Search Results (45)

Background/Objectives: Gestalt therapy traditionally opposes categorical diagnostic labelling due to its fundamental inconsistency with phenomenological and process-oriented ontology. However, this epistemological rigour can limit integration with structured evidence-based interventions for complex personality organizations such as Borderline Personality Disorder (BPD). Despite the evidence base for DBT and Schema Therapy in treating BPD, these approaches may inadvertently minimize the lived phenomenological experience and organismic wisdom central to recovery. Meanwhile, Gestalt therapy’s anti-diagnostic stance limits its integration with structured evidence-based protocols. This paper proposes a hybrid theoretical model that addresses this gap by integrating the clinical epistemology of Gestalt therapy with Linehan’s biosocial theory of Dialectical Behaviour Therapy (DBT) and schema-focused interventions, while preserving the core principles of Gestalt. Methods: we present a model of theoretical integration that draws on Gestalt contact theory, the four modules of DBT (mindfulness, distress tolerance, emotional regulation, interpersonal effectiveness) and the experiential techniques of Schema Therapy. The integration focuses on the dialectic of acceptance and change, which mirrors Gestalt’s paradoxical theory of change. The proposed framework preserves the non-protocol dimension of Gestalt therapy while incorporating the pragmatic utility of DBT and Schema Therapy. Results: key conceptual contributions we propose include: (1) theorizing the “Draft Self” as the object and subject of therapeutic work, (2) integrating mindfulness and grounding as embodied processes within live Gestalt experiments, (3) activation techniques to explore the identity fragmentation endemic to BPD. Conclusions:his integration offers a coherent, embodied, and process-oriented framework for understanding and treating BPD that validates patients’ lived experience, mobilizes evidence-based interventions, and opens up meaningful intertheoretical dialogue. Full article

Introduction: Pandemic communication faces significant challenges due to the dynamic nature of disease outbreaks, societal influences, and evolving communication platforms. Effective non-pharmaceutical interventions (NPIs) depend on robust health communication strategies. This study aims to develop a conceptual model to guide NPIs communication during pandemics, grounded in widely applied risk communication theories. Methods: Using Jabareen’s conceptual framework analysis method, this study synthesized interdisciplinary literature from public health, psychology, and risk communication. The method involves mapping data sources and concept categorization and integration. We examined Crisis and Emergency Risk Communication (CERC), the Social Amplification of Risk Framework (SARF), and Social Cognitive Theory (SCT) to develop a comprehensive NPIs communication framework. Results: The Pandemic Behavioral Prevention Framework delineates pandemic communication into five phases: pre-crisis, initial event, maintenance, resolution, and evaluation. It emphasizes targeting vulnerable populations, addressing trust deficits, and leveraging effective communication channels. Key concepts such as self-efficacy, vicarious learning, and social risk amplification are integrated to enhance public adherence to NPIs. Conclusion: The framework bridges gaps in pandemic communication by integrating risk and health communication principles, fostering trust, and addressing social determinants of health. It highlights the importance of pre-crisis education and the utilization of social media for targeted messaging. Full article

Fear modulates intergroup dynamics by amplifying biases, yet prior work predominantly examines integrated emotions (e.g., fear tied to intergroup conflict), neglecting incidental fear—transient states unrelated to group contexts. Furthermore, the reliance on Western samples limits insights into cultural variability, particularly in collectivist societies where group boundaries differ. Here, we conducted two experimental studies that involved Chinese participants and examined the effect of incidental fear on empathy for in-group and out-group members’ pain (operationalized as self-focused empathy, reflecting personal distress when witnessing pain, and other-focused empathy, reflecting compassionate concern for the sufferer). In Experiment 1 (N = 54), using a pain observation paradigm, incidental fear was elicited by randomly showing frightening images, while the differentiation between the in-group and out-group was based on natural ethnic differences (same races and other races). Experiment 2 (N = 52) replicated this using artificial social categorization (university affiliation). Fear reduced other-focused empathy for racial out-groups and socially defined out-groups. Self-focused empathy remained unaffected, suggesting fear selectively disrupts mentalizing-dependent processes. The Inclusion of Other in Self (IOS) scale revealed heightened psychological distance toward out-groups under fear, mediating empathy reduction. Incidental fear universally diminishes empathy for out-group pain across natural and artificial group boundaries, extending social identity theory to transient affective states. These findings highlight fear’s role in intergroup bias and underscore cultural generalizability beyond WEIRD populations. Full article

