Search Results (1,830)

Parenting practices involving violent discipline are a global health concern, particularly among low-income families. While the current literature offers general prevalence data, it lacks a comprehensive global perspective evaluating how diverse sociodemographic, cultural, and historical contexts intersect within disadvantaged households. This scoping review protocol aims to map the global evidence on parenting practices related to physical and psychological violence used as disciplinary practices against children within low-income contexts. Following the JBI Manual for Evidence Synthesis and PRISMA-ScR guidelines, we will conduct a comprehensive search across databases, including MEDLINE/PubMed (via the National Library of Medicine), CINAHL (EBSCO), APA PsycINFO (APA), Embase (Elsevier), ERIC, IBECS (via the VHL) and the WHO Global Index Medicus to capture global evidence published in recent years. Studies published in English, Portuguese, and Spanish between January 2015 and June 2026 that report violent disciplinary practices by parents or caregivers of children aged 1–8 years will be included. Rayyan software will assist with study selection. Mapping these practices across diverse socioeconomic settings may clarify current research gaps and synthesize the characteristics of families globally, shifting the interpretation of violent discipline from isolated parental choices to broader understanding of its social determinants and providing a clearer baseline to support future child protection research. Full article

Background/objectives: This study aimed to identify and categorise the educational, training, and support needs of informal caregivers of stroke survivors in order to inform the development of an Immersive Virtual Reality (IVR) intervention within the European caregIVR project (Project No. 101129454; EU4Health Programme). Methods: A qualitative descriptive study was conducted using three focus groups involving informal caregivers, healthcare professionals and other stakeholders, and academics and healthcare students in Portugal (n = 33). Discussions explored everyday caregiving challenges, priority educational needs, and expectations regarding digital support tools. Data were analysed using qualitative content analysis with an inductive–deductive coding strategy supported by NVivo software (version 14). Results: Participants identified the transition from hospital to home as the most critical stage of the caregiving journey, characterised by poor continuity of care and insufficient preparation before hospital discharge. Major challenges included limited stroke-related health literacy, difficulties adapting the home environment, and substantial emotional, financial, and social burdens that frequently resulted in social isolation and caregiver burnout. Participants regarded IVR as a promising educational strategy for delivering practical, repetitive, and low-risk skills training. Conclusions: The findings suggest that caregiver empowerment should be promoted through progressive, person-centred, and non-judgemental educational programmes tailored to caregivers’ evolving needs. Caregivers should be supported by multidisciplinary teams capable of addressing the clinical, practical, and psychosocial complexity of post-stroke home care. Rather than replacing professional support, IVR should be considered a complementary educational tool with the potential to improve caregivers’ preparedness, confidence, and safety in the home-care setting. Full article

Background: Adolescent boys often lack adequate menstrual education, leaving them susceptible to harmful sociocultural influences and reinforcing discriminatory attitudes. The purpose for this study was to explore adolescent boys’ knowledge, sociocultural beliefs, and attitudes toward menstruation. Methods: A descriptive-phenomenological qualitative study was conducted, involving 25 in-depth interviews with adolescent boys enrolled in senior high school (eligibility age range 14–19 years; achieved sample aged 15–19 years) from five districts in Ghana’s Volta Region. Participants were purposively sampled to ensure diverse perspectives. Semi-structured interviews explored knowledge sources, sociocultural influences, and attitudes toward menstruation. Data were analyzed thematically using Braun and Clarke’s six-phase framework with the aid of MAXQDA software. Results: Adolescent boys’ knowledge of menstruation was fragmented, stemming from family, school, and internet sources. Mothers were frequently cited as key informants, but misconceptions about menstruation persisted. Sociocultural and religious beliefs reinforced menstruation-related taboos, such as restrictions on cooking and entering sacred spaces, shaping discriminatory attitudes. Reactions to menstrual leaks varied from empathy to teasing. Conclusions: The findings highlight the need for inclusive menstrual education targeting boys and their families. Educational programs should include biological, emotional, and social aspects of menstruation to help reduce myths and nurture empathy. Full article

