Impact on online research on celebrities' uncommon diseases: the curious case of Justin Bieber and Ramsay Hunt syndrome.
Aim: We investigated how to use Internet user searches to gauge the impact of a celebrity illness on global public interest. Methods: The study design is cross-sectional. Data on Internet searches were obtained from Google Trends (GT) for the period between 2017–2022 using the search words "Ramsay H...
| Published in: | Journal of Public Health: From Theory to Practice (2198-1833) Vol. 32; no. 9; pp. 1707 - 1716 |
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| Main Authors: | , , |
| Format: | Article |
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Springer Nature
Sep2024
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| Subjects: | |
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=180518227&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 180518227 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 21981833 NENI jtl: Journal of Public Health: From Theory to Practice (2198-1833) issn: 21981833 maglogo: N pubinfo: dt: Sep2024 vid: 32 iid: 9 pid: 237 pub: Springer Nature artinfo: ui: 180518227 10.1007/s10389-023-01940-2 ppf: 1707 ppct: 9 formats: tig: atl: Impact on online research on celebrities' uncommon diseases: the curious case of Justin Bieber and Ramsay Hunt syndrome. aug: au: Santangelo, Omar Enzo Gianfredi, Vincenza Provenzano, Sandro affil: https://ror.org/054x2er76 Regional Health Care and Social Agency of Lodi, ASST Lodi, piazza Ospitale 10, 26900, Lodi, Italy https://ror.org/00wjc7c48 Department of Biomedical Sciences for Health, University of Milan, Via Pascal, 36, 20133, Milan, Italy Local Health Unit of Trapani, ASP Trapani, 91100, Trapani, Italy su: Cross-sectional method Social media Health Consumer attitudes Information resources Internet Information-seeking behavior Herpes zoster Pearson correlation (Statistics) Data analysis Medical informatics Descriptive statistics Information storage & retrieval systems Statistics Data analysis software sug: subj: Cross-sectional method Social media Health Consumer attitudes Information resources Internet Information-seeking behavior Internet Publishing and Broadcasting and Web Search Portals Wired Telecommunications Carriers Herpes zoster Pearson correlation (Statistics) Data analysis Medical informatics Descriptive statistics Information storage & retrieval systems Statistics Data analysis software keyword: Celebrities Global public interest Google trends Medical informatics computing Ramsay Hunt syndrome Wikipedia Celebrities Global public interest Google trends Medical informatics computing Ramsay Hunt syndrome Wikipedia ab: Aim: We investigated how to use Internet user searches to gauge the impact of a celebrity illness on global public interest. Methods: The study design is cross-sectional. Data on Internet searches were obtained from Google Trends (GT) for the period between 2017–2022 using the search words "Ramsay Hunt syndrome" (RHS), "Ramsay Hunt syndrome type 2," "Herpes zoster," and "Justin Bieber." The frequency of specific page views for "Ramsay Hunt syndrome," "Ramsay Hunt syndrome type 1," Ramsay Hunt syndrome type 2," Ramsay Hunt syndrome type 3," "Herpes zoster," and "Justin Bieber" were collected via a Wikipedia analysis tool that shows the number of times a specific page is viewed. Statistical analyses were performed using the Pearson (r) and Spearman's rank correlation coefficient (rho). Results: GT data, in 2022, show a strong correlation for Justin Bieber and RHS or RHS type 2 (r = 0.75); similarly, Wikipedia data show a strong correlation for Justin Bieber and the others explored terms (r > 0.75). Furthermore, the correlation was strong between GT and Wikipedia for RHS (rho = 0.89) and RHS type 2 (rho = 0.88). Conclusions: The peak search times for the GT and Wikipedia pages were during the same period. Useful new tools and analyses of Internet traffic data may be effective in assessing the impact of announced celebrity uncommon illnesses on global public interest. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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