Search Results (14,665)

Unintended pregnancies among adolescent and young women in low- and middle-income countries pose major public health challenges, underscoring the need for improved access to modern contraceptives. This study examined prevalence, preferences, and correlates of modern contraceptive use among young women living in urban slums of Kampala, Uganda, to inform targeted interventions. We analyzed baseline data from The Onward Project On Wellbeing and Adversity (TOPOWA), an NIH-funded, multi-component prospective cohort study on mental health among women aged 18–24 years. In 2023, 300 participants were recruited from three sites (Banda, Bwaise, Makindye). Interviewer-administered surveys assessed contraceptive choices, lifestyle, and demographic factors. Modified Poisson regression was used to examine correlates of contraceptive use. Among participants, 66.0% had ever used contraception, 40.0% were current users, and 38.0% reported modern contraceptive use. Multivariable analyses showed that having a consistent partner (PR = 3.28; 95% CI: 1.90–5.67), engaging in sex work (PR = 2.10; 95% CI: 1.46–3.02), older age (PR = 1.08; 95% CI: 1.01–1.16), and having children (PR = 1.72; 95% CI: 1.12–2.66) were associated with higher modern contraceptive use. Findings highlight important gaps in sustained contraceptive use and the need for tailored interventions addressing economic, social, and educational barriers to improve reproductive health in this low-resource setting. Full article

Financial literacy is essential for sustainable social and economic development, but several demographics and financial behaviors can influence informed decision-making. In this investigation, we examine the interaction between Financial Literacy (FL) and Financial Wellbeing and Behavior (FWB) across 286 Brazilian education professionals. We employ a two-step approach for analysis: step one is determining the influential demographic variables for Financial Literacy (FL); in step two, FL serves as a primary variable for explaining Financial Wellbeing and Behavior (FWB). We utilize both multiple regressions and supervised machine learning for factor verification for both concepts. The findings show that superior Financial Literacy is a highly significant and substantial positive antecedent of excellent Financial Wellbeing and Behavior ($p<0.01$). We also find that a significant gender gap exists in financial knowledge, such that women significantly underperform men on financial literacy tests. Machine learning models confirm that FL is the strongest feature for FWB prediction by far and that gender is the strongest antecedent of a consumer’s level of financial literacy. These findings suggest that policymakers must do more than provide primary financial literacy; they also need to deploy behavioral insights to raise long-term financial freedom and close the gender gap. Upscaling teacher financial literacy is a strategic social sustainability investment that promotes the explicit Sustainable Development Goals, including “Quality Education,” “Gender Equality,” “Decent Work” and “Economic Growth”. Full article

Background/Objectives: Rheumatic fever is preventable and can be treated successfully; however, a lack of understanding of the disease and barriers to timely healthcare can impact outcomes. Pacific people in Aotearoa New Zealand experience inequitable burdens, and a Pacific community group and health professional network are working together to co-design education initiatives. This descriptive, mixed-methods study aimed to (1) explore Pacific people’s awareness and understanding of rheumatic fever, (2) describe where Pacific people access health information. Methods: An online survey co-developed with Pacific community members was run from December 2024 to February 2025. Questions related to sore throats, rheumatic fever, medication adherence, long-term outcomes and where Pacific people access health information. Quantitative data was analyzed descriptively using SPSS version 28 and open-ended qualitative responses were analyzed using an inductive content analysis approach. Results: A total of 400 Pacific respondents were included: 34% were aged 16–24 years and 66% were female. Based on the analysis, 71% of Pacific participants knew that a sore throat should always be checked by a health professional and 65.3% had heard of rheumatic fever. Fever and sore throats were commonly identified as symptoms of rheumatic fever, with joint pain, body aches and chest pain mentioned less. Barriers to health services such as cost, long waiting times and cultural factors were discussed as reasons why many Pacific people often utilize social media and online forums for health information. Conclusions: This study highlights gaps in rheumatic fever knowledge and thus opportunities for health education initiatives for Pacific communities, potentially utilizing social media and online platforms. Full article

