Source Of Medical Information Research Articles

Canadians’ use of cannabis for therapeutic purposes since legalization of recreational cannabis: a cross-sectional analysis by medical authorization status

BackgroundThere has been a precipitous decline in authorizations for medical cannabis since non-medical cannabis was legalized in Canada in 2018. This study examines the demographic and health- and medical cannabis-related factors associated with authorization as well as the differences in medical cannabis use, side effects, and sources of medical cannabis and information by authorization status.MethodsIndividuals who were taking cannabis for therapeutic purposes completed an online survey in early 2022. Multivariable logistic regression was used to determine odds ratios (OR) and 95% confidence intervals (CI) of demographic and health- and medical cannabis-related variables associated with holding medical cannabis authorization. The differences in medical cannabis use, side effects, and sources of information by authorization status were determined via t-tests and chi-squared analysis.ResultsA total of 5433 individuals who were currently taking cannabis for therapeutic purposes completed the study, of which 2941 (54.1%) currently held medical authorization. Individuals with authorization were more likely to be older (OR ≥ 70 years vs. < 30 years, 4.85 (95% CI, 3.49–6.76)), identify as a man (OR man vs. woman, 1.53 (1.34–1.74)), have a higher income (OR > $100,000/year vs. < $50,000 year, 1.55 (1.30–1.84)), and less likely to live in a small town (OR small town/rural vs. large city, 0.69 (0.59–0.81)). They were significantly more likely to report not experiencing any side effects (29.9% vs. 23.4%; p < 0.001), knowing the amount of cannabis they were taking (32.1% vs. 17.7%; p < 0.001), obtaining cannabis from regulated sources (74.1% vs. 47.5%; p < 0.001), and seeking information about medical cannabis from healthcare professionals (67.8% vs. 48.2%; p < 0.01) than individuals without authorization.ConclusionsThese findings offer insight into the possible issues regarding equitable access to medical cannabis and how authorization may support and influence individuals in a jurisdiction where recreational cannabis is legalized, highlighting the value of a formal medical cannabis authorization process.

128. Understanding TikTok as a Source of Medical Information about Endometriosis

128. Understanding TikTok as a Source of Medical Information about Endometriosis

Evaluation of ChatGPT’s Response to Common Patient Questions for Total Ankle Arthroplasty

Introduction/Purpose: Many patients use the internet as a source for medical information regarding their medical condition. However, the accuracy and reliability of the information is variable. The recent release of general population facing artificial intelligence (AI) chatbot programs has created a potential alternative medical information source for patients. Our study examined the accuracy of the information provided by ChatGPT for total ankle arthroplasty (TAA), as determined by four fellowship-trained foot and ankle orthopedic surgeons. Methods: GPT-4, the latest ChatGPT model, was asked the 12 of the most common questions patients have regarding TAA. Its responses were recorded and evaluated by four fellowship-trained foot and ankle orthopedic surgeons on a scale of 1 – 4, with 1 representing an excellent response not requiring clarification and 4 representing an unsatisfactory response requiring significant clarification. Averages of scores for each question were recorded and an average of every score was used to develop an overall accuracy score. Results: The overall accuracy score of GPT-4 was 1.35. The responses by GPT-4 received a score of 1 for 32 of 48 (66.7%) responses. There was found to be no significant difference in scores for any of GPT-4’s responses. Conclusion: Our study found that GPT-4 performed well in providing accurate and near complete information to commonly questions asked to physicians by patients regarding TAA. Our results suggest that AI models, like GPT-4, may be an effective alternative source of medical information for patients. Further study with subsequent AI models and direct patient interaction may shed further light on the utility of this potential patient education modality. ChatGPT Response Accuracy Score Accuracy scores for ChatGPT, as determined by four foot and ankle fellowship-trained orthopedic surgeons

Dr. Google to Dr. ChatGPT: assessing the content and quality of artificial intelligence-generated medical information on appendicitis.

