Search Results (476)

Background/Objectives: Meaningful social connections are critical for well-being in later life, yet older adults living with HIV frequently experience social isolation and loneliness, compounded by stigma, mental health conditions, and systemic inequities. This study aimed to explore how older adults living with HIV and a concurrent mental health diagnosis experience social isolation and cultivate meaningful relationships, situating these experiences within Social Convoy Theory. Methods: Using a Heideggerian phenomenological approach, we conducted in-depth, semi-structured interviews with 33 adults aged 50 and older in Ontario, Canada, who self-identified as living with HIV and a diagnosed mental health condition. Participants were recruited through community-engaged strategies and snowball sampling. Data were analyzed iteratively, combining descriptive and interpretive coding to identify patterns in social isolation, relational meaning, and the influence of intersecting social, structural, and health determinants. Results: Participants described social isolation as both a physical and existential experience, influenced by stigma, mental health challenges, and contextual factors such as urban versus rural settings. Meaningful relationships were characterized by authenticity, trust, emotional safety, and reciprocity, often formed within peer networks sharing similar lived experiences. Community engagement and virtual platforms facilitated connection, while rural or suburban environments often intensified isolation. Relationships providing validation, agency, and continuity of experience were particularly impactful on participants’ well-being. Conclusions: Social isolation among older adults living with HIV and mental health conditions extends beyond objective network measures to include emotional and identity-related dimensions. Interventions should prioritize affirming, context-sensitive spaces that support disclosure, trust, and reciprocal relationships, recognizing the nuanced needs of this population for both social and existential connectedness. Full article

This study explores how school principals evacuated from their schools in the wake of the 7 October 2023 war perceived their unique challenges, the strategies they adopted, and the ways in which their agency was shaped during the extreme crisis. Using semi-structured, in-depth interviews with 33 displaced principals from elementary, middle, secondary, and special education schools, we identified four interconnected dimensions of the principals’ agency during wartime. Intrapersonal agency reflected the principal’s inner identity as a foundation for action. Critical agency emerged from frustration with systemic failures and bureaucratic obstacles, motivating the pursuit of meaningful change. Collaborative agency was expressed in building and maintaining trust-based networks and partnerships that enabled effective solutions. Finally, proactive agency was driven by an internal desire for growth and influence, promoting innovative strategies and renewal processes at organizational, emotional, and community levels. This leadership framework for understanding principalship in wartime highlights agency as a holistic framework that enables principals not only to ensure the survival of their schools, but also to respond to chaotic realities. Practically, the findings inform the design of models for ensuring educational continuity in emergencies, and tailored support mechanisms for displaced educational communities. Full article

The objective of this study was to analyze social perception, trust, and vaccine hesitancy through a combined approach of bibliometric analysis and qualitative synthesis, based on the most cited articles in the recent scientific literature. A systematic search was conducted in indexed databases, identifying patterns of production, collaboration, citation, thematic networks, and conceptual trends associated with the study of public trust in vaccines. The results reveal a marked geographic concentration of scientific production, dominated by the United States and the United Kingdom, as well as a strong articulation of thematic clusters linked to digital disinformation, health communication, risk perception, and psychosocial determinants of vaccine acceptance. The qualitative synthesis of the most influential studies reveals that vaccine hesitancy is a multidimensional phenomenon, determined by sociocultural, cognitive, emotional, and structural factors that interact dynamically according to each context. Disinformation, institutional trust, community narratives, and the credibility of sources emerge as central components in individual decision-making. Together, the integrated results enable a deeper understanding of vaccine hesitancy beyond traditional cognitive models, highlighting the need for contextualized communication strategies, intercultural approaches, and health policies based on trust and social participation. This study provides an integral view of the scientific landscape and establishes priority lines for future research and the design of effective public health interventions. Full article

