Search Results (665)

This study explores whether sustainability achievements—proxied through ESG (environmental, social, and governance) reporting—are associated with superior financial performance in Latvia’s manufacturing sector, where ESG maturity remains low and institutional readiness is still emerging. Building on stakeholder, legitimacy, signal, slack resources, and agency theories, this study applies a mixed-method approach (that consists of two analytical stages) suited to the limited availability and reliability of ESG-related data in the Latvian manufacturing sector. Financial indicators from three large firms—AS MADARA COSMETICS, AS Latvijas Finieris, and AS Valmiera Glass Grupa—are compared with industry averages over the 2019–2023 period using independent sample T-tests. ESG integration is evaluated through a six-stage conceptual schema ranging from symbolic compliance to performance-driven sustainability. The results show that AS MADARA COSMETICS, which demonstrates advanced ESG integration aligned with international standards, significantly outperforms its industry in all profitability metrics. In contrast, the other two companies remain at earlier ESG maturity stages and show weaker financial performance, with sustainability disclosures limited to general statements and outdated indicators. These findings support the synergy hypothesis in contexts where sustainability is internalized and operationalized, while also highlighting structural constraints—such as resource scarcity and fragmented data—that may limit ESG-financial alignment in post-transition economies. This study offers practical guidance for firms seeking competitive advantage through strategic ESG integration and recommends policy actions to enhance ESG transparency and performance in Latvia, including performance-based reporting mandates, ESG data infrastructure, and regulatory alignment with EU directives. These insights contribute to the growing empirical literature on ESG effectiveness under constrained institutional and economic conditions. Full article

Today, ‘social sustainability’ is a key feature of many organisations’ environmental, social, and governance strategies, as well as underpinning sustainable development goals. The term refers to the implementation of targets such as reduced societal inequalities, the promotion of social well-being, and the practice of positive community relations. Building a meaningful, accountable, and quantifiable evidence-base from which to translate these high-level concepts into tangible and achievable goals is, however, challenging. The complexities of measuring social capital—often described as a building block of social sustainability—have been documented. The challenge lies in measuring the person, group, or collective in interaction with the context under investigation, whether that be a climate goal, an institution, or a national policy. Social identity theory is a social psychological approach that articulates the processes through which an individual internalises the values, norms, and behaviours of their contexts. Levels of social identification—a concept capturing the state of internalisation—have been shown to be predictive of outcomes as diverse as communication and cognition, trust and citizenship, leadership and compliance, and health and well-being. Applying this perspective to the articulation and measurement of social sustainability provides an opportunity to build an empirical approach with which to reliably translate this high-level concept into achievable outcomes. Full article

Background: Pain is a problem faced by critically ill surgical patients and has a major impact on their outcomes. Pain assessment is therefore essential for effective pain management, with a combination of pharmacological and non-pharmacological treatment. Clinical supervision, supported by models such as SafeCare, can improve professional development, safety and the quality of care in intensive care units. Objectives: This study aimed to: (1) assess current pain assessment practices in a polyvalent Intensive Care Unit (ICU) in the Porto district; (2) identify nurses’ training needs regarding the Clinical Supervision-Sensitive Indicator—Pain; and (3) evaluate the impact of clinical supervision sessions on pain assessment practices. Methods: A quantitative, quasi-experimental, cross-sectional study with a pre- and post-intervention design was conducted. Based on the SafeCare model, it included a situational diagnosis, 6 clinical supervision sessions (February 2023), and outcome evaluation via nursing record audits (November 2022 and May 2023) in 31 total critical ill patients. Pain was assessed using standardised tools, in line with institutional protocols. Data was analysed using Software Statistical Package for the Social Sciences v25.0. Results: Pain was highly prevalent in the first 24 h, decreasing during hospitalisation. Generalised acute abdominal pain predominated, with mild to moderate intensity, and was exacerbated by wound care and mobilisation/positioning. Pain management combined pharmacological and non-pharmacological treatment. There was an improvement in all the parameters of the pain indicator post-intervention. Conclusions: Despite routine assessments, gaps remained in reassessing pain post-analgesia and during invasive procedures. Targeted clinical supervision and ongoing training proved effective in improving compliance with protocols and supporting safer, more consistent pain management. Full article

