Accurate Information Research Articles

Fake News Detection and Analysis

Abstract: The internet is filled with inaccurate information, which makes it tough to distinguish between what is true and what is not. This review paper explores how scholars and IT professionals are countering false information by examining various strategies. We start by looking at different types of fake news and how they circulate. We then discuss a range of methods and tools that can be used to identify false information, including advanced computer programs and language analysis. These approaches can be categorized into three groups: analysing the language used, taking into account contextual data, and studying the distribution trends on the internet. We also discuss a method for teaching computers to detect patterns using machine learning false narratives by learning to differentiate between emotions and language subtleties. The paper also emphasizes the significance of fairness and impartiality in detection technologies. We conclude by discussing possible future research areas for academics and technology professionals it's critical to stay current with the quickly developing field of fake news.

A machine learning based approach for generating point sketch maps from qualitative directional information

People often use qualitative relations to describe locations or directional information, especially in written communication, such as ‘the restaurant is located at the southeast corner of the square’. However, when a large number of spatial entities are involved, qualitative relations alone are not intuitive enough for people to understand a spatial configuration. In fact, many applications, e.g. pertaining to sharing travel experiences, use sketch maps, i.e. maps focusing on the main features of an area whilst abstracting exact scale measurements, to help demonstrate abstract qualitative relations with more intuitive geometric points. Current approaches for generating point sketch maps from qualitative spatial relations require a high level of expertise, face inherent difficulties with efficiently processing large-scale data in bulk, and are vulnerable to inaccurate or conflicting information contained in qualitative data. To address these limitations, by incorporating machine learning techniques, we propose to translate the problem into an optimization problem of data reconstruction, enabling a novel end-to-end approach for generating point sketch maps from qualitative directional relations in bulk. Experiments on real-world datasets show that the proposed approach has very high accuracy and is robust even with a large portion of inaccurate or incomplete information.

Reusable, Green, Portable Ionogels Based on Terpyridine-Imidazole Salt for Visual Monitoring of Pork Spoilage.

Ionogels have emerged as a promising approach because they combine the advantageous properties of ionic liquids and gels. Herein, a novel gelator bearing terpyridine and imidazolium salt units was designed and synthesized, which assembled into ionogels in three ionic liquids by a heating-cooling procedure. The properties of ionogels were characterized by FT-IR, UV-vis spectroscopy, POM, XRD, and rheology, and resonance light scattering and opacity measurements were conducted to investigate the gelation kinetics. Furthermore, the ionogels incorporating pH-sensitive dyes (BTB and MR) were exploited as colorimetric sensor to monitor total volatile basic nitrogen (TVB-N) of meat at -4 °C, which can easily and reliably estimate the quality of meat by naked eye recognition, and the results demonstrated a positive correlation between the color variation and TVB-N levels. Notably, the hydrophobic ionogel indicators are more suitable for potential application at high humidity thanks to their antiswelling advantage, which could prevent the inaccurate information produced by hydrogel indicators. In addition, the ionogels could be reused up to three times as colorimetric indicators, suggesting potential applications and competitiveness. Our research sheds new light on the novel application of ionogels in the food industry.

Barriers to pregnancy prevention for adolescents in rural Haiti: perceptions of healthcare providers.

