Search Results (955)

Food health misinformation poses risks to public well-being, often spreading through social media and interpersonal contexts. This study extends the Influence of Presumed Media Influence (IPMI) model to explain how individuals move from attention to misinformation toward corrective behavioral intentions, while examining the moderating role of media literacy. Data were collected from a national online survey of 1021 Chinese adults, measuring media attention, presumed exposure of others, perceived negative influence, personal norms, media literacy, and correction intentions. Structural equation modeling supported a positive serial mediation chain, in which media attention was positively associated with presumed exposure of others, which in turn positively predicted presumed negative influence on others, leading to stronger personal norms and, ultimately, greater corrective behavioral intentions. Multi-group analysis showed that media literacy moderated this process: lower literacy amplified the link from perceived influence to norms, while higher literacy strengthened the link from norms to behavior. These findings advance the IPMI framework by highlighting media literacy as a critical boundary condition and suggest that interventions should not only correct misinformation but also foster responsibility for others and enhance media literacy to encourage user-driven corrections. Full article

Rumour propagation in online social networks poses significant risks to public trust, economic stability, and crisis management. Existing models often struggle with heterogeneous feature spaces, adversarial dynamics between rumours and debunking information, and data sparsity in early outbreak stages. This study introduces a cross-domain framework for group behaviour prediction that integrates unified representation learning, game-theoretic adversarial modelling, and transfer adaptation. A hybrid BERT–Node2Vec encoder captures both semantic richness and structural influence, while evolutionary game theory quantifies competitive interactions between rumour-spreaders and refuters. To alleviate data scarcity, Joint Distribution Adaptation (JDA) aligns heterogeneous feature spaces across domains, enabling robust transfer learning. Evaluated on simulated and real-world social media datasets, the proposed model demonstrates improved accuracy and interpretability in predicting rumour diffusion trends under adversarial conditions. These findings highlight the value of integrating semantic, structural, and behavioural signals into a scalable architecture, offering a practical solution for safeguarding digital ecosystems against misinformation. Full article

Growing global environmental awareness has fueled a “green” market, but also a confusing array of information, raising risks of misinformation. In response, sustainability certifications and instruments have become crucial tools in the cosmetics industry. However, the rapid spread of these ecolabels has created new problems, including market fragmentation, consumer confusion, and heightened concerns about greenwashing. This study conducts a systematic comparative analysis of 24 prominent sustainability schemes within the cosmetics sector. We developed an analytical framework to assess each instrument across three dimensions: (i) value chain coverage (from sourcing to end-of-life), (ii) corporate sustainability scope (environmental, social, governance), and (iii) verification and transparency mechanisms. The results reveal a fragmented landscape with significant scope imbalances. Most instruments robustly cover upstream impacts (e.g., ingredient sourcing), but downstream phases—including consumer use, packaging, and circularity—are markedly under-addressed. At the corporate level, environmental criteria dominate, with social and governance dimensions inconsistently integrated. Verification rigor and transparency vary widely, with many relying on confidential audits or self-declaration. In conclusion, while valuable as market instruments, prevailing certifications are insufficient as standalone assurance tools. The findings highlight a misalignment with emerging regulations, underscoring the need for greater lifecycle integration, enhanced transparency, and alignment with comprehensive corporate sustainability frameworks. Full article

Ease-of-retrieval theories predict that information seems more credible when supporting reasons come to mind easily. However, it is unclear whether this holds for realistically ambiguous news headlines. We conducted two preregistered experiments (N = 128; N = 135) in which participants evaluated six pilot-tested real and fake headlines selected to minimize baseline credibility differences between veracity categories. In Experiment 1, participants generated either two or six reasons supporting or opposing each headline’s truth. In Experiment 2, the two-versus-six manipulation was crossed with a 20 s time limit. Headline veracity (real vs. fake) varied within participants, who then rated perceived task difficulty, credibility, and familiarity. Across experiments, generating six (vs. two) reasons increased perceived difficulty and reduced perceived deliberation time, indicating that the manipulation affected subjective fluency. However, linear mixed-effects analyses showed no reliable effect of the number of reasons on credibility. Credibility instead shifted with the direction of reasons required (supporting vs. opposing; ΔM ≈ 1.3) and increased with headline familiarity (r ≈ 0.40). These findings suggest that for ambiguous real-world headlines, classic ease-of-retrieval manipulations may alter perceived effort without translating into credibility judgments. Future work should test stronger fluency interventions and account for familiarity and motivational factors. Full article

