Search Results (199)

AI-powered conversational agents are becoming part of the everyday Internet information ecosystem, reshaping how users seek, interpret, and act on health-related information outside clinical encounters. As large language model (LLM)-based chatbots are increasingly used as on-demand digital health information tools, understanding how users perceive their credibility, usefulness, and limitations is essential for the responsible design of future Internet-based health services. This mixed-method survey study examined how general adults evaluated healthcare-related question–answer pairs provided by physicians and generated by AI chatbots. A sample of U.S.-based adults recruited through Prolific (N = 62) rated each answer on clarity, usefulness, appropriateness of detail, trustworthiness, and perceived evidence, and provided open-ended explanations of their judgments. Primary mixed-effects analyses showed that both ChatGPT- and Claude-generated responses received higher overall participant ratings than physician-provided responses, although the estimated difference was substantially larger for Claude (ChatGPT–physician estimate = 0.250, 95% CI [0.135, 0.364]; Claude–physician estimate = 0.825, 95% CI [0.710, 0.939]). ChatGPT received higher ratings on four of the five dimensions but not on clarity, whereas Claude received higher ratings across all five dimensions. However, physician, ChatGPT, and Claude responses were always presented first, second, and third, respectively. Response source was therefore confounded with presentation position, and the observed differences cannot be attributed exclusively to source. The responses were also not matched for length or format. Qualitative findings showed that participants valued detailed, specific, and evidence-like explanations. Participants also expressed concerns about hallucination, privacy, over-reliance, and the need for clinician verification. These findings suggest that LLM-based chatbots may be perceived as useful supplemental information tools within future Internet health ecosystems, but their deployment should include safeguards that support transparency, verification, and appropriate reliance. Full article

The introduction of Joint Clinical Assessments (JCAs) under the European Union Health Technology Assessment Regulation (EU HTAR) represents a major structural reform aimed at reducing fragmentation and duplication in clinical evidence assessment across Member States. While JCAs are intended to support national health technology assessment (HTA) processes through a common EU-level clinical evaluation, their integration into established national HTA and reimbursement systems remains untested at this early stage of implementation. This paper reports findings from two surveys conducted in 2025 among local affiliate representatives with expertise in relevant HTA and market access activities across 25 European countries (comprising 24 EU Member States and Norway), capturing early national perspectives on key aspects of JCA implementation. The surveys explored anticipated impact on national reimbursement timelines, current opportunities for early HTA advice and PICO input, approaches to handling post-JCA data availability, and nationally prioritised policy and implementation issues. Results indicate mixed expectations regarding the potential impact of JCA on reimbursement timelines, with perceived risks of delay largely viewed as possibly transitional and mitigable through national process adaptation. Respondents emphasised the importance of transparency in PICO consolidation and clarity on the use of JCA reports in national appraisals. Overall, the findings suggest that JCA may represent a reconfiguration rather than a centralisation of evidence assessment, with national influence exercised earlier in the assessment lifecycle. These insights provide policy-relevant input to inform ongoing EU HTA implementation and future refinement of the JCA framework. Full article

This mixed-methods study examines the associations among fintech advancement, green finance, and financial inclusion in Jordan, an emerging economy. It draws on a distinctive three-part dataset: survey data from 21 commercial banks (N = 21), a national household survey, and semi-structured interviews with stakeholders. The quantitative results indicate that the positive association between fintech adoption and the provision of green finance is statistically consistent with full mediation by banks’ absorptive capacity, particularly their digital maturity and data analytics capabilities. Proactive regulatory support significantly moderates this mediated relationship. Market demand, by contrast, has no statistically significant moderating effect. At the household level, the combined use of digital and green financial products is associated with higher formal account ownership and with the use of a greater number of financial products. The interviews support these results, pointing to institutional capacity and regulatory clarity as essential enabling factors. Given the cross-sectional bank-level data (N = 21) and the exploratory scope of the mediation analysis, causal interpretations should be avoided. Future longitudinal research is needed to examine temporal dynamics. Even so, these findings offer policymakers an initial empirical framework: channeling fintech toward sustainable development will likely require targeted interventions to build institutional digital capacity and establish clear regulatory frameworks, rather than depending solely on market forces. Full article

