Cameron S. Kay
Postdoctoral Scholar, Environmental Social Sciences
Bio
Cameron S. Kay is a postdoctoral scholar in the Climate Cognition Lab at Stanford University. His research explores the psychological foundations of antisocial beliefs and behaviours, including why people believe in conspiracy theories, harbour prejudicial beliefs, and gaslight others. To support this work, he develops psychometrically sound scales and tools for improving data quality. Before joining Stanford, Cameron was a visiting assistant professor at Union College in Upstate New York. He earned his PhD in psychology with a specialization in quantitative research methods at the University of Oregon, where he also completed master’s degrees in psychology and journalism. He holds a BA in psychology from the University of British Columbia.
Professional Education
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Ph.D., University of Oregon, Psychology (2023)
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M.S., University of Oregon, Psychology (2018)
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M.A., University of Oregon, Journalism (2018)
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B.A., University of British Columbia, Psychology (2015)
https://orcid.org/0000-0002-5210-427XAll Publications
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Why you shouldn't trust data collected on MTurk.
Behavior research methods
2025; 57 (12): 340
Abstract
Several prior studies have used advanced methodological techniques to demonstrate that there is an issue with the quality of data that can be collected on Amazon's Mechanical Turk (MTurk). The goal of the present project was to provide an accessible demonstration of this issue. We administered 27 semantic antonyms-pairs of items that assess clearly contradictory content (e.g., "I talk a lot" and "I rarely talk")-to samples drawn from Connect (N1 = 100), Prolific (N2 = 100), and MTurk (N3 = 400; N4 = 600). Despite most of these item pairs being negatively correlated on Connect and Prolific, over 96% were positively correlated on MTurk. This issue could not be remedied by screening the data using common attention check measures nor by recruiting only "high-productivity" and "high-reputation" participants. These findings provide clear evidence that data collected on MTurk simply cannot be trusted.
View details for DOI 10.3758/s13428-025-02852-7
View details for PubMedID 41214376
View details for PubMedCentralID 11539472
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Antecedents and consequences of COVID-19 conspiracy beliefs: A systematic review.
Social science & medicine (1982)
2022; 301: 114912
Abstract
RATIONALE: Belief in COVID-19 conspiracy theories can have severe consequences; it is therefore crucial to understand this phenomenon, in its similarities with general conspiracy belief, but also in how it is context-dependent.OBJECTIVE: The aim of this systematic review is to provide a comprehensive overview of the available research on COVID-19 conspiracy beliefs and to synthesise this research to make it widely accessible.METHODS: We present a synthesis of COVID-19 conspiracy belief research from 85 international articles, identified and appraised through a systematic review, in line with contemporary protocols and guidelines for systematic reviews.RESULTS: We identify a number of potential antecedents of COVID-19 conspiracy beliefs (individual differences, personality traits, demographic variables, attitudes, thinking styles and biases, group identity, trust in authorities, and social media use), their consequences (protective behaviours, self-centred and misguided behaviours such as hoarding and pseudoscientific health practices, vaccination intentions, psychological wellbeing, and other negative social consequences such as discrimination and violence), and the effect sizes of their relations with the conspiracy beliefs.CONCLUSIONS: We conclude that understanding both the potential antecedents and consequences of conspiracy beliefs and how they are context-dependent is highly important to tackle them, whether in the COVID-19 pandemic or future threats, such as that of climate change.
View details for DOI 10.1016/j.socscimed.2022.114912
View details for PubMedID 35354105