Search Results (381)

Understanding what people think about hydrogen energy and how this influences their acceptance of the associated technology is a critical area of research. The public’s willingness to adopt practical applications of hydrogen energy, such as hydrogen fuel-cell vehicles (HFCVs), is a key factor in their deployment. To analyse the direct and indirect effects of key attitudinal variables that could influence the intention to use HFCVs in Spain, an online questionnaire was administered to a representative sample of the Spanish population (N = 1000). A path analysis Structural Equation Model (SEM) was applied to determine the effect of different attitudinal variables. A high intention to adopt HFCVs in Spain was found (3.8 out of 5), assuming their wider availability in the future. The path analysis results indicated that general acceptance of hydrogen technology and perception of its benefits had the greatest effect on the public’s intention to adopt HFCVs. Regarding indirect effects, the role of trust in hydrogen technology was notable, having significant mediating effects not only through general acceptance of hydrogen energy and local acceptance of hydrogen refuelling stations (HRS), but also through positive and negative emotions and benefits perception. The findings will assist in focusing the future hydrogen communication strategies of both the government and the private (business) sector. Full article

Artificial intelligence (AI) techniques have propelled biomedical sensors beyond measuring physiological markers to interpreting subjective states like stress, pain, or emotions. Despite these technological advances, user trust is not guaranteed and is inadequately addressed in extant research. This review proposes the Cognition–Context–Contrast (CCC) conceptual framework to explain the trust and acceptance of AI-enabled sensors. First, we map cognition, comprising the expectations and stereotypes that humans have about machines. Second, we integrate task context by situating sensor applications along an intellective-to-judgmental continuum and showing how demonstrability predicts tolerance for sensor uncertainty and/or errors. Third, we analyze contrast effects that arise when automated sensing displaces familiar human routines, heightening scrutiny and accelerating rejection if roll-out is abrupt. We then derive practical implications such as enhancing interpretability, tailoring data presentations to task demonstrability, and implementing transitional introduction phases. The framework offers researchers, engineers, and clinicians a structured conceptual framework for designing and implementing the next generation of AI biosensors. Full article

Participation in organized sport is widely encouraged for youth development, yet positive outcomes are not guaranteed. Parents play a pivotal role in shaping young athletes’ experiences, requiring emotional support, interpersonal skills, and self-regulation. This study examines the meanings parents attribute to their children’s sports participation and how young athletes construct their experiences under parental and coaching influences. An interpretive phenomenological methodology involved semi-structured interviews with coaches, focus groups with parents, and open-ended questionnaires to young athletes. Seventeen players (M = 11.2 years, SD = 0.59), nineteen parents (M = 47.6 years, SD = 3.61), and two coaches from the same football club volunteered to participate in the study. Participants were selected through purposive sampling to ensure a homogeneous experience. The findings reveal that parental involvement balances support and pressure, while trust-building between parents and coaches significantly impacts the athletes’ experiences. The evolving role of technology and the importance of social dynamics within teams also emerged as critical factors. Intrinsic motivation, fostering emotional bonding through the sport, and adopting a developmental rather than purely competitive framework were emphasized factors identified as supporting positive youth sport experiences. These findings offer insights into how interconnected relationships among parents, coaches, and athletes influence children’s sports engagement and development. Full article

This paper explores emotional analysis in Hebrew texts, focusing on improving machine learning techniques for depression detection by integrating psychological feature lexicons. Hebrew’s complex morphology makes emotional analysis challenging, and this study seeks to address that by combining traditional machine learning methods with sentiment lexicons. The dataset consists of over 350,000 posts from 25,000 users on the health-focused social network “Camoni” from 2010 to 2021. Various machine learning models—SVM, Random Forest, Logistic Regression, and Multi-Layer Perceptron—were used, alongside ensemble techniques like Bagging, Boosting, and Stacking. TF-IDF was applied for feature selection, with word and character n-grams, and pre-processing steps like punctuation removal, stop word elimination, and lemmatization were performed to handle Hebrew’s linguistic complexity. The models were enriched with sentiment lexicons curated by professional psychologists. The study demonstrates that integrating sentiment lexicons significantly improves classification accuracy. Specific lexicons—such as those for negative and positive emojis, hostile words, anxiety words, and no-trust words—were particularly effective in enhancing model performance. Our best model classified depression with an accuracy of 84.1%. These findings offer insights into depression detection, suggesting that practitioners in mental health and social work can improve their machine learning models for detecting depression in online discourse by incorporating emotion-based lexicons. The societal impact of this work lies in its potential to improve the detection of depression in online Hebrew discourse, offering more accurate and efficient methods for mental health interventions in online communities. Full article

