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Keywords

Data Quality, Online Survey, Survey Fraud, Survey Bots

Abstract

Information technologies increasingly influence the quality of online survey data. To better understand the quality of online survey data, the researchers conducted a secondary analysis of a survey’s (Study 1; N = 98) data elements and a pilot study (Study 2; N = 20) with a new online survey. The researchers asked: (1) what data elements differed between suspected sincere or insincere survey participants and, (2) how have other researchers checked and perceived checked data from online surveys? In Study 1, the researchers grouped participants into suspected sincere or insincere cohorts based on their survey access method and email address verification. Then, the researchers evaluated the ability of other data elements to distinguish between the cohorts. In Study 2, the researchers distributed a new online survey explicitly to explore other researchers’ methods of checking data quality and confidence in checked data. In Study 1, survey completion times were longer for the sincere cohort than the insincere cohort. In addition, responses to open-ended survey questions and phone numbers differentiated the cohorts. In Study 2, around 25% of research personnel checked respondents’ sincerity on 80% to 100% of their surveys. Among the personnel who checked survey data, 55% checked responses to open-ended questions, and 40% reported needing resources to check responses to open-ended questions. Surveys must be constructed to enable data quality checks. Study 1 identified data elements (survey completion times, participant contact information, and open-ended question responses) that differentiated suspected sincere from insincere participants. Study 2’s results support that research institutions should promote data-quality checks.

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