Search Results (509)

This study addresses the ecological impact of the internet’s energy consumption by examining the topic of sustainable web design from a consumer-centric perspective. Sustainable web design, encompassing data volume reduction, website element optimization and compression, and ecological hosting, offers the potential to mitigate ecological footprints while simultaneously improving the technical performance and user experience. A mixed-methods research approach was implemented, combining preliminary expert interviews to establish five foundational attributes used in the second part of the study, a discrete choice experiment. Robustness checks of the results employed a mixed logit estimation and tertiary covariates controlling for different sustainability personality types. Rapid loading times turned out to be particularly decisive in generating a positive brand image and enhancing purchase intentions. In addition, communication measures of sustainable web design practices in the form of sustainability seals, the disclosure of green hosting and the provision of transparent information about sustainability efforts also have a positive impact, enhancing the brand perception, quality assessment and users’ purchase decision. The findings, however, reveal no indication whether inherently visible aspects of websites as compared to implemented communication tools, like seals, labels, or information pages, are more effective measures in general. Full article

Background: Social media, especially Instagram, spreads nutrition-related information that often lacks scientific rigor. Many women report feeling inadequately informed about women’s health by healthcare professionals, turning to social media, increasing exposure to misinformation. Objectives: The NutriWomen platform aims to assess the quality, methodological soundness, and credibility of nutritional health claims and dietary recommendations on Instagram targeting women across different life stages. Its goal is to develop a systematic and scientifically grounded evaluation framework to assess Instagram nutrition-related claims and the methodological quality and interpretability of their supporting evidence, and to translate the results into accessible outputs that help women make informed nutrition decisions across life stages. Methods: This study follows a five-stage design Stage 1 involves a retrospective content analysis of Instagram posts containing nutrition-related claims targeted at women, identified through the “Top posts” function and screened using predefined criteria. Stage 2 assesses information quality using a validated 14-item tool. Stage 3 evaluates the scientific accuracy of claims by formulating PI(E)CO(TS) questions, selecting key outcomes, retrieving evidence from PubMed and the Cochrane Database, and appraising systematic reviews with a modified AMSTAR-2 tool incorporating GRADE ratings, when available. Stage 4 develops the NutriWomen website platform to translate assessments into accessible visual summaries. Stage 5 conducts a mixed-methods study with peri-, meno-, and postmenopausal women to explore information needs and evaluate platform usability through focus groups. Conclusions: The NutriWomen platform will be the first website to systematically publish the results of evaluations assessing the scientific quality of nutritional health claims on Instagram targeted at women across different life stages. It will provide a replicable methodology, and a digital tool designed to empower women with trustworthy nutrition information, with the potential to enhance health literacy and promote better health outcomes. Full article

Background/Objectives: The internet is a major source of health information, including prostate cancer, but the quality of such content is inconsistent and may influence patient decision-making. This study aimed to evaluate the quality of online prostate cancer information by language, location, and user mode (“Logged off” vs. “Anonymous”) using the Google search engine. Methods: We conducted a cross-sectional, observational study between 5 and 11 December 2022, evaluating Google search results for prostate cancer information across three European cities (Basel, Munich, and Paris) and three languages (English, German, and French) in both “Logged off” and “Anonymous” user modes. A total of 900 websites (450 per mode) were retrieved and classified as: (1) university, (2) hospital, (3) governmental/medical societies, (4) industrial/commercial/NGOs, or (5) other. Website quality was assessed using the validated QUEST, which evaluates authorship, attribution, conflicts of interest, currency, and evidence. Inclusion rates and QUEST scores were compared across languages, locations, and categories using Kruskal-Wallis tests with multiple comparison adjustments. A total of 900 websites (450 per mode) were retrieved in English, German, and French from searches conducted in Basel, Munich, and Paris. Websites were classified as: (1) university, (2) hospital, (3) governmental/medical societies, (4) industrial/commercial/NGOs, or (5) other. Quality was assessed using the QUEST, which evaluates authorship, attribution, conflicts of interest, currency, and evidence. Inclusion rates and QUEST scores were compared across languages, locations, and categories using Kruskal-Wallis tests with multiple comparison adjustments. Results: Inclusion rates were high for both modes (Logged off: 86%; Anonymous: 85%). Location-based differences were significant for Basel (p = 0.04) and Paris (p = 0.02), while language-based differences were not significant. In “Logged off” mode, Category 1 achieved the highest median QUEST score (18.3), followed by 3 (17.8), while Category 2 scored lowest (14.2). Differences were significant (χ² = 50, p < 0.001), particularly between Categories 2 vs. 3 and 2 vs. 4 (p < 0.001). Similar patterns were observed in the “Anonymous” mode. Conclusions: Online prostate cancer information varies substantially in quality. French-language sites, despite high inclusion rates, were of lower quality, while English and German content more frequently met high-quality standards. University websites were the most reliable, hospital websites the least. Language, location, and site type influence the accessibility and reliability of online prostate cancer information. Full article

