Yi Chen

This study examines the relationship between perceived stress and society-wide moral judgment by integrating two influential frameworks: the neo-Kohlbergian approach and the CNI model of utilitarian-deontological decision-making. The neo-Kohlbergian approach to moral judgment proposes three moral schemas: (1) Personal Interest (PI), where decisions are self-focused; (2) Maintaining Norms (MN), which emphasizes adherence to social rules and norms; and (3) Postconventional (PC), where universal ethical principles are prioritized. The CNI model for Utilitarian-Deontological judgment features three psychological processes in decision-making: Sensitivity to Consequence, Sensitivity to Norm, and Inaction Preference. A survey study was conducted to measure perceived stress, neo-Kohlbergian moral judgment (using the behavioral Defining Issues Test [DIT]), and the psychological processes underlying utilitarian-deontological decision-making (CNI). The results indicate that higher perceived stress is linked to greater PI schema endorsement, reduced Norm Sensitivity, and increased Consequence Sensitivity. Furthermore, the PI schema mediated the relationship between perceived stress and Norm Sensitivity. These findings provide insights into how stress shapes moral reasoning and decision-making, with implications for psychological and ethical studies.

Item response theory (IRT) is a modern psychometric framework for estimating respondents’ latent traits (e.g., ability, attitude, and personality) based on their responses to a set of questions in psychological tests. The current study adopted an item response tree (IRTree) method, which combines the tree model with IRT models for handling the sequential process of responding to a test item, to score individual moral inclination for the CNI test—a broadly adopted model for examining humans’ moral decision-making with three parameters generated: sensitivity to moral norms, sensitivity to consequences, and inaction preference. Compared to previous models for the CNI test, the resulting EIRTree-CNI Model is able to generate individual scores without increasing the number of items (thus, less subject fatigue or compromised response quality) or employing a post hoc approach that is deemed statistically suboptimal. The model fits the data well, and the subsequent test also supported the concurrent validity and the predictive validity of the model. Limitations are discussed further.

AERA Online Paper Repository Viewer