JMIR infodemiology最新文献

Background: Diabetic retinopathy (DR) is a leading cause of vision loss, particularly in the Middle East. With the rise of online health information, many patients turn to the internet for knowledge about health conditions. However, the accuracy and quality of this information can be questionable, particularly in languages other than English.

Objective: We sought to evaluate the quality and reliability of Arabic websites on DR to address this knowledge gap and improve patient care.

Methods: The first 100 Arabic search results for DR were examined on Google, focusing on patient education websites in Arabic. Content was assessed using a 20-question model, quality was evaluated with the DISCERN instrument, and reliability was measured using the Journal of the American Medical Association (JAMA) benchmark. Two independent raters conducted evaluations, and data were analyzed with SPSS (IBM Corp). Descriptive statistics were used for website characteristics, and the first 10 Google web pages were compared to others using bivariate analysis with a significance level of P<.05.

Results: A Google search yielded 178,000 websites, and the first 100 were examined, with 29 meeting inclusion criteria. Most were hospital or medical center sites (n=20, 69%). The DISCERN assessment showed a low mean score of 36.59(SD 9.32) out of 80 points, with most rated "poor" or "very poor." The JAMA benchmarks indicated low reliability, with 62% (18/29) failing to meet any criteria.

Conclusions: This study identified significant failings in the content, quality, and reliability of Arabic websites on diabetic retinopathy, highlighting the need for stronger evidence-based online resources focused on early disease prevention.

Background: Alcohol consumption in China poses significant public health challenges. Alcohol marketing has been shown to increase public alcohol consumption, with social media platforms such as Douyin (TikTok in Mainland China) being among the main channels for alcohol marketing.

Objective: This study aimed to analyze the thematic content of alcohol advertising on the Douyin platform and to explore the factors influencing the popularity of these types of advertising.

Methods: Using data from the JINGDONG platform and alcohol industry reports, we identified 40 popular alcohol brands. For each brand, we located their official Douyin accounts and selected the top 20 most-liked videos posted between November 1, 2020, and November 1, 2021. In total, 659 videos from 37 brands were collected for analysis. Two trained researchers independently coded each video using a predefined codebook, which consisted of 7 sections and 20 items. Binary logistic regression was conducted with the grouping of the number of likes as the dependent variable, and the marketing strategies and warning elements of each video as independent variables.

Results: Among the 659 videos analyzed, 320 (48.6%) garnered more than 1000 likes. A significant portion of the videos was direct advertisements (281/659, 42.6%) and short skits (255/659, 38.7%), with 56.0% (369/659) featuring characters engaging in drinking-related behaviors or directly consuming alcohol. Additionally, many videos highlighted brand elements (510/659, 77.4%) and extended features (161/659, 24.4%). Cultural themes were also common, with 23.2% (153/659) of the videos promoting the enjoyment of life and 6.8% (45/659) emphasizing balance in life. However, age restrictions were missing for 26.9% (177/659) of the videos, and only 1.2% (8/659) included a health warning stating that "Drinking is harmful to health." Certain marketing strategies were significantly associated with greater video popularity, including the use of short skits (odds ratio [OR] 2.77, 95% CI 1.42-5.41), highlighting brand elements (OR 2.96, 95% CI 1.59-5.51), and emphasizing life balance (OR 3.44, 95% CI 1.11-10.66). In contrast, the presence of age restrictions (OR 0.32, 95% CI 0.15-0.67) and explicit health warnings (OR 0.06, 95% CI 0.01-0.84) were associated with lower popularity. The period from July to September and November was the peak release period for alcohol advertisements on Douyin.

Conclusions: Alcohol marketing strategies on Douyin leverage experiential, brand-driven, collaborative, and cultural marketing techniques to enhance video attractiveness and create alcogenic environments. Moreover, effective age restrictions and health warnings are largely absent. It is essential to legislate and enforce stricter alcohol marketing regulations to reduce the health risks associated with alcohol marketing.

Background: Sexual and reproductive health and rights (SRHR) are foundational to both individual autonomy and global well-being. Misinformation in this domain poses serious risks by undermining evidence-based decision-making, weakening systems of accountability, and perpetuating social injustices.

Objective: This scoping review aimed to map and synthesize evidence on the forms, spread, and impacts of misinformation related to SRHR in digital spaces, with a particular focus on implications for the protection and promotion of human rights.

Methods: We conducted a scoping review of scientific papers and gray literature. It was guided by the JBI (Joanna Briggs Institute) population, exposure, and outcomes framework. The extracted information was documented following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist. Thematic analysis was carried out and mapped against human rights standards: (1) equality and nondiscrimination; (2) Availability, Accessibility, Acceptability, and Quality; (3) informed decision-making; (4) privacy and confidentiality; (5) participation and inclusion; and (6) accountability.

