Search Results (42)

This research addresses the challenge of inferring complex psychological states, including stress, fatigue, anxiety, cognitive load, and boredom, from facial expressions. We propose an interpretable, literature-informed emotion-weighting methodology that transforms the eight-emotion probability outputs of facial emotion recognition models into continuous estimates of these five psychological states using weights derived from the Valence–Arousal framework, providing a principled bridge between discrete emotion predictions and higher-level affective constructs. The proposed formulation is evaluated across six representative deep learning architectures—a baseline CNN (ResNet-50), a modern CNN (ConvNeXt), a hybrid attention-based model (DDAMFN), and three Transformer-based models (ViT, BEiT, and Swin). Our results demonstrate that strong performance on discrete FER tasks does not directly translate to consistent behavior in complex state inference; instead, architectures capable of preserving subtle and distributed affective cues yield more stable and interpretable state estimates, with DDAMFN and Vision Transformer models exhibiting the most consistent performance across the evaluated psychological states. These findings highlight the central role of the proposed emotion-weighting formulation and the importance of architecture selection beyond categorical accuracy in complex affective state analysis. Full article

This article re-interprets V. S. Naipaul’s “Tell Me Who to Kill” from In a Free State (1971) through a Heideggerian lens, focusing on the ‘groundlessness’ of existence and the dialectics of ‘danger’ that structure the unnamed narrator’s life within colonial ‘modernity’. Using Hiedegger’s phenomenology as a rhetorical hermeneutic, it traces how ordinary existential structures—fear, anxiety, boredom, curiosity, idle talk, and ambiguity—surface in the narrator’s and other characters’ comportments and speech. In Heidegger’s sense, these moods do not simply describe psychological states but reveal the conditions of Dasein’s being-in-the-world and the ontological disclosures of a being unhomed by empire. By situating Heidegger’s concepts of Dasein, thrownness, and fallenness within Naipaul’s world of migration, labour, and racial precarity, the paper reveals how metaphysical homelessness becomes historically tangible. The narrator’s obsessive drive for success, his failed fraternal duty, and his descent into estrangement dramatize a colonial subjectivity torn between aspiration and abjection. In reframing Heidegger through the postcolonial experience, the article both deprovincializes European existentialism and reclaims phenomenology as a site for interrogating the psychic economies of empire. Ultimately, the novella becomes a poetics of nihilism—where the search for authenticity collapses under the weight of displacement. Full article

This article proposes a conceptual reformulation of the phenomenon of boredom by carefully distinguishing ordinary situational or psychologically driven boredom from what is here termed existential boredom: a specific mode of disconnection in which the subject’s capacity to inhabit a meaningful horizon of possibilities becomes temporarily suspended. Rather than interpreting boredom as a mere lack of stimulation, momentary dissatisfaction, or simple emotional discomfort, the study argues that certain forms of boredom reveal a phenomenological contraction of possibility, involving disturbances in lived temporality, value orientation, imaginative projection, and embodied intentionality. Through a critical analysis of key thinkers, the article clarifies the tensions and limitations within classical accounts and delineates the proposed concept of existential boredom from adjacent phenomena such as Unheimlichkeit, Frankl’s “existential vacuum”, clinical apathy, and everyday boredom. It is argued that existential boredom functions as a phenomenological indicator of existential disconnection, not as an ontological diagnosis of meaninglessness but as a liminal experience that renders visible the temporary suspension of the structures that normally sustain meaningful world-disclosure. This conceptualisation also illuminates the contemporary prevalence of this affective state within contexts of hyper-stimulation, attentional fragmentation, and the erosion of meaning frameworks. By offering an integrated analytical framework, the article contributes to a more rigorous understanding of boredom as an existential phenomenon, with implications for philosophy, contemporary psychology, and the study of human experience in modern life. This approach not only expands our understanding of boredom but also invites us on a journey of self-discovery and personal growth. Full article