This study examines how Environmental, Social, and Governance (ESG) reporting is communicated and perceived on YouTube. A dataset of 553 relevant videos and 5060 user comments was extracted on 2 April 2025 ranging between 2014 and 2025, and sentiment, topic, and stance analyses were applied to both transcripts and comments. The majority of video content strongly endorsed ESG reporting, emphasizing themes such as transparency, regulatory compliance, and financial performance. In contrast, viewer comments revealed diverse stances, including skepticism about methodological inconsistencies, accusations of greenwashing, and concerns over politicization. Notably, statistical analysis showed minimal correlation between video sentiment and audience sentiment, suggesting that user perceptions are shaped by factors beyond the tone of the videos themselves. These findings underscore the need for more rigorous ESG frameworks, enhanced standardization, and proactive stakeholder engagement strategies. The study highlights the value of online platforms for capturing stakeholder feedback in real time, offering practical insights for organizations and policymakers seeking to strengthen ESG disclosure and communication. Full article

Emerging markets face growing pressures to integrate sustainable English business practices while maintaining economic growth, particularly in addressing environmental challenges and achieving carbon neutrality goals. English Financial information extraction becomes crucial for supporting green finance initiatives, Environmental, Social, and Governance (ESG) compliance, and sustainable investment decisions in these markets. This paper presents FinATG, an AI-driven autoregressive framework for extracting sustainability-related English financial information from English texts, specifically designed to support emerging markets in their transition toward sustainable development. The framework addresses the complex challenges of processing ESG reports, green bond disclosures, carbon footprint assessments, and sustainable investment documentation prevalent in emerging economies. FinATG introduces a domain-adaptive span representation method fine-tuned on sustainability-focused English financial corpora, implements constrained decoding mechanisms based on green finance regulations, and integrates FinBERT with autoregressive generation for end-to-end extraction of environmental and governance information. While achieving competitive performance on standard benchmarks, FinATG’s primary contribution lies in its architecture, which prioritizes correctness and compliance for the high-stakes financial domain. Experimental validation demonstrates FinATG’s effectiveness with entity F1 scores of 88.5 and REL F1 scores of 80.2 on standard English datasets, while achieving superior performance (85.7–86.0 entity F1, 73.1–74.0 REL+ F1) on sustainability-focused financial datasets. The framework particularly excels in extracting carbon emission data, green investment relationships, and ESG compliance indicators, achieving average AUC and RGR scores of 0.93 and 0.89 respectively. By automating the extraction of sustainability metrics from complex English financial documents, FinATG supports emerging markets in meeting international ESG standards, facilitating green finance flows, and enhancing transparency in sustainable business practices, ultimately contributing to their sustainable development goals and climate action commitments. Full article

Background/Objectives: Psychosocial (PS) factors and cognitive dysfunction (CD) in patients with atrial fibrillation (AF) may negatively impact treatment compliance. The PS profile covers multiple psychological and socio-economic factors, although research is mostly limited to depression, anxiety, and work stress. This study assessed the prevalence of a broad range of PS factors in patients with AF and their relationship with cognitive decline. Methods: We retrospectively analyzed data from patients referred to a cardiovascular rehabilitation clinic between March 2017 and April 2023 who underwent standardized assessments of PS factors, cognition, and quality of life. Results: Of the 798 included patients, 230 (28.8%) had AF, with a mean age of 68.07 years (SD 9.60 years). Six of nine PS factors were present in more than half of the overall sample. Compared to non-AF patients, those with AF showed significantly higher levels of social isolation, depression, and hostility, whereas low socioeconomic status, family and work-related stress, and other mental disorders were more frequent in the non-AF group. CD was present in 67.4% of the total cohort and was more prevalent in AF patients with a higher PS burden. Patients with permanent AF reported the poorest health status. Conclusions: Integrating assessments of PS factors and cognition in cardiac rehabilitation is feasible and supports a more comprehensive, patient-centred model of care in AF. Full article

