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Accepted for/Published in: JMIR Cancer

Date Submitted: May 26, 2021
Date Accepted: Jun 9, 2021

The final, peer-reviewed published version of this preprint can be found here:

Strategies for the Identification and Prevention of Survey Fraud: Data Analysis of a Web-Based Survey

Pratt-Chapman M, Moses J, Arem H

Strategies for the Identification and Prevention of Survey Fraud: Data Analysis of a Web-Based Survey

JMIR Cancer 2021;7(3):e30730

DOI: 10.2196/30730

PMID: 34269685

PMCID: 8325077

Survey Fraud: Lessons Learned and Prevention Strategies

  • Mandi Pratt-Chapman; 
  • Jenna Moses; 
  • Hannah Arem

ABSTRACT

Background:

To assess impact of COVID-19 on cancer survivors, we fielded a survey promoted via email and social media in winter 2020. Examination of data showed suspicious patterns that warranted serious review.

Objective:

This paper reviews methods used to prevent and identify fraudulent responses.

Methods:

As precautions, we included CAPTCHA, a hidden question, and instructions for respondents to type a specific word. To identify likely fraudulent data, we defined a priori indicators that warranted elimination or suspicion. If a survey had two or more suspicious indicators, the survey was eliminated. We examined differences between retained and eliminated data sets.

Results:

Of total responses (n=1,977), nearly three-fourths (n=1,408) were dropped and a quarter retained (n=569) after data quality checking. Comparisons of the two data sets showed statistically significant differences across almost all demographic characteristics.

Conclusions:

Numerous precautions beyond CAPTCHA are needed when fielding online surveys, particularly if a financial incentive is offered. Clinical Trial: N/A


 Citation

Please cite as:

Pratt-Chapman M, Moses J, Arem H

Strategies for the Identification and Prevention of Survey Fraud: Data Analysis of a Web-Based Survey

JMIR Cancer 2021;7(3):e30730

DOI: 10.2196/30730

PMID: 34269685

PMCID: 8325077

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