Pub Date : 2026-01-19DOI: 10.1016/j.ssci.2026.107116
Meng Wei , Ying Cui , Jiaguo Liu
This study investigates the influencing factors of maritime accidents using a data-driven approach integrated with large language models (LLMs). First, DeepSeek V3 is utilized to extract data on humans, vessels, management, environment, time, and space from maritime accident reports. Second, the N-K model is applied to analyze coupled risks, revealing that the coupled risk value of the four factors is the highest, with humans, vessels, and management being key factors, while the environmental factor exerts a significant impact in specific accidents. Further spatiotemporal analysis indicates phased temporal risks and spatially aggregated coastal risks. A significant nonlinear superposition effect is identified: high spatial risk amplifies the marginal contribution of temporal risk increases, while low-level coupling significantly reduces overall risk. The study culminates in proposing a dynamic collaborative governance framework. This framework leverages an integrated cognitive architecture, powered by LLMs, to transform unstructured data into actionable risk intelligence, enabling graduated intervention protocols and optimized resource allocation for enhanced maritime safety management.
{"title":"Unveiling the influencing factors of maritime accidents through data-driven approaches: leveraging large language model tools","authors":"Meng Wei , Ying Cui , Jiaguo Liu","doi":"10.1016/j.ssci.2026.107116","DOIUrl":"10.1016/j.ssci.2026.107116","url":null,"abstract":"<div><div>This study investigates the influencing factors of maritime accidents using a data-driven approach integrated with large language models (LLMs). First, DeepSeek V3 is utilized to extract data on humans, vessels, management, environment, time, and space from maritime accident reports. Second, the N-K model is applied to analyze coupled risks, revealing that the coupled risk value of the four factors is the highest, with humans, vessels, and management being key factors, while the environmental factor exerts a significant impact in specific accidents. Further spatiotemporal analysis indicates phased temporal risks and spatially aggregated coastal risks. A significant nonlinear superposition effect is identified: high spatial risk amplifies the marginal contribution of temporal risk increases, while low-level coupling significantly reduces overall risk. The study culminates in proposing a dynamic collaborative governance framework. This framework leverages an integrated cognitive architecture, powered by LLMs, to transform unstructured data into actionable risk intelligence, enabling graduated intervention protocols and optimized resource allocation for enhanced maritime safety management.</div></div>","PeriodicalId":21375,"journal":{"name":"Safety Science","volume":"197 ","pages":"Article 107116"},"PeriodicalIF":5.4,"publicationDate":"2026-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145993595","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-15DOI: 10.1016/j.ssci.2026.107114
Hsuan-Hao Lo , Sheuwen Chuang , Cheng-Yu Lin
As organizations navigate an era of unprecedented disruption, organizational resilience has emerged as a critical capability, prompting corresponding growth in instruments for its measurement. This paper explores the organizational resilience measurement (ORM) literature through a scoping review, systematically mapping the origins, evolution, and features of its primary instruments. We searched three academic databases (Scopus, Web of Science, PubMed) for literature published through February 2025, augmented by a manual review of seminal publications, yielding a final corpus of 55 articles. Our findings indicate a field dominated by two instruments: the Resilience Assessment Grid (RAG) (49.1%) and the Benchmark Resilience Tool (BRT) (20.0%). Application of these tools is highly concentrated, with the healthcare sector accounting for 36.4% of studies. Comparative analysis reveals that the two dominant tools represent distinct philosophical approaches: RAG offers contextual, in-depth diagnosis of system potentials, while BRT provides standardized, cross-organizational benchmarking of organizational management. The study concludes that the ORM field may be maturing and consolidating around a two-paradigm model, raising intriguing questions about whether sequential integration of these instruments could offer advantages beyond their individual applications.