The increasing pressure for environmental, social, and governance (ESG) accountability in publicly funded institutions has raised concerns about the authenticity and efficiency of ESG implementation. This study investigates the relationship between public ESG funding, disclosure quality, and organizational efficiency across Greek public and financial entities. Using a mixed-methods approach—data envelopment analysis (DEA), qualitative ESG content scoring, and bibliometric mapping—we reveal that symbolic compliance remains prevalent, often decoupled from actual sustainability outcomes. Our DEA findings show that technical efficiency is strongly associated with reporting clarity, the use of verifiable metrics, and governance integration, rather than the mere volume of funding. The qualitative analysis further confirms that many disclosures reflect reputational signaling rather than impact-oriented transparency. Bibliometric results highlight a systemic underrepresentation of the public sector in ESG scholarship, particularly in Southern Europe, underscoring the need for regionally grounded empirical studies. This study provides practical implications for improving ESG accountability in publicly funded institutions and contributes a novel approach that integrates efficiency, content, and bibliometric analysis in the ESG context. Full article

Online Probability Panels (OPPs) have emerged as essential research infrastructures for social sciences, offering robust tools for longitudinal analysis and evidence-based policy-making. However, the growing role of the Open Science movement demands systematic evaluation of their compliance. This study compares major European OPPs—including LISS, GESIS, the GIP, ELIPSS, and the Swedish and Norwegian Citizen Panels—focusing on their practices of openness, recruitment, sampling, and maintenance. Through a qualitative analysis of public documentation and methodological reports, the study examines how their diverse approaches influence data accessibility, inclusivity, and long-term usability. Our findings highlight substantial variability across panels, reflecting the interplay between national contexts, governance models, technological infrastructures, and methodological choices related to recruitment, sampling, and panel maintenance. Some panels demonstrate stronger alignment with Open Science values—promoting transparency, interoperability, and inclusive engagement—while others operate within more constrained frameworks shaped by institutional or structural limitations. This comparative analysis contributes to the understanding of OPPs as evolving knowledge infrastructures and provides a reference framework for future panel development. In doing so, it offers valuable insights for enhancing the role of OPPs in advancing open and socially engaged research practices. Full article

Background/Objectives: The consumption of opioids is a public health problem that significantly affects quality of life. In Spain, 7585 people are enrolled in the Methadone Maintenance Programme (MMP), which is an effective intervention with a low adherence rate. In this study, factors associated with the quality of life of MMP users, especially perceived social support and treatment adherence, were analysed. We hypothesised that low levels of adherence and social support would be associated with poorer quality of life. Methods: This was a cross-sectional observational study with an analytical approach. Quality of life (WHOQoL-BREF), perceived social support (DUKE-UNC-11), and treatment adherence (MMAS-8) among MMP users were studied, and data on sociodemographic and clinical characteristics were collected through ad hoc questionnaires and a review of electronic medical records. Linear and logistic regression models were used. Results: A total of 70 individuals were included in this study. The mean age was 56.9 years, and 83% of the participants were male. The perceived quality of life was low in the four domains evaluated (range of 47.4–48.2). A total of 38.57% of the participants had low perceived social support. Treatment adherence was low or moderate in 77.1% of the participants. Greater perceived social support was associated with better quality of life in all domains (p < 0.05). Quality of social life was negatively associated with the use of nonbenzodiazepine neuroleptics and HIV status. Treatment adherence was lower in insulin therapy users. Conclusions: Social support is a key determinant of the quality of life of MMP users. Health policies should promote social support networks as a strategy to improve the well-being of this population. Full article

