Search Results (1,791)

Background/Objectives: Artificial intelligence (AI) tools for fracture detection in radiographs are increasingly approved for clinical use but remain underutilized. Understanding physician attitudes before implementation is essential for successful integration into emergency care workflows. This study investigates the acceptance of an AI-based fracture detection tool among physicians in emergency care settings, using the Unified Theory of Acceptance and Use of Technology (UTAUT) model. Methods: A cross-sectional, pre-implementation survey was conducted among 92 physicians across three hospitals participating in the SMART Fracture Trial (ClinicalTrials.gov: NCT06754137). The questionnaire assessed the four core UTAUT constructs—performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating conditions (FC)—and additional constructs such as attitude toward technology (AT), diagnostic confidence (DC), and workflow efficiency (WE). Responses were collected on a five-point Likert scale. Structural equation modeling (SEM) and confirmatory factor analysis (CFA) were performed to assess predictors of behavioral intention (BI). Results: PE was the strongest predictor of BI (β = 0.5882, p < 0.001), followed by SI (β = 0.391, p < 0.001), FC (β = 0.263, p < 0.001), and EE (β = 0.202, p = 0.001). These constructs explained a substantial proportion of variance in BI. WE received the lowest ratings, while internal consistency for SI and BI was weak. Moderator analyses showed prior AI experience improved EE, whereas more experienced physicians were more skeptical regarding WE and DC. However, none of the moderators significantly influenced BI. Conclusions: Physicians’ intention to use AI fracture detection is primarily influenced by perceived usefulness and ease of use. Implementation strategies should focus on intuitive design, targeted training, and clear communication of clinical benefits. Further research should evaluate post-implementation usage and user satisfaction. Full article

Background: Hospitalized patients’ expectations about their treatment play a key role in therapeutic adherence, satisfaction with care, and clinical outcomes. However, there is a lack of brief, psychometrically validated instruments in Spanish-speaking contexts that adequately assess this construct. Objective: The objective of this study is to culturally adapt and validate the Hospitalized Patients’ Expectations for Treatment Scale-Patient Version (HOPE-P) in a Peruvian population. Methods: A methodological, cross-sectional study was conducted with 277 hospitalized patients aged 18 to 85 years (M = 45.87; SD = 17.09). The adaptation process included translation, back-translation, expert review, and pilot testing. Confirmatory factor analysis (CFA) was performed to assess the factor structure, and reliability and validity indices were calculated. Results: The bifactorial model showed good fit (CFI = 0.97, TLI = 0.94, RMSEA = 0.06). One item with a low factor loading was removed to improve the model. Convergent and discriminant validity were confirmed through acceptable values of Average Variance Extracted (0.60 and 0.55) and inter-factor correlation (φ² = 0.23). Internal consistency was strong for both dimensions (α = 0.76–0.77; ω = 0.76–0.77). Conclusions: The Spanish version of the HOPE-P is a valid, reliable, and culturally appropriate instrument for evaluating treatment expectations in hospitalized Peruvian patients. Its implementation in clinical settings could enhance physician–patient communication, support shared decision-making, and contribute to better therapeutic outcomes, especially in high-demand healthcare environments. Full article

Background: This systematic review aims to summarize the most recent data from the literature on the psychological aspects of parents of children prenatally diagnosed with congenital heart defects (CHDs). Methods: A comprehensive literature search was conducted to identify relevant studies on the psychological issues faced by parents of children prenatally diagnosed with CHD. Searches were performed in multiple scientific databases, including PubMed, Science direct, Embase, Scopus, Medline, Clarivate, to ensure the broad coverage of the literature. The search was limited to studies published up until February 2025. The search strategy included the following terms and combinations: “congenital heart defect” OR “CHD” AND “prenatal diagnosis” AND “psychological impact” OR “parental distress” OR “coping”. Results: Eighteen studies involving the 673 parents of fetuses diagnosed with congenital heart defects were included. Studies spanned four continents and employed both qualitative (n = 14) and quantitative (n = 4) designs. Key psychological outcomes reported were anxiety, depression, stress, post-traumatic stress, coping strategies, maternal–fetal attachment, and life satisfaction. Anxiety and depression were the most frequent issues, with maternal anxiety reaching 65% and depression up to 45.7%. Stress related to diagnostic uncertainty was common. While some parents used adaptive coping (social support, emotional regulation), others experienced maladaptive patterns such as avoidance. One study reported increased maternal–fetal attachment following prenatal CHD diagnosis. Predictors of psychological distress included time of diagnosis, parental gender, education level, social support, and severity of the defect. Recommended interventions included early psychological screening, empathetic communication, structured counseling, and long-term emotional support. Despite heterogeneity in design and moderate overall bias, findings highlight a consistent psychological burden among parents, underscoring the need for integrated psychosocial care following a prenatal CHD diagnosis. Conclusions: Parents whose children have been prenatally diagnosed with a congenital heart defect are at an increased risk for psychological distress. To improve the quality of care, a multidisciplinary team is needed to provide parents with the necessary information on diagnosis, interventions, and potential outcomes. Full article

