搜索结果：affective

Individuals with autism spectrum disorder experience difficulties in the social interaction and communication domain, which includes recognising and expressing emotions, as well as observable behaviours such as verbal and facial expressions, gestures, and intonations, also known as social-affective behaviours. Such individuals need to learn social-affective behaviours appropriate for the social context to perceive the reasons and conditions that give rise to emotions. This study aimed to compare the effectiveness and efficiency of video modelling (VM) and video-animated modelling (VAM) in acquiring, maintaining, and generalising three social-affective behaviours (verbal and facial expressions and gestures) together in children with autism spectrum disorder. Three children aged between 4 and 6 years with autism spectrum disorder and their mothers participated in the study. The study used the nested form of a single-case design with non-concurrent multiple baselines and an adapted alternation of VM and VAM conditions. The results indicated that both VM and VAM procedures were effective, with no consistent or systematic differences across participants to acquire contextually appropriate social-affective behaviours including verbal and facial expressions and gestures. The efficiency findings varied across participants in terms of the number of errors and total time. Social validity findings showed that the participating children's mothers and teachers expressed positive opinions on the interventions.Recommendations and future research issues are discussed in line with the findings. Social-affective behaviours refer to observable behaviours, such as verbal and facial expressions, gestures, and intonations, displayed to recognise and express emotions with a social communicative function. Children with autism spectrum disorder (ASD) have difficulties in social interaction and communication manifested as an inability to understand and express emotions through social-affective behaviours. They display social-affective behaviours less accurately, and in out-of-context. Video-animated modelling is as effective as video modelling in teaching social-affective behaviours to children with ASD. Therefore, teachers can prefer to use video animated modelling, as an alternative and enjoyable option, in teaching social-affective behaviours appropriate for the social context to perceive the conditions that give rise to emotions.

Dairy calves are typically reared in environments that differ greatly from naturalistic conditions: separated from their dam after birth, housed without peer contact, and unable to graze or have outdoor access. An improved understanding of the effect of the farming environment on calves' affective states may help refine management practices to improve dairy calf welfare. In this narrative review, we examine how characteristics of dairy calf rearing systems relate to both short- and long-term affective states. Affective states are commonly inferred from behavioral proxy measures (e.g., changes in time budgets, play, etc.) or conditioned responses to affective-state paradigms. We categorized environmental elements through physical, social, and temporal components and discuss the current knowledge on their effects on indicators of affective states. Consistent evidence supports that physical features such as adequate milk allowance, different sources of solid food (e.g., concentrate and forage), soft and dry lying surfaces; and a social environment allowing full contact with conspecifics appear important for promoting positive affective states and reducing negative ones in dairy calves. Although the temporal characteristics of environmental features remain comparatively underexplored, available evidence suggests factors such as timing, predictability, and control can modulate how physical and social components are experienced. Overall, knowledge regarding longer-lasting mood states in dairy calves remains limited. Addressing these gaps through future research could help refine rearing practices that support not only the reduction of negative states, but also the promotion of positive welfare in dairy calves.

Bipolar disorders (BDs) represent a significant global health challenge, with frequent and severe affective episodes that impair quality of life. Accurate, early prediction of these episodes remains difficult. Recent advances in mobile sensing offer new possibilities to detect prodromal changes via smart digital phenotypes, such as geolocation data. This study aimed to examine whether spatial exploratory behavior, assessed via passive GPS data, can predict depressive and manic episodes in individuals with BD. Specifically, we evaluated the predictive value of unique places visited and related mobility metrics using statistical process control (SPC) techniques to identify both early deviations indicative of prodromal states and changes occurring during ongoing affective episodes. Using high-resolution GPS data from the BipoSense dataset, we applied Density-Based Spatial Clustering of Applications with Noise to extract behavioral mobility indicators: number of unique places visited, frequency of location changes, and time spent per location. We implemented exponentially weighted moving average (EWMA)-based SPC to identify "out-of-bounds" deviations from individual baselines. We then tested the alignment of these deviations with affective episodes and the prodromal periods. Optimization of SPC parameters (λ and control limit L) was performed to enhance predictive accuracy. The analysis included 28 participants with BD and a total of 10,213 observation days, covering 26 depressive and 20 (hypo)manic episodes. Examining whether control limits distinguish affective episodes from euthymic days via multilevel models revealed that median time spent at clusters indicated both depressive and (hypo)manic episodes the best, whereas the number of unique clusters showed no significant association with phase transitions. While EWMA-SPC detected behavioral deviations during affective episodes, no single variable consistently met predefined thresholds for both sensitivity and specificity. Optimized SPC settings improved performance, but the number of unique places alone did not robustly predict prodromal or acute episodes. No statistically significant predictive accuracy (eg, sensitivity >70% and specificity >70%) was achieved for any individual indicator (P>.05). However, some SPC charts suggested within-person temporal deviations preceding episodes, indicating limited yet potentially informative patterns. Although unique places visited alone may not suffice as a predictive marker, the application of EWMA-based SPC to GPS data holds promise for the development of smart digital phenotypes. Although our analysis to predict upcoming episodes did not yield robust predictive accuracy in its current form, it provides a promising conceptual framework for individualized, low-burden behavioral monitoring. Further research is needed to refine existing digital biomarkers, develop new ones, and validate their clinical utility in reducing the frequency and severity of illness phases.