Generative artificial intelligence (AI) chatbots have recently been posited as potential sources of online medical information for patients making medical decisions. Existing online patient-oriented medical information has repeatedly been shown to be of variable quality and difficult readability. Therefore, we sought to evaluate the content and quality of AI-generated medical information on acute appendicitis. A modified DISCERN assessment tool, comprising 16 distinct criteria each scored on a 5-point Likert scale (score range 16-80), was used to assess AI-generated content. Readability was determined using the Flesch Reading Ease (FRE) and Flesch-Kincaid Grade Level (FKGL) scores. Four popular chatbots, ChatGPT-3.5 and ChatGPT-4, Bard, and Claude-2, were prompted to generate medical information about appendicitis. Three investigators independently scored the generated texts blinded to the identity of the AI platforms. ChatGPT-3.5, ChatGPT-4, Bard, and Claude-2 had overall mean (SD) quality scores of 60.7 (1.2), 62.0 (1.0), 62.3 (1.2), and 51.3 (2.3), respectively, on a scale of 16-80. Inter-rater reliability was 0.81, 0.75, 0.81, and 0.72, respectively, indicating substantial agreement. Claude-2 demonstrated a significantly lower mean quality score compared to ChatGPT-4 (p = 0.001), ChatGPT-3.5 (p = 0.005), and Bard (p = 0.001). Bard was the only AI platform that listed verifiable sources, while Claude-2 provided fabricated sources. All chatbots except for Claude-2 advised readers to consult a physician if experiencing symptoms. Regarding readability, FKGL and FRE scores of ChatGPT-3.5, ChatGPT-4, Bard, and Claude-2 were 14.6 and 23.8, 11.9 and 33.9, 8.6 and 52.8, 11.0 and 36.6, respectively, indicating difficulty readability at a college reading skill level. AI-generated medical information on appendicitis scored favorably upon quality assessment, but most either fabricated sources or did not provide any altogether. Additionally, overall readability far exceeded recommended levels for the public. Generative AI platforms demonstrate measured potential for patient education and engagement about appendicitis.

(033) Artificial Intelligence ChatGPT and GPT4 Performance on Male and Female Sexual Dysfunction, Sexually Transmitted Infection, and Male Factor Infertility in the 2019 to 2023 American Urological Association Self-Assessment Study Programs

Abstract Introduction Large Language Model (LLM) applications in Medicine are increasing. Chatbots ChatGPT and GPT4 were tested against medical exams. The vetting of these tests as a source of information for both the patient and physician is needed. A credible source of medical information may be used as the gold standard against which the LLM can be tested. Objective We assess the performance of ChatGPT and GPT4 to answer the American Urological Association (AUA) Self-Assessment Study Program (SASP) questions on male sexual dysfunction (MSD), female sexual dysfunction (FSD), sexually transmitted infection (STI), and male factor infertility (MFI). We aim to find out how credible this LLM is as a source of medical advice. Methods Four registered users of the SASP identified the questions using open book mode in tests from 2019 to 2023, spanning their subscriptions. The questions were ranked for difficulty on a five-point Likert scale. OpenAI ChatGPT 3.5 and GPT4 were used to answer the questions. The GPT program was set to turn off chat history. No plug-ins or feedback were permitted. Prompts were generated from question stems masking question ID and adding the phrase "I am a urologist preparing for my board exam. Please answer the following question:" Images were deleted from questions and substituted with a brief description. All questions were answered separately, first using GPT-4 and then ChatGPT. Three consecutive responses were generated for each prompt, and the consensus answer was tallied. Answers were compared between GPT and provided answer key of SASP. Descriptive statistics, chi-Pearson Chi-square, and Fisher's exact tests were applied. Results We identified 115 questions in the domains of sexual dysfunction, STI, and MFI. Only one question had an associated image. GPT4 performed better than ChatGPT in all domains, providing correct answers of 60% versus 40% (p=0.000). A total of 89.9% of correct answers were three times unanimously regenerated by GPT4 (p=0.007) and 67.4% by ChatGPT (p=0.244). Within each domain, there was no significant difference in the correct answers for each chatbot (Table-1) or test year (p=0.682). The SASP source reference answers were Campbell's Urology only in 38.3 %, AUA guidelines only in 17.4%, AUA core curriculum only in 10.4%, and combinations with other sources in 33.9%. There was no significant association of source reference with the correct answers of GPT4 (p=0.058) or ChatGPT (p=0.451). Only 19.1% were open-access sources, 20% were partially open-access, and 60.9% were restricted to subscribers. The availability of the source did not significantly affect the correct answers of GPT4 (p=0.272) or ChatGPT (p=0.231). Both chatbots' correct answers were associated significantly with easier questions (Table-2). Conclusions The LLM tested has an average accuracy as a source of credible medical information on Sexual dysfunction, STI, and MFI. GPT4 performs better than ChatGPT, especially when there is a unanimous regenerated response. The development of a better model to serve a broader group of physicians and patients will require training of the chatbot on credible urology literature that includes the currently 81% restricted sources. Disclosure No.

