Title | Sociodemographic reporting in videomics research: a review of practices in otolaryngology - head and neck surgery. |
Publication Type | Journal Article |
Year of Publication | 2024 |
Authors | Kim YEun, Serpedin A, Periyakoil P, German D, Rameau A |
Journal | Eur Arch Otorhinolaryngol |
Date Published | 2024 May 05 |
ISSN | 1434-4726 |
Abstract | OBJECTIVE: To assess reporting practices of sociodemographic data in Upper Aerodigestive Tract (UAT) videomics research in Otolaryngology-Head and Neck Surgery (OHNS). STUDY DESIGN: Narrative review. METHODS: Four online research databases were searched for peer-reviewed articles on videomics and UAT endoscopy in OHNS, published since January 1, 2017. Title and abstract search, followed by a full-text screening was performed. Dataset audit criteria were determined by the MINIMAR reporting standards for patient demographic characteristics, in addition to gender and author affiliations. RESULTS: Of the 57 studies that were included, 37% reported any sociodemographic information on their dataset. Among these studies, all reported age, most reported sex (86%), two (10%) reported race, and one (5%) reported ethnicity and socioeconomic status. No studies reported gender. Most studies (84%) included at least one female author, and more than half of the studies (53%) had female first/senior authors, with no significant differences in the rate of sociodemographic reporting in studies with and without female authors (any female author: p = 0.2664; first/senior female author: p > 0.9999). Most studies based in the US reported at least one sociodemographic variable (79%), compared to those in Europe (24%) and in Asia (20%) (p = 0.0012). The rates of sociodemographic reporting in journals of different categories were as follows: clinical OHNS: 44%, clinical non-OHNS: 40%, technical: 42%, interdisciplinary: 10%. CONCLUSIONS: There is prevalent underreporting of sociodemographic information in OHNS videomics research utilizing UAT endoscopy. Routine reporting of sociodemographic information should be implemented for AI-based research to help minimize algorithmic biases that have been previously demonstrated. |
DOI | 10.1007/s00405-024-08659-0 |
Alternate Journal | Eur Arch Otorhinolaryngol |
PubMed ID | 38704768 |
PubMed Central ID | 7727333 |
Grant List | K76 AG079040 / AG / NIA NIH HHS / United States OT2 OD032720 / CD / ODCDC CDC HHS / United States |