Search Results (3,021)

Background/Objectives: The clinical decision between preserving periodontally compromised teeth and replacing them with dental implants represents a complex clinical dilemma influenced by biological, prosthetic, economic, and professional factors. The aim of this pilot study was to develop and preliminarily validate a questionnaire designed to assess dentists’ attitudes and therapeutic preferences regarding the use of periodontally compromised teeth as prosthetic abutments versus extraction and implant-supported rehabilitation. Methods: An observational cross-sectional study was conducted, among Romanian dentists, using a structured self-administered questionnaire consisting of 43 items organized into seven sections addressing clinical attitudes, decision-making factors, professional competence, prosthetic treatment preferences, and implant-related clinical practices. A total of 111 Romanian dentists completed the questionnaire. Responses were recorded using a five-point Likert scale. Statistical analysis was performed using IBM SPSS Statistics software. Internal consistency was evaluated using Cronbach’s alpha coefficient and intraclass correlation coefficient (ICC). Construct validity was assessed using exploratory factor analysis based on Principal Component Analysis with Varimax rotation. Results: The questionnaire demonstrated good internal consistency across most sections, with Cronbach’s alpha values ranging between 0.795 and 0.859 after scale optimization. Item–total correlations indicated adequate contribution of individual items to overall scale reliability. Intraclass correlation coefficients confirmed moderate reliability for individual items and good reliability for average section scores. Exploratory factor analysis showed satisfactory sampling adequacy (KMO = 0.709) and statistically significant Bartlett’s test of sphericity (p < 0.001), supporting the suitability of the data for factor analysis. The sample population was predominantly composed of early-career dentists with limited clinical experience, which should be considered when interpreting the findings. Conclusions: The developed questionnaire demonstrated satisfactory psychometric properties, including good internal consistency and acceptable construct validity, supporting its use as a research instrument for assessing Romanian dentists’ self-reported attitudes, therapeutic preferences, and perception-based decision patterns regarding the preservation of periodontally compromised teeth and implant-supported prosthetic rehabilitation. Full article

Industrial chains in agriculture are currently fragmented and do not support developing resource-based competitive advantages. This is true under the Big Food Framework’s strategic orientation. This research seeks to develop a new analytical framework for evaluating pathways to the integration of agricultural industrial chains and their impact on the performance of companies engaged in food processing in Xinjiang. A mixed-method approach, employing both an exploratory and sequential design, will be used to do this. The primary method of data collection for this study is the case study method, along with the questionnaire method involving 145 agricultural enterprises. From these data, structural equation modeling (SEM) will be used to test the paths of causation among cognitive managers of firms who have implemented the BFF. Evidence will be presented to demonstrate the relationship among three types of integration (vertical, horizontal, and lateral) in the agricultural industrial chain, dynamic capabilities, and company performance. Additionally, network topology and optimization simulations will be conducted to determine how effectively structures are organized in training the respective companies. Important findings revealed in this research include the following: The managerial cognition constructs offered by BFFs play a key role in enhancing the depth and structural balance of industry chain integration. There were complementary performance effects found, and they are related to vertical integration achieving operational efficiency and financial efficiency; horizontal integration improving market competitiveness and brand competitiveness; and lateral integration facilitating innovative growth. Dynamic capabilities are a significant mediating mechanism linking institutional support and digital capability with the depth of integration across different modes of integration. The findings from network optimization suggest that there is a positive effect of balanced connectivity across the different dimensions of integration on overall system efficiency and reduced structural inefficiencies. Based on these findings, the authors recommend that organizations establish governance mechanisms that facilitate coordinated connectivity; strengthen adaptive capabilities within the firm; and promote balanced integration across industrial networks. Future researchers should consider applying these findings to conducting longitudinal studies on network evolution; integrating sustainability measures as part of their analysis; and conducting comparative validation studies across regions or industry systems. Full article

