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Nutrition is a key determinant of health, and the dissemination of reliable nutrition information to consumers is of great importance for public health. Especially with the rise of digital communication technologies and the wide-spread online misinformation, the provision of qualitative science-based information related to diet is of great importance. The NutritionFacts.org has been established as a prominent online source of evidence-based nutrition information. In this work we aimed to investigate the use of the associated hashtag #NutritionFacts on X (formerly Twitter) over a 5 years period, from 10th of April 2018 to 10th of April 2023. The conducted analysis with the use of Symplur Signals revealed that 18,998 tweets mentioning #NutritionFacts were posted by 6,136 X users, generating a total of 50,348,223 impressions (views). Both institutional and individual accounts were broadly participating in the dissemination of #NutritionFacts tweets, and the user location profiling indicated wide international engagement with the hashtag. This work indicates that #NutritionFacts has been established as an important hashtag utilized on X for the dissemination of evidence-based information related to nutrition.

BackgroundThe digitalization of medicine is becoming a transformative force in modern healthcare systems. This study aims to investigate discussions regarding patient safety, as well as summarize perceived approaches to mitigating risks of adverse events expressed through the #PatientSafety Twitter hashtag during the COVID-19 pandemic.MethodsThis research is grounded in the analysis of data extracted from Twitter under the hashtag #PatientSafety between December 1, 2019 and February 1, 2023. Symplur Signals, which represents a tool offering a method to monitor tweets containing hashtags registered with the Symplur Healthcare Hashtag Project, was used for analyzing the tweets shared in the study period. For text analytics of the relevant data, we further used the word cloud generator MonkeyLearn, and VOSviewer.ResultsThe analysis encompasses 358′809 tweets that were shared by 90′079 Twitter users, generating a total of 1′183’384′757 impressions. Physicians contributed to 18.65% of all tweets, followed by other healthcare professionals (14.31%), and health-focused individuals (10.91%). Geographically, more than a third of tweets (60.90%) were published in the United States. Canada and India followed in second and third positions, respectively. Blocks of trending terms of greater interest to the global Twitter community within the hashtag #PatientSafety were determined to be: “Patient,” “Practical doctors,” and “Health Care Safety Management.” The findings demonstrate the engagement of the Twitter community with COVID-19 and problems related to the training, experience of doctors and patients during a pandemic, communication, the vaccine safety and effectiveness, and potential use of off-label drugs. Noteworthy, in the field of pharmacovigilance, Twitter has the possibility of identifying adverse reactions associated with the use of drugs, including vaccines. The issue of medical errors has been also discussed by Twitter users using the hashtag #PatientSafety.ConclusionIt is clear that various stakeholders, including students, medical practitioners, health organizations, pharmaceutical companies, and regulatory bodies, leverage Twitter to rapidly exchange medical information, data on the disease symptoms, and the drug effects. Consequently, there is a need to further integrate Twitter-derived data into the operational routines of healthcare organizations.

Digital health technologies have been in use for many years in a wide spectrum of healthcare scenarios. This narrative review outlines the current use and the future strategies and significance of digital health technologies in modern healthcare applications. It covers the current state of the scientific field (delineating major strengths, limitations, and applications) and envisions the future impact of relevant emerging key technologies. Furthermore, we attempt to provide recommendations for innovative approaches that would accelerate and benefit the research, translation and utilization of digital health technologies.

