SESSION KEYWORDS: Bots, Scammers, Fraudulent research participants, Sham participants, Recruitment

SESSION ABSTRACT

Aim: To share collaborative methods of mitigating bots, scammers and sham research participation in health research between research teams and Research Ethics Boards (REB). Background: The use of social media recruitment is becoming increasingly popular, especially as we emerge from the COVID-19 pandemic period when most research required novel strategies to recruit participants and collect data online. However, as conducting both recruitment and data collection using online platforms increase in popularity, so does the research participation of bots, scammers and sham participants (Godinho et al., 2020; Jones et al., 2021; Ridge et al., 2023; Roehl & Harland, 2022). Our mixed methods study designed to understand the types and impact of peer loneliness amongst adolescents with chronic pain in the context of the COVID-19 pandemic was not immune to sham research participants. The prevalence of bots, scammers and sham participants lead our team to streamline methods to identify these participants and exclude them from both phases of our mixed methods study in order to maintain data quality. Methods: Due to the mixed-method nature of our study, both quantitative and qualitative strategies were developed to deter and screen out non-eligible participants. Our quantitative survey employed strategies suggested by others as well as newly developed ones including: use of Completely Automated Public Turing test to tell Computers and Humans Apart (CAPTCHA), double data verification questions, and data surge screening (Jones et al., 2021). Our qualitative phase, which captured data using individual interviews via Zoom, employed strategies including mandatory use of Zoom cameras throughout the interview, data verification questions, and provision of photo identification prior to initiating the interview. Consultation with the local REB as well as sharing published articles on the topic provided support for the use of some of these processes. Results: As a result of the methods developed to exclude bots, scammers and sham participants, during the quantitative survey phase of the study, participants were excluded by screening for data surges (n = 1, 279), by invalid postal codes (n = 103), by data surges and invalid postal codes (n = 882) and by double data verification questions (n = 53). During the qualitative survey phase of the study, a total of two participants were excluded due to suspected double participation. The corresponding survey data from each of these participants was also removed from the study. Conclusions: In our experience, close collaboration between the research team and the REB was essential in ensuring ethical conduction of the research that allowed for the detection of non-eligible participants and ensured data integrity. Due to the increased prevalence of bots, scammers and sham research participants in health research, continued bilateral education and development of detection strategies between the researchers and REBs are needed to maintain and preserve rigorous data quality.