The transformation of university libraries into learning commons has highlighted the importance of informal learning spaces (ILSs). However, the mechanisms through which spatial elements influence learning experiences remain underexplored, particularly in western China. Drawing on person-environment fit theory and a multi-coupling framework, this study develops a four-dimensional analytical model comprising spatial layout, facility configuration, environmental quality, and cultural perception. A mixed-methods approach was employed, including 532 valid questionnaires, behavioral observations, and comprehensive environmental measurements (illuminance, noise, CO₂, PM2.5, TVOC, thermal conditions) across three university libraries in Lanzhou, China. Structural equation modeling (SEM) and coupling coordination degree modeling were used for analysis. Spatial layout (β = 0.324, p < 0.001), facility configuration (β = 0.287, p < 0.001), environmental quality (β = 0.196, p < 0.01), and cultural perception (β = 0.158, p < 0.05) all significantly predicted learning satisfaction, jointly explaining 67.3% of the variance. Learning satisfaction partially mediated the relationship between spatial elements and learning outcomes (indirect effect 31.2%). Coupling coordination degrees ranged from 0.578 to 0.634, revealing a “high coupling, low coordination” pattern, with cultural perception as the common shortfall. Environmental measurements showed CO₂ concentrations ranging from 823 to 946 ppm in quiet zones and up to 1085 ppm in lounge areas, correlating negatively with satisfaction (r = –0.41, p < 0.05). Spatial elements influence learning outcomes primarily through satisfaction enhancement. An integrated optimization framework is proposed, offering actionable strategies for ILS design in similar contexts. Full article

Background/Objectives: The multiple benefits of physical activity and exercise (PAE) for non-communicable diseases (NCDs) and, thus, for public health underscore the importance of their multidisciplinary implementation in clinical practice. However, there is a lack of validated instruments that comprehensively assess physicians’ knowledge, attitudes, intentions, abilities, and behaviour (KAIAB) regarding PAE promotion in NCD management. Methods: This study aimed to develop and validate a new questionnaire to assess physicians’ KAIAB towards PAE and to evaluate their KAIAB levels. A two-stage design, including an e-Delphi method and a cross-sectional study, was conducted in Greece from January 2022 to May 2022. Results: In the first stage, after achieving consensus and stability within a purposive sample of 16 physician–experts (response rate 100%), the questionnaire was effectively developed and validated (Content Validity Ratio: 0.5–1) using a two-round e-Delphi method. In the second stage, a cross-sectional study was conducted in two physician populations from 12 medical specialities (response rate: 18.2%) and demonstrated that the new questionnaire had sufficient face validity and high reliability (Cronbach’s alpha: 0.805– 0.931). The three original Bloom levels’ cut-off points were also used to classify physicians’ KAIAB levels in the second stage. KAIAB levels were assessed using median and interquartile range (Mdn/IQR) and were found to be low (13/6), moderate (128/79), high (35/9), moderate (21/8), and moderate (33/8), respectively. Conclusions: The new questionnaire is reliable and valid. It is recommended that the questionnaire be applied in larger studies to further verify its validity and applicability. Additionally, it was found that although physicians reported high intentions and moderately positive attitudes toward PAE promotion, their knowledge in these domains and their exercise prescription practices remained limited. This underscores the need to enhance policies and initiatives in medical education and the healthcare system. Full article

This study aims to identify the factors causing employer-induced disruption in construction projects and to examine why contractors do not file claims despite frequently encountering such losses. It also aims to develop a scale with tested reliability and validity to measure the causes of employer-induced disruption. Data for the study were collected through a structured questionnaire administered to architects and civil engineers working on the contractor side in projects conducted under the Public Procurement Law No. 4734. The data obtained in the study were analyzed using SPSS 27.0 and AMOS 24 software. The scale development process included exploratory and confirmatory factor analyses using separate samples following the reliability and validity assessments. The findings indicate that the proposed scale possesses a valid and reliable single-factor structure. Additionally, the results reveal that the most significant reasons for not filing a claim are: the lack of qualified technical staff required for record-keeping, the absence of a clause in the contract regarding disruption, and concerns about the potential deterioration of future employment relations with the employer. This study contributes to the literature by providing a validated measurement tool for assessing employer-related disruptions. It also offers recommendations for improving contract management, the documentation process, and awareness of issues among technical staff. Full article

