From Doubt to Confidence—Overcoming Fraudulent Submissions by Bots and Other Takers of a Web-Based Survey
2024

Overcoming Fraudulent Submissions in Web-Based Surveys

Sample size: 1624 publication 10 minutes Evidence: moderate

Author Information

Author(s): Andrew Coristine, Yanping Duan, Elyse R Park, Jeffrey J Hardesty, Elizabeth Crespi, Joshua K Sinamo, Qinghua Nian, Alison Breland, Thomas Eissenberg, Ryan David Kennedy, Joanna E Cohen

Primary Institution: Johns Hopkins University

Hypothesis

How can researchers effectively mitigate fraudulent submissions in web-based surveys?

Conclusion

The study successfully implemented various strategies to improve data integrity and reduce fraudulent submissions in web-based surveys.

Supporting Evidence

  • Only 22.4% of the initial survey completions were likely valid.
  • Mitigation strategies included personal record verification and CAPTCHA.
  • Five waves of data collection were completed without additional threats.

Takeaway

This study shows how researchers can make sure that the answers they get from online surveys are real and not from people trying to cheat.

Methodology

The study involved a longitudinal web-based survey with multiple waves of data collection, focusing on adults who frequently use e-cigarettes.

Potential Biases

The study may have introduced sampling bias by primarily recruiting from online platforms.

Limitations

The study's reliance on self-reported data and the potential for sampling bias due to recruitment methods.

Participant Demographics

Adults aged 21 years and older who frequently use e-cigarettes.

Digital Object Identifier (DOI)

10.2196/60184

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