Methods to reduce fraudulent participation and highlight autistic voices in research.
Add ID check, slow open questions, and a brief chat to your online sign-up form to block scammers without shutting out autistic responders.
01Research in Context
What this study did
de Jonge et al. (2025) built a fraud-screening recipe for online autism studies. They layered three checks: verify ID, ask open questions with no time limit, then run a short follow-up interview.
The team tested the steps on real applicants. They kept the process autistic-friendly by allowing extra time and typed answers.
What they found
The layered screen caught scammers while letting genuine autistic people through. Quick bots and repeat applicants dropped out early. Thoughtful responders moved on.
Autistic participants said the format felt respectful and clear.
How this fits with other research
Pellicano et al. (2024) first waved the red flag. Their letter told of fake respondents slipping into three online autism studies. E et al. answer that warning with a ready-to-use fix.
Cascio et al. (2020) said research must keep autistic voices central. The new screen honors that goal by giving flexible response options instead of harsh cut-offs.
Scior et al. (2023) warned that big autism data sets can rot if quality checks are weak. E et al. show a small-scale check that stops one big threat before it enters the spreadsheet.
Why it matters
If you run online surveys, parent interviews, or remote preference assessments, stolen data wastes grant money and skews results. Plug this low-cost screen into your Qualtrics or REDCap flow. You will spend ten extra minutes per participant and save weeks of bad data cleanup later.
Want CEUs on This Topic?
The ABA Clubhouse has 60+ free CEUs — live every Wednesday. Ethics, supervision & clinical topics.
Join Free →Insert one untimed open question into your next online form and keep the link open for 48 hours.
02At a glance
03Original abstract
Alongside the rise in online qualitative research, fraudulent representation of research participants is increasing, and current strategies to address this issue within studies of non-neurodiverse samples may exclude autistic voices. Seeking to reduce fraudulent or "scammer" participation in our focus group study, and increase data validity and expenditure efficiency, we implemented strategies suggested in the literature and tested additional strategies. This research adds to the growing conversation around best practices for reducing scammers in autism research using online methods by (1) providing data evaluating the utility of existing strategies; (2) testing emerging strategies; and (3) discussing ethical dilemmas involved in addressing scammers in studies. We received over 200 expressions of interest and the established strategies suggested in the literature plus emerging strategies proved critical for mitigating the enrollment of scammers in focus groups. Protecting the integrity of data about human subjects from fraud is essential for rigorous autism research; trustworthy conclusions cannot be otherwise drawn from analysis. However, the strategies inherently require subjective decision-making that could systematically exclude participants with more limited or atypical communication and result in unfair subject selection. Procedures we recommend incur resources and are time consuming but are beneficial to ensure data integrity and inclusivity.Lay abstractOver the last decade, especially since the pandemic, more research has been happening online. Conducting research online can create opportunities to include autistic people across the world and make our studies more diverse. However, conducting research online had led to scammers, or people pretending to be autistic, participating in autism research studies. Strategies to stop scammers may accidentally leave out autistic people who have difficulty with processing time and open-ended questions. We tried out documented strategies to stop scammers from participating in autism research. We also tested new strategies to understand how helpful they are. Using these strategies, we suspected over 100 people who wanted to participate were scammers and did not invite them to participate. As researchers, we must ensure we stop scammers from participating in our studies. It's important to highlight autistic voices and guarantee we get accurate results. However, the strategies to identify scammers may also leave out autistic people who have communication differences. This is unfair and could also make our results less reliable. The existing and new strategies to stop scammers take a lot of time and resources but they're worth it to make sure our data are reliable, and include only autistic voices.
Autism : the international journal of research and practice, 2025 · doi:10.1177/13623613241298037