Sharing Health Information Research Articles

A Middleware Applications Design for Health Information Sharing

The interoperability between electronic health records (EHR) and electronic medical records (EMR) from various healthcare facilities for comprehensive patient care is important. However, integrating such systems, including the need for interoperability standards, data privacy, and security, is a highly challenging task, especially since patient rights in data access must be considered. The primary problem addressed is the challenge of integrating electronic health records (EHR) and electronic medical records (EMR) within various healthcare facilities to ensure comprehensive patient care while maintaining data privacy, security, and adherence to patient rights. This work presents an innovative application for consolidating patient health records from various medical facilities. Facilitates seamless data access, improving the efficiency of healthcare care delivery. The GGD approach was used in developing the prototype to ensure that the delivered product was able to meet the user requirements. Four phases are divided into six stages used in this method: research, modeling, requirements definition, framework definition, refinement, and support. The evaluation involved two phases, back-end and front-end testing, using white-box and black-box testing. White-box testing delivers an average frame-rendering rate of up to 56 fps, and black-box testing has shown 100% successful results in the given task. In conclusion, the Med-OID prototype was successfully developed. Integrates and securely transmits medical records across various healthcare services, demonstrating significant potential to enhance personalized medicine and healthcare coordination. The evaluations underscored the robustness of the prototype and its ability to improve interoperability and data sharing in healthcare systems.

Patient experiences of information-sharing and patient-centred care across the broad landscape of primary care practice and provision: a nationally representative survey of Australian adults

BackgroundAustralian government strategies and frameworks have been developed in recent years to encourage the integration and coordination of primary care delivery; including patient-centred approaches to clinical and preventative care, and health promotion. This study aims to explore patient experiences of information-sharing and patient-centred care across various primary care clinical settings, with a particular focus on clinical encounters with GPs, naturopaths, osteopaths and acupuncturists.MethodsData about healthcare utilisation and experiences from a 63-item cross-sectional survey obtained from a nationally representative sample of Australian adults aged ≥ 18 years were analysed. Chi-square and Kruskal-Wallis H tests were used to explore differences in the experiences of knowledge and information sharing during GP consultations among those who also consulted with a naturopath, osteopath or acupuncturist, compared those who had not. Logistic regression was used to investigate correlations between participants perceptions about GP consultation outcomes, and the GP’s information-sharing behaviour or perceived experience of patient-centredness.ResultsAcross 2354 participants, verbal explanation (76.3%) and/or individualised handouts (16.8%) were the most common type of information shared in GP consultations. Individuals who consulted with a GP and a naturopath, an osteopath, or an acupuncturist reported a lower rate of receiving a verbal explanation from their GP but higher rate of receiving other types of information sources including handouts. Over one quarter of study participants who visited a GP did not discuss any of their health information with their GP. Information sharing was lower for individuals who also visited a naturopath, osteopath or acupuncturist. Participants scored their consultations with a GP as patient-centred, but these scores were lower among participants who also consulted with at least one other primary care practitioner type included in the study.ConclusionsPublic health and health services researchers, policymakers and leaders of primary care professions have a role and responsibility to ensure practitioners are confident and competent in sharing health information with their patients that considers their health literacy needs, and the importance of patient-centred care. Research focussed on a more in-depth understanding of the differences and relationships observed across the primary care landscape in this study is recommended.

Computational model of engagement with stigmatised sentiment: COVID and general vaccine discourse on social media