Objectives: The objectives of this study were to educate the healthcare professional and the general public about interoperable vaccine records by elaborating on its definition, why we need one, what the challenges are, and what progress has been made in this direction. Methods: The vaccination practices and vaccine record-keeping in the Nordic countries, the UK, and the USA are used as examples to demonstrate the necessity of interoperable vaccine records. The authors’ expertise and experience in interoperability, medicine, and HealthIT, along with the literature, informed this paper’s content, structure, and organization. Real-world examples and scenarios illustrate the reality and significance of interoperable vaccine records. Results: This paper provides a brief description of vaccination records and their practices in the Nordic countries, the UK, and the USA, which can inform future best practices for vaccination record-keeping. This paper also proposes a conceptual roadmap for achieving an interoperable vaccine record, which is a critical component for maintaining the integrity of an individual’s health record longitudinally, an essential cornerstone for receiving safe and effective healthcare, improving patient outcomes, controlling healthcare costs, avoiding unnecessary revaccination (overvaccination), and enabling alignment with up-to-date vaccine recommendations. This paper examines the intersection of vaccinations, HealthIT, and vaccine record-keeping, and it provides a brief discussion of the social and political aspects of vaccination. Conclusions: Although achieving interoperable vaccine records is technically feasible and clinically important, their large-scale implementation is not a simple task amid the social and political challenges related to vaccine misinformation, acceptance, and hesitancy. Full article

Deepfake technology can produce highly realistic manipulated media which pose as significant cybersecurity threats, including fraud, misinformation, and privacy violations. This research proposes a deepfake prevention approach based on symmetric and asymmetric ciphers. Post-quantum asymmetric ciphers were utilized to perform digital signature operations, which offer essential security services, including integrity, authentication, and non-repudiation. Symmetric ciphers were also employed to provide confidentiality and authentication. Unlike classical ciphers that are vulnerable to quantum attacks, this study adopts quantum-resilient ciphers to offer long-term security. The proposed approach enables entities to digitally sign media content before public release on other platforms. End users can subsequently verify the authenticity of content using the public keys of the media creators. To identify the most efficient ciphers to perform cryptography operations required for deepfake prevention, the study explores the implementation of quantum-resilient symmetric and asymmetric ciphers standardized by NIST, including Dilithium, Falcon, SPHINCS+, and Ascon-80pq. Additionally, this research provides comprehensive comparisons between the various classical and post-quantum ciphers in both categories: symmetric and asymmetric. Experimental results revealed that Dilithium-5 and Falcon-512 algorithms outperform other post-quantum ciphers, with a time delay of 2.50 and 251 ms, respectively, for digital signature operations. The Falcon-512 algorithm also demonstrates superior resource efficiency, making it a cost-effective choice for digital signature operations. With respect to symmetric ciphers, Ascon-80pq achieved the lowest time consumption, taking just 0.015 ms to perform encryption and decryption operations. Also, it is a significant option for constrained devices, since it consumes fewer resources compared to standard symmetric ciphers, such as AES. Through comprehensive evaluations and comparisons of various symmetric and asymmetric ciphers, this study serves as a blueprint to identify the most efficient ciphers to perform the cryptography operations necessary for deepfake prevention. Full article