How Does ChatGPT Use Source Information Compared With Google? A Text Network Analysis of Online Health Information.

The lay public is increasingly using ChatGPT (a large language model) as a source of medical information. Traditional search engines such as Google provide several distinct responses to each search query and indicate the source for each response, but ChatGPT provides responses in paragraph form in prose without providing the sources used, which makes it difficult or impossible to ascertain whether those sources are reliable. One practical method to infer the sources used by ChatGPT is text network analysis. By understanding how ChatGPT uses source information in relation to traditional search engines, physicians and physician organizations can better counsel patients on the use of this new tool. (1) In terms of key content words, how similar are ChatGPT and Google Search responses for queries related to topics in orthopaedic surgery? (2) Does the source distribution (academic, governmental, commercial, or form of a scientific manuscript) differ for Google Search responses based on the topic's level of medical consensus, and how is this reflected in the text similarity between ChatGPT and Google Search responses? (3) Do these results vary between different versions of ChatGPT? We evaluated three search queries relating to orthopaedic conditions: "What is the cause of carpal tunnel syndrome?," "What is the cause of tennis elbow?," and "Platelet-rich plasma for thumb arthritis?" These were selected because of their relatively high, medium, and low consensus in the medical evidence, respectively. Each question was posed to ChatGPT version 3.5 and version 4.0 20 times for a total of 120 responses. Text network analysis using term frequency-inverse document frequency (TF-IDF) was used to compare text similarity between responses from ChatGPT and Google Search. In the field of information retrieval, TF-IDF is a weighted statistical measure of the importance of a key word to a document in a collection of documents. Higher TF-IDF scores indicate greater similarity between two sources. TF-IDF scores are most often used to compare and rank the text similarity of documents. Using this type of text network analysis, text similarity between ChatGPT and Google Search can be determined by calculating and summing the TF-IDF for all keywords in a ChatGPT response and comparing it with each Google search result to assess their text similarity to each other. In this way, text similarity can be used to infer relative content similarity. To answer our first question, we characterized the text similarity between ChatGPT and Google Search responses by finding the TF-IDF scores of the ChatGPT response and each of the 20 Google Search results for each question. Using these scores, we could compare the similarity of each ChatGPT response to the Google Search results. To provide a reference point for interpreting TF-IDF values, we generated randomized text samples with the same term distribution as the Google Search results. By comparing ChatGPT TF-IDF to the random text sample, we could assess whether TF-IDF values were statistically significant from TF-IDF values obtained by random chance, and it allowed us to test whether text similarity was an appropriate quantitative statistical measure of relative content similarity. To answer our second question, we classified the Google Search results to better understand sourcing. Google Search provides 20 or more distinct sources of information, but ChatGPT gives only a single prose paragraph in response to each query. So, to answer this question, we used TF-IDF to ascertain whether the ChatGPT response was principally driven by one of four source categories: academic, government, commercial, or material that took the form of a scientific manuscript but was not peer-reviewed or indexed on a government site (such as PubMed). We then compared the TF-IDF similarity between ChatGPT responses and the source category. To answer our third research question, we repeated both analyses and compared the results when using ChatGPT 3.5 versus ChatGPT 4.0. The ChatGPT response was dominated by the top Google Search result. For example, for carpal tunnel syndrome, the top result was an academic website with a mean TF-IDF of 7.2. A similar result was observed for the other search topics. To provide a reference point for interpreting TF-IDF values, a randomly generated sample of text compared with Google Search would have a mean TF-IDF of 2.7 ± 1.9, controlling for text length and keyword distribution. The observed TF-IDF distribution was higher for ChatGPT responses than for random text samples, supporting the claim that keyword text similarity is a measure of relative content similarity. When comparing source distribution, the ChatGPT response was most similar to the most common source category from Google Search. For the subject where there was strong consensus (carpal tunnel syndrome), the ChatGPT response was most similar to high-quality academic sources rather than lower-quality commercial sources (TF-IDF 8.6 versus 2.2). For topics with low consensus, the ChatGPT response paralleled lower-quality commercial websites compared with higher-quality academic websites (TF-IDF 14.6 versus 0.2). ChatGPT 4.0 had higher text similarity to Google Search results than ChatGPT 3.5 (mean increase in TF-IDF similarity of 0.80 to 0.91; p < 0.001). The ChatGPT 4.0 response was still dominated by the top Google Search result and reflected the most common search category for all search topics. ChatGPT responses are similar to individual Google Search results for queries related to orthopaedic surgery, but the distribution of source information can vary substantially based on the relative level of consensus on a topic. For example, for carpal tunnel syndrome, where there is widely accepted medical consensus, ChatGPT responses had higher similarity to academic sources and therefore used those sources more. When fewer academic or government sources are available, especially in our search related to platelet-rich plasma, ChatGPT appears to have relied more heavily on a small number of nonacademic sources. These findings persisted even as ChatGPT was updated from version 3.5 to version 4.0. Physicians should be aware that ChatGPT and Google likely use the same sources for a specific question. The main difference is that ChatGPT can draw upon multiple sources to create one aggregate response, while Google maintains its distinctness by providing multiple results. For topics with a low consensus and therefore a low number of quality sources, there is a much higher chance that ChatGPT will use less-reliable sources, in which case physicians should take the time to educate patients on the topic or provide resources that give more reliable information. Physician organizations should make it clear when the evidence is limited so that ChatGPT can reflect the lack of quality information or evidence.