随着组织在一个前所未有的颠覆时代中航行，组织弹性已经成为一种关键能力，促使其测量工具的相应增长。本文通过对组织弹性测量（ORM）的范围回顾，系统地描绘了其主要工具的起源、演变和特征，探索了ORM的文献。我们检索了三个学术数据库（Scopus, Web of Science, PubMed），检索了截至2025年2月发表的文献，并通过对开创性出版物的人工审查进行了扩充，最终获得了55篇文章的语料库。我们的研究结果表明，该领域由两种工具主导：弹性评估网格（RAG）（49.1%）和基准弹性工具（BRT）（20.0%）。这些工具的应用高度集中，医疗保健部门占研究的36.4%。对比分析表明，这两种主要工具代表了不同的哲学方法：RAG提供了对系统潜力的情境性、深度诊断，而BRT提供了组织管理的标准化、跨组织基准。该研究的结论是，ORM领域可能正在围绕两范式模型走向成熟和巩固，这提出了一个有趣的问题，即这些工具的顺序集成是否可以提供超越其单独应用的优势。
{"title":"A scoping review of organizational resilience measurement – instruments, indicators, and implications","authors":"Hsuan-Hao Lo , Sheuwen Chuang , Cheng-Yu Lin","doi":"10.1016/j.ssci.2026.107114","DOIUrl":"10.1016/j.ssci.2026.107114","url":null,"abstract":"<div><div>As organizations navigate an era of unprecedented disruption, organizational resilience has emerged as a critical capability, prompting corresponding growth in instruments for its measurement. This paper explores the organizational resilience measurement (ORM) literature through a scoping review, systematically mapping the origins, evolution, and features of its primary instruments. We searched three academic databases (Scopus, Web of Science, PubMed) for literature published through February 2025, augmented by a manual review of seminal publications, yielding a final corpus of 55 articles. Our findings indicate a field dominated by two instruments: the Resilience Assessment Grid (RAG) (49.1%) and the Benchmark Resilience Tool (BRT) (20.0%). Application of these tools is highly concentrated, with the healthcare sector accounting for 36.4% of studies. Comparative analysis reveals that the two dominant tools represent distinct philosophical approaches: RAG offers contextual, in-depth diagnosis of system potentials, while BRT provides standardized, cross-organizational benchmarking of organizational management. The study concludes that the ORM field may be maturing and consolidating around a two-paradigm model, raising intriguing questions about whether sequential integration of these instruments could offer advantages beyond their individual applications.</div></div>","PeriodicalId":21375,"journal":{"name":"Safety Science","volume":"196 ","pages":"Article 107114"},"PeriodicalIF":5.4,"publicationDate":"2026-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145977375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-14DOI: 10.1016/j.ssci.2025.107109
Jan Hayes , Martin Inge Standal , Kristine Vedal Størkersen , Sarah Maslen
Standardization committees and their chairs sit at the center of standard development, and have influence over the standards’ scope, level of ambition, and framing. However, little is known about how the standard chairs themselves conceptualize and develop the standards. Situated in the literature on standardization and riskwork, we address what standard chairs see as the primary purpose of the standard for which they are responsible, how they conceptualize the usage of the standard, and the implications of their practice for risk management in general. We adopted a collated fieldwork approach, drawing together semi-structured interviews from two studies to look at the accounts of three standard chairs in Australia (AS 2885.6) and Norway (NORSOK Z-013 and NS 5814). We show how all chairs seek to influence the riskwork of direct users of the standards and senior managers. The chairs also emphasize the importance of expert judgement and reflecting on the inherent uncertainty in risk analyses. Chairs view the standards as frameworks rather than prescriptive methods. A good standard thus enables expert judgement, management decision making, and local adaptations while also establishing a rigorous process in risk management. This has implications for selection of standard chairs and for theoretical considerations of what it means to standardize.
{"title":"The three chairs: How the leaders of risk standards committees influence decision-making and accountability","authors":"Jan Hayes , Martin Inge Standal , Kristine Vedal Størkersen , Sarah Maslen","doi":"10.1016/j.ssci.2025.107109","DOIUrl":"10.1016/j.ssci.2025.107109","url":null,"abstract":"<div><div>Standardization committees and their chairs sit at the center of standard development, and have influence over the standards’ scope, level of ambition, and framing. However, little is known about how the standard chairs themselves conceptualize and develop the standards. Situated in the literature on standardization and riskwork, we address what standard chairs see as the primary purpose of the standard for which they are responsible, how they conceptualize the usage of the standard, and the implications of their practice for risk management in general. We adopted a collated fieldwork approach, drawing together semi-structured interviews from two studies to look at the accounts of three standard chairs in Australia (AS 2885.6) and Norway (NORSOK Z-013 and NS 5814). We show how all chairs seek to influence the riskwork of direct users of the standards and senior managers. The chairs also emphasize the importance of expert judgement and reflecting on the inherent uncertainty in risk analyses. Chairs view the standards as frameworks rather than prescriptive methods. A good standard thus enables expert judgement, management decision making, and local adaptations while also establishing a rigorous process in risk management. This has implications for selection of standard chairs and for theoretical considerations of what it means to standardize.</div></div>","PeriodicalId":21375,"journal":{"name":"Safety Science","volume":"196 ","pages":"Article 107109"},"PeriodicalIF":5.4,"publicationDate":"2026-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145977377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-13DOI: 10.1016/j.ssci.2026.107112
Huiling Hu , Tingting Feng , Hui Ge , Jiashuai Li , Xue Wu , Xuanna Wu
Objective
To investigate how novice Intensive Care Unit (ICU) nurses engage cognitive control mechanisms when managing multitasking conflicts of differing severity, and how risk awareness modulates these processes.
Background
Digital transformation in healthcare has introduced more technological systems into ICUs, heightening multitasking demands and cognitive load. Novice nurses, lacking well-developed clinical schemas, rely more on executive control. Understanding how cognitive control is deployed—and how individual risk awareness shapes these processes—is essential for safeguarding patient safety in high-risk environments.