To thoroughly investigate the effects of high-impact weather and compound weather types on the triggering of severe influenza outbreaks and to effectively support the implementation of related weather risk forecasting services, methodologies from synoptic meteorology, climatology, medical statistics, time-lag effect, seasonally stratified correlation analysis, and SPSS (IBM SPSS Statistics 25) software were integrated, and severe influenza episodes in Langfang, China, were explored. The research encompasses the collection and processing of meteorological, influenza, and air pollution data; the study and analysis of the characteristics of severe influenza occurrences and associated meteorological conditions; the categorization of high-impact weather types, compound patterns, and their associated influenza distribution characteristics that induce severe influenza episodes; the analysis of the synergistic effects of air pollution coupled with high-impact weather events such as haze on triggering severe influenza; and the assessment of the effects of social prevention and control measures in mitigating severe influenza outbreaks. This study establishes an influenza risk forecasting grade based on high-impact weather classification, providing a scientific reference for the public to defend against influenza. Full article

The Post Office Horizon scandal represents one of the most severe miscarriages of justice in modern British legal history, rooted in the deployment of a defective IT system and the institutional suppression of evidence that exposed its unreliability. This paper provides a systematic analysis of the scandal through the combined lenses of cyber security, digital forensics, and IT governance, drawing directly on the Post Office Horizon Public Inquiry dataset—including witness testimony, technical documentation, audit records, and internal communications spanning more than two decades. While many of the technical and procedural failures discussed have been documented in prior scholarship, the paper’s principal contribution is the systematic mapping of those failures against recognised governance frameworks and the Legally Accountable Digital Systems (LADS) proposal this mapping motivates. We identify and analyse five interconnected failure categories: software defects and poor system design; deficient patch governance; inadequate audit logging and compromised evidence integrity; investigative failures and prosecutorial conflict of interest; and a systemic absence of technical expertise and independent oversight. Each category is mapped against nine governance framework documents, including ISO/IEC 27001, NIST SP 800-53 Rev. 5, NIST SP 800-218 (SSDF), COBIT 2019, ISO/IEC 27035, NIST SP 800-61, and ISO/IEC 27036, with ISO/IEC 27037 applied additionally to evidential handling failures and NIST SP 800-92 to log management failures. A counterfactual analysis indicates that compliance with these frameworks could plausibly have detected, exposed, or substantially reduced most of the documented failures, though this claim is necessarily inferential and conditional on good-faith implementation. The scandal was therefore not caused primarily by the absence of adequate frameworks but by their wholesale non-application and by institutional incentives, examined later in the paper, that can undermine even fully compliant controls. However, the analysis also surfaces a governance gap that no existing framework addresses: the institutional failure mode in which the organisation responsible for system integrity holds active incentives to suppress evidence of failure rather than remediate it. To address this gap, we propose the concept of Legally Accountable Digital Systems (LADS)—a governance category for systems whose outputs are used as evidence in legal proceedings—and outline three supplementary pillars: technical independence, institutional independence, and forensic admissibility governance. We draw a parallel with the Sarbanes–Oxley Act of 2002, arguing that the Horizon Inquiry dataset provides an equivalent empirical foundation for the statutory reform of digital evidence governance. Finally, we outline the substantial research opportunities the Inquiry dataset presents across IT systems analysis, cyber security, forensic accounting, social network analysis, and legal informatics—a resource comparable in significance to the Enron materials that shaped a generation of corporate governance reform. Full article

Carried out with 30 students enrolled in the Computer Technologies Department of a vocational school at a public university in Türkiye, this qualitative study examines university students’ perceptions and institutional expectations regarding the integration of sustainable artificial intelligence (AI) in universities. Data were collected through semi-structured interviews. The interview protocol was developed by the researchers and refined based on feedback from three field experts to ensure content validity. Before the main data collection, the interview form was reviewed and refined through an initial exploratory application with a small group of participants to assess the clarity and comprehensibility of the questions and to identify potential issues in the data collection process. The data analysis was conducted using qualitative content analysis supported by MAXQDA software. The findings indicate that students generally associate sustainable AI with energy efficiency, environmental responsibility, and ethical use of technology. Participants demonstrated awareness of large-scale AI systems’ environmental impacts. Although students viewed the development of environmentally friendly AI systems positively, they expressed concerns about ethical boundaries, excessive energy consumption, and the absence of clear regulatory frameworks. Overall, the findings suggest that structured content on the environmental, ethical, and social dimensions of AI should be integrated into vocational higher education curricula. Full article