Previous research has predominantly focused on the impact of emotions on trust repair, yet has largely neglected how the manner of emotional communication influences this process. Centering on guilt—the emotion most commonly experienced by transgressors following a trust breach—this study examines whether spontaneous versus strategic guilt communication exerts differential effects on trust repair, and explores how the severity of the trust violation moderates this relationship. Study 1 compared the trust repair efficacy of spontaneous and strategic guilt communication. Study 2 tested the moderating role of violation severity. Results from Study 1 indicated that spontaneous guilt communication facilitated significantly greater trust repair than strategic communication. Study 2 further revealed that this advantage emerged only when the trust violation was severe. These findings advance theoretical understanding of guilt as a trust repair strategy and offer practical guidance for nurturing and restoring trust in interpersonal contexts, thereby promoting relational harmony. Full article

Increasing automation and the rapidly growing use of robots in industrial as well as social areas result in a greater need for research regarding collaboration between humans and robots. Key factors for a safe and successful combination of human and robot abilities include acceptance and trust in the robot. In order to prevent physical and psychological harm to humans, reducing these negative emotions and increasing trust and acceptance are essential. One way to achieve this is through the use of virtual training methods and environments. However, current research scarcely covers this approach. Therefore, this research focusses on an experimental approach to investigate emotional and psychophysiological (ECG, EDA) reactions while performing a collaborative assembly task (screwing) with an industrial robot in a real and a virtual setting, respectively. The study sample consisted of 46 participants (23 female) with an age range from 20 to 58 years. The results of the analyzed subjective and objective psychophysiological (cardiovascular and electrodermal responses) measures provide more information regarding the suitability of virtual trainings for human–robot collaboration. Differences in task complexity were measurable in both virtual and real environments. Furthermore, gender differences were also shown. Full article

Despite growing interest in AI technologies, there is a lack of integrated models explaining AI adoption in SMEs from a consumer perspective. This study addresses this gap. Although artificial intelligence (AI) has gained traction in digital innovation strategies, especially among SMEs, existing research lacks integrative models that address cognitive, contextual, and emotional factors driving AI adoption. This study addresses this gap by developing a theoretical model based on TAM and UTAUT2, enhanced with passion, workplace integration, and trust. Drawing on the Technology Acceptance Model and consumer trust theories, the study provides empirical insights into how these factors shape behavioral intentions to adopt AI technologies. The findings aim to inform both theory and practice by highlighting how emerging digital tools affect consumer decision making and engagement across personal and professional contexts. The study contributes to both theory and practice by offering empirical evidence on the drivers of AI adoption and by providing managerial recommendations for SMEs to implement AI-driven personalization responsibly. Full article

Background: Equine-assisted experiential learning (EAL) is an emerging approach that uses human–horse interactions to develop leadership skills through experiential methods. Purpose: This review synthesizes the literature on the role of EAL in developing leadership competencies and explores its implications for workplace learning. Design/methodology/approach: A narrative review was conducted examining empirical studies and theoretical frameworks on EAL and leadership development. Findings/Conclusions: Recent studies show EAL improves self-awareness, emotional intelligence, nonverbal communication, trust building, adaptability, and problem solving. These competencies are fostered through activities such as ground-based exercises, join-up techniques, and trust-building tasks, which require congruence between intention and action. Participants report behavioral changes such as improved empathy, clarity under pressure, and team cohesion. These align with core management skills for organizational performance. Implications: EAL complements traditional leadership training by developing relational and embodied leadership skills, including trust building, adaptability, and emotional intelligence, which contribute to organizational resilience and sustainable growth. Full article

