政策抽象作为认知努力避免的预测因素
Ceyda Sayalı1, Jordan Rubin-McGregor2, David Badre3
1Center for Psychedelic and Consciousness Research, Johns Hopkins University School of Medicine.
Journal of experimental psychology. General
|August 24, 2023
概括
人们避免困难的认知任务,但确切的原因尚不清楚. 这项研究发现,需要更高的政策抽象或复杂的规则遵循的任务是最容易避免的,甚至比错误率更高的任务更容易避免.
科学领域:
- 认知心理学 认知心理学
- 决策 决策 决策 决策 决策
- 行为经济学是一种行为经济学.
背景情况:
- 广泛的研究表明,个人避免认知要求高的任务.
- 驱动这种回避或认知努力成本的具体特征仍然不完全理解.
- 以前的假设集中在任务持续时间,错误可能性和认知控制需求上.
研究的目的:
- 调查一种新的假设,即需要更高程度的政策抽象的任务被认为是更加费力的.
- 为了确定政策抽象是否预测任务回避独立于性能指标,如任务时间或错误概率.
- 探索语境偶然性在任务规则复杂性中的作用及其与努力厌恶的关系.
主要方法:
- 结合了两个既定的认知控制任务,系统地改变了政策抽象.
- 使用需求选择任务程序来评估任务回避.
- 控制性能因素,包括任务时间和预期错误率 (ER).
主要成果:
- 政策抽象成为认知努力选择的最强有力的预测因素.
- 错误的可能性是避免任务的第二个最重要的预测因素.
- 这些发现在多项研究和分析中是一致的.
结论:
- 政策抽象是一个关键的任务特征,独立于性能,驱动任务回避.
- 这提供了对导致认知努力的厌恶体验的因素的新理解.
- 结果支持一个机会成本框架来解释认知努力厌恶.
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