The growth rate of new social media users continues to surpass new Internet users and new unique mobile phone subscribers and this trend remains consistent over the past 5 years (2019–2023). The most frequently visited types of websites or apps worldwide are chat and messaging, closely followed by social networks and this trend has also remained relatively constant. The dominating role of social media, especially as a source for information seeking, is staggering, particularly during the COVID-19 pandemic. However, the research in Keller et al. (J Mec Internet Res 16:e8, 2014) indicates that not many experts consider social media as a tool for sharing their expertise or for integrating social media into their research efforts. This is a troubling fact, especially considering that stigmatised health narrative are fueled in the face of uncertainty and spread very quickly among the lay population. The latter contributes to the spread of misinformation and, consequently, fosters hesitancy about preventive measures such as vaccines. This research presents new evidence on engagement with stigmatised vaccine discourse on Facebook (Meta), Twitter (X), YouTube and Reddit. Engagement with health-related sentiment can be an important indicator of perceptions regarding preventive measures. The current research can draw the attention of public health experts to the connection between stigmatised discourse and engagement in health discussions, as well as the potential impact of other linguistic features on engagement. It can also guide health authorities and medical professionals in developing effective communication strategies for the general public. Moreover, there are only a handful of studies discussing engagement with socially shared health-care discussions. The research focuses on examining engagement with stigmatised sentiment in vaccination discussions during and prior to the COVID-19 pandemic, using a cross-sectional approach. The study is based on primary data from social media domains, supplemented by secondary data analyses of literature related to the topic. To achieve the research goal, the study employs a multi-method design primarily based on quantitative methods of content analyses, such as Linguistic Inquiry and Word Count (LIWC) (Pennebaker et al. in Linguistic inquiry and word count: Liwc 2001, vol 71. Lawrence Erlbaum Associates, Mahway, 2001) to extract general language features and analyse stigmatised sentiment as the result of previous research findings in Straton et al. (Stigma annotation scheme and stigmatized language detection in health-care discussions on social media. In: Proceedings of The 12th Language Resources and Evaluation Conference (LREC, 2020), pp 1178–1190 (European Language Resources Association, 2020), Straton (Appl Intell, pp 1–26, 2022). Unsupervised K-means clustering methods, along with F-score and Z-score measures, are applied to draw insights from the features. The goal is to explore the phenomena of engagement with socially shared health information, investigate whether stigma can affect the engagement, and identify any other language features that may have an impact. Highly engaging general vaccine discussions before the pandemic appear to be more planned and less emotional. They exhibit reasoning and differentiation typical of more complex discussion sections, incorporating references to authority and family concerns simultaneously. The engaging messages convey stigmatised sentiment, likely shared either with the intent to deceive, or are based on a genuinely biased belief. Some elements of stigmatised discussions indicate deception, while others are more frequent in truthful statements. Engaging content in COVID vaccine discussions, similar to general vaccine content, lacks emotional elements and exhibits high linguistic complexity. However, there seems to be no connection between engagement and stigmatised sentiment. This difference is likely due to the removal of public anti-vaccination pages during the pandemic where anti-vaccination groups moved to discussion section of posts that try to disprove vaccine conspiracy theories. Mixing polarised groups will result in different feedback and engagement with the content. Almost half of the features in COVID and general vaccine discussions have a similar impact on engagement. However, further exploration of the findings suggests that there are distinct differences. Understanding the differences is very important to prevent generalisation errors in the conclusions drawn from the data. Engagement with written text on social media should be measured within a narrow scope: limited regional, demographic and temporal scope. Otherwise, interpretation of the findings risks on being inconsistent.

Variations in Pattern of Social Media Engagement between Individuals with Chronic Conditions and Mental Health Conditions

The use of the internet and supported apps is at historically unprecedented levels for the exchange of health information. The increasing use of the internet and social media platforms can affect patients’ health behavior. This study aims to assess the variations in patterns of social media engagement between individuals diagnosed with either chronic diseases or mental health conditions. Data from four iterations of the Health Information National Trends Survey Cycle 4 from 2017 to 2020 were used for this study with a sample size (N) = 16,092. To analyze the association between the independent variables, reflecting the presence of chronic conditions or mental health conditions, and various levels of social media engagement, descriptive statistics and logistic regression were conducted. Respondents who had at least one chronic condition were more likely to join an internet-based support group (Adjusted Odds Ratio or AOR = 1.5; Confidence Interval, CI = 1.11–1.93) and watch a health-related video on YouTube (AOR = 1.2; CI = 1.01–1.36); respondents with a mental condition were less likely to visit and share health information on social media, join an internet-based support group, and watch a health-related video on YouTube. Race, age, and educational level also influence the choice to watch a health-related video on YouTube. Understanding the pattern of engagement with health-related content on social media and how their online behavior differs based on the patient’s medical conditions can lead to the development of more effective and tailored public health interventions that leverage social media platforms.

