Complacency, or sub-optimal monitoring of automation performance, has been cited as a contributing factor in numerous major transportation and medical incidents. Researchers are working to identify individual differences that correlate with complacency as one strategy for preventing complacency-related accidents. Automation-induced complacency potential is an individual difference reflecting a general tendency to be complacent across a wide variety of situations which is similar to, but distinct from trust. Accurately assessing complacency potential may improve our ability to predict and prevent complacency in safety-critical occupations. Much past research has employed an existing measure of complacency potential. However, in the 25 years since that scale was published, our conceptual understanding of complacency itself has evolved, and we propose that an updated scale of complacency potential is needed. The goal of the present study was to develop, and provide initial validation evidence for, a new measure of automation-induced complacency potential that parallels the current conceptualization of complacency. In a sample of 475 online respondents, we tested 10 new items and found that they clustered into two separate scales: Alleviating Workload (which focuses on attitudes about the use of automation to ease workloads) and Monitoring (which focuses on attitudes toward monitoring of automation). Alleviating workload correlated moderately with the existing complacency potential rating scale, while monitoring did not. Further, both the alleviating workload and monitoring scales showed discriminant validity from the previous complacency potential scale and from similar constructs, such as propensity to trust. In an initial examination of criterion-related validity, only the monitoring-focused scale had a significant relationship with hypothetical complacency ( r = -0.42, p < 0.01), and it had significant incremental validity over and above all other individual difference measures in the study. These results suggest that our new monitoring-related items have potential for use as a measure of automation-induced complacency potential and, compared with similar scales, this new measure may have unique value.
It is well established in the risk literature that men tend to take more risks than women. This gender difference, however, is often qualified by its domain specificity. Considering recent research on the domain generality of risk taking as a disposition, there is a need to examine the degree to which men take more risks than women, in general. In order to make substantive conclusions about the gender differences in risk‐taking propensity, one must first establish measurement invariance, which is required for the meaningful interpretation of observed group differences. In this paper, we examined the measurement invariance of the Domain‐Specific Risk‐Taking scale (DOSPERT)—one of the most popular measures of individual differences in risk taking. We found that the DOSPERT violated configural invariance in a bifactor model, indicating that the underlying factor structure of the DOSPERT differs between men and women. Even after removing the social risk dimension, DOSPERT still failed to reach scalar invariance. Taken together, these findings suggest that score differences in the DOSPERT may be due to response artifacts rather than true differences in the latent construct. Therefore, gender differences in the DOSPERT must be interpreted with caution. Implications for the measurement of risk taking are discussed.
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