Nudges for people who think.

IF 3.2 3区心理学 Q1 PSYCHOLOGY, EXPERIMENTAL

Psychonomic Bulletin & Review Pub Date : 2025-01-03 DOI:10.3758/s13423-024-02613-1

Aba Szollosi, Nathan Wang-Ly, Ben R Newell

引用次数: 0

Abstract

The naiveté of the dominant 'cognitive-miser' metaphor of human thinking hampers theoretical progress in understanding how and why subtle behavioural interventions-'nudges'-could work. We propose a reconceptualization that places the balance in agency between, and the alignment of representations held by, people and choice architects as central to determining the prospect of observing behaviour change. We argue that two aspects of representational (mis)alignment are relevant: cognitive (how people construe the factual structure of a decision environment) and motivational (the importance of a choice to an individual). Nudging thinkers via the alignment of representations provides a framework that offers theoretical and practical advances and avoids disparaging people's cognitive capacities.

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对有思想的人的鞭策。

“认知吝啬鬼”这一占主导地位的人类思维隐喻的幼稚，阻碍了理解微妙的行为干预（“轻推”）如何以及为何起作用的理论进步。我们提出了一种重新概念化，将人与选择建筑师之间的代理平衡和代表的一致性作为确定观察行为变化前景的核心。我们认为表征（错误）一致性的两个方面是相关的：认知（人们如何解释决策环境的事实结构）和动机（选择对个人的重要性）。通过表征的一致性来推动思考者提供了一个框架，提供了理论和实践的进步，并避免贬低人们的认知能力。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Psychonomic Bulletin & Review Multiple-

CiteScore

6.70

自引率

2.90%

发文量

165

期刊介绍： The journal provides coverage spanning a broad spectrum of topics in all areas of experimental psychology. The journal is primarily dedicated to the publication of theory and review articles and brief reports of outstanding experimental work. Areas of coverage include cognitive psychology broadly construed, including but not limited to action, perception, & attention, language, learning & memory, reasoning & decision making, and social cognition. We welcome submissions that approach these issues from a variety of perspectives such as behavioral measurements, comparative psychology, development, evolutionary psychology, genetics, neuroscience, and quantitative/computational modeling. We particularly encourage integrative research that crosses traditional content and methodological boundaries.