Search Results (4,300)

Reliable evaluation of emotional expression in large language model (LLM) outputs remains methodologically under-specified, particularly for long-form generation where label-only correctness provides limited evidence of affective reliability. A claim-conditioned framework is introduced for cross-model comparison under matched elicitation conditions, with TEAS (Text Emotion Adherence Score) as its core continuous metric. Defined in a shared prototype space induced by a frozen reference encoder, TEAS combines affective separability with entropy-aware uncertainty, enabling reliability assessment beyond discrete agreement within a fixed evaluator. Evaluation is conducted on a controlled synthetic corpus under a ground-truth-free, claim-conditioned protocol across four widely used LLM families (Gemini, GPT, Grok, and Mistral). In addition to overall comparative ordering, auxiliary diagnostic measures are reported to localize failure modes and support interpretation of model behavior, together with Holm-corrected pairwise comparisons, sequence-level drift analysis, and local hyperparameter sensitivity analysis. Empirical results show stable endpoint separation, aggregation-sensitive differences among close models, measurable sequence-level degradation, and stable relative orderings under tested local parameter variations. Overall, the study provides an interpretable and statistically grounded protocol for assessing emotion-expression reliability in LLM-generated text within a fixed reference space rather than as a human gold measure of emotional truth. Full article

Background/Objectives: Thinness is widely idealized as a standard of beauty, and late school-age girls are increasingly exposed to sociocultural pressures that may be associated with excessive drive for thinness and maladaptive body esteem. These body-related cognitive distortions often emerge regardless of actual weight status and may precede unhealthy dieting behaviors and emotional difficulties. This study aimed to develop and evaluate a school-based Rational Emotive Behavior Therapy (REBT) intervention designed to modify excessive drive for thinness and maladaptive body esteem among late school-age girls. Methods: A quasi-experimental, non-equivalent control group design with repeated measures was employed. Participants were 62 girls in grades 5–6 recruited from two public elementary schools in South Korea (experimental group: n = 30; control group: n = 32). The experimental group participated in a five-week REBT intervention consisting of 10 structured sessions grounded in the A-B-C-D-E model, while the control group received no intervention. Outcomes were assessed at pretest, posttest, and follow-up, including drive for thinness, body esteem, positive affect, negative affect, disordered eating behaviors, and social media overuse. Data were analyzed using repeated measures ANOVA. Results: Significant group × time interaction effects were observed for drive for thinness, body esteem, positive affect, negative affect, and disordered eating behaviors, with greater changes observed in the experimental group. No significant group × time interaction was found for social media overuse. Conclusions: The school-based REBT intervention was associated with reductions in excessive drive for thinness and improvements in body esteem and was also associated with changes in emotional outcomes and reductions in disordered eating behaviors among late school-age girls. These findings support early cognitive modification as a preventive strategy within school settings. Full article