This paper presents a dataset collected through a visitor questionnaire survey conducted at the Archaeological Site of Ancient Dodona, Greece, a large-scale, spatially complex open-air archaeological site. The dataset documents visitors’ experiences, perceptions, and information needs, as well as their attitudes toward the use of digital technologies for heritage interpretation and engagement. The questionnaire was administered in printed form to adult visitors at the entrance and exit of the archaeological site. A total of 99 valid responses were collected. The dataset includes information on visitor demographics, visit characteristics, perceptions of existing interpretive material, spatial behavior within the site, and attitudes toward digital applications such as augmented reality, digital storytelling, and interactive tools. All data are fully anonymized and contain no personally identifiable or sensitive information. The dataset supports research in the fields of visitor studies, cultural heritage interpretation, digital heritage, and cultural tourism, and may be reused for comparative studies or for the design and evaluation of digital mediation applications in archaeological contexts. The dataset enables cross-tabulation analyses exploring associations between visitor characteristics and attitudes toward digital mediation, thereby supporting visitor segmentation and the evidence-based development of digital interpretation strategies in archaeological contexts. Full article

This study validates Danielson Framework for Teaching (DFfT) instruments’ structure, dependability, and contextual appropriateness within the multicultural, standards-driven education system of the United Arab Emirates (UAE) in accordance with Vision 2021 and national teacher competency frameworks. Quantitative data were collected from 629 UAE schoolteachers through administering a questionnaire-based survey. Principal Component Analysis and Confirmatory Factor Analysis yielded discriminant, convergent, and construct validity in addition to internal consistency using the Composite Reliability Index and Average Variance Extracted for all scales. Four DFfT domains were shown to have a stable structure based on Principal Component Analysis results: planning and preparation (six factors, α = 0.92–0.99), learning environment (five factors, α = 0.98–0.99), learning experiences (five factors, α = 0.96–0.99), and principled teaching (six factors, α = 0.69–0.99). Notably, all constructs had excellent model fit with substantial factor loadings and inter-item as confirmed by the results of the Confirmatory Factor Analysis. With the exception of one minor subscale (α = 0.69), all dependability coefficients exceeded recommended benchmarks. The first-order full DFfT structural model of the four main domains validation demonstrated a reliable framework (CFI = 0.917, TLI = 0.902, IFI = 0.919, χ²/df = 1.635, and RMSEA = 0.078) for professional development, instructional improvement, and policy alignment with potential relevance beyond the UAE context, as well as psychometric soundness and contextual adaptability for teachers’ professional growth and evaluation in UAE schools. The study’s findings are significant, as they are the first to empirically validate the psychometric properties of the Danielson framework of teaching instruments in the UAE. Full article