Genealogy is a powerful analytical framework for understanding the cultural evolution of tribes, communities, and societies. This article demonstrates that the recurrent reliance on genealogical structures is a common feature of human societies, serving as a fundamental mechanism for cultural evolution through time, space, and culture. Based on comparative analysis of indigenous tribal societies (e.g., Aboriginal Australian kinship, Polynesian chiefly genealogies), agrarian civilizations (e.g., European feudal lineages, Chinese patriliny), and modern nation-states (e.g., nationalist mythmaking, DNA-based ancestry movements), this study reveals consistent patterns in genealogical functions. Drawing on an interdisciplinary perspective from anthropology, sociology, history, and evolutionary biology, it is argued that genealogical systems are not passive records of descent but dynamic forces of cultural continuity and adaptation. The evidence shows that, despite vast sociocultural differences, genealogy widely operates as a dual-purpose instrument. It preserves cultural memory and legitimizes political authority while simultaneously facilitating social adaptation and innovation in response to new challenges. The paper also critiques contemporary trends like commercial genetic genealogy, highlighting its potential for reconnecting diasporic communities alongside its risks of biological essentialism. Ultimately, the work establishes that the persistent and patterned reliance on genealogy from oral traditions to genetic data offers a critical lens for understanding the deep structures of cultural continuity and transformation in human societies. It further underscores the importance of genealogy in cultural evolution, historical persistence, societal transformation, and the construction of belonging in an increasingly globalized world. Full article

Background/Objectives: Change detection of social cues across individuals plays an important role in human interaction. Methods: Here we investigated the automatic change detection of facial and vocal attractiveness in 19 female participants by recording event-related potentials (ERPs). We adopted a ‘deviant-standard-reverse’ oddball paradigm where high- or low-attractive items were embedded as deviants in a sequence of opposite attractive standard stimuli. Results: Both high- and low-attractive faces and voices elicited mismatch negativities (MMNs). Furthermore, low-attractive versus high-attractive items induced larger mismatch negativities in the voice condition but larger P3 amplitudes in the face condition. Conclusions: These data indicate that attractiveness can be automatically detected but that differences exist between facial and vocal attractiveness processing. Generally, change detection seems to work better for unattractive than attractive information, possibly in line with a negativity bias. Full article

Modern lightweight pedestrian bridges exhibit heightened susceptibility to human-induced vibration due to low natural frequencies and high flexibility. This study integrates behavioral science to explore pedestrian–structure coupling, developing a novel bidirectional biomechanical model capturing vertical/lateral movements. Body dynamics were solved iteratively. Concurrently, an agent-based cellular automata model embedded pedestrian social attributes and mutual exclusion to simulate crowd flow. Coupling these with finite element bridge analysis simulated vibration responses. Experimental validation confirms the model’s validity. This work advances a behavioral science perspective for mechanistically understanding pedestrian-induced vibration in flexible bridges, thereby contributing to strategies for mitigating vibration-induced disasters like structural damage or crowd panic. Full article

As artificial intelligence (AI) technologies increasingly shape sustainability agendas, organizations face the strategic challenge of aligning AI-driven innovation with long-term environmental and social goals. While academic interest in this intersection is growing, research remains fragmented and often lacks actionable insights into the organizational capabilities needed to operationalize sustainable AI innovation. This study addresses this gap by exploring how knowledge-based organizational capabilities—such as absorptive capacity, knowledge integration, organizational learning, and strategic leadership—support the alignment of AI initiatives with sustainability strategies. Grounded in the knowledge-based view of the firm, we conduct a bibliometric and thematic analysis of 216 peer-reviewed articles to identify emerging conceptual domains at the nexus of AI, innovation, and sustainability. The analysis reveals five dominant capability clusters: (1) data governance and decision intelligence; (2) policy-driven innovation and green transitions; (3) digital transformation through education and innovation; (4) collaborative adoption for sustainable outcomes; and (5) AI for smart cities and climate action. These clusters illuminate the multi-dimensional roles that knowledge management and organizational capabilities play in enabling responsible, impactful, and context-sensitive AI adoption. In addition to mapping the intellectual structure of the field, the study proposes a set of strategic and policy-oriented recommendations for applying these capabilities in practice. The findings offer both theoretical contributions and practical guidance for firms, policymakers, and educators seeking to embed sustainability into AI-driven transformation. This work advances the discourse on innovation and knowledge management by providing a structured, capability-based perspective for designing and implementing sustainable AI strategies. Full article

