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Comparison of Online Learning Video Platforms Regarding Laparoscopic Adrenalectomy: YouTube and WebSurg.

Bülent ÇitgezNurcihan AygunBanu YigitMehmet Uludag
Published in: Journal of laparoendoscopic & advanced surgical techniques. Part A (2021)
Background: The internet is a widely used source for receiving medical information. Nevertheless, the quality of data on online platforms is still questioned. Our aim was to compare the laparoscopic adrenalectomy videos published on the two online platforms, WebSurg® (WS) and YouTube® (YTb) regarding the quality of data, educational power, and accuracy of the sources. Materials and Methods: Most viewed popular visual content returned by YTb in reply to the keyword "laparoscopic adrenalectomy" were involved in the research protocol. The quality of the data, educational power, and the accuracy and reliability of the sources were assessed by applying new scoring systems. A novel scoring method estimated technical quality. The 10 most viewed videos in the WS were compared with 10 YTb videos with the highest technical scores. Results: Scoring systems measuring the quality of data and educational power of the mostly viewed WS visual content revealed higher scores than those of the most technically qualified 10 YTb videos (10 videos having the highest laparoscopic adrenalectomy scoring system scores [LASS-S]; P = .021; P = .003; P = .025, respectively). Also, there was no significant difference between the top 10 most viewed WS videos and 10 YTb videos having the highest LASS-S in terms of LASS-S (P = .34). Conclusions: Although WS videos were passed through a professional reviewing process, and were mostly provided by academicians, they remained below the expected quality. The presented research showed that attentively chosen YTb content on laparoscopic adrenalectomy is almost as accurate as WS content. Notwithstanding all its limitations, the informative power or potential of YTb should not be neglected.
Keyphrases
  • robot assisted
  • health information
  • quality improvement
  • randomized controlled trial
  • big data
  • healthcare
  • drinking water
  • risk assessment
  • minimally invasive
  • mass spectrometry
  • high resolution
  • artificial intelligence