Consumer trust is critical to the sustainable development of cross-border B2C e-commerce platforms. Accurately evaluating and diagnosing trust weaknesses has become a key concern for both practitioners and researchers. To address the inherent limitations of existing trust evaluation methods, this study proposes an improved AHP-Ridge Regression hybrid model that integrates expert knowledge with actual consumer perception data. First, an improved Analytic Hierarchy Process based on stakeholder-oriented nonlinear programming is employed to optimize the evaluation weights of nine experts, reduce subjective bias, and generate expert prior weights for each dimension and indicator. Second, these prior weights are incorporated as the regularization prior mean of the Ridge Regression model to construct the improved AHP-Ridge Regression model. Based on survey data from 387 valid respondents across five major cross-border platforms (Tmall Global, JD International, Pinduoduo Global, Sam’s Club Global, and CDFG Duty-Free), the model is compared with six baseline models using a 30-times repeated five-fold nested cross-validation. The proposed model achieves the lowest RMSE (0.3179) and highest R² (0.6510) among all compared models, with statistically significant improvements over all baselines (Nadeau–Bengio-corrected p < 0.001, large Cohen’s d effect sizes). However, the improvement over conventional Linear Regression is modest in absolute magnitude (ΔRMSE ≈ 0.0012). The primary value of the proposed model lies not in a dramatic leap in predictive accuracy but in its theoretical grounding, interpretability, and diagnostic capability. Permutation importance analysis reveals that Platform Fluidity, AI Technology Usability, Page Layout & Navigation Clarity, Content Accuracy, and Policy Assurance are the most important predictors of consumer trust. Comprehensive calibration and residual diagnostics (including MAE, normality tests, and heteroscedasticity checks) confirm the model’s predictive reliability. Furthermore, platform-specific diagnostics identify three distinct trust profiles (high-trust benchmark, trust-improvement priority, and mixed-profile platforms), providing managers with actionable insights for resource allocation. This study offers cross-border B2C e-commerce platforms a trust evaluation tool that balances predictive accuracy and interpretability, and provides implications for sustainable platform governance and ESG-oriented management by linking trust diagnostics with platform accountability frameworks. Full article

Background: Teachers routinely encounter children whose behaviour reflects emotional distress and dysregulation, yet they have limited opportunities to practise the relational skills required to respond effectively. These challenges are particularly pronounced in Alternative Provision (AP), which serves children who frequently present with histories of trauma, neurodevelopmental differences, and complex emotional and behavioural needs. Mentalization, the capacity to understand behaviour in terms of underlying mental states, is central to effective relational practice in such contexts. Conversational Artificial Intelligence (AI) may offer a scalable means of supporting this form of skills development, but its feasibility as a teacher-training modality remains largely unexplored. Methods: This mixed-methods proof-of-concept feasibility study evaluated MentaClassAI, a novel AI-based training tool in which educators engaged in simulated voice conversations with AI child characters portraying classroom dysregulation and subsequently received individualised, mentalization-informed feedback. Eleven staff members from a single AP school (four teachers and seven teaching assistants) completed a single training session and were allocated to either a psychoeducation video condition (n = 6) or a no-video condition (n = 5). The video condition received a brief introduction to mentalization and epistemic trust prior to engaging with the simulation. Pre- and post-engagement measures included the Reflective Functioning Questionnaire (RFQ-8) and a Teacher Self-Efficacy Scale. Post-engagement measures included an 18-item acceptability questionnaire, a Technology Acceptance Model scale, and open-ended questions analysed using thematic analysis. Results: Acceptability was high, with 84.8% of questionnaire responses falling within the positive range (overall M = 5.60/7). Feedback accuracy (M = 6.55) and clarity (M = 6.36) received the highest ratings. Participants reported higher teacher self-efficacy after the session than before (d = 1.20, p = 0.003), with 10 of 11 participants demonstrating improvement. Self-reported hypomentalizing was lower after the session (d = −0.86, p = 0.017). Between-condition differences (video versus no-video) were not statistically significant. The video condition scored numerically higher on the directional indicators. Qualitative analysis identified five themes: the value of consequence-free rehearsal; the specificity and usefulness of feedback; appreciation of the focus on the child’s emotional experience; limitations in the ecological diversity of AI child characters; and a desire for more naturalistic interaction. Conclusions: These findings provide preliminary support for the feasibility and acceptability of AI-based mentalization practice for AP staff. The principal value of the tool appears to lie not only in the simulation itself but in the quality of the reflective feedback generated. Although based on a small sample, the observed pre–post changes provide an encouraging signal that may justify a controlled trial. The contribution of pre-session psychoeducation to training outcomes remains an important question for future research. Full article