Suicide is a major public health problem worldwide, and its reported reasons and methods show marked variation by gender and age. Although suicide rates are generally higher among men, suicides among women demonstrate distinct sociodemographic and age-related patterns that remain insufficiently explored. In Türkiye, national suicide statistics are available; however, nationwide, age-stratified analyses focusing exclusively on women are limited. This study aimed to investigate long-term trends, age-related differences in reported reasons and methods of suicide among women in Türkiye, and to provide insights relevant to age- and gender-sensitive prevention strategies. This retrospective, nationwide descriptive study analysed female suicide data obtained from the Turkish Statistical Institute between 2009 and 2023. A total of 12,868 female suicide cases were included (mean age 36.5 ± 19.3 years). Data were evaluated according to year, age group, marital status, educational level, suicide cause, and suicide method. Causes and methods were classified based on official administrative categories. Descriptive statistics were calculated, and associations between age groups and suicide causes and methods were assessed using Pearson’s chi-square test. During the 15-year study period, 12,868 women died by suicide in Türkiye. The annual suicide rate ranged from 1.81 to 2.46 per 100,000 population, with the lowest rate observed in 2017 and the highest in 2022. Among all age groups, the most frequent cause of suicide was illness, especially in women aged 45 and older. The proportion of suicides due to illness was 13.9% in the 15–24 age group, 24.6% in 25–34, 41.0% in 45–54, and 42.3% in 55–64 (p < 0.001). Emotional and relationship-related causes were more prevalent among younger women, particularly in the 15–24 age group (4.8%), but declined significantly with age (p < 0.001). Economic hardship was the least cited cause overall, especially among women under 35 (p < 0.001). Regarding methods of suicide, hanging was the most common method in all age groups and increased with age—35.8% in 15–24, 55.1% in 45–54, and 63.5% in 75+ age group (p < 0.001). The use of chemical substances peaked in the 15–24 age group (12.4%) and declined in older women (5.8% in 75+). Firearm use showed a significant inverse relationship with age, from 24.6% in those under 15 to 0.8% in women aged 75 and over (p < 0.001). These age-related differences in both the causes and methods of suicide were statistically significant (p < 0.001). Female suicide in Türkiye exhibits pronounced age-dependent differences in both causes and methods. Illness-related suicides and hanging predominate in older age groups, while younger women show a more diverse pattern of reported reasons and methods. The high prevalence of nonspecific classifications highlights limitations in current suicide reporting systems. These findings underscore the need for improved suicide classification, enhanced surveillance, and age- and gender-sensitive prevention strategies tailored to women across the lifespan. Full article

School-based social and emotional learning (SEL) programs have the potential to meaningfully foster healthy development. NaliniKIDS is a school-based program designed to focus on promoting SEL and school connectedness by bridging physical and mental health through exercises, a book series, and schoolwide activities. This mixed-method study explored the effects of NaliniKIDS on students’ mental health and school climate and the teachers’ perspectives regarding the implementation in a racially diverse, urban, Title I public elementary school. Quantitative data comprised of student (N = 253) and parent (N = 29) self-reports at pre- and post-test; qualitative data were collected via two focus groups with teachers (N = 10 participants). Survey results showed small increase in prosocial behavior among students after NaliniKIDS implementation. Focus groups highlighted the importance of training, protecting time and resources, and adapting the program to students’ background to maximize its implementation and relevance. NaliniKIDS may be a promising SEL program that facilitates the integration of physical and emotional health. The findings emphasize the health benefits of investments and policies focused on school-based programs that are integrated in the school. The successful implementation of SEL programs such as NaliniKIDS may significantly promote elementary student physical and mental health. Full article

Background: Dating violence and emotional dependence are consistently associated with mental health problems among university students. However, less is known about how these associations operate indirectly and whether they differ by gender, particularly in Latin American contexts. Objective: To evaluate a model examining the association between dating violence (X) and mental health problems (Y) among university students, with emotional dependence (M) as an intervening variable and gender (W) as a moderator. Methods: A quantitative, cross-sectional study was conducted with 3202 university students. Participants completed the Dating Violence Questionnaire (CUVINO), the Emotional Dependence Questionnaire (CDE), and the Strengths and Difficulties Questionnaire (SDQ-Cas). Conditional process analyses were performed using Hayes’ PROCESS macro (Model 14) with bootstrapping procedures. Results: Dating violence and emotional dependence were significantly associated with internalizing mental health problems. Emotional dependence showed a significant indirect association between dating violence and internalizing problems. This indirect association varied by gender, as indicated by a significant index of moderated mediation. Conclusions: The findings support a conditional indirect association between dating violence and internalizing mental health problems through emotional dependence, moderated by gender. These results highlight the importance of considering relational and gender-related factors when examining the mental health correlates of dating violence among university students. Full article