Background/Objectives: This study aimed to investigate the impact of allergic diseases (AD) or obstructive sleep apnea (OSA) risk, as a host factor, on the development of severe Mycoplasma pneumoniae Pneumonia (SMPP) in children by analyzing the clinical data of pediatric patients with Mycoplasma pneumoniae Pneumonia (MPP). Methods: This retrospective study enrolled children hospitalized with Mycoplasma pneumoniae pneumonia (MPP) at Shanghai Ninth People’s Hospital from November 2024 to November 2025. Patients were classified into severe (SMPP) and mild (MMPP) groups. Demographic, clinical, laboratory, and questionnaire data were collected and compared between groups. Univariate and multivariate logistic regression analyses were performed to identify independent predictors of SMPP and construct a nomogram. The model was validated for discrimination, calibration, and clinical utility using ROC curves, calibration plots, and decision curve analysis, with internal validation by bootstrap resampling. Results: Among the 150 enrolled children with MPP, 35 (23.3%) were classified as severe (SMPP) and 115 (76.7%) as mild (MMPP). Patients with SMPP exhibited significantly higher frequencies of allergic diseases, prolonged fever and steroid use, elevated inflammatory markers (CRP, LDH, D-dimer, ferritin, ALT), and higher PSQ and RQLQ scores (all p < 0.05). Disease severity was positively correlated with these clinical, laboratory, and questionnaire-based parameters. Multivariate logistic regression identified allergic diseases, PSQ score, LDH, and ferritin as independent predictors of SMPP. A nomogram incorporating these four factors demonstrated good predictive performance, with an internally validated C-index of 0.827, satisfactory calibration (Hosmer–Lemeshow p = 0.116), and clinical utility within a 0–25% threshold probability range on decision curve analysis. Conclusions: Children with MPP and comorbid AD or OSA risk are more likely to develop SMPP. Among children aged 6–12 years, RQLQ score is positively correlated with the severity of MPP. AD, PSQ score, LDH, and ferritin are independent risk factors for SMPP. Clinicians should be alert to the development of SMPP when children with MPP present with a history of AD, PSQ score >3.5, LDH >327.50 U/L, or ferritin >120.05 ng/mL. The visual nomogram model constructed by combining these risk factors demonstrates improved predictive performance for SMPP, with high predictive efficacy and accuracy. It has great clinical value and can be used for individualized risk assessment and early intervention. However, our proposed nomogram requires external validation prior to broader implementation. Full article

Pediatric pain remains a highly prevalent and under-addressed health problem worldwide, largely due to educational gaps, limited humanization of care, and insufficient integration of digital and pedagogical innovations in higher education, and the purpose of this study is to describe and implement an international, higher education–driven model to improve training in humanized pediatric pain management. This multicenter mixed-methods study involves 15 universities from Europe, Africa, and Latin America and includes the development and cross-cultural validation of the HUPEDCARE-Q questionnaire to identify knowledge gaps, the design of an open-access, multilingual digital learning platform (PEDCARE) that integrates learning management and social networking functions, and the implementation of capacity-building workshops based on a training-the-trainers model for students, educators, health professionals, and families. The expected outcomes of the project include the establishment of a standardized instrument for assessing educational needs, the creation of a scalable digital educational environment, and the feasibility of international academic collaboration to strengthen competencies in pediatric pain care. The study suggests that higher education, combined with digital transformation and culturally sensitive approaches, may support the humanization of pediatric pain management and address educational and health inequities, although further research is needed to confirm these potential impacts. Full article

Building Information Modelling (BIM) has emerged as a transformative approach for improving efficiency, coordination, and sustainability in the construction industry; however, its adoption in developing regions remains limited. In the Kurdistan Region of Iraq (KRG), BIM implementation—particularly within the residential construction sector—remains at an early stage and lacks comprehensive empirical investigation. This study aims to assess stakeholders’ perspectives on current BIM practices, identify key adoption barriers, and develop a context-specific strategic framework to support BIM implementation. A mixed-method research design was employed, incorporating literature review, expert validation through semi-structured interviews, and a structured questionnaire survey. A total of 319 valid responses were analyzed using descriptive statistics, Relative Importance Index (RII), Cronbach’s alpha for reliability, Spearman’s rank correlation, independent samples t-tests, and one-way ANOVA. In addition to ranking barriers, an inter-barrier correlation analysis was conducted to examine the relationships, clustering patterns, and hierarchical structure of BIM adoption challenges. The results indicate that while BIM awareness is moderately established among stakeholders, its practical application remains limited, particularly beyond the design phase. The most critical barriers include lack of training and expertise, absence of regulatory frameworks and standards, insufficient government support, and financial constraints. The correlation analysis reveals that these barriers are interdependent, with policy and institutional deficiencies acting as root drivers influencing technical, financial, and awareness-related challenges. Based on these findings, the study proposes a four pillar conceptual strategic framework encompassing human capital development, regulatory and standardization enablement, awareness and demand generation, and organizational and collaborative enhancement. The framework is explicitly derived from empirical results, linking barrier clusters to prioritized strategies, thereby enhancing its practical applicability. This study contributes to the existing literature by providing one of the first multi-province empirical assessments of BIM adoption in the KRG residential sector, integrating statistical validation with strategic development, and offering transferable insights for other developing regions at a similar stage of BIM adoption. Full article

