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Google Trends for Pain Search Terms in the World’s Most Populated Regions Before and After the First Recorded COVID-19 Case: Infodemiological Study

机译:谷歌在第一个录制的Covid-19之前和之后的世界上最具人口最多的地区的痛苦搜索术语趋势:Infodemiological学习

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摘要

BackgroundWeb-based analysis of search queries has become a very useful method in various academic fields for understanding timely and regional differences in the public interest in certain terms and concepts. Particularly in health and medical research, Google Trends has been increasingly used over the last decade. ObjectiveThis study aimed to assess the search activity of pain-related parameters on Google Trends from among the most populated regions worldwide over a 3-year period from before the report of the first confirmed COVID-19 cases in these regions (January 2018) until December 2020. MethodsSearch terms from the following regions were used for the analysis: India, China, Europe, the United States, Brazil, Pakistan, and Indonesia. In total, 24 expressions of pain location were assessed. Search terms were extracted using the local language of the respective country. Python scripts were used for data mining. All statistical calculations were performed through exploratory data analysis and nonparametric Mann–Whitney U tests. ResultsAlthough the overall search activity for pain-related terms increased, apart from pain entities such as headache, chest pain, and sore throat, we observed discordant search activity. Among the most populous regions, pain-related search parameters for shoulder, abdominal, and chest pain, headache, and toothache differed significantly before and after the first officially confirmed COVID-19 cases (for all, P<.001). In addition, we observed a heterogenous, marked increase or reduction in pain-related search parameters among the most populated regions. ConclusionsAs internet searches are a surrogate for public interest, we assume that our data are indicative of an increased incidence of pain after the onset of the COVID-19 pandemic. However, as these increased incidences vary across geographical and anatomical locations, our findings could potentially facilitate the development of specific strategies to support the most affected groups.
机译:背景技术对搜索查询的基于网络分析已成为各种学术领域的一个非常有用的方法,以了解某些条款和概念的公共利益及时和区域差异。特别是在健康和医学研究中,谷歌趋势在过去十年中越来越多地使用。客观的研究旨在评估从全世界最普遍的地区的谷歌趋势的搜索活动,从这些地区第一次确认的Covid-19案件报告(2018年1月)之前的3年期间,直到12月2020.方法研究来自以下地区的术语用于分析:印度,中国,欧洲,美国,巴西,巴基斯坦和印度尼西亚。总共评估了24种疼痛位置的表达。搜索字词是使用相应国家的本地语言提取的。 Python脚本用于数据挖掘。通过探索性数据分析和非参数Mann-Whitney U测试进行所有统计计算。结果虽然与疼痛有关的术语的整体搜索活动增加,但除了头痛,胸痛和喉咙痛等疼痛实体外,我们都观察到不和谐的搜索活动。在最初的肩部,腹部和胸痛,头痛和牙痛的疼痛相关的搜索参数中,在第一个正式证实的Covid-19案例(全部,P <.001)之前和之后的疼痛相关搜索参数显着不同。此外,我们观察到最多人口稠密的地区之间的疼痛相关的搜索参数的异质,显着的增加或减少。结论互联网搜索是一个替代公共利益的代理,我们假设我们的数据表明在Covid-19大流行发生后的疼痛发生率增加。然而,由于这些增加的发病率因地理和解剖地位而异,因此我们的研究结果可能促进制定支持最受影响的群体的具体策略。

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