Dueling COVID-19 misinformation: Perceptions and behavior of the rural population from South Asian countries

This multi-lingual study presents the awareness, perceptions, and behavior regarding COVID-19 “misinformation” and “fake news,” among the rural population of the South Asian (SA) countries of Bangladesh, India, and Pakistan. The survey questionnaire was distributed to a convenient sample of 400 respondents from the three most populated SA countries selected due to their shared socio-cultural history; limited by fund availability and travel restrictions due to the prevailing lockdowns during the data collection period of early 2022. Results indicate that 92.98% of the participants perceived the presence of COVID-19 misinformation to varying degrees around them with less than 10% finding it easy to verify the accuracy of the information. The results indicate that the participants initially believed the made-up news and information to be true and then experienced fear or uncertainty upon realizing that it was fake. Results further show significant differences in perception and behavior when analyzed with the parameters of gender, age, education, and religion. Our study highlighted that female respondents perceived less than male respondents that fake news was around them, and younger participants of the study had less perception of the presence of fake news around them. The present study also found that the education level of respondents is a strong predictor of their perception of COVID-19 misinformation. Respondents with high school degrees perceived less made-up news and information than associate and master-level degree holders. The findings indicate a lack of media literacy, with a vast majority of individuals being susceptible to false information. The findings of the study will help healthcare professionals, information professionals, social workers, extension workers, and policymakers to deal with the Infodemic and further also assist in designing shared health information literacy programs across the region.

Where Do Oncology Patients Seek and Share Health Information? Survey Study

Where Do Oncology Patients Seek and Share Health Information? Survey Study

Characterizing Information Seeking Events in Health-Related Social Discourse

Social media sites have become a popular platform for individuals to seek and share health information. Despite the progress in natural language processing for social media mining, a gap remains in analyzing health-related texts on social discourse in the context of events. Event-driven analysis can offer insights into different facets of healthcare at an individual and collective level, including treatment options, misconceptions, knowledge gaps, etc. This paper presents a paradigm to characterize health-related information-seeking in social discourse through the lens of events. Events here are board categories defined with domain experts that capture the trajectory of the treatment/medication. To illustrate the value of this approach, we analyze Reddit posts regarding medications for Opioid Use Disorder (OUD), a critical global health concern. To the best of our knowledge, this is the first attempt to define event categories for characterizing information-seeking in OUD social discourse. Guided by domain experts, we develop TREAT-ISE, a novel multilabel treatment information-seeking event dataset to analyze online discourse on an event-based framework. This dataset contains Reddit posts on information-seeking events related to recovery from OUD, where each post is annotated based on the type of events. We also establish a strong performance benchmark (77.4% F1 score) for the task by employing several machine learning and deep learning classifiers. Finally, we thoroughly investigate the performance and errors of ChatGPT on this task, providing valuable insights into the LLM's capabilities and ongoing characterization efforts.

Development of Systemic Interventions to Decrease Breast Cancer Risk: A Group Concept Mapping Study.

As breast cancer continues to take a devasting public health toll, most primary prevention approaches are targeted at individual actions. We have proposed, instead, developing systemic, population approaches to preventing the disease. We used a combined qualitative-quantitative methodology, group concept mapping (GCM), to identify Importance and Feasibility ratings of systemic interventions across a wide spectrum of approaches and stakeholders. Participants (n = 351) from across the state of California sorted 84 potential interventions into topical piles, and then rated each intervention on perceived Importance and Feasibility. Multidimensional scaling and a cluster analysis identified eleven clusters or themes of interventions. Participants rated interventions on Importance and Feasibility differently depending on the region of the state in which they lived. The results of this study underscore the importance of sharing health information with and seeking public health solutions from community partners in general and from beyond the urban areas usually studied.

