UNASSIGNED: Research on food addiction has increased significantly in recent years. It has been demonstrated that food addiction can lead to impairments in physiological, psychological, and social functioning in individuals. However, there is a lack of studies investigating the influence of how individuals handle social situations on food addiction and the specific mechanisms involved.
UNASSIGNED: A cross-sectional survey was conducted with 1,151 university students, with a mean age of 21.44 (SD = 4.77) years. The sample comprised 74.46% female and 25.54% male students. Participants completed the Chinese version of the modified Yale Food Addiction Scale 2.0, the Social Physique Anxiety Scale, the Expressive Suppression Scale, and the Social Avoidance and Distress Scale. Statistical analyses were performed using SPSS 26.0 and the Process (Version 3.4) plug-in.
UNASSIGNED: The results of the study supported our hypothesis that the association between social physique anxiety and food addiction symptoms could be partially explained by expressive suppression and social avoidance and distress. This association remained significant even after adjusting for covariates such as gender, number of cigarettes smoked per day, bedtime, education, and BMI. Specifically, more severe social physique anxiety was found to be associated with frequent use of expressive suppression and social avoidance and distress, which in turn was associated with more severe food addiction symptoms.
UNASSIGNED: This study explored the role of expression suppression and social avoidance and distress in the relationship between social physique anxiety and food addiction symptoms. The findings provide a theoretical basis for developing interventions for food addiction in college students. These interventions could include helping students develop a healthy perception of body image, encouraging emotional expression, and promoting active social participation to reduce food addiction symptoms.

Wisdom is the hallmark of social judgment, but how people across cultures recognize wisdom remains unclear-distinct philosophical traditions suggest different views of wisdom\'s cardinal features. We explore perception of wise minds across 16 socio-economically and culturally diverse convenience samples from 12 countries. Participants assessed wisdom exemplars, non-exemplars, and themselves on 19 socio-cognitive characteristics, subsequently rating targets\' wisdom, knowledge, and understanding. Analyses reveal two positively related dimensions-Reflective Orientation and Socio-Emotional Awareness. These dimensions are consistent across the studied cultural regions and interact when informing wisdom ratings: wisest targets-as perceived by participants-score high on both dimensions, whereas the least wise are not reflective but moderately socio-emotional. Additionally, individuals view themselves as less reflective but more socio-emotionally aware than most wisdom exemplars. Our findings expand folk psychology and social judgment research beyond the Global North, showing how individuals perceive desirable cognitive and socio-emotional qualities, and contribute to an understanding of mind perception.

Aiming at the problem that existing emotion recognition methods fail to make full use of the information in the time, frequency, and spatial domains in the EEG signals, which leads to the low accuracy of EEG emotion classification, this paper proposes a multi-feature, multi-frequency band-based cross-scale attention convolutional model (CATM). The model is mainly composed of a cross-scale attention module, a frequency-space attention module, a feature transition module, a temporal feature extraction module, and a depth classification module. First, the cross-scale attentional convolution module extracts spatial features at different scales for the preprocessed EEG signals; then, the frequency-space attention module assigns higher weights to important channels and spatial locations; next, the temporal feature extraction module extracts temporal features of the EEG signals; and, finally, the depth classification module categorizes the EEG signals into emotions. We evaluated the proposed method on the DEAP dataset with accuracies of 99.70% and 99.74% in the valence and arousal binary classification experiments, respectively; the accuracy in the valence-arousal four-classification experiment was 97.27%. In addition, considering the application of fewer channels, we also conducted 5-channel experiments, and the binary classification accuracies of valence and arousal were 97.96% and 98.11%, respectively. The valence-arousal four-classification accuracy was 92.86%. The experimental results show that the method proposed in this paper exhibits better results compared to other recent methods, and also achieves better results in few-channel experiments.

