Eye Gaze Patterns Associated with Aggressive Tendencies in Adolescence

Evaluating the Link between Visual Attention Bias and Emotion Dysregulation of Young Children

The ability to regulate emotions is vital to successful social interactions. This study explores whether visual attention bias is associated with emotion dysregulation (ED) in early childhood. Parental reports of child ED (Child Behaviour Checklist (CBCL) and Temper Tantrum Scale) were examined in relation to child visual attention bias whilst viewing emotional faces. Results indicated that the level of eye gaze fixation towards emotional images and faces was associated with ED when social function (measured with the Social Responsiveness Scale), gender, age, and attention problems (measured from the CBCL subscale), were adjusted. The modifying effect on visual attention bias was evaluated using interaction analysis in the generalized linear model. The level of visual attention bias, indicated by the proportion of eye gaze fixation time on areas of interest (AOIs) in images displaying unpleasant emotions (such as anger), was inversely associated with the level of externalising problem behaviours (p = .014). Additionally, the association of eye gaze fixation time for AOIs displaying negative emotional cues with the level of externalising problem behaviours varied by age (p = .04), with younger children (aged < 70 months) demonstrating a stronger association than older children (aged ≥ 70 months). Findings suggest that young children with greater ED symptoms look less at unpleasant emotional cues. However, this relationship is attenuated as children become older. Further research to identify objective biomarkers that incorporate eye-tracking tasks may support prediction of ED-related mental health issues in the early years.

Effects of victimization and perpetration in observing bullying scenes: an eye-tracker study{es}: Efectos de la victimización y la perpetración en la observación de escenas de acoso: un estudio con eye-tracker

Introduction

Previous research showed that bullying experiences are associated with different ways of interpreting and behaving in bullying dynamics. However, it remains uncertain whether these distinctions can already be present during the first step of information processing: the allocation of attention.

Aims

The study explored attentional patterns of Italian students with different bullying experiences in daily life while observing different roles represented through bullying vignettes.

Methods

Participants (72 students, Mage= 11.18) were categorized as victims, bully-victims, or not involved based on their scores on a self-report questionnaire. They observed 9 bullying vignettes on which different portraits were presented (bully, victim, pro-bully, defender, bystander) while the eye-tracker registered attentional indexes (fixation, visit and duration).

Results

Kruskal- Wallis and pairwise comparisons revealed a significant effect for the portraits of the bully and the pro-bully as bully-victims exhibited greater fixations and visits than victims, while students not involved showed no significant differences with the other groups.

Conclusion

Our research reveals that bully-victims focused more on threatening cues while victims diverged their gaze from them, confirming that the experience of bullying influences how they explore aggressive situations. Learning how involved students direct their attention helps us understand different responses, leading to powerful interventions.

AI for Psychometrics: Validating Machine Learning Models in Measuring Emotional Intelligence with Eye-Tracking Techniques

AI, or artificial intelligence, is a technology of creating algorithms and computer systems that mimic human cognitive abilities to perform tasks. Many industries are undergoing revolutions due to the advances and applications of AI technology. The current study explored a burgeoning field-Psychometric AI, which integrates AI methodologies and psychological measurement to not only improve measurement accuracy, efficiency, and effectiveness but also help reduce human bias and increase objectivity in measurement. Specifically, by leveraging unobtrusive eye-tracking sensing techniques and performing 1470 runs with seven different machine-learning classifiers, the current study systematically examined the efficacy of various (ML) models in measuring different facets and measures of the emotional intelligence (EI) construct. Our results revealed an average accuracy ranging from 50-90%, largely depending on the percentile to dichotomize the EI scores. More importantly, our study found that AI algorithms were powerful enough to achieve high accuracy with as little as 5 or 2 s of eye-tracking data. The research also explored the effects of EI facets/measures on ML measurement accuracy and identified many eye-tracking features most predictive of EI scores. Both theoretical and practical implications are discussed.