Ambient Assisted Living (AAL) environments aim to enable older people to remain active and lead an autonomous and independent life for as long as possible. Among the technologies that can be incorporated into these settings, socially assistive robots (SAR) seek to establish a more natural and intuitive means of interaction with people, whilst helping them to carry out everyday tasks. One of the main challenges facing the design of these robots is how to enable them to undertake more complex tasks. Recent advances in Large Language Models (LLMs) have opened new avenues for flexible robot deliberation, yet their integration into real-time robotic systems remains challenging due to latency constraints, reasoning reliability, and the complexity of coordinating multi-step tasks. This paper proposes a hierarchical multi-agent architecture for robot deliberation that addresses these challenges by combining LLM-based planning with structured execution mechanisms within the ROS 2 ecosystem. The proposed architecture employs a supervisor agent that decomposes high-level natural language instructions into prioritised subtasks, enabling a priority-driven execution model that dynamically adapts to task relevance, temporal constraints, and environmental feedback. Subtasks are delegated to a set of Single-Purpose Agents (SPAs), orchestrated via LangGraph state machines and coordinated through a priority-aware scheduling mechanism. A key design principle is the use of Behaviour Trees (BTs) as high-level callable tools through the Model Context Protocol (MCP), encapsulating closed-loop control strategies while enabling preemptive and priority-consistent execution. This reduces the number of LLM inference steps required per task and improves robustness under dynamic conditions. A further contribution concerns the deployment of fine-tuned, lightweight LLMs—on the order of 0.6 billion parameters—specifically adapted for both the supervisor and the individual SPA roles through parameter-efficient low-rank adaptation (LoRA). These models are trained on role-specific tool-calling datasets to specialise in constrained reasoning patterns and task-specific decision-making, enabling efficient, low-latency inference directly on edge hardware. The combination of fine-tuning and hierarchical priority control enhances both the determinism and responsiveness of the system while mitigating error propagation across agent interactions. The paper presents the full software architecture, a formal characterisation of the system as a priority-aware hierarchical policy over a graph of agent workflows, and an experimental evaluation in an Ambient Assisted Living scenario assessing task success rate, inference efficiency, responsiveness under competing priorities, and overall user experience. Because SPA execution is decoupled from the supervisor’s own reasoning loop, the architecture is designed to keep accepting, processing, and queuing new user queries while previously dispatched SPAs are still executing their tasks. Full article

The integration of artificial intelligence (AI) and data science into organizational evaluation practices creates socio-technical systems in which human rating behavior, organizational templates, regulatory pressure, and analytical algorithms jointly determine what can be measured and learned. This single-case study examines the measurement of Environmental, Social, and Governance (ESG) compliance in financial software engineering projects, treating one firm’s project evaluation practice as a socio-technical system and applying an open-source data science and machine learning workflow to 207 anonymized archival project records. Correlation analysis revealed near-unity associations between the stakeholder-rated social and governance factors and the overall project score (r = +0.995 and +0.966, p < 0.001), while the environmental factor was unrelated to the score; post-hoc diagnostics (a seven-component principal-component structure, Harman’s screen, selective near-zero same-source correlations, and marker-variable partial correlations) bind, but cannot eliminate, method-based explanations, so the coefficients are interpreted as a descriptive property of the firm’s evaluation system rather than as estimates of relationships between validated, distinct constructs. Exploratory machine learning classifiers performed weakly—kNN at chance (AUC = 0.497) and SVM only modestly above the no-information baseline (accuracy 61.8%)—a result consistent with the constraints that the social subsystem imposes on the learnability of the records it generates, although technical factors, including the dichotomization of the target variable, the modest sample size, and model configuration, cannot be ruled out as contributing explanations; descriptive statistics are reported for all variables, and a diagnostic analysis reconciles the apparent divergence between the near-unity correlations and the weak classification performance by showing that the two rest on different feature sets, the near-redundant social and governance ratings having been withheld from the classifiers. The findings offer a proof of concept and a structured agenda for AI-enabled, project-level ESG measurement in socio-technical systems. Full article