Anthropomorphized robots are increasingly integrated into human social life, playing vital roles across various fields. This study aimed to elucidate the neural dynamics underlying users\' perceptual and emotional responses to robots with varying levels of anthropomorphism. We investigated event-related potentials (ERPs) and event-related spectral perturbations (ERSPs) elicited while participants viewed, perceived, and rated the affection of robots with low (L-AR), medium (M-AR), and high (H-AR) levels of anthropomorphism. EEG data were recorded from 42 participants. Results revealed that H-AR induced a more negative N1 and increased frontal theta power, but decreased P2 in early time windows. Conversely, M-AR and L-AR elicited larger P2 compared to H-AR. In later time windows, M-AR generated greater late positive potential (LPP) and enhanced parietal-occipital theta oscillations than H-AR and L-AR. These findings suggest distinct neural processing phases: early feature detection and selective attention allocation, followed by later affective appraisal. Early detection of facial form and animacy, with P2 reflecting higher-order visual processing, appeared to correlate with anthropomorphism levels. This research advances the understanding of emotional processing in anthropomorphic robot design and provides valuable insights for robot designers and manufacturers regarding emotional and feature design, evaluation, and promotion of anthropomorphic robots.

Non-suicidal self-injury (NSSI) is an international public health problem. Qualitative synthesis of the psychological experiences associated with NSSI in adolescents remains limited. This study aimed to systematically review the factors, emotional experiences, coping strategies, and help-seeking experiences of adolescents who engage in NSSI. A comprehensive search of 10 databases was conducted. Two researchers independently conducted study screening, data extraction, and quality assessment. Eighteen articles were included and analyzed using a meta-aggregation approach. Four themes were identified: (1) factors contributing to NSSI, (2) emotions associated with engaging in NSSI, (3) coping strategies, and (4) potential barriers to seeking help. Our findings provide a comprehensive picture of the psychological experiences of adolescents who engage in NSSI. They primarily adopt negative coping strategies to deal with serious problems, and there are potential barriers to seeking help. Further research is needed to explore the true needs of adolescents, as well as how schools, families, and hospitals can play a collaborative role in improving adolescents\' psychological issues.

Based on the theory of socio-emotional selectivity, this study examines the effect of digital engagement on the mental health of older individuals using data from the 2018 China Longitudinal Aging Social Survey (CLASS). The results show that digital engagement has a significant effect on the mental health of older individuals, manifested by a decline in depression and an enhancement of cognitive abilities. The results are robust by Using instrumental variables to solve endogenous problem and the propensity score matching method to solve selective bias. The analysis of heterogeneity demonstrates that digital engagement can significantly reduce the depression level of older people without chronic diseases and at lower ages and promote the cognitive ability of older adults without chronic diseases and older adults of higher ages. Mechanistic analysis shows that digital engagement can reduce depression in older adults by alleviating loneliness and improving emotional well-being and cognitive performance by enhancing social support. Therefore, digital engagement gives older people a more positive emotional experience and more social support and thereby improves mental health, delivering proactive answers to the problems an aging population brings.

Mixed emotions have attracted increasing interest recently, but existing datasets rarely focus on mixed emotion recognition from multimodal signals, hindering the affective computing of mixed emotions. On this basis, we present a multimodal dataset with four kinds of signals recorded while watching mixed and non-mixed emotion videos. To ensure effective emotion induction, we first implemented a rule-based video filtering step to select the videos that could elicit stronger positive, negative, and mixed emotions. Then, an experiment with 80 participants was conducted, in which the data of EEG, GSR, PPG, and frontal face videos were recorded while they watched the selected video clips. We also recorded the subjective emotional rating on PANAS, VAD, and amusement-disgust dimensions. In total, the dataset consists of multimodal signal data and self-assessment data from 73 participants. We also present technical validations for emotion induction and mixed emotion classification from physiological signals and face videos. The average accuracy of the 3-class classification (i.e., positive, negative, and mixed) can reach 80.96% when using SVM and features from all modalities, which indicates the possibility of identifying mixed emotional states.

