Health-related Content Research Articles

Sexual health communication targeting adolescents in public service Media: the case of Finland

Abstract Background Given the substantial time adolescents spend online, sexual health promotion and education through online media constitute a promising public health action. However, monitoring of sexual health-related online media content is warranted, and considering the scope and aims of public service media, this forum can be regarded as being of particular interest. This study aimed to analyze how and to what extent sexuality and sexual health-related content targeting adolescents is communicated and portrayed in public service media in Finland, with a particular interest in health promotion perspectives and participatory practices. Methods Based on predetermined inclusion criteria and guidance from professionals at the Finnish public service company Yle, podcasts were specified as the media format of interest. Three Finnish podcasts (a total of 66 episodes) produced during the years 2021-2023, targeting young people and focusing on sexual health, were included in this study and subject to critical content analysis. Results Most podcast episodes focused equally on the sexual health resource and risk perspectives, while a third emphasized a resource perspective. Concerning participatory practices, adolescents participate in only five episodes in total, and most often, the podcast hosts’ own experiences are at the center of the episodes. Conclusions The findings highlight how sexuality and sexual health content is communicated in public service media podcasts targeting adolescents in Finland, as well as how the communication aligns with health education and promotion guidelines. The study sheds light on participatory practices, emphasizing a lack of stakeholder involvement, i.e., dialogue between podcast hosts and listeners. Results carry implications for developing sexual health promotion through public service media targeting young people in Finland and other European countries alike. Key messages • The findings highlight how sexuality and sexual health content is portrayed in public service media podcasts in Finland and how the communication aligns with health promotion values and principles. • The findings show a lack of participatory practices in Finnish public service media podcasts targeting adolescent sexual health - a health promotion concern also pertinent to other countries.

Integrating health in urban planning curriculum across Indian planning institutes

Urban planning significantly influences the physical and health profile of urban environments. This paper explores the critical nexus between urban planning and public health, emphasizing the urgent need to integrate health considerations into the urban planning curriculum in India. Current urban planning courses often overlook public health aspects, resulting in a disconnect that could hinder the ability of urban environments to meet the health and well-being needs of their populations. Through a comprehensive review and analysis of curriculum data from selected Indian institutions of national importance—including the School of Planning and Architecture, Indian Institute of Technology Kharagpur, and National Institute of Technology, Bhopal—this study identifies significant gaps in the inclusion of health-related content in urban planning education. The analysis reveals a low occurrence of health-related themes within the planning curriculum, with essential topics like public health history, environmental health, and health impact assessments seldom addressed. To bridge these gaps, the paper suggests incorporating mandatory health-focused courses, such as Health Impact Assessments and public health fundamentals, into the curriculum. It also recommends interdisciplinary collaboration with public health professionals to enrich planning education. By restructuring the curriculum to include more comprehensive health-related education, future urban planners can be better equipped to create healthier and more sustainable urban environments, ultimately enhancing public health outcomes in rapidly urbanizing spaces. This research not only sheds light on current educational inadequacies but also proposes actionable steps towards a more holistic integration of health and urban planning disciplines.

A systematic review upon the online content provided for self-management of diabetes

Background: Diabetes is a major illness that requires appropriate education in order to increase one's understanding of self-management. With the advancement of the internet, the proliferation of online health-related content in supporting the management of chronic illness like diabetes has been ongoing; however, little is understood on the sort of acceptable and/or effective information attainable online. Objective: The aim of this review is to evaluate the current literature in hindsight of online management in diabetes whilst establishing the effectiveness of online management tools, the quality of the online information, and the methods of obtaining online information. Methods: A series of systematic searches of online databases were conducted in accordance with strictly defined inclusion and exclusion criteria relevant to the research question. Additionally, an evidence-based literature (EBL) checklist tool was used to assess the methodological and reporting quality of each study. Each article was peer-reviewed and screened for any biases. Results: A result of 11 electronic searches were critically appraised using the EBL appraisal checklist tool and all were found to have overall validity. The results indicate an increase use of online technology to empower an understanding of one's own health. Web-based tools like social media were useful in promoting the management of diabetes but were not able to provide quality information. Conclusion: Current research indicates the need for more investigation and future development of readily accessible and qualitative information in order to support the self-management of diabetes.

