Abstract Purpose: This paper draws on a sociological analysis of the 2024 Azerbaijan Airlines flight J2-8243 incident to critique the Conflict Zone Information Bulletin (CZIB) normative-bureaucratic safety protocol. Sociological theories referenced include: passive and active learning; latent and active error; systems-thinking; organisational accident and the Swiss cheese model of accident trajectory. The Azerbaijan Airlines Flight J2-8243 incident followed earlier shoot-downs. For example: Iran Air Flight 655; Malaysia Airlines Flight MH17; Ukraine International Airlines Flight PS752. Earlier shoot-downs confirmed the importance of risk-free routing.Design/methodology: The paper draws on authoritative secondary data, for example, the 2025 Preliminary Report published by Kazakhstan’s Commission for Aviation Investigation, to mount a critique of the Conflict Zone Information Bulletin (CZIB) normative-bureaucratic safety protocol. The paper: Describes the factors that contributed to the shoot-down; Tests the efficacy of normative-bureaucratic defences against shoot-downs, such as the sharing of information via International Civil Aviation Organisation (ICAO) Annex 13-compliant investigations and the issuing of CZIBs; Asks whether accident investigators pay sufficient attention to the social, economic and political context of a near-miss, incident, accident or shoot-down when establishing causation; Assesses the workload implications of considering the social, economic and political context of a near-miss, incident, accident or shoot-down.Findings: It is concluded that Azerbaijan Airlines failed to act on the relevant CZIB for two reasons. First, Azerbaijan’s government expected the airline to maintain an air bridge with its influential neighbour. While a private concern, Azerbaijan Airlines is the country’s de facto flag carrier, and is expected to act as such by the government. Secondly, the authoritarian character of Azerbaijan’s government discouraged the airline from questioning its government. It is concluded that the European Union’s CZIB normative-bureaucratic safety protocol is compromised by realpolitik without and within the aviation industry. Normative-bureaucratic safety protocols such as CZIBs may create a false sense of security, given this reality.Originality/value: To the best of the author’s knowledge, at the time this paper was written the 2024 Azerbaijan Airlines flight J2-8243 accident trajectory had not been subjected to a holistic, sociological analysis. The paper’s value lies in that fact that it examines the immediate and proximate causes of the flight J2-8243 incident through a powerful sociological lens that draws on the work of risk-management luminaries such as Professor James Reason, whose Swiss Cheese model of system failure is used by many aviation accident investigators.

SummaryBackground:Despite ongoing rabies control efforts in Arequipa, Peru—including mass dog vaccination campaigns and reactive ring interventions—the region has failed to reduce the number of rabid dogs, leading to the first reported human dog-mediated rabies case after 8 years. The gaps in the rabies control program and the complex dynamics among stakeholders are unknown.Objective:To integrate epidemiologic, socio-ecological, and policy data to identify the factors contributing to the 2023 human rabies case and propose strategies to make this a ‘never event’.Methods:We used stakeholder mapping and field quantitative and qualitative data to identify the roles and connections of key actors in rabies control, identifying gaps in their functions. We then applied the Swiss Cheese model to characterize the defense layers against dog-mediated rabies, highlighting critical vulnerabilities across these protective barriers.Conclusions:We identified multiple breaches in the defense against dog-mediated human rabies. Weak surveillance, insufficient dog vaccination, and inadequate management of free-roaming and feral dogs, coupled with bureaucratic inefficiencies, were key gaps. Outbreak responses were delayed and insufficient, and access to post-exposure prophylaxis (PEP) remained limited. Communication breakdowns exacerbated the problem. Systemic issues, such as outdated public health policies, insufficient training of health professionals, and fragmented efforts, further hindered timely exposure response. Dog ecology and demographic factors also contributed to dog rabies spread. These failures in policy, response, capacity, and external factors led to the 2023 human rabies case. Despite awareness of these challenges, the contributing conditions remain unchanged. Eliminating dog-mediated human rabies by 2030 will require targeted interventions, including enhanced surveillance, context-specific policy reforms, stronger community and institutional collaboration, and better management of free-roaming dogs.