Background and Objectives: Orthodontic treatment aims to enhance dental aesthetics and function, yet many patients report dissatisfaction. This study was designed with the following objectives: To assess overall patient satisfaction during active orthodontic treatment; to identify key psychosocial and clinical predictors of satisfaction, including self-confidence, social experiences, and cost perception; to evaluate the impact of orthodontist–patient communication on satisfaction and perceived treatment outcomes; to explore the relationship between aesthetic improvement and willingness to undergo treatment again. Materials and Methods: A cross-sectional survey was conducted using structured questionnaires to assess satisfaction, pain perception, treatment expectations, and communication quality. Statistical analyses, including correlations and regression models, were used to identify predictors of satisfaction. The study included 450 orthodontic patients from the north-eastern region of Romania, undergoing active treatment at the time of data collection. Results: The strongest predictor of satisfaction was improved self-confidence and smile aesthetics (r = 0.62). Effective communication with orthodontists significantly increased satisfaction (r = 0.58, p = 0.002), while perceived high costs had a negative impact (r = −0.41). Pain and discomfort were common, with 90% of patients experiencing treatment-related pain, leading to reduced compliance. Social embarrassment due to braces also contributed to dissatisfaction (r = −0.47). Conclusions: Patient satisfaction with orthodontic treatment is primarily influenced by aesthetic improvements and effective communication. While enhanced smile perception boosts confidence, financial concerns and social discomfort may negatively affect the overall experience. Improving accessibility to treatment and providing comprehensive patient support are essential for optimizing patient satisfaction. Full article

Hepatitis C is an infectious liver disease which contributes to an estimated 400,000 deaths each year. The disease is caused by the hepatitis C virus (HCV) and is spread by direct blood contact between infected and susceptible individuals. While the magnitude of its impact on human populations has prompted a growing body of scientific work, the current epidemiological models of HCV transmission among injecting drug users treat risk behaviors as fixed parameters rather than as outcomes of a dynamic, decision-making process. Our study addresses this gap by constructing a game-theoretic model to investigate the implications of voluntary participation in clean needle exchange programs on the spread of HCV among this high-risk population. Individual drug users weigh the (perceived) cost of clean equipment usage relative to the (perceived) cost of infection, as well as the strategies adopted by the rest of the population, and look for a selfishly optimal level of protection. We find that the spread of HCV in this population can theoretically be eliminated if individuals use sterile equipment approximately two-thirds of the time. Achieving this level of compliance, however, requires that the real and perceived costs of obtaining sterile equipment are essentially zero. Our study demonstrates a robust method for integrating game theory with epidemiological models to analyze voluntary health interventions. It provides a quantitative justification for public health policies that eliminate all barriers—both monetary and social—to comprehensive harm-reduction services. Full article

This paper presents an integrated Smart City platform that combines digital twin technology, advanced machine learning, and a private blockchain network to enhance data-driven decision making and operational efficiency in both public enterprises and small and medium-sized enterprises (SMEs). The proposed cloud-based business intelligence model automates Extract, Transform, Load (ETL) processes, enables real-time analytics, and secures data integrity and transparency through blockchain-enabled audit trails. By implementing the proposed solution, Smart City and public service providers can significantly improve operational efficiency, including a 15% reduction in costs and a 12% decrease in fuel consumption for waste management, as well as increased citizen engagement and transparency in Smart City governance. The digital twin component facilitated scenario simulations and proactive resource management, while the participatory governance module empowered citizens through transparent, immutable records of proposals and voting. This study also discusses technical, organizational, and regulatory challenges, such as data integration, scalability, and privacy compliance. The results indicate that the proposed approach offers a scalable and sustainable model for Smart City transformation, fostering citizen trust, regulatory compliance, and measurable environmental and social benefits. Full article

