Identifying New Frontiers for Social Media Engagement in Global Surgery: An Observational Study
Bibliographic record
Abstract
BACKGROUND: The purpose of this observational study is to characterize the use of social media content pertaining to global surgery. METHODS: A search for public posts on social media related to global surgery was performed over a 3-month window, from January 1st, 2019, to March 31st, 2019. Two public domains were included in the search: Instagram and Twitter. Posts were selected by filtering for one hashtag: #GlobalSurgery. A binary scoring system was used for media format, perspective of the poster, timing of the post, tone, and post content. Data were analyzed using Chi-squared tests with significance set to p < 0.05. RESULTS: Overall, 2633 posts with the hashtag #GlobalSurgery were publicly shared on these two social media platforms over the 3-month period. Of these, 2272 (86.3%) referenced content related to global surgery and were original posts. Physicians and other health professionals authored a majority (60.5%, 1083/1788) of posts on Twitter, whereas organizations comprised a majority of the posts on Instagram (59.9%, 290/484). Posts either had a positive (50.2%, 1140/2272) or neutral (49.6%, 1126/2272) tone, with only 0.3% or 6/2272 of posts being explicitly negative. The content of the posts varied, but most frequently (43.4%, 986/2272) focused on promoting communication and engagement within the community, followed by educational content (21.3%, 486/2272), advertisements (18.8%, 427/2272), and published research (13.2%, 299/2272). The majority of global surgery posts originated from the USA, UK, or Canada (67.6%, 1537/2272), followed by international organizations (11.5%, 261/2272). Chi-squared analysis comparing Instagram with Twitter performed examining media content, tone, perspective, and content, finding statistically significant differences (p < 0.001) the two platforms for each of the categories. CONCLUSION: The online social media community with respect to global surgery engagement is predominantly composed of surgeons and health care professionals, focused primarily on promoting dialogue within the online community. Social media platforms may provide a scalable tool that can augment engagement between global surgeons, with remaining opportunity to foster global collaboration, community engagement, education and awareness.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".