Background: Quality-of-life (QoL) assessment has become an essential component of outcome evaluation in oral and maxillofacial surgery (OMFS), particularly in interventions with functional implications for breathing, sleep, and oro-facial performance. Existing instruments often lack specificity for the postoperative OMFS population. This study aimed to develop and psychometrically validate the OMFS-QoL-18 questionnaire, a condition-oriented patient-reported outcome measure designed for postoperative assessment. Methods: A cross-sectional validation study was conducted on 226 adult patients evaluated 6–12 months after orthognathic or function-oriented OMFS procedures. Internal consistency was assessed using Cronbach’s alpha, and reproducibility using the intraclass correlation coefficient (ICC) based on a two-way random-effects model with absolute agreement. The internal structure of the instrument was explored through an exploratory dimensionality analysis using Principal Component Analysis (PCA), including Kaiser–Meyer–Olkin (KMO) testing and Bartlett’s test of sphericity. Descriptive statistics were calculated for item and domain scores. Results: The OMFS-QoL-18 demonstrated good internal consistency (Cronbach’s α = 0.789; standardized α = 0.783) and satisfactory reproducibility (ICC = 0.81; 95% CI: 0.74–0.87). The exploratory dimensionality analysis suggested a multidimensional structure, with five components explaining 67.1% of the total variance. Item clustering was broadly consistent with the predefined conceptual domains, including respiratory comfort, sleep quality, daytime function, oro-maxillofacial function, and global satisfaction. Given the use of PCA as a component-based method, these findings are interpreted as preliminary evidence of dimensional organization rather than confirmation of latent constructs. Conclusions: The OMFS-QoL-18 demonstrated good internal consistency and preliminary evidence of a coherent factor structure. These findings support its use as a promising condition-specific instrument, pending further validation studies. Further multicenter and longitudinal validation studies are warranted to confirm structural stability and responsiveness over time. Full article

Despite growing recognition of blockchain technology’s potential to enhance traceability, verifiability, and integrity in financial reporting, empirical evidence from regulated banking environments in developing economies remains scarce. This study investigates whether blockchain adoption is positively associated with transparency and accounting disclosure in digital financial reports among Jordanian listed banks. A structured questionnaire was distributed to managers, financial managers, and accountants across 15 banks listed on the Amman Stock Exchange, yielding 312 valid responses. Partial Least Squares Structural Equation Modeling (PLS-SEM) with 5000 bootstrap subsamples was employed for data analysis. The results show that blockchain adoption is positively and significantly associated with transparency (β = 0.361, p < 0.001) and accounting disclosure (β = 0.437, p < 0.001), explaining 13.0% and 19.1% of the variance, respectively. These findings suggest that blockchain-enabled systems are perceived by banking professionals as contributing to greater reporting credibility. By providing empirical evidence from a developing economy banking sector, this study indicates that blockchain adoption may serve as a governance-supporting mechanism associated with improved perceived transparency and disclosure quality. Full article

