Related Experiment Video
Updated: Jul 17, 2025
Generation of Electronic Cigarette Aerosol by a Third-Generation Machine-Vaping Device: Application to Toxicological Studies
Published on: August 25, 2018
Online Interest for Electronic Cigarettes Using Google Trends in the UK: A Correlation Analysis
Zainah Sindhoo1, Shayaan Sindhoo2, Abhishek Ghosh3
1Lincoln Medical School, Universities of Nottingham and Lincoln, Nottingham, UK.
Background:
Google Trends provides an easily accessible and cost-effective method of providing real-time insight into user interest.
Objective:
to address the gap in UK prevalence data for e-cigarettes by analyzing Google Trends to identify correlations with official data from Action on Smoking and Health. The study further evaluates Google Trend's sensitivity to real-time events and the ability for predictive models to forecast future data based on Google Trends.
Methods:
UK Google Trends data from 2012 to 2021 was analyzed to assess (a) the most popular electronic nicotine device terminology; (b) statistically significant points in time; (c) correlations between Relative Search Volumes and official reports on electronic cigarette use and (d) whether Google Trends could predict future patterns in data. These were achieved using Locally Weighted Scatterplot Smoothing regression, Pruned Exact Linear Time Method, cross correlation, and Autoregressive Integrated Moving Average algorithms respectively.
Results:
"Vape" was revealed to be the most popular electronic nicotine device terminology with a correlation coefficient greater than +0.9 when compared to official electronic cigarette consumption data within a one-year timescale (lag 0). Results from ARIMA modeling were varied with the algorithms forecasted trends line occasionally lying outside of a 95% prediction interval.
Conclusion:
Google Trends may correspond to population-based prevalence of electronic cigarette use. The changing trends coincide with changing policy decisions. Google Trends based prediction for online interest in electronic cigarettes requires further validation so should currently be used in conjunction with other traditional methods of data collections.
More Related Videos
10:44Comparing the Effects of Electronic Cigarette Vapor and Cigarette Smoke in a Novel In Vivo Exposure System
Published on: May 24, 2017
09:30A Microcontroller Operated Device for the Generation of Liquid Extracts from Conventional Cigarette Smoke and Electronic Cigarette Aerosol
Published on: January 18, 2018
Related Concept Videos
01:25Statistical Methods for Analyzing Epidemiological Data
01:29Stimulants
Cocaine can be administered via snorting, injection, or smoking. It primarily functions by blocking the reuptake of dopamine, resulting in a euphoric high characterized by an intense sensation of happiness and...
01:25Correlation between ECG and Cardiac Cycle
A cardiac action potential originates in the SA node and spreads throughout the atria and the AV node in approximately 0.03 seconds. This results in the P wave in an ECG and triggers atrial contraction. The action potential is then briefly slowed at the AV node, allowing the atria to contract and fill the ventricles with blood before...
01:15Drug Concentration Versus Time Correlation
Two pivotal parameters are the minimum effective concentration (MEC) and the minimum toxic concentration (MTC). The MEC is the...
01:11Observational Studies
There are three types of observational studies – Prospective, retrospective, and cross-sectional.
Prospective Study
Prospective studies, also known as longitudinal or cohort studies, are carried out by collecting future data from groups sharing similar characteristics. One...
01:23Correlation of Experimental Data
For example, a spherical particle moving through a viscous fluid experiences drag. Dimensional analysis shows that the drag force depends on the particle's diameter, velocity,...