Geolocation to Identify Online Study-Eligible Gay, Bisexual, and Men who have Sex with Men in Philadelphia, Pennsylvania.
Geolocation to Identify Online Study-Eligible Gay, Bisexual, and Men who have Sex with Men in Philadelphia, Pennsylvania.
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通过地理定位来识别宾夕法尼亚州费城符合在线研究资格的同性恋、双性恋和男男性行为者。
DOI：
10.1097/ede.0000000000001607
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发表时间：
2023
期刊：
影响因子：
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通讯作者：
Goldstein,NealD
中科院分区：
文献类型：
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作者：
Tran,NguyenK;Welles,SethL;Goldstein,NealD
背景：排除机器人生成的响应的数据收集和清理程序用于维护在线调查样本的数据完整性。然而，这些程序可能很耗时，而且难以执行。因此，我们的目标是评估一个单步地理定位算法的有效性，招募合格的同性恋，双性恋，和男人谁与男人发生性关系在Philadelphia for an online study.Methods：我们使用了一个4步的方法，根据常见的做法，用于评估机器人生成的和欺诈性的反应，以评估参与者的Qualtrics调查数据作为我们的参考标准的有效性。然后，我们将其与Qualtrics的单步地理定位算法进行了比较，该算法使用MaxMind商业数据库将参与者的互联网协议地址映射到他们的大致位置。我们计算的灵敏度，特异性，阳性预测值（PPV），和阴性预测值（NPV）的一步地理定位方法相对于4-step approach.Results：有826受访者完成了调查，440（53%）有资格登记的基础上的4-step approach。单步地理定位方法的灵敏度为91%（95% CI= 88%，93%），特异性为79%（95% CI= 74%，83%），PPV为83%（95% CI= 80%，86%），NPV为88%（95% CI= 85%，91%）。仅地理位置就提供了与4-这两种方法都可能导致额外的错误分类。研究人员可能需要考虑多种程序来确保在线样本的数据完整性。
Background:Data collection and cleaning procedures to exclude bot-generated responses are used to maintain the data integrity of samples from online surveys. However, these procedures may be time-consuming and difficult to implement. Thus, we aim to evaluate the validity of a single-step geolocation algorithm for recruiting eligible gay, bisexual, and men who have sex with men in Philadelphia for an online study.Methods:We used a 4-step approach, based on common practices for evaluating bot-generated and fraudulent responses, to assess the validity of participants’ Qualtrics survey data as our referent standard. We then compared it to Qualtrics’ single-step geolocation algorithm that used the MaxMind commercial database to map participants’ Internet protocol address to their approximate location. We calculated the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the single-step geolocation approach relative to the 4-step approach.Results:There were 826 respondents who completed the survey and 440 (53%) were eligible for enrollment based on the 4-step approach. The single-step geolocation approach yielded a sensitivity of 91%(95% CI= 88%, 93%), specificity of 79%(95% CI= 74%, 83%), PPV of 83%(95% CI= 80%, 86%), and NPV of 88%(95% CI= 85%, 91%).Conclusions:Geolocation alone provided a moderately high level of agreement with the 4-step approach for identifying geographically eligible participants in the online sample, but both approaches may be subject to additional misclassification. Researchers may want to consider multiple procedures to ensure data integrity in online samples.