Detecting and Mitigating Fraudulent Participation: Lessons Learned from a Mixed Methods Study

A surge in social media research recruitment has led to increased fraudulent participation, impacting studies such as our sequential mixed methods research (MMR) study on peer loneliness among adolescents with chronic pain during COVID-19. The purpose of this paper is to describe the challenges and subsequent strategies implemented to prevent and identify fraudulent participants during a MMR study that used online data collection methods. The results of the various mitigation strategies implemented are provided along with recommendations for future research. This article makes a valuable contribution to MMR literature by highlighting the threat to data integrity and detailing various mitigation strategies for different phases of MMR. These strategies should be proactively implemented by researchers to increase data integrity.

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Publication Details

Journal
Journal of Mixed Methods Research
Published
2026-01-20
DOI
https://doi.org/10.1177/15586898261416725
Primary Topic
Social Media in Health Education
Type
article
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Detecting and Mitigating Fraudulent Participation: Lessons Learned from a Mixed Methods Study

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Journal of Mixed Methods Research
Social Media in Health Education
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Detecting and Mitigating Fraudulent Participation: Lessons Learned from a Mixed Methods Study

Bruce D. Dick, Rachel Kelly, Paula Forgeron, Delane Linkiewich, Michelle Lamont, Sina Negarandeh, Abbie Jordan, Jennifer N. Stinson, Verena Kantere
article en

Abstract

A surge in social media research recruitment has led to increased fraudulent participation, impacting studies such as our sequential mixed methods research (MMR) study on peer loneliness among adolescents with chronic pain during COVID-19. The purpose of this paper is to describe the challenges and subsequent strategies implemented to prevent and identify fraudulent participants during a MMR study that used online data collection methods. The results of the various mitigation strategies implemented are provided along with recommendations for future research. This article makes a valuable contribution to MMR literature by highlighting the threat to data integrity and detailing various mitigation strategies for different phases of MMR. These strategies should be proactively implemented by researchers to increase data integrity.

Journal of Mixed Methods Research
University of Ottawa (CA), University of Alberta (CA), University of Toronto (CA), Hospital for Sick Children (CA), University of Bath (GB), University of Guelph (CA)
Peace, Justice and strong institutions
Openalex Percentile: Top 87%
Social Media in Health Education
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