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首页> 外文期刊>Intelligence: A Multidisciplinary Journal >Working memory capacity, short-term memory capacity, and the continued influence effect: A latent-variable analysis
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Working memory capacity, short-term memory capacity, and the continued influence effect: A latent-variable analysis

机译：工作记忆容量，短期内存容量和持续影响效果：潜在变量分析

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Misinformation often affects inferences and judgments even after it has been retracted and discredited. This is known as the continued influence effect. Memory processes have been theorized to contribute to the continued influence effect, and much previous research has focussed on the role of long-term memory processes at the time misinformation is retrieved during inferential reasoning and judgments. Recently, however, experimental research has focussed upon the role of working memory (WM) processes engaged in the updating and integration of information, when the retraction is encoded. From an individual differences perspective, susceptibility to continued influence effects should be predicted by a person's WM abilities, if continued reliance on misinformation is influenced, at least in part, by insufficient integration of the initial misinformation and its subsequent retraction. Consequently, we hypothesized that WM capacity would predict susceptibility to continued influence effects uniquely and more substantially than short-term memory (STM) capacity. Participants (N = 216) completed a continued-influence task, as well as a battery of WM and STM capacity tasks. Based on a latent variable model, our hypothesis was supported (WM capacity: beta = -0.36, p = .013; STM capacity: beta = 0.22, p = .187). Consequently, we suggest that low WM capacity is a measurable "risk factor" for continued reliance on misinformation.
机译：误导往往会影响推断和判断，即使在缩回和错位后也是如此。这被称为持续影响效果。已经理论上已经过记忆过程促进了持续的影响效应，并且前以前的研究侧重于在推理推理和判断期间检索时间错误的长期记忆过程的作用。然而，最近，实验研究侧重于工作存储器（WM）过程的作用，当时编码收缩时，从事信息的更新和集成。从个体差异的角度来看，如果继续依赖于错误信息，应至少部分地通过初始错误信息的整合和随后的缩回不足，应通过人的WM能力预测对持续影响效应的易受影响。因此，我们假设WM容量将预测易受影响影响的易感性，并且比短期内存（STM）容量更大。参与者（n = 216）完成了一个持续影响任务，以及电池和STM容量任务。基于潜在的变量模型，支持我们的假设（WM容量：Beta = -0.36，P = .013; STM容量：Beta = 0.22，P = .187）。因此，我们建议低WM容量是可衡量的“风险因素”，以继续依赖于误导。

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