Bots and nots: Safeguarding online survey research with underrepresented and diverse populations

The COVID-19 pandemic has intensified the use of online recruitment and data collection for reaching historically underrepresented minorities (URMs) and other diverse groups. Preventing and detecting responses from automated accounts "bots" and those who misrepresent themselves is one challenge in utilizing online approaches. Through internet-mediated methods, interested LGBTQ+ and non-LGBTQ+ couples facing advanced cancer completed an interest form via REDCap®. Eligible participants received a direct link to electronic consent and surveys in REDCap®. Once responses to the interest form (N = 619) were received, the study PI: 1) assessed participants' entries and non-response survey data (time of completion, rate of recruitment, etc.), 2) temporarily postponed recruitment, 3) sent eligibility questionnaires, consent documents, and validated surveys to N= 10 couples and scrutinized these data for suspicious patterns or indications of untrustworthy data, 4) responded to potential participants via email, and 5) implemented additional strategies for detecting and preventing untrustworthy survey responses. Investigators must consider multi-step eligibility screening processes to detect and prevent the collection of untrustworthy data. Investigators' reliance on internet-mediated approaches for conducting research with diverse, hard-to-reach populations increases the importance of addressing threats to data validity. Ultimately, safeguarding internet-mediated research supports research accessibility and inclusion for URMs while also protecting participant data integrity.