Lie for a Dime: When Most Prescreening Responses Are Honest but Most Study Participants Are Impostors
SOCIAL PSYCHOLOGICAL AND PERSONALITY SCIENCE(2017)
摘要
The Internet has enabled recruitment of large samples with specific characteristics. However, when researchers rely on participant self-report to determine eligibility, data quality depends on participant honesty. Across four studies on Amazon Mechanical Turk, we show that a substantial number of participants misrepresent theoretically relevant characteristics (e.g., demographics, product ownership) to meet eligibility criteria explicit in the studies, inferred by a previous exclusion from the study or inferred in previous experiences with similar studies. When recruiting rare populations, a large proportion of responses can be impostors. We provide recommendations about how to ensure that ineligible participants are excluded that are applicable to a wide variety of data collection efforts, which rely on self-report.
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关键词
individual differences,measurement,research methods,gender,consumer behavior,sexuality
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