Search Results (1,123)

This study explores the challenges and theoretical transformations that the widespread application of AI technology in social governance brings to the protection of citizens’ fundamental rights. By examining typical cases in judicial assistance, technology-enabled law enforcement, and welfare supervision, it explains how AI characteristics such as algorithmic opacity, data bias, and automated decision-making affect fundamental rights including due process, equal protection, and privacy. The article traces the historical evolution of privacy theory from physical space protection to informational self-determination and further to modern data rights, pointing out the inadequacy of traditional rights-protection paradigms in addressing the characteristics of AI technology. Through analyzing AI-governance models in the European Union, the United States, Northeast Asia, and international organizations, it demonstrates diverse governance approaches ranging from systematic risk regulation to decentralized industry regulation. With a special focus on China, the article analyzes the special challenges faced in AI governance and proposes specific recommendations for improving AI-governance paths. The article argues that only within the track of the rule of law, through continuous theoretical innovation, institutional construction, and international cooperation, can AI technology development be ensured to serve human dignity, freedom, and fair justice. Full article

Background/Objectives: Chickenpox is an ongoing health threat for young children. This study aimed to investigate varicella vaccination uptake among children and its determinants at both the individual and interpersonal levels. Methods: A cross-sectional survey of parents of children aged 0–15 years and with administrative health records was conducted between September and October 2024 in Shenzhen, China. Participants were recruited through multistage random sampling. This analysis was based on a subsample of 996 parents whose children were 1–10 years old and without a prior history of chickenpox. Multivariate logistic regression models were fitted. Results: Among the participants, 47.0% reported that their children had received a varicella vaccination. Parents who believed that chickenpox was highly contagious (adjusted odds ratios [AOR]: 1.62, 95% confidence interval [CI]: 1.23, 2.13), perceived more benefits (AOR: 1.22, 95% CI: 1.05, 1.41) and cues to action (AOR: 1.33, 95% CI: 1.04, 1.69), and exhibited greater self-efficacy (AOR: 1.40, 95% CI: 1.09, 1.80) related to children’s varicella vaccination reported higher varicella vaccination uptake for their children. Greater perceived barriers related to vaccination (AOR: 0.89, 95% CI: 0.83, 0.95) and dysfunctional interactions with children (AOR: 0.97, 95% CI: 0.94, 0.99) were associated with lower varicella vaccination uptake for children. In addition, higher exposure to information encouraging parents to vaccinate their children against chickenpox (AOR: 1.24, 95%CI: 1.08, 1.41) and thoughtful consideration of the veracity of the information were associated with higher varicella vaccination uptake among children (AOR: 1.19, 95% CI: 1.05, 1.36). Conclusions: There is a strong need to promote varicella vaccination for children in China. Full article

Seafood processing byproducts (SB) such as bones and skin can be safely used as food ingredients to increase profitability for the seafood sector and provide nutritional value. An online survey of 716 US adult seafood consumers was conducted to explore SB trial intent, responsiveness to health and safety information, and associated elicited emotions (nine-point Likert scale). Consumers’ SB-elicited emotions were defined as those changing in reported intensity (from a baseline condition) after the delivery of SB-related information (dependent t-tests). As criteria for practical significance, a raw mean difference of >0.2 units was used, and Cohen’s d values were used to classify effect sizes as small, medium, or large. Differences in willingness-to-try, responsiveness to safety and health information, and SB-elicited emotions were found based on self-reported gender and race, with males and Hispanics expressing more openness to SB consumption. SB-elicited emotions were then used to model consumers’ willingness-to-try foods containing SB via logistic regression modeling. Traditional stepwise variable selection was compared to variable selection using raw mean difference > 0.2 units and Cohen’s d > 0.50 constraints for SB-elicited emotions. Resulting models indicated that extrinsic information considered at the point of decision-making determined which emotions were relevant to the response. These new approaches yielded models with increased Akaike Information Criterion (AIC) values (lower values indicate better model fit) but could provide simpler and more practically meaningful models for understanding which emotions drive consumption decisions. Full article