Background: Primary Sclerosing Cholangitis (PSC), Primary Biliary Cholangitis (PBC), and Autoimmune Hepatitis (AIH) are rare immune-mediated liver conditions that significantly affect patients’ quality of life. In Romania, access to specialized information and patient support resources is limited, underscoring the need for tailored educational tools. The aim was to describe the methodology for developing, implementing, and conducting a feasibility study of an online platform for patients with PSC, PBC, and AIH, as a pilot study, providing early insights. Methods: The platform offers educational materials, registration, a discussion forum, and digital tools for quality-of-life assessment. Data on demographics, usage, and quality of life were collected using standardized questionnaires (CLDQ-PSC, PBC-10) and non-standardized questionnaires, and analyzed with Microsoft Office Excel and DATATab. Results: The website was created using an online platform requiring no advanced IT skills. Content was developed in accordance with international guidelines (EASL, AASLD) and translated and adapted for Romanian patients. As of 15 July 2025, 81 patients had been registered (26% PSC, 68% PBC, 6% AIH), with a predominance of urban participants (all patients: 87% female, mean age at diagnosis = 44.5 years). Most participants used mobile devices and reported improved understanding and engagement with their health after using the platform. Conclusions: The first dedicated digital platform has been established in Romania to address the health literacy needs of patients with PSC, PBC, and AIH. The study offers insights into future directions and a replicable model for similar initiatives. The pilot evaluation of the platform faced several limitations, including self-selection bias, non-standardized assessments, and a small sample size. Full article

University website research to date tends to focus on conformity with technical standards. It rarely analyses the systemic nature of digital noise and its cognitive impacts. The study measures the intensity of digital noise on public websites of Polish universities (n = 65) and identifies its most common sources. The author investigates five dimensions: Distraction Intensity, Content Overload, Readability, Visual Balance, and Signal-to-Noise Ratio. The results are aggregated into a synthetic Noise Level Score (NLS) and analysed statistically. Four categories of digital noise have emerged from the observations: obligatory, compensated, ornamental, and habitual. This categorisation indicates that digital noise is not always random. It can be a supervised or even intentionally designed phenomenon when specific elements (such as disclaimers, system alerts, or consent layers) are not only expected but required by the user or the law. The study reveals a highly homogeneous sample and strong convergence of the results, indicating a systemic problem. Over 47% of the websites exhibited high NLS, while only 9% scored low. This means that content, visual, and interaction overloads are not incidental. Instead, it follows from the institutional and technological constraints on Polish higher education. The results ought to be interpreted in the context of the institutional communication imperative, defined as a constant pressure from legal obligations, standards, PR, market, and organisational factors towards constant publishing for multiple audiences through multiple channels. Full article