Background/Objectives: Dietary behavior in eating disorders (EDs) is often framed through either nutritional or psychological perspectives, yet emerging evidence suggests that eating may involve a transdiagnostic, emotionally embedded, and relationally negotiated process. While research highlights the role of emotion regulation difficulties, perfectionism, control, and overvaluation of weight and shape in ED maintenance, less is known about how these processes are interpreted and managed in clinical practice across different cultural contexts. This study explored psychotherapists’ perspectives on dietary behavior, nutritional assessment, and interdisciplinary collaboration in ED treatment in Greece and the United Kingdom. Methods: Eighteen psychotherapists (9 Greek and 9 British) with experience in treating individuals with EDs participated in in-depth semi-structured interviews. Data were analyzed using reflexive thematic analysis. Results: Three themes were developed. First, therapists conceptualized dietary behavior as reflecting broader transdiagnostic psychological processes, particularly perfectionism, control, emotion regulation difficulties, and body image concerns. Second, nutritional assessment and intervention (e.g., food diaries and meal plans) were experienced as emotionally significant practices that required negotiation of timing, meaning, and clients’ readiness for change. Third, interdisciplinary collaboration was described as involving ongoing negotiation of nutritional authority, with therapists balancing nutritional considerations and psychological safety, influenced by contextual differences between UK and Greek mental health systems. Conclusions: Findings suggest that dietary behavior in ED treatment may benefit from approaches that integrate psychological and nutritional perspectives. Clinicians may consider attending to clients’ emotional readiness, the symbolic meanings of food, and the dynamics of multidisciplinary collaboration, offering insights that can inform clinical practice and future research. Full article

Large Language Models (LLMs) demonstrate remarkable performance across a variety of natural language understanding tasks, yet their sensitivity to emotional framing in user prompts remains underexplored. This paper presents an empirical study investigating how four emotional tones—joy, apathy, anger, and fear—affect LLM performance on the SuperGLUE benchmark. We evaluate five instruction-tuned, open-weight models across eight diverse tasks, systematically modulating input prompts with affective cues while keeping semantic content constant. Results reveal that prompts framed with joy and apathy lead to consistently higher accuracy, with gains of up to 4.5 percentage points compared to fear-framed inputs, which yield the lowest performance. These findings demonstrate that affective modulation in user prompts measurably impacts LLM reasoning and task outcomes, suggesting that emotional framing is not merely stylistic but functionally relevant to model behavior. Our study provides a reproducible experimental framework and an open-source prompt set, offering a foundation for future research on affect-aware prompting strategies and their implications in human–AI interaction. Full article

Personality recognition and emotion recognition, two core tasks within affective computing, are fundamentally constrained by data scarcity as collecting and annotating human behavioral data is expensive and restricted by privacy concerns. Under these limited data conditions, existing models tend to rely on superficial shortcut features such as background appearance, lighting conditions, or color variations, rather than behavior-relevant cues including facial expressions, posture, and motion dynamics. To address this issue, we propose Style-Abstraction-based Data Augmentation, a style transfer-based augmentation strategy that reduces dependency on low-level appearance information while preserving high-level semantic cues. Specifically, we employ cartoonization to generate stylized variants of training videos that retain expressive characteristics but remove stylistic bias. We validate our approach on three diverse personality benchmarks (First Impression v2, UDIVA v0.5, and KETI) and emotion benchmark(Emotion Dataset) using state-of-the-art models including ViViT (Video Vision Transformer), TimeSformer, and VST (Video Swin Transformer). Our experiments indicate that increasing the proportion of style-abstracted data in the training set can improve performance on the evaluated datasets. Notably, our method yields consistent gains across all benchmarks: a 0.0893 reduction in MSE on UDIVA v0.5 (with VST), a 0.0023 improvement in 1-MAE on KETI (with TimeSformer), and a 0.0051 improvement on First Impression v2 (with TimeSformer). Furthermore, extending style-abstraction-based data augmentation to a four-class categorical emotion recognition task demonstrates similar performance gains, achieving up to a 3.44% accuracy increase with the TimeSformer backbone. These findings verify that our style-abstraction-based data augmentation facilitates learning of behavior-relevant features by reducing reliance on superficial shortcuts. Overall, cartoonization-based style abstraction for data augmentation functions as both an effective augmentation strategy and a regularization mechanism, encouraging the model to learn more stable and generalizable representations for affective computing applications. Full article