Identifying the Risk Factors of Allergic Rhinitis Based on Zhihu Comment Data Using a Topic-Enhanced Word-Embedding Model: Mixed Method Study and Cluster Analysis.

Allergic rhinitis (AR) is a chronic disease, and several risk factors predispose individuals to the condition in their daily lives, including exposure to allergens and inhalation irritants. Analyzing the potential risk factors that can trigger AR can provide reference material for individuals to use to reduce its occurrence in their daily lives. Nowadays, social media is a part of daily life, with an increasing number of people using at least 1 platform regularly. Social media enables users to share experiences among large groups of people who share the same interests and experience the same afflictions. Notably, these channels promote the ability to share health information. This study aims to construct an intelligent method (TopicS-ClusterREV) for identifying the risk factors of AR based on these social media comments. The main questions were as follows: How many comments contained AR risk factor information? How many categories can these risk factors be summarized into? How do these risk factors trigger AR? This study crawled all the data from May 2012 to May 2022 under the topic of allergic rhinitis on Zhihu, obtaining a total of 9628 posts and 33,747 comments. We improved the Skip-gram model to train topic-enhanced word vector representations (TopicS) and then vectorized annotated text items for training the risk factor classifier. Furthermore, cluster analysis enabled a closer look into the opinions expressed in the category, namely gaining insight into how risk factors trigger AR. Our classifier identified more comments containing risk factors than the other classification models, with an accuracy rate of 96.1% and a recall rate of 96.3%. In general, we clustered texts containing risk factors into 28 categories, with season, region, and mites being the most common risk factors. We gained insight into the risk factors expressed in each category; for example, seasonal changes and increased temperature differences between day and night can disrupt the body's immune system and lead to the development of allergies. Our approach can handle the amount of data and extract risk factors effectively. Moreover, the summary of risk factors can serve as a reference for individuals to reduce AR in their daily lives. The experimental data also provide a potential pathway that triggers AR. This finding can guide the development of management plans and interventions for AR.

Blockchain-Based Dynamic Consent and its Applications for Patient-Centric Research and Health Information Sharing: Protocol for an Integrative Review.

Blockchain has been proposed as a critical technology to facilitate more patient-centric research and health information sharing. For instance, it can be applied to coordinate and document dynamic informed consent, a procedure that allows individuals to continuously review and renew their consent to the collection, use, or sharing of their private health information. Such has been suggested to facilitate ethical, compliant longitudinal research, and patient engagement. However, blockchain-based dynamic consent is a relatively new concept, and it is not yet clear how well the suggested implementations will work in practice. Efforts to critically evaluate implementations in health research contexts are limited. The objective of this protocol is to guide the identification and critical appraisal of implementations of blockchain-based dynamic consent in health research contexts, thereby facilitating the development of best practices for future research, innovation, and implementation. The protocol describes methods for an integrative review to allow evaluation of a broad range of quantitative and qualitative research designs. The PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols) framework guided the review's structure and nature of reporting findings. We developed search strategies and syntax with the help of an academic librarian. Multiple databases were selected to identify pertinent academic literature (CINAHL, Embase, Ovid MEDLINE, PubMed, Scopus, and Web of Science) and gray literature (Electronic Theses Online Service, ProQuest Dissertations and Theses, Open Access Theses and Dissertations, and Google Scholar) for a comprehensive picture of the field's progress. Eligibility criteria were defined based on PROSPERO (International Prospective Register of Systematic Reviews) requirements and a criteria framework for technology readiness. A total of 2 reviewers will independently review and extract data, while a third reviewer will adjudicate discrepancies. Quality appraisal of articles and discussed implementations will proceed based on the validated Mixed Method Appraisal Tool, and themes will be identified through thematic data synthesis. Literature searches were conducted, and after duplicates were removed, 492 articles were eligible for screening. Title and abstract screening allowed the removal of 312 articles, leaving 180 eligible articles for full-text review against inclusion criteria and confirming a sufficient body of literature for project feasibility. Results will synthesize the quality of evidence on blockchain-based dynamic consent for patient-centric research and health information sharing, covering effectiveness, efficiency, satisfaction, regulatory compliance, and methods of managing identity. The review will provide a comprehensive picture of the progress of emerging blockchain-based dynamic consent technologies and the rigor with which implementations are approached. Resulting insights are expected to inform best practices for future research, innovation, and implementation to benefit patient-centric research and health information sharing. PROSPERO CRD42023396983; http://tinyurl.com/cn8a5x7t. DERR1-10.2196/50339.

