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The healthy = sustainable heuristic: Reaction Times and heuristic scope

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PsychArchives2025-07-14 更新2026-04-25 收录
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https://hdl.handle.net/20.500.12034/12256
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Aim one of this study is to investigate whether the ‘healthy = sustainable’-heuristic occurs on an automatic, more implicit level. Aim two of the study is to determine the scope of the heuristic, i.e., if it is applied only to foods which are 'ambiguous', i.e., not clearly healthy or unhealthy or also is applied to 'unambiguous' foods such as vegetables or sweets. The sample of N = 534 living in Austria will be collected via a panel provider. In part one, participants see images of foods with custom-made high/low sustainability labels and are asked to decide if the foods are healthy or unhealthy while their reaction times are recorded. In part two participants see images of foods with manipulated food labels depicting either the Nutri-Score or the Eco-Score and are asked to rate foods on several dimensions (among which healthiness and sustainability). Data will be analysed using Bayesian multi-level-modelling. unknown other

本研究旨在达成两项核心目标:其一,探究“健康即可持续”认知启发式(heuristic)是否会在自动化且更为内隐的层面上显现;其二,明确该认知启发式的适用边界,即该启发式是否仅适用于“模糊类食品”——也就是健康性与不健康性界定不明的食品,抑或是同样会应用于蔬菜、甜点这类“明确类食品”。本研究将通过面板服务商招募共计534名常住奥地利的被试。实验第一阶段,被试将观看带有定制化高/低可持续性标签的食品图像,并需判断该食品是否健康,实验过程中将同步记录其反应时。实验第二阶段,被试将观看带有经过修改的食品标签的图像,这些标签分别展示营养评分系统(Nutri-Score)与生态评分系统(Eco-Score),随后需从多个维度对食品进行评分(其中包含健康性与可持续性两个维度)。本研究将采用贝叶斯多层模型(Bayesian multi-level-modelling)开展数据分析。其余信息未知。
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PsychArchives
创建时间:
2025-07-14
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