Perceived experts are prevalent and influential within an antivaccine community on Twitter.

Perceived experts (i.e. medical professionals and biomedical scientists) are trusted sources of medical information who are especially effective at encouraging vaccine uptake. The role of perceived experts acting as potential antivaccine influencers has not been characterized systematically. We describe the prevalence and importance of antivaccine perceived experts by constructing a coengagement network of 7,720 accounts based on a Twitter data set containing over 4.2 million posts from April 2021. The coengagement network primarily broke into two large communities that differed in their stance toward COVID-19 vaccines, and misinformation was predominantly shared by the antivaccine community. Perceived experts had a sizable presence across the coengagement network, including within the antivaccine community where they were 9.8% of individual, English-language users. Perceived experts within the antivaccine community shared low-quality (misinformation) sources at similar rates and academic sources at higher rates compared to perceived nonexperts in that community. Perceived experts occupied important network positions as central antivaccine users and bridges between the antivaccine and provaccine communities. Using propensity score matching, we found that perceived expertise brought an influence boost, as perceived experts were significantly more likely to receive likes and retweets in both the antivaccine and provaccine communities. There was no significant difference in the magnitude of the influence boost for perceived experts between the two communities. Social media platforms, scientific communications, and biomedical organizations may focus on more systemic interventions to reduce the impact of perceived experts in spreading antivaccine misinformation.