Hybrid model of unsupervised and supervised learning for multiclass sentiment analysis based on users’ reviews on healthcare web forums

<p>Twitter has become a popular platform for sharing health information, including diabetes-related content. Recent research studies have shown that Twitter data can be used for various purposes such as monitoring illnesses, promoting health, analyzing sentiment, and potentially aiding in medical directing. However, detecting fitness-related tweets in the vast amount of data on Twitter can be difficult. This pilot study, therefore, aimed to classify patient text about drugs and disease-associated tweets into meaningful health-related segments. The unlabeled dataset is divided into several groups using an unsupervised learning technique called K-Means Clustering, using this first label the text and followed by a combination of neural networks and machine learning classifiers, they classified 32046 diabetes-related tweets and 161290 drug text lines into five groups. Approximately 66.38% of drug line text was classified as health-related, with 55.14% “treatment and medication”, 7.10% “prevention” and 4.14% “symptoms and causes”. Over 33% were categorized as “Other and News”. If we talk about the tweets as a dataset then the tweet was classified as health-related, with 44.30% “treatment and medication”, 7% “prevention” and 5.3% “symptoms and causes”. Over 56.10% were categorized as “Other and News. After this multiclass classification, we applied three machine learning and two deep learning models to find accuracy, precision, recall, and F1 scores. Drug review was used as a dataset then SVM and LR models provided an accuracy of 98% and when tweets were used as a dataset then LR models provided an accuracy of 97%. This research shows the importance of social media data in the decision-making system in the healthcare domain.</p>

Privacy Concerns About Sharing General and Specific Health Information on Twitter: Quantitative Study.

Twitter is a common platform for people to share opinions, discuss health-related topics, and engage in conversations with a wide audience. Twitter users frequently share health information related to chronic diseases, mental health, and general wellness topics. However, sharing health information on Twitter raises privacy concerns as it involves sharing personal and sensitive data on a web-based platform. This study aims to adopt an interactive approach and develop a model consisting of privacy concerns related to web-based vendors and web-based peers. The research model integrates the 4 dimensions of concern for information privacy that express concerns related to the practices of companies and the 4 dimensions of peer privacy concern that reflect concerns related to web-based interactions with peers. This study examined how this interaction may affect individuals' information-sharing behavior on Twitter. Data were collected from 329 Twitter users in the United States using a web-based survey. Results suggest that privacy concerns related to company practices might not significantly influence the sharing of general health information, such as details about hospitals and medications. However, privacy concerns related to companies and third parties can negatively shape the disclosure of specific health information, such as personal medical issues (β=-.43; P<.001). Findings show that peer-related privacy concerns significantly predict sharing patterns associated with general (β=-.38; P<.001) and specific health information (β=-.72; P<.001). In addition, results suggest that people may disclose more general health information than specific health information owing to peer-related privacy concerns (t165=4.72; P<.001). The model explains 41% of the variance in general health information disclosure and 67% in specific health information sharing on Twitter. The results can contribute to privacy research and propose some practical implications. The findings provide insights for developers, policy makers, and health communication professionals about mitigating privacy concerns in web-based health information sharing. It particularly underlines the importance of addressing peer-related privacy concerns. The study underscores the need to build a secure and trustworthy web-based environment, emphasizing the significance of peer interactions and highlighting the need for improved regulations, clear data handling policies, and users' control over their own data.

