Seasonal Variation for Plantar Fasciitis: Evidence from Google Trends Search Query Data

Abstract

We aimed to determine the seasonal trends in internet searches for plantar fasciitis and related symptoms in various countries using search engine query data on Google. We used Google Trends to obtain internet search query data from January 2009 to December 2019. We collected monthly search volumes for the query terms “plantar fasciitis” and “heel pain” in the USA, Canada, the U.K., Ireland, Australia, and New Zealand. Statistical analysis of the seasonal effects on plantar fasciitis was performed using a cosinor model. The cosinor analyses confirmed statistically significant seasonal patterns in the relative search volumes for the terms “plantar fasciitis” and “heel pain” in the USA, Canada, the U.K., Ireland, and Australia, with peaks during the summer and troughs during the winter. For New Zealand, the seasonal trend was statistically significant only for the term “plantar fasciitis”, while a similar trend for the term “heel pain” was present without achieving statistical significance for seasonality. This seasonality is thought to be related to more frequent occurrence of plantar fasciitis due to increased physical activity of people during the warmer months. In this study, the search query data using the terms “plantar fasciitis” and “heel pain” on Google Trends show significant seasonal variation across several countries, with a peak in the summer and a trough in the winter.

Seasonal Trends in Suicide Attempts-Keywords Related Searches: A Google Trends Analysis

“…This investigation addresses a critical gap in understanding the relationship between the volume of suicide attempts-related Google searches and national suicide attempt rates. Another novelty of this study is that the database of analyzed words is significantly larger than those used in other studies leveraging Google Trends for suicide research [14,24] or infodemiology in general [13,15].…”

“…Google Trends has been used in many different infodemiology studies for analysis [8,[12][13][14][15]. It has also revealed correlations between the frequency of certain search phrases and mental health conditions and addiction rates [12].…”