In the digital economy, information asymmetry among individuals, data users, and governments limits the full realization of personal data value. To address this, “symmetry enhancement” strategies aim to reduce information gaps, enabling more balanced decision-making and facilitating efficient data flow. This study establishes a tripartite evolutionary game model based on personal data collection and development, conducts simulations using MATLAB R2024a, and proposes countermeasures based on equilibrium analysis and simulation results. The results highlight that individual participation is pivotal, influenced by perceived benefits, management costs, and privacy risks. Meanwhile, data users’ compliance hinges on economic incentives and regulatory burdens, with excessive costs potentially discouraging adherence. Governments must carefully weigh social benefits against regulatory expenditures. Based on these findings, this paper proposes the following recommendations: use personal data application scenarios as a guide, rely on the construction of personal trustworthy data spaces, explore and improve personal data revenue distribution mechanisms, strengthen the management of data users, and promote the maximization of personal data value through multi-party collaborative ecological incentives. Full article

This study investigates voluntary compliance with the Task Force on Climate-Related Financial Disclosures (TCFD) framework in 64 financial, Environmental, Social, and Governance (ESG) reports from six Spanish IBEX-35 energy firms (2020–2023) and explores the implications for intangible assets and corporate reputation, employing empirical quantitative text mining and Natural Language Processing (NLP) in Python. A validated scale-based taxonomy within the TCFD framework applies query-driven rules to extract relevant text. This enables an evaluation of aspects of the reports, facilitating the development of a compliance index measuring each company’s adherence to TCFD recommendations. All companies showed year-on-year improvements (2023 was the most comprehensive), yet none fully adhered due to information gaps. Disparities in the disclosures of Scope 1,2 and 3, persisted, suggesting reputational risks. A replicable methodological model generating a compliance index that assesses the ‘being’ (‘true performance’) versus ‘seeming’ (‘external perception’) dichotomy within sustainability reports and acts as a potential reputational barometer for stakeholders. By providing unprecedented evidence of TCFD reporting in the Spanish energy sector, this study closes a significant academic gap. Future research may analyze ESG reports using AI agents, study the impact of ESG on energy-intensive companies from AI data centers, supporting services like Copilot, ChatGPT, Claude, Gemini, and extend this methodology to other industrial sectors. Full article

The ability to effectively engineer robots with appropriate social behaviors that conform to acceptable social norms and with the potential to influence human behavior remains a challenging area in robotics. Given this, we sought to provide insights into “what can be considered a socially appropriate and effective behavior for robots charged with enforcing social compliance of various magnitudes”. To this end, we investigate how social robots can be equipped with context-inspired persuasive behaviors for human–robot interaction. For this, we conducted three separate studies. In the first, we explored how the android robot “ERICA” can be furnished with negative persuasive behaviors using a video-based within-subjects design with N = 50 participants. Through a video-based experiment employing a mixed-subjects design with N = 98 participants, we investigated how the context of norm violation and individual user traits affected perceptions of the robot’s persuasive behaviors in the second study. Lastly, we investigated the effect of the robot’s appearance on the perception of its persuasive behaviors, considering two humanoids (ERICA and CommU) through a within-subjects design with N = 100 participants. Findings from these studies generally revealed that the robot could be equipped with appropriate and effective context-sensitive persuasive behaviors for human–robot interaction. Specifically, the more assertive behaviors (displeasure and anger) of the agent were found to be effective (p < 0.01) as a response to a situation of repeated violation after an initial positive persuasion. Additionally, the appropriateness of these behaviors was found to be influenced by the severity of the violation. Specifically, negative behaviors were preferred for persuasion in situations where the violation affects other people (p < 0.01), as in the COVID-19 adherence and smoking prohibition scenarios. Our results also revealed that the preference for the negative behaviors of the robots varied with users’ traits, specifically compliance awareness (CA), agreeableness (AG), and the robot’s embodiment. The current findings provide insights into how social agents can be equipped with appropriate and effective context-aware persuasive behaviors. It also suggests the relevance of a cognitive-based approach in designing social agents, particularly those deployed in sensitive social contexts. Full article