A Cross-Sectional Analysis of Breast Reconstruction with Fat Grafting Content on TikTok

Abstract

As of November 2021, TikTok has one billion monthly active users and is recognized as the most engaging social media platform. TikTok has seen a surge in users and content creators, ranging from athletes to medical professionals. In the past year, content creators have utilized the app to advocate for social reforms, education, and other uses that were not previously considered. Breast cancer is the most commonly diagnosed cancer in women, with an expected 281,550 new cases of invasive breast cancer in 2021. As more individuals with breast cancer choose to undergo resection, the demand for autologous fat grafting in breast reconstruction has increased due to the natural look and feel of breast tissue. The purpose of this article is to analyze content related to breast reconstruction with fat grafting found on TikTok and recommend methods to improve patient education, care, and outcomes.We searched TikTok on November 1, 2021, for videos using the phrase “breast reconstruction with fat grafting.” The top 200 videos retrieved from the TikTok search algorithm were analyzed, and all commentaries, duplicates, and nonrelevant videos were removed. Video characteristics were collected, and two independent reviewers generated a DISCERN scoreA total of 131 videos were included in the study. They were found to have a combined 1,871,980 likes, 41,113 comments, and 58,662 shares. The videos had an average DISCERN score of 2.16. Content creators had an overall low DISCERN score in items involving the use of references, disclosure of risks for not obtaining treatment, and support for shared decision-making. When stratified, the DISCERN score was higher for videos created by physicians (DISCERN average 2.48) than for videos created by nonphysicians (DISCERN average 1.99; p < 0.001).Content creators can improve the quality of their videos by disclosing treatment risks, benefits and risks, discussing risks for not obtaining treatment, and advocating for shared decision-making. Furthermore, including citations and academic references may offer increased credibility and promote evidence practice. This article is limited by the variability seen on the TikTok platform that is influenced by algorithmic trends. The top 200 search results vary, making each compilation of videos selected for analysis unique. Furthermore, although DISCERN is a reliable source to assess patient information, it has not been tested for its reliability with videos such as on TikTok. Despite TikTok being developed as a social media platform, it has shown to be a medium for patient outreach and an educational tool.

Myopia information on TikTok: analysis factors that impact video quality and audience engagement

“…The video retrieval process in existing literature involved both the user-preference-based MLS strategy [ 19 , 30 , 31 , 33 – 35 ] and the mainly used DCS strategy [ 13 , 16 , 36 – 40 ], and four cut-off sample sizes ( n = 50 [ 13 , 33 ], 100 [ 16 , 19 , 34 , 35 , 38 – 40 ], 150 [ 30 ] and 200 [ 31 , 36 , 37 ]) were all reported. This is the first study to analyze whether these two retrieval algorithms influence the audience-available video quality and audience engagement.…”

How TikTok Is Being Used to Help Individuals Cope With Breast Cancer: Cross-sectional Content Analysis

“…To our knowledge, this is the first study describing the content of the most viewed TikTok videos on the larger topic of breast cancer. Our review of the literature revealed one prior publication focusing on fat grafting in breast cancer [ 27 ]. Prior research evaluated breast cancer coverage on various social media platforms [ 16 , 28 ].…”

A rapid review of quality of health information on TikTok

“…3 Chen Z, Pan S, Zuo S. Anal Fissures 62 videos TikTok: An Opportunity for Antibiotic Education? 22 Evans E, Gory L, O'Kane A Antibiotics 300 videos A Cross-Sectional Analysis of Breast Reconstruction with Fat Grafting Content on TikTok. 23 Gupta R, John J, Gupta Across all health topics, the median DISCERN and PEMAT-AV scores were 2.02±0.23/5 and 56 ±16.488, respectively (95% CI; Figure 2).…”