BACKGROUND: The reactive aggressive behavior in individuals typically shows a rapid growth trend as individuals enter adolescence, and peaks during middle-school period. According to the Comprehensive Cognitive Model of Trait Anger, trait anger and hostile attribution bias play important roles in the development of reactive aggressive behavior. Based on this, current study explored the relationship between trait anger and reactive aggressive behavior in middle school students, as well as the mediating role of hostile attribution bias and interventions.
METHODS: The current study consisted of three sub-studies. Study 1 recruited 87 middle school students with an average age of 12.367 ± 0.889 years, investigated the relationship between trait anger and reactive aggressive behavior, as well as the mediating role of trait hostile attribution bias. Study 2 recruited 62 middle school students with an average age of 13.376 ± 0.963 years, investigated the relationship between trait anger and reactive aggressive behavior, as well as the mediating role of state hostile attribution bias. Study 3 recruited 80 middle school students with an average age of 13.392 ± 0.977 years, implemented an intervention targeting trait hostile attribution bias in middle school students with high trait anger to reduce their reactive aggressive behavior. In current study, data management was performed using SPSS 22.0. Descriptive statistics, independent samples t-test, paired samples t-test, repeated measures analysis of variance (ANOVA), and path analysis were used for statistical analysis.
RESULTS: The results of Study 1 showed that trait anger predicted reactive aggressive behavior through trait hostile attribution bias. The results of Study 2 indicated that trait and state hostile attribution bias played mediating role intermediary, and trait hostile attribution bias had a stronger mediating effect than state hostile attribution bias. The results of Study 3 suggested that the intervention effectively decreased trait hostile attribution bias and reactive aggressive behavior.
CONCLUSIONS: Trait anger can predict the reactive aggressive behavior of junior high school students, with trait hostility attribution bias and state hostility attribution bias mediating this relationship. Intervening in the hostility attribution bias of high-anger junior high school students can effectively reduce their reactive aggressive behavior.

In their seminal experiment in 1944, Heider and Simmel revealed that humans have a pronounced tendency to impose narrative meaning even in the presence of simple animations of geometric shapes. Despite the shapes having no discernible features or emotions, participants attributed strong social context, meaningful interactions, and even emotions to them. This experiment, run on traditional 2D displays has since had a significant impact on fields ranging from psychology to narrative storytelling. Virtual Reality (VR), on the other hand, offers a significantly new viewing paradigm, a fundamentally different type of experience with the potential to enhance presence, engagement and immersion. In this work, we explore and analyze to what extent the findings of the original experiment by Heider and Simmel carry over into a VR setting. We replicate such experiment in both traditional 2D displays and with a head mounted display (HMD) in VR, and use both subjective (questionnaire-based) and objective (eye-tracking) metrics to record the observers\' visual behavior. We perform a thorough analysis of this data, and propose novel metrics for assessing the observers\' visual behavior. Our questionnaire-based results suggest that participants who viewed the animation through a VR headset developed stronger emotional connections with the geometric shapes than those who viewed it on a traditional 2D screen. Additionally, the analysis of our eye-tracking data indicates that participants who watched the animation in VR exhibited fewer shifts in gaze, suggesting greater engagement with the action. However, we did not find evidence of differences in how subjects perceived the roles of the shapes, with both groups interpreting the animation\'s plot at the same level of accuracy. Our findings may have important implications for future psychological research using VR, especially regarding our understanding of social cognition and emotions.

Malicious online trolling is prevalent among Chinese college students and has recently garnered extensive attention from researchers due to the substantial harm it causes to the victims and the damage it inflicts on the online environment. Most previous studies have focused on examining how personal traits related to malicious online trolling. Further comprehensive research is needed to explore the mechanisms linking external environmental factors (antisocial media exposure) and malicious online trolling. A total of 1259 Chinese college students completed questionnaires regarding malicious online trolling, antisocial media exposure, hostile attribution bias, and empathy. The results indicated a positive association between antisocial media exposure and malicious online trolling among Chinese college students, with hostile attribution bias serving as a mediating factor. Furthermore, the direct and mediated paths between antisocial media exposure and malicious online trolling were moderated by empathy. Specifically, as the level of empathy increased among college students, the relations between the variables all weakened. Excessive exposure to antisocial media content among college students may trigger hostile attribution bias and lead to more malicious online trolling behavior. However, the relation between antisocial media exposure and malicious online trolling, hostile attribution bias and malicious online trolling, was attenuated when college students\' empathy levels were high.