With the ongoing advancement of urbanization in China, a disparity has arisen between population demands and the allocation of community resources, resulting in a persistent increase in residential vacancy rates. The integration of service facilities into vacant residential spaces has enabled functional housing transformations. This study analyzes three typical types of communities in Xi’an to examine these transformations, identifying distinct types and patterns across five scenarios, which include social, health, leisure, cultural, and educational contexts. Through structured questionnaires and in-depth interviews, we collected data on residents’ life satisfaction and NIMBY (not in my backyard) perceptions. Applying a NIMBY index algorithm, we quantified characteristics and identified root causes. The results demonstrated that leisure scenarios most significantly affected satisfaction, while social scenarios showed the highest NIMBY index. Using an ordered logistic regression model, we determined key NIMBY factors influencing satisfaction across scenarios, revealing their differential impact mechanisms. Drawing on the findings, we investigated coordination mechanisms between the transformations of residential spaces and the needs of residents. Based on this analysis, the research objective was to explore how vacant housing can integrate service facilities while mitigating NIMBY effects and meeting resident needs. Proposed strategies include hierarchical facility allocation, NIMBY mitigation measures, and spatial planning optimization, ultimately adapting to diverse lifestyles and housing demands. Full article

This study explored a competency-based soft-skills programme supporting evolving community pharmacy professionals’ roles and sustainable practice in Serbia. Four researchers with academic and practice backgrounds developed the programme using healthcare guidelines and the International Pharmaceutical Federation’s competency framework. The process involved defining objectives, selecting methods, designing and organising activities, accreditation, and evaluating outcomes based on the Kirkpatrick model. From January 2021 to March 2025, the “Galenika Academy” was implemented through webinars, accredited tests, onsite courses, and a mobile application. Satisfaction was assessed via a validated online questionnaire among participants attending ≥80% of sessions, following evaluation of attendance and test performance. The programme reached 5107 participants, 10,427 webinar views, and 8252 test completions. The “Galiverse” mobile app, launched in February 2023, had 5558 users by March 2025. The most attended webinar was “Burnout” (787). Average test success was 82.9%, with 95.3% for “Resilience” and 61.0% for “Team Management.” Satisfaction was 95.5% for content, 94.2% for quality, 92.3% for materials, 77.1% for the application, and 96.3% would recommend it. Among those reporting improved resilience, 96.9% believed it could positively impact pharmacy operations. Pharmacists found the programme relevant and effective. Further research is needed to evaluate its impact on practice and patient outcomes. Full article

This article develops an innovative and intelligent method for analysing the criminal community’s influence on risk-forming parameters based on an analysis of regional economic processes. The research motivation was the need to create an intelligent method for quantitative assessment and risk control arising from the interaction between regional economic processes and criminal activity. The method includes a three-level mathematical model in which the economic activity dynamics are described by a modified logistic equation, taking into account the criminal activity’s negative impact and feedback through the integral risk. The criminal activity itself is modelled by a similar logistic equation, taking into account the economic base. The risk parameter accumulates the direct impact and delayed effects through the memory core. To numerically solve the spatio-temporal optimal control problem, a neural network based on the convolutional architecture was developed: two successive convolutional layers (N₁ with 3 × 3 filters and N₂ with 3 × 3 filters) extract local features, after which two 1 × 1 convolutional layers (FC₁ and FC₂) form a three-channel output corresponding to the control actions U_E, U_C, and U_I. The loss function combines the supervised component and the residual terms of the differential equations, which ensures the satisfaction of physical constraints. The computational experiment showed the high accuracy of the model: accuracy is 0.9907, precision is 0.9842, recall is 0.9983, and F1-score is 0.9912, with a minimum residual loss of 0.0093 and superiority over alternative architectures in key metrics (MSE is 0.0124, IoU is 0.74, and Dice is 0.83). Full article