Harmful cyanobacteria blooms (CyanoHABs) have become a common problem in freshwater ecosystems. Monitoring at the federal and state level in response to this threat has increased over the last decade across the United States. In 2018, Pennsylvania environmental agencies began collecting CyanoHAB data to inform state regulatory and management efforts. 998 discrete samples from 138 waterbodies were collected over four years. These data were used to determine if indicators often used in CyanoHAB monitoring co-occurred with toxic conditions. Cyanotoxins were detected in more than half of the samples in Pennsylvania’s monitoring program with anatoxin, saxitoxins, and microcystins detected in similar proportions. It is important to note that the monitoring program is not designed to be representative of all Pennsylvania lakes but instead is targeted toward sites with greater exposure (recreational beaches) or sites with suspected blooms. Our findings suggest that cyanobacteria growth and cyanotoxin production may be driven by independent variables, as only microcystins concentrations were positively correlated with cyanobacteria counts. While increased cyanobacteria counts were related to all environmental variables considered in this study (warmer water temperatures, increased dissolved oxygen concentrations, and reduced water clarity), the relationships between cyanotoxins and environmental variables were mixed. Our analyses highlight the complexities of bloom occurrence and severity, and the challenges of incorporating these factors into monitoring and management strategies. Long-term monitoring approaches like the one analyzed here can inform management strategies that rely on environmental cues and cyanobacteria enumeration to evaluate risk of cyanotoxin presence. Full article

Background/Objectives: The predictive value of the Nursing Child Assessment Feeding Scale (NCAFS) for eating, diet, and growth outcomes among healthy infants is not well-described. Methods: In this prospective cohort study, healthy infants (n = 227) were assessed with the NCAFS at 0.5, 2, and 4 months and outcomes were measured concurrently and at 12 months. Maternal feeding and infant eating behaviors were observed during a separate feeding and assessed with the Infant Feeding Styles Questionnaire, Baby Eating Behavior Questionnaire, Children’s Eating Behavior Questionnaire-Toddler, and a diet questionnaire. Sucking was measured and anthropometry obtained. Results: In mixed models with repeated measures, concurrent associations included maternal verbalization while waiting for a separate feeding with maternal Sensitivity to Cues (β = 0.80) and maternal Cognitive Growth Fostering (β = 1.05); maternal verbalization during a separate feeding with maternal Social–Emotional Growth Fostering (β = 1.10) and maternal Cognitive Growth Fostering (β = 1.37); suck duration with infant Clarity of Cues (β = −5.35); feeding duration with maternal Social–Emotional Growth Fostering (β = 0.04), maternal Cognitive Growth Fostering (β = 0.03), and infant Responsiveness to Caregiver (β = 0.06); and bottle-feeding intensity with maternal Social–Emotional Growth Fostering (β = −1.11). Prospective associations included maternal Sensitivity to Cues with infant weight-for-length z-score change per month (β = −0.02) and maternal Social–Emotional Growth Fostering with breastmilk feeding intensity (β = 0.06). Conclusions: Associations were primarily null. However, more social interaction during feeding, less nutritive sucking (i.e., shorter suck duration), longer feeding duration, and lower bottle-feeding intensity were associated with more optimal NCAFS scores concurrently, and more optimal NCAFS scores were associated with lower weight-for-length z-score change and greater breastmilk feeding intensity prospectively. Full article