Trusting the tube? YouTube®’s role in pacemaker patient and physician education

ObjectiveYouTube®, attracts billions of monthly viewers, including those seeking health-related content. However, the quality standards of information are highly variable. The study aimed to evaluate the educational merit of YouTube® concerning pacemakers, focusing on quality and reliability for educating both patients and physicians. MethodsThe term “pacemaker” was searched on YouTube®. Following the application of exclusion criteria based on video language, duration, and minimum view count, a total of 71 videos were analyzed. Quality was assessed using the Global Quality Score (GQS), while reliability was evaluated using the modified DISCERN (mDISCERN) score. Data and metrics available regarding the channel and the specific video were obtained. The Kolmogorov–Smirnov test was employed to assess data normality, and the Mann-Whitney U test was utilized to determine statistical significance. ResultsYoutube videos on cardiac pacemakers proved to be of moderate quality, with an average GQS score of 3.10, and of moderate reliability, indicated by a mean mDISCERN score of 3.08. Higher scores were reported for videos of more than five minute duration, the ones that were targeted at physicians, and the videos with higher view ratios. The presence of a board-certified MD yielded statistically greater mean GQS, but not mDISCERN score. No statistical difference was observed based on the number of likes. ConclusionIn conclusion, while YouTube® offers significant education opportunities, there is a clear need for enhanced oversight and quality control. Healthcare providers should guide patients towards valid resources and consider collaborating with platforms to develop content standards.

Machine learning and natural language processing to assess the emotional impact of influencers' mental health content on Instagram.

This study aims to examine, through artificial intelligence, specifically machine learning, the emotional impact generated by disclosures about mental health on social media. In contrast to previous research, which primarily focused on identifying psychopathologies, our study investigates the emotional response to mental health-related content on Instagram, particularly content created by influencers/celebrities. This platform, especially favored by the youth, is the stage where these influencers exert significant social impact, and where their analysis holds strong relevance. Analyzing mental health with machine learning techniques on Instagram is unprecedented, as all existing research has primarily focused on Twitter. This research involves creating a new corpus labelled with responses to mental health posts made by influencers/celebrities on Instagram, categorized by emotions such as love/admiration, anger/contempt/mockery, gratitude, identification/empathy, and sadness. The study is complemented by modelling a set of machine learning algorithms to efficiently detect the emotions arising when faced with these mental health disclosures on Instagram, using the previous corpus. Results have shown that machine learning algorithms can effectively detect such emotional responses. Traditional techniques, such as Random Forest, showed decent performance with low computational loads (around 50%), while deep learning and Bidirectional Encoder Representation from Transformers (BERT) algorithms achieved very good results. In particular, the BERT models reached accuracy levels between 86-90%, and the deep learning model achieved 72% accuracy. These results are satisfactory, considering that predicting emotions, especially in social networks, is challenging due to factors such as the subjectivity of emotion interpretation, the variability of emotions between individuals, and the interpretation of emotions in different cultures and communities. This cross-cutting research between mental health and artificial intelligence allows us to understand the emotional impact generated by mental health content on social networks, especially content generated by influential celebrities among young people. The application of machine learning allows us to understand the emotional reactions of society to messages related to mental health, which is highly innovative and socially relevant given the importance of the phenomenon in societies. In fact, the proposed algorithms' high accuracy (86-90%) in social contexts like mental health, where detecting negative emotions is crucial, presents a promising research avenue. Achieving such levels of accuracy is highly valuable due to the significant implications of false positives or false negatives in this social context.

How influencers motivate inactive adolescents to be more physically active: a mixed methods study.

