Depletion or activation? Challenging linear models of ego depletion

自我耗竭 本我、自我与超我 心理学 社会心理学 自我控制
作者
Xu Yi,Hugo Chan,Zhiye Ran,Jianping Xu
出处
期刊:Acta Psychologica [Elsevier BV]
卷期号:259: 105346-105346 被引量:1
标识
DOI:10.1016/j.actpsy.2025.105346
摘要

This study investigates the interplay between depletion and activation effects in ego-depletion research, addressing ongoing controversies regarding ego depletion. A total of 244 participants were randomly assigned to depletion, control, or practice groups. Classical ANOVA and Bayesian hypothesis testing were used to compare post-manipulation performance. Results revealed no significant group differences; Bayes factors strongly supported the null hypothesis over both the traditional depletion and reverse depletion hypotheses. However, theoretical reasoning suggested that activation and depletion effects may have coincided, thereby canceling each other out. This hypothesis was supported by partial correlation network analysis, which revealed a nonlinear dual-path structure: greater effort led to increased fatigue (indicative of depletion) and decreased performance, but also enhanced attention (indicative of activation), with attention positively predicting post-task performance. Additionally, boredom reduced attention both directly and indirectly via fatigue, suggesting that task-induced boredom may suppress activation effects and increase susceptibility to ego depletion. Centrality analysis highlighted fatigue as a core mediator linking effort, attention, and performance. Rather than rejecting ego depletion theory, our findings reinterpret its behavioral variability as the outcome of interacting nonlinear processes. The relative dominance of depletion or activation may depend on task duration, intensity, and individual traits (e.g., boredom proneness, willpower beliefs). Ego depletion thus reflects a dynamic equilibrium between costs and compensatory mechanisms, explaining the difficulty of replicating these effects under standard conditions. Future research should move beyond linear models and adopt system-level approaches to capture the dynamic nature of self-control.
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