The adoption of pulse oximetry screening (POS) in low- and middle-income countries remains limited. We describe the development, implementation, and evaluation of a POS program at two of the leading tertiary centers in Accra, Ghana, based on a modified American Academy of Pediatrics protocol. Screening was conducted by trained research assistants. Operational experiences of research assistants were evaluated using a mixed-methods approach, including post-implementation surveys (n = 14) and focus group discussions (n = 10). Although participants felt comfortable with the level of instruction, they recommended incorporating simulation exercises to strengthen management of failed screens. Key challenges included difficulty locating newborns due to fragmented wards and paper-based records, equipment durability issues, and complex coordination for echocardiography following failed screens. Early discharge practices and high neonatal intensive care unit admissions reduced screening coverage among high-risk infants. Despite limited referral systems and surgical capacity, the POS pilot increased provider awareness, improved diagnostic clarity and demonstrated feasibility. Sustainable expansion will require more efficient referral networks as well as investment in pediatric cardiology training and cardiac surgical infrastructure. Full article

Background/Objectives: This decentralized, real-world observational cohort study assessed whether Cheers Restore (Houston, TX, USA), a commercially available dietary supplement, is associated with improved next-day subjective well-being (energy, mental clarity, physical well-being, and sleep quality) following alcohol consumption in healthy adults. A secondary aim evaluated the feasibility of integrating consumer wearables into future controlled studies. Methods: Ninety adults (56% female; mean age 44.4 years) were enrolled via the Alethios digital research platform and contributed 2958 morning surveys across three self-selected behavioral conditions: Alcohol-Only (reference), Cheers Restore, and Non-Drinking Baseline. Four subjective outcomes (energy, mental clarity, physical well-being, sleep quality rating; 1–10 scale) were modeled using linear mixed-effects models with random intercepts for participant and centered drink count as a covariate. Results: Cheers Restore use was associated with statistically significant improvements across all four subjective outcomes relative to alcohol-only nights: mental clarity (β = 0.356, 95% CI 0.214–0.499, p < 0.001), physical well-being (β = 0.335, 95% CI 0.189–0.482, p < 0.001), energy (β = 0.270, 95% CI 0.133–0.407, p < 0.001), and sleep quality rating (β = 0.263, 95% CI 0.096–0.430, p = 0.002). Standardized effect sizes were small (Cohen’s d = 0.20–0.32). Paired Alcohol Use Disorders Identification Test–Consumption (AUDIT-C) analysis confirmed stable consumption with no evidence of increased alcohol consumption over the short, self-reported follow-up. Conclusions: In this observational cohort, Cheers Restore use was associated with consistent improvements in next-day subjective well-being. These findings warrant a randomized, placebo-controlled trial to establish causality. ClinicalTrials.gov: NCT07069608, registered 16 July 2025. Full article

Depressive symptoms are highly prevalent among individuals with substance use disorders, particularly opioid use disorder (OUD), yet their clinical meaning is often difficult to determine. In routine practice, these symptoms are commonly interpreted within a binary framework, either as manifestations of an independent mood disorder or as substance-induced states related to intoxication, withdrawal, or early abstinence. Although clinically useful, this distinction may not fully capture a third configuration in which depressive psychopathology emerges within the chronic addictive process itself. This Perspective proposes a tripartite model of depressive states in OUD informed primarily by clinical and dimensional studies conducted in populations with heroin use disorder. First, substance-induced depression refers to mood symptoms temporally linked to the acute or subacute pharmacological effects of substances and generally expected to improve with stabilization or sustained abstinence. Second, an independent mood disorder may coexist with OUD, with particular attention warranted for bipolar-spectrum presentations characterized by affective instability, cyclothymic or irritable temperaments, mixed features, and mood-related patterns of substance use. Third, addiction-related depression describes a persistent depressive configuration associated with reward dysregulation, hypophoria, motivational depletion, cognitive inefficiency, and the Worthlessness/Being Trapped dimension identified primarily in dimensional studies of heroin use disorder. These configurations should not be regarded as rigid or mutually exclusive categories, but as longitudinal clinical formulations that may predominate at different stages of the addictive trajectory. Distinguishing among them may improve diagnostic clarity and support a hierarchical clinical approach in which stabilization of OUD is generally an initial therapeutic priority, while antidepressant and mood-stabilizing interventions are guided by symptom severity, temporal course, psychopathological organization, and evidence of an independent mood disorder. Full article