Regular physical activity offers numerous health benefits, particularly for adolescents. However, only 14% of school-aged children in Switzerland achieve the World Health Organization's recommendation of 60 min of moderate to vigorous physical activity per day. Changing health behaviors is a complex process in which understanding behavioral and communication patterns is crucial. Because adolescents spend substantial time on social media channels and obtain information from them, these are potential channels for accessing health-related content. This study explores the questions of which influencers and what content motivate adolescents to be more physically active and whether influencers can impact enjoyment and the intention to engage in physical activity. The study employed a convergent mixed methods approach, combining self-assessment questionnaires and semi-structured interviews. Ninety-three adolescents aged 14-20 years who exercised < 1 h per day participated. They followed one of the six participating influencers on Instagram. Over 6 weeks, the questionnaires collected quantitative data, measuring enjoyment, stages of change, and physical activity levels. Furthermore, semi-structured interviews were conducted with 23 adolescents and six influencers to gain in-depth insights. The quantitative findings indicate that adolescent followers enjoyed physical activity more after the social media intervention and at follow-up than at the beginning of the study. The followers' stages of change progressed over time. Compared with those following more athletic influencers, followers of nonathletic influencers (that is, a singer, a journalist, and an eFootballer) showed increased physical activity over time. Qualitative analysis highlighted Instagram factors influencing physical activity, including resonance with influencers' lifestyles and preference for simple, relatable activities. Authentic content was positively associated with increased exercise, particularly among already motivated followers. Unexpectedly, nonathletic influencers, such as a singer, a journalist, and an eFootballer, motivated adolescents best despite their nontraditional focus on physical activity. Their success stems from relatable lifestyles and simple activities that are easily incorporated into their daily routines. Conversely, athletic influencers demonstrated challenging exercises that were fascinating but difficult to adopt. This finding suggests the potential for utilizing nonathletic influencers in future campaigns targeting inactive adolescents.

The Role of Health Belief Model Constructs and Content Creator Characteristics in Social Media Engagement: Insights from COVID-19 Vaccine Tweets.

The Health Belief Model (HBM) has been widely studied, but it is unclear how social media post creators use HBM constructs to influence the public's awareness of health topics, particularly for COVID-19 preventative health behaviors. Moreover, there is limited knowledge about how content creators enhance user engagement with COVID-19 vaccine tweets. A content analysis of COVID-19 vaccine tweets (n = 362) examined how HBM constructs were used in social media posts and their relationship to content creator characteristics (e.g., race, education level) and user engagement behaviors (e.g., number of favorites). Content creators' tweets about COVID-19-related topics generally centered on two HBM constructs-benefits and barriers-while fewer tweets emphasized perceived susceptibility or self-efficacy; tweets containing these constructs were retweeted less often. Findings revealed that tweets from politicians, health experts, and white and Asian sources emphasized the perceived benefits of the COVID-19 vaccine. Individual tweets, especially from Black individuals and celebrities, generated more user engagement. Understanding the factors that contribute to social media user engagement with health-related content is important for designing more focused and impactful health communication campaigns and promoting healthier habits and perspectives. Thus, by demonstrating the possible relevance of the HBM to digital communication strategies or health campaigns, our study provides useful guidance for health promoters and policymakers who use social media to raise public health awareness.

“Examining The Gratification Of Women From Health Communication On Social Media By Women”

In the digital age, social media has emerged as a crucial platform for health communication; significantly influencing how health information is disseminated and consumed. This study examines the gratification that women experience from health communication on social media. In the contemporary digital landscape, social media has become an essential platform for health communication, particularly for women. This medium provides a valuable space for sharing health information, fostering community support, and promoting wellbeing. Health communication on social media has the potential to significantly influence women’s health behaviors, attitudes, and knowledge. This study aims to examine the gratification of women from health communication on social media, focusing on main objectives like studying the socio-demographics characteristics of the women, identifying their usage patterns of social media, to investigate the gratification derived by women from engaging with health related content on social media. As well as to identify the types of health information that is most influential and trusted by women on social media platforms. For this study, the descriptive research design was adopted, and the primary data of 130 respondents were selected randomly for the collection of primary data through a structured questionnaire

Large Language Models Can Enable Inductive Thematic Analysis of a Social Media Corpus in a Single Prompt: Human Validation Study.