This study examines the influence of pedagogical agents on enhancing emotional engagement in higher education settings through the provision of cognitive and affective feedback. The research focuses on students in a collaborative “Database Systems and Design”, comparing the effects of feedback from a human teacher (control group) to those of an Affective Pedagogical Tutor (APT) (experimental group). Emotional engagement was measured through key positive emotions such as motivation, curiosity, optimism, confidence, and satisfaction, as well as the reduction in negative emotions like boredom, anger, insecurity, and anxiety. Results suggest that APT feedback was associated with higher levels of emotional engagement compared to teacher feedback. Cognitive feedback from the APT was perceived as supporting learning outcomes by offering detailed, task-specific guidance, while affective feedback further supported emotional regulation and positive emotional states. Students interacting with the APT reported feeling more motivated, curious, and optimistic, which contributed to sustained participation and greater confidence in their work. At the same time, boredom and anger were notably reduced in the experimental group. These findings illustrate the potential of affective pedagogical agents to complement educational experiences by fostering positive emotional states and mitigating barriers to engagement. By integrating affective and cognitive feedback, pedagogical agents can create more emotionally supportive and engaging learning environments, particularly in collaborative and complex academic tasks. Full article

Understanding affective responses to the climate and ecological emergency is essential for developing and ensuring compliance with mitigation policies. Previous evidence indicates that individuals feeling negative emotions about the state of nature and the climate are more likely to show greater support for environmental policy. This study investigates which of twenty distinct emotions predict attitudes towards nationally relevant UK environmental policies, with specific hypotheses differentiating between unambiguous and ambiguous emotions. We conducted two cross-sectional online surveys with 651 UK residents, who rated their support for three policy sets: the Conservative Government’s manifesto, the Climate and Ecology Bill, and the Green New Deal Bill. By integrating theoretical expectations with exploratory analysis, we found that higher levels of worry and horror predicted greater policy support, whereas boredom predicted opposition. Our analytical strategy underscores the importance of integrating both a priori and explorative models to enhance statistical sensitivity, thereby capturing a broader spectrum of affective states that might otherwise be overlooked but may be crucial for designing targeted interventions. These findings suggest that policymakers can leverage specific emotions, such as worry, to foster support, while addressing boredom to mitigate resistance, thereby enhancing the effectiveness of environmental communication and interventions. Full article

This study was conducted in a Portuguese slaughterhouse for finishing pigs. A total of 93 batches with an average slaughter weight of 93.3 kg (±0.6) were assessed in the lairage pens using the qualitative behavior assessment (QBA) tool to evaluate both positive and negative descriptors. Social interaction behaviors and the physical conditions of pigs in each batch were also measured. Physical examination revealed that pigs with body condition scores of 4 or 5 were less active and playful, presenting negative correlations with these descriptors. Groups of pigs at rest showed negative correlations (p < 0.001) with active (r = −0.338), lively (r = −0.352), and playful (r = −0.424) behaviors, while resting behavior was positively correlated (p < 0.01) with relaxed groups (r = 0.331). The presence of fighting and mounting the backs of other animals was highly correlated (p < 0.001) with negative emotional states like agitation, distress, irritability, and tense. Batches exhibiting positive emotional states, such as calmness and relaxation, showed significant associations with behaviors like fighting and mounting the backs of other animals. This indicates that experiencing positive emotions can lead to a decrease in aggressive or stress-related behaviors. Ear biting correlated with the descriptor “bored”, indicating a potential relationship between this behavior and a lack of environmental stimulation. The descriptors “frustration” and “bored” (p < 0.001) showed an association with the behavior of chewing without a substrate, regardless of whether fights occurred. Descriptors like ”active”, ”friendly”, “positively occupied”, ”sociable”, and “lively” have higher loadings on principal component 1 (PC1), reflecting positive affective welfare. In PC2, descriptors representing relaxation are positioned as opposite to terms like “irritable”, “distressed”, and “tense”, suggesting that PC2 could be useful for identifying conditions of high stress in pigs. These findings underscore the relationship between emotional states and behaviors, suggesting that combining QBA with behavioral observations provides a comprehensive framework for assessing animal welfare. Improving pig welfare could be achieved by reducing aggression and enhancing environmental enrichment to alleviate boredom during lairage. Full article