This article reports the design, implementation, and formative perception-based evaluation of an early-stage virtual reality (VR) prototype that integrates a virtual cane, localized haptic feedback, 3D audio, and a three-layer bioinspired sensing framework. The prototype was implemented in Unity 2022.3 using the XR Interaction Toolkit and URP and was structured according to design science research methodology (DSRM). The bat–whisker–contact framework was used as a functional abstraction to organize distal auditory reference or warning, proximal haptic feedback, and contact confirmation; it was not evaluated against a non-bioinspired baseline. The completed evaluation consisted of an anonymous, voluntary, post-use questionnaire administered to 25 sighted participants who could select which visual-input configurations to experience. The analysis focused on reported clarity, tolerability, initial signal interpretability, and design feedback; it did not include objective navigation metrics or assess clinical efficacy, training transfer, accessibility outcomes, or orientation-and-mobility performance in blind or low-vision users. General responses suggested favorable perceived clarity and multimodal usefulness, while cane length, floor-versus-wall/obstacle differentiation, and reported discomfort identified priorities for technical refinement. In the simulated no-vision condition (n = 21), participants reported high reliance on the cane response, whereas reported initial insecurity or doubt and basic mental map ratings remained mixed. The study contributes an early-stage technological artifact and a formative basis for subsequent controlled evaluations with objective performance measures, reference conditions, and target users or orientation and mobility specialists. Full article

Architectural design studios increasingly emphasize sustainable, people-centered outdoor space, yet students often treat vegetation as ornament rather than as a spatial and environmental device, rarely translating spatial analysis into explicit design decisions. This study examines how intermediate-level architecture students translate space-syntax indicators—choice/betweenness, local integration and visual integration—into strategic vegetation decisions for paths, pause areas, visual filters and comfort in a minimal sustainable shelter. Using an exploratory mixed-methods design, fourteen anonymized student sheets from a design-studio examination at Universidad Técnica Particular de Loja (Ecuador), located in Pucará Park, were assessed with a five-criterion analytic rubric (scored out of 1.00), complemented by content analysis coding nine vegetation functions. The mean score was 0.84 (SD = 0.06), with high internal consistency (Cronbach’s α = 0.93). Achievement differed across criteria (Friedman test, p = 0.014): graphic clarity was highest (87.1%) and the reading of spatial analysis—especially operationalizing choice/betweenness—lowest (82.5%). Spatial-analysis and vegetation-function scores were positively associated (Spearman’s ρ = 0.61). Coupling space syntax with strategic vegetation offers a replicable, evidence-based pedagogical model, while indicating that operationalizing configurational indicators requires more explicit instructional scaffolding. Full article