This research study addresses the critical contradiction within global food systems: unsustainable consumption patterns and persistent food insecurity coexist and are exacerbated by food waste, which deepens socioeconomic inequalities and generates negative environmental externalities. In this scenario, higher education plays a central role in adopting comprehensive strategic frameworks to develop specialized human capital and influence society. This study analyzes a Service Learning model that integrates the CFS-IRA Principles to promote the SDGs and ensure responsible consumption. Based on a case study of the Food Bank Chair spanning 10 years and 212 projects, the implementation of this model was evaluated using the Working with People (WWP) method, which combines the development of postgraduate students’ skills with community service to address social problems. The results demonstrated the effectiveness of the SL-WWP model in strengthening students’ technical, social, and ethical competencies while reducing food waste. The evaluation showed strong alignment with key SDGs, with outstanding performance in governance, although the need to strengthen environmental and social criteria was identified. The originality lies in integrating the CFS-IRA Principles into an SL model that encourages innovative cooperation among universities, civil society, and public–private sectors, offering a replicable proposal for higher education institutions to establish themselves as agents of change towards sustainability. Full article

This paper presents a thematic literature review of 35 studies to examine key developmental factors influencing expatriate adaptation, including language, identity integration, cultural intelligence, and spousal/family relations, impacting expatriate adaptation and acclimation to the host country. For the purposes of this review, the term “expatriate” refers to individuals who temporarily relocate abroad for education or professional assignments (self-initiated and assigned), often accompanied by spouses or family members. “Adaptation” is defined as the multidimensional process of adjustment to new academic, workplace, and social environments, encompassing both practical adjustment (e.g., communication, work/study tasks) and psychological well-being. This review uses two bibliometric reviews to set the foundation for exploring the impacts of language, identity integration, cultural intelligence, and family, highlighting that interactions with locals foster language development, identity integration, and cultural intelligence, which collectively enhances expatriates’ perceived sense of comfort and belonging. Spousal and family dynamics appear to be particularly influential, with the potential to either support or hinder successful adaptation. Although prior literature often focuses on these factors in isolation, this paper synthesizes them to provide a more holistic understanding of expatriate acclimation. It emphasizes the need for future research to explore the interrelated nature of these variables and their combined impact on expatriate well-being. Full article

Figurative language (metaphor, idiom, irony/sarcasm) is central to pragmatic communication but is frequently challenging for children and adolescents with autism spectrum disorder (ASD). A scoping review was conducted to map pedagogical and clinical interventions that target figurative-language skills in school-age learners with ASD and to summarize reported outcomes. Following a PCC (Population–Concept–Context) framework and PRISMA-ScR reporting, systematic searches were performed in ERIC and Google Scholar (2010–2025). Eligibility required an ASD sample (ages 5–18), an intervention explicitly addressing figurative-language comprehension, and empirical outcome data from educational or related practice settings. Seven studies met inclusion criteria: five targeting metaphors, one targeting idioms, and one targeting sarcasm/irony. Interventions were predominantly delivered one-to-one or in small groups and emphasized structured, explicit instruction with visual scaffolds and stepwise prompting. Across studies, participants demonstrated clear gains on trained items. Generalization beyond trained material was most often observed for metaphor and sarcasm interventions, particularly when instruction highlighted underlying semantic relations or cue-based pragmatic signals; by contrast, the idiom program yielded item-specific learning with minimal near-term transfer. Limited follow-up data suggested short-term maintenance where assessed. Reported variability across individuals was substantial, underscoring the influence of underlying structural-language skills and social-pragmatic demands. Overall, the evidence indicates that figurative-language skills in ASD are amenable to targeted intervention; effective programs tend to combine explicit teaching, visual supports, multiple exemplars, and planned generalization opportunities. Given small samples and methodological heterogeneity, further classroom-based trials with longer follow-up and detailed learner profiles are needed. The findings support integrating figurative-language goals within individualized education and speech-language therapy plans, while aligning instructional complexity with each learner’s linguistic and pragmatic profile. Full article

