Using google trends to assess for seasonal variation in knee injuries

Abstract

IntroductionThe Google Trends search engine provides an insight into the search habits of individuals using the Google search engine. Usage of such data can provide us with information about the incidence of medical condition that are otherwise hard to track as patients do not always seek medical attention. An example of this is injuries to the knee. This study aimed to assess the seasonality of patients with knee symptoms that may be suggestive of a knee injury using data from Google Trends. Materials & methodsData was downloaded for ‘knee pain’ and ‘knee swelling’ from the Google Trends search engine from 4th January 2004 to 2nd January 2016. Statistical analysis was conducted to assess for trends and seasonality for these search terms. ResultsThe data demonstrated that there has been an overall increase in the volume of searches for both ‘knee pain’ and ‘knee swelling’ over time. The month of April demonstrated the highest number of searches. Statistical analysis demonstrated a statistically significant increase in searches in warmer months compared to colder months. ConclusionThe Google Trends search engine represents a method of data collection and analysis that may complement more traditional methods Our study shows that internet searches for symptoms related to knee injuries demonstrated a seasonal trend that has also been shown to be present for knee injuries in professional athletes.