This paper examines how humans judge the capabilities of artificial intelligence (AI) to evaluate human attributes, specifically focusing on two key dimensions of human social evaluation: morality and competence. Furthermore, it investigates the impact of exposure to advanced Large Language Models on these perceptions. In three studies (combined N = 200), we tested the hypothesis that people will find it less plausible that AI is capable of judging the morality conveyed by a behavior compared to judging its competence. Participants estimated the plausibility of AI origin for a set of written impressions of positive and negative behaviors related to morality and competence. Studies 1 and 3 supported our hypothesis that people would be more inclined to attribute AI origin to competence-related impressions compared to morality-related ones. In Study 2, we found this effect only for impressions of positive behaviors. Additional exploratory analyses clarified that the differentiation between the AI origin of competence and morality judgments persisted throughout the first half year after the public launch of popular AI chatbot (i.e., ChatGPT) and could not be explained by participants\' general attitudes toward AI, or the actual source of the impressions (i.e., AI or human). These findings suggest an enduring belief that AI is less adept at assessing the morality compared to the competence of human behavior, even as AI capabilities continued to advance.

Learning how others perceive us helps us tune our behavior to form adaptive relationships. But which perceptions stick with us? And when in the learning process are they codified in memory? We leveraged a popular television series-The Office-to answer these questions. Prior to their functional magnetic resonance imaging (fMRI) session, viewers of The Office reported which characters they identified with, as well as which characters they perceived another person (i.e. counterpart) was similar to. During their fMRI scan, participants found out which characters other people thought they and the counterpart were like, and also completed rest scans. Participants remembered more feedback inconsistent with their self-views (vs. views of the counterpart). Although neural activity while encoding self-inconsistent feedback did not meaningfully predict memory, returning to the inconsistent self feedback during subsequent rest did. During rest, participants reinstated neural patterns engaged while receiving self-inconsistent feedback in the dorsomedial prefrontal cortex (DMPFC). DMPFC reinstatement also quadratically predicted self-inconsistent memory, with too few or too many reinstatements compromising memory performance. Processing social feedback during rest may impact how we remember and integrate the feedback, especially when it contradicts our self-views.

Impressions of trustworthiness are formed quickly from faces. To what extent are these impressions shared among observers of the same or different races? Although high consensus of trustworthiness evaluation has been consistently reported, recent studies suggested substantial individual differences. For instance, negative implicit racial bias and low contact experience towards individuals of the other race have been shown to be related to low trustworthiness judgments for other-race faces. This pre-registered study further examined the effects of implicit social bias and experience on trustworthiness judgments of other-race faces. A relatively large sample of White (N = 338) and Black (N = 299) participants completed three tasks: a trustworthiness rating task of faces, a race implicit association test, and a questionnaire of experience. Each participant rated trustworthiness of 100 White faces and 100 Black faces. We found that the overall trustworthiness ratings for other-race faces were influenced by both implicit bias and experience with individuals of the other-race. Nonetheless, when comparing to the own-race baseline ratings, high correlations were observed for the relative differences in trustworthiness ratings of other-race faces for participants with varied levels of implicit bias and experience. These results suggest differential impact of social concepts (e.g., implicit bias, experience) vs. instinct (e.g., decision of approach-vs-avoid) on trustworthiness impressions, as revealed by overall vs. relative ratings on other-race faces.

