Sociodemographic reporting in videomics research: a review of practices in otolaryngology - head and neck surgery

Eur Arch Otorhinolaryngol. 2024 Nov;281(11):6047-6056. doi: 10.1007/s00405-024-08659-0. Epub 2024 May 5.

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.

Keywords: Artificial intelligence; Computer vision; Upper aerodigestive tract endoscopy.

Publication types

  • Review

MeSH terms

  • Biomedical Research
  • Endoscopy / methods
  • Endoscopy / statistics & numerical data
  • Female
  • Humans
  • Otolaryngology*
  • Sociodemographic Factors
  • Video Recording