Granwald Tobias, Dayan Peter, Lengyel Máté, Guitart-Masip Marc
Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden.
Center for Cognitive and Computational Neuropsychiatry (CCNP), Karolinska Institutet, Stockholm, Sweden.
Commun Psychol. 2025 May 22;3(1):82. doi: 10.1038/s44271-025-00254-1.
Failing to make decisions that would actively avoid negative outcomes is central to helplessness. In a Bayesian framework, deciding whether to act is informed by beliefs about the world that can be characterised as priors. However, these priors have not been previously quantified. Here we administered two tasks in which 279 participants decided whether to attempt active avoidance actions. In both tasks, participants decided between a passive option that would for sure result in a negative outcome of varying size, and a costly active option that allowed them a probability of avoiding the negative outcome. The tasks differed in framing and valence, allowing us to test whether the prior generating biases in behaviour is problem-specific or task-independent and general. We performed extensive comparisons of models offering different structural explanations of the data, finding that a Bayesian model with a task-invariant prior for active avoidance provided the best fit to participants' trial-by-trial behaviour. The parameters of this prior were reliable, and participants' self-rated positive affect was weakly correlated with this prior such that participants with an optimistic prior reported higher levels of positive affect. These results show that individual differences in prior beliefs can explain decisions to engage in active avoidance of negative outcomes, providing evidence for a Bayesian conceptualization of helplessness.
未能做出能够积极避免负面结果的决策是无助感的核心所在。在贝叶斯框架中，决定是否采取行动是由对世界的信念所引导的，这些信念可以被描述为先验概率。然而，这些先验概率此前尚未被量化。在此，我们进行了两项任务，279名参与者需要决定是否尝试采取积极的回避行动。在这两项任务中，参与者需要在一个肯定会导致不同程度负面结果的被动选项和一个代价高昂的主动选项之间做出选择，主动选项使他们有一定概率避免负面结果。这两项任务在框架和效价方面有所不同，使我们能够测试导致行为偏差的先验概率是特定于问题的还是与任务无关且具有普遍性的。我们对提供不同数据结构解释的模型进行了广泛比较，发现一个具有主动回避任务不变先验概率的贝叶斯模型最能拟合参与者逐次试验的行为。这个先验概率的参数是可靠的，并且参与者的自评积极情绪与这个先验概率存在微弱的相关性，即具有乐观先验概率的参与者报告的积极情绪水平更高。这些结果表明，先验信念的个体差异可以解释参与积极回避负面结果的决策，为无助感的贝叶斯概念化提供了证据。