Blended and virtual learning have become an integral part in international higher education, especially in the wake of the COVID-19 pandemic and the European Union’s Digital Education Action Plan. These modalities have enabled more inclusive, flexible, and sustainable forms of international collaboration, such as Collaborative Online International Learning (COIL) and Blended Intensive Programs (BIPs), reshaping the landscape of global academic mobility. This paper introduces the INVITE Learning Design Framework (LDF), developed to support higher education instructors in designing high-quality, internationalized blended and virtual learning experiences. The framework addresses the growing need for structured, theory-informed approaches to course design that foster student engagement, intercultural competence, and motivation in non-face-to-face settings. The INVITE LDF was developed through a rigorous scoping review of existing models and frameworks, complemented by needs-identification analysis and desk research. It integrates Self-Determination Theory, Active Learning principles, and the ADDIE instructional design model to provide a comprehensive, adaptable structure for course development. The framework was successfully implemented in a large-scale online training module for over 1000 educators across Europe. Results indicate that the INVITE LDF enhances educators’ ability to create engaging, inclusive, and pedagogically sound international learning environments. Its application supports institutional goals of internationalization by making global learning experiences more accessible and scalable. The findings suggest that the INVITE LDF can serve as a valuable tool for higher education institutions worldwide, offering a replicable model for fostering intercultural collaboration and innovation in digital education. This contributes to the broader transformation of international higher education, promoting equity, sustainability, and global citizenship through digital pedagogies. Full article

This study investigates the encroachment risk in the Makause informal settlement by analysing resident survey data to identify key contributing factors and build predictive models. Encroachment threatens the water infrastructure through damage, contamination, and service disruptions, highlighting the need for informed, community-based planning. The data was collected from 105 residents, with responses (“Yes,” “No,” “Unsure”) analysed using descriptive statistics and a one-way ANOVA to identify significant differences across categories. The ReliefF algorithm was used to rank the importance of features predicting the encroachment risk. These inputs were then used to train, validate, and test an Artificial Neural Network (ANN) model. The Artificial Neural Network demonstrated a high predictive accuracy, achieving correlation coefficients above 95% and low mean squared errors. The ANOVA identified statistically significant mean differences for selected variables, while ReliefF helped determine the most influential predictors. A high agreement level (p > 0.900) between predicted and actual responses confirmed the model’s validity. This research introduces an innovative, data-driven framework that integrates machine learning and a statistical analysis to support municipalities and utility providers in engaging informal communities to protect infrastructure. While this study is limited to Makause and may be affected by a self-reported bias, it demonstrates the potential of Artificial Neural Networks and ReliefF in enhancing the risk analysis and infrastructure management in informal settlements. Full article

Background and Objectives: Emotional intelligence (EI) plays a critical role in safeguarding the emotional and psychological well-being of healthcare workers, acting as a buffer against burnout, and influencing the quality of patient care. Despite its significance, there remains a need to understand how EI levels correlate with burnout and what factors predict burnout in high-stress healthcare environments. This study, conducted at King Khaled Hospital in Al-Majmaah, Saudi Arabia, aims to assess the EI levels of healthcare staff, to determine the relationship between EI and burnout, and to identify key predictors of burnout to inform targeted interventions for improving workforce resilience and patient outcomes. Materials and Methods: Both self-reporting and standardized tests were integrated using cross-sectional surveys to evaluate the EI of each participant and the burnout they experience by averaging the rating of a 30-item questionnaire, allowing comparison of the interaction between EI, burnout, and work factors. Results: A significantly moderate level of EI was identified, while a high level of well-being was associated with a low level of burnout, and a high level of emotionality was associated with a high level of burnout. Results indicated that high job demands, call rotation, or casual work, and insufficient staff support were organizational correlates of burnout. Conclusions: Improving EI with a focus on the well-being sub-dimension may prevent burnout, and, for that, the interventions must be specific at both personal and organizational levels. Full article