The Effects of Covert Narcissism on Chinese College Students Cyberbullying: The Mediation of Hostile Attribution Bias and the Moderation of Self-Control

Purpose

The prevalence of cyberbullying has increased along with the growth of social media, which has brought about many adverse effects on individual development. The current study aimed to explore the connection between covert narcissism and cyberbullying and to test the roles of hostile attribution bias and self-control in the relationship between covert narcissism and cyberbullying.

Materials and Methods

A total of 672 Chinese college students filled up questionnaires measuring covert narcissism, cyberbullying, hostile attribution bias, and self-control.

Results

The results indicated that covert narcissism positively and significantly predicted cyberbullying. Hostile attribution bias partially mediated the relationship between covert narcissism and cyberbullying. Additionally, self-control moderated the relationship between covert narcissism and cyberbullying. Specifically, the positive predictive effect of covert narcissism on cyberbullying gradually weakened as self-control improved.

Conclusion

This study explored the underlying mechanism of cyberbullying and found that covert narcissism could affect cyberbullying through hostile attribution bias. Self-control moderated the relationship between covert narcissism and cyberbullying. The results have significant implications for the intervention and prevention of cyberbullying and additional evidence for the relationship between covert narcissism and cyberbullying.

The remediating effect of Attention Bias Modification on aggression in young offenders with antisocial tendency: A randomized controlled trial

BACKGROUND AND OBJECTIVES

An attention bias toward hostile stimuli is associated with an increased risk of aggressive behavior. Thus, reducing hostile attention bias may help to reduce aggression in young offenders. We evaluated the remediating effects of Attention Bias Modification (ABM) on hostile attention bias and aggressive behavior in Chinese male young offenders with antisocial tendencies.

METHODS

Institutionalized male young offenders (ages 16-18) were recruited and randomly assigned to ABM (n = 28), placebo (n = 28), or waiting list (n = 28). The ABM group received four weeks of training using visual search of emotional faces; the placebo group underwent similar training using visual search of neutral objects. Before and after treatment, aggressive behavior, attention bias toward positive stimuli and hostile stimuli were assessed.

RESULTS

Linear mixed models and hierarchical multiple regression analyses showed that the intervention effect of ABM was moderated by participants' initial attention bias. Young offenders with a high level of initial hostile attention bias, or with a low level of initial positive attention bias, benefitted most from ABM.

LIMITATIONS

The small sample size impedes investigation of the mechanism of the intervention's effects. Further research can determine whether the current results can be extrapolated to the population of female young offenders.

CONCLUSION

The results of the present study suggest that ABM is helpful for young offenders who show the greatest bias toward hostile stimuli and away from positive stimuli. These findings highlight the importance of matching the intervention and the participant.

TRIAL REGISTRATION

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Attentional variability and avoidance of hostile stimuli decrease aggression in Chinese male juvenile delinquents

BACKGROUND

As a prominent issue worldwide, juveniles' aggressive and violent crimes have attracted much interest in recent years. Based on the social information processing model, the present study aimed to evaluate the Chinese male juvenile delinquents' attention bias towards hostile stimuli from both static and dynamic perspectives. Additionally, the predictive effect of attention bias on aggressive behavior and the moderating effect of group (juvenile delinquents and the controls with no criminal history) were also investigated.

METHODS

The hostile attention bias and aggressive behavior of 76 juvenile delinquents (M_age = 17.5 years, SD = 0.59 years) and 67 controls (M_age = 18.3 years, SD = 0.73 years) were measured with the emotional dot-probe task, emotional Stroop task, and the Chinese version of the Buss & Perry aggression questionnaire, respectively.

RESULTS

The results showed that compared with controls, juvenile delinquents showed more attention biases towards hostile faces and words, and demonstrated higher levels of physical aggression and anger. Furthermore, the type of participants moderated the relationship between hostile attention bias and aggressive behavior. For juvenile delinquents, attention bias away from hostile stimuli and attention variability negatively predicted anger, while for controls, attention variability positively predicted self-directed aggression.

CONCLUSION

Attentional variability and avoidance of hostile stimuli are expected to reduce the aggressive level of Chinese male juvenile delinquents. The relationship between attention bias and aggression should be further considered and applied in the clinical practice.