Little is known about healthcare providers' (HCPs) contraceptive views for adolescents in Haiti, who experience high rates of unintended pregnancy. We sought to describe HCPs' perspectives on barriers and facilitators to contraceptive care delivery in rural Haiti. We conducted a cross-sectional survey and qualitative interviews with HCPs in two rural communities in Haiti from 08/2021-03/2022. We assessed demographics, clinical practice behaviors and explored contraception perspectives according to Theory of Planned Behavior constructs: attitudes, subjective norms, and perceived behavioral control (e.g., people's perceptions of their ability to perform a given behavior, barriers and facilitators of a behavior).15-17 We used descriptive statistics to report proportions and responses to Likert scale and multiple-choice questions. Guided by content analysis, we analyzed interview transcripts through thematic inductive coding and team debriefing. Among 58 respondents, 90% (n = 52) were female and 53% (n = 31) were nurses. Most reported always (n = 16, 28%) or very often (n = 21, 36%) obtaining a sexual history for adolescents. A majority agreed/strongly agreed that clinicians should discuss pregnancy prevention (n = 45, 78%), high-risk sexual behaviors (n = 40, 69%), and should prescribe contraception (n = 41, 71%) to adolescents. The most frequently cited provider-level barriers (i.e., significant or somewhat of a barrier) included insufficient contraception knowledge (n = 44, 77%) and time (n = 37, 64%). HCPs were concerned about barriers at the patient-level (e.g. adolescents' fear of parental notification [n = 37, 64%], adolescents will give inaccurate information about sexual behaviors [n = 25, 43%]) and system-level (e.g. resistance to providing care from administration [n = 33, 57%]). In interviews (n = 17), HCPs generally supported contraception care for adolescents. Many HCPs echoed our quantitative findings on concerns about privacy and confidentiality. HCPs reported concerns about lack of contraception education leading to misconceptions, and community and parental judgement. HCPs expressed interest in further contraception training and resources and noted the importance of providing youth-friendly contraceptive care. While HCPs support contraceptive care, we identified actionable barriers to improve care for adolescents in rural Haiti. Future efforts should include increasing HCP knowledge and training, community and parent coalition building to increase contraception support and offering youth-friendly contraceptive care to offset risk for related adverse health outcomes in adolescents in rural Haiti.

Acceptance and use of ChatGPT in the academic community

AbstractSince OpenAI released ChatGPT, the discussion on its usage in education has been conducted by students and teachers of every education level. Also, many studies have been performed on the tool’s possibilities and the threats related to its usage, such as incomplete or inaccurate information obtained or even plagiarism. Many universities worldwide have introduced specific regulations on ChatGPT usage in academic work. Furthermore, research on using ChatGPT by students and their attitudes towards it has appeared. However, a research gap exists in higher education teachers’ acceptance of AI solutions. The goal of this research was to explore the level of acceptance of the usage of ChatGPT by academics in Poland, as well as point out factors influencing their intention to use this tool. The study motivation was related to an ongoing academic discussion mainly focusing on the disadvantages of AI solutions used in scientific work and the willingness to fill the gap by showing teachers’ attitudes toward AI. The data was collected online by inviting academic teachers from Polish public universities to complete the prepared survey. The survey was prepared using the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model extended with Personal Innovativeness. It revealed the acceptance level of ChatGPT usage in Polish universities by teachers and researchers and the antecedents influencing willingness to use this technology in academic work. The paper contributes to the theory of AI usage by structuring the studies regarding ChatGPT application for teaching and research, and provides practical recommendations on ChatGPT adoption in the work of academics.

Analysis of Ethical and Legal Aspects in Implementing a Medical Record System in Hospitals on Patient Health Practices

Implementing a medical record system in a hospital plays an integral role in managing patient health information. This article analyzes the ethical and legal aspects involving medical record management, and their impact on patient health practices in hospitals. Findings regarding breaches of confidentiality, inaccurate information, inappropriate access, delays in patient access, and non-transparency of information are the main focus. Ethical implications involve the risk of losing patient trust and the establishment of a positive doctor-patient relationship, while legal implications include potential lawsuits by patients and administrative sanctions against medical record system administrators. Thus, improvements in regulatory compliance, increased ethical awareness among health workers, and implementation of best practices are recognized as crucial steps in maintaining the integrity of the health system and ensuring ethical and legally compliant health practices. In conclusion, collaboration between stakeholders and a holistic approach are needed to achieve the implementation of a medical record system that prioritizes patient rights and interests, strengthens trust, and improves the quality of health services in hospitals.

