Search Results (1,395)

Cinematic representations of mental health operate at the intersection of science, culture and visual meaning, while medical academic discourse plays an important role in shaping how such representations are conceptualized. This study examines how the PubMed-indexed literature (2010–2025) engages with mental health in relation to narrative film and related screen media, combining bibliometric mapping with interpretive analysis. Through a structured PubMed query and VOSviewer co-occurrence analysis, this study identifies 5292 unique terms, of which 530 meet the minimum frequency threshold. Comparison between low- and high-frequency maps reveals a shift from lexical diversity to a consolidated biomedical core centered on classification, diagnosis and measurable affect. Six clusters are identified (neuro-affective, educational stigma, media–behavioral, neuropharmacological–technological, perceptual–emotional and pandemic-related), which together structure the field’s dominant semantic orientations. The findings indicate three main patterns: the predominance of standardized biomedical language, the limited visibility of intersectional categories (e.g., gender, race, identity) at the level of indexed metadata, and a gap between visual processes and narrative meaning. While individual studies often engage with cinematic complexity, this dimension is only partially reflected in the dominant lexical structure. Building on these results, a cluster-informed conceptual framework for film-based medical education is proposed, in which narrative film can support complementary forms of clinical, social and interpretive learning. This study contributes to the field of Medical Humanities by demonstrating that medical discourse not only reflects but also structures the visibility of mental health in relation to screen media, while highlighting the need for more integrated approaches that connect biomedical knowledge with narrative and cultural understanding. Full article

The study applies a multiphase, multimethod research approach based on participatory methodology. It integrates the perspectives of professionals from the tourism and hospitality industry and academic experts with the aim of developing an integrated conceptual model of the influence of AI and IoT technologies on work processes, skill development, and job attractiveness in the industry. The research provides a comprehensive understanding of how digital technologies indirectly shape employment through changes in work organization and the development of transferable digital and socio-emotional skills. The paper aims to contribute to redefining the perception of work in tourism and hospitality by emphasizing the sector not only as a career choice, but also as a platform for acquiring skills transferable to other industries. The findings revealed that employees’ intentions to enter or remain in the industry are not directly influenced by AI and IoT technologies; rather, these effects are mediated through changes in work processes and, more importantly, through skill development. The study contributes theoretically by developing and empirically validating an integrated conceptual model that connects technology implementation, work transformation, skill development, and employment outcomes. From a practical perspective, the results highlight the importance of human-centered implementation strategies based on training, communication, and employee inclusion in order to maximize the benefits of digital technologies. Full article

The Behavioral Finance (BF) has undergone significant developments due to the transformative influence of Environmental, Social and Governance (ESG) practices. BF and Sustainable Investment (SI) are closely intertwined domains, both of which bring into line with the broader framework of ESG. Integrating BF into the field of SI expands the understanding of how psychological biases, emotional factors, and cognitive constraints influence investors decisions connected to sustainability focused assets. Despite their growing relevance, the existing literature lacks a comprehensive review that provides holistic reviewing of research integrating into these areas. To address this gap, we provide an overview of BF and SI research in Socially Responsible Investments (SRI). Using both co-citation and bibliometric-coupling analysis, we infer the thematic structure of key words of BF and SI for a period of 20 years starting from 2004 to September 2025. Additionally using performance analysis and co-occurrence analysis, we highlighted trends and research directions regarding BF and SI. Further, seven thematic clusters and coupling networks were also identified which are offering to the researchers a structured foundation to explore emerging trends and consolidate knowledge within the BF and SI field. This Bibliometric study aids in recognizing the emerging topics for research in the domain of BF and SI. Full article

Artificial intelligence (AI), virtual reality (VR), and exergame technologies have been increasingly used in dance and movement activities. However, this literature remains dispersed across different areas, making it difficult to determine how the field has developed. This study mapped the research landscape and thematic development of AI-, VR-, and exergame-based dance and movement research on psychological outcomes using bibliometric analysis and latent Dirichlet allocation (LDA) topic modeling. A total of 252 records indexed in the Web of Science Core Collection from 2011 to 2025 were included. Five related thematic strands were identified: immersive dance interaction and technology-supported teaching; rehabilitation-oriented dance or rhythm training; school-based exergaming and psychophysiological assessment; behavioral program design and intervention implementation; and AI-based motion or emotion recognition. These strands indicate that the field has developed into a multi-layered research space shaped by technology functions, movement contexts, intervention formats, and psychological constructs, rather than a single dance-intervention or technology-application domain. At the same time, psychological outcomes were not represented with equal clarity across these strands. Participation-related and psychosocial constructs, including enjoyment, motivation, engagement, self-efficacy, social interaction, emotional expression, and quality of life, were more frequently represented, whereas mental-health-related outcomes such as anxiety, depression, stress, loneliness, and psychological well-being were less consistently connected to technology-supported dance or movement interventions. These findings clarify where evidence is concentrated, how major themes are organized, and where psychological outcome measurement requires clearer theoretical and methodological specification. Future studies should use comparative and longitudinal designs to examine whether VR/AI-based feedback-supported movement training offers added value over conventional dance or movement programs for psychological outcomes, participation, exercise experience, and longer-term behavior change. Full article