Aim: To explore the experiences, beliefs, and values of patients who participated in a two-arm randomized clinical trial assessing a nurse-led intervention program for chronic pain self-management, which demonstrated positive effects on pain reduction, depression, and anxiety, and on health-related quality of life 24 months after completion of the program. Design: Descriptive phenomenological qualitative study. Methods: Patients were recruited via telephone, informed about the study, and invited to participate in an individual interview at a place of their choice (hospital or home). All interviews were audiotaped, and an inductive thematic analysis was performed. Results: Seven interviews were carried out between both groups. Six emerging categories were found: effective relationship with the healthcare system, learning to live with pain, family and social support, behaviors regarding pain, resources for self-management, and concomitant determinants. Conclusions: Patients report key aspects that help us to understand the impact of this type of nurse-led group intervention: the intrinsic therapeutic effect of participating in the program itself, the ability to learn to live with pain, the importance of family and social support, the modification of pain-related behaviors, and the identification of resources for self-care. The findings highlight the need for gender-sensitive, individualized care approaches to chronic pain, addressing stigma and social context. Expanding community-based programs and supporting caregivers is essential, as is further research into gender roles, family dynamics, and work-related factors. Full article

This study proposes a novel approach to constructing composite indicators, utilizing discriminant analysis to identify the determining factors for the diagnosis of multidimensional depression and to provide an index that represents the multidimensionality of this construct. By focusing solely on factors that significantly correlate with the diagnosis of multidimensional depression, this method provides a more precise and objective representation of the problem. The application of the method to the 2019 Brazilian Health Survey data demonstrated its effectiveness, resulting in a composite indicator that separates individuals who self-declare as having depression from individuals who self-declare as not having depression. The results highlight individuals who have a limiting chronic condition, high levels of education, less support from friends and family, perform unhealthy work, and are male. In contrast, individuals with the opposite characteristics are associated with a negative multidimensional depression diagnosis. The proposed composite indicator not only improves the measurement accuracy but also offers a new means of visualizing and understanding the multidimensional nature of depression diagnosis, providing valuable information for the formulation of targeted public health policies aimed at reducing the time for which people show symptoms of depression. Full article

Bring them home, keep them home is research based in New South Wales (NSW) Australia, that aims to understand successful and sustainable reunification for Aboriginal families who have children in out-of-home care (OOHC). This research is led by Aboriginal researchers, and partners with Aboriginal organisations. It is informed by the experiences of 20 Aboriginal parents and family members, and more than 200 practitioners and professionals working in child protection and reunification. This paper traces the evolution of Bring them home, keep them home which is now at the forefront of influence for NSW child protection reforms. Using specific examples, it highlights the role of research advocacy and resistance in challenging and disrupting systems in ways that amplify the voices of Aboriginal families and communities and embeds these voices as the foundation for radical innovation for child reunification approaches. The paper shares lessons being learned and insights for Aboriginal-led research with communities in the pursuit of restorative justice, system change, and self-determination. Providing a framework for liberating Aboriginal families from child abduction systems, this paper seeks to offer a truth-telling and practical contribution to the international efforts of Indigenous resistance to child abduction systems. Full article

(1) Background: Physical activity (PA) is a key modifiable risk factor for chronic diseases, yet many adults do not meet PA guidelines. Just-in-time adaptive interventions (JITAIs), a type of mobile health (mHealth) intervention, offer tailored support based on an individual’s context to promote PA. Integrating behavior change techniques (BCTs) and theories is critical to the design of effective mHealth interventions. Understanding which BCTs and theories work best can inform future JITAI development. (2) Objective: The objective of this study is to examine how behavior change theories and BCTs are implemented in mHealth PA JITAIs and assess their relationship with PA-related outcomes. (3) Methods: This scoping review followed the PRISMA-ScR guidelines. A total of 29 studies were included. (4) Results: The most commonly used BCTs include prompts/cues (n = 29), goal-setting (behavior) (n = 15), and feedback on behavior (n = 14), while self-determination theory (n = 4) and social cognitive theory (n = 4) are the most commonly used theories. However, there is insufficient evidence as to which theories and BCTs are most effective in eliciting effective PA behavior change. (5) Conclusions: Clearer reporting and integration of BCTs and behavior change theories, along with optimized user interfaces, are needed to improve the intervention quality, replicability, and long-term effectiveness of PA JITAIs. Full article