Virtual museums are increasingly adopted to sustain public engagement with cultural heritage, yet the mechanisms through which virtual exhibition experiences motivate on-site visitation remain underexplored. Drawing on the Stimulus–Organism–Response (SOR) framework and extending the Information Systems Success Model (IS Success Model), this study proposes and tests a psychological pathway linking virtual museum experience quality to offline visiting intention. Using the official website of the Sanxingdui Museum as the empirical context, we surveyed 467 users in China who explored the virtual exhibition but had never visited the museum in person. Virtual exhibition experience quality was operationalised through five dimensions: information quality, system quality, perceived interactivity, perceived authenticity and perceived enjoyment. Perceived cultural value and cultural identity were specified as mediators. Structural equation modelling revealed that higher levels of virtual exhibition experience quality significantly enhanced perceived cultural value and cultural identity. Perceived cultural value, in turn, positively predicted cultural identity, and both constructs were positively associated with intention to visit the physical museum, with a significant sequential mediation from experience quality to offline visiting intention via perceived cultural value and cultural identity. These findings clarify how virtual heritage platforms can foster cognitive appreciation and emotional identification that translate into real-world visitation, offering guidance for designing sustainable digital pathways to long-term engagement with cultural institutions. Full article

Urban Building Energy Modeling (UBEM) plays a critical role in supporting data-driven strategies for the energy transition of cities. However, its application is often hindered by the lack of harmonized, high-quality input data representing the building stock. This paper presents the methodology and outputs of a national research project to construct an Italian library of reference buildings suitable for UBEM applications described with scorecards. The methodological workflow included six key phases: definition of a national data classification framework, acquisition and integration of heterogeneous data sources, data harmonization, statistical analysis and clustering, archetype formalization, and dissemination. The result is a library of 380 scorecards covering residential, educational, office, commercial, and catering buildings across multiple climate zones and construction periods. Each scorecard is based on empirical data from public databases, field surveys, or technical standards, and includes detailed descriptions of geometry, envelope characteristics, HVAC systems, internal gains, and ventilation. The scorecards are shared openly on the project’s website and were built to work with different UBEM platforms. Overall, both the method and the results help bring more consistency to UBEM practice and support better, data-driven urban energy planning. Full article

Artificial intelligence (AI) plays an important role in analyzing air quality, providing new insights that enable informed environmental policy decisions at the local level based on air pollution modeling and forecasting. The aim of this study is to analyze various hybrid AI methods to predict, model, and anticipate hourly ground-level ozone concentrations. Ground-level ozone concentrations impact human health and the environment. The data used in this study was downloaded from the website of the Romanian Agency for Environmental Protection and spans five years (2020–2024). The dataset comprises two categories of data: (i) seven meteorological parameters, including temperature (T), relative humidity, precipitation, air pressure, solar brightness, wind direction, and velocity; (ii) twenty air pollutants, including two types of particulate matter, carbon monoxide, sulfur dioxide, ground-level ozone, three types of nitrogen oxide, ammonia, six volatile organic compounds, and five toxic elements. The study follows a six-stage approach: (1) data preprocessing is conducted to identify and address anomalies, outliers, and missing values, while ozone trends are analyzed; (2) correlations between ozone concentrations and other variables are examined, considering only non-missing values; (3) data splitting is carried out in training and testing sets; (4) a total of 27 hybrid AI-based algorithms are applied to determine the optimal predictive model for ozone concentration based on related variables; (5) fifty feature selection methods are applied to find the most relevant predictors for predicting ozone concentration; (6) a novel deep NARMAX model is employed to model and anticipate hourly ozone levels in Craiova. Using a set of statistical metrics, the results of the models are assessed. This research provides a novel perspective on the robustness of the predictive performance of the proposed model. Full article

This study proposed a methodology for obtaining a valid database of food retail establishments and characterized the community food environment, understood as the distribution and type of food outlets, in a Brazilian medium-sized municipality after the collapse of a mining tailings dam. An ecological study was conducted with establishments selling food for home consumption (butcher shops, fish markets; fruit and vegetable specialty markets; large- and small-chain supermarkets; bakeries and local markets) and immediate consumption (bars, snack bars, and restaurants). For home-consumption establishments, data were requested from governments and completed with website/app searches, virtual audits (Google Street View), and on-site audits. For immediate-consumption establishments, only on-site audit was used due to the low quality of the secondary databases. Agreement between databases was assessed with the Kappa statistic. Density (d) was calculated by the area (in km²) of the sampling stratum. Public databases presented low validity (23.0%; Kappa −0.388; p = 1.000), even after virtual auditing (31.4%; Kappa 0.37; p < 0.001). 96 establishments for home consumption and 261 for immediate consumption were identified, with predominance of local markets (35.4%), bars (35.2%), and snack bars (29.1%). The region with the highest density of establishments was the “Other Areas” stratum (d = 4.7 for home-consumption establishments and d = 13.2 for immediate-consumption establishments). Audit proved most effective, especially for small establishments. The lack of governmental databases and the identified food environment should inform municipal policies to promote food and nutrition security and reduce inequalities after the disaster. Full article

