Department of Psychology, Northeastern University, Boston, MA, USA.
Department of Psychology, Yale University, New Haven, CT, USA.
Nat Commun. 2022 Apr 26;13(1):2252. doi: 10.1038/s41467-022-29742-2.
Flow is a subjective state characterized by immersion and engagement in one's current activity. The benefits of flow for productivity and health are well-documented, but a rigorous description of the flow-generating process remains elusive. Here we develop and empirically test a theory of flow's computational substrates: the informational theory of flow. Our theory draws on the concept of mutual information, a fundamental quantity in information theory that quantifies the strength of association between two variables. We propose that the mutual information between desired end states and means of attaining them - [Formula: see text] - gives rise to flow. We support our theory across five experiments (four preregistered) by showing, across multiple activities, that increasing [Formula: see text] increases flow and has important downstream benefits, including enhanced attention and enjoyment. We rule out alternative constructs including alternative metrics of associative strength, psychological constructs previously shown to predict flow, and various forms of instrumental value.
流畅是一种主观状态，其特点是沉浸于当前的活动并全身心投入其中。流畅对生产力和健康的益处有充分的记录，但流畅产生过程的严格描述仍然难以捉摸。在这里，我们开发并实证检验了一种关于流畅的计算基础的理论：流畅的信息理论。我们的理论借鉴了互信息的概念，互信息是信息论中的一个基本数量，用于量化两个变量之间的关联强度。我们提出，期望的最终状态和实现这些状态的手段之间的互信息——[公式：见正文]——会产生流畅感。我们通过在多个活动中展示，在五个实验（其中四个预先注册）中支持我们的理论，即增加[公式：见正文]会增加流畅感，并带来重要的下游益处，包括提高注意力和享受度。我们排除了其他的构建，包括替代的关联强度指标、先前被证明可以预测流畅感的心理构建，以及各种形式的工具价值。