Results: Of the 254 eligible studies and documents, 133 focused on the information ecosystem, 37 on the individual, 32 on service delivery and health system, 31 on law and policy, and 21 on community levels. SRHR misinformation impacts individuals' informed SRHR decisions by shaping their beliefs, attitudes, and health-seeking behaviors. It reinforces harmful and discriminatory social norms at community levels and the exclusion of marginalized voices. SRHR misinformation impacts health systems by shaping provider knowledge and practice, disrupting service delivery, and creating barriers to equitable care. It may function as a legal and policy tool to erode SRHR protections. The design of online platforms, digital marketing strategies, and content moderation policies enables misinformation to spread widely while restricting credible SRHR content.

Conclusions: SRHR misinformation in digital spaces is a systemic issue that undermines human rights across multiple levels, highlighting the urgent need for integrated, rights-based approaches to research, policy, and intervention.

Background: Digital media memes have emerged as influential tools in health communication, particularly during the COVID-19 pandemic. While they offer opportunities for emotional engagement and community resilience, they also act as vectors for health misinformation, contributing to the global infodemic. Despite growing interest in their communicative power, the role of memes in shaping public perception and misinformation diffusion remains underexplored in infodemiology.

Objective: This integrative review aims to analyze how memes influence emotional, behavioral, and ideological responses to health crises, and to examine their dual role as both contributors to and potential mitigators of infodemics. The paper also explores strategies for integrating memes into public health campaigns and infodemic management.

Methods: A comprehensive literature search was conducted across 3 major databases (MEDLINE, Scopus, and Web of Science), identifying a total of 386 records. Following duplicate removal and eligibility screening, 14 peer-reviewed studies published between 2020 and 2025 were included. An integrative narrative approach was used to synthesize evidence on social media behavior, misinformation dynamics, and digital health campaigns. The analysis was grounded in infodemiological and infoveillance frameworks as established by Eysenbach, incorporating insights from psychology, media studies, and public health.

Results: Memes function as emotionally salient and visually potent carriers of health-related narratives. While they can simplify complex messages and foster adaptive humor during crises, they are also susceptible to distortion, particularly in echo chambers and conspiracy communities. Findings reveal that misinformation-laden memes often leverage humor and disgust to bypass critical thinking, and their viral potential is linked to emotional intensity. However, memes have also been successfully integrated into prebunking strategies, increasing engagement and reducing susceptibility to false claims when culturally tailored. The review identifies key mechanisms that enhance or hinder the infodemiological value of memes, including political orientation, digital literacy, and narrative framing.

Conclusions: Memes are a double-edged sword in the context of infodemics. Their integration into infodemic surveillance and digital health campaigns requires a nuanced understanding of their emotional, cultural, and epistemic effects. Public health institutions should incorporate meme analysis into real-time infoveillance systems, apply evidence-based meme formats in prebunking efforts, and foster digital literacy that enables critical meme consumption. Future infodemiology research should further explore the long-term behavioral impacts of memetic misinformation and the scalability of meme-based interventions.

Background: Patients with knee osteoarthritis have a considerable need for information about their condition, its progression, and available treatments. Decision-making is often complex and requires evidence-based health information material (HIM). When medical consultations do not sufficiently address patients' needs, many seek additional information independently.

Objective: This study aimed to examine the quality of German-language HIM on knee osteoarthritis treatment and its suitability for supporting informed choice. In particular, the study analyzed the content of the HIM and assessed the balance in the presentation of treatment options.

Methods: A descriptive cross-sectional study was conducted. HIM was identified through a combination of search strategies, including a systematic internet search using commonly used German terms related to the treatment of knee osteoarthritis. Identified HIMs were independently assessed by 2 raters using the validated Mapping the Quality of Health Information (MAPPinfo) checklist, which operationalizes the criteria of the Guideline Evidence-Based Health Information. Information quality was calculated on a scale from 0% to 100%, representing compliance with the quality standard. A descriptive content analysis was also carried out to examine the range and balance of treatment options presented, as well as the reporting of benefits and complications associated with total knee arthroplasty (TKA). The presence of certification was recorded.

Results: A total of 94 HIMs were included. On average, the material met 14.6% (SD 9.4%) of the quality criteria. HIM from public and nonprofit providers performed better (mean 40.1%, SD 3.6% and mean 37.2%, SD 23.1%, respectively) than those from other providers. Overall, 14 HIMs presented treatment options in a balanced manner. Among the 78 HIMs that covered TKA, 38.5% (n=30) did not report any benefits, and 35.9% (n=28) omitted potential complications. Certified HIMs showed only moderately higher information quality than uncertified material (mean 26.8%, SD 16% vs mean 12.7%, SD 5.9%).