This study investigates the development of cognitive, emotional, and social skills in pre-service teachers through extracurricular activities, addressing 21st century challenges in preparing educators for diverse learning environments. It was hypothesized that extracurricular activities would positively influence cognitive skills (self-efficacy, self-regulation), emotional dimensions (professional interest), social competencies (teacher–student relationships), and academic achievement. This study employed predictive correlational methodology based on an integrated theoretical framework combining Social Cognitive Theory, Self-Determination Theory, Self-Regulation Theory, and Interpersonal Relationships Theory within formal–informal learning contexts. A psychometrically robust instrument (“Scale on the Contribution of Extracurricular Activities to Professional Development”) was developed and validated through exploratory and confirmatory factor analyses, yielding a five-factor structure with strong reliability indicators (Cronbach’s α = 0.91–0.93; CR = 0.816–0.912; AVE = 0.521–0.612). Data from 775 pre-service teachers (71.1% female) across multiple disciplines at a Turkish university were analyzed using structural equation modeling (χ²/df = 2.855, RMSEA = 0.049, CFI = 0.93, TLI = 0.92). Results showed that extracurricular participation significantly influenced self-efficacy (β = 0.849), professional interest (β = 0.418), self-regulation (β = 0.191), teacher–student relationships (β = 0.137), and academic achievement (β = 0.167). Notably, an unexpected negative relationship emerged between self-efficacy and academic achievement (β = −0.152). The model demonstrated strong explanatory power for self-efficacy (R² = 72.8%), professional interest (R² = 78.7%), self-regulation (R² = 77.2%), and teacher–student relationships (R² = 63.1%) while explaining only 1.8% of academic achievement variance. This pattern reveals distinct developmental pathways for professional versus academic competencies, leading to a comprehensive practical implications framework supporting multidimensional assessment approaches in teacher education. These findings emphasize the strategic importance of extracurricular activities in teacher education programs and highlight the need for holistic approaches beyond traditional academic metrics, contributing to Sustainable Development Goal 4 by providing empirical evidence for integrating experiential learning opportunities that serve both academic researchers and educational practitioners seeking evidence-based approaches to teacher preparation. Full article

Science teachers continue to face decreased motivation, lower achievement levels, and decreased enrollment in post-secondary science programs. Teachers ask themselves this question: How do I motivate my students to achieve? Student-centered pedagogies, such as an in-depth pedagogy informed by Self-Determination Theory, can improve students’ motivation by addressing students’ basic psychological needs for autonomy, competency, and relatedness. Problem-based learning presents students with relevant situations and actively engages them in developing plausible solutions to problems. Environmental sustainability encompasses issues concerning our ecological and social environments. Teachers can focus on these issues to develop authentic problem-based learning units that offer a student-relevant pathway to improve motivation and scientific literacy. We propose a pedagogical framework, drawing on Self-Determination Theory, to promote students’ motivation to engage keenly with environmental sustainability education through problem-based learning. This framework is designed for secondary science classrooms to inform science teachers’ pedagogical practice. Full article

Background: Influenza is a significant global respiratory infection, and vaccinating reproductive-age women, particularly in densely populated countries like China, cannot be overlooked. In this study, we aimed to determine influenza vaccination coverage, vaccine hesitancy, as well as associated factors among Chinese women aged 18–49 years old. Methods: A cross-sectional survey among women aged 18–49 years was conducted in China from 15 to 30 March 2023. We collected information such as past-year influenza vaccination, demographic characteristics, health-related factors, COVID-19-related factors, and perceived susceptibility and severity of influenza. Influenza vaccine acceptance among participants who did not receive influenza vaccination in the past year was also investigated. Multivariable logistic regression analyses were employed to investigate the influencing factors of vaccine coverage and vaccine hesitancy. Results: A total of 1742 reproductive-aged women were included in the final analysis. The past-year influenza vaccine coverage among women aged 18–49 years old was only 39.32% in China. Age ≥ 35 years (aOR = 0.72, 95% CI: 0.56–0.94), renting accommodation (aOR = 0.57, 95% CI: 0.44–0.75), and history of COVID-19 infection (aOR = 0.65, 95% CI: 0.47–0.89) and COVID-19 vaccine hesitancy (aOR = 0.39, 95% CI: 0.29–0.54) were all identified as negative correlates of influenza vaccine coverage among Chinese reproductive-aged women, while participants with a history of chronic diseases (aOR = 1.57, 95% CI: 1.23–2.01) and noticeable pandemic fatigue due to COVID-19 (aOR = 1.45, 95% CI: 1.05–2.00) were prone to have higher vaccination rates. Among reproductive-aged women who did not receive influenza vaccination in the past year, the hesitancy rate regarding future influenza vaccination was 31.79%. Factors such as older age, urban residence, living with others, poor self-rated health status, absence of chronic diseases, completion of full COVID-19 vaccination, COVID-19 vaccine hesitancy, pandemic fatigue, and failure to perceive the susceptibility and severity of influenza might increase influenza vaccine hesitancy. Discussion: Overall, a lower coverage rate of influenza vaccine was notably observed among Chinese reproductive-age women, as well as the hesitancy regarding future vaccination. To effectively mitigate the impact of influenza and reduce the incidence of associated diseases, it is imperative to devise targeted intervention strategies and policies tailored to reproductive-age women. Full article

