@文章{信息:doi/10.2196/27385，作者="Card, Kiffer G和Lachowsky, Nathan J和Hogg, Robert S"，标题="使用谷歌趋势来了解同性恋、双性恋和其他与男性发生性行为的男性的人口规模估计和空间分布:概念验证研究"，期刊="JMIR公共卫生监测"，年="2021"，月="11"，日="29"，卷="7"，数="11"，页="e27385"，关键词="同性恋、双性恋和其他与男性发生性行为的男性;空间分布;种群规模估计;色情的;背景:我们必须对数据源进行三角测量，以最好地了解边缘人群的空间分布和人口规模，从而使公共卫生领导人能够满足特定人群的需求。现有的种群规模估计技术是困难和有限的。目的:我们试图确定一种被动监测策略，利用互联网和社交媒体来增强、验证和三角测量同性恋、双性恋和其他男男性行为者(gbMSM)的人口规模估计。方法:我们探索谷歌趋势平台，以近似估计gbMSM人口分布的空间异质性。这是通过比较搜索词“同性恋色情片”和搜索词“色情片”的流行程度来完成的。“结果:我们的结果表明，大多数城市的gbMSM人口规模在总人口的2 %到4 %之间，大型城市中心相对于农村或郊区有更高的估计。 This represents nearly a double up of population size estimates compared to that found by other methods, which typically find that between 1{\%} and 2{\%} of the total population are gbMSM. We noted that our method was limited by unequal coverage in internet usage across Canada and differences in the frequency of porn use by gender and sexual orientation. Conclusions: We argue that Google Trends estimates may provide, for many public health planning purposes, adequate city-level estimates of gbMSM population size in regions with a high prevalence of internet access and for purposes in which a precise or narrow estimate of the population size is not required. Furthermore, the Google Trends platform does so in less than a minute at no cost, making it extremely timely and cost-effective relative to more precise (and complex) estimates. We also discuss future steps for further validation of this approach. ", issn="2369-2960", doi="10.2196/27385", url="https://publichealth.www.mybigtv.com/2021/11/e27385", url="https://doi.org/10.2196/27385", url="http://www.ncbi.nlm.nih.gov/pubmed/34618679" }