With the increasing prominence of sustainable consumption and the rising influence of Generation Z in the fashion market, secondhand fashion e-commerce platforms have become essential carriers of green fashion. Although AI-assisted recommendation mechanisms are widely embedded in these platforms, their psychological and behavioral effects on users’ continuous use and social engagement remain insufficiently examined. To address this gap, this study incorporates the Stimulus–Organism–Response (SOR) framework to investigate the psychological reaction pathways and behavioral intentions of Generation Z users within Human-AI Collaboration-enabled green e-commerce environments. Three AI-driven service stimuli—Human-AI Collaborative Recommendation Perception, AI Interaction Transparency, and Perceived Personalization—were conceptualized as stimulus variables; Psychological Immersion, Emotional Triggering, Cognitive Engagement, and Platform Trust were modeled as organism variables; and Continuous Use Intention and Social Sharing Intention served as behavioral response variables. Based on 498 valid samples analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM), the results demonstrate strong empirical support for all proposed hypotheses. Specifically, AI-driven stimuli significantly and positively influence psychological responses, which subsequently strengthen users’ continuous usage and social sharing intentions. This research provides theoretical insights for developing Human-AI Collaboration-enabled service systems that balance efficiency and emotional resonance on green e-commerce platforms, and offers practical implications for promoting sustainable fashion values among younger consumers. Full article

International shopping is a significant motive for outbound travel; however, evidence on the experiential drivers of luxury travel retail among Chinese luxury travelers remains limited. This study investigates the factors shaping overseas shopping experiences and assesses the adequacy of the luxury customer experience (LCX) framework in this episodic, time-constrained, cross-border context. A quantitative survey of Chinese luxury travelers (N = 407) was conducted and analyzed using IBM SPSS Statistics (Version [30.0], Mac) within the LCX framework. The results show that modern artistic visual merchandising positively predicts overall experience evaluation (β = 0.162, p < 0.001), and emotional connection significantly predicts repurchase intention (β = 0.197, p < 0.001). We find that overall experience evaluation and subsequent behavioral responses are shaped by specific drivers, including service-related post-purchase factors, emotional fulfillment and brand trust, visual appeal, and affective/cognitive evaluations. These results point to possible gaps in theory when LCX is used in short-term travel retail contexts. To address these gaps, we propose the transient experience, relationship quality, action outcomes, connection, and engagement (TRACE) conceptual framework for analyzing feedback-driven encounters throughout the travel experience. Overall, this study extends LCX to episodic, time-constrained contexts and introduces TRACE as a conceptual complementary model to guide future theory testing and model validation in luxury travel retail contexts. Full article

Artificial intelligence (AI) has become a highly relevant tool in higher education. However, its acceptance by university students depends not only on technical or functional characteristics, but also on cognitive, contextual, and emotional factors. This study proposes and validates a model of acceptance of the use of AI devices (MIDA) in the university context. The model considers contextual variables such as anthropomorphism (AN), perceived value (PV) and perceived risk (PR). It also considers cognitive variables such as performance expectancy (PEX) and perceived effort expectancy (PEE). In addition, it considers emotional variables such as anxiety (ANX), stress (ST) and trust (TR). For its validation, data were collected from 517 university students and analysed using structural equations (CB-SEM). The results indicate that perceived value, anthropomorphism and perceived risk influence the willingness to accept the use of AI devices indirectly through performance expectancy and perceived effort. Likewise, performance expectancy significantly reduces anxiety and stress and increases trust, while effort expectancy increases both anxiety and stress. Trust is the main predictor of willingness to accept the use of AI devices, while stress has a significant negative effect on this willingness. These findings contribute to the literature on the acceptance of AI devices by highlighting the mediating role of emotions and offer practical implications for the design of AI devices aimed at improving their acceptance in educational contexts. Full article