Introduction: Tuberculosis [TB] and diabetes mellitus (DM) remain major public health concerns worldwide. TB negatively affects an individual’s glucose tolerance, increasing the risk of developing DM. Similarly, DM reduces the host’s ability to fight TB infection and increases the likelihood of developing TB and poor response to TB medication. This study analysed stigma and health-seeking behaviour in a sub-district of Accra Metropolis. Methods: We used a mixed-methods research approach involving a cross-sectional survey and in-depth interviews to explore community knowledge, stigma, and health-seeking behaviour related to TB and DM. A total of 437 individuals were selected for a survey using a simple random sampling technique, while 22 participants, including three TB patients, four nurses, one medical doctor, four students from a nursing and midwifery school, five students from a school of hygiene, and five community members, were involved in the study. Healthcare providers and patients were purposively selected, while students and community members were recruited through convenience sampling. Descriptive and logistic regression analyses were performed on the quantitative data using STATA, while the qualitative data were thematically analysed using the MAXQDA software. Results: Participants’ age, sex, and educational levels were significantly associated with their knowledge of TB and DM. Males were 0.600 times as likely as females to be knowledgeable about DM (95% CI: 0.386–0.934, p = 0.024). Social determinants of health, such as poverty, local beliefs, stigma, and negative attitudes from healthcare workers, may influence TB patients’ preference for traditional remedies over biomedical treatment. Conclusion: Therefore, we observed that addressing cultural barriers, stigma, and financial costs related to TB and diabetes care will help increase patients’ willingness for biomedical treatment. Full article

Recent years have seen explosive growth of both personal and professional use of large language models (LLMs). This article considers the impact of these developments on formal and informal cyber–social systems: the meta-systems created through integrative interactions between (groups of) humans and technological components. The analysis is based on Emergent Information Theory, a theoretical framework encompassing both biological and technological information systems. A qualitative distinction is demonstrated between LLM-based cyber–social systems and those involving other types of information technology such as expert systems and traditional fixed-function software. The article concludes with a discussion of the potential impact of this relatively new type of artificial intelligence on the future of cyber–social systems. Full article

Social Network Analysis (SNA) in peasant organizations in Cómbita, Colombia, examines how relationships between different actors influence organizational dynamics and the circulation of knowledge. Using a mixed approach, four peasant organizations were characterized through interviews and SNA using UCINET 6.0, KeyPlayer 2.0, and NetDraw 2.192 software to identify key actors, information flows, and structural indicators. The results show that the source actors tend to be external, especially entities such as SENA, input suppliers, and technical advisors, while producers play the main role as disseminators and coordinators within each organization. The indicators of density, average degree, geodesic distance, diameter, components, and centralization show variability among the networks: Tierra de Quesos and Acuadinámica show greater cohesion and internal communication. In contrast, El Olivo shows greater connection and decentralization. However, all networks show levels of fragmentation and dependence on certain strategic actors, which increases their organizational vulnerability. The results suggest that strengthening internal ties and diversifying coordinating actors could improve the adaptive capacity of these peasant organizations; establishing the effect of these strategies on organizational sustainability will require longitudinal evidence linking network structure to concrete sustainability outcomes. Full article

Grounded in Social Cognitive Theory, this study investigates how digital technologies shape employees’ work experiences and social life in digitally transforming hotel organizations. Specifically, it examines the role of digital empowering leadership in fostering digital work engagement through the mediating mechanisms of digital self-efficacy and digital thriving at work within five-star hotels in Egypt. As digital technologies increasingly redefine how employees interact, collaborate, and derive meaning from their work, understanding the human and social consequences of digital transformation has become a critical research priority. Data were collected from 394 full-time employees working in five-star hotels in Egypt and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with WarpPLS software. The findings reveal that digital empowering leadership significantly enhances employees’ digital work engagement, digital self-efficacy, and digital thriving at work. Furthermore, digital self-efficacy and digital thriving at work positively influence digital work engagement and partially mediate the relationship between digital empowering leadership and digital work engagement. By highlighting how digitally enabled leadership shapes employees’ psychological capabilities and flourishing in technology-rich workplaces, this study contributes to the growing literature on the social implications of digital technologies in organizational settings. The findings underscore that successful digital transformation extends beyond technological adoption to encompass employees’ empowerment, well-being, and meaningful engagement in digital work environments. Practical implications are provided for hotel managers seeking to cultivate human-centered digital workplaces that support employees’ social and psychological flourishing amid ongoing technological change. Full article