Background: Population ageing is a global challenge, prompting ageing-in-place policies in Hong Kong to support community-dwelling older adults while reducing healthcare costs. Yet, their impact on health-related quality of life (HRQoL) remains underexplored amid Hong Kong’s long life expectancy and growing older population. Traditional surveys are costly and time-consuming, while routinely collected registration data offers a large, efficient source for health insights. This study uses enhanced administrative data to track HRQoL trajectories and inform policy. Methods: This is a prospective, open-ended longitudinal study, enrolling adults aged 50 or older from a collaborating non-governmental organization in Hong Kong’s Southern District. Data collection, started in February 2021, occurs annually via phone and face-to-face interviews by trained social workers and volunteers using a standardized questionnaire to assess individual (e.g., socio-demographics), environmental (e.g., social support via Lubben Social Network Scale-6), biological (e.g., chronic illnesses), functional (e.g., cognition via Montreal Cognitive Assessment), and HRQoL (e.g., EQ-5D-5L) factors. A secure online system links health and service use data (e.g., service utilization like community care visits). Analysis employs descriptive statistics, group comparisons, correlations, growth modelling to identify health trajectories, and structural equation modelling to test a revised quality-of-life framework. Sample size (projected 470–580 after two follow-ups from a 2321 baseline) is based on power calculations: 300–500 for latent class growth analysis (LCGA) class detection and 200–400 for structural equation modelling (SEM) fit (e.g., RMSEA < 0.06) at 80% power/α = 0.05, simulated via Monte Carlo with a 50–55% attrition. Discussion: This is the first longitudinal HRQoL study in Hong Kong using enhanced non-governmental organization (NGO) administrative data, integrating social–ecological and HRQoL models to predict trajectories (e.g., stable vs. declining mobility) and project care demands (e.g., increase in in-home care for frailty). Unlike prior cross-sectional or inpatient studies, it offers a scalable model for NGOs, informing ageing-in-place policy effectiveness and equitable geriatric care. Full article

Teacher wellbeing is a matter of social justice since burnout syndrome disproportionately affects those working in under-resourced and diverse educational contexts by limiting their ability to foster inclusive and equitable learning. To this situation, art museums respond as pedagogical spaces for wellbeing while contributing to socially just and sustainable arts education. School teachers are offered new opportunities for ongoing professional development tailored to their well-being needs, such as burnout prevention. A two-round international Delphi study with experts from universities, schools, museums, and arts-and-wellbeing organizations (n = 26 1st round, n = 17 2nd round)—rather than focusing on teachers’ personal accounts—develops consensus on a pedagogical framework for art-based programs designed to prevent teacher burnout and enhance wellbeing. The findings identify nine pedagogical guidelines highlighting participatory approaches—audience, objectives, content, methodology, scheduling, facilitators, activities, evaluation, and program adherence. By positioning art museums as democratic, inclusive, and relational spaces, the framework advances the role of the arts in addressing systemic challenges in education, such as supporting teachers’ wellbeing. This research contributes to the international debate on socially just arts education by demonstrating how teacher wellbeing can be fostered through innovative, evidence-based museum practices aligned with SDG 4. Full article