Access to ecologically grown, nutritious food remains limited in low-income U.S. communities due to cost, structural inequities, and the dominance of industrial food systems. Stone Barns Center’s Leading an Ecological and Accessible Food System (LEAF) program—developed through a community-based participatory partnership in the South Bronx—aims to address these challenges through biweekly distributions of regeneratively grown produce, seasonal gardening kits, and culturally responsive nutrition education. This study presents findings from the first two years (2023 and 2024) of a multi-timepoint repeated cross-sectional evaluation using six household-level surveys (n = 79–80 families per round). The surveys captured changes in fruit and vegetable consumption, gardening comfort, emotional well-being, participation in SNAP and WIC programs, food purchasing behaviors, and unmet needs. Statistically significant (p < 0.05) improvements were observed across key outcomes: mean fruit and vegetable intake increased from 3.8 to 4.5 (1–5 scale), comfort with growing food increased from 3.1 to 4.6, emotional response to gardening from 4.1 to 4.6. SNAP participation increased from 15% (12 of 79 households) to 33% (26 of 79 households), and purchasing shifted toward local access points. Notably, 99% (79 of 80 households) of Year 1 families returned for Year 2, reflecting strong engagement and trust. These results highlight the potential of integrated, community-partnered, and climate-aligned interventions to advance health equity, ecological literacy, and food justice. The LEAF program offers a replicable model that may support pathways towards more sustainable and community-aligned food systems in other under-resourced settings. Full article

Phishing attacks continue to evolve and exploit fundamental human impulses, such as trust and the need for a rapid response, as well as emotional triggers. This makes the human mind both a valuable asset and a significant vulnerability. The proliferation of zero-day vulnerabilities has been identified as a significant exacerbating factor in this threat landscape. To address these evolving challenges, we introduce CrossPhire: a multimodal deep learning framework with an end-to-end architecture that captures semantic and visual cues from multiple data modalities, while also providing methodological insights for anti-phishing multimodal learning. First, we demonstrate that markup-free semantic text encoding captures linguistic deception patterns more effectively than DOM-based approaches, achieving 96–97% accuracy using textual content alone and providing the strongest single-modality signal through sentence transformers applied to HTML text stripped of structural markup. Second, through controlled comparison of fusion strategies, we show that simple concatenation outperforms a sophisticated gating mechanism so-called Mixture-of-Experts by 0.5–10% when modalities provide complementary, non-redundant security evidence. We validate these insights through rigorous experimentation on five datasets, achieving competitive same-dataset performance (97.96–100%) while demonstrating promising cross-dataset generalization (85–96% accuracy under distribution shift). Additionally, we contribute Phish360, a rigorously curated multimodal benchmark with 10,748 samples addressing quality issues in existing datasets (96.63% unique phishing HTML vs. 16–61% in prior benchmarks), and provide LIME-based explainability tools that decompose predictions into modality-specific contributions. The rapid inference time (0.08 s) and high accuracy results position CrossPhire as a promising solution in the fight against phishing attacks. Full article

Digital retail is undergoing a paradigm shift driven by the deep integration of artificial intelligence (AI) and augmented reality (AR). Although prior studies have examined the independent effects of AI-based personalized recommendation (cognitive path) and AR-enabled immersion (experiential path), how their integration systematically shapes user behavior through internal psychological mechanisms remains an important unresolved theoretical gap. To address this gap, this study develops an integrated model grounded in the stimulus–organism–response (S-O-R) framework and trust transfer theory. Specifically, the model examines how personalized recommendation, as a dynamic external stimulus, influences users’ cognitive state (perceived usefulness) and experiential state (immersion); how the overall trust of users in the integrated platform can be used as a key boundary condition to adjust the transformation efficiency from the above stimulus to the internal state; and how the above cognitive and experiential states can ultimately drive the continued usage intention through the mediation of positive emotional response. Based on survey data from 400 Chinese consumers with AR shopping experience on Taobao, analyzed using structural equation modeling (SEM), the results indicate that (1) personalized recommendation positively affects both immersion and perceived usefulness; (2) platform trust significantly and positively moderates the effects of personalized recommendation on both immersion and perceived usefulness; (3) both cognitive and experiential states stimulate positive emotions, which in turn enhance continued usage intention, with perceived usefulness exerting a stronger effect; (4) a key theoretical finding is that there is a significant positive correlation between perceived usefulness and immersion, revealing the coupling of psychological paths in an integrated environment; however, immersion does not moderate the effect of personalized recommendation on emotional responses, suggesting that the current integration mode emphasizes the formation of a stable psychological structure rather than real-time interaction. This study makes three contributions to the existing literature. First, it extends the application of S–O–R theory in a complex technological environment by analyzing the “organism” as a parallel and related cognitive-experience dual path and confirming its coupling relationship. Second, it elucidates the enabling role of trust as a moderating mechanism rather than a direct antecedent, thereby enriching micro-level evidence for trust transfer theory in the context of technology integration. Finally, by contrasting path coupling with process regulation, this study provides a more detailed distinction for understanding the theoretical connotations and boundaries of AI–AR technology integration, which may mainly be a kind of structural integration. Full article

