JMIR Infodemiology

Focusing on determinants and distribution of health information and misinformation on the internet, and its effect on public and individual health.

Editor-in-Chief:

Tim Ken Mackey, MAS, PhD, University of California San Diego, USA


Impact Factor 3.5 CiteScore 4.8

JMIR Infodemiology (JI, ISSN 2564-1891, (inaugural Journal Impact Factor™ 3.5, (Journal Citation Reports™ from Clarivate, 2024))) launched in 2021, is a PubMed Central/PubMed, MEDLINE, Scopus, DOAJ, Web of Science, EBSCO/EBSCO Essentials, and CABI-indexed, peer-reviewed journal, focusing on infodemiology, the study of determinants and the distribution of health information and misinformation on the internet, and its effect on public and individual health. The new scientific discipline of "Infodemiology," first introduced in 2002, has been gaining momentum due to the COVID-19 infodemic, with the WHO recognizing it as an important pillar to manage public health emergencies. JMIR Publications is proud to have been spearheading the advancement of this new scientific discipline for more than a decade. We are now accelerating the development of this new interdisciplinary discipline with the first and only journal devoted to this rapidly evolving field, by bringing together thought leaders in research, data science, and policy. Areas of interest include information monitoring (infoveillance, including social listening); ehealth literacy and science literacy; knowledge refinement and quality improvement processes and policies; and the influence of political and commercial interests on effective knowledge translation. 

In 2024, JMIR Infodemilogy received an inaugural Journal Impact Factor (JIF) of 3.5 from the 2024 Journal Citation Reports™ (JCR), placing it into the first quartile (Q1) in the category HEALTH CARE SCIENCES & SERVICES (30/174 journals) as well as Q1 in the category PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH (84/403). According to Scopus' Citescore, the journal is a Q1 journal in the category "Health Policy".

JMIR Infodemiology received a CiteScore of 4.8, placing it in the first quartile as a Q1 journal in the field of Health Policy (#78 of 310), according to Scopus data.

Recent Articles

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Misinformation and Disinformation Outbreaks and Information Prevalence Studies

Social media has become a vital tool for health care providers to quickly share information. However, its lack of content curation and expertise poses risks of misinformation and premature dissemination of unvalidated data, potentially leading to widespread harmful effects due to the rapid and large-scale spread of incorrect information.

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Infoveillance and Social Listening

Video games have rapidly become mainstream in recent decades, with over half of the US population involved in some form of digital gaming. However, concerns regarding the potential harms of excessive, disordered gaming have also risen. Internet gaming disorder (IGD) has been proposed as a tentative psychiatric disorder that requires further study by the American Psychological Association (APA) and is recognized as a behavioral addiction by the World Health Organization. Substance use among gamers has also become a concern, with caffeinated or energy drinks and prescription stimulants commonly used for performance enhancement.

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Theme Issue 2023: Exploring the Intersection Between Health Information, Misinformation, and Generative AI Technologies

During the COVID-19 pandemic, the rapid spread of misinformation on social media created significant public health challenges. Large language models (LLMs), pretrained on extensive textual data, have shown potential in detecting misinformation, but their performance can be influenced by factors such as prompt engineering (ie, modifying LLM requests to assess changes in output). One form of prompt engineering is role-playing, where, upon request, OpenAI’s ChatGPT imitates specific social roles or identities. This research examines how ChatGPT’s accuracy in detecting COVID-19–related misinformation is affected when it is assigned social identities in the request prompt. Understanding how LLMs respond to different identity cues can inform messaging campaigns, ensuring effective use in public health communications.

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Infoveillance and Social Listening

Following the signing of the Tobacco 21 Amendment (T21) in December 2019 to raise the minimum legal age for the sale of tobacco products from 18 to 21 years in the United States, there is a need to monitor public responses and potential unintended consequences. Social media platforms, such as Twitter (subsequently rebranded as X), can provide rich data on public perceptions.

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Reviews in Infodemiology

The growing availability of big data spontaneously generated by social media platforms allows us to leverage natural language processing (NLP) methods as valuable tools to understand the opioid crisis.

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Assessing and Building eHealth / Digital Literacy in Populations

The COVID-19 pandemic has had a significant impact on different countries because of which various health and safety measures were implemented, with digital media playing a pivotal role. However, digital media also pose significant concerns such as misinformation and lack of direction.

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Reviews in Infodemiology

During health emergencies, effective infodemic management has become a paramount challenge. A new era marked by a rapidly changing information ecosystem, combined with the widespread dissemination of misinformation and disinformation, has magnified the complexity of the issue. For infodemic management measures to be effective, acceptable, and trustworthy, a robust framework of ethical considerations is needed.

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Theme Issue 2023: Exploring the Intersection Between Health Information, Misinformation, and Generative AI Technologies

Manually analyzing public health–related content from social media provides valuable insights into the beliefs, attitudes, and behaviors of individuals, shedding light on trends and patterns that can inform public understanding, policy decisions, targeted interventions, and communication strategies. Unfortunately, the time and effort needed from well-trained human subject matter experts makes extensive manual social media listening unfeasible. Generative large language models (LLMs) can potentially summarize and interpret large amounts of text, but it is unclear to what extent LLMs can glean subtle health-related meanings in large sets of social media posts and reasonably report health-related themes.

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Theme Issue 2023: Exploring the Intersection Between Health Information, Misinformation, and Generative AI Technologies

Politicization and misinformation or disinformation of unproven COVID-19 therapies have resulted in communication challenges in presenting science to the public, especially in times of heightened public trepidation and uncertainty.

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Infodemic Management

Infectious disease surveillance is difficult in many low- and middle-income countries. Information market (IM)–based participatory surveillance is a crowdsourcing method that encourages individuals to actively report health symptoms and observed trends by trading web-based virtual “stocks” with payoffs tied to a future event.

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Infoveillance and Social Listening

TikTok (ByteDance) experienced a surge in popularity during the COVID-19 pandemic as a way for people to interact with others, share experiences and thoughts related to the pandemic, and cope with ongoing mental health challenges. However, few studies have explored how youth use TikTok to learn about mental health.

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Infoveillance and Social Listening

Prenatal alcohol exposure represents a substantial public health concern as it may lead to detrimental outcomes, including pregnancy complications and fetal alcohol spectrum disorder. Although UK national guidance recommends abstaining from alcohol if pregnant or planning a pregnancy, evidence suggests that confusion remains on this topic among members of the public, and little is known about what questions people have about consumption of alcohol in pregnancy outside of health care settings.

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Preprints Open for Peer-Review

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