YouTube and TikTok as a source of medical information on dissociative identity disorder

BackgroundDissociative Identity Disorder (DID) is a rare condition that causes alternation of at least two separate personality states and has a prevalence of less than 1% in the general population. This study aims to appraise the social media platforms, YouTube and TikTok, as sources of medical information on DID. MethodsYouTube and TikTok were queried using the following search phrases: “Dissociative Identity Disorder,” “Multiple Personality Disorder,” and “Split Personality Disorder.” The top 60 videos by views for YouTube and likes for TikTok were selected from each search term on each platform. Videos were reviewed by four independent reviewers using a modified DISCERN (mDISCERN) Scale, Global Quality Scale (GQS), and they were further classified as useful, misleading, or neither useful or misleading. ResultsNumber of videos that met criteria were 60 YouTube videos and 97 TikTok videos. After classification, 51.7% of YouTube videos were useful while only 5.2% of TikTok videos were useful. A significant difference was found between (mDISCERN and GQS) score and the video source, type of content, and classification (α < 0.05). LimitationsThis study focused exclusively on English videos. Additionally, it did not evaluate other social media platforms that are used worldwide. ConclusionThis results of this study show the need for healthcare professionals and organizations to not only create content of high quality but increase engagement on social media platforms, particularly TikTok, in order to educate users on DID.

Judicious use of the YouTube platform as a complementary source of reliable medical information for physiotherapy students — a paradigm shift in educational methodology during the COVID-19 pandemic.

: Background. The COVID-19 pandemic has imposed a paradigm shift in the pedagogical methodology for a resilient medical educational university system. The epidemiological context has imposed a large-scale closure of universities and disturbed traditional methods of teaching and learning (the direct face-to-face patient-student clinical interactions). Social networks such as the YouTube platform seemed to be a complementary source for medical information, providing a modern, viable e-health strategy for physiotherapy students. Only nine studies addressed rehabilitation in various pathologies, but none of them analyzed the quality of videos focusing on neuraxial rehabilitation. Methods. During the 2021–2022 academic year, six undergraduate license theses focused on the frequently encountered pathology in the Neuromuscular Rehabilitation Clinic of TEHBA: rehabilitation after spinal cord injury, stroke, Parkinson`s disease, and disk hernia. The studies started with the hypothesis that the materials posted on the YouTube platform might have variable-quality content depending on the provider who posted the film. The students were given guidance to search for and select the videos and instructions to use the DISCERN and global quality (GQS) scales and to classify the technical and scientific features of each item using descriptive analysis. These qualitative Likert scales assess several video parameters, including the audio-visual flow, the content's medical knowledge value, and its applicability to physiotherapy students. Given the use of public-domain videos available to the general public and posted in the mass media on the YouTube platform, the approval of the Ethical Council was not necessary. Results. Each movie's scientific content was assessed according to its significance, relevance, and clarity. Videos posted to the YouTube platform by healthcare professionals (including experienced physiotherapists), healthcare institutions, and academic health organizations achieved the highest DISCERN and GQS scores compared to other video sources. Videos posted by vloggers (independent authors or patients) received the lowest reliability and quality scores. Discussion. The article presents a timely and relevant study on integrating digital tools in medical education. Although many YouTube videos with kinesiotherapy and rehabilitation content have offered valuable information, students and younger residents should be aware that the social platform sometimes fails to provide high-quality content. YouTube administrators, vloggers, and publishers should use validity scales (such as DISCERN and GQS) as standard guides for quality self-control and promote reliable, evidence-based medical information. Conclusions. A judicious use of e-health education and social media platforms during the COVID-19 pandemic represented complementary sources of reliable medical information for physiotherapy students.

The System of Pulse Diagnostics of the Body in the Smartphone is A New Source of Medical Information

At present, for high-quality monitoring of the body at home, it is necessary to have many different devices with you and transfer information from them separately to the doctor. It is expensive, burdensome and inefficient. To solve this problem, a new integral patented system of “pulse diagnostics” is proposed, which provides information on a smartphone in the form of graphs of the functional activity of various organs and body systems in the continuous monitoring mode with the possibility of assessing the main biochemical parameters by calculation.

Patient values and preferences regarding communicating risk versus benefit of benzodiazepine initiation: A cross-sectional survey study.