The high need for optimal diabetes management among an ever-increasing number of patients dictates the development and implementation of new digital sensors for continuous glucose monitoring. The purpose of this work is to systematize the global patenting trends of digital sensors for continuous glucose monitoring and analyze their effectiveness in controlling the treatment of diabetes patients of different ages and risk groups. The Lens database was used to build the patent landscape of sensors for continuous glucose monitoring. Retrospective analysis showed that the patenting of sensors for continuous glucose monitoring had positive trend over the analyzed period (2000–2022). Leading development companies are Dexcom Inc., Abbott Diabetes Care Inc., Medtronic Minimed Inc., Roche Diabetes Care Inc., Roche Diagnostics Operations Inc., Roche Diabetes Care Gmbh, and Ascensia Diabetes Care Holdings Ag, among others. Since 2006, a new approach has emerged where digital sensors are used for continuous glucose monitoring, and smartphones act as receivers for the data. Additionally, telemedicine communication is employed to facilitate this process. This opens up new opportunities for assessing the glycemic profile (glycemic curve information, quantitative assessment of the duration and amplitude of glucose fluctuations, and so on), which may contribute to improved diabetes management. A number of digital sensors for minimally invasive glucose monitoring are patented, have received FDA approval, and have been on the market for over 10 years. Their effectiveness in the clinic has been proven, and advantages and disadvantages have been clarified. Digital sensors offer a non-invasive option for monitoring blood glucose levels, providing an alternative to traditional invasive methods. This is particularly useful for patients with diabetes who require frequent monitoring, including before and after meals, during and after exercise, and in other scenarios where glucose levels can fluctuate. However, non-invasive glucose measurements can also benefit patients without diabetes, such as those following a dietary treatment plan, pregnant women, and individuals during fasting periods like Ramadan. The availability of non-invasive monitoring is especially valuable for patients in high-risk groups and across different age ranges. New world trends have been identified in the patenting of digital sensors for non-invasive glucose monitoring in interstitial skin fluid, saliva, sweat, tear fluid, and exhaled air. A number of non-invasive devices have received the CE mark approval, which confirms that the items meet European health, safety, and environmental protection standards (TensorTip Combo-Glucometer, Cnoga Medical Ltd.; SugarBEAT, Nemaura Medical; GlucoTrack, GlucoTrack Inc.), but are not FDA-approved yet. The above-mentioned sensors have characteristics that make them popular in the treatment of diabetes: they do not require implantation, do not cause an organism reaction to a foreign body, and are convenient to use. In the EU, in order to increase clinical safety and the level of transparency about medical devices, manufacturers must obtain certificates in accordance with Regulation (EU) 2017/745, taking into account the transition period. The development of systems, which include digital sensors for continuous glucose monitoring, mobile applications, and web platforms for professional analysis of glycemic control and implementation of unified glycemic assessment principles in mobile healthcare, represent promising approaches for controlling glycaemia in patients.

Google Trends data have been used to investigate various themes on online information seeking. It was unclear if the population from different parts of the world shared the same amount of attention to different mask types during the COVID-19 pandemic. This study aimed to reveal which types of masks were frequently searched by the public in different countries, and evaluated if public attention to masks could be related to mandatory policy, stringency of the policy, and transmission rate of COVID-19. By referring to an open dataset hosted at the online database Our World in Data, the 10 countries with the highest total number of COVID-19 cases as of 9th of February 2022 were identified. For each of these countries, the weekly new cases per million population, reproduction rate (of COVID-19), stringency index, and face covering policy score were computed from the raw daily data. Google Trends were queried to extract the relative search volume (RSV) for different types of masks from each of these countries. Results found that Google searches for N95 masks were predominant in India, whereas surgical masks were predominant in Russia, FFP2 masks were predominant in Spain, and cloth masks were predominant in both France and United Kingdom. The United States, Brazil, Germany, and Turkey had two predominant types of mask. The online searching behavior for masks markedly varied across countries. For most of the surveyed countries, the online searching for masks peaked during the first wave of COVID-19 pandemic before the government implemented mandatory mask wearing. The search for masks positively correlated with the government response stringency index but not with the COVID-19 reproduction rate or the new cases per million.

