Researchers have limited control over the completion context and response process in web surveys compared to interviewer- administered surveys. Respondents can answer questions from any location, at any time, and on various devices, often while multitasking. This variability may affect data quality. This study addresses the issue by examining the completion context and its associations with data quality using a Hungarian online survey. We used latent class analysis based on completion-related questions to identify five respondent profiles. Many respondents completed the survey under conditions often considered sub-optimal, such as on small screens, without privacy, or while multitasking. However, these factors showed little impact on conventional data quality indicators. The effects were limited to self-reported noise and concentration levels. We conclude that while sub-optimal conditions are common, their practical impact on data quality appears minimal. Nonetheless, monitoring completion behavior remains advisable in web surveys.
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Ságvári et al. (2026) studied this question.
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