Manually analyzing public health-related content from social media provides valuable insights into the beliefs, attitudes, and behaviors of individuals, shedding light on trends and patterns that can inform public understanding, policy decisions, targeted interventions, and communication strategies. Unfortunately, the time and effort needed from well-trained human subject matter experts makes extensive manual social media listening unfeasible. Generative large language models (LLMs) can potentially summarize and interpret large amounts of text, but it is unclear to what extent LLMs can glean subtle health-related meanings in large sets of social media posts and reasonably report health-related themes. We aimed to assess the feasibility of using LLMs for topic model selection or inductive thematic analysis of large contents of social media posts by attempting to answer the following question: Can LLMs conduct topic model selection and inductive thematic analysis as effectively as humans did in a prior manual study, or at least reasonably, as judged by subject matter experts? We asked the same research question and used the same set of social media content for both the LLM selection of relevant topics and the LLM analysis of themes as was conducted manually in a published study about vaccine rhetoric. We used the results from that study as background for this LLM experiment by comparing the results from the prior manual human analyses with the analyses from 3 LLMs: GPT4-32K, Claude-instant-100K, and Claude-2-100K. We also assessed if multiple LLMs had equivalent ability and assessed the consistency of repeated analysis from each LLM. The LLMs generally gave high rankings to the topics chosen previously by humans as most relevant. We reject a null hypothesis (P<.001, overall comparison) and conclude that these LLMs are more likely to include the human-rated top 5 content areas in their top rankings than would occur by chance. Regarding theme identification, LLMs identified several themes similar to those identified by humans, with very low hallucination rates. Variability occurred between LLMs and between test runs of an individual LLM. Despite not consistently matching the human-generated themes, subject matter experts found themes generated by the LLMs were still reasonable and relevant. LLMs can effectively and efficiently process large social media-based health-related data sets. LLMs can extract themes from such data that human subject matter experts deem reasonable. However, we were unable to show that the LLMs we tested can replicate the depth of analysis from human subject matter experts by consistently extracting the same themes from the same data. There is vast potential, once better validated, for automated LLM-based real-time social listening for common and rare health conditions, informing public health understanding of the public's interests and concerns and determining the public's ideas to address them.

Self-disclosure in online social networks: An empirical study of location-based check-ins and impression management

Leveraging online networks like Twitter and Foursquare, our study explores the dynamics of self-disclosure and impression management through location sharing. Grounded in social and hyperpersonal information processing theories, we investigate how peer influence, geographical proximity, and exposure to promotional content impact self-disclosure behaviors. Through an integrated dataset, we determine that friends’ check-ins and their physical proximities significantly sway individual self-disclosure. Particularly, in the presence of health-conscious peers, users tend to avoid check-ins that create a negative health impression. Furthermore, exposure to health-related promotional content significantly influences these behaviors. Our findings provide crucial perspectives on impression management in the digital age.

Relating caregiver experiences to personalized "push" content in mobile applications among caregivers of pediatric patients with oncology conditions.

With the evolution of data algorithms and personalized push systems in mobile applications, patients who have searched for disease-related information may repeatedly receive similar content on app homepages or through notifications. This study aims to assess the influence of health-related content delivered through mobile applications on the anxiety and depression levels of caregivers of pediatric oncology patients. A survey consisting of 16 questions was conducted among 91 caregivers of pediatric oncology patients at the Children's Hospital affiliated with Chongqing Medical University. The questionnaire was designed by oncologists and the Hospital Anxiety and Depression Scale was used to assess the caregivers' psychological states. The study found that 31.5% of caregivers exhibited borderline anxiety symptoms, while 20.2% displayed borderline depression symptoms. Caregivers who noticed changes in homepage recommendations reported higher levels of anxiety (p=.004) and depression (p=.034). Additionally, 50.6% occasionally felt anxious or uneasy due to personalized notifications and 19.1% frequently felt this way. Moreover, 53.9% of the caregivers reported a negative impact on their emotions or daily life. Personalized push notifications related to disease information in mobile applications can impose a significant psychological burden on patients and their caregivers. Mobile application developers and healthcare providers must strengthen their support in the digital health domain to enhance the emotional well-being of cancer patients and their caregivers.