Background: Hidradenitis suppurativa (HS) is a chronic inflammatory disorder characterized by recurrent nodules, abscesses, and sinus tracts in apocrine gland-bearing areas. Surgery plays a key role in moderate-to-severe disease. As patients increasingly rely on the internet for decision-making, the quality of online information on HS surgery requires critical evaluation. Previous studies have shown poor quality and limited coverage of surgical aspects. This study systematically assesses publicly available websites on the surgical and reconstructive management of HS, quantifies their quality using the modified Ensuring Quality Information for Patients (mEQIP) tool, and identifies areas needing improvement to support informed decisions. Methods: Google, Bing, and Yahoo were searched using five HS surgery-related keywords. The first 50 results per keyword and engine were collected (n = 750), and 214 websites met the inclusion criteria. Sites were categorized by provenance (practitioners, hospitals, healthcare portals, professional societies, encyclopedias) and assessed using the 36-item mEQIP checklist. High quality was defined as ≥23/36 (75th percentile). Comparisons were made by publication era (pre-/post-COVID-19) and source type. Results: The mean mEQIP score was 21.7; only 51 websites (23.8%) met the high-quality threshold. No significant difference emerged between pre- and post-COVID publications. Healthcare portals scored highest (22.8), followed by practitioners (21.5) and hospital sites (21.2); professional societies (19.7) and encyclopedias (17.3) performed worst. Major deficiencies included limited discussion of surgical risks, quality-of-life outcomes, and postoperative care. Conclusions: Online resources on HS surgery are frequently incomplete and omit essential details on risks, recurrence, and reconstructive options. Surgeons should direct patients toward vetted sources, and professional societies should develop accessible, evidence-based patient guidelines. Full article

The tourism industry is currently experiencing a substantial digital transformation, with Online Travel Agencies (OTAs) committed to integrating innovations such as artificial intelligence (AI) in order to enhance service delivery and personalize user experiences. This study investigates the relationship between the utilization of AI and the technical quality scores of tourism websites, aiming to identify significant associations and variances in the critical conversion phase. An exploratory research design is employed to evaluate the technical quality of three prominent international tourism websites, i.e., Booking.com, Airbnb.com, and Tripadvisor.com. The investigation uses Google Lighthouse, with Performance, Accessibility, Best Practices, and Search Engine Optimization (SEO) as variables analyzed across both desktop and mobile versions, as well as on pages with and without AI functionality. Data analysis is performed using JASP (version 0.19.3), including linear regression analysis to quantify the predictive relationship. The analysis confirms that the Performance variable is the most sensitive to the influence of AI. AI integration demonstrates a significant positive influence on the Performance score of travel websites. The regression model indicates that AI usage explains 78.9% of the variation in the Performance score (${\mathrm{R}}^2$ = 0.789, p < 0.001), indicating a substantial correlation with technical sustainability. Nevertheless, there remains an ongoing necessity for optimization, particularly with regard to the enhancement of overall performance and improvement of scores for mobile devices. The study acknowledges certain limitations related to the sample size of AI applications and the accessibility of specific AI versions in particular geographic regions. Full article