Communicating information about the risks and benefits of benzodiazepines so that it is meaningful to the patient has not been previously described. This study aims to determine patient preferences regarding information received before initiating a benzodiazepine. An online survey was distributed through social media and advertisements to Canadians ≥18 years old over a 6-month period (May-Oct 2022) to collect participant's rating of importance of statements and factors about the risk and benefits of benzodiazepines before initiating treatment using a 10-point Likert-type scale. Treatment preferences based on efficacy and risk information were also elicited. The survey was developed and pilot-tested in collaboration with an advisory committee of individuals with lived and living experience with benzodiazepine use. Thirty-seven participants responded to the survey (mean age 30 years old, 81.1% identified as female). The majority of respondents had a history of anxiety (83.8%) or insomnia (32.4%), and 10 (27.0%) respondents had used a benzodiazepine. Patient counseling related to withdrawal symptoms of benzodiazepines, risk of harm in combination with other sedating agents, risk of physical and psychological dependence, and risk of effects on cognition were rated high in the importance of receiving this information before starting a benzodiazepine relative to efficacy endpoints, such as improvement in sleep parameters. When provided with information about the chance of efficacy and risk of harm, 100% would have selected cognitive behavioral therapy as the best treatment option. The most frequently reported source of medication information where patients have sought information was from the internet (25.0%), followed by doctors (21.9%) and pharmacists (18.8%). This study identified patient important factors and statements viewed as important to communicate before initiating a benzodiazepine. The findings of this survey study will help inform decision-making when considering treatment options for managing anxiety or insomnia.

Perception and attitude of medical sciences students towards the use of online Internet information in Oman

Background: The trend of seeking medical and health information through the Internet has been continuously increasing among youth population specially college students. The aim of this study was to record the perception and attitude of medical sciences students studying in Oman towards the use of medical and health information on the internet. Methods: A cross sectional study which involved medical sciences students studying in four higher education institutions. The questionnaire was composed of 23 close-ended questions grouped into demographic and students’ perception and attitudes towards medical and health information in the internet. Results: The internet was used as source for medical literature and medical information along with other activities in 71.1% of students and PubMed and Google were used as trusted search engines. The majority of students (96.9%) tend to check the accuracy and reliability of internet medical and health information through searching for particular information in two or more websites. 72.1% of the students believe that the internet offers great potential to meet academic needs and promote learning. The statistical analysis showed a significant statistical correlation (p=0.0001) in certain aspects of the perception and attitude of the participating students towards the utilization of medical and health information on the internet. Conclusion: Although majority of students were trained on utilizing medical and health information during their university education, it seems this exposure varies between the four academic majors. Educational institutions in Oman are encouraged to design their e-health literacy program based on the individual requirements of medical sciences curricula.

Insights Into Korean Public Perspectives on Urology: Online News Data Analytics Through Latent Dirichlet Allocation Topic Modeling.

The objective of the study was to explore how urology-related news, one of the medical specialties profoundly linked to human health and life, is communicated to the public through media outlets that serves as primary sources of medical information for the public. In this study, articles were retrieved using the keyword 'Urology' from the Bigkinds spanning from January 1, 1990 to August 17, 2023. The Beautifulsoup library in Python was utilized for parsing the text to collect both titles and bodies of the articles. The gathered data was then analyzed using the latent Dirichlet allocation (LDA) algorithm from the scikit-learn library. Additionally, tools such as Wordcloud and Networkx were employed to visualize the relationships and patterns within the data. The keyword analysis led to the identification of various themes in the articles, with a clear distinction between those providing medical information and those promoting healthcare services, technologies, and products. Notably, the content frequently intertwined informational aspects with promotional ones. Articles on men's health and pet diseases, for example, often combined educational material with product or procedure promotions. This overlap highlights the complexity of categorizing media content into distinct themes. Furthermore, the coverage of health insurance and treatment methods including recent advancements like robotic surgery reflected the evolving nature of healthcare discussions to emphasize the interplay between policy changes, medical advancements, and media portrayal. By identifying 10 distinct topics mentioned in the news, the analysis determined which topics are common in urology-related news coverage. The findings revealed a substantial volume of medical information on urology in the media with a wide range of topics including treatment and prevention of urologic conditions, insurance information, new treatments, and news stories promoting new products or hospitals.

Importance of parental involvement in paediatric palliative care in Hong Kong: qualitative case study

ObjectiveTo compare and contrast the perceived care needs of children with life-limiting conditions (CLLC) from the perspectives of the children, parents and healthcare providers.DesignA qualitative case study method using semistructured...