Social Media Authentication and Users' Assessments of Health Information: Random Assignment Survey Experiment.

In an effort to signal the authenticity of user accounts, social networking sites (SNSs) such as Facebook and X, formerly known as Twitter, use visual heuristics (blue checkmarks) to signify whether accounts are verified. While these verification badges are generally well recognized (and often coveted) by SNS users, relatively little is known about how they affect users' perceptions of accuracy or their likelihood of engaging with web-based information. This is particularly true in the case of information posted by medical experts and health care professionals. This study aims to use an experimental survey design to assess the effect of these verification badges on SNS users' assessments of information accuracy as well as their proclivity to recirculate health information or follow verified medical experts in their social network. A survey experiment using random assignment was conducted on a representative sample of 534 adult SNS users in Florida, United States. A total of 2 separate experimental scenarios exposed users to vaccine-related posts from verified medical experts on X. In each case, the original post contained a platform-issued verification badge (treatment group), which was subsequently edited out of the image as an experimental control. For each scenario, respondents were randomly assigned to either the treatment or control group, and responses to 3 follow-up questions were assessed through a series of chi-square analyses and 2 logit regression models. Responses were fielded using a stratified quota sampling approach to ensure representativeness of the state's population based on age, sex, race, ethnicity, and political affiliation. Users' assessments of information accuracy were not significantly impacted by the presence or absence of verification badges, and users exposed to the experimental treatment (verification badge) were not any more likely to repost the message or follow the author. While verification badges did not influence users' assessments or subsequent behaviors, reliance on social media for health-related information and political affiliation were substantial predictors of accuracy assessments in both experimental scenarios. In scenario 1, which included a post addressing COVID-19 vaccine efficacy, users who relied on social media "a great deal" for health information were 2 times more likely to assess the post as accurate (odds ratio 2.033, 95% CI 1.129-3.661; P=.01). In scenario 2, which included a post about measles vaccines, registered Republicans were nearly 6 times less likely to assess the post as accurate (odds ratio 0.171, 95% CI 0.097-0.299; P<.001). For health professionals and medical experts wishing to leverage social networks to combat misinformation and spread reliable health-related content, account verification appears to offer little by way of added value. On the basis of prior research, other heuristics and communication strategies are likely to yield better results.

Assessing ChatGPT Ability to Answer Frequently Asked Questions About Essential Tremor.

Large-language models (LLMs) driven by artificial intelligence allow people to engage in direct conversations about their health. The accuracy and readability of the answers provided by ChatGPT, the most famous LLM, about Essential Tremor (ET), one of the commonest movement disorders, have not yet been evaluated. Answers given by ChatGPT to 10 questions about ET were evaluated by 5 professionals and 15 laypeople with a score ranging from 1 (poor) to 5 (excellent) in terms of clarity, relevance, accuracy (only for professionals), comprehensiveness, and overall value of the response. We further calculated the readability of the answers. ChatGPT answers received relatively positive evaluations, with median scores ranging between 4 and 5, by both groups and independently from the type of question. However, there was only moderate agreement between raters, especially in the group of professionals. Moreover, readability levels were poor for all examined answers. ChatGPT provided relatively accurate and relevant answers, with some variability as judged by the group of professionals suggesting that the degree of literacy about ET has influenced the ratings and, indirectly, that the quality of information provided in clinical practice is also variable. Moreover, the readability of the answer provided by ChatGPT was found to be poor. LLMs will likely play a significant role in the future; therefore, health-related content generated by these tools should be monitored.

Psychische Gesundheit am Arbeitsplatz – Welche Rolle spielen sozioökonomische, geschlechterspezifische und migrationsbedingte Ungleichheiten?