Background and Objectives: The aim of this study is to evaluate impulsivity in childhood anxiety disorders and to examine its relationship with anxiety sensitivity and emotion regulation. Materials and Methods: The study group consisted of a total of 60 children aged 8–12 years diagnosed with generalized anxiety disorder (GAD, n = 30) and other anxiety disorders (n = 30). The control group consisted of 40 healthy children of similar age without a psychiatric diagnosis. Data collection forms included the Barratt Impulsiveness Scale Short Form (BIS-S), the Children’s Anxiety Sensitivity Index (ASI-3), the Emotion Regulation Checklist (ERC), and The Screen for Child Anxiety Related Emotional Disorders (SCARED). Results: Our study found no significant differences in BIS-S scores between GAD, other anxiety disorders, and the control group. The total/physical and ERC subscales of the ASI-3 were higher in the generalized anxiety disorder and other anxiety disorder group than in the control group. However, there were no significant differences in the social dimension and cognitive dimension scores of the ASI-3. It has been determined that anxiety sensitivity does not significantly mediate the relationship between emotion regulation and impulsivity, and that emotional variability/negativity is directly and completely related to impulsivity. Conclusions: Our study suggests that children with anxiety disorders experience greater difficulties in regulating their emotions compared to healthy children, and that emotional variability is directly related to impulsivity. In this context, enhancing emotion regulation skills in anxiety disorders may prove to be a pivotal factor in the efficacy of treatment and the maintenance of behavioral control. Full article

Electroencephalography (EEG) has attracted growing interest as a biometric modality because it reflects ongoing brain activity and is inherently difficult to counterfeit. At the same time, EEG signals are influenced by internal conditions such as emotions, which may affect identification stability, particularly when recordings are obtained using portable consumer-grade systems. This study examines how emotional states influence EEG-based biometric performance and evaluates deep learning architectures to determine an effective modeling approach for cross-emotion robustness. EEG data were collected from 65 participants using a 14-channel Emotiv EPOC X headset, with 54 subjects retained after self-reported emotional validation. Recordings were acquired under neutral, positive, and negative visual stimuli. To address variability associated with portable acquisition, preprocessing made use of the device’s internal signal quality metrics to select reliable segments, compensate for degraded regions, and reduce noise. Among the evaluated models, a Bidirectional Long Short-Term Memory (BiLSTM) network enhanced with Convolutional Block Attention Module (CBAM) and Multi-Head Self-Attention (MHSA) achieved highest performance in our experiments. The model was trained on neutral-state data and subsequently evaluated under emotional conditions. It reached 95.91% accuracy in the neutral condition and maintained high performance under positive (94.31%) and negative (92.99%) states. Despite a modest decline under negative stimuli, identification performance remained stable. These findings support the feasibility of robust EEG-based biometric authentication using consumer-grade devices in realistic settings. Full article

Facial emotion recognition (FER) plays an important role in healthcare, human–computer interaction, and intelligent security systems. However, despite recent advances, many state-of-the-art FER methods depend on computationally intensive CNN or transformer backbones and large-scale annotated datasets while suffering noticeable performance degradation under cross-dataset evaluation because of domain shift. These limitations hinder practical usage in resource-constrained and real-world environments. To address this issue, we propose Cross-Adaptive Gated Fusion Network (CA-GFNet), a lightweight dual-stream FER framework that explicitly combines shallow structural features with deep semantic representations. The proposed architecture integrates domain-robust gradient-based descriptors with compact deep features extracted from a VGG-based backbone. After face detection and normalization, the structural stream captures fine-grained local appearance cues, whereas the semantic stream encodes high-level facial configurations. The two feature streams are projected into a shared latent space and adaptively fused using a gated fusion mechanism that learns sample-specific weights, allowing the model to prioritize the more reliable feature source under dataset shift. Extensive experiments on KDEF along with zero-shot cross-dataset evaluation on CK+ using a strict train-on-KDEF/test-on-CK+ protocol with subject-independent splits demonstrate the effectiveness of the proposed method. CA-GFNet achieves 99.30% accuracy on KDEF and 98.98% on CK+ while requiring significantly fewer parameters than conventional deep FER models. These results confirm that adaptive gated fusion of shallow and deep features can deliver both high recognition accuracy and strong cross-dataset robustness. Full article