This study assessed the relationship between team psychological safety and patient safety event and error reporting among nurses in a tertiary hospital during the last quarter of 2025. A descriptive–correlational design was employed, using complete enumeration that yielded responses from 437 nurses. The study utilized an adapted version of Edmondson’s Psychological Safety Scale (1999) and selected dimensions of the Hospital Survey on Patient Safety Culture. Data were analyzed using descriptive statistics, chi-square tests, Cramer’s V, and Pearson r to determine relationships among demographic profile, psychological safety, and incident reporting. Results showed a moderate level of team psychological safety and a high overall level of patient safety event reporting, with lower scores observed in near-miss reporting and non-punitive response to error. Significant relationships were found between demographic variables and both psychological safety and reporting behaviors. Team psychological safety demonstrated significant positive correlations with frequency of events reported, non-punitive response to error, communication openness, and overall reporting levels. These findings support Edmondson’s Theory of Psychological Safety and align with Reason’s Swiss Cheese Model, highlighting the role of supportive team environments in strengthening patient safety. A Psychological Safety and Incident Reporting Enhancement Plan is proposed to address identified gaps and strengthen the hospital’s safety culture.

This study examines how safety training affects both the frequency of workplace accidents and the duration of accident-free intervals in high-risk construction settings. Based on a 36-month dataset from six major firms, workers were divided into four groups according to training type: specialized, general, informal, or none. Using a combined methodological approach—Poisson regression, multivariate Poisson modeling, and Weibull survival analysis—the study quantifies the impact of training on both the likelihood and timing of accidents. Specialized training was associated with up to a 50% reduction in accident frequency and nearly doubled the length of safe intervals (k < 1), particularly in high-rise construction projects. General training showed moderate effects, while informal or absent training had minimal impact, with hazard rates remaining stable or rising. Drawing on Heinrich’s Safety Pyramid and Reason’s Swiss Cheese Model, and validated through AIC, BIC, and likelihood ratio tests, the findings suggest that structured safety programs lead to meaningful, lasting behavioral change. The study advocates for task-specific, technology-enhanced training—such as virtual reality and wearables—as essential components of modern safety strategies in complex construction environments.

Airport airspace safety is increasingly threatened by small, unmanned aircraft systems and wildlife that traditional radar cannot detect. While earlier reviews addressed general counter-UAS techniques, individual sensors, or the detection of single objects such as birds or drones, none has systematically reviewed airport-based, multi-sensor surveillance strategies through a safety-theoretical lens. A systematic review, performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 statement, synthesized recent research on fixed, ground-based aerial detection capabilities for small aerial hazards, specifically unmanned aircraft systems (sUAS) and avian targets, within operational airport environments. Searches targeted English-language, peer-reviewed articles from 2016 through 2025 in Web of Science and Scopus. Due to methodological heterogeneity across sensor technologies, a narrative synthesis was executed. The review of thirty-six studies, analyzed through Reason’s Swiss Cheese Model and Endsley’s Situational Awareness framework, found that only layered multi-sensor fusion architectures effectively address detection gaps for Low-Slow-Small (LSS) threats. Based on these findings, the review proposes seamless integration with Air Traffic Management (ATM) and UAS Traffic Management (UTM) systems through standardized data-exchange interfaces, complemented by theoretically grounded risk-based deployment strategies aligning surveillance technology tiers with operational risk profiles, from basic Remote ID receivers in low-risk rural environments to comprehensive multi-sensor fusion at high-density hubs, major airports, and urban vertiports.

Universities can neither ban nor ignore generative AI (GenAI); they must govern and design for it. This paper argues that the core challenge is not ‘cheating’ per se but the misalignment between legacy assessment designs and AI-mediated learning. We contribute (1) a practical, tiered governance model that aligns policy, pedagogy, and assessment operations; (2) an assessment redesign heuristic that integrates authenticity, cognitive demand, and evidence provenance; and (3) a risk-mitigation view adapted from the Swiss-cheese model that places student learning, rather than surveillance, at the centre of integrity work. Building on recent philosophical critiques of instrumental responses to GenAI in education, we position assessment as a socio-technical system where teacher judgement, student agency, and tool affordances co-evolve. We illustrate the approach with ready-to-adopt patterns (e.g. oral defence with artefact trail; cohort-specific data briefs; constrained-tools practicals) and specify implementable governance levers (role clarity, template language, moderation workflows, analytics). The result is a coherent pathway ‘beyond bans’ toward trustworthy assessment that is educative, fair, and feasible at scale.

Applications of the Injury Equity Framework to Address Pediatric Injury Inequities.