Background/Objectives: Anosognosia for hemiplegia (AHP) is a multifaceted syndrome in which stroke survivors fail to recognize motor impairments. Although AHP has significant clinical implications, rehabilitation strategies have remained fragmented and underexplored. This systematic review aimed to critically evaluate rehabilitation interventions for AHP published between 2006 and 2025, categorize intervention types, and assess clinical outcomes to inform future research and practice. Methods: A structured search was conducted in the PubMed and PsycINFO databases on 31 March 2025, using predefined keywords related to stroke, anosognosia, and rehabilitation. The eligible studies included randomized controlled trials, case–control studies, and case studies. Following title, abstract, and full-text screening, nine studies focusing on rehabilitation interventions for AHP were selected and analyzed. Results: The interventions reviewed included sensorimotor recalibration techniques, neuromodulatory approaches, error-based cognitive training, and self-observation in video replay strategies. Interventions emphasizing motor intention monitoring, error correction, and self-observation were more consistently associated with durable improvements in motor awareness than neglect-based spatial interventions were. However, many studies were limited by small sample sizes and a lack of standardized outcome measures. Assessment methodologies vary widely, highlighting the need for multidimensional theory-driven evaluation tools. Conclusions: Effective rehabilitation for AHP requires strategies targeting disrupted self-monitoring and agency mechanisms, rather than spatial realignment alone. The video self-observation and error-based learning paradigms show particular promise. Future research should focus on controlled trials, longitudinal tracking, and the integration of individualized, mechanism-specific rehabilitation models to optimize outcomes for stroke survivors with AHP. Full article

Attachment styles, rooted in Bowlby’s Attachment Theory, significantly influence our romantic relationships, workplace behavior, and decision-making processes. Traditional methods like self-report questionnaires often have biases, so we aimed to develop a predictive model using objective physiological data. In our study, participants engaged in the Secretary problem, a sequential decision-making task, while their brain activity was recorded with a 16-electrode EEG device. We transformed this data into coherence graphs and used Node2Vec and PCA to convert these graphs into feature vectors. These vectors were then used to train a machine learning model, XGBoost, to predict attachment styles. Using participant-level nested 5-fold cross-validation, our first model achieved 80% accuracy for Secure and 88% for Fearful-avoidant styles but had difficulty distinguishing between Avoidant and Anxious styles. Analysis of the first three principal components showed these two groups overlapped in coherence space, explaining the confusion. To address this, we created a second model that categorized participants as Secure, Insecure, or Extremely Insecure, improving the overall accuracy to about 92%. Together, the results highlight (i) large-scale EEG connectivity as a viable biomarker of attachment, and (ii) the empirical similarity between Anxious and Avoidant profiles when measured electrophysiologically. This method shows promise in using EEG data and machine learning to understand attachment styles. Our findings suggest that future research should include larger and more diverse samples to refine these models. If validated in multi-site cohorts, such graph-based EEG markers could guide personalised interventions by objectively assessing attachment-related vulnerabilities. This study demonstrates the potential for using EEG data to classify attachment styles, which could have important implications for both research and therapeutic practices. Full article

Whilst there has been an increasing trend of women holding academic positions in European Higher Tertiary Institutions (HTIs), leadership positions are held predominantly by men. The study draws on radical feminism theory with which its methodology is aligned by investigating the perceptions of both genders. To that end, the study categorizes the impediments holding women back from breaking the glass ceiling into endogenous and exogenous factors. By doing so, the authors are in a better position to recommend the implementation of policies and procedures to address this inequality and navigate towards achieving sustainable gender equality. The research was conducted using an online survey questionnaire administered among all academic and administrative staff of universities in the Republic of Cyprus, the country with the highest glass ceiling in the EU. The authors found that the binary genders differ in their perceptions of what keeps women from breaking the glass ceiling and that this is attributable to exogenous factors, namely, (a) the walls created by male leaders, reinforcing a feeling of marginalization and mansplaining; and (b) family obligations enhancing women’s experiencing a lack of time and burnout. Furthermore, the exogenous factors and the extremely gendered higher echelons of HTIs underpin the endogenous factor of self-sabotage, making women feel they would rather avoid the toxic leadership environment with its lack of professional credit, a view supported by radical feminism theory. The authors suggest practical policy implications to rectify the gender imbalance in leadership in HTIs and suggest directions for future research. Full article