By combining musicology, sound studies, and linguistics, this article goes beyond existing studies of voice and popular song to analyse vocal modifiers in four songs recorded by The Miracles in 1960 and 1967: ‘Way over there’ (1960), ‘Shop around’ (1960), ‘Who’s lovin’ you’ (1960) and ‘I second that emotion’ (1967). Vocal modifiers, a sub-category of paralanguage, are a nonverbal characteristic of speech that can alter meaning or convey emotion. By adopting a mixed methodology (spectral and music analysis alongside paralinguistics), I argue that aspects of The Miracles’ performative quality reside in their use of vocal modifiers, which occur in performance and are retained on recordings. Over time, specific uses, especially by the lead singer William “Smokey” Robinson, give rise to expressive tropes (significant or recurring themes, similar to a motive in Western art music). Expressive tropes are important for not only do they create aural connections across songs, they can also represent thematic content without the aid of lyrics and reveal subtle insights into non-lexical sounds that have long been acknowledged but have resisted analysis. Full article

Mixed reality (MR) technologies enable users to experience computer-generated content within the physical environment through spatial computing and head-mounted displays. By supporting real-time interaction through speech, gesture, gaze, and movement, MR offers new opportunities for game design beyond productivity and educational applications. However, relatively few studies have examined interaction modalities in MR games. In this paper, we present the design and deployment of four MR games on the Microsoft HoloLens 2: three that use monomodal input (speech, gaze, or gesture) and one that uses multimodal input (speech, gaze, and gesture). We conducted a study with ten participants and evaluated player experience using subjective self-reports of task load, emotional engagement, and comfort alongside objective measures, namely brain activity data collected with a five-channel electroencephalogram (EEG) device. Our preliminary findings suggest two clusters of interaction modalities based on subjective measures, a pattern that is also reflected in the objective EEG measures. Our analysis combining subjective and EEG data indicates that interaction modality influences task load and emotional engagement. Additionally, our functional connectivity analysis showed links in activity across the prefrontal, temporal, and occipital brain regions for different input modalities in the MR games. Full article

(1) Background: Student burnout, widely regarded as a form of “hidden dropout” among adolescents, is associated with lower educational quality and mental health. Grounded in the Study Demands–Resources (SD–R) and Conservation of Resources (COR) theories, this study investigates the relationship between school-based resources, family dynamics, and personal resources by examining how teacher emotional support is associated with burnout through family cohesion and meaning in life; (2) Methods: a moderated mediation model was tested using a sample of 1224 adolescents (Mage = 14.27, SD = 1.72; 48% female); (3) Results: Analysis revealed that: 1. Teacher emotional support significantly and negatively predicted student burnout (β = −0.28, p < 0.001). 2. Family cohesion partially mediated this relationship, accounting for 36% of the total effect. 3. Meaning in life significantly moderated both the direct path and the second half of the mediation pathway (family cohesion → burnout). Notably, meaning in life was associated with a stronger negative association between teacher emotional support and student burnout, but a weaker negative association between family cohesion and student burnout, a pattern consistent with differential resource utilization; (4) Conclusions: These findings suggest a differentiated pattern of resource interplay: school-based emotional resources may connect to family-based relational resources, and the protective role of each external resource may be further moderated by adolescents’ internal meaning systems. These findings highlight the agentic role of adolescents in resource management and point to the value of multi-system interventions. Full article

Environmental education projects can often be short-term or in extra-curricular spaces, rather than holistically nestled into a way of teaching and learning. Research has highlighted the importance of considering the emotional and active aspects of learning, arguing that we must address education for sustainability through the hands (doing) and the heart (feeling) as well as the head (thinking). Here we ask how this consciousness can be embedded into a school ethos. This paper reports on a co-created ethnographic case study, drawing primarily on observation data, aiming to understand how connectivity with nature is cultivated within a Steiner Waldorf school in the UK. We found that Steiner Waldorf Education cultivates connectivity with nature through play and creativity, the use of songs and verses, prevalence of natural materials, a reverence for Mother Earth and a focus on the rhythm of the seasons through festivals. Through this holistic practice, a strong connectivity with nature is fostered. Based on the evidence that connectivity with nature increases pro-environmental behaviours, we seek to contribute to the environmental education literature the potential of a holistic approach to education that foregrounds the hands and heart in the elementary stages of education rather than addressing environmental challenges head on. We argue that this approach can inspire change through strengthening our relationship to the natural world, thus empowering young people to shape a more sustainable future. Full article