Background: Mental health conditions remain a major yet underrepresented public health concern in Pakistan and globally, highlighting the need for innovative and complementary interventions. Nature-based interventions (NBIs), which involve structured engagement with natural environments to enhance health and wellbeing, offer a promising approach, particularly in the Hazara Division of Khyber Pakhtunkhwa, Pakistan, a region renowned for its Himalayan forests, scenic valleys, and rich biodiversity. Methods: This study employed a qualitative descriptive design to explore mental health clinicians’ perceptions of NBIs in community mental health settings. Fourteen clinicians from the Hazara Division, Khyber Pakhtunkhwa, Pakistan, were recruited using purposive and snowball sampling between February and March 2026. Data were collected through semi-structured interviews and audio-recorded. Transcripts were analysed using inductive thematic analysis following Braun and Clarke’s framework, supported by HyperRESEARCH software. Results: Participants generally perceived engagement with nature as calming, restorative, and therapeutically beneficial, and many reported informally encouraging clients to participate in nature-related activities. Clinicians expressed willingness to integrate NBIs into routine practice and identified potential benefits including improved mood, relaxation, empowerment, and enhanced social connectedness. However, several barriers were also identified, including client-related factors such as anxiety, low motivation, and skepticism, as well as contextual and organisational constraints such as gender-based limitations in access to natural spaces and safety-related policies. Conclusions: Despite these challenges, clinicians demonstrated strong support for NBIs, suggesting their potential as a feasible adjunct to mental health care in Pakistan. Addressing identified barriers may facilitate integration into routine services and enhance access to holistic mental health support in community settings. Full article

Placing children in alternative care serves to safeguard their well-being while social workers work to resolve the issues that necessitated their removal from the home. Despite this intention, social workers face numerous difficulties when implementing family reunification services. This article explores the challenges encountered by social workers in South Africa in delivering these services. The study adopted an exploratory sequential mixed-methods design and involved social workers employed at five child protection organisations across the country. Data were gathered through 15 qualitative interviews and 127 completed questionnaires. Thematic analysis, guided by Creswell’s framework, was used to interpret the qualitative data, while quantitative data were processed using a statistical software package for social sciences (SPSS) version 23. The findings reveal a range of institutional, infrastructural, and human resource constraints that hinder effective service delivery. Social workers also reported difficulties arising from uncooperative biological parents and strained relationships between biological and foster parents, often marked by mistrust, suspicion, and hostility. At times, tensions also emerged between biological parents and social workers themselves. The study concludes that recognising these challenges creates an opportunity to address them more effectively. It recommends the development of a rights-based family reunification service model to guide and support social workers in providing timely and effective reunification interventions. Full article

Corporate governance is a complex, adaptive open system; yet it is usually modeled, in the classical agency tradition, as a closed matrix of legal and financial contracts. Adopting an open systems perspective, we decode the “social software”—the informal institutions—behind the wide variation in corporate governance across countries. At the heart of this system lies an element that comparative corporate governance research has largely overlooked: generalized trust. To our knowledge, ours is the first framework to unite open systems theory and generalized trust in explaining cross-country corporate governance. Drawing on the classic systems theory works of Ashby and Luhmann, we theorize trust as a systemic connector that absorbs complexity that formal rules would otherwise have to carry. Where trust carries that load, firms can govern through relationship-based collaboration rather than rule-based control. Using 4837 firm-year observations from 1293 firms in 23 countries (2003–2008)—a pre-crisis structural baseline—we document a robust negative association between trust and shareholder-oriented corporate governance: where trust is high, informal social regulation substitutes for formal control. The two cultural moderators—individualism and uncertainty avoidance—act on this connector in opposing directions. Individualism amplifies the substitution because monitoring conflicts with the desire for autonomy; uncertainty avoidance attenuates it because trust cannot supply the structural predictability that these cultures demand. Where individualism is high and uncertainty avoidance is low, formal control falls away steeply as trust rises; where that configuration is reversed, formal structures persist even when trust is abundant. Corporate governance architecture, these results suggest, is regulated by its surrounding cultural ecosystem—with trust as its central, and long-neglected, connector. Full article