Internet-based studies are widely used in social and behavioral health research, yet bots and fraud from "survey farming" bring significant threats to data integrity. For research centering marginalized communities, data integrity is an ethical imperative, as fraudulent data at a minimum poses a threat to scientific integrity, and worse could even promulgate false, negative stereotypes about the population of interest. Using data from two online surveys of sexual and gender minority populations (young men who have sex with men and transgender women of color), we (a) demonstrate the use of online survey techniques to identify and mitigate internet-based fraud, (b) differentiate techniques for and identify two different types of "survey farming" (i.e., bots and false responders), and (c) demonstrate the consequences of those distinct types of fraud on sample characteristics and statistical inferences, if fraud goes unaddressed. We provide practical recommendations for internet-based studies in psychological, social, and behavioral health research to ensure data integrity and discuss implications for future research testing data integrity techniques. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

中文翻译：

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在线世界中的数据完整性：在两项针对边缘人群的在线社会和行为研究中演示多模式机器人筛选工具以及维护数据完整性的注意事项。


基于互联网的研究广泛应用于社会和行为健康研究，但“调查农业”中的机器人和欺诈行为给数据完整性带来了重大威胁。对于以边缘化社区为中心的研究来说，数据完整性是一项道德要求，因为欺诈性数据至少会对科学完整性构成威胁，更糟糕的是甚至可能传播关于相关人群的错误、负面的刻板印象。利用对性少数群体（男男性行为的年轻男性和有色人种变性女性）进行的两项在线调查的数据，我们 (a) 展示了如何使用在线调查技术来识别和减少基于互联网的欺诈，(b)区分技术并识别两种不同类型的“调查农业”（即机器人和虚假响应者），以及 (c) 证明如果欺诈行为得不到解决，这些不同类型的欺诈行为对样本特征和统计推论的影响。我们为心理、社会和行为健康研究中基于互联网的研究提供实用建议，以确保数据完整性并讨论对未来研究测试数据完整性技术的影响。 （PsycInfo 数据库记录 (c) 2024 APA，保留所有权利）。