Design
EEG-based experimental study.
Methods
Twenty-six novice ICU nurses participated in a simulated technologically-induced multitasking paradigm. Behavioral accuracy, response times, and EEG measures (P1/P3 components, oscillatory power in alpha, beta, and theta bands) were recorded. Risk awareness was assessed via self-report scales.
Results
Nurses achieved higher accuracy in high-severity tasks, though response times did not differ significantly. ERP analyses showed significantly lower P1 peak amplitudes for high-severity tasks, particularly among nurses with higher risk awareness. Time–frequency analyses revealed greater alpha, beta, and theta power during low-severity tasks, suggesting increased cognitive flexibility under lower demands. Significant task severity × risk awareness interactions indicated that individuals with higher risk awareness deployed more targeted neural resources under high-severity conditions.
Conclusions
Task severity and individual risk awareness jointly shape cognitive control in technologically mediated multitasking among novice ICU nurses. These findings highlight the importance of integrating neurocognitive evidence into simulation-based training and interface design to strengthen nurses’ attentional management, reduce error risks, and enhance patient safety in the digital age of healthcare.
{"title":"Differential cognitive control in response to task severity during technologically-induced concurrent multitasking: The role of risk awareness in ICU nurses","authors":"Huiling Hu , Tingting Feng , Hui Ge , Jiashuai Li , Xue Wu , Xuanna Wu","doi":"10.1016/j.ssci.2026.107112","DOIUrl":"10.1016/j.ssci.2026.107112","url":null,"abstract":"<div><h3>Objective</h3><div>To investigate how novice Intensive Care Unit (ICU) nurses engage cognitive control mechanisms when managing multitasking conflicts of differing severity, and how risk awareness modulates these processes.</div></div><div><h3>Background</h3><div>Digital transformation in healthcare has introduced more technological systems into ICUs, heightening multitasking demands and cognitive load. Novice nurses, lacking well-developed clinical schemas, rely more on executive control. Understanding how cognitive control is deployed—and how individual risk awareness shapes these processes—is essential for safeguarding patient safety in high-risk environments.</div></div><div><h3>Design</h3><div>EEG-based experimental study.</div></div><div><h3>Methods</h3><div>Twenty-six novice ICU nurses participated in a simulated technologically-induced multitasking paradigm. Behavioral accuracy, response times, and EEG measures (P1/P3 components, oscillatory power in alpha, beta, and theta bands) were recorded. Risk awareness was assessed via self-report scales.</div></div><div><h3>Results</h3><div>Nurses achieved higher accuracy in high-severity tasks, though response times did not differ significantly. ERP analyses showed significantly lower P1 peak amplitudes for high-severity tasks, particularly among nurses with higher risk awareness. Time–frequency analyses revealed greater alpha, beta, and theta power during low-severity tasks, suggesting increased cognitive flexibility under lower demands. Significant task severity × risk awareness interactions indicated that individuals with higher risk awareness deployed more targeted neural resources under high-severity conditions.</div></div><div><h3>Conclusions</h3><div>Task severity and individual risk awareness jointly shape cognitive control in technologically mediated multitasking among novice ICU nurses. These findings highlight the importance of integrating neurocognitive evidence into simulation-based training and interface design to strengthen nurses’ attentional management, reduce error risks, and enhance patient safety in the digital age of healthcare.</div></div>","PeriodicalId":21375,"journal":{"name":"Safety Science","volume":"196 ","pages":"Article 107112"},"PeriodicalIF":5.4,"publicationDate":"2026-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145977376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-10DOI: 10.1016/j.ssci.2025.107105
Courtney T Blondino , Karla M Téllez , Noémie Le Pertel , Ariel Joab Almazan , Lorna Friedman
Objectives
Psychosocial risk or work-related hazard can lead to harmful individual and organizational outcomes. This study used 2023 data collected in compliance with Mexico’s NOM-035-STPS-2018 regulation to characterize overall psychosocial risk by sex, generation, industry, and explore domain-specific psychosocial risk by industry.
Methods
Frequencies (n) and percentages (%) were reported to describe the distribution of psychosocial risk. Significant difference testing was done with the chi-square statistic to test for differences in overall psychosocial risk by risk factor (α < 0.05).
Results
Data from 58,994 employees from 67 organizations operating in Mexico that implemented NOM-035-STPS-2018 in 2023 were included. Approximately 27% of the sample had high or very high overall psychosocial risk. Males had significantly higher psychosocial risk than females (28.3% vs 25.5%, p < 0.05) and there was no difference in psychosocial risk by generation. The construction, energy, and manufacturing industry had the highest level of psychosocial risk for lack of control over work (29.8%), leadership (20.5%), violence (12.8%), performance recognition (12.3%), working conditions (13.0%), and work relationships (3.5%) relative to the other four industry categories.