Background/Objectives: Attention Deficit Hyperactivity Disorder (ADHD) is one of the most common neurodevelopmental disorders in childhood and it tends to remain during adulthood. It not only affects cognitive abilities and behavior but also often presents emotional disturbances and alterations in the perceived quality of life. These symptoms are primarily related to dysfunctions in the ventromedial and dorsolateral prefrontal network. The main objective was to evaluate the feasibility and explore the initial outcomes of an integrated protocol combining neuropsychological treatment and transcranial direct current stimulation (tDCS). Methods: This study presents a single-case experimental A-B design of a 21-year-old woman, diagnosed with predominantly inattentive ADHD, treated at the University Psychology Clinic of Loyola Andalucía University. The treatment was carried out twice a week for 5 weeks (10 sessions in total), with 20 min of anodal tDCS at F3 and cathodal tDCS at F4 (2 mA), while digital neurorehabilitation exercises and psychotherapeutic support were provided. Results: An overall significant improvement was observed in cognitive functions (p = 0.008), with clinically significant gains in cognitive flexibility, visual working memory, and planning. Mixed results were found in inhibition, with improvement in interference control but no change in response inhibition. No significant changes were observed in sustained attention, auditory working memory, or processing speed. In terms of emotional state, an overall improvement was noted (p = 0.046), particularly in depression symptoms and perceived quality of life related to physical and psychological health. However, no significant changes were observed in anxiety symptoms or in areas related to the environment and social relationships. These findings reflect pilot-level evidence of clinical change within a feasibility framework. Conclusions: The combined treatment was found to be safe and feasible, showing promising preliminary improvements in cognitive and emotional domains. As a single-case study, these results serve as hypothesis-generating evidence for future controlled trials. Full article

Objective: To evaluate changes in emotion regulation, skin-picking disorder (SPD) severity, and repetitive thoughts and behaviors in adolescents with attention-deficit/hyperactivity disorder (ADHD) and comorbid SPD during methylphenidate treatment, and to examine the association between emotion regulation and SPD severity. Materials and Methods: This naturalistic follow-up study included 26 adolescents aged 11–17 years with ADHD and comorbid SPD. Participants received methylphenidate and were reassessed after three months. Emotion regulation, SPD severity, and repetitive thoughts and behaviors were assessed at baseline and follow-up using the Difficulties in Emotion Regulation Scale (DERS), Skin Picking Scale–Revised (SPS-R), and Repetitive Thoughts and Behaviors Scale–Child Form (RTBS-CF). Pre–post differences were analyzed using paired-sample tests, and associations were examined using correlation and linear regression analyses. Results: Significant reductions were observed in total DERS scores (p < 0.001, Cohen’s d = 1.35) and all subscales except non-acceptance (p = 0.686, Cohen’s d = 0.08). SPS-R and RTBS-CF scores decreased significantly (both p < 0.001, Cohen’s d = 1.79 and 0.91, respectively). Changes in DERS scores were moderately correlated with changes in SPS-R scores (r = 0.554, p = 0.003). Changes in emotion regulation were significantly associated with changes in SPD severity, accounting for approximately 31% of the variance in this sample. Conclusions: Methylphenidate treatment was associated with significant improvements in emotion regulation and concurrent reductions in skin-picking severity in adolescents with ADHD and comorbid SPD. Given the single-arm, pre–post naturalistic design, these findings should be interpreted as associative and exploratory rather than causal. Full article