Emotion recognition through electroencephalogram (EEG) signals is crucial for brain–computer interfaces (BCIs), yet existing methods often struggle with heterogeneous feature fusion and capturing long-range temporal dependencies. To address these challenges, we propose MAF-TransNet, a novel unified spatiotemporal framework. Specifically, parallel Fully Connected Neural Network (FCNN) modules first non-linearly align heterogeneous differential entropy (DE) and power spectral density (PSD) features. Subsequently, an Adaptive Channel-wise Feature Encoder (ACFE) recalibrates spatial–spectral responses to highlight emotion-relevant cortical activations. Finally, a Transformer encoder dynamically models the global temporal evolution of emotional states. Evaluated on the SEED-IV and DEAP datasets, MAF-TransNet achieves superior subject-dependent (SD) accuracies of 88.80% and 96.58%, respectively, alongside robust subject-independent (SI) performance. Furthermore, Granger causality analysis reveals distinct emotion-dependent prefrontal asymmetry, while t-SNE visualizations confirm the formation of a highly discriminative, linearly separable feature manifold. Ultimately, MAF-TransNet effectively unifies local spatial–spectral extraction with global temporal modeling, providing an accurate and robust approach, while offering preliminary insights into the spatiotemporal dynamics of emotion for future affective BCI applications. Full article

This narrative review examines research on artificial intelligence (AI), including rule-based systems, natural language processing models, and large language models, in relation to well-being, social connection, and personal growth. After briefly tracing the history of AI, we review evidence from AI-facilitated well-being interventions, educational applications, interpersonal skill development, AI-mediated communication, and AI companionship. In clinical and nonclinical settings, structured AI applications show some short-term benefits for anxiety, stress, loneliness, self-esteem, learning, and social confidence, while emerging evidence suggests that AI companions may provide temporary emotional support and a sense of connection. However, findings across these domains are not consistent and appear to depend on how AI is used, the structure of the interaction, the type of feedback provided, and the broader context. Important risks include emotional dependence, overreliance, reduced human connection, weakened authenticity in communication, cognitive or socioemotional skill erosion, bias, and poor crisis response. Preliminary findings suggest that AI may be most beneficial when used to support, rather than replace, human capacities and relationships. Future research should examine long-term outcomes, individual differences, real-world use of publicly available AI systems, and the conditions under which AI strengthens or undermines well-being, relationships, and personal growth. Full article

Bottom-up approaches to climate resilience are increasingly promoted, yet there remains a gap in understanding how science-society connections can be operationalized in everyday contexts to support adaptive land-use practices, particularly in small towns and peripheral regions. This paper addresses this gap by examining how Living Labs (LLs) can function as process-oriented interfaces between scientific knowledge, local experience, and participatory negotiation, rather than as instruments for producing novel biophysical and social-learning insights. Drawing on selected case studies from the Biodiversity Hub and the Department for Building and Environment at the University for Continuing Education Krems (Austria), the study applies a qualitative, transdisciplinary Living Lab approach combining regular shared site walks, emotional communication, and cross-sectoral ecosystem services assessment matrices (aligned with established classifications and quantitative data collection). Resilience is grounded in the literature as a social–ecological capacity for adaptation and transformation and is operationalized pragmatically as the strengthening of connectedness between people, place, and ecological processes. The key findings show that short, place-based, and experiential interactions—such as shared walks and co-creative ecosystem service assessments—can lower participation barriers, mitigate power asymmetries, and enable rapid integration of scientific perspectives into everyday land-use decision-making. Rather than producing directly replicable outcomes, Living Labs generate transferable process principles, including emotional correspondence, structured negotiation, and the use of simple boundary tools to support collective learning and action. The paper contributes to resilience and land-system research by demonstrating how Living Labs can enhance local adaptive capacity and climate resilience through process design, immediate feedback, and continuous experimentation. It thereby complements conventional, indicator-driven assessments by illustrating how resilience can be enacted through participatory, place-based governance practices, offering practical guidance for municipalities and regions facing climate-related risks such as heat stress, drought, soil degradation, biodiversity loss, and increasing pressures on the secure provision of food, materials, and drinking water. Full article