Film cognition explores the influence of cinematic elements, such as editing and film color, on viewers\' perception. The Kuleshov effect, a famous example of how editing influences viewers\' emotional perception, was initially proposed to support montage theory through the Kuleshov experiment. This effect, which has since been recognized as a manifestation of point-of-view (POV) editing practices, posits that the emotional interpretation of neutral facial expressions is influenced by the accompanying emotional scene in a face-scene-face sequence. However, concerns persist regarding the validity of previous studies, often employing inauthentic film materials like static images, leaving the question of its existence in authentic films unanswered. This study addresses these concerns by utilizing authentic films in two experiments. In Experiment 1, multiple film clips were captured under the guidance of a professional film director and seamlessly integrated into authentic film sequences. 59 participants viewed these face-scene-face film sequences and were tasked with rating the valence and emotional intensity of neutral faces. The findings revealed that the accompanying fearful or happy scenes significantly influence the interpretation of emotion on neutral faces, eliciting perceptions of negative or positive emotions from the neutral face. These results affirm the existence of the Kuleshov effect within authentic films. In Experiment 2, 31 participants rated the valence and arousal of neutral faces while undergoing functional magnetic resonance imaging (fMRI). The behavioral results confirm the Kuleshov effect in the MRI scanner, while the neural data identify neural correlates that support its existence at the neural level. These correlates include the cuneus, precuneus, hippocampus, parahippocampal gyrus, post cingulate gyrus, orbitofrontal cortex, fusiform gyrus, and insula. These findings also underscore the contextual framing inherent in the Kuleshov effect. Overall, the study integrates film theory and cognitive neuroscience experiments, providing robust evidence supporting the existence of the Kuleshov effect through both subjective ratings and objective neuroimaging measurements. This research also contributes to a deeper understanding of the impact of film editing on viewers\' emotional perception from the contemporary POV editing practices and neurocinematic perspective, advancing the knowledge of film cognition.

Innovative products entering the market will cause dynamic changes in market demand, and consumers\' purchase regret and their return behavior make the market environment more and more complex, which in turn affects the dynamic decision-making in the supply chain. In this paper, under the situation of discrete decision time, combining with the objective reality, we make discrete modification to the classical Bass diffusion model (Bass model), construct a manufacturer-led, retailer-followed supply chain differential game model, analyze the optimal decision-making of the manufacturer and the retailer by combining with the theory of discrete optimal control, and then verify the conclusions by numerical simulation. The results show that: when retailers purchase directly from the manufacturer and sell in the market, the optimal pricing of the innovative product can make the supply chain as a whole, realizing Pareto optimality; consumer\'s purchase regret will increase the amount of returns, which will lead to the decrease of product sales and the profits of the manufacturer and the retailer; when the innovative product accounts for a different share of the market, the impact of purchase regret on the wholesale price and the retail price are also different. Therefore, manufacturers need to have an extensive comprehension of the market to minimize the negative effects of consumer regret and returns, and to formulate a reasonable pricing strategy for their products to gain as much profit as possible.

BACKGROUND: Prior research has indicated a potential connection between psychological stress and how individuals perceive their own age. Building on this foundation, the current study explores the relationship between negative emotions and self-perceived age.
METHODS: We conducted a cross-sectional analysis using data from the UK Biobank, a comprehensive cohort study representing the UK population. The analysis included 347 892 participants, aged between 39 and 73 years, of which 184 765 were women, accounting for 53.1% of the sample. Participants were categorized into three groups based on their self-perceived age: feeling younger than their chronological age (group Younger), feeling older than their chronological age (group Older), and feeling as old as their actual age (group Same). To investigate the relationship between negative emotions and self-perceived age, we utilized a multinomial logistic regression model with the Younger group serving as the reference category.
RESULTS: Of 347 892 participants, after adjusted for covariates, the results showed that participants with irritability, nervous feelings, worrier/anxious feelings or fed-up feelings, worry too long and loneliness/isolation are more likely to be rated as \"about your age\" or \"older than you are,\" with \"younger than you are\" as the reference group, indicating that negative emotions may influence one\'s self-perceived age. Among those negative emotions, irritability has the most significant impact self-perceived age, with the odds ratios (ORs) being 1.44 (95% CI: 1.35-1.54) and 1.11 (95% CI: 1.09-1.14).
CONCLUSIONS: Negative emotions are associated with older self-perceived age, and irritability has the greatest impact. Further studies analyzing self-perceived age are needed to take psychological factors into consideration.