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Background The easy accessibility of smartphones and internet connections enables people to stay virtually connected to communities via social media. However, social media is also being explored for health care education and dissemination of health-related information. Twitter (Twitter, Inc., San Francisco, California) is one of the popular social media used for spreading health-related information. Twitter enables users to create polls to get opinions from their users. The Twitter poll is a less-explored avenue for health surveys. Objective In this pilot study, we aimed to explore the feasibility of conducting a questionnaire-based health survey (on the preference of different systems of medicine for the treatment of various health problems) as a Twitter poll. Methods This observational study was conducted on Twitter for five consecutive days starting from May 31, 2021. We posted five Twitter polls, one poll each day, for five days in a #INPST unique Twitter campaign. Preferences on the use of modern medicine, traditional medicine, a combination of these two systems, and self-medication were collected on five health conditions. We collected the data from the landing poll page and Tweet Analytics (insight about the engagement of tweets provided free by Twitter). The Chi-square test, binomial test, and one-way Analysis of Variance were used to compare data, and Spearman's rank correlation coefficient was used to find a correlation between categorical variables. Results We had a mean 4358.6±590.3 poll reach with the engagement of 108.2±36.87 Twitter users and 67.6±28.06 votes. Most of the responses were received on the first day of posting the poll. The participation then gradually decreased. Modern medicine was the first choice for emergency medical care (85.1%, P <0.0001), treatment of cancer (43.6%, P <0.0001), and sexual disorder or transmitted diseases (48.9%, P <0.0001). Traditional medicine was the first choice (37.5%, P = 0.63) for the treatment of common illnesses, and a combination of modern and traditional medicine was the first choice (37.5%, P = 0.01) for the treatment of chronic diseases. Conclusion A medical survey with short questions with a maximum of four response options can be conducted on Twitter. Survey results can be obtained without any third-party analytic service. The response rate is highest on the first day and participation may decrease when multiple polls are posted within a Twitter campaign. Preference for systems of medicine found in this study can be used for designing large-scale surveys in the future.
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BACKGROUND: Digital teaching in medical education has grown in popularity in the recent years. However, to the best of our knowledge, no bibliometric report to date has been published that analyzes this important literature set to reveal prevailing topics and trends and their impacts reflected in citation counts. OBJECTIVE: We used a bibliometric approach to unveil and evaluate the scientific literature on digital teaching research in medical education, demonstrating recurring research topics, productive authors, research organizations, countries, and journals. We further aimed to discuss some of the topics and findings reported by specific highly cited works. METHODS: The Web of Science electronic database was searched to identify relevant papers on digital teaching research in medical education. Basic bibliographic data were obtained by the "Analyze" and "Create Citation Report" functions of the database. Complete bibliographic data were exported to VOSviewer for further analyses. Visualization maps were generated to display the recurring author keywords and terms mentioned in the titles and abstracts of the publications. RESULTS: The analysis was based on data from 3978 papers that were identified. The literature received worldwide contributions with the most productive countries being the United States and United Kingdom. Reviews were significantly more cited, but the citations between open access vs non-open access papers did not significantly differ. Some themes were cited more often, reflected by terms such as virtual reality, innovation, trial, effectiveness, and anatomy. Different aspects in medical education were experimented for digital teaching, such as gross anatomy education, histology, complementary medicine, medicinal chemistry, and basic life support. Some studies have shown that digital teaching could increase learning satisfaction, knowledge gain, and even cost-effectiveness. More studies were conducted on trainees than on undergraduate students. CONCLUSIONS: Digital teaching in medical education is expected to flourish in the future, especially during this era of COVID-19 pandemic.