Background: Artificial intelligence (AI) is being increasingly promoted as a means to enhance diagnostic accuracy, to streamline workflows, and to improve overall care quality in primary care. However, empirical evidence on how primary care physicians (PCPs) perceive, engage with, and emotionally respond to AI technologies in everyday clinical settings remains limited. Concerns persist regarding AI’s usability, transparency, and potential impact on professional identity, workload, and the physician–patient relationship. Methods: This qualitative study investigated the lived experiences and perceptions of 28 PCPs practicing in diverse outpatient settings across Germany. Participants were purposively sampled to ensure variation in age, practice characteristics, and digital proficiency. Data were collected through in-depth, semi-structured interviews, which were audio-recorded, transcribed verbatim, and subjected to rigorous thematic analysis employing Mayring’s qualitative content analysis framework. Results: Participants demonstrated a fundamentally ambivalent stance toward AI integration in primary care. Perceived advantages included enhanced diagnostic support, relief from administrative burdens, and facilitation of preventive care. Conversely, physicians reported concerns about workflow disruption due to excessive system prompts, lack of algorithmic transparency, increased cognitive and emotional strain, and perceived threats to clinical autonomy and accountability. The implications for the physician–patient relationship were seen as double-edged: while some believed AI could foster trust through transparent use, others feared depersonalization of care. Crucial prerequisites for successful implementation included transparent and explainable systems, structured training opportunities, clinician involvement in design processes, and seamless integration into clinical routines. Conclusions: Primary care physicians’ engagement with AI is marked by cautious optimism, shaped by both perceived utility and significant concerns. Effective and ethically sound implementation requires co-design approaches that embed clinical expertise, ensure algorithmic transparency, and align AI applications with the realities of primary care workflows. Moreover, foundational AI literacy should be incorporated into undergraduate health professional curricula to equip future clinicians with the competencies necessary for responsible and confident use. These strategies are essential to safeguard professional integrity, support clinician well-being, and maintain the humanistic core of primary care. Full article

In October 2024, a DANA (Isolated Depression at High Levels) triggered torrential rains across the Valencian Community, causing 227 deaths, severe infrastructure damage, and economic losses estimated at €17.8 billion. In this context of crisis, startups, despite having fewer resources and less experience than large corporations, played a significant role in crisis communication, shaping public perception and operational continuity. This study explores the communication strategies adopted by startups during and after the disaster, focusing on their activity on Instagram, TikTok, and Facebook between October 2024 and January 2025. Using a mixed-methods approach, we conducted a quantitative analysis of digital discourse through the Fanpage Karma tool, assessing metrics such as engagement, reach, and posting frequency. Sentiment analysis was performed using GPT-4, an advanced natural language processing model, and in-depth interviews with startup representatives provided qualitative insights into reputational impacts. The findings reveal that startups which aligned their discourse with the social context, prioritizing transparency and emotional proximity, enhanced their visibility and credibility. These results underscore how effective crisis communication not only mitigates reputational risk but also strengthens the local entrepreneurial ecosystem through trust-building and social responsibility. Full article

Background/Objectives: Pelvic organ prolapse (POP) is a common condition that significantly impacts quality of life. Research has focused largely on older women, while experiences of younger women remain relatively underexplored despite challenges unique to this population. Informed by the biopsychosocial model of illness, this study aims to assess the symptom burden, treatment goals, and information needs of younger women complaining of prolapse by analyzing questionnaire responses from an existing electronic Personal Assessment Questionnaire—Pelvic Floor (ePAQ-PF) dataset. Methods: Mixed-methods content analysis was conducted using free-text data from an anonymized multi-site ePAQ-PF dataset of 5717 responses collected across eight UK NHS trusts (2018–2022). A quantitative, deductive approach was first used to identify younger women (≤50 years old) with self-reported prolapse. ePAQ-PF scores for younger women with prolapse were compared with those aged >50 years, using Mann–Whitney tests. Free-text response data were analyzed inductively to qualitatively explore younger women’s symptom burden, treatment goals, and information needs. Results: Of the 1473 women with prolapse identified, 399 were aged ≤50 years. ePAQ-PF scores of the younger cohort demonstrated significantly greater symptom severity and bother than those aged >50, particularly in bowel, prolapse, vaginal, body image, and sexual health domains (p < adjusted threshold). Qualitative analysis undertaken to understand women’s concerns and priorities produced five health-related themes (physical health; functionality; psychosocial and emotional wellbeing; reproductive and sexual health; and healthcare journeys) and a sixth intersecting theme representing information needs. Conclusions: The findings highlight the substantial symptom burden of younger women with prolapse, as well as treatment goals and information needs specific to this population. The development of age-specific resources is identified as a requirement to support this group. Full article