ZusammenfassungHintergrundRisikofaktoren für die psychische Gesundheit sind häufig in sozioökonomischen, geschlechter- und migrationsspezifischen Ungleichheiten begründet. Diese sowie die Ausprägung der Depressivität, Ängstlichkeit und Somatisierung von Beschäftigten wurden in der vorliegenden Studie untersucht.MethodenIm Rahmen der friaa-Studie („Frühe Intervention am Arbeitsplatz“) wurden psychisch belastete Beschäftigte an 5 Standorten in Deutschland zu soziodemografischen, arbeits-, migrations- und gesundheitsbezogenen Inhalten befragt. Mittels Regressionsanalysen wurde der Zusammenhang dieser Faktoren mit Depressivität (Patient-Health-Questionnaire-9, PHQ-9), Ängstlichkeit (Generalized Anxiety Disorder-2, GAD-2) und Somatisierung (Somatic Symptom Scale-8, SSS-8) an der gesamten Stichprobe sowie bei Personen mit Migrationshintergrund (MH) untersucht. Bei Letzteren wurden zusätzlich die Akkulturation (Frankfurter Akkulturationsskala, FRAKK) und das Belastungsempfinden gegenüber Migrationsanforderungen (Demands of Immigration Scale, DIS) berücksichtigt.ErgebnisseDie 550 Beschäftigten (12 % mit MH) wiesen im Durchschnitt eine klinisch relevante Depressivität (M = 13,0, SD = 5,1) (PHQ-9 ≥ 10), Ängstlichkeit (M = 3,5, SD = 1,7) (GAD ≥ 3) sowie Somatisierung (M = 13,0, SD = 5,8) (SSS-8 ≥ 12) auf. Das weibliche Geschlecht war mit höheren Werten für Ängstlichkeit und Somatisierung assoziiert. Höheres Alter und Nachtschichtarbeit hingen mit stärkerer Somatisierung zusammen.DiskussionDie Ergebnisse bestätigen die hohe psychische Belastung der Beschäftigten in dieser Stichprobe aus Deutschland. Um deren psychische Gesundheit aufrechtzuerhalten, sollten Unterstützungsmaßnahmen insbesondere für vulnerable Gruppen wie Frauen, ältere Beschäftigte und Nachtschichtarbeitende angeboten werden.

"It starts on TikTok": Looping Effects and The Impact of Social Media on Psychiatric Terms

Abstract: This paper examines the impact of TikTok on the public's understanding and engagement with psychiatric and psychological concepts. The rise of mental health-related content on social media has been linked to an increase in adults seeking a diagnosis of ADHD (Yeung et al., 2022). By reviewing a case study: the revision of the term "object permanence" from a developmental stage to an attention-deficit/hyperactivity disorder symptom, I argue that a looping effect, modeled after Hacking (1999), can explain the pattern of language revision for psychological terms on TikTok. Interviews with TikTok users provide preliminary evidence for this looping effect and the research is contextualized within the broader psychiatric discourse.

Painkiller intake and problematic health literacy in sport and music students - A cross-sectional study

Previous works have suggested a high prevalence of painkiller intake (PI) among sport students but also improved health literacy (HL) for sports-active students than for sports-inactive students. Since health-related content also forms part of the sport science curriculum, the study focuses on these seemingly paradoxical results. Music students who are also physically active through their instrumental practice, who act in an area with increased PI and who have no health-related teaching content in their curriculum composed the comparison group. Therefore, this study investigated the prevalence of PI and HL in cohorts of sport (n = 222; 54.5% female) and music students (n = 89; 67.4% female) using a cross-sectional online survey in Lower Saxony, Germany. The hypothesis tests were validated by calculating frequentist and Bayesian statistics. The results show that 50.9% of sport and 28.1% of music students exhibit PI concerning their study programs, often for prophylactical purposes and in the presence of low HL levels. The weak negative correlation between PI and HL was not statistically confirmed and requires further research with improved test power. Regarding the possible health consequences of an inconsiderate PI, target group-specific prevention is indicated to increase general health awareness and HL.

