Re‐Thinking the Imposter Participant: Online Research Methods, Ethics, <scp>AI</scp> and Trust

ABSTRACT Imposter participants are participants who falsely claim to meet inclusion criteria. They are an increasingly recognised issue in the interdisciplinary methods literature, an issue which has been exacerbated by the development of online research methods. This existing work recognises imposter participants as a frustration in the research process and provides important interventions that raise awareness and provide strategies of detection and prevention. However, this paper flips the dominant narrative in academia on fraudulent, imposter or ‘fake’ participants. Drawing on the authors' experience of imposter participants and Generative AI in online methods, this paper provides a series of ethical arguments around incentives, trust and power imbalances. The paper provides a critical lens through which to examine wider questions of trust in online research, making wider contributions to debates on research methods and ethics. Indeed, the paper argues that imposter participants raise urgent questions, not just for the validity and research integrity of individual projects, but for revealing wider structural inequalities and how to potentially navigate this going forward.

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Published
2026-05-18
DOI
https://doi.org/10.1111/area.70123
Primary Topic
Focus Groups and Qualitative Methods
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article
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article

Re‐Thinking the Imposter Participant: Online Research Methods, Ethics, AI and Trust

Sophie Cranston, Sarah Mills, Ellie Moore, David Maidment et al.
Area
Focus Groups and Qualitative Methods
article

Re‐Thinking the Imposter Participant: Online Research Methods, Ethics, AI and Trust

Sophie Cranston, Sarah Mills, Ellie Moore, David Maidment, Masa Nooh, Rosanna Cant
article en

Abstract

ABSTRACT Imposter participants are participants who falsely claim to meet inclusion criteria. They are an increasingly recognised issue in the interdisciplinary methods literature, an issue which has been exacerbated by the development of online research methods. This existing work recognises imposter participants as a frustration in the research process and provides important interventions that raise awareness and provide strategies of detection and prevention. However, this paper flips the dominant narrative in academia on fraudulent, imposter or ‘fake’ participants. Drawing on the authors' experience of imposter participants and Generative AI in online methods, this paper provides a series of ethical arguments around incentives, trust and power imbalances. The paper provides a critical lens through which to examine wider questions of trust in online research, making wider contributions to debates on research methods and ethics. Indeed, the paper argues that imposter participants raise urgent questions, not just for the validity and research integrity of individual projects, but for revealing wider structural inequalities and how to potentially navigate this going forward.

AreaVol. 58(2)
Loughborough University (GB), Loughborough College (GB)
Reduced inequalities
Openalex Percentile: Top 3%
Focus Groups and Qualitative Methods
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