Magnetopause location modeling using machine learning: inaccuracy due to solar wind parameter propagation

An intrinsic limitation of empirical models of the magnetopause location is a predefined magnetopause shape and assumed functional dependences on relevant parameters. We overcome this limitation using a machine learning approach (artificial neural networks), allowing us to incorporate general, purely data-driven dependences. For the training and testing of the developed neural network model, a data set of about 15,000 magnetopause crossings identified in the THEMIS A-E, Magion 4, Geotail, and Interball-1 satellite data in the subsolar region is used. A cylindrical symmetry around the direction of the impinging solar wind is assumed, and solar wind dynamic pressure, interplanetary magnetic field magnitude, cone angle, clock angle, tilt angle, and corrected Dst index are considered as parameters. The effect of these parameters on the magnetopause location is revealed. The performance of the developed model is compared with other empirical magnetopause models. Finally, we demonstrate and discuss the inaccuracy of magnetopause models due to the inaccurate information about the impinging solar wind parameters based on measurements near the L1 point. This inaccuracy imposes a theoretical limit on the precision of magnetopause predictions, a limit that our model closely approaches.

The Use of Generative AI for Scientific Literature Searches for Systematic Reviews: ChatGPT and Microsoft Bing AI Performance Evaluation.

A large language model is a type of artificial intelligence (AI) model that opens up great possibilities for health care practice, research, and education, although scholars have emphasized the need to proactively address the issue of unvalidated and inaccurate information regarding its use. One of the best-known large language models is ChatGPT (OpenAI). It is believed to be of great help to medical research, as it facilitates more efficient data set analysis, code generation, and literature review, allowing researchers to focus on experimental design as well as drug discovery and development. This study aims to explore the potential of ChatGPT as a real-time literature search tool for systematic reviews and clinical decision support systems, to enhance their efficiency and accuracy in health care settings. The search results of a published systematic review by human experts on the treatment of Peyronie disease were selected as a benchmark, and the literature search formula of the study was applied to ChatGPT and Microsoft Bing AI as a comparison to human researchers. Peyronie disease typically presents with discomfort, curvature, or deformity of the penis in association with palpable plaques and erectile dysfunction. To evaluate the quality of individual studies derived from AI answers, we created a structured rating system based on bibliographic information related to the publications. We classified its answers into 4 grades if the title existed: A, B, C, and F. No grade was given for a fake title or no answer. From ChatGPT, 7 (0.5%) out of 1287 identified studies were directly relevant, whereas Bing AI resulted in 19 (40%) relevant studies out of 48, compared to the human benchmark of 24 studies. In the qualitative evaluation, ChatGPT had 7 grade A, 18 grade B, 167 grade C, and 211 grade F studies, and Bing AI had 19 grade A and 28 grade C studies. This is the first study to compare AI and conventional human systematic review methods as a real-time literature collection tool for evidence-based medicine. The results suggest that the use of ChatGPT as a tool for real-time evidence generation is not yet accurate and feasible. Therefore, researchers should be cautious about using such AI. The limitations of this study using the generative pre-trained transformer model are that the search for research topics was not diverse and that it did not prevent the hallucination of generative AI. However, this study will serve as a standard for future studies by providing an index to verify the reliability and consistency of generative AI from a user's point of view. If the reliability and consistency of AI literature search services are verified, then the use of these technologies will help medical research greatly.

Using Multimedia to Help Agricultural Producers Communicate with Consumers about GMOs

Genetically modified organisms (GMOs) and their uses are often misunderstood. Consumers are regularly unsure what GMOs are, or if they are safe for consumption and the environment. Contradictory and sometimes inaccurate information is available from numerous sources, and challenges consumers and others to separate the facts from sensationalized stories. Agricultural producers often communicate with consumers, neighbors, and members of the general public; however, they do not have information to share about GMOs. Multimedia resources can provide agricultural producers with science-based information to share with consumers. Agricultural communicators and Extension educators can create science-based multimedia resources to bridge the communication gap.

