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.

To determine if the Central Sensitization Inventory questionnaire (CSI) functions as a mental health measure among a cross-section of people seeking musculoskeletal specialty care, we asked: (1) What is the association of CSI total score and item groupings identified in factor analysis with mental health measures? and (2) What is the association between specific CSI items that represent each factor well and specific mental health measures? One hundred and fifty-seven adults seeking specialty care for musculoskeletal symptoms completed the CSI, a measure of catastrophic thinking, and 3 measures of distress (symptoms of health anxiety, general anxiety, and depression). Exploratory factor analysis was used to identify item groupings. Exploratory factor analysis identified 4 item groupings (factors): (1) thoughts and feelings (mental health), accounting for 52% of the variation in the CSI, (2) urinary and visual symptoms (15%) (3) body aches (10%), and (4) jaw pain (8.1%). More than half the variation in both the CSI total score (51%) and the thoughts and feelings factor (57%) were accounted for by variation in measures of catastrophic thinking and distress. Specific items that account for large amounts of the variation in the CSI also had notable correlations with mental health measures. The strong relationship between the CSI and thoughts and emotions suggests that the CSI functions largely as a mental health measure. If the concept of central sensitization is to help people get and stay healthy, it will depend on evidence that central sensitization can be measured and quantified distinct from mental health.

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.

Heart rate variability (HRV) has been linked to resilience and emotion regulation (ER). How HRV and brain processing interact during ER, however, has remained elusive. Sixty-two subjects completed the acquisition of resting HRV and task HRV while performing an ER functional Magnetic Resonance Imaging (fMRI) paradigm, which included the differential strategies of ER reappraisal and acceptance in the context of viewing aversive pictures. We found high correlations of resting and task HRV across all emotion regulation strategies. Furthermore, individuals with high levels of resting, but not task, HRV showed numerically lower distress during ER with acceptance. Whole-brain fMRI parametrical modulation analyses revealed that higher task HRV covaried with dorso-medial prefrontal activation for reappraisal, and dorso-medial prefrontal, anterior cingulate and temporo-parietal junction activation for acceptance. Subjects with high resting HRV, compared to subjects with low resting HRV, showed higher activation in the pre-supplementary motor area during ER using a region of interest approach. This study demonstrates that while resting and task HRV exhibit a positive correlation, resting HRV seems to be a better predictor of ER capacity. Resting and task HRV were associated with ER brain activation in mid-line frontal cortex (i.e. DMPFC).

UNASSIGNED: This study aimed to explore the arousal and valence that people experience in response to Hangul phonemes based on the gender of an AI speaker through comparison with Korean and Chinese cultures.
UNASSIGNED: To achieve this, 42 Hangul phonemes were used, in a combination of three Korean vowels and 14 Korean consonants, to explore cultural differences in arousal, valence, and the six foundational emotions based on the gender of an AI speaker. A total 136 Korean and Chinese women were recruited and randomly assigned to one of two conditions based on voice gender (man or woman).
UNASSIGNED: This study revealed significant differences in arousal levels between Korean and Chinese women when exposed to male voices. Specifically, Chinese women exhibited clear differences in emotional perceptions of male and female voices in response to voiced consonants. These results confirm that arousal and valence may differ with articulation types and vowels due to cultural differences and that voice gender can affect perceived emotions. This principle can be used as evidence for sound symbolism and has practical implications for voice gender and branding in AI applications.

BACKGROUND: Having more \"autistic traits\" is associated with an increased risk of mental health conditions. However, few studies have examined autistic traits in nonclinical samples. This study aims to analyze the relationship between autistic traits and internalizing symptoms among early adolescents and to examine the moderating effect of self-efficacy.
METHODS: Survey data were collected from early adolescents ages 10-14 living in Darjeeling, India (n = 274) to assess autistic traits, self-efficacy, and internalizing symptoms.
RESULTS: Higher internalizing symptoms were significantly associated with a higher report of autistic traits. Academic, social, and emotional dimensions of self-efficacy moderated the relationship between autistic traits and internalizing symptoms.
CONCLUSIONS: The moderation effects between social and emotional self-efficacy among youth with high versus low autism trait scores suggest the need for social-emotional learning interventions designed for and with neurodivergent youth. Such interventions aim to reduce internalizing symptoms during early adolescence and improve future mental health trajectories.