Introduction: Lifestyle is characterized by identifiable behavioral patterns that can affect individuals’ health, and is considered one of the predominant factors for maintaining both quality of life and people’s health. This triad (lifestyle, quality of life and health) is closely associated with well-being. Objective: The aim of this study is to evaluate the relationship between lifestyles, well-being, and self-esteem in students who have completed secondary education and are in the process of transitioning to higher education. Methods: Data were collected using a questionnaire of sociodemographic (e.g., age, gender) and physical (e.g., BMI) variables, a Self-Esteem Scale, a Well-Being scale, and the FANTASTICO Lifestyle questionnaire. Statistical analysis was performed using canonical correlation analysis and a Structural Equation Model. Results: The sample consisted of 235 students, with a mean age of 18.4 years. Canonical correlation analysis revealed that lifestyle explains 58.5% of the variance in mental health. The first (most important) canonical function (r = 0.86; p < 0.001) highlighted that the domains of introspection, sleep/stress management, and family/social support are the primary predictors of higher levels of self-esteem and psychological well-being. Structural Equation Modeling confirmed that lifestyle positively predicts psychological well-being through both direct and indirect pathways (β = 0.172; 95.0% BC CI [0.095, 0.253]). Self-esteem emerged as a significant partial mediator in this relationship, suggesting that healthy lifestyle habits reinforce the perception of personal competence, which, in turn, enhances emotional adjustment. Together, these findings validate the dynamic triad between behavior, self-perception, and well-being during the transition to higher education. Conclusions: This study shows that the transition to higher education is a pivotal period where lifestyle patterns significantly shape students’ psychological adjustment. The findings confirm that a healthy lifestyle, specifically centered on stress management, sleep, and social support, serves as a robust predictor of both self-esteem and psychological well-being. By identifying self-esteem as a key partial mediator, the results suggest that healthy habits do more than just improve physical health. Full article

Background/Objective: Breast cancer is one of the leading diseases affecting the Brazilian population and is often diagnosed at advanced stages. Due to its heterogeneity, treatment involves multiple therapeutic modalities, such as chemotherapy, hormone therapy, immunotherapy, and radiotherapy. The aim of this study was to characterize the profile of patients undergoing treatment for breast cancer in a private hospital in southern Brazil, and to assess the physical and psychological effects associated with different therapeutic modalities. Methods: An ambidirectional longitudinal cohort study was conducted from September 2018 to December 2024, incorporating retrospective data since 2013. Clinical and therapeutic data were collected, and Patient-Reported Outcome Measures (PROMs) using the QLQ-C30 Summary Score (QLQ-BR23, FACT-ES, BREAST-Q, LMC21) and Symptom Global Score questionnaires were analyzed using mixed-effects models to evaluate physical, emotional, cognitive, social, and overall quality-of-life domains, as well as body image. The temporal trend of time-to-treatment was assessed via linear regression. Results: Among 871 individuals evaluated, 98.4% were female, and invasive ductal carcinoma was the predominant histological type (75.1%). Radiotherapy was one of the most frequently used treatment modalities (39.2%), while immunotherapy had the lowest usage rate (2.7%). A significant reduction in the time between diagnosis and initiation of treatment was observed from 2013 to 2024 (from 21.0 to 10.9 days; p < 0.01), reflecting improvements in healthcare services. Mixed-effects models for PROMs indicated significant improvements across all assessed domains (p < 0.01) over the 48-month follow-up, despite a median follow-up of 22 months. Conclusions: High-quality and timely oncological care provided to breast cancer patients in a private hospital in southern Brazil demonstrates the implementation of a dynamic, agile, and human-centered care model, contributing to improved clinical and patient-reported outcomes validated by robust longitudinal analysis. Full article