Introduction: Vitiligo, an autoimmune disorder causing skin depigmentation, significantly impacts quality of life. With over 1 billion users, TikTok has become a major platform for health information dissemination. However, its engagement‐driven algorithm raises concerns about misinformation. This study evaluates the accuracy of the most‐liked vitiligo‐related TikTok videos and examines the platform's role in health education. Methods: We retrieved TikTok videos using “#Vitiligo” and analyzed the first 100 videos that met inclusion criteria. Videos were categorized into healthcare providers (HP) and non‐healthcare providers (NHP). Content characteristics and engagement metrics were extracted. Three independent reviewers assessed quality using multiple assessment tools—Patient Education Materials Assessment Tool (PEMAT), modified DISCERN (mDISCERN), Video Information and Quality Index (VIQI), and Global Quality Score (GQS). A novel tool, V‐TRACE, was developed to evaluate (1) clinical aspects (pathophysiology, clinical presentation, treatment, and autoimmune comorbidities) and (2) social aspects (body image and representation of people of color). Results: Of 100 videos analyzed, 25% were from HP, demonstrating significantly higher quality across all metrics. HP videos focused on education (96% vs. 20%, p < 0.01) and scored higher on mDISCERN (2.66 vs. 1.66, p < 0.01), GQS (2.66 vs. 1.6, p < 0.01), and VIQI (12.33 vs. 10.00, p < 0.01). NHP produced 75% of videos, received higher engagement ( p = 0.04), and had a more positive tone (30.7% vs. 12%, p = 0.05). Conclusion: Vitiligo‐related TikTok content lacks reliability. HPs produce higher‐quality content, while NHPs dominate engagement and potentially spread misinformation. There is a need for more evidence‐based, engaging content to improve patient education on the platform.

Medical students often begin their studies with preconceived notions about specialties, which may evolve as they gain clinical experience. This study aimed to assess changes in specialty preferences over six years of medical training and to compare two cohorts of first-year students. A repeat cross-sectional design was used, analyzing survey data from the 2019 class during preclinical (first–second year) and clinical (sixth year) stages, and from the 2024 first-year cohort. A total of 367 students participated. Comparing preclinical and clinical students revealed a significant increase in interest in ophthalmology (2.9% vs. 11%, p = 0.012), along with non-significant upward trends in obstetrics and gynecology and family medicine. Declines were observed in psychiatry, oncology, neurosurgery, and surgery. The 2024 cohort included a higher proportion of students with a prior medical background compared with the 2019 cohort (43% vs. 23%, p = 0.002), but no other demographic or specialty preference differences were identified. These findings suggest that specialty preferences among medical students may shift during clinical training, while initial preferences appear relatively consistent across cohorts. Understanding how medical education influences career development may guide curricular strategies to balance specialty distribution and address workforce needs.