Health Information Sharing Pattern on Social Media and User Engagement: A Content Analysis on Facebook Public Posts in Bangladesh

In this age of social media, people are using various platforms for seeking and sharing information. This study aims at exploring the patterns of sharing health information on the widely used social media platform Facebook and the users' engagement with the information. For this purpose, the researchers used mixed-method content analysis. We analyzed 485 Facebook posts about 14 types of issues across nine categories. The study results showed that the highest number (27.84%) of posts were related to health awareness, and the lowest were personal opinions. This paper offers a basis for comprehending the processes of sharing health information and how it could affect user involvements. To clarify the structures that guide user interactions with health content on social media, the study also integrates components from communication and information-sharing concepts. The study thus offers empirical insights into the kinds of health information provided, the most popular health topics, and user engagement patterns through a thorough content analysis of public Facebook postings in Bangladesh. The analysis provides sophisticated knowledge of the issues impacting engagement, including language, kind of material, and multimedia use, by measuring the interactions of users. Scholars can understand from this study how users interact with health-related content in the digital era. The result of this study can be used by academics exploring public health, media studies, and health communication to improve theories and create focused interventions for health communication. Additionally, this research can provide useful information for health practitioners to improve their online communication tactics.

Trust, discrimination and preference for shared decision-making in adolescents diagnosed with depression: Implications from Chinese mental health professionals

BackgroundWhile evidence suggests that the attitudes of healthcare providers toward medical decision-making in adolescents diagnosed with depression merit exploration, research on their preferences for Shared Decision-Making (SDM) and the factors affecting these preferences remains limited. ObjectiveTo investigate Chinese mental health professionals’ (MHPs) preferences for SDM in adolescents with depression and identify the relationships between their preference for SDM and trust and discrimination. MethodsA cross-sectional design was used in this study. Clinical Decision-making Style-Staff (CDMS-S) was applied to evaluate their preferences for SDM. Physician Trust in the Patient Scale (PTPS) was utilised to assess their trust in consumers. Social Distance Scale to Mental Illness (SDSMI) was utilised to measure their discrimination against people with mental illness. ResultsA total of 581 MHPs were identified in China. MHPs rated their preference for participation in decision making (PD) as shared (1.89 ± 0.472), information (IN) as moderate (2.62 ± 0.682), and family involvement (FI) as high (3.13 ± 0.840). The preferences for three decision topics ranked from the highest to the lowest score were working-related decision (2.35 ± 0.681), general preferences in decision (1.82 ± 0.581) and medication-related decision (1.74 ± 0.826). The mean score of PTPS and SDSMI were 34.71 (SD=9.709) and 15.17 (SD=4.299), respectively. Logistic regression indicated that the preference for PD was associated with discrimination; the preference for IN was associated with trust, discrimination and SDM-related training experience; and the preference for FI was associated with both trust and discrimination. ConclusionsWhile MHPs generally exhibit a favourable attitude toward SDM, this positivity is not universally observed across all contexts. There remains room for improvement in the willingness to co-develop medication regimens and share health information. Rational recognition of depression, and building trusting and friendly therapeutic relationships are key to promoting MHPs’ preferences for SDM. Practical valueMHPs' preferences for SDM have a significant impact on SDM implementation, which will be promoted by implementing SDM-related training.

Association Between the Composite Cardiovascular Risk and mHealth Use Among Adults in the 2017-2020 Health Information National Trends Survey: Cross-Sectional Study.

