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Respiratory medicine · 2026

Network-based analysis of images and lesions expressed by digital interpretation and transmission of bronchoscopy findings on social media (NAILED-IT).

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Gilbert Christopher R, Yarmus Lonny B, Kapp Christopher, Argento A Christine, Akulian Jason A, Gorden Jed A, Thiboutot Jeffrey, Silvestri Gerard A, Maldonado Fabien

Аннотация

INTRODUCTION: Diagnostic bronchoscopy has advanced rapidly over the last two decades with the adoption of novel technologies. Concurrently, social media platforms have proliferated, with some pulmonologists sharing and promoting these new technologies and diagnostic successes. The impact of this content on perceptions of diagnostic yield and utility remains unclear.

METHODS: A scoring system was developed to evaluate social media posts related to bronchoscopy. The BIASED score ranges from 1 to 6 points, awarding one point each for the inclusion of: Brand/technology mention, Imaging (diagnostic), Anatomy description, Successful diagnosis, Educational value, and Data on the procedure. Nine participants reviewed and scored bronchoscopy-related posts across multiple social media platforms. Descriptive statistics were used to summarize findings.

RESULTS: Social media platforms were reviewed that included Facebook, Instagram, LinkedIn, TikTok, and YouTube. Diagnostic bronchoscopy related posts were identified and scored after visual filtering for the presence of radiographic or bronchoscopic imaging. The mean BIASED score was 4.59. Most posts emphasized positive diagnostic outcomes, with only two social media accounts posting content related to non-diagnostic bronchoscopy results.

DISCUSSION: This study represents one of the first attempts at descriptive assessment of bronchoscopy-related content on social media. Many posts demonstrated high BIASED scores, which appear to emphasize favorable outcomes with diagnostic bronchoscopy. The BIASED scoring system provides a feasible method to quantify characteristics of bronchoscopy-related social media content and may serve as a framework for future analyses.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты