Characterizing internet search patterns for neurologic and neurosurgical conditions following celebrity diagnosis

Background: Social media and internet platforms have become significant drivers of massinformation. Highly publicized events, such as John McCain’s announcement of his glioblastoma diagnosis, often drive national public interest in medical topics. Improved understanding of the temporality of interest spikes as well as the nature of the information that garners attention from outside the medical community can help inform ways in which the medical community can boost awareness of (and interest in) the field of neurosurgery. Methods: We utilized the “Explore Topics” feature on Google Trends to obtain web, news, and YouTube search data from May 1, 2015 to May 1, 2019 for the terms “Glioblastoma,” “Brain Tumor,” “Stroke,” and “Multiple Sclerosis” to identify periods of visibly increased search interest. Results: Search results for “Glioblastoma” showed significantly elevated average interest during the period of July 3-23, 2017 as compared to that generated since this specific time period (42.6 vs 8.73, p<0.001). This increased search activity therefore directly correlated with John McCain’s public announcement of his glioblastoma diagnosis, and a similar search interest spike was evident using the search term “Brain Tumor” (87.3 vs 64.2, p<0.001). Search results for “Multiple Sclerosis” showed - as a result of the online buzz created by Selma Blair’s battle with the disease - significantly elevated average interest from October 8, 2018 to October 28, 2018 and February 11, 2019 to March 3, 2019 when compared to the average interest of the remaining time (59 vs 40.16, p<0.001 and 69 vs 40.16, p<0.001). Finally, there were no corresponding elevations in YouTube search interest for any of the terms associated with increased interest on Google Trends. Conclusions: Following major events related to the neurological disease of public figures there is an expected rise in Google search interest relevant to these topics. Our findings suggest that there is an optimal window of app