Artificial Intelligence (AI) is transforming smart healthcare by enhancing diagnostic precision, automating clinical workflows, and enabling personalized treatment strategies. This review explores the current landscape of AI in healthcare from two key perspectives: capability types (e.g., Narrow AI and AGI) and functional architectures (e.g., Limited Memory and Theory of Mind). Based on capabilities, most AI systems today are categorized as Narrow AI, performing specific tasks such as medical image analysis and risk prediction with high accuracy. More advanced forms like General Artificial Intelligence (AGI) and Superintelligent AI remain theoretical but hold transformative potential. From a functional standpoint, Limited Memory AI dominates clinical applications by learning from historical patient data to inform decision-making. Reactive systems are used in rule-based alerts, while Theory of Mind (ToM) and Self-Aware AI remain conceptual stages for future development. This dual perspective provides a comprehensive framework to assess the maturity, impact, and future direction of AI in healthcare. It also highlights the need for ethical design, transparency, and regulation as AI systems grow more complex and autonomous, by incorporating cross-domain AI insights. Moreover, we evaluate the viability of developing AGI in regionally specific legal and regulatory frameworks, using South Korea as a case study to emphasize the limitations imposed by infrastructural preparedness and medical data governance regulations. Full article

Political polarization in the United States has made conversations across ideological divides increasingly difficult to navigate. This study explores how students at a regional university in the southern U.S. experience and manage these challenges. Based on in-depth interviews with 30 students from diverse social and political backgrounds, we identify four key conversational strategies: disengagement, negotiation, context adaptation, and information processing. Rather than viewing these as surface-level techniques, we argue they represent deeper identity management processes aimed at reducing the social and cognitive risks of political disagreement. Drawing on Self-Categorization Theory and Identity Control Theory, we show how these strategies reflect efforts to maintain identity coherence and manage relational stakes when political identity becomes salient. Our findings suggest that while these strategies may help students avoid conflict in the moment, they may also limit deeper engagement across divides. We conclude by discussing the implications of these findings for dialog practice, highlighting the importance of fostering tolerance for identity discomfort and helping students rediscover the common bonds that unite them across political differences. Full article

This study systematically analyzes the factors influencing the social integration of reservoir resettlers, aiming to provide a theoretical basis and policy recommendations for enhancing their social integration. Grounded in social capital theory and social cognitive theory, the influencing factors are categorized into five dimensions: social norms, social trust, social networks, self-efficacy, and outcome expectations. Structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) are employed to analyze field survey data and uncover the mechanisms through which these factors influence social integration. The results indicate that social norms, social trust, and social networks positively affect resettlers’ self-efficacy and outcome expectations, which, in turn, have a positive impact on their social integration. The fsQCA results further identify five configurations, which are consolidated into three driving types: the internal-external driving path, the proactive integration path, and the capital-enabled path. By integrating the perspectives of social capital and social cognition and employing both SEM and fsQCA methodologies, this study provides valuable insights for policy-making related to the social integration of reservoir resettlers. Full article

