2019
DOI: 10.1007/s00403-019-01921-0
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Seasonal variation in the internet searches for psoriasis

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Cited by 35 publications
(34 citation statements)
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“…Consistent with the recent study by Kardeş,20 which provides additional evidence for seasonality in psoriasis and new research approach for studying seasonal patterns of other dermatological diseases, we also found that public interest in psoriasis through Google search activity presents a seasonal pattern, with peaks in February or March for the northern hemisphere countries and July or August for the southern hemisphere countries. While the pathogenesis of psoriasis remains unknown, several environmental factors have been reported to play a key role in the development of the disease 25.…”
Section: Discussionsupporting
confidence: 91%
See 1 more Smart Citation
“…Consistent with the recent study by Kardeş,20 which provides additional evidence for seasonality in psoriasis and new research approach for studying seasonal patterns of other dermatological diseases, we also found that public interest in psoriasis through Google search activity presents a seasonal pattern, with peaks in February or March for the northern hemisphere countries and July or August for the southern hemisphere countries. While the pathogenesis of psoriasis remains unknown, several environmental factors have been reported to play a key role in the development of the disease 25.…”
Section: Discussionsupporting
confidence: 91%
“…Currently, few studies have investigated the potential role of seasonality in disease development, clinical severity and progression of psoriasis, and a recent study by Kardeş20 has explored the seasonality of psoriasis in a large geographical scale using internet search data. However, a global trend analysis on searches for the query term ‘psoriasis’ as well as the top rising topics is lacking.…”
Section: Introductionmentioning
confidence: 99%
“…Google Trends has been demonstrated as a powerful tool in surveying outbreaks and monitoring public interest [17][18][19][20]. It was used in previous outbreaks including influenza [21][22][23] and Zika virus [24].…”
Section: Introductionmentioning
confidence: 99%
“…A popular tool for big data mining is represented by Google Trends (GT), which allows users to explore oscillations in public interest, by selecting filters on geographical location and time [14]. Owing to these circumstances, it is not surprising that many health-related issues have already been associated with internet-search peaks in recent years to complement traditional data sources [15][16][17][18][19][20][21][22]. Noteworthy, previous studies on nose bleeding and GT suffered from two major methodological shortcomings: First, no systematical approach Electronic supplementary material The online version of this article (https ://doi.org/10.1007/s0040 5-020-05915 -x) contains supplementary material, which is available to authorized users.…”
Section: Introductionmentioning
confidence: 99%