This paper examines the ethical implementation of mask mandates as a pandemic mitigation measure in the context of the ongoing SARS-COV-2 (COVID-19) pandemic and how mask mandates benefit disabled and immunocompromised individuals as well as the general public. Using the Kass Ethical Framework, this paper explores the ethical tensions present in public health when it comes to pandemic mitigation using the Swiss Cheese Model of Pandemic Mitigation as a guide to determine how to approach pandemic mitigation from a multilayered perspective. This paper makes clear that mask mandates have been effective in reducing transmission of COVID-19 and that they are a necessary public health strategy to protect disabled and immunocompromised individuals while providing massive benefits for society at large. Furthermore, this paper will examine ethical concerns often raised when mask mandates are discussed such as economic, accessibility, and enforcement concerns with solutions highlighted to address such concerns such as resource redistribution efforts like mask blocs. While mask mandates have been highly controversial, this paper argues that such mandates are necessary and ethical to keep populations safe, especially when concerns over equity are considered.Given the recent confirmation of vaccine and pandemic denialists such as Robert F. Kennedy Jr., mask mandates and other pandemic mitigation measures must be revisited and discussed. The election of Donald Trump in November of 2024 and the attempts at appointing political directors with questionable scientific backgrounds, especially at the same time as H5N1 is emerging as a viable threat, makes this the time to discuss mask mandates and other pandemic mitigation measures with a focus on disabled and immunocompromised individuals who are at most need of protecting from both the ongoing COVID-19 pandemic and any other emerging pandemics.

A layered strategy for tackling antimicrobial resistance: the Swiss cheese model for policy, prevention, and engagement.

This study aims to solve a critical limitation in conventional fragmented risk assessments: the failure to engineer a link between technical failures and organizational safety culture. To address this, an integrated safety model for a hydrogen vent system was developed using the MBSE methodology. The core contribution of this research is the proposal of an 'Integrated Safety Analysis Profile (ISAP)', which engineeringly implements James Reason's 'Swiss Cheese Model'. This profile formally links 'Latent Conditions (<<LatentCondition>>)' and 'Active Failures (<<ActiveFailure>>)' within a SysML model. This framework secures Risk Traceability on a 'Single Source of Truth (SSOT)' model for the entire pathway: 'Safety Culture' (Root Cause) → 'Technical Failure' (Direct Cause) → 'Safety Requirement Violation' (Accident Consequence). It provides a novel methodological foundation for the integrated management of technical design and organizational safety culture.

Turn Around activities in the oil and gas industry involve the mobilization of thousands of temporary contract workers with non-technical backgrounds who face extreme and risky working environments, creating a high potential for work accidents that threaten lives and the operational sustainability of strategic national refineries. This study aims to analyze the influence of the work environment, occupational safety and health (OSH) training, work experience, and education level on work accidents, considering the mediating role of unsafe actions as manifestations of risky behavior that directly trigger incidents. An explanatory quantitative approach was applied through Structural Equation Modeling-Partial Least Squares, involving 242 Turn Around worker respondents to test a complex structural model. The results reveal significant findings where unsafe actions are proven to be the dominant predictor of workplace accidents, while work experience actually increases the risk of accidents both directly and through the mediation of unsafe actions due to the phenomena of overconfidence and complacency. OSH training and education levels, which should be protective, significantly increased unsafe actions because they created an illusion of competence without real practical skills, while the work environment had a direct effect on accidents but not through behavioral mediation. The academic contribution of the research lies in the empirical validation that in the ultra-complex petrochemical industry system, the Normal Accident Theory and Swiss Cheese Model are more relevant than the classic individual approach, while the practical contribution is the recommendation for a fundamental transformation of the safety management system from a quantitative-formalistic approach to the quality of interventions that are contextual to the actual operational complexity. The study concludes that workplace accidents in the context of Turn Around are the result of systemic interactions between organizational failures in providing relevant training, the mismatch between worker competencies and task demands, and the normalization of risky behavior reinforced by overconfidence from pseudo-experience and inapplicable education.

A comprehensive analysis of the systemic causes of safety accidents in sports tourism on the Qinghai-Tibet Plateau is significant for high-quality development. Utilizing 32 verified accident cases (2010–2025) in the Tibet Autonomous Region of China, this study extracted six critical factors through content analysis: organizational professionalism, rescue capacity, management systems, natural environment, tourist vulnerability, and tourist behavior. The Swiss Cheese Model (SCM) analyzed latent/active failures through case reports and regional environmental data, while the fuzzy-set Qualitative Comparative Analysis (fsQCA) deciphered nonlinear configuration paths across six factors. The results reveal that sports tourism accidents in Tibet arise from the coupling of multiple factors. Specifically, the combination of six influencing factors constitutes the causal paths for severe and general accidents. Among these factors, environmental factors and tourist characteristics are key contributors to accidents. Based on these findings, it is essential to establish a sports tourism risk prevention system for Tibet, which should comprise four layers: natural defense, behavioral defense, managerial defense, and rescue defense. This study deepens the understanding of sports tourism safety accidents on the Qinghai-Tibet Plateau. It integrates the SCM and the fsQCA method, contributing to sports tourism safety research. The proposed risk prevention system provides useful references for local safety management. Future research can focus on the dynamic changes of influencing factors and test the research framework and risk prevention system’s applicability in other similar areas.