In the Southeastern Ordos Basin, the Chang 2 low-permeability sandstone reservoir of the Triassic Yanchang Formation is a typical heterogeneous reservoir. Quantitatively characterizing and analyzing its complex pore throat structure has become crucial for enhancing storage and production in the study area. The pore throat structure is a key factor influencing reservoir properties. To achieve this, a comprehensive suite of analytical techniques was employed, including cast thin section (CTS), scanning electron microscopy (SEM), cathodoluminescence (CL), X-ray diffraction (XRD), and mercury intrusion capillary pressure (MICP). This study quantitatively characterizes the pore size distribution of reservoirs in the Southeast Ordos Basin. Based on fractal theory, it clarifies the complexity of the pore throat structure and the degree of microscopic heterogeneity at different scales. Finally, this study reveals the correlation between fractal dimensions and storage and permeability capacities and analyzes the controlling factors. The findings indicate that the predominant lithotype in the study area is fine-grained feldspar sandstone, which develops pore types such as intergranular pores, dissolution pores, and microfractures. Based on the shapes of mercury injection curves and pore throat structural parameters, and in conjunction with SEM images, the samples are categorized into three types. Type I samples exhibit good pore throat connectivity and are characterized by a lattice model. Type II samples are characterized by a tubular pore throat model. Type III samples have poor pore throat connectivity and are characterized by an isolated model. The pore throat network of low-permeability sandstone is primarily composed of micropores (pore throat radius r < 0.1 μm), mesopores (0.1 < r < 1.0 μm), and macropores (r > 1.0 μm). The complexity of the reservoir pore throat structure was quantitatively characterized by fractal theory. The total fractal dimension (D) of all the samples is between 2 and 3, which indicates that the reservoir has capillary fractal characteristics. The average fractal dimension of micropores (D1) is 2.57, while that for mesopores (D2) and macropores (D3) is slightly higher, at an average of 2.68. This suggests that micropores have higher self-similarity and homogeneity. The fractal dimensions D1, D2, and D3 of the three types of reservoirs all exhibit a negative correlation with porosity and permeability. This shows that the more complex the pore throat structure is, the worse the storage and seepage capacity of the reservoir. For type I samples, the correlation of D3 with pore throat structural parameters such as entry pressure, skewness, and maximum mercury saturation is better than that of D2 and D1. For type II and type III samples, D2 shows a significant correlation with pore throat structural parameters. This indicates that the heterogeneity and complexity of mesopores are key factors influencing the pore throat structure of poor-quality reservoirs. Different mineral compositions have varying effects on the fractal characteristics of pore structures. Quartz, feldspar, and clay exert both negative and positive dual impacts on reservoir quality by altering the pore throat structure and the diagenetic processes. The mineral content exhibits a complex quadratic relationship with the fractal dimension. Moreover, micropores are more significantly influenced by the mineral content. The study of the relationship between the fractal dimension and physical properties, pore throat structural parameters, and mineral composition can improve the understanding of the reservoir quality of low-permeability reservoirs. This provides a theoretical basis for exploration and improving the recovery rate in the study area. Full article

Buddhism is renowned for its adherence to the principle of “Anatta”, yet it does not merely negate the self. Instead, Buddhism employs a flexible categorization and stratification of the self based on specific value orientations and practical objectives. Although Christian traditions present a variety of perceptions of the self, they align with Buddhism in terms of stratifying the self. In the practical path of self-cultivation, both religions adopt meditation as a spiritual exercise, aiming to manifest the true self. A comparative analysis of Buddhist and Christian meditation practices within the framework of naturalism not only enhances the profound understanding of the self-concept for both parties but also fosters the creative transformation and innovative development of the theories of self within these two religious traditions. Full article

The accurate description of excited states is crucial for the development of electronic structure theory. In addition to determining excitation energies, strong state interactions arise when electronic states with the same symmetry are degenerate or nearly degenerate, often requiring a multi-state treatment. These strong correlation effects and state interactions can be effectively handled by the Hamiltonian matrix correction-based density functional valence bond (hc-DFVB) method, a multi-reference density functional theory capable of accurately describing electronic state interactions. In this paper, we explore the low-lying excited states of four isoelectronic systems (C₂H, CN, CO⁺, BO) using valence bond methods, including the valence bond self-consistent field (VBSCF) and hc-DFVB methods. Our results show that the hc-DFVB method provides significantly better excitation energies compared to VBSCF. Furthermore, hc-DFVB can reliably predict the correct ordering of excited states, whereas VBSCF shows some ordering inconsistencies. By categorizing the VB structures into groups based on point group symmetry, we can extract the key structural contributions and bonding pictures of each state from the weight distribution of these groups. Additionally, we study the potential energy curves for lithium fluoride (LiF) and a mixed-valence spiro cation, demonstrating the superior performance of hc-DFVB when applied to the study of near-degenerate excited states in the avoided crossing region. Full article