Three-dimensional forest structure features extraction based on TomoSAR

Abstract. Forest structure is an important indicator for evaluating forest ecosystem and an indispensable input parameter for estimating forest carbon sink. Synthetic Aperture Radar (SAR) Tomography (TomoSAR), as a novel microwave remote sensing technique with 3D imaging capability, has been demonstrated to be an valuable tool for accurate inversion of forest structure. At present, the forest vertical structure parameters inversion is almost all concentrated on the forest height estimation. However, the spatial structure of forests is complex, and it is not enough to only use the forest height to express the forest structure. This fails to identify tree canopy, branch layer and underlying vegetation layer, etc., resulting in the partial and inaccurate forest vertical structure information. To solve this problem, this paper constructs 3D structural indices from tomograms, namely Horizontal Structure Index (HS) and Vertical Structure Index (VS). The HS primarily describes canopy density, compensating for the lack of information on the horizontal dimension of forest structure provided by traditional TomoSAR techniques; while VS describes the complexity of canopy distribution in the altitude direction, further enriching information on forest structure vertically. In order to verify their feasibility and validity, HS and VS are extracted using six fully-polarized L-band SAR images covering the Krycklan watershed in Sweden. Moreover, the accuracy is verified by using external high-precision LiDAR data. The results indicate a strong correlation between the structural indices extracted from TomoSAR and those extracted from LiDAR.

Reasons for the Continuous Existence of the Pink Tax

The price difference between almost identical products, because of the difference in who they are sold to and the overall higher sales price of women's products than of men's products, is known as the "pink tax.". The study analyzes the reasons for the persistence of the pink tax in the market for a long time, utilizing questionnaires and interviews. The main factors that contribute to the persistence of the pink tax are information, customer, market, and policy. Due to inaccurate and incomplete product information, the pink tax is unavoidable. Compared to men, female consumers are more likely to buy expensive products as they are more willing to spend on design and impulse consumption. Therefore, for the market, the fact that it is easier to profit from female consumers will undoubtedly contribute to the phenomenon of the pink tax, which will help businessmen make more profits from female consumers. In addition, as some potential problems are insensible to the government, some policies are not able to protect womens rights perfectly.

HOW INFORMATION AND DISINFORMATION IN SOCIAL MEDIA AFFECTS NEUROLOGISTS’ MEDICAL PRESCRIPTIONS

Neurologists must critically evaluate social media information, due to the possibility of misinformation influencing their prescriptions. Misinformation on these platforms may mislead patients into seeking unproven treatments. Neurologists should educate their patients about the prevalence of inaccurate information online and promote the use of credible health websites. They must also stay updated with recent research, establish guidelines for discussing internet research with patients, and collaborate with human-computer interaction professionals for better results. A cautious approach towards social media can ensure accurate prescriptions and mitigate potential harm to patient care.

THE ROLE OF ATOMIC SCATTERING FACTORS IN DETERMINING THE MINERAL COMPOSITION OF THE BAZHENOV SUITE'S ROCKS

For the first time, it was demonstrated, that the use of standard atomic-structural parameters of minerals in X-ray diffraction (XRD) analysis to determine the phase composition in the Bazhenov suite's core is incorrect and most often leads to inaccurate information when calculating their quantitative ratio. In particular, by decomposing the XRD — based quantitative data on the mineral composition of the core of the Bazhenov suite into the main rock-forming oxides and further comparing them with reliable X-ray fluorescence spectrometry (XRF) data, an unsatisfactory convergence between them was established. At the same time, significant differences in the results of XRD and XRF have been shown in terms of oxides of silicon, sodium, magnesium, potassium, and iron, both at large and small mass fractions. It has been found that even with perfect XRD, achieved by optimizing the standard mineral structure parameters (lattice period, crystallite size, crystal lattice microdistortion, absorption coefficient, crystallographic texture, background) and achieving a very high degree of convergence (more than 95%) of experimental and theoretical diffractograms, the differences between oxide forms are still significant. It is shown, that the results of XRD of Bazhenov suite are questioned due to detected inconsistencies in oxide forms. Using the analysis of multiple factors and data from diffractograms of many samples, it has been established that the identified differences are primarily caused by the use of incorrect initial atomic-structure parameters of minerals in modeling. It is shown that rock minerals in the Bazhenov suite are primarily characterized by significant changes in the values of atomic scattering factors and significant displacements of atomic positions in the nodes of the crystal lattice, caused by the action of the high pressures and temperatures in the formation. For the first time, the XRD algorithm that has been developed, is presented and implemented in Bazhenov suite rocks, with consideration of the state of atoms in the analyzed mineral. Furthermore, it was found that the authors XRD approach enables the identification and quantification of the Bazhenov suite minerals with a relatively low content, which are challenging to identify during traditional XRD.