IntroductionMultiple studies have shown how valuable Twitter hashtags can be for promoting content related to different themes in the online community. This arena has grown into a rich data source for public health observation and understanding key trends in healthcare on a global scale. In the field of mental health in particular, it would be of benefit to understand and report the key stakeholders' (individual mental health professionals, academic organizations and their countries) trends and patterns of psychiatric knowledge and information dissemination using #PsychTwitter.ObjectiveIn this study, we aim to evaluate the achieved outreach of psychiatry-related tweets using the hashtag #PsychTwitter.MethodsWe utilized the Symplur Signals research analytics tool to characterize tweets containing #PsychTwitter from the 20th of August, 2019, to the 20th of August, 2022.ResultsThe #PsychTwitter movement resulted in 125,297 tweets that were shared by 40,058 Twitter users and generated a total of 492,565,230 impressions (views). The three largest identified groups of contributors were Doctors (13.8% of all tweets), Org. Advocacy (6.2% of all tweets), and Researcher/Academic (4% of all tweets) stakeholders. The top influential accounts consisted of 55 psychiatrists and 16 institutional or organizational accounts. The top 5 countries from where most of the tweets containing #PsychTwitter were shared include the United States (54.3% of all users), the United Kingdom (10.4% of all users), Canada (4.9% of all users), India (2% of all users), and Australia (1.8% of all users).ConclusionThis is the first of its kind study featuring the influence and usage of #PsychTwitter and covering its global impact in the field of psychiatry using the Twitter platform. Our results indicate that Twitter represents a broadly used platform for mental health-related discussions.

BackgroundHospitals are institutions whose primary task is to treat patients. Family-centered care, which considers loved ones as equal partners in patient care, has been gaining recognition in the adult care setting. Our aim was to record experiences of and opinions on communication between hospital-based healthcare providers and patients' loved ones, related but not limited to the rigorous mitigation measures implemented during the COVID-19 pandemic.MethodsThe Twitter profile @HospitalsTalkTo and hashtag #HospitalsTalkToLovedOnes were created to interact with the Twitter public between 7 June 2021 and 7 February 2022. Conversations surrounding #HospitalsTalkToLovedOnes were extracted and subjected to natural language processing analysis using term frequency and Markov chain analysis. Qualitative thematic analysis was performed on the 10% most interacted tweets and of tweets mentioning “COVID” from a personal experience-based subset.ResultsWe collected 4412 unique tweets made or interacted by 7040 Twitter users from 142 different countries. The most frequent words were patient, hospital, care, family, loved and communication. Thematic analysis revealed the importance of communication between patients, patients' loved ones and hospitals; showed that patients and their loved ones need support during a patient's hospital journey; and that pediatric care should be the gold standard for adult care. Visitation restrictions due to COVID-19 are just one barrier to communication, others are a lack of phone signal, no space or time for asking questions, and a complex medical system. We formulate 3 recommendations to improve the inclusion of loved ones into the patient's hospital stay.Conclusions“Loved ones are not ‘visitors' in a patient's life”. Irrespective of COVID-19, patient's loved ones need to be included during the patient's hospital journey. Transparent communication and patient empowerment increase patient safety and improve the hospital experience for both the patients and their loved ones. Our findings underline the need for the concept of family-centered care to finally be implemented in adult nursing clinical practice.

