TY  - JOUR
AU  - Pratt-Chapman, Mandi
AU  - Moses, Jenna
AU  - Arem, Hannah
PY  - 2021
DA  - 2021/7/16
TI  - Strategies for the Identification and Prevention of Survey Fraud: Data Analysis of a Web-Based Survey
JO  - JMIR Cancer
SP  - e30730
VL  - 7
IS  - 3
KW  - cancer survivors
KW  - pandemic
KW  - COVID-19
KW  - fraudulent responses
KW  - survey
KW  - research methods
KW  - cancer patients
KW  - fraud
KW  - CAPTCHA
KW  - data integrity
KW  - online surveys
AB  - 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. 
SN  - 2369-1999
UR  - https://cancer.jmir.org/2021/3/e30730
UR  - https://doi.org/10.2196/30730
UR  - http://www.ncbi.nlm.nih.gov/pubmed/34269685
DO  - 10.2196/30730
ID  - info:doi/10.2196/30730
ER  -