Tweeting influenza vaccine to cardiovascular health community

Women in Cardiology: Role of Social Media in Advocacy

Digital and social media have transformed the field of medicine. They are powerful tools that academic and non-academic physicians and healthcare providers are using to influence others, promote ideas, obtain knowledge, disseminate research and communicate with others. The history of advocacy for women in medicine and the role of social media in influencing the choice of women to choose Cardiology as a career and its role in advocacy for Women in Cardiology (WIC) have been reviewed. It has changed the way cardiologists learn, educate, and interact with each other. Social media has proven especially useful in advocating for WIC, but whether it can help improve the numbers of female doctors going into Cardiology remains to be seen. In addition to encouraging women to pursue cardiology, social media has drawn attention to key women's rights issues affecting practicing female cardiologists.

Methods for Social Media Monitoring Related to Vaccination: Systematic Scoping Review

Background

Social media has changed the communication landscape, exposing individuals to an ever-growing amount of information while also allowing them to create and share content. Although vaccine skepticism is not new, social media has amplified public concerns and facilitated their spread globally. Multiple studies have been conducted to monitor vaccination discussions on social media. However, there is currently insufficient evidence on the best methods to perform social media monitoring.

Objective

The aim of this study was to identify the methods most commonly used for monitoring vaccination-related topics on different social media platforms, along with their effectiveness and limitations.

Methods

A systematic scoping review was conducted by applying a comprehensive search strategy to multiple databases in December 2018. The articles’ titles, abstracts, and full texts were screened by two reviewers using inclusion and exclusion criteria. After data extraction, a descriptive analysis was performed to summarize the methods used to monitor and analyze social media, including data extraction tools; ethical considerations; search strategies; periods monitored; geolocalization of content; and sentiments, content, and reach analyses.

Results

This review identified 86 articles on social media monitoring of vaccination, most of which were published after 2015. Although 35 out of the 86 studies used manual browser search tools to collect data from social media, this was time-consuming and only allowed for the analysis of small samples compared to social media application program interfaces or automated monitoring tools. Although simple search strategies were considered less precise, only 10 out of the 86 studies used comprehensive lists of keywords (eg, with hashtags or words related to specific events or concerns). Partly due to privacy settings, geolocalization of data was extremely difficult to obtain, limiting the possibility of performing country-specific analyses. Finally, 20 out of the 86 studies performed trend or content analyses, whereas most of the studies (70%, 60/86) analyzed sentiments toward vaccination. Automated sentiment analyses, performed using leverage, supervised machine learning, or automated software, were fast and provided strong and accurate results. Most studies focused on negative (n=33) and positive (n=31) sentiments toward vaccination, and may have failed to capture the nuances and complexity of emotions around vaccination. Finally, 49 out of the 86 studies determined the reach of social media posts by looking at numbers of followers and engagement (eg, retweets, shares, likes).

Conclusions

Social media monitoring still constitutes a new means to research and understand public sentiments around vaccination. A wide range of methods are currently used by researchers. Future research should focus on evaluating these methods to offer more evidence and support the development of social media monitoring as a valuable research design.

Future Direction for Using Artificial Intelligence to Predict and Manage Hypertension

PURPOSE OF REVIEW

Evidence that artificial intelligence (AI) is useful for predicting risk factors for hypertension and its management is emerging. However, we are far from harnessing the innovative AI tools to predict these risk factors for hypertension and applying them to personalized management. This review summarizes recent advances in the computer science and medical field, illustrating the innovative AI approach for potential prediction of early stages of hypertension. Additionally, we review ongoing research and future implications of AI in hypertension management and clinical trials, with an eye towards personalized medicine.

RECENT FINDINGS

Although recent studies demonstrate that AI in hypertension research is feasible and possibly useful, AI-informed care has yet to transform blood pressure (BP) control. This is due, in part, to lack of data on AI's consistency, accuracy, and reliability in the BP sphere. However, many factors contribute to poorly controlled BP, including biological, environmental, and lifestyle issues. AI allows insight into extrapolating data analytics to inform prescribers and patients about specific factors that may impact their BP control. To date, AI has been mainly used to investigate risk factors for hypertension, but has not yet been utilized for hypertension management due to the limitations of study design and of physician's engagement in computer science literature. The future of AI with more robust architecture using multi-omics approaches and wearable technology will likely be an important tool allowing to incorporate biological, lifestyle, and environmental factors into decision-making of appropriate drug use for BP control.

Mining twitter to understand the smoking cessation barriers

Smoking cessation is challenging and lack of positive support is a known major barrier to quitting cigarettes. Previous studies have suggested that social influences might increase smokers’ awareness of social norms for appropriate behavior, which might lead to smoking cessation. Although social media use is increasing among young adults in the United States, research on the relationship between social media use and smoking cessation is lacking. Twitter has provided a rich source of information for researchers, but no overview exists as to how the field uses Twitter in smoking cessation research. To the best of our knowledge, this study conducted a data mining analysis of Twitter to assess barriers to smoking cessation. In conclusion, Twitter is a cost-effective tool with the potential to disseminate information on the benefits of smoking cessation and updated research to the Twitter community on a global scale.