Affective Explanation Captioning (AEC) aims to perform viewer-centered visual emotion analysis by not only identifying the emotions evoked by an image but also explaining their underlying causes. Prior efforts have achieved promising results by fine-tuning LLMs on affective data; however, two key challenges remain: 1) the inherent subjectivity of human emotion leads to diverse interpretations of the same image, making it difficult for models to catch dominant emotions; and 2) the affective gap between abstract emotions and concrete visual content hinders models from capturing both semantic and emotional aspects effectively. To tackle these challenges, we propose Consensus-Prompted Emotion Reasoning (CPER), a new framework that explicitly models emotional diversity and enforces emotional-semantic alignment. Inspired by psychological studies, we observe that common emotional patterns often emerge within certain groups, which we refer to as affective consensus. Capturing this consensus across varying levels is helpful for bridging the subjectivity in AEC. Specifically, we introduce a consensus-based bucket prompt, which depicts the consensus level of each emotional perspective, serving as a control signal to adjust the emotion reasoning. To reconcile abstract emotion understanding and concrete visual grounding, we design a dual-space representation, where a CLIP encoder extracts objective semantic evidence and an emotion encoder captures abstract affective cues for AEC. Furthermore, an emotion consistency learning strategy is devised, which explicitly aligns the generated explanation with the input image and the emotion label, ensuring both emotionally and semantically grounded explanations. Extensive experiments on three benchmark datasets, ranging from visual arts (ArtEmis v1.0 and ArtEmis v2.0) and real-world images (Affection), demonstrate the effectiveness of our CPER in terms of emotional diversity and semantic coherence compared to state-of-the-art methods. Our code is publicly available at https://github.com/songpipi/CPER.

Emotions are closely implicated in how states are represented and interpreted. This study examines the affective dimensions of South Korean media portrayals of the United States and China from 1992 to 2025, focusing on variation in evaluative tone and emotional intensity. Drawing on theories of affective framing and media agenda-setting, the analysis traces long-term patterns in valence and arousal using a large corpus of newspaper articles and a computational text analysis approach. The results indicate a persistent asymmetry. Coverage of the United States remains relatively stable, with moderately positive evaluations and low levels of emotional intensity, whereas portrayals of China become more negative and more affectively charged over time. These differences appear as sustained patterns rather than isolated fluctuations and are consistent with broader features of South Korea's geopolitical context, including alliance relations, historical memory, and media environments. By documenting these patterns, this study contributes to the analysis of affect in media discourse and provides a framework for examining how major powers are represented in national contexts over time.

Marital status, such as marriage and divorce, is an important aspect of one's life and is associated with biopsychosocial and economic factors. The present study aimed to investigate the association of marital status with affective temperament, education, occupation, and bonding style. The dataset included 112 individuals consisting of 28 unmarried, 69 married, and 15 divorced individuals. First, demographic data, including age, gender, education, occupation, affective temperament, and bonding style, were compared among the three groups (unmarried, married, and divorced) using analysis of variance or χ2 test. Second, multinominal logistic regression analyses were performed. The proportion of full-time employees was significantly lower than that of homemakers in married participants compared with divorced participants, whereas neither education, affective temperament, nor parental bonding was significantly associated with marital status. The present findings suggest that the proportion of full-time employees may be significantly lower than that of homemakers in married participants compared with divorced participants. Further prospective studies are needed to clarify causality and additional contributing factors.

Internet use plays an important role in social participation in later life, yet little is known about how different domains of Internet use are linked to social outcomes or which factors shape engagement in these domains. Using an integrative approach, this study examines cognitive and affective attitudes toward Information and Communication Technology (ICT), age, and gender as predictors of social, informational, and entertainment-related Internet use and investigates how these domains relate to subjective (loneliness) and objective (social activity) indicators of social participation. Data were drawn from the baseline assessment of the SMART-AGE randomized controlled trial, comprising 648 community-dwelling adults aged 67-93 years (M = 75.0, SD = 5.63; 52% female). The proposed structural equation model showed good fit to the data. Positive affective but not cognitive attitudes as well as younger age were significantly correlated with all three Internet use domains. Male gender was associated with greater informational and entertainment Internet use, but not with social use. Among the Internet use domains, social use was linked to lower loneliness, informational use was positively associated with social activity, and entertainment use was negatively associated with social activity. Taken together, these findings highlight the importance of affective attitudes in shaping engagement in different forms of Internet use and contribute to a more nuanced understanding of how different forms of Internet use are related to social participation in later life.

