A multi-group analysis of online survey respondent data quality: Comparing a regular USA consumer panel to MTurk samples

By Scott M. Smith, Catherine A. Roster, L. Golden, G. Albaum. 2016

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Data quality in online human-subjects research: Comparisons between MTurk, Prolific, CloudResearch, Qualtrics, and SONA (2023, background): “In yet another study, Smith and colleagues [15] compared US and non-US based MTurk participants with a Qualtrics sample and found that while MTurk workers spent less time responding to the items, they correctly responded to the attention checks scattered through the survey.”
Individuals’ intentions to engage in last chance tourism: applying the value-belief-norm model (2020, background): “Therefore, individuals who are older or with lower incomes or those living in more remote parts of the country may not be adequately represented in this survey (Smith et al., 2016).”
An Analysis of Data Quality: Professional Panels, Student Subject Pools, and Amazon's Mechanical Turk (2017, methodology): “” In addition to the measures of participant involvement, four attention check questions were included that have been recommended as metrics for respondent data quality (Goodman, Cryder, and Cheema 2013; Oppenheimer, Meyvis, and Davidenko 2009; Smith et al. 2016).”
Amazon's Mechanical Turk: A Comment (2017, background): “There are two types of problem respondents when it comes to data from MTurk, as explained by Smith et al. (2016): cheaters and speeders.”