Workplace health and safety issues have long plagued the construction industry. While safety efforts have traditionally focused on physical risks, increasing attention is being paid to mental health and work-related stressors, which can negatively affect both productivity and safety. In Saudi Arabia, the construction sector presents a unique context because of its highly diverse, multinational workforce. Workers of different nationalities often operate on the same job site, leading to potential communication barriers, cultural misunderstandings, and inconsistent safety practices, all of which may amplify stress and safety risks. This research aims to investigate the influence of work-related stressors on construction workers’ safety in Saudi Arabia and identify which stressors most significantly contribute to the risk of injury. A structured questionnaire was distributed to 349 construction workers across 16 job sites in Saudi Arabia. The survey measures ten key stressors identified in the literature, including job site demand, job control, job certainty, skill demand, social support, harassment and discrimination, conflict with supervisors, interpersonal conflict, and job satisfaction. Data were analyzed using logistic regression and Pearson correlation to examine relationships between stressors and self-reported injuries. The findings indicated that work-related stressors significantly predict workplace injury. While the first regression model showed a modest effect size, it was statistically significant. The second model identified job site demand and job satisfaction as the most influential predictors of injury risk. Work-related stressors, particularly high job demands and low job satisfaction, substantially increase the likelihood of injury among construction workers. These findings emphasize the importance of incorporating psychosocial risk management into construction safety practices in Saudi Arabia. Future studies should adopt longitudinal designs to explore causal relationships over time and include qualitative methods such as interviews to gain a deeper understanding. Additionally, factors such as nationality, organizational policies, and management style should be investigated to better understand their moderating effects on the stress–injury relationship. Full article

This study investigates urban life satisfaction and residents’ settlement intention as emergent outcomes of interconnected urban systems and examines the moderating role of urban regeneration budget execution as a systemic policy input. Drawing on the bottom-up spillover perspective and policy feedback theory, this study posits that satisfaction with core aspects of urban living—such as housing, transportation, and public safety—reflects the functioning of multiple interrelated urban subsystems, which accumulate into a global sense of well-being that influences settlement intention. Furthermore, when urban regeneration budgets are visibly and fully executed, they operate as institutional feedback mechanisms, leading residents to attribute their life satisfaction to effective system performance and reinforcing their desire to stay. Using survey data from Incheon Metropolitan City and Gyeonggi Province in South Korea, the study employs stereotype logistic regression to test the proposed model. The findings reveal that urban life satisfaction significantly predicts stronger settlement intention, and this effect is amplified in municipalities with higher levels of budget execution. These results contribute to theoretical understanding by linking subjective well-being with institutional performance and offer practical guidance for South Korean local governments seeking to strengthen community resilience through transparent and outcome-driven urban policy delivery. Full article

Background: Genomic information is becoming integral to nursing practice, yet undergraduate curricula often provide limited opportunities to apply this knowledge in realistic settings. Objective: To evaluate the impact of a clinical simulation-based intervention on nursing students’ learning of genetic counseling, with a focus on knowledge acquisition, communication skills, and student satisfaction. Methods: A sequential mixed-methods study was conducted with 30 third-year nursing students enrolled in the elective Genetics Applied to Health Sciences. Quantitative data comprised (i) pre-/post-simulation knowledge tests, (ii) a satisfaction questionnaire, and (iii) final course grades, which were compared with grades of a cohort from the previous academic year that had no simulation component (n = 28). Qualitative insights were gathered through field notes and semi-structured interviews with six purposively selected participants. During the intervention each student rotated through the roles of genetic-counseling nurse, patient, and observer, followed by a facilitated debriefing. Results: Post-simulation knowledge scores and final course grades were significantly higher than both baseline values and the historical comparison cohort. Students reported very high satisfaction, highlighting the authenticity of the scenarios and the usefulness of immediate feedback. Qualitative analysis showed that role rotation fostered deeper understanding of counseling complexities, improved empathic communication, and bolstered self-confidence when discussing hereditary risk. Conclusions: Embedding standardized-patient simulation into undergraduate genetics courses measurably improves students’ knowledge, communication proficiency, and satisfaction. These findings support incorporating similar simulation-based learning activities to bridge the gap between theoretical genetics content and real-world nursing practice. Full article