This study explored how smart governance can foster city demographic sustainability by shaping youth retention intention in developed cities. In the case of Busan, South Korea, a structural model was constructed and tested to link the dimensions of perceived value of smart governance (PV)—including Accessibility and Efficiency of Public Services (PV-A), Transparency and Information Accessibility of Governance (PV-T), Participation and Responsiveness (PV-P), Career Development and Innovation Support (PV-C), and Contribution to Urban Quality of Life (PV-Q)—with perceived demographic sustainability (PDS) and youth retention intention (YRI). On the basis of 939 valid questionnaires, confirmatory factor analysis and a structural equation model were used to test the measurement validity, model fitting, and mediating effects. Consequently, all the dimensions of smart governance had a positive effect on youth retention intention (YRI), with all path coefficients statistically significant at p < 0.001, and perceived demographic sustainability (PDS) partially mediated the effects of each dimension on youth retention intention (YRI), with indirect effects significant at p < 0.05. Among the dimensions, PV-T had the strongest effect, with a standardized coefficient of β = 0.283 at p < 0.001, followed by PV-P (β = 0.185, p < 0.001) and PV-Q (β = 0.167, p < 0.001), while PV-A and PV-C showed comparatively weaker but still statistically significant effects. In view of governance orientation and cognitive mechanism, this study provides empirical support for demographic sustainability design in smart cities. Full article

Background: To explore the correlation between spatial dose distribution and post-implant urinary toxicity, aiming to assist decision making in low-dose-rate (LDR) treatment planning, thereby improving patient outcomes. Methods: Eighty-five prostate LDR patients with >12-month follow-up were included. Patient-reported urinary toxicity was collected prospectively using the International Prostate Symptom Score (IPSS) questionnaire, from before implant (baseline) to post-implant follow-up. Patients were then grouped into those whose symptom scores returned to ≤2 points above baseline by 12 months (no long-term toxicity) vs. those who did not (long-term toxicity). A total of 106 features were extracted for each patient, including principal components of dose-volume histograms (DVHs) from multiple prostate subzones, the whole prostate and urethra, along with baseline IPSS, implantation characteristics, and additional DVH indicators for the prostate and the urethra. A machine learning (ML) model incorporating backward feature selection algorithm was developed to predict long-term toxicity status, using a shuffle-and-split validation strategy for model evaluation during feature selection. A univariate statistical analysis was conducted on the model’s selected features. Results: Out of 85 patients, 41 (48%) had long-term urinary toxicity. Seven features were selected during model training, including baseline IPSS and six dosimetric features from several prostate subzones primarily located in the posterior prostate. The model achieved a high mean area under the receiver operating characteristic curve (AUC) of 0.81, with a balanced sensitivity and specificity of 0.78 by adjusting the probability threshold. In univariate analysis, only baseline IPSS and one selected dose feature were significantly correlated with long-term toxicity with AUC < 0.71. Conclusions: The proposed ML model, integrating baseline IPSS and spatial dosimetric features, effectively predicts long-term urinary toxicity after prostate LDR. This approach offers a practical method for risk stratification, allowing clinicians to identify patients at elevated risk and prioritize them for targeted preventative measures and closer follow-up. Full article

In the context of the aesthetic economy and the rapid development of digital intelligence, product design is increasingly required to address not only functional performance but also users’ emotional needs. However, due to the ambiguity and subjectivity of perceptual requirements, it remains difficult to accurately translate user emotions into specific design solutions. To address this challenge, this study proposes an integrated Kansei Engineering–machine learning framework for optimizing product design. First, user perceptual data are collected through questionnaires and interviews, and key perceptual imagery words are extracted using the Latent Dirichlet Allocation (LDA) model and factor analysis. Then, product design elements are systematically decomposed, and their relative importance is determined using the fuzzy analytic hierarchy process (FAHP). Based on this, a mapping relationship between perceptual imagery and design elements is established. Subsequently, the XGBoost model is employed to predict and optimize design element combinations. The optimized design schemes are further generated using AIGC technology and validated through eye-tracking experiments and subjective evaluations.The results show that the proposed method achieves high predictive accuracy (R² = 0.87) and significantly improves the emotional expression of product design. This study contributes to the integration of Kansei Engineering and machine learning by providing a data-driven approach for emotional design optimization, offering theoretical, practical, and strategic guidance for intelligent product design in industrial contexts. Full article