Numerous studies have suggested that the relationship between cardiovascular disease (CVD) risk and the usage of mobile health (mHealth) technology may vary depending on the total number of CVD risk factors present. However, whether higher CVD risk is associated with a greater likelihood of engaging in specific mHealth use among US adults is currently unknown. We aim to assess the associations between the composite CVD risk and each component of mHealth use among US adults regardless of whether they have a history of CVD or not. This study used cross-sectional data from the 2017 to 2020 Health Information National Trends Survey. The exposure was CVD risk (diabetes, hypertension, smoking, physical inactivity, and overweight or obesity). We defined low, moderate, and high CVD risk as having 0-1, 2-3, and 4-5 CVD risk factors, respectively. The outcome variables of interest were each component of mHealth use, including using mHealth to make health decisions, track health progress, share health information, and discuss health decisions with health providers. We used multivariable logistic regression models to examine the association between CVD risk and mHealth use adjusted for demographic factors. We included 10,531 adults, with a mean age of 54 (SD 16.2) years. Among the included participants, 50.2% were men, 65.4% were non-Hispanic White, 41.9% used mHealth to make health decisions, 50.8% used mHealth to track health progress toward a health-related goal, 18.3% used mHealth to share health information with health providers, and 37.7% used mHealth to discuss health decisions with health providers (all are weighted percentages). Adults with moderate CVD risk were more likely to use mHealth to share health information with health providers (adjusted odds ratio 1.49, 95% CI 1.24-1.80) and discuss health decisions with health providers (1.22, 95% CI 1.04-1.44) compared to those with low CVD risk. Similarly, having high CVD risk was associated with higher odds of using mHealth to share health information with health providers (2.61, 95% CI 1.93-3.54) and discuss health decisions with health providers (1.56, 95% CI 1.17-2.10) compared to those with low CVD risk. Upon stratifying by age and gender, we observed age and gender disparities in the relationship between CVD risk and the usage of mHealth to discuss health decisions with health providers. Adults with a greater number of CVD risk factors were more likely to use mHealth to share health information with health providers and discuss health decisions with health providers. These findings suggest a promising avenue for enhancing health care communication and advancing both primary and secondary prevention efforts related to managing CVD risk factors through the effective usage of mHealth technology.

Associations and gender differences between OHI-seeking behaviors and eHealth literacy among Chinese university students.

to explore associations and gender differences between OHI-seeking (online health information seeking) behaviors and eHealth (electronic health) literacy among Chinese university students. Online questionnaires of eHealth literacy scale and OHI-seeking behaviors created in software Wenjunxing were used in this survey. Chi-squared tests, t-test, and Pearson correlation analysis were performed using SPSS for data analysis. Among 5,383 participants, 72.4% were girls, 77.5% lived in rural areas, 51.2% majored in liberal arts, 76.6% with low education parents. The average C-eHEALS scores of boys and girls were 26.53 ± 5.861 and 26.84 ± 5.816, respectively, with no significant difference (P = 0.084). The top three OHI-seeking behaviors for boys and girls, as well as for the C-eHEALS low and high groups, were "finding information about physical exercises" "reading or sharing health information via social media" "finding information about nutrition and diet", all of which had significant gender and eHealth literacy differences. Gender and eHealth literacy differences should be focused for intervention when developing and implementing eHealth intervention training for parents and adolescents in schools and communities.

Contextual Integrity and Personal Health Information Sharing in Online Social Networks

Many online social network (OSN) users exchange health-related information on OSNs to manage their health, obtain support, and offer assistance to others facing similar medical challenges. Nonetheless, OSN users are concerned about the privacy of their health information. Extant studies on online information privacy have largely resorted to a calculus perspective, focusing on the costs and benefits of information exchange with commercial vendors. Such a perspective, however, fails to capture the nuanced flows of personal health information (PHI) on OSNs, which involves more than two parties. To address this gap and further advance the research on information privacy, this paper embraces the theory of contextual integrity to explore the distinctive contextual idiosyncrasies of PHI flow on OSNs. In particular, we examine how context-specific values and norms affect OSN users’ personal privacy norms and their PHI disclosure intentions. Our theory-driven empirical results suggest that contextual values and normative expectations related to technology control, legislation, and peer users collectively influence OSN users’ personal privacy norms. In addition, perceived personal value and perceived altruistic value serve as motivators to promote PHI disclosure intentions, working in tandem with personal privacy norms. The key findings of the study also have important implications for policymakers and OSN providers in the context of OSN-mediated healthcare through (1) advancing our understanding of the complex dynamics of PHI flow on OSNs and (2) designing effective information privacy measures (i.e., policies, technical features, and programs) to uphold contextual integrity and nurture the development of patient-centered healthcare paradigms.