BackgroundArtificial intelligence (AI) has the potential to reshape medical practice and the delivery of healthcare. Online discussions surrounding AI's utility in these domains are increasingly emerging, likely due to considerable interest from healthcare practitioners, medical technology developers, and other relevant stakeholders. However, many practitioners and medical students report limited understanding and familiarity with AI.ObjectiveTo promote research, events, and resources at the intersection of AI and medicine for the online medical community, we created a Twitter-based campaign using the hashtag #MedTwitterAI.MethodsIn the present study, we analyze the use of #MedTwitterAI by tracking tweets containing this hashtag posted from 26th March, 2019 to 26th March, 2021, using the Symplur Signals hashtag analytics tool. The full text of all #MedTwitterAI tweets was also extracted and subjected to a natural language processing analysis.ResultsOver this time period, we identified 7,441 tweets containing #MedTwitterAI, posted by 1,519 unique Twitter users which generated 59,455,569 impressions. The most common identifiable locations for users including this hashtag in tweets were the United States (378/1,519), the United Kingdom (80/1,519), Canada (65/1,519), India (46/1,519), Spain (29/1,519), France (24/1,519), Italy (16/1,519), Australia (16/1,519), Germany (16/1,519), and Brazil (15/1,519). Tweets were frequently enhanced with links (80.2%), mentions of other accounts (93.9%), and photos (56.6%). The five most abundant single words were AI (artificial intelligence), patients, medicine, data, and learning. Sentiment analysis revealed an overall majority of positive single word sentiments (e.g., intelligence, improve) with 230 positive and 172 negative sentiments with a total of 658 and 342 mentions of all positive and negative sentiments, respectively. Most frequently mentioned negative sentiments were cancer, risk, and bias. Most common bigrams identified by Markov chain depiction were related to analytical methods (e.g., label-free detection) and medical conditions/biological processes (e.g., rare circulating tumor cells).ConclusionThese results demonstrate the generated considerable interest of using #MedTwitterAI for promoting relevant content and engaging a broad and geographically diverse audience. The use of hashtags in Twitter-based campaigns can be an effective tool to raise awareness of interdisciplinary fields and enable knowledge-sharing on a global scale.

Background: Twitter, representing a big social media network, is broadly used for the communication of health-related information. In this work, we aimed to identify and analyze the scientific literature on Twitter use in context of health by utilizing a bibliometric approach, in order to obtain quantitative information on dominant research topics, trending themes, key publications, scientific institutions, and prolific researchers who contributed to this scientific area.Methods: Web of Science electronic database was searched to identify relevant papers on Twitter and health. Basic bibliographic data was obtained utilizing the “Analyze” function of the database. Full records and cited references were exported to VOSviewer, a dedicated bibliometric software, for further analysis. A term map and a keyword map were synthesized to visualize recurring words within titles, abstracts and keywords.Results: The analysis was based on the data from 2,582 papers. The first papers were published in 2009, and the publication count increased rapidly since 2015. Original articles and reviews were published in a ratio of 10.6:1. The Journal of Medical Internet Research was the top journal, and the United States had contributions to over half (52%) of these publications, being the home-country of eight of the top ten most productive institutions. Keyword analysis identified six topically defined clusters, with professional education in healthcare being the top theme cluster (consisting of 66 keywords). The identified papers often investigated Twitter together with other social media, such as YouTube and Facebook.Conclusions: A great diversity of themes was found in the identified papers, including: professional education in healthcare, big data and sentiment analysis, social marketing and substance use, physical and emotional well-being of young adults, and public health and health communication. Our quantitative analysis outlines Twitter as both, an increasingly popular data source, and a highly versatile tool for health-related research.

Objective: Medical errors represent a leading cause of patient morbidity and mortality. The aim of this study was to quantitatively analyze the existing scientific literature on medical errors in order to gain new insights in this important medical research area.Study Design: Web of Science database was used to identify relevant publications, and bibliometric analysis was performed to quantitatively analyze the identified articles for prevailing research themes, contributing journals, institutions, countries, authors, and citation performance.Results: In total, 12,415 publications concerning medical errors were identified and quantitatively analyzed. The overall ratio of original research articles to reviews was 8.1:1, and temporal subset analysis revealed that the share of original research articles has been increasing over time. The United States contributed to nearly half (46.4%) of the total publications, and 8 of the top 10 most productive institutions were from the United States, with the remaining 2 located in Canada and the United Kingdom. Prevailing (frequently mentioned) and highly impactful (frequently cited) themes were errors related to drugs/medications, applications related to medicinal information technology, errors related to critical/intensive care units, to children, and mental conditions associated with medical errors (burnout, depression).Conclusions: The high prevalence of medical errors revealed from the existing literature indicates the high importance of future work invested in preventive approaches. Digital health technology applications are perceived to be of great promise to counteract medical errors, and further effort should be focused to study their optimal implementation in all medical areas, with special emphasis on critical areas such as intensive care and pediatric units.