Public Health Students and Instructors Weigh in on Generative Artificial Intelligence: Are They on The Same Page?

Generative artificial intelligence (genAI) technology is used among students, yet it remains unclear how public health students and instructors perceive it to be effective in a learning environment. We described how and why public health students and instructors are using genAI technology along with their perceived benefits and limitations of using genAI, noting where perceptions overlap. We surveyed public health students and instructors at a higher education institution in the United States. Student survey questions covered which genAI technologies they used, which activities they used genAI for, and perceived benefits and limitations of using genAI. Questions for instructors covered which genAI technology they used, course activities genAI was integrated, and perceived benefits and limitations of using genAI. Student respondents ( n = 300) indicated using genAI technology for writing or clarifying concepts. Students and instructors ( n = 62) agreed genAI technology could save time on tedious tasks and will be part of our future workforce. They agreed that appropriate use in the classroom will better prepare future professionals. Alternatively, students and instructors indicated genAI may impede learning, produce inaccurate information, and pose opportunities for unethical behavior. While students and instructors agree on many aspects of genAI technology, instructors should be explicit about their expectations and rationale for use of genAI technology in classrooms.

POST-COVID-19 RANDOMIZED CONTROLLED TRIALS COMPARING INTRAMEDULLARY NAILS AND SLIDING HIP SCREW CONSTRUCTS FOR INTERTROCHANTERIC FRACTURES DO NOT REPRESENT TYPICAL PATIENT DEMOGRAPHICS: A SYSTEMATIC REVIEW

Extracapsular Hip Fractures (EHF's) are a significant health burden on healthcare services. Optimal treatment is controversial with conflicting evidence being reported. Currently treatment is undertaken with Intramedullary Nail (IMN) or Dynamic Hip Screw (DHS) constructs with a recent increase in IMN use (1). This study aims to conduct a systematic review of Randomised Control Trials published between 2020 and 2023 with particular focus on patient demographics and holistic patient outcomes.Using a unified search-protocol, RCT's published between 2020 and 2023 were collected from CENTRAL, PubMed, MEDLINE and EMBASE. Rayyan software screened duplicates. Using the CASP and Cochrane Risk of Bias Tool papers were critically examined twice, and Blood Loss, Infection and Mobility described the patient journey. Patient demographics were recorded and were contrasted with geographically diverse cohort studies to compare population differences. Parametric tests were used to determine significance levels between population demographics, namely Age and Sex.Eleven papers were included, representing 908 patients (436 Male). The mean age for patients was 64.39. There was considerable risk of bias in 7/11 studies owing to the randomization process and the recording of data. Four Cohort studies were selected for comparison representing 14314 patients. Mean age was significantly different between Cohort Studies and RCT's (Independent T-Test, df 13, t=7.8, p = <0.001, mean difference = 19.251, 95% CI = 13.888, 24.613). This was also true for sex ratios included in the studies (df 13, t = -2.268, p = 0.024, Mean Difference = -0.4884, 95% CI = -0.9702, -0.0066).To conclude, RCT's published in the post COVID-19 era are not representative of patient demographics. This has the potential to provide inaccurate information for implant selection. Additionally further research must be conducted in how to better improve RCT patient inclusion so as to be more representative of patients whilst balancing the risks of operations.

Exploring Trust in Pregnancy Care Clinicians Among Latine Patients in Spanish and English: A Qualitative Study [ID 2683628

