%0 Journal Article
%@ 2369-1999
%I JMIR Publications
%V 7
%N 3
%P e30730
%T Strategies for the Identification and Prevention of Survey Fraud: Data Analysis of a Web-Based Survey
%A Pratt-Chapman,Mandi
%A Moses,Jenna
%A Arem,Hannah
%+ GW Cancer Center, The George Washington University, 2600 Virginia Ave, #300, Washington, DC, 20037, United States, 1 202 994 5502, mandi@email.gwu.edu
%K cancer survivors
%K pandemic
%K COVID-19
%K fraudulent responses
%K survey
%K research methods
%K cancer patients
%K fraud
%K CAPTCHA
%K data integrity
%K online surveys
%D 2021
%7 16.7.2021
%9 Original Paper
%J JMIR Cancer
%G English
%X Background: To assess the impact of COVID-19 on cancer survivors, we fielded a survey promoted via email and social media in winter 2020. Examination of the data showed suspicious patterns that warranted serious review. Objective: The aim of this paper is to review the methods used to identify and prevent fraudulent survey responses. Methods: As precautions, we included a Completely Automated Public Turing test to tell Computers and Humans Apart (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 contained two or more suspicious indicators, the survey was eliminated. We examined differences between the retained and eliminated data sets. Results: Of the total responses (N=1977), nearly three-fourths (n=1408) were dropped and one-fourth (n=569) were retained after data quality checking. Comparisons of the two data sets showed statistically significant differences across almost all demographic characteristics. Conclusions: Numerous precautions beyond the inclusion of a CAPTCHA are needed when fielding web-based surveys, particularly if a financial incentive is offered. 
%M 34269685
%R 10.2196/30730
%U https://cancer.jmir.org/2021/3/e30730
%U https://doi.org/10.2196/30730
%U http://www.ncbi.nlm.nih.gov/pubmed/34269685