Conclusions: Our results highlight the urgent need to improve the quality of German-language HIM on knee osteoarthritis. The deficits identified are fundamental and affect all dimensions of information quality. Although HIM from public or nonprofit organizations has better information quality, this does not facilitate informed choice. The frequent omission of complications and benefits of TKA and the unbalanced presentation of treatment options can influence decisions. Until structural improvements are made, patients seeking quality information should favor material from public or nonprofit providers. Additionally, the MAPPinfo checklist could form the basis of a differentiated certification system to make information quality more transparent for patients.

Background: Opioid overdose is a global public health emergency, with the United States experiencing high rates of morbidity and mortality due to prescription and illicit opioid use. Traditional public health monitoring systems often fail to provide real-time insights, limiting their capacity for early detection and intervention. Social media platforms, especially Reddit, offer a promising alternative for timely toxicovigilance due to the abundance of user-generated, real-time content.

Objective: This study aimed to explore the use of Reddit as a real-time, high-volume source for toxicovigilance and develop an automated system that can classify and analyze opioid-related social media posts to detect behavioral patterns and monitor the evolution of public discourse on opioid use.

Methods: To investigate evolving social media discourse around opioid use, we collected a large-scale dataset from Reddit spanning 6 years, from January 1, 2018, to December 30, 2023. Using a comprehensive opioid lexicon-including formal drug names, street slang, common misspellings, and abbreviations-we filtered relevant posts for further analysis. A subset of these data was manually annotated according to well-defined annotation guidelines into 4 categories: self-misuse, external misuse, information, and unrelated, with distributions of 37.21%, 27.25%, 27.57%, and 7.97%, respectively. To automate the classification of opioid-related chatter, we developed a robust natural language processing pipeline leveraging classical machine learning algorithms, deep learning models, and transformer-based architecture, and fine-tuned a state-of-the-art large language model (LLM; OpenAI GPT-3.5 Turbo). In the final stage, the trained LLM was deployed on an unlabeled dataset comprising 74,975 additional Reddit chatter posts. This enabled a detailed temporal analysis of opioid-related discussions, aligned with 6 years of opioid-related death records from the Centers for Disease Control and Prevention (CDC). For this study, self-misuse and external misuse were merged into a misuse category for direct comparison with the CDC's mortality data, examining whether trends in social media discourse on opioid misuse reflect patterns in real-world mortality statistics.

Results: The fine-tuned GPT-3.5 Turbo model achieved the highest classification accuracy of 0.93, outperforming the baseline (random forest 0.85) by representing a performance improvement of 9.14% over the machine learning model. The temporal analysis of the unlabeled data revealed evolving trends in opioid-related discussions, indicating shifts in user behavior and overdose-related chatter over time. To quantify this relationship, we calculated the Pearson correlation coefficient between misuse-related posts and CDC death records (r=0.854). This correlation was statistically significant (P<.001), indicating a strong positive relationship betwe

Background: The quality of health information on social media is a major concern, especially during the early stages of public health crises. While the quality of the results of the popular search engines related to particular diseases has been analyzed in the literature, the quality of health-related information on social media, such as X (formerly Twitter), during the early stages of a public health crisis has not been addressed.

Objective: This study aims to evaluate the quality of health-related information on social media during the early stages of a public health crisis.

Methods: A cross-sectional analysis was conducted on health-related tweets in the early stages of the most recent public health crisis (the COVID-19 pandemic). The study analyzed the top 100 websites that were most frequently retweeted in the early stages of the crisis, categorizing them by content type, website affiliation, and exclusivity. Quality and reliability were assessed using the DISCERN and JAMA (Journal of the American Medical Association) benchmarks.

Results: Our analyses showed that 95% (95/100) of the websites met only 2 of the 4 JAMA quality criteria. DISCERN scores revealed that 81% (81/100) of the websites were evaluated as low scores, and only 11% (11/100) of the websites were evaluated as high scores. The analysis revealed significant disparities in the quality and reliability of health information across different website affiliations, content types, and exclusivity.

Conclusions: This study highlights a significant issue with the quality, reliability, and transparency of online health-related information during a public health challenge. The extensive shortcomings observed across frequently shared websites on Twitter highlight the critical need for continuous evaluation and improvement of online health content during the early stages of future health crises. Without consistent oversight and improvement, we risk repeating the same shortcomings in future, potentially more challenging situations.