Evaluating the effectiveness of social media in health communication: assessing the impact and outcomes of health communication campaigns conducted on x (Twitter)

Twitter, a leading health communication channel, has effectively promoted health awareness and continues to do so. It provides health information quickly and easily, serving as a vital source of health information. Health practitioners often use Twitter to disseminate health information, a trend that has become more prevalent than engaging audiences in multi-way conversations and interactions. This reassures us of the platform's effectiveness in reaching a broad audience. Twitter has emerged as a powerful tool for reaching a broader audience, offering platforms like Twitter Space for discussion and engagement with health professionals. This technology has brought a new dimension to healthcare, enlightening the public and promoting health behaviors, benefits, challenges, and preventive measures. This research delved into the effectiveness of Twitter in health communication. The study employed a quantitative approach, using a survey to assess the impact of health-related content on Twitter and evaluate the effectiveness of shared health communication. The anticipated outcomes of this research include a comprehensive understanding of the effectiveness of Twitter on health communication, insights into the effectiveness of health content Twitter users access, and recommendations for improving health outcomes through targeted audience campaigns by providing empirical evidence on the effectiveness of Twitter on health communication and a positive and crucial role play in promoting health awareness. Twitter has been used as a tool for health communication campaigns, and many Twitter users benefit from the health information gained there

Usability and Utility of a Mobile App to Deliver Health-Related Content to an Older Adult Population: Pilot Noncontrolled Quasi-Experimental Study.

Digital patient-centered interventions may be important tools for improving and promoting social interaction, health, and well-being among older adults. In this regard, we developed a mobile app called DigiAdherence for an older adult population, which consisted of easy-to-access short videos and messages, to improve health-related knowledge among them and prevent common health conditions, such as falls, polypharmacy, treatment adherence, nutritional problems, and physical inactivity. This study aimed to assess the usability and utility of the DigiAdherence app among Portuguese older adults 65 years or older. In this pilot noncontrolled quasi-experimental study, older adults who were patients at the primary health care center in Portimão, Portugal, and owned a smartphone or tablet were recruited. Participants were assessed at baseline, given access to the DigiAdherence app for 1 month, and assessed again immediately after 30 days (first assessment) and 60 days after stopping the use of the app (second assessment). App usability and utility (primary outcomes) were analyzed in the first follow-up assessment using a structured questionnaire with 8 items. In the second follow-up assessment, our focus was on knowledge acquired through the app. Secondary outcomes such as treatment adherence and health-related quality of life were also assessed. The study included 26 older adults. Most participants rated the different functionalities of the app positively and perceived the app as useful, attractive, and user-friendly (median score of 6 on a 7-point Likert scale). In addition, after follow-up, participants reported having a sense of security and greater knowledge in preventing falls (16/24, 67%) and managing therapies and polypharmacy (16/26, 62%). The DigiAdherence mobile app was useful and highly accepted by older adults, who developed more confidence regarding health-related knowledge. RR2-10.2196/29675.

YouTube as a source of information for self-skin examinations: an analysis of content and quality.

YouTube stands as the premier video-sharing platform in the USA, boasting over 2 billion daily views. Despite YouTube’s declaration of using machine learning algorithms to curb misinformation, research indicates a notable deficiency in the quality of health-related content shared on the platform. We sought to evaluate the quality of skin self-examination videos on YouTube and compare them to the recommendations of the American Academy of Dermatology and the American Cancer Society.

The Digital Medic: Assessing the Role of Social Media in Empowering Individuals with Health Knowledge and Choices

Purpose: The rapid expansion of social media platforms has significantly transformed communication patterns and information access. This study examines the role of social media in sharing health-related content among Indian users, evaluating its trust, influence, and impact. Methodology: A questionnaire survey was conducted among 100 people using SPSS v24, G-power, and literature reviews. Statistical methods assessed reliability, trust, influencing behaviour, and impact perspectives. A model was developed using SPSS 21 AMOS software. Findings: This study examines the transformative potential of social media platforms like YouTube and Instagram for health-oriented information dissemination. It found a significant association between gender and the use of social media for medical information, with independent variables including reliability and Trust, Influence and Behaviour Impact and perspective, and positive impact. The value of ANOVA in the regression model was 0.00, indicating a better fit for the regression model. Practical Implication: The effectiveness of tools in decision-making is crucial for organisations like fitness clubs, gyms, and yoga centres to boost publicity, increase consumer base, and achieve higher revenues, while general people can find trustworthy healthcare information platforms.