How Careless Responding and Acquiescence Response Bias Can Influence Construct Dimensionality

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Systems Perspective of Amazon Mechanical Turk for Organizational Research: Review and Recommendations (2017, background): “Careless or insufficient-effort responding is a serious issue for sampling in general (Meade and Craig, 2012; Huang et al., 2015b; Kam and Meyer, 2015; Ran et al., 2015), but particularly for MTurk samples because many workers are likely incentivized to complete HITs quickly to maximize their return”
Careless responding in questionnaire measures: Detection, impact, and remedies (2020, methodology): “In addition, it needs to be kept in mind that the way careless responding affects the results is an interplay of the rate of careless responders in the sample, the most dominant careless response pattern (DeSimone, DeSimone, Harms, & Wood, 2018), and the scale features (Kam & Meyer, 2015).”
The quality of data collected online: An investigation of careless responding in a crowdsourced sample (2020, background): “data collected in online surveys on crowdsourcing services as the primary focus of this study, in line with previous research (Kam and Meyer, 2015; Niessen et al., 2016).”