Evaluation of Oropharyngeal Cancer Information from Revolutionary Artificial Intelligence Chatbot.

With burgeoning popularity of artificial intelligence-based chatbots, oropharyngeal cancer patients now have access to a novel source of medical information. Because chatbot information is not reviewed by experts, we sought to evaluate an artificial intelligence-based chatbot's oropharyngeal cancer-related information for accuracy. Fifteen oropharyngeal cancer-related questions were developed and input into ChatGPT version 3.5. Four physician-graders independently assessed accuracy, comprehensiveness, and similarity to a physician response using 5-point Likert scales. Responses graded lower than three were then critiqued by physician-graders. Critiques were analyzed using inductive thematic analysis. Readability of responses was assessed using Flesch Reading Ease (FRE) and Flesch-Kincaid Reading Grade Level (FKRGL) scales. Average accuracy, comprehensiveness, and similarity to a physician response scores were 3.88 (SD = 0.99), 3.80 (SD = 1.14), and 3.67 (SD = 1.08), respectively. Posttreatment-related questions were most accurate, comprehensive, and similar to a physician response, followed by treatment-related, then diagnosis-related questions. Posttreatment-related questions scored significantly higher than diagnosis-related questions in all three domains (p < 0.01). Two themes of the physician critiques were identified: suboptimal education value and potential to misinform patients. The mean FRE and FKRGL scores both indicated greater than an 11th grade readability level-higher than the 6th grade level recommended for patients. ChatGPT responses may not educate patients to an appropriate degree, could outright misinform them, and read at a more difficult grade level than is recommended for patient material. As oropharyngeal cancer patients represent a vulnerable population facing complex, life-altering diagnoses, and treatments, they should be cautious when consuming chatbot-generated medical information. N/A Laryngoscope, 2023.

Orthodontic patients and the information found on the web: a cross-sectional study.

In recent years, the Web has become a source of medical information for patients, even though the information available online may be incorrect or qualitatively inadequate. Younger generations, immersed in a digital environment since a very tender age, are more likely to get informed online. This study aims to understand the relevance of online information for prospective orthodontic patients and to investigate the effects of digital research on patients' decision-making process, and it also aims to investigate potential generational differences between digital natives and digital immigrants. An anonymous questionnaire was developed to investigate patients' orthodontic-themed Web searches as well as the effects digital material had on their decision-making process. Before submitting the newly designed survey to patients, it was validated in a pilot study. Univariate analysis was applied to analyze the relationship between the demographic characteristics of respondents and their answers on the use of digital research for the decision-making process. 64.6% of the study population searched the Web for orthodontic information prior to their visit. Google was the most used platform regardless of patients' age. The perceived reliability of online sources varied significantly with age. Men displayed more trusting behavior towards their doctor than women. Prospective patients' satisfaction with affected patients' decision-making processes, and the perceived reliability of online sources of information had repercussions on the doctor-patient relationship. Orthodontists should be aware that the majority of patients use the Internet as a source for orthodontic information, and that patients who are digital immigrants are more prone to trust the information found online. Patients who perceive the information found on the Web as either useful or reliable don't easily discard it, even if it is inconsistent with the orthodontist's opinion.

Understanding Tiktok as a Source of Medical Information about Endometriosis

Understanding Tiktok as a Source of Medical Information about Endometriosis

BIRTH INJURY, DUCHENNE-ERBʼS OBSTETRIC PALSY. DIAGNOSIS AND TREATMENT (LITERATURE REVIEW)