We introduce a novel optimization method, the Bud Lifecycle Algorithm (BLA), and present a mathematical model for optimizing urban transportation systems, demonstrated through a Baltimore case study. Our approach centers on the Proximity Topology Attribute Model, which integrates topological graph properties with K-means clustering to partition city nodes and identify key activity areas via betweenness centrality. A simulated bridge collapse reveals significant impacts on insurance companies and transport users. To balance traffic efficiency with construction costs in public transport projects, we propose a multi-objective optimization model prioritizing transit hubs while minimizing expenses in congested zones. We introduce the Bud Lifecycle Algorithm (BLA) to enhance traditional Genetic Algorithm performance, achieving improvements in system coverage, cost-efficiency, and user satisfaction. Our findings suggest that expanding public transport networks and optimizing rail projects could substantially boost employment and tourism in West Baltimore. We propose the Smart Traffic Management System (STMS) and Community Traffic Safety Program (CTSP) to enhance traffic safety, reduce congestion, and improve residents’ quality of life. Full article

Background: Face masks are used in healthcare for the prevention of the spread of disease; however, the recent COVID-19 pandemic raised awareness of the challenges of typical opaque masks that obscure nonverbal cues. In addition, various masks have been shown to attenuate speech above 1000 Hz, and lack of nonverbal cues exacerbates speech understanding in the presence of background noise. Transparent masks can help to overcome the loss of nonverbal cues, but they have greater attenuative effects on higher speech frequencies. This study evaluated a newer prototype transparent face mask redesigned from a version evaluated in a previous study. Methods: Thirty participants (10 with normal hearing, 10 with moderate hearing loss, and 10 with severe-to-profound hearing loss) were recruited. Selected lists from the Connected Speech Test (CST) were digitally recorded using male and female talkers and presented to listeners at 65 dB HL in 12 conditions against a background of 4-talker babble (+5 dB SNR): without a mask (auditory only and audiovisual), with an opaque mask (auditory only and audiovisual), and with a transparent mask (auditory only and audiovisual). Results: Listeners with normal hearing performed consistently well across all conditions. For listeners with hearing loss, speech was generally easier to understand with the male talker. Audiovisual conditions were better than auditory-only conditions, and No Mask and Transparent Mask conditions were better than Opaque Mask conditions. Conclusions: These findings continue to support the use of transparent masks to improve communication, minimize medical errors, and increase patient satisfaction. Full article

Access to assistive technology (AT) remains a major global challenge, with only 10% of people in need having access to essential devices. Free loan banks of assistive products have emerged as a strategy to promote equitable access, reduce costs, and improve autonomy and quality of life. This systematic review aimed to synthesize the available evidence on the impact of free loaner assistive device programs. A comprehensive search, following PRISMA guidelines, was conducted in Medline, Web of Science, and Scopus. Eight studies met the inclusion criteria, covering diverse populations and study designs. The results suggest a positive influence of these programs on autonomy, social participation, and quality of life, with a high demand for mobility and augmentative communication devices. Programs that incorporated interdisciplinary professional support reported better device-person matching, lower abandonment rates, and higher user satisfaction, as measured by tools such as PIADS, QUEST, and the MPT model. Moreover, loan programs demonstrated economic sustainability through reuse strategies, achieving up to 55% cost reduction. Despite these benefits, challenges remain, including unequal access, financial sustainability, and lack of standardized evaluation tools. Strengthening research, policy support, and professionalized management is essential to ensure the long-term success and scalability of AT loan programs. Full article