Travel-associated Legionnaires’ disease (TALD) events can generate public concern when environmental surveillance findings are communicated without an adequate explanation of the results. This study examined how surveillance data on Legionella spp. were framed and amplified during a TALD-related investigation in Crete, Greece, from June to July 2025. A mixed infodemiology and environmental surveillance approach was applied, including the analysis of 95 online media items across nine languages, Google Trends search-interest data, and hotel water-system surveillance data from epidemiologically linked facilities. Sampling conducted in a limited number of hotels associated with TALD cases indicated that approximately 50% of the water samples exceeded the laboratory reporting limit of ≥50 CFU/L for Legionella spp., a numerically correct but context-specific finding. Numerical misframing occurred in 83.7%, 41.7%, and 18.2% of Greek, German, and English language items, respectively, with significant differences across language markets (χ² (8) = 43.75, p < 0.0001; Cramér’s V = 0.679). Public search-interest signals were transient and geographically limited. Environmental surveillance showed no increase in Legionella pneumophila risk, with similar proportions of samples ≥50 CFU/L in the pre-/peri-infodemic (January–July 2025) and post-infodemic (August–November 2025) periods (23.11% [95% CI: 18.21–28.87] vs. 24.45% [19.34–30.41]) and similar exceedance of ≥1000 CFU/L (13.45% [9.69–18.36] vs. 14.41% [10.45–19.55]). Overall, the loss of contextual interpretation of surveillance results and conflation of laboratory reporting limits with regulatory thresholds were associated with inconsistent public risk perception, without evidence of increased environmental hazard. Full article

Rumor source detection aims to identify the initial origin of misinformation diffusion in social networks. Accurate source localization is essential for effective rumor intervention and early mitigation in large-scale social media platforms. Existing rumor source detection methods often struggle to model complex propagation structures. However, applying mathematical models uniformly to all samples introduces unnecessary computational overhead and limits scalability. By leveraging GNN-based candidate ranking, our approach effectively narrows the source search space and provides a reliable structural foundation for subsequent reasoning. Prior studies typically perform end-to-end inference without considering prediction confidence, leading to inefficient processing of low-uncertainty samples. To address this issue, we introduce an entropy-based uncertainty filtering mechanism that selectively identifies high-uncertainty cases requiring further reasoning, significantly reducing redundant computation. Meanwhile, existing methods lack semantic interpretability when handling ambiguous propagation patterns, motivating the incorporation of large language model (LLM) reasoning. We employ LLM-based reasoning only on filtered samples to enhance semantic understanding while controlling inference cost. Based on these designs, we propose TSR-RSD, a tri-stage selective reasoning framework that integrates GNN-based structural modeling, uncertainty-driven sample selection, and LLM-based semantic reasoning. Experimental results on GossipCop, PolitiFact, and PHEME demonstrate that TSR-RSD consistently outperforms GNN-based baselines in terms of Hit@1, Hit@3, Hit@5, and Mean Reciprocal Rank (MRR), reflecting improved accuracy and stability in rumor source ranking. Furthermore, the entropy-based uncertainty filtering mechanism significantly reduces the LLM invocation ratio by approximately 40–60%, while maintaining comparable or improved ranking performance. As a result, TSR-RSD achieves an overall inference time reduction of 35–50%, effectively balancing localization accuracy, computational efficiency, and interpretability. Full article

(1) Background: The incidence and impact of misleading information on public opinion in the field of nutrition and food science, focusing on the mechanisms of dissemination and their potential consequences, are increasingly being explored in academia. It is therefore essential to highlight the importance of studying discourse to understand the contexts and motivations behind the persistent circulation of hoaxes. For this reason, this research compiles and analyses the news content on food fake news published in the web repository of Spanish information verifiers Newtral and Maldita Alimentación. (2) Method: The period analysed extends from the launches of both platforms (2018 and 2021, respectively) to 2024, examining a total of 564 news items using computerised analysis software. (3) Results: The results show three thematic clusters related to the information refuted by Newtral and five clusters belonging to Maldita Alimentación. The findings of this research are consistent with a prevalence of concern for public health; the risk of disease due to poor food management; the role of authorities, especially in the European context; the supervision of food quality and the protection of public health; and the debunking of messages about food properties without scientific evidence. (4) Conclusions: The article highlights the importance of implementing strategies that foster trust in information sources, such as fact-checkers, and encourage the scientific dissemination of food-related content in an accessible manner. Full article

