Maintenance Notice

Due to necessary scheduled maintenance, the JMIR Publications website will be unavailable from Monday, March 11, 2019 at 4:00 PM to 4:30 PM EST. We apologize in advance for any inconvenience this may cause you.

Who will be affected?

Advertisement

Currently submitted to: Journal of Medical Internet Research

Date Submitted: Jun 8, 2019
Open Peer Review Period: Jun 11, 2019 - Aug 6, 2019
(currently open for review)

Headache and Rhinitis: A 15-Year Long Content Analysis in a Search Engine Query Data

  • Diego Swerts; 
  • Mario Peres; 
  • Guilherme Barbosa

ABSTRACT

Background:

There has been an increase in search engine data being used in healthcare research being an important tool for a better understanding of the epidemiology of diseases, a guide for public policies and increasingly inserted in decision making. Our study aims to study the relationship between headache and rhinitis, through Google Trends, a Google search tool, seeking to better understand the temporal distribution of these pathologies in Brazil during the last 15 years. In addition, we sought to analyze the correlation between these conditions.

Objective:

: Headaches and sinus disorders have been linked in several ways. Rhinitis – commonly referred to as hay fever - and chronic headaches are both highly common conditions that coexist in the general world population. In order to shed light into the mechanisms between headache and rhinitis, using a digital epidemiology methodology, we aimed to investigate the correlation between the two terms and their temporal pattern in a search engine database.

Methods:

On January 8th, 2019, we queried the Google Trends website for the terms ‘rinite’ and ‘dor de cabeça,’limiting the search region to Brazil and other Portuguese-speaking countries. Data was obtained for every month from January 2004 to December 2018, and then extracted to a csv, Microsoft Excel file. After the descriptive analysis by dispersion diagrams, the Pearson test was performed to evaluate the correlation between the volume of research on rhinitis, headache and Alzheimer's disease, which was included as a control group. A linear regression model was used to predict the volume of searches for the term headache from the term rhinitis, with a 95% confidence interval. Finally, we analyzed the seasonality of rhinitis research volume.

Results:

: As a result, we found that the Pearson coefficient for rhinitis and headache was 0.80 indicating a strong correlation in the time interval analyzed. On the other hand, the test result for Alzheimer's and headache and rhinitis was respectively -0.18 and -0.09, indicating a very low correlation. The regression model showed that the increase in rhinitis volume increased by 2.69 the volume of headache. In addition we note seasonality in the volume of research of the term rhinitis, we noticed that the peaks of research volume tend to concentrate in the month of May, with the smaller volumes of research concentrating during the months of spring and early summer, and in the autumn (months of May and June) this volume of research increases. Finally, we note an increase in the research volume of the term headache, which may suggest an increase in the burden of this pathology.

Conclusions:

Headaches and rhinitis were significantly correlated in 15 years of Google Search query data, where a circannual variation could be observed with both conditions. Further studies using digital search engine query data may be useful for better understanding of comorbidity in headache disorders and possible treatments.


 Citation

Please cite as:

Swerts D, Peres M, Barbosa G

Headache and Rhinitis: A 15-Year Long Content Analysis in a Search Engine Query Data

JMIR Preprints. 08/06/2019:14942

DOI: 10.2196/preprints.14942

URL: https://preprints.jmir.org/preprint/14942


Request queued. Please wait while the file is being generated. It may take some time.

© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.