Guided by self-determination theory (SDT), we examined whether department-based need-supportive leadership, conceptualized as an SDT-based leadership behavior construct, is associated with affective job satisfaction among Chinese university teachers and whether work-related basic psychological need satisfaction and work motivation statistically account for this association through independent and serial indirect pathways. We surveyed in-service Chinese university teachers (N&#x202f;=&#x202f;424). After controlling for gender, age, and academic rank, we tested a regression-based serial mediation model (PROCESS Model 6; 5,000 percentile bootstrap samples). Department-based need-supportive leadership was positively associated with affective job satisfaction (&#x3b2;_total&#x202f;=&#x202f;0.334, p&#x202f;<&#x202f;0.001; total effect B&#x202f;=&#x202f;0.4938, 95% CI [0.3625, 0.6252]). The direct effect remained significant after including work-related basic psychological need satisfaction and work motivation (&#x3b2;&#x202f;=&#x202f;0.187, p&#x202f;<&#x202f;0.001; c'&#x202f;=&#x202f;0.2758, 95% CI [0.1491, 0.4026]). The total indirect effect was 0.2180 (95% CI [0.1528, 0.2900]; 44.15%), with significant specific indirect effects via work-related basic psychological need satisfaction (B&#x202f;=&#x202f;0.0583, 95% CI [0.0107, 0.1093]; 11.81%), via work motivation (B&#x202f;=&#x202f;0.0856, 95% CI [0.0309, 0.1478]; 17.33%), and via the serial pathway through work-related basic psychological need satisfaction and work motivation (B&#x202f;=&#x202f;0.0741, 95% CI [0.0492, 0.1053]; 15.01%). Department-based need-supportive leadership showed a positive association with teachers' affective job satisfaction that was partially accounted for by indirect effect estimates via work-related basic psychological need satisfaction and work motivation. Given the cross-sectional, self-report design, findings should be interpreted as associations and indirect effect estimates rather than evidence of temporal ordering or causal mechanisms.

This study addresses the complex associations between current suicidal symptoms, lifetime suicide attempt history, C-reactive protein (CRP) levels, and executive dysfunction among young people with major affective disorders. A total of 171 young people with major affective disorders presenting varying levels of suicidal symptoms and 97 healthy young people aged 12 to 24 years were recruited for this study. Current suicidal symptom severity was classified as none, mild, or strong if an individual has scores of 0, 2-3, and &#x2265;&#x2009;4, respectively, on item 10 of the Montgomery-&#xc5;sberg Depression Rating Scale (MADRS). The presence of a lifetime history of suicide attempts was also determined. All participants had CRP levels measured and underwent the Wisconsin Card Sorting Test (WCST). Generalized linear models (GLM) with adjustments for demographic characteristics, diagnoses, and non-suicidal depressive symptoms indicated that patients presenting strong suicidal symptoms had the highest CRP levels (p&#x2009;=&#x2009;0.004) and percentage of nonperseverative errors on the WCST (p&#x2009;=&#x2009;0.002), whereas those with mild suicidal symptoms were more likely to have intermediate CRP levels relative to non-suicidal young people. Only young people with a history of suicide attempts exhibited an increased percentage of perseverative errors on the WCST (p&#x2009;=&#x2009;0.023) compared with the healthy controls. Our findings suggest that CRP levels and the percentage of nonperseverative errors on the WCST served as concurrent markers of suicidality, whereas the percentage of perseverative errors served as a trait marker of suicidality among young people with major affective disorders.

Youths differ substantially in how they emotionally respond to daily experiences. Repeated episodes of heightened negative affect in daily life may accumulate over time and increase vulnerability for developing depressive disorders. This study examined whether individual differences in negative affective reactivity to daily social experiences (i.e., social media use and upward social comparisons) predict changes in depressive symptoms over two weeks. Using a 14-day diary design with 200 early adolescents (103 female; ages 10-14), we assessed daily social media use, daily upward social comparisons, daily negative affect, and depressive symptoms at pre- and posttest. We employed multilevel structural equation modeling, estimating the within-person coupling between daily social media use (Model 1) or upward social comparisons (Model 2) and daily negative affect and tested whether between-person differences in the strength of this coupling predicted average negative affect and depressive symptom change. Findings revealed that a stronger within-person coupling between upward social comparisons and negative affect, but not between social media use and negative affect, was associated with an increase in depressive symptoms via elevated negative affect across the study. These results highlight the importance of capturing dynamic affective responses to daily social comparison processes when assessing psychological risk in early adolescence.