Deep learning models have obvious advantages in detecting oil spills, but the training of deep learning models heavily depends on a large number of samples of high quality. However, due to the accidental nature, unpredictability, and urgency of oil spill incidents, it is difficult to obtain a large number of labeled samples in real oil spill monitoring scenarios. Surprisingly, few-shot learning can achieve excellent classification performance with only a small number of labeled samples. In this context, a new cross-domain few-shot SAR oil spill detection network is proposed in this paper. Significantly, the network is embedded with a hybrid attention feature extraction block, which consists of a coordinate attention module to perceive the channel information and spatial location information, as well as a global self-attention transformer module capturing the global dependencies and a multi-scale self-attention module depicting the local detailed features, thereby achieving deep mining and accurate characterization of image features. In addition, to address the problem that it is difficult to distinguish between the suspected oil film in seawater and real oil film using few-shot due to the small difference in features, this paper proposes a double loss function category determination block, which consists of two parts: a well-designed category-perception loss function and a traditional cross-entropy loss function. The category-perception loss function optimizes the spatial distribution of sample features by shortening the distance between similar samples while expanding the distance between different samples. By combining the category-perception loss function with the cross-entropy loss function, the network’s performance in discriminating between real and suspected oil films is thus maximized. The experimental results effectively demonstrate that this study provides an effective solution for high-precision oil spill detection under few-shot conditions, which is conducive to the rapid identification of oil spill accidents. Full article

Background: Antibiotic resistance (AMR) is a critical global and national health challenge, largely driven by the misuse and overuse of antibiotics. Understanding the public′s knowledge and practices regarding antibiotic use is essential for informing effective interventions. This study aimed to assess the levels of knowledge, attitude, and practice (KAP) related to antibiotic use among adults in Saudi Arabia’s Western Region and to identify the demographic and behavioral determinants of these outcomes. Methods: A regional cross-sectional survey was conducted from March to June 2025 using a 40-item self-administered online questionnaire. Adults aged ≥ 18 years residing in the Western Region of Saudi Arabia were recruited via social media using snowball sampling. Descriptive statistics and Chi-square tests were used to examine associations, while multivariate logistic regression was employed to identify determinants of high knowledge and good practices, presented as adjusted odds ratios (aOR) with 95% confidence intervals (CI). Results: A total of 891 participants were included; most were female (63.6%) and aged 18–30 years (56.2%). Moderate knowledge of antibiotic use was observed in 54.0% of participants, while 30.8% had high knowledge. In terms of attitude and practice, 55.6% demonstrated good performance and 42.8% average performance. High knowledge was significantly associated with the female gender (aOR = 1.90; 95% CI: 1.34–2.70), age of 41–50 years (aOR = 2.22; 95% CI: 1.42–3.48), and a postgraduate education (aOR = 15.37; 95% CI: 1.84–128.13). Good practices were associated with the female gender (aOR = 2.32; 95% CI: 1.66–3.24) and being married (aOR = 1.99; 95% CI: 1.43–2.77). A moderate positive correlation was found between knowledge and practice scores (r = 0.406, p < 0.001). Conclusions: Significant variability in public KAP regarding antibiotic use was identified. Female gender, older age, and higher education were key determinants of better KAP. These findings emphasize the need for targeted educational strategies focusing on high-risk groups to support rational antibiotic use and mitigate antimicrobial resistance. Full article