During COVID-19 “lockdown” most high school and college students experienced a sudden ending of face-to-face classes and were forced into multiple, rapidly prepared online courses. These experiences produced students more knowledgeable about online education than ever before. With this came a degree of certainty regarding their future educational delivery preferences. This survey (2021–2024) examined the attitudes and barriers associated with online course selection at a university within the State University of New York (SUNY) system. Using an introductory nutrition course, 658 surveys were exclusively collected from the face-to-face sections of a Natural Science course. Only 30.2% of these students reported a preference for online courses. Respondents reported similar percentages on Course Difficulty (48.5% online vs. 51.5% face-to-face) and which course required more Work/Time (43.2% online vs. 56.8% face-to-face). Previous negative online experiences were affirmed by 27.4% of the students. Importantly, only 14.5% self-reported a better academic performance in online courses. Major online avoidance variables were boredom (53.1%), inferior learning (52.9%), and communication limitations (43.0%). Surprisingly, 67.7% stated they would consider taking future online courses. Understanding post-COVID-19 student attitudes and barriers provides useful information and should be part of any comprehensive approach to future online education design and implementation. Full article

The acceleration of urbanization has resulted in a heightened awareness of the impacts of urban environments on residents’ emotional states. This present study focuses on the Lixia District of Jinan City. By using urban street view big data and deep learning methods, we undertook a detailed analysis of the impacts of urban color features on residents’ emotional perceptions. In particular, a substantial corpus of street scene image data was extracted and processed. This was performed using a deep convolutional neural network (DCNN) and semantic segmentation technology (PSPNet), which enabled the simulation and prediction of the subjective perception of the urban environment by humans. Furthermore, the color complexity and coordination in the street scene were quantified and combined with residents’ emotional feedback to carry out a multi-dimensional analysis. The findings revealed that color complexity and coordination were significant elements influencing residents’ emotional perceptions. A high color complexity is visually appealing, but can lead to fatigue, discomfort, and boredom; a moderate complexity stimulates vitality and pleasure; high levels of regional harmony and aesthetics can increase perceptions of beauty and security; and low levels of coordination can increase feelings of depression. The environmental characteristics of different areas and differences in the daily activities of residents resulted in regional differences regarding the impacts of color features on emotional perception. This study corroborates the assertion that environmental color coordination has the capacity to enhance residents’ emotions, thereby providing an important reference point for urban planning. Planning should be based on the functional characteristics of the region, and color complexity and coordination should be reasonably regulated to optimize the emotional experiences of residents. Differentiated color management enhances urban aesthetics, livability, and residents’ happiness and promotes sustainable development. In the future, the influences of color and environmental factors on emotions can be explored in depth, with a view to assist in the formulation of fine urban design. Full article

In a digitally oriented society, smartphones provide continual online accessibility to daily life while simultaneously predisposing adolescents to engage in prolonged connections for various purposes, thus escalating the risk of Internet addiction (IA). Cognitive processes such as multitasking and attentional shifting are frequently associated with smartphone activities. Additionally, online engagements may serve as emotional strategies for regulating negative states (e.g., boredom and distress), redirecting attention towards more gratifying activities, such as social media contents. This study delves into cognitive–emotional processes (i.e., emotion regulation, attention impulsiveness, online vigilance, and multitasking) and emotional/behavioural factors (i.e., emotional problems, conduct problems, hyperactivity/inattention, peer relationships, and prosocial behaviours) that may be implicated in smartphone activities and technology addiction among adolescents. A community sample of Italian high school students (N = 676; 42.2% females) completed the Smartphone Distraction Scale (SDS), the Strength and Difficulties Questionnaire (SDQ) for internalising/externalising symptoms and the Internet Addiction Test (IAT) to assess the presence and severity of IA. The scores on the SDS were found to be positively associated with IA levels. Furthermore, students exhibiting higher internalising/externalising symptoms, particularly those with traits of attention deficit hyperactivity disorder (ADHD), are more likely to manifest problematic smartphone usage. The implications for screening adolescents more susceptible to developing IA symptoms and for implementing preventive interventions are discussed. Full article

