Photographic Misrepresentation on Instagram After Facial Cosmetic Surgery: Is Increased Photography Bias Associated With Greater User Engagement?

BACKGROUND Before and after images are commonly used on Instagram to advertise aesthetic surgical treatments and are a powerful means of prospective patient engagement. Consistency between before and after images accurately demonstrating the postoperative result on Instagram, however, has not been systematically assessed. OBJECTIVES Our aim was to systematically assess facial cosmetic surgery before and after photography bias on Instagram. METHODS The authors queried 19 Instagram facial aesthetic surgery-related hashtags on 3 dates in May 2020. The "top" 9 posts associated with each hashtag (291 posts) were analyzed by 3 plastic surgeons using 5-item rubric quantifying photographic discrepancies between preoperative and postoperative images. Duplicate posts and those that did not include before and after images after facial aesthetic surgery procedures were excluded. RESULTS A total of 3,477,178 posts were queried. Photography conditions were observed to favor visual enhancement of the post-operative result in 282/291 analyzed top posts, with an average bias score of 1.71/5 (± 1.01). Plastic surgeons accounted for only 27.5% of top posts. Physicians practicing outside their scope of practice accounted for 2.8% of top posts including a general surgeon, dermatologist, dentist, ophthalmologist, and maxillofacial surgeon. Accounts with a greater number of followers (p = 0.017) and posts originating from Asia (p = 0.013) were significantly associated with a higher post-operative photography bias score. CONCLUSIONS Photographic misrepresentation, with photography conditions biased towards enhancing the appearance of the postoperative result, is pervasive on Instagram. This pattern was observed across all physician specialties and raises significant concerns. Accounts with a greater number of followers demonstrated significantly greater postoperative photography bias, suggesting photographic misrepresentation is awarded by greater user engagement.