations in Italy: Retrospective Infodemiological Analysis.”
This brief paper [1] examines the effective approach to investigating vaccine adherence against COVID-19 via Google Trends. The topic is interesting and important to provide actionable data to the World Health Organization or other related health organizations to prioritize their risk communication efforts.
JMIRx Med 2022;3(2):e38726
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This is a peer-review report submitted for the paper “Google Trends as a Predictive Tool for COVID-19 Vaccinations in Italy: Retrospective Infodemiological Analysis.”
The paper [1] uses Google Trends (GT) to identify correlations between search queries and vaccinations. GT has been used previously by others for similar and other problems. The paper is well written. The Methods section can be improved. The Results section has a good explanation.
The novelty of the paper is limited.
JMIRx Med 2022;3(2):e38724
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