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Online Interest for Electronic Cigarettes Using Google Trends in the UK: A Correlation Analysis.
Sindhoo, Zainah; Sindhoo, Shayaan; Ghosh, Abhishek; Kaur, Simranjit; Soyiri, Ireneous; Ahmadi, Keivan.
Afiliação
  • Sindhoo Z; Lincoln Medical School, Universities of Nottingham and Lincoln, Nottingham, UK.
  • Sindhoo S; Imperial College London, London, UK.
  • Ghosh A; Department of Psychiatry, Postgraduate Institute Medical Education and Research, Chandigarh, India.
  • Kaur S; Department of Computer Science and Engineering, Thapar Institute of Engineering and Technology, Patiala, Punjab, India.
  • Soyiri I; University of Hull, Hull, UK.
  • Ahmadi K; Department of Primary Care and Public Health, School of Public Health, Faculty of Medicine, Imperial College London, NIHR Applied Research Collaboration Northwest London (ARC NWL), London, UK.
Subst Use Misuse ; 58(14): 1791-1797, 2023.
Article em En | MEDLINE | ID: mdl-37671780
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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Sistemas Eletrônicos de Liberação de Nicotina Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans País/Região como assunto: Europa Idioma: En Revista: Subst Use Misuse Assunto da revista: TRANSTORNOS RELACIONADOS COM SUBSTANCIAS Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Sistemas Eletrônicos de Liberação de Nicotina Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans País/Região como assunto: Europa Idioma: En Revista: Subst Use Misuse Assunto da revista: TRANSTORNOS RELACIONADOS COM SUBSTANCIAS Ano de publicação: 2023 Tipo de documento: Article