Affective disorders (ADs) are characterized by profound emotional processing deficits involving disrupted neural network activity and connectivity, particularly within the default mode network and fronto-temporal circuits, with abnormalities in theta and alpha oscillatory patterns. While current treatments primarily target mood symptoms, emotional processing impairments often persist and predict relapses. Awe, a complex self-transcendent emotion, may counteract such deficits through its capacity to reduce rumination and enhance positive affect. However, the neural correlates of awe experiences in clinical populations remain unexplored. For the first time, this exploratory study investigated the electroencephalographic (EEG) correlates of awe induced by validated virtual reality (VR) scenarios in individuals with ADs compared to healthy controls (HCs). Participants were exposed to immersive VR scenarios designed to elicit different awe experiences (mountains, waterfall, Earth) and a reference (awe-neutral) scenario. EEG activity was recorded during VR exposure and at baseline, followed by emotional state questionnaires. Power spectral density and graph-theoretical connectivity indices - Nodal Positive Strength and Global Efficiency - were computed across theta, alpha, and beta bands. Healthy controls showed high awe responses in awe-inducing scenarios with selective, scenario-specific modulations in alpha and theta band activity and connectivity, reflecting preserved cognitive flexibility. Conversely, ADs reported similar awe responses across all VR scenarios with reduced environmental differentiation. With respect to HCs, ADs showed elevated theta power in bilateral frontal and temporal regions, suggesting compensatory activity related to emotional processing alterations. Both groups exhibited VR-induced reductions in alpha-band global efficiency, more pronounced in ADs, suggesting compromised neural integration during complex emotional processing. Taken together, the results suggest that the emotional processing deficits inherent to ADs may limit the capacity to engage differentially with emotionally complex stimuli such as awe, while nonetheless providing initial evidence that VR-based awe exposure combined with neurophysiological recording represents a valuable approach for discriminating differential cerebral emotional responses in clinical populations. This proof-of-concept work warrants further investigation in larger cohorts to evaluate the therapeutic potential of awe-based interventions for affective disorders.

Major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SZ) are severe psychiatric disorders with distinct and overlapping clinical and neurobiological features. Despite extensive evidence of brain structural abnormalities, the transdiagnostic neuropathological mechanisms remain poorly understood. A comprehensive literature search was performed for voxel-based morphometry (VBM) studies reporting altered gray matter volume (GMV) in MDD, BD or SZ. A transdiagnostic meta-analysis was conducted to identify common and disorder-specific GMV alterations using the Seed-based d Mapping toolbox. Disease epicenter and buffering mapping were further investigated using a normative functional connectome to understand the network-constrained GM atrophy patterns. A total of 221 studies (MDD: n&#x2009;=&#x2009;66; BD: n&#x2009;=&#x2009;59; SZ: n&#x2009;=&#x2009;96) encompassing 10,485 patients and 12,128 healthy controls were included. Transdiagnostic GMV reductions were identified in the medial prefrontal cortex and superior temporal gyrus. Less atrophy in the limbic/paralimbic regions and temporoparietal junction were observed for MDD, whereas SZ patients exhibited more pronounced GMV reductions in these areas. The ventrolateral prefrontal cortex emerged as a shared disease epicenter and the precuneus as a common buffer across these affective and psychotic disorders. The visual and dorsal attention networks exhibited the most pronounced buffering effects, while epicenter effects were primarily concentrated within the limbic, frontoparietal, subcortical and default mode networks. These findings suggested that affective and psychotic disorders are characterized by both shared and unique network-constrained GM atrophy patterns, which might advance precision diagnostics and inform targeted therapeutic strategies in the future.

The current study investigates differences between anticipated and experienced warm glow (WG), as well as scope sensitivity, across joint and separate evaluations. Participants (N&#xa0;=&#xa0;1500) in an online experiment were randomized to one condition in a mixed 2&#xa0;&#xd7;&#xa0;2&#xa0;&#xd7;&#xa0;2 design, where affective response (anticipated, experienced), evaluations (separate, joint), and number of children (1, 6) were manipulated. Two variations of joint evaluations were used (choice and simultaneous). Results show an impact bias in WG where participants overestimate the WG levels they think they will experience. Moreover, results show scope insensitivity in both separate evaluations and joint-evaluations-simultaneous, where participants donate and feel WG similarly for one child as for six. Additionally, scope sensitivity is evident in joint-evaluations-choice, where participants give and feel more WG for six children than for one. Lastly, participants accurately predict their own scope insensitivity; they do not think they will feel more WG if they help more children (in separate evaluations and joint-evaluations-simultaneous). These results can have important implications for understanding the psychological mechanisms behind prosocial behavior, which in turn might contribute to promoting this type of behavior.