Although communication quality is widely recognized as a catalyst for workplace innovation, existing research seldom integrates communication quality, trust in leadership, and organizational commitment within a single explanatory framework, particularly in team-based enterprises operating in emerging economies. This study examines how communication quality fosters employee innovation through the sequential mediating roles of trust in leadership and organizational commitment, emphasizing its contribution to sustainable enterprise performance. Rooted in Social Exchange Theory (SET), the study illustrates how transparent, reciprocal, and supportive communication enhances relational trust, strengthens employees’ emotional attachment to their organizations, and creates a climate conducive to creativity and collaborative problem-solving. A quantitative design was employed using data from employees engaged in innovation-driven projects within medium- and large-sized software firms in Turkey’s ICT sector. A total of 339 valid responses were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to test the hypothesized relationships. The findings demonstrate that communication quality directly promotes employee innovation and indirectly strengthens innovation through trust in leadership and organizational commitment as sequential mediators. Additionally, organizational commitment amplifies the influence of communication quality on innovation, indicating that committed employees more effectively translate constructive communication into innovative behaviors. These results underscore the strategic importance of communicative clarity, relational leadership, and commitment-building practices in shaping resilient, innovation-oriented teams. The study advances SET by identifying trust and commitment as key relational mechanisms through which communication quality drives innovation, offering theoretical enrichment and practical guidance for sustainable human resource management and team-based organizational development. Full article

This study aimed to develop and validate a self-report instrument—the Perceived Teacher Trust Behavior Scale (PTTBS)—to assess primary school students’ perceptions of trust-related behaviors exhibited by their teachers. Adopting a child-centered perspective within the school context, we first conducted in-depth interviews and applied a grounded theory approach to identify dimensions and generate initial items. A cluster sampling method was used to recruit 1400 students (Grades 3~5) from three schools in Guizhou Province, China, who completed the questionnaire. The collected data were analyzed via exploratory factor analysis and confirmatory factor analysis using SPSS 30.0 and Mplus8.10 software. The final version of the PTTBS consists of 13 items across four dimensions: Emotional Support, Competence Recognition, Academic Support, and Moral Recognition. The scale demonstrated excellent internal consistency (Cronbach’s α = 0.90) and split-half reliability (Spearman–Brown coefficient = 0.847). Significant correlations with an established Student-Teacher Relationship Scale were observed, along with good convergent validity (0.502~0.629) and construct validity. The PTTBS exhibits robust psychometric properties and serves as a valid tool for measuring Chinese primary school students’ perceptions of teacher trust behaviors, suitable for both research and practical applications. Full article

Background/Objectives: Home care plays a crucial role in contemporary healthcare systems, particularly in the long-term care of people with chronic and progressive illnesses. Family caregivers often experience substantial physical, emotional, and organizational burden. Telemedicine and digital health applications have the potential to support home care by improving health monitoring, communication, and care coordination. However, their use among family caregivers remains inconsistent, and little is known about how organizational support structures such as telemedicine centers influence acceptance and everyday use. This study aims to examine the benefits of telemedicine in home care and to evaluate the role of telemedicine centers as supportive infrastructures for family caregivers. Methods: A mixed-methods design was applied. Quantitative data were collected through an online survey of 58 family caregivers to assess the use of telemedicine and digital health applications, perceived benefits, barriers, and support needs. This was complemented by an in-depth qualitative case study exploring everyday caregiving experiences with telemedicine technologies and telemedicine center support. A systematic literature review informed the theoretical framework and the development of the empirical instruments. Results: Most respondents reported not using telemedicine or digital health applications in home care. Among users, telemedicine was associated with perceived improvements in quality of care, particularly through enhanced health monitoring, improved communication with healthcare professionals, and increased feelings of safety and control. Key barriers to adoption included technical complexity, data protection concerns, and limited digital literacy. Both quantitative findings and the qualitative case study highlighted the importance of structured support. Telemedicine centers were perceived as highly beneficial, providing technical assistance, training, coordination, and ongoing guidance that facilitated technology acceptance and sustained use. Conclusions: Telemedicine and digital health applications can meaningfully support home care and reduce caregiver burden when they are embedded in supportive socio-technical structures. Telemedicine centers can function as central points of contact that enhance usability, trust, and continuity of care. The findings suggest that successful implementation of telemedicine in home care requires not only technological solutions but also accessible organizational support and targeted training for family caregivers. Full article