Blocking the Holes: A Systems-Based Approach to Error Prevention in the Operating Room Using the Swiss Cheese Model.

Although "Failure to Rescue" (FTR) has been widely studied in general healthcare contexts, and a few clinical specialties, its definition and implications remain underexplored within maternal health, particularly given the heightened risks for marginalized women. The quality measure was retired as a national quality metric before formal adoption into obstetric care, leaving significant gaps in maternal patient safety. High rates of preventable maternal morbidity and mortality, highlight the urgent need to explore and define this concept specifically within maternal health. To conduct a concept analysis of FTR in obstetrics, examining systemic patient safety failures using both Charles Vincent's patient safety framework and Reason's Swiss Cheese Model of human error, and propose strategic improvements for maternal care delivery. A comprehensive literature search guided by Walker and Avant's concept analysis method was performed, synthesizing evidence from multidisciplinary sources on failure to rescue, and maternal morbidity, and mortality on national patient safety. A systematic review of obstetric and patient safety literature was conducted using PubMed, CINAHL, MEDLINE, Google Scholar, and The Cochrane Library. In total, 30 articles met the inclusion criteria, including those outside of U.S. health systems. Key themes relating to system failures, nurse staffing, and obstetric complications were extracted to refine FTR's defining attributes, antecedents, and outcomes for maternal care. Analysis revealed FTR in obstetrics involves multiple, intersecting system-level breakdowns rather than isolated provider errors. The failure to rescue factors identified include inadequate recognition of clinical deterioration, delayed escalation of care, fragmented interdisciplinary communication, and biases exacerbating health disparities. Amber Rose Isaac's model case exemplified intersection of the following factors: critical lab results were missed, warnings of severe complications were ignored, and pandemic-induced care constraints further compromised and compounded timely intervention. Although the formal FTR measure was retired prior to adoption in obstetrics, addressing many of the underlying systemic failures described in this analysis is essential. Integrating proactive, standardized maternal early-warning systems, surveillance monitoring systems, and robust policies to ensure equitable care is crucial. Re-envisioning maternal safety through the lens of FTR not only addresses immediate clinical gaps, but also aligns healthcare practice with its fundamental ethical duty to protect every woman, family, and community from preventable harm.

There are numerous ways to improve the quality of healthcare services, and Quality Improvement (QI) tools play a central role in this. These tools are essential for identifying problems, reducing errors and costs, modifying practices, generating innovative ideas, acquiring and analysing data, visualising issues, and supporting decision-making. Using them effectively promotes healthcare quality, patient safety, and optimal resource utilisation. Despite the importance of QI tools, the lack of systematic and comprehensive data on the frequency and purpose of their use in healthcare facilities constitutes the main problem area of this study. This descriptive and cross-sectional study examines the frequency and purpose of QI tool usage among quality managers in hospitals across Türkiye. The study population comprised quality managers from 248 hospitals who fully completed the survey. It focused on the use of 18 widely recognised QI tools, including Brainstorming, Fishbone Diagram, Five Whys, Flowchart, Control Chart, PDCA Cycle, FMEA, Histogram, Scatter Diagram, Process Mapping, and others. The results indicated that the least known tools were the Swiss Cheese Model, Spaghetti Diagram, Six Thinking Hats, House of Quality, Mapping the Last Ten Patients, Tree Diagram, and Pareto Chart. Conversely, Brainstorming, Fishbone Diagram, Five Whys, and Flowcharts were the most frequently used. QI tools were primarily used for generating ideas, visualisation, identifying problems, and analysing them. Significant differences in tool usage were observed based on experience in healthcare and quality roles. The findings underscore the complementary nature of QI tools and the need for enhanced training and awareness.