Extensive literature probes labor market discrimination through correspondence studies in which researchers send pairs of resumes to employers, which are closely matched except for social signals such as gender or ethnicity. Upon perceiving these signals, individuals quickly activate associated stereotypes. The Stereotype Content Model (SCM; Fiske 2002) categorizes these stereotypes into two dimensions: warmth and competence. Our research integrates findings from correspondence studies with theories of social psychology, asking: Can discrimination between social groups, measured through employer callback disparities, be predicted by warmth and competence perceptions of social signals? We collect callback rates from 21 published correspondence studies, varying for 592 social signals. On those social signals, we collected warmth and competence perceptions from an independent group of online raters. We found that social perception predicts callback disparities for studies varying race and gender, which are indirectly signaled by names on these resumes. Yet, for studies adjusting other categories like sexuality and disability, the influence of social perception on callbacks is inconsistent. For instance, a more favorable perception of signals like parenthood does not consistently lead to increased callbacks, underscoring the necessity for further research. Our research offers pivotal strategies to address labor market discrimination in practice. Leveraging the warmth and competence framework allows for the predictive identification of bias against specific groups without extensive correspondence studies. By distilling hiring discrimination into these two dimensions, we not only facilitate the development of decision support systems for hiring managers but also equip computer scientists with a foundational framework for debiasing Large Language Models and other methods that are increasingly employed in hiring processes.

The gaze-following patch (GFP) is located in the posterior temporal cortex and has been described as a cortical module dedicated to processing other people\'s gaze-direction in a domain-specific manner. Thus, it appears to be the neural correlate of Baron-Cohen\'s eye direction detector (EDD) which is one of the core modules in his mindreading system-a neurocognitive model for the theory of mind concept. Inspired by Jerry Fodor\'s ideas on the modularity of the mind, Baron-Cohen proposed that, among other things, the individual modules are domain specific. In the case of the EDD, this means that it exclusively processes eye-like stimuli to extract gaze-direction and that other stimuli, which may carry directional information as well, are processed elsewhere. If the GFP is indeed EDD\'s neural correlate, it must meet this expectation. To test this, we compared the GFP\'s BOLD activity during gaze-direction following with the activity during arrow-direction following in the present human fMRI study. Contrary to the expectation based on the assumption of domain specificity, we did not find a differentiation between gaze- and arrow-direction following. In fact, we were not able to reproduce the GFP as presented in the previous studies. A possible explanation is that in the present study-unlike the previous work-the gaze stimuli did not contain an obvious change of direction that represented a visual motion. Hence, the critical stimulus component responsible for the identification of the GFP in the previous experiments might have been visual motion.

Although aversive responses to sensory stimuli are common in autism spectrum disorder (ASD), it remains unknown whether the social relevance of aversive sensory inputs affects their processing. We used functional magnetic resonance imaging (fMRI) to investigate neural responses to mildly aversive nonsocial and social sensory stimuli as well as how sensory over-responsivity (SOR) severity relates to these responses. Participants included 21 ASD and 25 typically-developing (TD) youth, aged 8.6-18.0 years. Results showed that TD youth exhibited significant neural discrimination of socially relevant versus irrelevant aversive sensory stimuli, particularly in the amygdala and orbitofrontal cortex (OFC), regions that are crucial for sensory and social processing. In contrast, ASD youth showed reduced neural discrimination of social versus nonsocial stimuli in the amygdala and OFC, as well as overall greater neural responses to nonsocial compared with social stimuli. Moreover, higher SOR in ASD was associated with heightened responses in sensory-motor regions to socially-relevant stimuli. These findings further our understanding of the relationship between sensory and social processing in ASD, suggesting limited attention to the social relevance compared with aversiveness level of sensory input in ASD versus TD youth, particularly in ASD youth with higher SOR.

The presence of face masks can significantly impact processes related to trait impressions from faces. In the present research, we focused on trait impressions from faces either wearing a mask or not by addressing how contextual factors may shape such inferences. In Study 1, we compared trait impressions from faces in a phase of the COVID-19 pandemic in which wearing masks was a normative behavior (T1) with those assessed one year later when wearing masks was far less common (T2). Results at T2 showed a reduced positivity in the trait impressions elicited by faces covered by a mask. In Study 2, it was found that trait impressions from faces were modulated by the background visual context in which the target face was embedded so that faces wearing a mask elicited more positive traits when superimposed on an indoor rather than outdoor visual context. Overall, the present studies indicate that wearing face masks may affect trait impressions from faces, but also that such impressions are highly flexible and can significantly fluctuate across time and space.