This study examines how El Sistema, a global social music education program active in over 60 countries, contributes to the United Nations Sustainable Development Goals (SDGs). The program is analyzed using Sheerens’ CIPO (Context–Input–Process–Output) framework, which enables comprehensive evaluation of education from design and implementation to outcomes beyond simple result-focused assessment. The framework also accounts for political, social, and economic contexts, making it effective for understanding country-specific cases. Using this approach, this study analyzed how El Sistema has been localized across five representative case countries—Scotland, the United States, Sweden, Republic of Korea, and Japan. Data were collected through a narrative review integrating academic studies and credible non-academic sources, including government and organizational reports, program brochures, official websites, news articles, and multimedia materials. Findings indicate alignment with SDGs 1, 3, 4, 5, 8, 10, 11, 16, and 17. Country-specific strategies include community engagement in Scotland (SDG 17), partnerships in the United States (SDG 17), immigrant integration in Sweden (SDGs 11, 16), inclusive music education and cultural revitalization in the Republic of Korea (SDGs 11, 16, 17), and quality and healing education for disaster-affected and disabled children in Japan (SDG 11). These results suggest that El Sistema can serve as a sustainable model of social music education when supported by localized strategies, stable resources, multi-level governance, systematic evaluation, and proactive engagement with environmental initiatives. Full article

Background: The vast majority of patients, considering information for allergic conditions, use the Internet as a source of health information. The aim of our study is to assess the quality of patient information on allergic rhinitis available on the internet. Methods: Three hundred Websites, found through the most recognizable search engines, were evaluated using the modified Ensuring Quality Information for Patients (EQIP) instrument. Results: Eighty-five websites were assessed after the exclusion of duplicates and Websites in languages other than English. Websites that scored higher than 21 (over the 75th percentile) were categorized as high-score sites. Websites that were developed by health professionals tended to have a higher score. The EQIP score of the websites ranged between 5 and 26 out of the total of 34 points, with a median value of 16.5 points. Conclusions: The quality of patient information on allergic rhinitis on the Internet is inferior, and the existing Websites present insufficient information. Full article

Purpose: The objective of this research was to assess the quality, substance, and ease of reading of online information regarding the use of 3D printing in dental practices. Materials and Methods: The search term selected was ‘3D printing in dentistry’. The first 100 websites retrieved through the Google Search Engine based on this search term were reviewed. Duplicate websites, scientific articles, social media links, videos, advertisements, and broken links were excluded from our study. The quality of the websites analyzed in this study was assessed using the DISCERN tool and JAMA benchmarks, while their readability was measured using the Flesch Reading Ease Score (FRES) and the Flesch-Kincaid Grade Level (FKGL). A significance level of p < 0.05 was established for the analysis. Results: The 75 websites reviewed were categorized into two groups: blogs and commercial sites. It was determined that commercial sites (N: 42) were the majority compared to blog websites (N: 33). Blog websites scored higher than commercial sites in the total DISCERN, DISCERN 1, and Q16 scores. In the JAMA criteria, the minimum sources criterion (n = 12) and the maximum authorship criterion (n = 71) were met. There was no statistically significant difference between the groups in terms of FRES and FKGL scores (p > 0.05). Conclusions: The quality of online information sources regarding ‘3D printers in dentistry’ worldwide is considered to be at a moderate level. The readability of the data is at a low level. There is a need for higher quality and highly readable websites about ‘3D printing in dentistry’. Full article

Website performance directly impacts user experience, trust, and competitiveness. While numerous studies have proposed evaluation methods, there is still no comprehensive synthesis that integrates performance metrics with predictive models. This study conducts a systematic literature review (SLR) following the PRISMA framework across seven academic databases (2010–2024). From 6657 initial records, 30 high-quality studies were included after rigorous screening and quality assessment. In addition, 59 website performance metrics were identified and validated through an expert survey, resulting in 16 core indicators. The review highlights a dominant reliance on traditional evaluation metrics (e.g., Load Time, Page Size, Response Time) and reveals limited adoption of machine learning and deep learning approaches. Most existing studies focus on e-government and educational websites, with little attention to e-commerce, healthcare, and industry domains. Furthermore, the geographic distribution of research remains uneven, with a concentration in Asia and limited contributions from North America and Africa. This study contributes by (i) consolidating and validating a set of 16 critical performance metrics, (ii) critically analyzing current methodologies, and (iii) identifying gaps in domain coverage and intelligent prediction models. Future research should prioritize cross-domain benchmarks, integrate machine learning for scalable predictions, and address the lack of standardized evaluation protocols. Full article