Introduction: The preferences of people with profound intellectual and multiple disabilities (PIMD) often remain unfulfilled since it stays challenging to decode their idiosyncratic behavior resulting in a negative impact on their quality of life (QoL). Physiological data (i.e. heart rate (variability) and motion data) might be the missing piece for identifying emotions of people with PIMD, which positively affects their QoL. Method: Machine learning (ML) processes and statistical analyses are integrated to discern and predict the potential relationship between physiological data and emotional states (i.e. numerical emotional states, descriptive emotional states and emotional arousal) in everyday interactions and activities of two participants with PIMD. Results: Emotional profiles were created enabling a differentiation of the individual emotional behavior. Using ML classifiers and statistical analyses, the results regarding the phases partially confirm previous research, and the findings for the descriptive emotional states were good and even better for the emotional arousal. Conclusion: The results show the potential of the emotional profiles especially for practitioners and the possibility to get a better insight into the emotional experience of people with PIMD including physiological data. This seems to be the missing piece to better recognize emotions of people with PIMD with a positive impact on their QoL.

BACKGROUND: Healthy siblings of children with life-limiting conditions often experience emotional and behavioural struggles over the course of the ill child\'s condition(s). Resources to support these siblings are limited due to a lack of understanding about their needs. Therefore, this study was designed to characterize the emotional and behavioural trajectories among siblings of children with progressive, life-limiting genetic, metabolic, or neurological conditions over a 12-month observation period.
METHODS: Seventy siblings were recruited from a large-survey based study (Charting the Territory) that examined the bio-psychosocial health outcomes of parents and siblings. Linear mixed effect models were used to assess the association between siblings\' emotions and behaviour trajectories and selected demographic variables. Siblings\' emotions and behaviour were measured with Child Behaviour Checklist (CBCL).
RESULTS: Siblings\' mean age was 11.2 years at baseline and Internalizing, Externalizing, and Total Behaviour Problems mean scores were within normal ranges across time. However, 7-25% of siblings had scores within the clinical range. Brothers had higher levels of Internalizing Problems than sisters, whereas sisters had higher levels of Externalizing Problems than brothers. When treatment was first sought for the ill child less than a year prior to study participation, siblings had higher levels of Internalizing and Externalizing Problems compared with siblings who participated more than one year after treatment was sought.
CONCLUSIONS: Healthy siblings experience emotional and behavioural problems early in the child\'s disease trajectory. Although these problems improve with time, our findings show that brothers and sisters experience different types of challenges. Therefore, timely support for siblings is important as they navigate through the uncertainties and challenges.

BACKGROUND: Undergraduates\' workplace learning is an important part of health sciences education. Educational psychology research considers many different aspects of self-regulated learning at the workplace, including cognition, motivation, emotions, and context. Multivariate longitudinal and diary studies in this field require fewer items than alternatives or even a single item per construct and can reveal the sub-processes of workplace learning and contribute to a better understanding of students\' learning. Short instruments are necessary for application in workplace settings, especially stressful ones, to mitigate survey fatigue. The present study aimed to assess the psychometric properties of single items measuring various aspects of workplace learning.
METHODS: Twenty-nine single items selected from the Workplace Learning Inventory in Health Sciences Education were analyzed for reliability, information reproduction, and relationships within the nomological network. The authors additionally analyzed four generally formulated single items\' relationships with the full Workplace Learning Inventory scales and external criteria within the nomological network. Participants were 214 ninth- or tenth-semester veterinary medicine students in Austria and Germany who were learning at varied workplaces during the winter semester of 2021/2022.
RESULTS: Of the 29 single items selected from existing scales, 27 showed sufficient reliability, but mixed results were obtained regarding validity. Although the items\' relationships within the nomological network were similar to those of the full scales, information reproduction was insufficient for most items. The four general single items showed acceptable validity, but the reliability of these measures of states could not be assessed.
CONCLUSIONS: This paper reported findings on the psychometric properties of single items for undergraduates\' workplace learning in health science education. The findings are crucial for deciding whether to use scales versus single-item measures in future studies. By applying the findings, researchers can be more economical in their workplace learning data collection and can include more constructs.

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.