The COVID-19 pandemic revealed substantial variation in vaccine attitudes and susceptibility to misinformation, raising concerns from an occupational health perspective about potential differences across employment sectors. This study examined associations between employment category and pandemic-related changes in mental health, and vaccine-related misinformation among adults in Poland. Data were collected between 13 January and 14 February 2022 using a cross-sectional online survey. Complete questionnaires from 7018 respondents were analyzed. Employment category (services, industry, agriculture, unemployed) was examined in relation to self-reported changes in sleep, mental health, physical activity, and diet. A misinformation index was constructed based on agreement with eight vaccine-related misinformation statements. Overall, 81.8% of participants reported being vaccinated. Employment category was significantly associated with perceived changes in sleep, mental health, and diet. The misinformation index was consistently higher among unvaccinated individuals across all employment groups, with the largest differences observed among the unemployed and agricultural workers. These findings show a strong link between vaccine misinformation and remaining unvaccinated, highlighting the need for targeted occupational health education and reliable health information. Increasing vaccination coverage therefore requires not only vaccine availability but also systematic efforts to counteract misinformation and strengthen digital health literacy across occupational groups. Full article

Objective: To evaluate the level of knowledge, attitudes, and practices of Hungarian general practitioners (GPs) concerning human papillomavirus (HPV) infection, cervical cancer prevention, and HPV vaccination, and to identify physician-level factors associated with proactive recommendation practices. Methods: A cross-sectional nationwide survey was conducted between 30 April and 1 June 2024. The online questionnaire was distributed to practicing Hungarian GPs listed in the National Health Insurance Fund database. Anonymous responses were collected on demographic data, knowledge of HPV transmission and oncogenic potential, awareness of vaccination guidelines, and clinical counseling habits. Descriptive and inferential statistical analyses were performed. A total of 413 responses were received. Results: Most respondents were female (72.6%) with an average of 22.4 ± 9.6 years of professional experience. Although 89.8% correctly identified the causal link between HPV and cervical cancer, only 56.2% were aware of the complete vaccination schedule recommended for adolescents initiating after age 15. Knowledge scores were significantly higher among female physicians, urban practitioners, and those with postgraduate preventive medicine training. While the overall attitude toward HPV vaccination was positive (mean 4.6/5), 38.4% of respondents reported parental hesitancy as a common barrier, often citing misinformation regarding vaccine safety (64.9%) and lack of perceived need for boys (58.7%). Regression analysis revealed that familiarity with WHO and national vaccination guidelines independently predicted proactive vaccine recommendation (β = 0.43, p < 0.001). Conclusions: Hungarian general practitioners demonstrate good baseline awareness of HPV and its oncogenic role; however, knowledge gaps persist regarding vaccination schedules and counseling practices. Enhancing continuous medical education and communication training could strengthen GPs’ role as key advocates in HPV vaccine promotion. Full article

Human papillomavirus (HPV) is the most common sexually transmitted infection worldwide and is a leading cause of cervical, anal, penile, and oropharyngeal cancers. This review summarizes the epidemiology of HPV and the immunogenicity, clinical efficacy, and current HPV vaccination recommendations among people living with HIV (PLWH). PLWH experience a disproportionate burden of HPV-related infection and HPV-related malignancies. Although HPV vaccines have been shown to be highly effective, vaccination coverage among PLWH remains suboptimal, particularly in low- and middle-income countries. Barriers to vaccination include extended dosing schedules, limited awareness of the vaccine, and misinformation. Evidence indicates HPV vaccines are safe and induce a robust antibody response in PLWH, especially among individuals with higher CD4+ cell counts and viral suppression on antiretroviral therapy. However, evidence for reduction in clinical HPV-related disease in this population remains limited. Ongoing research is aimed at optimizing the HPV vaccination schedule for PLWH and expanding vaccination in older, high-risk subgroups. Integrating HPV vaccination into HIV care is essential to reduce HPV-related morbidity and mortality in PLWH. Full article

