Global Surveillance of Public Interest in Cosmetic Tourism for Aesthetic Eyelid Surgery Abroad: Cross-Sectional Infodemiology Investigation of Internet Search Trends and Social Media Content
Bibliographic record
Abstract
Background: Global medical tourism for aesthetic surgery has become a popular phenomenon through ease of access in the digital era, though such services are not without potential risks. The application of infodemiology for global health surveillance may provide unique insights into unknown patient travel patterns and surgeon workforce dynamics abroad. Objective: This study aimed to evaluate American cosmetic tourism trends in oculofacial plastic surgery, including demand profile and qualifications of the most sought-after international eyelid surgeons on social media. Methods: This cross-sectional infodemiology study queried Google Trends to assess US interests in aesthetic eyelid surgery abroad in 25 destination countries from 2013 to 2023. The highest-rated content posted by 55 eyelid surgeons (US: n=11; international: n=44) on a social media platform (Instagram; Meta Platforms) was evaluated. The main outcomes included Google search volumes for aesthetic eyelid surgery for each destination country, as well as specialty training and professional medical society affiliations of popular eyelid surgeons on social media in each of these countries. Results: The top 5 destinations Americans sought for aesthetic eyelid surgery abroad were South Korea, Mexico, Canada, Turkey, and China. Interest in eyelid surgery abroad remained stable over the last decade despite 118% growth in blepharoplasty searches. Social media indicated eyelid surgeons abroad were more often general plastic surgeons than in the United States (30/44, 68% vs 2/11, 18%; P=.003). US surgeons more frequently completed oculofacial plastics, facial plastics, or aesthetic plastics fellowships compared with international surgeons (9/11, 82% vs 10/44, 23%; P<.001) and had membership in professional medical societies (11/11, 100% vs 22/44, 50%; P=.002). Conclusions: American demand for international eyelid surgery remained stable over the past decade despite a 2-fold increase in the US interest for blepharoplasty. Digital epidemiology data reveal a shortage of international surgeons with specialized aesthetic eyelid fellowship training or professional society affiliations on social media among the preferred destinations for Americans seeking aesthetic eyelid surgery. These findings may provide beneficial insights for patients interested in traveling abroad for eyelid surgery, as well as for surgeons or academic societies seeking to increase social media presence or patient-directed educational content via social media engagement.
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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 | 0.005 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".