University students face increased stress and potential school burnout amid rapid digital transformation and competitive academic environments, yet little is known about how socioemotional processes explain the link between burnout and life satisfaction. This study examined how school burnout affects life satisfaction, mediated by loneliness and fear of alienation. A cross-sectional survey of 1783 students was conducted to measure school burnout, loneliness, fear of alienation, and life satisfaction. Structural equation modeling showed that school burnout had a significant negative direct effect on life satisfaction, mediated by loneliness. Higher burnout predicted greater loneliness, which in turn lowered life satisfaction. Although school burnout positively predicted fear of alienation, fear of alienation showed a complex association, with a positive direct path to life satisfaction. However, when loneliness was considered in the full mediation model, the overall indirect effect remained significantly negative. The sequential mediation pathway (school burnout → loneliness → fear of alienation → life satisfaction) highlighted how students’ social disconnection can intensify concerns about exclusion, ultimately affecting their well-being. These findings extend the literature by clarifying the socioemotional mechanisms linking school burnout and life satisfaction. Interventions should address academic demands and bolster emotional support, including resilience training, social skills development, and community-building programs, to mitigate loneliness and manage alienation concerns, thereby promoting students’ life satisfaction and psychological wellness. Full article

As the global carbon neutrality process accelerates, the proportion of distributed power sources such as wind power and photovoltaic power continues to increase. This transformation, while promoting the development of clean energy, also brings about the issue of new energy consumption. As wind and solar distributed generation rapidly expands into modern power grids, consumption issues become increasingly prominent. In this paper, a robust optimal scheduling method considering multiple uncertainties is proposed for community microgrids containing multiple renewable energy sources based on potential games. Firstly, the flexible loads of community microgrids are quantitatively classified into four categories, namely critical base loads, shiftable loads, power-adjustable loads, and dispersible loads, and a stochastic model is established for the wind power and load power; secondly, the user’s comprehensive electricity consumption satisfaction is included in the operator’s scheduling considerations, and the user’s demand is quantified by constructing a comprehensive satisfaction function that includes comfort indicators and economic indicators. Further, the flexible load-response expectation uncertainty and renewable generation uncertainty model are used to establish a robust optimization uncertainty set. This set portrays the worst-case scenario. Based on this, a two-stage robust optimization framework is designed: with the dual objectives of minimizing operator cost and maximizing user satisfaction, a potential game model is introduced to achieve a Nash equilibrium between the interests of the operator and the users, and solved by a column and constraint generation algorithm. Finally, the rationality and effectiveness of the proposed method are verified through examples, and the results show that after optimization, the cost dropped from CNY 2843.5 to CNY 1730.8, a reduction of 39.1%, but the user satisfaction with electricity usage increased to over 98%. Full article

Background/Objectives: Radiology often presents communication challenges due to its technical complexity, particularly for patients, trainees, and non-specialist clinicians. This study aims to evaluate the effectiveness of RadioBot, an AI-powered chatbot developed on the Botpress platform, in enhancing radiological communication through natural language processing (NLP). Methods: RadioBot was designed to provide context-sensitive responses based on guidelines from the American College of Radiology (ACR) and the Radiological Society of North America (RSNA). It addresses queries related to imaging indications, contraindications, preparation, and post-procedural care. A structured evaluation was conducted with twelve participants—patients, residents, and radiologists—who assessed the chatbot using a standardized quality and satisfaction scale. Results: The chatbot received high satisfaction scores, particularly from patients (mean = 4.425) and residents (mean = 4.250), while radiologists provided more critical feedback (mean = 3.775). Users appreciated the system’s clarity, accessibility, and its role in reducing informational bottlenecks. The perceived usefulness of the chatbot inversely correlated with the user’s level of expertise, serving as an educational tool for novices and a time-saving reference for experts. Conclusions: RadioBot demonstrates strong potential in improving radiological communication and supporting clinical workflows, especially with patients where it plays an important role in personalized medicine by framing radiology data within each individual’s cognitive and emotional context, which improves understanding and reduces associated diagnostic anxiety. Despite limitations such as occasional contextual incoherence and limited multimodal capabilities, the system effectively disseminates radiological knowledge. Future developments should focus on enhancing personalization based on user specialization and exploring alternative platforms to optimize performance and user experience. Full article