Toothpaste-related interests of Google users from different countries Article Swipe
Bruna Di Profio
,
Matheus Lotto
,
Patricia Estefanía Ayala Aguirre
,
Cristina Cunha Villar
,
Giuseppe Alexandre Romito
,
Mariana Minatel Braga
,
Thiago Cruvinel
,
Cláudio Mendes Pannuti
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1590/1807-3107bor-2023.vol37.0124
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1590/1807-3107bor-2023.vol37.0124
The Internet is a growing source of knowledge and can provide information about oral health. This ecological study aimed to characterize the interests in toothpaste among Google users from different countries. Our hypothesis was that there would be an increase in Google users' interest in information about toothpaste. This retrospective longitudinal ecological study analyzed the toothpaste-related interest of Google users from 10 countries between January 2004 and December 2020. The monthly variation in relative search volume (RSV) and the main related queries were determined using Google Trends. Autoregressive integrated moving average (ARIMA) forecasting models were built to establish the predictive RSV values for toothpaste for an additional 12 months. Autocorrelation plots and the generalized additive model (GAM) were used to diagnose trends and seasonality in RSV curves. Additionally, the influence of social isolation related to the outbreak of COVID-19 was analyzed. Although not detected by autocorrelation function (ACF) and partial autocorrelation function (PACF) analyses, the heuristic analysis showed an increase in the interest in toothpaste-related information in all countries, with a stable trend observed in the 12-month forecasts, except for the increases in the United Kingdom and South Africa. Also, GAM analyses demonstrated a non-significant monthly or quarterly seasonal influence on data. In addition, social isolation during the COVID-19 pandemic did not influence the online information-seeking behavior of Google Search users linked to this topic. We confirmed the hypothesis that the interest of Google Search users in information about toothpaste increased in all of the 10 assessed countries.
Related Topics
Concepts
Toothpaste
Autoregressive integrated moving average
Partial autocorrelation function
Demography
Coronavirus disease 2019 (COVID-19)
Generalized additive model
Pandemic
Geography
Advertising
Medicine
Business
Statistics
Mathematics
Sociology
Disease
Pathology
Dentistry
Time series
Infectious disease (medical specialty)
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1590/1807-3107bor-2023.vol37.0124
- https://www.scielo.br/j/bor/a/bbyMkcgZCY9LnPSHdjGN6wp/?lang=en&format=pdf
- OA Status
- diamond
- Cited By
- 3
- References
- 37
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4389782467
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4389782467Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1590/1807-3107bor-2023.vol37.0124Digital Object Identifier
- Title
-
Toothpaste-related interests of Google users from different countriesWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-01-01Full publication date if available
- Authors
-
Bruna Di Profio, Matheus Lotto, Patricia Estefanía Ayala Aguirre, Cristina Cunha Villar, Giuseppe Alexandre Romito, Mariana Minatel Braga, Thiago Cruvinel, Cláudio Mendes PannutiList of authors in order
- Landing page
-
https://doi.org/10.1590/1807-3107bor-2023.vol37.0124Publisher landing page
- PDF URL
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https://www.scielo.br/j/bor/a/bbyMkcgZCY9LnPSHdjGN6wp/?lang=en&format=pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
-
https://www.scielo.br/j/bor/a/bbyMkcgZCY9LnPSHdjGN6wp/?lang=en&format=pdfDirect OA link when available
- Concepts
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Toothpaste, Autoregressive integrated moving average, Partial autocorrelation function, Demography, Coronavirus disease 2019 (COVID-19), Generalized additive model, Pandemic, Geography, Advertising, Medicine, Business, Statistics, Mathematics, Sociology, Disease, Pathology, Dentistry, Time series, Infectious disease (medical specialty)Top concepts (fields/topics) attached by OpenAlex
- Cited by
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3Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1, 2024: 2Per-year citation counts (last 5 years)
- References (count)
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37Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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