Ballard Timothy, Neal Andrew, Farrell Simon, Lloyd Erin, Lim Jonathan, Heathcote Andrew
School of Psychology.
School of Psychological Science.
Psychol Rev. 2022 Jan;129(1):146-174. doi: 10.1037/rev0000324. Epub 2021 Sep 27.
We present a unified model of the dynamics of goal-directed motivation and decision-making. The model-referred to as the GOAL architecture-provides a quantitative framework for integrating theories of goal pursuit and for relating their predictions to different types of data. The GOAL architecture proposes that motivation changes over time according to three gradients that capture the effects of the distance to the goal (i.e., the progress remaining), the time to the deadline, and the rate of progress required to achieve the goal. This enables the integration and comparison of six theoretical perspectives that make different predictions about how these dynamics unfold when pursuing approach and avoidance goals. Hierarchical Bayesian modeling was used to analyze data from three experiments which manipulate distance to goal, time to deadline, and goal type (approach vs. avoidance), and data from the naturalistic context of professional basketball. The results show that people rely on the distance and rate gradients, and to a lesser degree the time gradient, when making resource allocation decisions during goal pursuit, although the relative influence of the gradients depends on the goal type. We also demonstrate how the GOAL architecture can be used to answer questions about the influence of goal importance. Our findings suggest that goal pursuit unfolds in a complex manner that cannot be accounted for by any one previous theoretical perspective, but that is well-characterized by our unified framework. This research highlights the importance of theoretical integration for understanding motivation and decision-making during goal pursuit. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
我们提出了一个目标导向动机与决策动态的统一模型。该模型被称为GOAL架构，它提供了一个定量框架，用于整合目标追求理论，并将其预测与不同类型的数据联系起来。GOAL架构提出，动机随时间的变化遵循三个梯度，这些梯度反映了与目标的距离（即剩余进度）、截止日期的时间以及实现目标所需的进度速率的影响。这使得六种理论观点能够进行整合与比较，这些观点对追求趋近和回避目标时这些动态如何展开做出了不同的预测。我们使用分层贝叶斯建模来分析来自三个实验的数据，这些实验操纵了与目标的距离、截止日期的时间和目标类型（趋近与回避），以及来自职业篮球自然情境的数据。结果表明，在目标追求过程中做出资源分配决策时，人们依赖距离和速率梯度，在较小程度上依赖时间梯度，尽管这些梯度的相对影响取决于目标类型。我们还展示了GOAL架构如何用于回答有关目标重要性影响的问题。我们的研究结果表明，目标追求以一种复杂的方式展开，任何一种先前的理论观点都无法解释，但我们的统一框架能够很好地描述这一过程。这项研究强调了理论整合对于理解目标追求过程中的动机和决策的重要性。（PsycInfo数据库记录 (c) 2022美国心理学会，保留所有权利）