Obstetric practice dates back thousands of years, providing assistance to women in labor is often complicated by the rapid course of labor, pelvic presentation of the fetus, shoulder dystocia with a possible clavicle fracture. Damage to CV–CVI roots, classic Duchenne–Erb palsy, accounts for 46 % of the total number of obstetric palsies. Objective. To analyze the scientific and medical literature in order to identify historical scientific and practical information about the study of childbirth injuries, and, in particular, Duchenne–Erb's obstetric palsy. Methods. To study and analyze sources of scientific and medical information, publications from Google search engines, electronic databases PubMed, Google Scholar, archival medical journals. Results. The first data on obstetric paralysis were provided by Duchesne in 1872, highlighting thorough reports on upper extremity muscle damage. Subsequently, in 1874, Erb performed electrical stimulation of the affected muscles, finding out the zone of neurological damage. The history of the development and formation of this scientific issue is quite ambiguous, because it borders on two medical fields: neurosurgery and orthopedics. According to literary sources, it is obvious that the pathohistology and pathophysiology of the direct injury zone (roots CV–CVI), delayed changes in the function of the upper limb, and the latest diagnostic technologies simplify the understanding of the presentation. The existing methods of operative interventions allow physicians to improve the child's life. However, the question remains open regarding the use of certain operative interventions in relation to the child's age and further rehabilitation. Conclusions. Despite a significant stratum of scientific and practical research on Duchenne–Erb's obstetric palsy, there are still a number of questions regarding the diagnosis and treatment of children with this abnormality. The search for improving the functional state of the upper limb in children should continue.

UNICONDYLAR KNEE ARTHROPLASTY — PROS AND CONS (LITERATURE REVIEW)

In the modern world, despite the increased availability of hightech orthopedic care, the number of patients with gonarthrosis does not decrease, and thanks to public awareness, more and more people turn to orthopedists for surgical help. Due to its high efficiency, the leading role in the treatment of terminal gonarthrosis has been firmly occupied by total knee arthroplasty for more than four decades. Unicondylar knee arthroplasty in patients with unilateral arthrosis allows to largely preserve physiological kinematics, to achieve minimal bone and soft tissue traumatization during surgery and, as a result, to obtain a higher functional result. The objective of the work is to analyze the data of the world literature regarding unicondylar knee arthroplasty, its advantages and disadvantages. Material and methods. The authors analyzed the publications devoted to single-condylar knee arthroplasty from the Google search engine, scientific and metric electronic databases PubMed, Medline and other relevant sources of scientific and medical information. Correct patient selection is vital to ensure a successful outcome with OEKS. The main indication for OEKS is deforming arthrosis of the II–III century. with a predominant lesion of the internal part of the knee joint and varus deformation of the lower limb or with a more pronounced pathology of the external part of the knee joint and valgus deformation of the lower limb. Results. The authors analyzed the literature sources on single-condylar endoprosthesis of the knee joint. Indications, contraindications, biomechanical features, type of endoprosthesis fixation, type of endoprosthesis platform, features of lateral gonarthrosis, and complications of single-condylar knee arthroplasty are determined. Conclusions. The analysis of selected literary sources showed that single-condylar arthroplasty of the knee joint is an effective means of preserving the bone. However, careful patient selection and precision of surgical technique remain the key to a successful outcome.

Content Analysis of YouTube Videos on the Effect of Vitamin C on Common Cold.

With the growth of the Internet, social media platforms have emerged as major sources of medical information. We assessed the reliability, quality, and accuracy of the most-viewed YouTube videos containing information on the effect of vitamin C on the common cold. The YouTube videos were searched on August 1, 2022, using the keywords: ("ascorbic acid" OR "vitamin C" OR "Sodium Ascorbate" OR "L-ascorbic") AND "common cold". The 30 most-viewed videos were included in our study. The reliability and quality of the videos were analyzed using modified DISCERN and Global Quality Scales, respectively. When the videos included at least one correct or inaccurate scientific statement about the effect of vitamin C on the common cold, they were classified as accurate or misleading videos, respectively; those without any pertinent information were considered neither accurate nor misleading. If a video contained both accurate and inaccurate statements, it was classified as misleading. Of the 30 most-viewed videos, 73% were unreliable, and 67% contained misleading information and were of a poor quality. Of these 30 videos, 14 videos were produced and posted by customers who were not specialized in medicine or nutrition. Moreover, these videos were of significantly lower reliability, quality, and accuracy than those produced by nutrition or fitness channels or by medical or nutrition professionals. The reliability, quality, and accuracy of videos uploaded by non-professionals were low. Therefore, video creators should upload reliable, high-quality videos to ensure the dissemination of accurate medical information.