How we use social media to supplement a novel curriculum in medical education
Abstract
BACKGROUND: The millennial learner is reliant on technology to gain knowledge. Social media in the form of Twitter and Facebook provide a unique way to reach these learners. AIMS: To demonstrate a supplement to a curriculum using "push technology" via Twitter and Facebook to deliver educational content to mobile devices. METHODS: A curriculum consisting of high-yield ultrasound concepts was developed and posted to Twitter @EDUltrasound daily. Followers received tweets "pushed" directly to their mobile devices. Following the year-long program, followers were surveyed regarding the program's effectiveness. To determine the ways in which tweets were reaching users, followers were categorized demographically. RESULTS: Daily "tweets" were posted each morning beginning on July 1, 2010. By the end of the year, there were 87 followers on Twitter and 78 on Facebook. The majority of followers (55.6%) had not previously used Twitter. The majority of followers (88.9%) found Twitter user-friendly, while most (81.5%) found the information useful. CONCLUSIONS: Due to ease of use and widespread applicability, Twitter and Facebook are excellent applications of "push technology" as a means to deliver educational content. This pilot project demonstrates the potential of social media to both supplement and enhance traditional educational methods.
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Social media has been proven to be used for educational purposes at medical schools, for example to complement university courses.
“SM has been proven to be used for educational purposes at medical schools, for example, to complement university courses [134,135].”
From Dangers and Benefits of Social Media on E-Professionalism of Health Care Professionals: Scoping Review (2021) · cites this paper as [134]
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Gandotra, S., Stewart, N. H., Khateeb, D. M., Garcha, P., Carlos, W. G., Carroll, C. L., & Kaul, V. (2021) · ATS Scholar · doi:10.34197/ats-scholar.2020-0100oc · Cited by 10 · see citing works
Monroe, K. S., Evans, M. A., Mukkamala, S. G., Williamson, J. L., Jabaley, C. S., Mariano, E. R., & O’Reilly-Shah, V. N. (2018) · Korean Journal of Anesthesiology · doi:10.4097/kja.d.18.00014 · Cited by 10 · see citing works
Applications and Effects of EdTech in Medical Education
Hong, H., & Kim, Y. (2021) · Korean Medical Education Review · doi:10.17496/kmer.2021.23.3.160 · Cited by 9 · see citing works
Cano, E. V., & García, M. L. S. (2019) · Edutec Revista Electrónica de Tecnología Educativa · doi:10.21556/edutec.2019.68.1311 · Cited by 8 · see citing works
- Authors
- Bahner, D. P., Adkins, E., Patel, N., Donley, C., Nagel, R., & Kman, N. E.
- Affiliations
- The Ohio State University (US)
- Corresponding author
- Bahner, David P.
- Venue
- Medical Teacher
- Publisher
- Informa UK Limited
- Published
- 2012-03-27
- Volume
- 34
- Issue
- 6
- Pages
- 439-444
- ISSN
- 0142-159X (ISSN-L)
- 1466-187X
- OpenAlex
- W2162130466
- Cited by
- 189
- References
- 8
- Citations by year
- 2026: 3 · 2025: 3 · 2024: 7 · 2023: 4 · 2022: 15 · 2021: 14 · 2020: 19 · 2019: 15 · 2018: 17 · 2017: 20 · 2016: 13 · 2015: 24 · 2014: 17 · 2013: 16 · 2012: 2
- FWCI
- 21.61
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Medical Teacher (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Health › Social Media in Health Education
- Physical Sciences › Computer Science › Information Systems › Educational Technology in Learning
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Innovations in Medical Education
- Keywords
- social media in medical education, Twitter, Facebook, push technology, mobile learning, ultrasound training, millennial students, educational content delivery
- MeSH terms
- Curriculum, Education, Medical, Humans, Blogging, Social Media
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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