Survey Satisficing Inflates Reliability and Validity Measures: An Experimental Comparison of College and Amazon Mechanical Turk Samples.

This study examined the predictors and psychometric outcomes of survey satisficing, wherein respondents provide quick, "good enough" answers (satisficing) rather than carefully considered answers (optimizing). We administered surveys to university students and respondents-half of whom held college degrees-from a for-pay survey website, and we used an experimental method to randomly assign the participants to survey formats, which presumably differed in task difficulty. Based on satisficing theory, we predicted that ability, motivation, and task difficulty would predict satisficing behavior and that satisficing would artificially inflate internal consistency reliability and both convergent and discriminant validity correlations. Indeed, results indicated effects for task difficulty and motivation in predicting survey satisficing, and satisficing in the first part of the study was associated with improved internal consistency reliability and convergent validity but also worse discriminant validity in the second part of the study. Implications for research designs and improvements are discussed.