Quantifying the emotional impact of street greening during the full-leaf seasons in spring, summer, and fall is important for well-being-focused urban construction. Current emotional perception models usually focus on the influence of objects identified through semantic segmentation of street view images and lack explanation. Therefore, interpretability models that quantify street greening’s emotional effects are needed. This study aims to measure and explain the influence of street greening on emotions to help urban planners make decisions. This would improve the living environment, foster positive emotions, and help residents recover from negative emotions. In Hangzhou, China, we used the Baidu Map API to obtain street view images when plants were in the full-leaf state. Semantic segmentation was used to separate plant parts from street view images, enabling the calculation of the Green View Index, Plant Level Diversity, Plant Color Richness, and Tree–Sky View Factor. We created a dataset specifically designed for the purpose of emotional perception, including four distinct categories: pleasure, relaxation, boredom, and anxiety. This dataset was generated through a combination of machine learning algorithms and human evaluation. Scores range from 1 to 5, with higher values indicating stronger emotions and lower values indicating less intense ones. The random forest model and Shapley Additive Explanation (SHAP) algorithm were employed to identify the key indicators that affect emotions. Emotions were most affected by the Plant Level Diversity and Green View Index. These indicators and emotions have an intricate non-linear relationship. Specifically, a higher Green View Index (often indicating the presence of 20–35 fully grown trees within a 200 m range in street view images) and a greater Plant Level Diversity significantly promoted positive emotional responses. Our study provided local planning departments with support for well-being-focused urban planning and renewal decisions. Based on our research, we recommend the following actions: (1) increase the amount of visible green in areas with a low Green View Index; (2) plant seasonal and flowering plants like camellia, ginkgo, and goldenrain trees to enhance the diversity and colors; (3) trim plants in areas with low safety perception to improve visibility; (4) introduce evergreen plants like cinnamomum camphor, osmanthus, and pine. Full article

The use of electroencephalography (EEG) techniques has many advantages in the study of human performance in air traffic control (ATC). At present, these are non-intrusive techniques that allow large volumes of data to be recorded on a continuous basis using wireless equipment. To achieve the most with these techniques, it is essential to establish appropriate EEG parameters with a clear understanding of the process followed to obtain them and their practical application. This study explains, step by step, the approach adopted to obtain six EEG parameters: excitement, stress, boredom, relaxation, engagement, and attention. It then explains all the steps involved in analysing the relationship between these parameters and two other parameters that characterise the state of the air traffic control sector during the development of real-time simulations (RTS): taskload and number of simultaneous aircraft. For this case study, the results showed the highest relationships for the engagement and attention parameters. In general, the results confirmed the potential of using these EEG parameters. Full article

Emotion can reflect in the perception of food consumption. An increase in food intake during emotional and psychological conditions may have a negative impact on human health. The aim of this cross-sectional study was to determine the associations between food consumption, emotional eating behavior, and emotional conditions such as stress, depression, loneliness, boredom eating, maintaining vigilance and alertness, and emotional food consolation. We used a Motivations for Food Choices Questionnaire (Eating Motivations, EATMOT) to determine the emotional aspects of food consumption in 9052 respondents living in 12 European countries between October 2017 and March 2018. Ordinal linear regression was used to identify the associations between the emotional eating behavior and emotional conditions such as stress, depression, loneliness, emotional consolation, and reasons to improve physical and psychological conditions. The regression models confirmed the associations between food consumption, emotional conditions, and emotional eating behavior. Associations were found between the emotional eating behavior and stress (odds ratio (OR) = 1.30, 95% confidence interval (CI) = 1.07–1.60, p = 0.010), depressive mood (OR = 1.41, 95% CI = 1.40–1.43, p < 0.001), loneliness (OR = 1.60, 95% CI = 1.58–1.62, p < 0.001), boredom (OR = 1.37, 95% CI = 1.36–1.39, p < 0.001), and emotional consolation (OR = 1.55, 95% CI = 1.54–1.57, p < 0.001). Emotional eating was associated with an effort to improve physical and psychological conditions, such as controlling body weight (OR = 1.11, 95% CI = 1.10–1.12, p < 0.001), keeping awake and alert (OR = 1.19, 95% CI = 1.19–1.20, p < 0.001) and consumption to feel good (OR = 1.22, 95% CI = 1.21–1.22, p < 0.001). In conclusion, emotions might provoke emotional eating behavior. The appropriate way to handle stress, depression, or other emotional states is important in conditions of being emotionally overwhelmed. The public should be educated on how to handle different emotional states. The focus should be moved somehow from emotional eating and the consumption of unhealthy food to healthy lifestyle practices, including regular exercise and healthy eating habits. Thus, it is necessary to halt these negative health effects on human health through public health programs. Full article