INTRODUCTION: Trust between patients and clinicians is critical for better experiences and outcomes, yet there is no consensus on how trust is defined and measured in pregnancy care. We aimed to explore how patients define trust in clinicians; facilitators and barriers to building trust; and how trust may be eroded and rebuilt over time. METHODS: A bilingual, multicultural team led this qualitative focus group study. The semistructured discussion guide included definitions of trust based on a literature review, how trust is built, when trust is lost, external factors that influence the patient–clinician relationship, previous pregnancy experiences, and sources of trustworthy information during pregnancy. The discussions were audiorecorded and transcribed in the language in which they were held. We performed thematic content analysis on transcripts using both deductive and inductive approaches in each language. Codes were organized and synthesized according to emerging themes. The IRB approved this study. RESULTS: We held eight focus groups of Hispanic/Latine pregnant and postpartum patients; five were held in Spanish and three in English with a total of 35 participants. We identified five constructs of trust: communication, comfort, caring, competency, and accompaniment (“acompañamiento”). Facilitators of trust were warm interpersonal dynamics, continuity with clinician and care team, rapid direct communication with clinician, and language concordance. Barriers of trust were inadequate or inaccurate information, rotating clinicians, cold interpersonal dynamics, and language discordance. There were few differences between Spanish and English groups. CONCLUSION: Patient perspectives about building trust with clinicians are critical for improving the quality of patient–clinician relationships, especially when language barriers exist.

تصميم وتنفيذ جهاز محمول لقياس كثافة العظام بالموجات فوق الصوتية

هشاشة العظام مرض يتميز بانخفاض كتلة العظام مما يزيد من خطر الإصابة بالكسور. يعتبر مقياس كثافة امتصاص الأشعة السينية ثنائي الطاقة (DXA) بمثابة المعيار الذهبي لقياس كثافة المعادن في العظام (BMD). في سورية، يعد DXA مكلفاً وغير متوفر على نطاق واسع ويقترن بتردد قوي بين المرضى فيما يتعلق بالتعرض للإشعاع المؤين. من ناحية أخرى، وجدت العديد من الدراسات الحديثة أن الموجات فوق الصوتية الكمية (QUS) مفيدة في تحديد تشخيص هشاشة العظام وإعطاء معلومات دقيقة حول صفات العظام. كان الهدف من هذه الدراسة هو تصميم وبناء جهاز قياس كثافة العظام بالموجات فوق الصوتية لقياس كثافة المعادن بالعظام. الجهاز محمول (0.4 كيلو غرام) وهو اقل تكلفة بكثير وليس له اي اثر ضار من الاشعاعات المؤينة. تم تصميم الجهاز باستخدام زوج من أجهزة توليد واستشعار بالموجات فوق الصوتية HC-SR04 لإرسال واستقبال الموجات فوق الصوتية عبر العظم ثم تضخيمها وقراءتها رقمياً باستخدام منصة Arduino. تم تنفيذ الجهاز باستخدام نموذج مُصمم مسبقاً باستخدام برنامج CAD، مع رأس قياس متحرك بحيث يمكن أن يكون مناسباً للعديد من المرضى من مختلف الأعمار. تم اختبار الجهاز على العديد من الأفراد الأصحاء والمرضى من مختلف الجنسين، الذين تتراوح أعمارهم بين 18 و 85 عاماً، كما تمت معايرته والتحقق من صحته باستخدام قيمة كثافة المعادن بالعظام التي يوفرها مقياس كثافة العظام DXA. أظهرت النتائج أن أجهزتنا حساسة بدرجة كافية للتمييز بين الأفراد الأصحاء والمرضى باستخدام أدوات منخفضة التكلفة. وفقًا لذلك، قد يكون للجهاز المقترح فرصة جيدة في المستقبل ليتم اعتباره مقياس كثافة عظام محمول فعال ومنخفض التكلفة.

Modeling the Impact of Misinformation on the Transmission Dynamics of COVID-19

The threat posed by the COVID-19 pandemic has been accompanied by an epidemic of misinformation, causing confusion and mistrust among the public. Misinformation about COVID-19 whether intentional or unintentional takes many forms, including conspiracy theories, false treatments, and inaccurate information about the origins and spread of the virus. Though the pandemic has brought to light the significant impact of misinformation on public health, mathematical modeling emerged as a valuable tool for understanding the spread of COVID-19 and the impact of public health interventions. However, there has been limited research on the mathematical modeling of the spread of misinformation related to COVID-19. In this paper, we present a mathematical model of the spread of misinformation related to COVID-19. The model highlights the challenges posed by misinformation, in that rather than focusing only on the reproduction number that drives new infections, there is an additional threshold parameter that drives the spread of misinformation. The equilibria of the model are analyzed for both local and global stability, and numerical simulations are presented. We also discuss the model’s potential to develop effective strategies for combating misinformation related to COVID-19.

