a Department of Psychology , University of Central Florida , Orlando , FL , USA.
Ergonomics. 2019 Aug;62(8):983-994. doi: 10.1080/00140139.2019.1614681. Epub 2019 May 20.
This study explored distinct perceptual and decisional contributions to spam email mental construal. Participants classified spam emails according to pairings of three stimulus features - presence or absence of awkward prose, abnormal message structure, and implausible premise. We examined dimensional interactions within general recognition theory (GRT; a multidimensional extension of signal detection theory). Classification accuracy was highest for categories containing either two non-normal dimension levels (e.g. awkward prose and implausible premise) or two normal dimension levels (e.g. normal prose and plausible premise). Modelling indicated both perceptual and decisional contributions to classification responding. In most cases, perceptual discriminability was higher along one dimension when stimuli contained a non-normal level of the paired dimension (e.g. prose discriminability was higher with abnormal structure). Similarly, decision criteria along one dimension were biased in favour of the non-normal response when stimuli contained a non-normal level of the paired dimension. Potential applications for training are discussed. We applied general recognition theory (i.e. multivariate signal detection theory) to spam email classification at low or high levels of three stimulus dimensions: premise plausibility, prose quality, and email structure. Relevant to training, this approach helped identify perceptual and decisional biases that could be leveraged to individualise training.
这项研究探讨了不同的感知和决策贡献对垃圾邮件心理构建的影响。参与者根据三个刺激特征（生硬的语言、异常的信息结构和不合理的前提）的配对来对垃圾邮件进行分类。我们在广义识别理论（GRT；信号检测理论的多维扩展）内研究了维度交互作用。对于包含两个非正常维度水平（例如生硬的语言和不合理的前提）或两个正常维度水平（例如正常的语言和合理的前提）的类别，分类准确性最高。模型表明，分类响应既存在感知贡献，也存在决策贡献。在大多数情况下，当刺激包含配对维度的非正常水平时，沿一个维度的感知可辨别性更高（例如，结构异常时语言的可辨别性更高）。同样，当刺激包含配对维度的非正常水平时，沿一个维度的决策标准偏向于非正常响应。讨论了潜在的培训应用。我们在三个刺激维度（前提合理性、语言质量和电子邮件结构）的低水平或高水平应用广义识别理论（即多元信号检测理论）进行垃圾邮件分类。与培训相关的是，这种方法有助于确定可以利用的感知和决策偏差，以实现个性化培训。