Background: The shift toward nuclear family structures in China has resulted in a growing number of elderly individuals living alone, intensifying the imbalance between the supply and demand of elderly care services. Objectives: This study aims to systematically examine the care needs of elderly individuals living alone in China and propose practical strategies to enhance their quality of life. Methods: Using the Kano model and ERG theory, 22 care services were categorized into three types: essential (must-have), attractive, and future-focused (outlook) elements. Survey data were gathered from 230 elderly individuals living alone in Yan’an, Baoji, and Hanzhong, located in Shaanxi Province. To determine the factors influencing the intensity of demand for these services, multivariate ordinal logistic regression analysis was applied. Results: The findings show that demand intensity for care services is significantly shaped by factors such as gender, age, marital status, education level, income, self-rated health, loneliness, and family support. The highest demand was observed for medical and mental health services, followed by life support services. Conclusions: To address the gaps in elderly care services, this study suggests standardizing institutional frameworks, diversifying service options, utilizing familial support networks, and integrating intelligent technologies. These measures are especially critical for reducing service disparities in rural and less developed regions, contributing to a fairer and more effective elderly care system in China. Full article

Background/Objective: This study aimed to validate the eight-item Suicidality Scale (SS) in Spanish in a Colombian sample to aid in suicide risk assessment, given the pressing need for accurate, accessible tools in resource-strained settings. Methods: A sample of 313 participants, drawn from both clinical and community settings, was used to evaluate the psychometric properties of the SS through tests of internal consistency, item response theory (IRT), and comparisons with clinical risk evaluations. Results: The SS demonstrated strong psychometric properties, with high internal consistency (ω = 0.96) and a significant correlation with clinical risk assessments (r = 0.84). Model fit indices confirmed a unidimensional eight-item structure with low error rates, while item response analysis revealed strong item discrimination. No differential item functioning was observed by gender or psychiatric diagnosis, supporting its consistency across demographics. Items on past suicide attempts and desire to live were excluded as they did not improve scale performance. Variability within risk levels suggests that individual differences may require clinical judgment. Conclusions: The findings validate the Colombian–Spanish SS as a valuable tool for suicide risk assessment, usable in both self-report and clinician-administered formats. Its brief, culturally adapted structure supports its utility in resource-limited environments, providing an accessible option for rapid screening. While the SS effectively categorizes general risk, further longitudinal studies are recommended to enhance its applicability in guiding clinical decisions and long-term risk management. Full article

Community-supported agriculture (CSA) has emerged as a pivotal model for sustainable and humanistic agricultural practices, emphasizing the symbiotic relationship between food production, consumption, and sustainable ecosystems. Despite the growing interest, a comprehensive analysis of research themes and trends within the CSA framework remains sparse. This paper undertakes a systematic review of CSA literature from 1999 to 2023, identifying evolving research hotspots, dominant themes, and prospective directions by keyword analysis to corroborate Maslow’s hierarchy of needs theory. The research analysis location is categorized into four temporal phases, revealing a geographical expansion from North America to encompass Asia, Africa, and other continents. This expansion corroborates Maslow’s theory, illustrating a global shift from fulfilling basic physiological needs towards recognizing sustainable practices, particularly in developing regions. The results of temporal trends (5 phases) and the hotspots of keyword analysis support each other by showing a societal shift from basic sustenance to a deeper understanding of nutrition and diet. Most of the recent research keywords are grouped into the “environment” and “health and education” categories, indicating an increasing emphasis on transforming the food system and nutrition education. This review suggests conducting an integrated analysis that links the various stages of the food supply chain with the criteria outlined in the Sustainable Agriculture Matrix (SAM). It highlights that the “environment” theme is a stage of building up esteem and self-realization that needs to be unfolded in the future, given that most research on community-supported agriculture (CSA) focuses on the “economy and society” aspect and consumption stage, which burnish self-morality in the theory of Maslow. Overall, this review proposes an analysis of the relevance among different subject categories and between food supply chain stages, which reveals that the trend of research under CSA development is accorded to the theory of Maslow’s hierarchy of needs and calls for a more holistic approach to agricultural research that considers ecological, health, and social imperatives. Full article