Value certainty and choice confidence are multidimensional constructs that guide decision-making

Abstract

The degree of certainty that decision-makers have about their evaluations of available choice alternatives and their confidence about selecting the subjectively best alternative are important factors that affect current and future value-based choices. Assessments of the alternatives in a given choice set are rarely unidimensional; their values are usually derived from a combination of multiple distinct attributes. For example, the taste, texture, quantity, and nutritional content of a snack food may all be considered when determining whether to consume it. Here, we examined how certainty about the levels of individual attributes of an option relates to certainty about the overall value of that option as a whole and/or to confidence in having chosen the subjectively best available option. We found that certainty and confidence are derived from unequally-weighted combinations of attribute certainties rather than simple, equal combinations of all sources of uncertainty. Attributes that matter more in determining choice outcomes are also weighted more in metacognitive evaluations of certainty or confidence. Moreover, we found that the process of deciding between two alternatives leads to refinements in both attribute estimations and the degree of certainty in those estimates. Attributes that are more important in determining choice outcomes are refined more during the decision process in terms of both estimates and certainty. Although certainty and confidence are typically treated as unidimensional, our results indicate that they, like value estimates, are subjective, multidimensional constructs.

Changes in preferences reported after choices are informative, not merely statistical artifacts.

“…In each of these studies, SoA was significantly greater in the standard condition relative to the control conditions. The SoA effect has thus been shown to be highly robust, supported by many recent studies published even after the revelation of the statistical artifact explanation (Chammat et al, 2017;Colosio et al, 2017;Coppin et al, 2012Coppin et al, , 2014Greenberg & Spiller, 2016;Hagège et al, 2018;Ito et al, 2019;Izuma et al, 2010;Koster et al, 2015;Lee & Coricelli, 2020;Lee & Daunizeau, 2020Lee & Hare, 2023;Lee & Holyoak, 2021a, 2021bSharot et al, 2012;Tandetnik et al, 2021;Voigt et al, 2017Voigt et al, , 2019; see (Enisman et al, 2021) for a meta-analysis. This suggests that while the statistical artifact may contribute to observed measures of SoA, it is not enough to rule out true choice-induced preference changes.…”

“…Furthermore, the distinct information contained in postchoice ratings is aligned with the choices. This creates the asymmetrical patterns reported above, where postchoice ratings are more predictive of the choices (and related variables, such as response time and confidence) than prechoice ratings (Lee & Daunizeau, 2020, 2021; Lee & Hare, 2023; Lee & Holyoak, 2021b). Indeed, the SoA arises from precisely this novel information.…”

“…Using these simulated data sets, we tested the predictions of the different accounts against the experimental data from (Lee & Holyoak, 2021b). We also examined data from four additional studies, where the vast majority of trials had very low dV1 (Lee & Coricelli, 2020; Lee & Daunizeau, 2020, 2021; Lee & Hare, 2023). We report the results of these additional analyses in the .…”