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Data or Deception: Imposter Participants in Online Qualitative Research.
Paul Sharp1,2, Nina Gao2, Matthew Sha2
1School of Health Sciences, University of New South Wales, Sydney, NSW, Australia.
Qualitative Health Research
|February 28, 2026
Summary
Online qualitative research faces challenges from "imposter participants" seeking honoraria, risking data integrity and increasing administrative burdens. Strategies are needed to detect and deter these individuals while ensuring inclusive participant recruitment.
Area of Science:
- Qualitative Research Methods
- Online Data Collection
- Research Ethics
Background:
- Online recruitment and data collection in qualitative research surged during the COVID-19 pandemic, offering cost and time efficiencies.
- The rise of online methods introduced risks, notably 'imposter participants' motivated by study honoraria.
- These imposters create administrative burdens and threaten data integrity and equitable sampling.
Purpose of the Study:
- To explore the challenges and strategies related to identifying and managing 'imposter participants' in online qualitative research.
- To provide insights from a Canadian photovoice study on men's mental health and peer support.
- To address the impact of imposter participants on data integrity, researcher workload, and institutional security.
Main Methods:
- Analysis of experiences from an online Canadian photovoice study.
- Thematic exploration of challenges including detecting imposters, screening for authenticity, and researcher strain.
- Review of technological tools, human strategies, and ethical considerations for participant screening.
Main Results:
- 'Imposter participants' pose significant risks to data integrity and increase project costs in online qualitative research.
- Effective detection and deterrence require a combination of technological tools and human-centered strategies.
- Balancing participant screening for authenticity with inclusivity is crucial to avoid excluding eligible individuals.
Conclusions:
- The prevalence of imposter participants necessitates robust strategies for detection, deterrence, and researcher support.
- University systems require upgrades for improved security and risk management against AI-generated scams.
- Addressing researcher strain and fatigue is vital for maintaining the quality and ethical conduct of online qualitative research.
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