{"title":"新冠肺炎对谷歌趋势数据分析的影响","authors":"L. Bertolaccini, A. Cara, Gabriele Maffeis, E. Prisciandaro, A. Mazzella, N. Filippi, L. Spaggiari","doi":"10.21037/jmai-22-2","DOIUrl":null,"url":null,"abstract":"Background: In response to the coronavirus disease 2019 (COVID-19) pandemic, the use of Telemedicine has skyrocketed. This study aimed to assess the relationship between the changes in Google relative search volume (RSV) of telehealth and COVID-19 worldwide and in different Italian regions over 18 months during the pandemic. Methods: Data about the Google searches Telemedicine and COVID-19 were analysed (01/12/2019– 31/08/2021). The number of Google searches was measured in RSV (range, 0–100). Results: Mean worldwide RSV was 52.2±17.6 for the Telemedicine and 57.7±19.5 for COVID-19;mean Italian RSV was 17.5±21.6 for the Telemedicine and 42.0±20.0 for COVID-19. The maximum interest for Telemedicine was observed on 16/02/2020, while the maximum interest for COVID-19 was registered on 25/10/2020. The RSV curve of COVID-19 presented two nadirs during the summer periods. On the other hand, the RSV curve of Telemedicine presented a single peak in May 2020. After the peak, interest in Telemedicine continued declining (mean RSV =18). Conclusions: COVID-19 has expanded the use of all telemedicine modalities. Future research is required to improve the understanding of user needs and the effects of Telemedicine on providers at various levels of experience to guide efforts to encourage telemedicine adoption and usage after the COVID-19 pandemic. © Journal of Medical Artificial Intelligence. All rights reserved.","PeriodicalId":73815,"journal":{"name":"Journal of medical artificial intelligence","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The COVID-19 repercussion on Google Trend data analyses\",\"authors\":\"L. Bertolaccini, A. Cara, Gabriele Maffeis, E. Prisciandaro, A. Mazzella, N. Filippi, L. Spaggiari\",\"doi\":\"10.21037/jmai-22-2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Background: In response to the coronavirus disease 2019 (COVID-19) pandemic, the use of Telemedicine has skyrocketed. This study aimed to assess the relationship between the changes in Google relative search volume (RSV) of telehealth and COVID-19 worldwide and in different Italian regions over 18 months during the pandemic. Methods: Data about the Google searches Telemedicine and COVID-19 were analysed (01/12/2019– 31/08/2021). The number of Google searches was measured in RSV (range, 0–100). Results: Mean worldwide RSV was 52.2±17.6 for the Telemedicine and 57.7±19.5 for COVID-19;mean Italian RSV was 17.5±21.6 for the Telemedicine and 42.0±20.0 for COVID-19. The maximum interest for Telemedicine was observed on 16/02/2020, while the maximum interest for COVID-19 was registered on 25/10/2020. The RSV curve of COVID-19 presented two nadirs during the summer periods. On the other hand, the RSV curve of Telemedicine presented a single peak in May 2020. After the peak, interest in Telemedicine continued declining (mean RSV =18). Conclusions: COVID-19 has expanded the use of all telemedicine modalities. Future research is required to improve the understanding of user needs and the effects of Telemedicine on providers at various levels of experience to guide efforts to encourage telemedicine adoption and usage after the COVID-19 pandemic. © Journal of Medical Artificial Intelligence. All rights reserved.\",\"PeriodicalId\":73815,\"journal\":{\"name\":\"Journal of medical artificial intelligence\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of medical artificial intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.21037/jmai-22-2\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of medical artificial intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21037/jmai-22-2","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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