This study maps how cognitive and behavioral concepts such as trust, emotion, and bias are represented in the literature on digital financial accounting-based decision-making and FinTech adoption (artificial intelligence, blockchain, big data analytics, and automated reporting). The study employs a bibliometric mapping analysis of 19,655 publications from SCOPUS, creating three visualizations through the VOSviewer software: Network, Overlay, and Density Visualization. This technique maps thematic clusters and identifies conceptual connections in the literature on cognitive and behavioral dimensions of FinTech adoption. Results highlight trust as a central node linking FinTech adoption with cognitive and behavioral factors. Key cognitive biases, including overconfidence, anchoring, and loss aversion, appear in the literature as recurrent concepts associated with FinTech adoption, while financial literacy is frequently discussed as a mitigating factor. The study extends behavioral financial accounting-based theory and technology acceptance models by integrating psychological and technological approaches into a unified conceptual framework, providing theoretical and practical implications for FinTech designers, regulatory authorities, and educational institutions. Full article

Background: Precise decoding of brain states is essential for closed-loop neuromodulation, but current electrodes and recording strategies are inadequate. Multi-region recording offers network-level advantages over single-region approaches, yet remains underdeveloped due to the lack of low-cost, flexible multi-region electrodes and standardized workflows. Methods: We developed a low-cost, modular, silica capillary tube-based 16-channel electrode for multi-region local field potential (LFP) recording in small animals, along with an integrated workflow for spectral analysis, functional connectivity assessment, and machine learning-based brain state decoding. Results: Our electrode design enables flexible customization of target regions and low-cost (~19.43 USD/unit) assembly without specialized equipment. In vivo validation in rats targeting eight emotional network nuclei achieved 79.2% implantation accuracy, with stable LFP recordings maintained for over 3 months. In a reserpine-induced depression model, spectral analysis revealed state-specific oscillatory changes including reduced alpha power in the infralimbic cortex. Inter-regional functional connectivity analysis further captured drug-induced network-level synchronization changes. We also developed a machine learning pipeline with random forest classifier that achieved ~96.4% accuracy in decoding brain states from the multi-region signals. Conclusions: This modular multi-region electrode provides a practical, adaptable, and low-cost platform for long-term distributed network recording, supporting quantitative LFP analysis, functional connectivity assessment, and high-accuracy brain state decoding, laying a technical foundation for preclinical closed-loop neuromodulation research. Full article

Although prior research has typically examined the relationship between parenting styles and left-behind children’s social adaptation using broad categories without identifying directly linked dimensions, the present study employed network analysis to conceptualise both as interconnected dimensional networks. Methods: A total of 2452 children (713 left-behind, 1739 non-left-behind) were included. Results: (1) The results revealed that interpersonal adaptation and learning adaptation were core dimensions in the SA networks of both groups. (2) In the combined PS-SA network for left-behind children, the core dimensions were interpersonal adaptation, learning adaptation, father’s rejection, and mother’s rejection; for non-left-behind children, they were interpersonal adaptation, learning adaptation, mother’s rejection, and mother’s emotional warmth. (3) Network comparisons further indicated that the connections between father’s rejection and interpersonal adaptation, father’s rejection and learning adaptation, and father’s emotional warmth and learning adaptation were stronger in the left-behind group, whereas the connections between mother’s emotional warmth and positive emotional adaptation, and between interpersonal adaptation and learning adaptation, were stronger in the non-left-behind group. Conclusions: these findings visualise and specify how distinct parenting dimensions relate to different facets of social adaptation, offering parents and schools potential targets for adaptation education tailored to left-behind children. Full article

Loneliness describes a complex experience, the subjective incongruence between one’s desired and perceived social connections. The study of loneliness has increased but mostly through quantitative methods, leaving a gap in the personal experience and understanding of what it means to be lonely. The everyday language used to articulate the personal experience of loneliness remains underexamined. To address this gap, we conducted 18 semi-structured life story interviews with older adult mental health service users. Interviews were conducted via telephone and lasted on average 45 min. Participants were included on the basis of being objectively classified as lonely and ranged in age from 66 to 84. This paper provides a thematic analysis of responses to the question “What does loneliness mean to you?” Responses include subjective and objective aspects, as well as frequency, duration, and intensity, and social, emotional, and existential loneliness. Loneliness is a multidimensional, personal experience, rather than a single construct. Participants discussed loneliness alongside social isolation, depression, grief, feelings of emptiness, purpose, meaning, boredom and hopelessness. These insights are important for informing how we frame loneliness in research, policy, and practice, and for highlighting that our language needs to be sufficiently inclusive to capture the complexity of loneliness, not only for work with mental health service users but in public health. Full article