This research investigates how hybrid review systems integrating human-generated reviews and AI-generated summaries shape consumer trust and decision-related confidence. Across three controlled experiments conducted in simulated e-commerce environments, when and how hybrid reviews enhance consumer evaluations were examined. Study 1 demonstrates that hybrid reviews, which combine the emotional authenticity of human input with the analytical objectivity of AI, elicit greater levels of review trust and decision confidence than single-source reviews. Study 2 employs an experimental manipulation of presentation order and demonstrates that decision confidence increases when human reviews are presented before AI summaries, because this sequencing facilitates more effective cognitive integration. Finally, Study 3 shows that AI literacy strengthens the positive effect of perceived diagnosticity on confidence, while information overload mitigates it. By explicitly testing these processes across three experiments, this research clarifies the mechanisms through which hybrid reviews operate, identifying authenticity and objectivity as dual mediators, and sequencing, literacy, and cognitive load as critical contextual moderators. This research advances current theories on human–AI complementarity, information diagnosticity, and dual-process cognition by demonstrating that emotional and analytical cues can jointly foster trust in AI-mediated communications. This integrative evidence contributes to a nuanced understanding of how hybrid intelligence systems shape consumer decision-making within digital marketplaces. Full article

This research addresses a critical gap in the Public–Private Partnership (PPP) research field by analysing risk allocation in an emergent African context: Morocco. Based on semi-structured interviews with six selected practitioners, along with lexicometric and sentiment analysis, this study identifies the major risks and the determinants influencing their allocation. Findings show a risk profile dominated by commercial, political, and industrial uncertainties. In addition, the research uncovers that risk allocation is not simply a technical task, but a multidimensional negotiation influenced by project characteristics, partner capabilities, macro-environmental imperatives, and transaction dynamics. Moreover, sentiment analysis reveals a vocabulary mainly reflecting the emotions of fear, anticipation, and trust, which points to the affective side of the contract. This study provides a qualitative framework that is sensitive to the context and that challenges standard economic models; it gives clear directions to policymakers handling complicated PPP arrangements in emerging markets. Full article

As artificial intelligence (AI) agents become deeply integrated into fitness systems, trustworthy human–AI agent interaction has become pivotal for user engagement in smart home fitness (SHF) e-commerce platforms. Grounded in the Computers Are Social Actors (CASA) framework, this study empirically investigates how, acting as AI fitness coaches, AI agents’ technical and social features shape users’ active engagement in the in-home social e-commerce context. A mixed-method approach was employed, combining computational text mining of 17,582 user reviews from fitness e-commerce platforms with a survey (N = 599) of Chinese consumers. The results show that (1) the technical–social features of AI agents serving as AI fitness coaches include visibility, gamification, interactivity, humanness, and sociability; (2) these five technical–social features of AI agents positively influence user compliance via both cognitive and emotional trust in AI agents; (3) these five technical–social features of AI agents serving as AI fitness coaches positively impact active engagement via both cognitive and emotional trust in AI agents. This study extends the CASA framework to the domain of AI coaching by demonstrating the parallel roles of cognitive and emotional trust in AI agents. For designers and managers in the fitness e-commerce industries, this study offers actionable insights for designing AI agents integrating functional and social features that foster trust and drive behavioral outcomes. Full article