Electronic cigarettes (ECs) users’ profiles and behaviors during the COVID-19 pandemic remain unclear. This cross-sectional study aimed to explore Malaysian EC users’ profiles and their associations with related behaviors during the pandemic. The EC users (N = 351) were recruited from an official national vape entity. Respondents were predominantly of Malay ethnicity (90.6%), aged 31 to 35 years (27.6%), males (97.7%), married (68.7%), from Malaysia’s west region states (63.5%) and tertiary educated (69.2%). The majority (80.3%) were non-dual users, and most purchased their vaping products online (77.2%), liked that they can vape while working at home (83.8%) and vaped more because of boredom (55.3%), had low and moderate nicotine addiction levels (94.9%), had low motivation level to quit EC use (92.6%) and were more likely to perceive that vaping did not increase the chances of complications from COVID-19. Respondents with moderate to high addiction levels had twice the odds of checking on their current EC supplies, whilst respondents with low motivation to quit had higher odds of using their tank/pod until the last drop and distancing from others when vaping. EC users should be encouraged to quit EC use, especially during the COVID-19 pandemic. Full article

Since the outbreak of COVID-19, remote teaching methods have been widely adopted by schools. However, distance education can frequently lead to low student emotional engagement, which can not only cause learning burnout, but also weaken students’ interest in online learning. In view of the above problems, this study first proposed a learner knowledge state model that integrates learning emotions under the background of digital teaching to accurately describe the current learning state of students. Then, on the basis of the public face dataset lapa, we built an online multi-dimensional emotion classification model for students based on ResNet 18 neural network. Experiments showed that the method has an average recognition accuracy of 88.76% for the four cognitive emotions of joy, concentration, confusion, and boredom, among which the accuracy of joy and boredom is the highest, reaching 96.3% and 97.0% respectively. Finally, we analyzed the correlation between students’ emotional classification and grades in distance learning, and verified the effectiveness of the student’s emotional classification model in distance learning applications. In the context of digital teaching, this study provides technical support for distance learning emotion classification and learning early warning, and is of great significance to help teachers understand students’ emotional states in distance learning and promote students’ deep participation in the distance learning process. Full article

Digital technology is increasingly becoming a part of daily life, including the lives of children. Portable digital devices are omnipresent and integrated into activities that did not previously require them. The related skills are often referred to as 21st-century skills, constituting a new type of literacy: digital literacy. These devices and skills bring unique, innovative elements to the learning experience; yet, we do not know the extent to which behavior, emotion, and socialization are affected by such experience. For preschool-aged children, interactions with digital devices and games for the purposes of learning can lead to a state of confusion and boredom, an emotional driving force that may generate mind-wandering and exploration, which, in turn, may facilitate learning. Our interdisciplinary observational case study examined the behavioral patterns linked to digital game-based learning (DGBL) by observing how a child’s mind-wandering contributed to iPad use when they were allowed to freely engage with the device and explore independently during the learning process. Building on a previous case study of a 28-month-old boy, “Ryan”, we evaluated the effects of bouts of mind-wandering as he played various DGBL applications (apps) by examining the length of time that Ryan exhibited relevant affective and behavioral states, iPad manipulations, and social interaction during the playtime. Ryan’s interactions with the iPad were video recorded for five weeks, and the video footage was coded using a detailed rubric. The results indicated that negative emotions, such as boredom, distraction, and confusion, if coupled with attentiveness and persistence, led to positive mind-wandering and positive learning outcomes. However, when boredom was coupled with frustration, it led to negative mind-wandering and a lack of learning outcomes. In conclusion, our study presents evidence that DGBL apps may improve learning by capitalizing on positive and avoiding negative mind-wandering. Full article