Accuracy and consistency of online large language model-based artificial intelligence chat platforms in answering patients' questions about heart failure

BackgroundHeart failure (HF) is a prevalent condition associated with significant morbidity. Patients may have questions that they feel embarrassed to ask or will face delays awaiting responses from their healthcare providers which may impact their health behavior. We aimed to investigate the potential of large language model (LLM) based artificial intelligence (AI) chat platforms in complementing the delivery of patient-centered care. MethodsUsing online patient forums and physician experience, we created 30 questions related to diagnosis, management and prognosis of HF. The questions were posed to two LLM-based AI chat platforms (OpenAI's ChatGPT-3.5 and Google's Bard). Each set of answers was evaluated by two HF experts, independently and blinded to each other, for accuracy (adequacy of content) and consistency of content. ResultsChatGPT provided mostly appropriate answers (27/30, 90%) and showed a high degree of consistency (93%). Bard provided a similar content in its answers and thus was evaluated only for adequacy (23/30, 77%). The two HF experts' grades were concordant in 83% and 67% of the questions for ChatGPT and Bard, respectively. ConclusionLLM-based AI chat platforms demonstrate potential in improving HF education and empowering patients, however, these platforms currently suffer from issues related to factual errors and difficulty with more contemporary recommendations. This inaccurate information may pose serious and life-threatening implications for patients that should be considered and addressed in future research.

Impact of medical bloggers’ activities on the prevention of disease risk, public, population and individual health: the opinion of social media users

Due to the high information and communication importance and potential of the medical blogosphere in the formation of health literacy of the population, there is the increased need to study the opinions of Russian social media users on the impact of the content of medical blogs on personal and public health. Aim of the study was to find out the opinion of social media users on the extent to which the activities of bloggers specializing in public health and health care topics influence the prevention of major non-communicable and infectious diseases, public and personal health, within the changing boundaries of medical knowledge broadcasting (using sociological methods). Material and methods. The authors conducted a quantitative sociological survey of 178 respondents - users of social media: 55 (30.9 %) women and 123 (69.1 %) men about visiting blogs specializing in public health and healthcare. The collection of information was carried out by e-mailing a questionnaire developed by the authors, and analyzed the answers to questions from active blog users through a Google form in April – May 2023. Results. The study results of the impact of bloggers’ activities on personal and public health, including those related to the quality of medical information disseminated in social media, are described. Respondents believe that medical bloggers have a greater impact on public health than personal health. At the same time, according to the respondents, the spheres of influence in the field of public health do not coincide with the spheres of influence in the field of personal health. Thus, 74.7 % of respondents believe that medical bloggers have an impact on maintaining a healthy lifestyle of the population, prevention (61.8 % of all respondents think so) and treatment of infectious diseases (61.2 %). The requirements for the quality of information provided by bloggers are considered. Based on the analysis of Russian and foreign scientific literature, the authors developed a graphical diagram of the effect of dissemination through the blogosphere of information in the field of health care and disease prevention. Conclusions. The content published on medical blogs affects the health literacy of the population. That is why, medical blogs can be seen as a social determinant of health, because health blogs can be the key to the success of disease prevention and control efforts for public health maintaining. For organizing a communication intervention of medical personnel in social media to inform the population about methods for preventing the risk of developing major non-communicable and infectious diseases and increasing the level of health literacy of the population, medical blogs can and should be used to inform and educate patients as part of general or targeted multimodal educational practices or as a means of delivering electronic content. The risks of publishing inaccurate information in the blogosphere must be considered, whereby patients can easily become misinformed, which can have serious consequences for their health, and even increase their risk of mortality. To make the best use of the blogosphere, it is necessary to solve the problems of content accuracy and increase the level of professionalism of bloggers who write on medical topics. They need to be professionally trained to work for health, contributing to the prevention of the risk of developing major non-communicable and communicable diseases, improving the health of the population through education, and raising the level of health literacy. It makes sense to assess the success of the communicative intervention of doctors in social media and their management of the training of medical bloggers as a personnel determinant of public health, since it will depend on the personnel potential of the healthcare sector.