This article examines how the Southern lady is represented in three major Southern women’s novels set during the American Civil War: Macaria (1864) by Augusta Jane Evans Wilson, The Battle-Ground (1902) by Ellen Glasgow, and Gone with the Wind (1936) by Margaret Mitchell. Although separated by over seven decades and distinct historical perspectives—Wilson as a contemporary witness, Glasgow as a postwar observer, and Mitchell as a nostalgic inheritor—their works collectively shaped enduring images of the South in American popular culture. Through textual analysis, the study explores how each author depicts female endurance, illness, and mortality to symbolize both individual and social transformation. The heroines (Wilson’s Electra and Irene, Glasgow’s Betty Ambler, and Mitchell’s Scarlett O’Hara) embody resilience amid collapse, assuming active roles in the reconstruction of Southern identity. Their struggles reflect broader tensions between traditional femininity and emerging female agency. Ultimately, the article argues that portrayals of women’s frailty and death function as metaphors for the decline of the antebellum order and the inevitable demise of the Southern lady ideal, revealing illness and death as physical and cultural markers of the South’s transformation in war and its aftermath. Full article

Background: Aging populations make expanded workforce participation among older adults an economic and public health priority. The COVID-19 pandemic accelerated the growth of virtual work, providing new opportunities for healthy aging in the workplace through increased flexibility and less physical strain. However, digital exclusion, ergonomically challenging tasks, and social isolation can limit these opportunities for older populations. Objective: This scoping review aimed to synthesize interdisciplinary research on the relationship between remote work and labor force participation among adults aged 45 years and older, focusing on health-related outcomes, barriers, and facilitators. Methods: Following the JBI Manual for Evidence Synthesis and PRISMA-ScR guidelines, we conducted a comprehensive search across seven databases for peer-reviewed and gray literature published between 2000 and 2025. Of 2108 records screened, 33 studies met the inclusion criteria. Data were extracted using a standardized charting tool and analyzed thematically. Results: Most studies were published after 2020 and originated in North America (45%) and Europe (40%). Core barriers included digital exclusion, ageism, and adverse ergonomic environments. Facilitators involved flexible working hours, a supportive organizational environment, and digital skills. Health-related outcomes such as stress reduction and improved well-being were commonly reported. However, only 18% of studies assessed policy effects, and very few examined intersectionality (e.g., gender, socioeconomic status). Conclusions: Remote and flexible work options can improve the health and participation of older adults in the workforce, but technology, infrastructure, and social barriers remain. Age-inclusive policies, digital equity efforts, and inclusive workplace practices are necessary to maximize the benefits of remote arrangements for aging populations. Full article

The rapid growth of technology has introduced robots into daily life, necessitating navigation frameworks that enable safe, human-friendly movement while accounting for social aspects. Such methods must also scale to situations with multiple humans and robots moving simultaneously. Recent advances in Deep Reinforcement Learning (DRL) have enabled policies that incorporate these norms into navigation. This work presents a socially aware navigation framework for mobile robots operating in environments shared with humans and other robots. The approach, based on single-agent DRL, models all interaction types between the ego robot, humans, and other robots. Training uses a reward function balancing task completion, collision avoidance, and maintaining comfortable distances from humans. An attention mechanism enables the framework to extract knowledge about the relative importance of surrounding agents, guiding safer and more efficient navigation. Our approach is tested in both dynamic and static obstacle environments. To improve training efficiency and promote socially appropriate behaviors, Imitation Learning is employed. Comparative evaluations with state-of-the-art methods highlight the advantages of our approach, especially in enhancing safety by reducing collisions and preserving comfort distances. Results confirm the effectiveness of our learned policy and its ability to extract socially relevant knowledge in human–robot environments where social compliance is essential for deployment. Full article