SOCIAL PRESSURE IN THE QUARTER LIFE CRISIS THROUGH POSTER MEDIA

Quarter Life Crisis is a time when a person experiences confusion, uncertainty and stress which is often experienced by individuals in their 20s to early 30s. One cause is social pressure. The characteristics of someone experiencing a quarter life crisis include, the individual does not know what his desires and goals in life are, his achievements at that age do not match expectations, he is afraid of failure, he does not want his childhood and adolescence to fail. This community empowerment activity is carried out online via Instagram Post from the @phoffeedu account. This activity aims to provide education to Instagram followers @phoffeedu and people who are within Instagram's reach through the hashtag (#) displayed on posts, explore, stories, etc. Regarding the definition, characteristics and methods of preventing and managing quarter life crisis, social media can be used to share health information so that it is effective in changing people's behavior. One of the health promotion media is posters. The theme of this poster is Social Pressure in the Quarter Life Crisis. 50 hours since the poster was uploaded, it has received approximately 147 likes. Of the 41 comments submitted on the poster, 100% of them showed positive reactions from the audience. There were also those who said that the poster really helped them, especially generation Z, in preparing for, preventing or overcoming a quarter life crisis. This means that the goal of the post to raise awareness about the quarter-life crisis has been achieved according to the comments.

Determinants of American Adults' Use of Digital Health and Willingness to Share Health Data to Providers, Family, and Social Media: A Cross-sectional Study.

With the global pandemic driving the adoption of digital health, understanding the predictors or determinants of digital health usage and information sharing gives an opportunity to advocate for broader adoption. We examined the prevalence and predictors of digital health usage and information-sharing behaviors among American adults. Data were from the Health Information National Trends Survey 5 Cycle 4. More than two-thirds used a digital resource for health-related activities (eg, to check test results). About 81% were willing to share their digital data with their provider, 75% with family, and 58% with friends. Only 14% shared health information on social media. Gender, education, device types, and performance expectancy of digital health were common factors associated with both digital health usage and information-sharing behaviors. Other predictors included rurality, patient portal access, income, and having a chronic disease. Of note, we found that Asian American Pacific Islanders, compared with Whites, were less likely to share information with providers. Performance expectancy was a significant determinant of information sharing. Those diagnosed with diabetes were 4% less likely to share information with their providers. With the growing digital divide, there is a need to advocate for more usable and accessible digital health to assist with person-centered care.

What influences trust in and understanding of clinical trials? An analysis of information and communication technology use and online health behavior from the Health Information National Trends Survey.

Using information and communication technologies to seek, discuss, and share health-related information influences people's trust and knowledge of several health practices. However, we know little about the associations between individuals' information and communication technology use and their perceptions of trust and knowledge of clinical trials. Examining these associations may lead to the identification of target audiences and channels for developing effective educational interventions and campaigns about clinical trials. In this study, we analyzed Health Information National Trends Survey data to document perceptions of clinical trial-related knowledge and trust that were recently added as questions in this annual national survey of US adults. We also examined correlates of these clinical trial perceptions that included sociodemographic factors and individuals' use of information and communication technologies to seek health information, discuss such information with their healthcare providers, and share the information in their network. More than 90% of participants had no or limited perceived knowledge about clinical trials. Knowledge was higher among those who seek or discuss health-related information online. Differences in perceived knowledge and trust emerged for some racial/ethnic subgroups and other demographic factors. Providers were considered the most trusted source of information (73.6%), followed by health organizations (19.4%) and social support (7.1%). Trust in health organizations compared to health providers was higher among those who used online resources to share health information online with others. Trust in social support was significantly higher among those who used information and communication technologies to communicate about health. Based on these findings, we recommend developing online resources about clinical trials to be distributed through social media. These resources should facilitate a dialogue and be targeted to several groups considering their information and communication technologies' use.