This article explores the integration of artificial intelligence (AI) in digital marketing through social and mobile networks and its role in fostering sustainable consumer behavior. AI enhances personalization, sentiment analysis, and campaign automation, reshaping marketing dynamics and enabling brands to engage interactively with users. A quantitative study conducted on 501 social media users evaluates how perceived benefits, risks, trust, transparency, satisfaction, and social norms influence the acceptance of AI-driven marketing tools. Using structural equation modeling (SEM), the findings show that social norms and perceived transparency significantly enhance trust in AI, while perceived benefits and satisfaction drive user acceptance; conversely, perceived risks and negative emotions undermine trust. From a sustainability perspective, AI supports the efficient targeting and personalization of eco-conscious content, aligning marketing with environmentally responsible practices. This study contributes to ethical AI and sustainable digital strategies by offering empirical evidence and practical insights for responsible AI integration in marketing. Full article

Chemical, biological, radiological, and nuclear (CBRN) incidents pose significant challenges requiring swift, coordinated responses to safeguard public health. This is especially the case in densely populated urban areas, where the public is not only at risk but can also be of assistance. Public cooperation is critical to the success of mass decontamination efforts, yet prior research has primarily focused on technical and procedural aspects, neglecting the psychological and social factors driving casualty behaviour. This paper addresses this gap through a narrative literature review, chosen for its flexibility in synthesising fragmented and interdisciplinary research across psychology, sociology, and emergency management. The review identified two primary pathways influencing casualty decision making: rational and affective. Rational pathways rely on deliberate decisions supported by clear communication and trust in responders’ competence, while affective pathways are shaped by emotional responses like fear and anxiety, exacerbated by uncertainty. Trust emerged as a critical factor, with effective —i.e., transparent, empathetic, and culturally sensitive— communication being proven to enhance public cooperation. Cultural and societal norms further shape individual and group responses during emergencies. This paper demonstrates the value of narrative reviews in addressing a complex, multifaceted topic such as casualty behaviour, enabling the integration of diverse insights. By emphasising behavioural, psychological, and social dimensions, the results of this paper offer actionable strategies for emergency responders to enhance public cooperation and improve outcomes during CBRN incidents. Full article

Background: The outbreak of the COVID-19 pandemic has highlighted the importance of online health consultations, as they can help reduce the risk of contagion and infection. However, due to limited trust, these services have not yet gained widespread adoption and usage among patients. Objective: This research aims to examine the impact of perceived quality on patients’ adoption and usage of online health consultations from three perspectives: emotional support, responsiveness, and service continuity. Additionally, this research further explores the moderating effects of online service prices on these relationships. Methods: Based on trust theory, this research constructs theoretical models and empirically tests them by using a panel dataset that comprises 1255 physicians and 65,314 physician–patient communication records. Results: The empirical results confirm that emotional support, responsiveness, and service continuity positively influence patients’ adoption and usage behaviors. Additionally, higher online service prices negatively moderate the impact of emotional support and responsiveness on adoption behavior. Moreover, increased online service prices weaken the positive relationship between emotional support and usage behavior while strengthening the positive relationship between service continuity and usage behavior. Conclusions: This research extends the existing literature on online health services and provides practical guidance for platform managers, physicians, and policymakers to improve overall service acceptance. Full article

Introduction: Hospitalization of children creates significant emotional and psychological stress for parents, highlighting the importance of addressing their needs in pediatric care settings. Aims: This study examines the perceptions of both parents and pediatric nurses regarding the needs of hospitalized children. Method: A cross-sectional survey using the validated Needs of Parents of Hospitalized Children (NPQ) was administered to 218 parents and 218 pediatric nurses in four hospitals in Jeddah, Saudi Arabia. Key domains assessed included trust, information, and support. Group differences were evaluated using non-parametric statistical analyses. Results: Trust was prioritized more by parents (83.9%) than nurses (72.4%) (p < 0.05). Both groups deemed information important, but parents (87.2%) rated it as more necessary than nurses (74.1%) (p = 0.02). Parents (79.8%) expressed a greater need for support compared to nurses (67.3%) (p = 0.03). Conclusions: This study identified perceptual differences between parents and nurses regarding trust, communication, and support. Some differences were statistically significant at the p < 0.01 level, while others were suggestive (p-value between 0.01 and 0.05) and require further investigation. These disparities suggest a need to foster mutual understanding and improve communication practices to better align healthcare delivery with family expectations and strengthen family-centered care. Full article