Moral bias toward different social classes

The influence of social class on prosocial behaviour has long been a focus of intense research interest. The present research involved four studies that covered four moral exemplars (villains, victims, heroes, and beneficiaries) to test whether people of different social classes are treated equally in moral judgements. We described moral events experienced by different agents of varying social classes and asked participants to rate the morality of the events and their emotional responses. The results revealed that compared with the low-class condition, high-class individuals had an overall moral disadvantage when they were regarded as villains, victims, and beneficiaries. For the exemplar of hero, the high-class condition was no different from the low-class condition except that high-class heroes evoked less elevation than low-class heroes. The results reveal that people hold a biased moral attitude toward individuals in different social classes.     

How do friendship artificial intelligence chatbots (FAIC) benefit the continuance using intention and customer engagement?

Although there have been many AI chatbots in industry service, social media, and e-commerce platforms, research on AI chatbots such as Replika, neglected the effects of human-like traits on users' continuance using intention. This article aims to explore the main effects of human-like traits (perceived warmth vs. perceived competence) of friendship AI chatbots (FAIC) on continuance using intention and customer engagement, and the moderating effects of the need to belong and information sensitivity. Three studies are conducted to collect data (N_total = 1420). Our findings of Study 1 demonstrate that perceived warmth and perceived competence can increase the continuance using intention to FAIC and customer engagement, and perceived usefulness plays a mediating role in our conceptual model. Additionally, consumers' need to belong (high vs. low) (Study 2) and information sensitivity (high vs. low) (Study 3) related to chat contents moderate the main effects significantly. This article contributes to the literature on the relationship between FAIC and consumers by presenting the influence of perceived warmth and perceived competence and establishing the underlying process. Analogously, the findings can be beneficial for marketers and firms in designing and developing the coding program of FAIC to promote consumers' continuance using intention and customer engagement.     

抑郁认知易感性应激模式的研究：起源、发展和整合

近年来,对抑郁易感性的研究,已经成为探寻抑郁心理病理的一个热点。文章介绍了抑郁易感性应激模型的相关定义、起源、及主要特点。介绍了在当代具有代表性的3个理论：（1）Abramson的抑郁无望理论;（2）Beck的认知易感理论;（3）双信息过程理论。尤其对抑郁认知易感性因素本身的起源、发展及影响因素进行了评述。最后,介绍了整合的抑郁认知易感性应激模型。在此基础上,提出了模型进一步完善和发展的方向     

初中生英语词汇记忆策略的研究

通过对134名初中三年级学生英语词汇记忆策略的问卷调查以及记忆不同难度的词汇时所使用的策略的分析,发现初三学生以使用机械的、一般性的记忆策略为主;优生比差生更善于选用具体的词汇记忆策略;词汇记忆难度增大时,选择和使用多种策略的频率与人数有所增加。     

伦理何为

伦理学是“成人”,“做人”之维。人离不开伦理,伦理学首先是“成人”之道。“人”成为什么样的人也离不开伦理,伦理学又是“做人”之维。伦理要内化成人心理的存在,才能成为“成人”之道,“做人”之维。道德建设要符合“成人”与“做人”的要求。     

多元宇宙样分析：简介及应用

选择性分析和报告是造成心理科学研究可重复性危机的一个重要因素。近年来研究者提出用多元宇宙样分析的方法,囊括多种数据分析策略,减少分析过程中的主观选择性和随意性,并进行稳健性检验以提高结果的可靠性。以手机使用与手机压力的关系为例,介绍该方法和操作步骤。该方法已在心理学和认知神经科学等领域得到一定的应用。未来研究应继续发展和完善该方法的统计推断,使之运用到更多的数据类型和更广的研究领域中。     

基于用户动态信息加工的信息流广告回避机制与重定向策略

信息流广告飞速发展的同时用户广告回避愈发普遍,然而传统广告回避结论无法平移到该情境。本研究基于用户动态的信息加工视角,试图探讨(1)动态信息加工状态下(收敛式vs发散式)产生广告屏蔽和广告跳过行为的内在机制;(2)采用归因引导重定向策略,挖掘用户屏蔽广告的“残留效应”所带来的信号价值;(3)采用广告凸显重定向策略,突破用户跳过广告的“学习效应”造成的负面影响。丰富现有理论的同时,为信息流广告的响应式优化提供理论和决策支持。     

Why Do you Often Stop your Impulsive Behavior at the Last Moment?

Psychonomic Bulletin & Review - Intentional inhibition, a critical ability of human cognitive control, is the capacity to internally withhold a to-be-performed action. In the voluntary...     

反馈相关负波与成瘾

反馈相关负波(feedback-related negativity, FRN)是反馈加工诱发的脑电成分, 体现了个体对奖赏的敏感性。成瘾分为物质成瘾和行为成瘾, 两类个体的反馈加工都呈现病理性模式。相对于普通反馈物(如金钱), 物质成瘾个体在加工成瘾物质时诱发的FRN波幅显著增大; 在与非成瘾被试的对照研究中, 物质成瘾者加工金钱反馈时的FRN也表现出与成瘾相关的异常模式; 在行为成瘾个体中亦观察到与物质成瘾个体类似的FRN失调现象。但以往多数研究中对成瘾类型的区分还不够详细, 未来研究应进一步考虑成瘾不同亚型的特点; 且成瘾个体往往伴随其他精神障碍(如抑郁、焦虑), 将来的研究要区分共病因素的影响, 揭示成瘾独特的奖赏加工机制问题。     

眼动轨迹匹配法：一种研究决策过程的新方法

眼动轨迹匹配法是近年来新兴的一种眼动数据分析方法, 该方法包括注视数据的预处理、兴趣区划分和编码、形成眼动轨迹字符串、计算相似性得分四个步骤。研究者采用眼动轨迹匹配法对决策过程理论及其影响因素进行的探索性研究, 证实了眼动轨迹匹配法在决策领域的可行性、精确性和高价值性。未来的研究应进一步利用眼动轨迹匹配法加强对各种决策理论及其影响因素的研究, 以揭示决策的认知过程, 构建更加完善的决策理论模型。