Hospitals, though essential for healing, are fraught with risks, and errors are more common than previously thought. In high-income countries, about 1 in 10 patients experience adverse events, while low- and middle-income nations face 134 million unsafe care incidents annually, contributing to 2.6 million deaths. Traditional thinking blames individual errors, but this hinders open learning and accountability.Patient safety is the discipline focused on preventing harm through systems, procedures, and a culture that minimizes risks and fosters recovery from errors. It involves improving healthcare delivery by addressing safety issues at the "sharp end" (where care is provided) and the "blunt end" (upstream factors like system design and organization).Common sources of harm include medication errors, surgical mistakes, healthcare-associated infections, diagnostic errors, patient falls, venous thromboembolism, pressure ulcers, unsafe trans-fusions, patient misidentification, and unsafe injection practices. Patient harm is often due to a combination of system flaws, technological issues, human error, and patient-related factors.Achieving patient safety involves creating a culture of transparency, learning from adverse events, and implementing frameworks like the Swiss Cheese Model, which visualizes how errors pass through multiple layers of safety. Tools like root cause analysis (RCA) and Failure Modes and Effects Analysis (FMEA) help identify systemic issues and prevent future harm. Healthcare workers must collaborate in teams, emphasizing continuous learning and system redesign to improve patient safety. Building accountability, ensuring safe practices, and supporting healthcare professionals are essential for creating a safe, trustworthy healthcare system.

Human error is a leading cause of cybersecurity breaches, yet inconsistent reporting due to a lack of structured frameworks hinders mitigation. Analysis of five major 2024 cybersecurity reports (Verizon DBIR, IBM, ENISA, Microsoft, Global CISO Survey) reveals how human error is characterized and quantified. Significant inconsistencies, gaps, and ambiguities are identified in classifying “human error” across these sources. Current industry reporting lacks a standardized taxonomy, hampering comparison and effective mitigation strategy development. Drawing on established frameworks (e.g., HFACS, Swiss Cheese Model), integrating a formal human factors classification system into reporting is proposed to improve clarity and actionability. The need for an integrated systemic framework is underscored, calling for industry adoption of standardized human error classification to enable more effective cybersecurity strategies.

The waters of Raja Ampat in Papua are one of the world's top maritime tourism destinations, attracting over 30,000 tourists annually since 2020. However, the challenging geographical conditions, such as shallow coral reefs, strong sea currents, and busy speedboat traffic, significantly increase the risk of maritime accidents. According to the National Disaster Management Agency (BNPB), from 2012 to 2024, six incidents in the area caused serious accidents, including vessel damage and injuries. This study aims to analyze the risks of tourist speedboat accidents in Raja Ampat using three complementary risk assessment methods: the Swiss Cheese Model (SCM), interviews, and questionnaires. The Swiss Cheese Model identifies gaps in several layers, such as Environment and Weather, Vessel and Safety Equipment, Skills and Competence of Operators, and Tourism Safety Management and Regulations. The analysis shows that the skills and competence of boat operators are significant weaknesses in accident cases, and it recommends that boat operators in Raja Ampat participate in SCRB (Survival Craft and Rescue Boat) training and certification programs.

Background. Healthcare systems operate under high public demand for medical care and require ongoing improvement of organizational activities despite limited resources. These improvements can be achieved by applying lean manufacturing techniques and technologies. The purpose of the study is to assess the feasibility of utilizing incidents identified in medical organizations as an informational basis for implementing measures to eliminate losses and defects in the treatment and diagnostic processes. Materials and methods. The study analyzed open-access scientific sources databases such as PubMed, CyberLeninka, and eLibrary. It employed case study methods, the “5 Whys” approach, and the Swiss cheese model to describe how incidents can serve as a source of information for implementing lean technologies. Results. The collection and analysis of incidents represent effective tools for introducing lean manufacturing in healthcare. This approach allows one to identify and improve processes that lead to losses and unnecessary waste iof resources in medical organizations.

ABSTRACT Digital evidence is the most critical component in digital forensics, and its admissibility in court is very challenging. Although it carries a legal connotation, digital evidence involves scientific concepts, techniques, and methods and requires advanced IT knowledge, skills, and legal expertise to ensure its admissibility. This study aims to identify common patterns and possible factors contributing to DF deficiencies leading to inadmissible evidence. To understand the causes of failures, we use the Swiss cheese model, known as the accident causation model, proposed by Reason (2000). Our findings show that the inadmissibility of the evidence is the consequence of adverse events caused by the combination of human, environmental, hardware/software, and legal factors. We conclude that understanding the different types of mishaps and identifying the active failures and latent conditions can help forensic practitioners navigate complex situations and adapt to changing environments to create a more robust and reliable digital forensic practice.