Genetic cardiomyopathies (GCMs) are chronic heart muscle disorders requiring lifelong monitoring and treatment. Although quality of life (QoL) and health-related quality of life (HRQoL) are increasingly recognized as important outcomes in cardiomyopathy care, their conceptualization and measurement remain inconsistent. This scoping review aims to (a) identify the tools most commonly used to assess QoL and HRQoL in adults with genetic cardiomyopathies and (b) map the thematic areas of existing studies, including symptom burden, psychological distress, diagnostic challenges, and the impact of medical and psychological interventions. PubMed, Scopus, and PsycINFO were systematically searched, and the final search was completed in November 2025. Seventeen peer-reviewed studies met the inclusion criteria and were included in this scoping review. The review followed the PRISMA extension for Scoping Reviews and included both quantitative, qualitative and mixed-methods designs. Most studies employed standardized tools such as EQ-5D (N = 5), SF-36/SF36v2 (N = 5), and the Kansas City Cardiomyopathy Questionnaire (N = 3), while others included the Minnesota Living with Heart Failure Questionnaire (N = 2) and disease-specific or ad hoc measures. The most frequently investigated themes included impairments in physical functioning, emotional well-being, symptom burden, psychological distress, and social participation. Several studies showed that patients’ perceived QoL was more closely associated with symptom burden and psychological adjustment than with objective clinical indicators alone. Clinical interventions showed mixed or limited effects on QoL and HRQoL outcomes, even when clinical parameters improved. Qualitative research further emphasized the lived experiences of patients and families, highlighting unmet needs in care. Less commonly addressed findings concerned caregiver perspectives, patient–provider communication, treatment adherence, socioeconomic disadvantage, healthcare costs, productivity loss, and the experiences of patients with rarer cardiomyopathy-related conditions. The results highlight how QoL and HRQoL are central but still inconsistently assessed outcomes in cardiomyopathy research. This review calls for greater conceptual clarity between QoL and HRQoL, greater standardization in measurement tools, broader inclusion of psychosocial variables, and more patient-centred research approaches to better support individuals living with cardiomyopathies. Full article

Here, we consider a nonlinear hydrodynamic model with mixed dispersion–temporal evolution as the scalar version of the generalized shallow-water wave equation, which specifically provides a comprehensive and versatile framework for studying energy propagation in nonlinear fluids of constrained depth. This equation is acknowledged as an integrable model in the analysis of tidal wave dynamics and in simulations of weather variations, tsunami prediction, and irrigation flows. We also investigate a few of its singular and periodic solitary wave solutions by employing various Riccati-based ansatzes. These results highlight the necessity of studying various nonlinear wave phenomena, which may have potential applications in various domains of physics and applied mathematics. These results extend the variety of its solutions and also enrich the existing knowledge about its solutions with various profiles. To improve visual clarity and to facilitate structural understanding, the solution profiles are represented graphically using Maple software (version 2023.2) in 3D, 2D, and contour plots.We also discuss its invariance under infinitesimal transformations, which yields a one-dimensional Hamilton–Jacobi-like equation. Full article

This study examines farmers’ perceptions of how policy support is associated with ecological agriculture adoption and perceived green development outcomes in Xinjiang under China’s Rural Revitalization Strategy. A sequential explanatory mixed-methods design was used, in which the qualitative phase was deliberately connected to the quantitative phase through a shared sampling frame and a construct-aligned interview guide, and the two strands were integrated using a joint display and meta-inferences. In the quantitative phase, survey data from 300 farmers were analyzed using partial least squares structural equation modelling (PLS-SEM) to test the relationships among perceived policy support, ecological agriculture adoption, and green development. In the qualitative phase, semi-structured interviews with 30 participants drawn from the same respondent pool were thematically analyzed to explain, qualify, and contextualize the statistical relationships. The quantitative findings show a strong positive association between perceived policy support and ecological agriculture adoption (β = 0.659, p < 0.001), a strong positive association between ecological agriculture adoption and green development (β = 0.689, p < 0.001), and a smaller but significant direct association between perceived policy support and green development (β = 0.324, p < 0.001). The indirect effect of perceived policy support on green development through ecological agriculture adoption (β = 0.454) indicates partial mediation. The model explains 43.4% of the variance in ecological agriculture adoption and 47.4% of the variance in green development. The integrated joint display shows that technical training, policy clarity, and extension support helped farmers translate policy support into ecological practices, whereas high initial costs, financing constraints, and market uncertainty limited adoption and created uneven outcomes. The integrated findings suggest that policy effectiveness depends not only on the availability of support instruments but also on farmers’ practical capacity, economic security, and confidence in market returns. The study contributes perception-based mixed-method evidence on the policy–adoption–green development nexus in an ecologically vulnerable agricultural region. Full article