Building resilience is largely affected by the socioeconomic characteristics of the community as well as the physical and environmental local characteristics. The effectiveness of the adopted policies for resilience building partly relies on considering public concerns and insights. Insights from public narratives can enrich the resilience-building policies by sharing experiences or evidence from past disasters. Furthermore, it reveals priorities and concerns that society is expecting to be addressed. Even if the concerns are triggered by misinformation, addressing them (e.g., by disseminating corrective information) can increase the success of resilience-building policies. Tracing the public narrative over time shows how much people’s perspectives have changed after the disaster and how the relief and resilience-building efforts were compatible with society’s expectations. This study is aimed at extracting such insights from the public narrative on social media platforms after Morocco’s 2023 earthquake. Full article

Background/Objectives: Vaccine hesitancy arises from multiple determinants, including individual beliefs, cognitive style, social norms, political identity and the information environment. In this context, health literacy, e-health literacy, susceptibility to health misinformation, conspiracy beliefs and trust in science may be relevant in mediatized societies. Aim: The aim of the study was to examine how susceptibility to health misinformation relates to vaccine hesitancy in Poland and how this association is influenced by health literacy, e-health literacy, trust in scientists and sociodemographic factors. Methods: Data came from a web-based survey conducted in December 2024 among 2200 adults aged 18–75 years. The questionnaire included validated scales of vaccine hesitancy, health literacy, e-health literacy, vaccine conspiracy beliefs and trust in scientists. The susceptibility to health misinformation was measured with ad hoc instrument based on the statement from fact-checking services. Items assessing digital media use, political sympathies, religious practices and sociodemographics were also applied. Multivariable linear regression was applied with continuous vaccine hesitancy as the dependent variable. Results: The model explained 57.8% of the variance in vaccine hesitancy. Susceptibility to misinformation (B = 0.11, 95% CI: 0.08–0.15) and vaccine conspiracy beliefs (B = 0.44, 95% CI: 0.41–0.46) were positive predictors, whereas trust in scientists (B = −0.20, 95% CI: −0.23–−0.17) and e-health literacy (B = −0.07, 95% CI: −0.11–−0.02) were protective. Older age was associated with lower hesitancy (B = −0.02, 95% CI: −0.03–0.00). Secondary education (B = −0.58) and a master’s degree (B = −0.77) predicted lower hesitancy. Health literacy categories were not significantly related to vaccine hesitancy. Conclusions: Susceptibility to health misinformation and vaccine conspiracy beliefs were key predictors of vaccine hesitancy, outweighing the effects of health literacy and the protective impact of trust in scientists and e-health literacy, and indicating a need for interventions that combine prebunking and literacy-focused strategies with efforts to strengthen confidence in health institutions. Full article

Artificial intelligence is increasingly being used in all branches of the media system and has transformed the way specialists in this field work in recent years. Currently, applications of artificial intelligence are used across a range of processes involved in the production, editing, distribution, and consumption of media content. These include technologies such as generative chatbots, automated transcription, writing, translation, and editing tools, as well as applications for image and video creation. All of these types of applications have taken over a significant portion of the traditional activities carried out by media professionals. From a technological point of view, these uses primarily rely on machine learning, natural language processing, and computer vision techniques, complemented by generative models that automatically analyze, generate, and interpret text, sound, and images. Although these technologies contribute to increased efficiency, faster work, and reduced operating costs, they also pose significant risks, particularly regarding the spread of false information. From a theoretical perspective, artificial intelligence goes beyond the status of a technological tool, being conceptualized as a communicational actor that actively intervenes in the generation, structuring, and circulation of messages, influencing the relationships between producers, content, and audiences in the current media environment. Full article