====== TikTok ======

{{rss>https://pubmed.ncbi.nlm.nih.gov/rss/search/1-A-YYVQW9EfsxlmNGVebfus9cOpB1eSDNPF44KbcbQ9blgsQw/?limit=15&utm_campaign=pubmed-2&fc=20250318060014}}

As the [[Internet]] becomes an increasingly vital source of [[medical information]], the [[quality]] and [[reliability]] of [[brain tumor]]-related short [[video]]s on [[platform]]s such as TikTok and Bilibili have not been adequately evaluated. Therefore, this study aims to assess these aspects and explore the factors influencing the dissemination of such videos.

A [[cross-sectional]] analysis was conducted on the top 100 brain tumor-related short videos from TikTok and Bilibili. The videos were evaluated using the Global Quality Score and the [[DISCERN]] reliability instrument. An eXtreme Gradient Boosting algorithm was utilized to predict dissemination outcomes. The videos were also categorized by content type and uploader.

TikTok videos scored relatively higher on both the Global Quality Score (median 2, interquartile range [2, 3] on TikTok vs. median 2, interquartile range [1, 2] on Bilibili, p = 1.51E-04) and the DISCERN reliability instrument (median 15, interquartile range [13, 18.25] on TikTok vs. 13.5, interquartile range [11, 16] on Bilibili, p = 1.66E-04). Subgroup analysis revealed that videos uploaded by professional individuals and institutions had higher quality and reliability compared to those uploaded by non-professional entities. Videos focusing on disease knowledge exhibited the highest quality and reliability compared to other content types. The number of followers emerged as the most important variable in our dissemination prediction model.

The [[overall]] quality and reliability of brain tumor-related short videos on TikTok and Bilibili were unsatisfactory and did not significantly influence video dissemination. Future research should expand the scope to better understand the factors driving the dissemination of medical-themed videos
((Zhang R, Zhang Z, Jie H, Guo Y, Liu Y, Yang Y, Li C, Guo C. Analyzing dissemination, quality, and reliability of Chinese brain tumor-related short videos on TikTok and Bilibili: a cross-sectional study. Front Neurol. 2024 Oct 18;15:1404038. doi: 10.3389/fneur.2024.1404038. PMID: 39494168; PMCID: PMC11527622.))
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[[Physician]]s aim to provide optimal [[care]], considering patient [[experience]]s and [[satisfaction]]. Traditional in-clinic [[survey]]s assessing surgical [[outcome]]s face [[limitation]]s, including [[bias]] and inadequate [[inclusion]] of diverse [[demographics]]. [[Social media]] is an emerging [[platform]] for patients to share their healthcare experiences, providing an alternative [[method]] for gathering patient [[feedback]].

A study explores the prevalent themes of [[moyamoya disease]] experiences shared on social media.

Posts containing "#moyamoya" and "#moyamoya warrior" from [[Instagram]], [[TikTok]], and [[Twitter]] were analyzed. Posts unrelated to patient experiences were excluded. Relevant posts were categorized by themes and analyzed based on the platform, gender, and identity of the poster (patient or someone else). Chi-squared tests determined the significance of theme prevalence.

Of the 1,005 social media posts analyzed, 63.8% were by patients, and 75.0% were by females. Most patients (83.0%) had undergone one surgery. Instagram posts focused on Recovery/Rehabilitation (69.7%), Survival (66.7%), and Spreading Positivity (45.8%), while TikTok posts more frequently discussed Survival (97.2%), Recovery/Rehabilitation (81.3%), and Spreading Positivity (84.1%) (p < 0.001). Females were less likely to post on these themes than males, who discussed religious topics more frequently (p=0.029). Patients discussed appearance (p<0.001), resiliency (p=0.002), and quality of life (p=0.014) more than their loved ones.

This study demonstrates social media's potential to augment traditional methods of obtaining patient feedback, highlighting significant gender- and platform-based differences in shared experiences. Despite limitations, leveraging social media can enhance understanding patient needs, ultimately improving care [[quality]] for Moyamoya disease patients
((Hou NY, Gajjar AA, Hou E, Barpujari A, Salem MM, Sioutas G, Srinivasan VM, Jankowitz BT, Burkhardt JK. [[Moyamoya Disease]]: Understanding Patient [[Experience]]s through Thematic Analysis of Instagram, TikTok, and Twitter Posts. J Stroke Cerebrovasc Dis. 2025 Mar 15:108293. doi: 10.1016/j.jstrokecerebrovasdis.2025.108293. Epub ahead of print. PMID: 40096923.)).