Date of Graduation
Doctor of Philosophy in Psychology (PhD)
Second Committee Member
Base Rates;CAC;Estimator Variables;Eyewitness;Pristine Conditions
Researchers have used signal-detection theory-based approach to show that when police use proper practices with eyewitnesses, highly confident witnesses will be highly accurate even when viewing conditions may be suboptimal (Wixted & Wells, 2017). This is referred to as the pristine conditions hypothesis. There have been multiple, and often contradictory, studies that have investigated the relationship between viewing conditions and memory degradation (Giacona et al., 2021; Grabman et al., 2019; Lockamyeir et al, 2020; Semmler et al., 2018). In the current study, I systematically manipulated five estimator variables (lighting, distance, retention interval, exposure duration, and race) as either suboptimal or optimal to further investigate this relationship. I found that, as expected, overall memory strength decreased as the number of suboptimal estimator variables increased. Next, I assessed CAC curves for the number of suboptimal estimator variables and found that the pristine conditions hypothesis holds, except when all five variables are suboptimal, at which point high confidence does not equal high accuracy. Additionally, these results did not hold for when base rates were low. Similarly, when collapsing across viewing type, it was found that under low base rates, high confidence did not equal high accuracy when the conditions were suboptimal. While this research found a lot of support for the pristine conditions hypothesis, it also established important boundary conditions for when this hypothesis is not valid. Further research is still needed to continue to address the confidence-accuracy relationship.
Giacona, A. M. (2023). How Systematically Increasing Estimator Variables Affects the Confidence-Accuracy Relationship. Graduate Theses and Dissertations Retrieved from https://scholarworks.uark.edu/etd/4938