Abstract: A Descriptive Analysis of Health Influencer Videos on YouTube in the Ostomy Community

◆ Sarah Bell, University of Illinois at Urbana-Champaign

The expansion of YouTube into the mainstream media and its place as the second most-used website in the world makes it a prime place for health information seeking. However, content can be created and uploaded by anyone and thus, the threat of misinformation on YouTube is high. Although medical researchers have established that YouTube videos can promote accurate information, videos by non-professionals promote generally inaccurate or misleading information. Yet, these videos often receive more views and higher relevance rankings on YouTube. To better understand this phenomenon, a descriptive study was used. The study focused on videos created by non-health professionals in the Ostomy community. The goal of this study was to thoroughly describe the innate features of the videos using media richness theory, and to describe social support and illness narrative using the framework of social presence theory.

This study analyzed videos from 39 unique channels (N= 50), the majority of the video creators were female (64%) and primarily White (88%). The number of views ranged from 19 to 2,452,050 (M= 145,253.40, SD= 385,848.73). Research question one aimed to describe the features contained within the videos (i.e., number of text insertions, images, video clips, music, and props), participants made frequent use of props (M= 4.44, SD= 4.97) and images (M= 4.82, SD= 15.24) within their video. Research question two, three, and six examined relationships related to user engagement (i.e., averaging views, likes, and comments into a single variable). A two-tailed Pearson correlation showed that the relationship between the number of features present in a video and user engagement was not significant (r = − 0.022, p = 0.880). Therefore, the number of features present in a video is not significantly related to user engagement. Research question 3 asked if there was a relationship between engagement and video production quality. A two-tailed Pearson correlation showed a significant positive relationship between these variables (r = 0.357, p = 0.011). Therefore, the production quality is significantly related to user engagement. Research question four assessed the amount of social support present within the ostomy videos. Three types of social support were measured: informational, emotional, and instrumental. Given that a driving assumption in this study was that YouTube is a source of health information, it was unsurprising that informational support was the most common type of support, present in 88% of the videos (n = 44). Finally, research question five and six explained questions about illness narrative. Using Frank’s illness typologies, restitution narratives were most frequent (n= 14, 28%); however, 40% of the videos did not contain a narrative at all. Finally, research question six asked if there were differences between types of narratives and user engagement. A one-way ANOVA showed no significant effect of narrative on engagement (F(3, 46) = 1.44, p = 0.242). Overall, these results provide a deep description into this particular community of non-professional health influencers and pave the way for more work.