Conclusions
NOM-035 presents a unique opportunity to explore psychosocial risk in Mexico’s employees. In 2023, there was no difference in psychosocial risk by generation, and psychosocial risk was highest in workers of blue-collar industries. More research is needed to further explore these associations to inform interventions for employers and regulatory bodies.
目的社会心理风险或与工作相关的危害可能导致有害的个人和组织结果。本研究使用符合墨西哥NOM-035-STPS-2018法规的2023年数据，按性别、年龄、行业划分整体社会心理风险特征，并按行业探索特定领域的社会心理风险。方法报告频率(n)和百分比（%）来描述心理社会风险的分布。采用卡方统计检验各危险因素对整体心理社会风险的差异（α < 0.05）。结果包括来自67家在墨西哥运营的组织的58,994名员工的数据，这些组织在2023年实施了nom -035- stp -2018。大约27%的样本具有高或非常高的整体社会心理风险。男性的社会心理风险显著高于女性（28.3% vs 25.5%, p < 0.05），而社会心理风险在代际上没有差异。相对于其他四个行业类别，建筑、能源和制造业在缺乏对工作的控制（29.8%）、领导（20.5%）、暴力（12.8%）、绩效认可（12.3%）、工作条件（13.0%）和工作关系（3.5%）方面的社会心理风险水平最高。结论：som -035为探索墨西哥雇员的社会心理风险提供了一个独特的机会。在2023年，各代人的社会心理风险没有差异，蓝领行业的社会心理风险最高。需要更多的研究来进一步探索这些关联，为雇主和监管机构的干预提供信息。
{"title":"Describing psychosocial risk in the Mexican working population by sex, generation, and industry: a cross-sectional study","authors":"Courtney T Blondino , Karla M Téllez , Noémie Le Pertel , Ariel Joab Almazan , Lorna Friedman","doi":"10.1016/j.ssci.2025.107105","DOIUrl":"10.1016/j.ssci.2025.107105","url":null,"abstract":"<div><h3>Objectives</h3><div>Psychosocial risk or work-related hazard can lead to harmful individual and organizational outcomes. This study used 2023 data collected in compliance with Mexico’s NOM-035-STPS-2018 regulation to characterize overall psychosocial risk by sex, generation, industry, and explore domain-specific psychosocial risk by industry.</div></div><div><h3>Methods</h3><div>Frequencies (n) and percentages (%) were reported to describe the distribution of psychosocial risk. Significant difference testing was done with the chi-square statistic to test for differences in overall psychosocial risk by risk factor (α < 0.05).</div></div><div><h3>Results</h3><div>Data from 58,994 employees from 67 organizations operating in Mexico that implemented NOM-035-STPS-2018 in 2023 were included. Approximately 27% of the sample had high or very high overall psychosocial risk. Males had significantly higher psychosocial risk than females (28.3% vs 25.5%, p < 0.05) and there was no difference in psychosocial risk by generation. The construction, energy, and manufacturing industry had the highest level of psychosocial risk for lack of control over work (29.8%), leadership (20.5%), violence (12.8%), performance recognition (12.3%), working conditions (13.0%), and work relationships (3.5%) relative to the other four industry categories.</div></div><div><h3>Conclusions</h3><div>NOM-035 presents a unique opportunity to explore psychosocial risk in Mexico’s employees. In 2023, there was no difference in psychosocial risk by generation, and psychosocial risk was highest in workers of blue-collar industries. More research is needed to further explore these associations to inform interventions for employers and regulatory bodies.</div></div>","PeriodicalId":21375,"journal":{"name":"Safety Science","volume":"196 ","pages":"Article 107105"},"PeriodicalIF":5.4,"publicationDate":"2026-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145925864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-10DOI: 10.1016/j.ssci.2026.107110
Haruka Ohba , Shinya Mizuno
This study proposes a mathematical optimization model based on the Capacitated Vehicle Routing Problem to support the efficient transport of ”Residents in Need of Assistance in Evacuation” — such as the elderly and persons with disabilities — during nuclear disasters. The target area is Omaezaki City, Shizuoka Prefecture in Japan, where geographic open data — including census data, elevation data from the Geospatial Information Authority of Japan, and OpenStreetMap — were integrated to construct realistic road networks reflecting road accessibility during disasters. In particular, assuming tsunami-induced road flooding, we evaluated the impact of elevation-based road access restrictions on evacuation plans and identifying Residents in Need of Assistance in Evacuation in areas difficult to access. The model was optimized using both a Mixed-Integer Linear Programming approach and a genetic algorithm, and the results showed that Gurobi outperformed Genetic Algorithm in terms of both solution quality and computation time. The proposed model enables the quantitative identification of regions with limited accessibility based on the spatial distribution of home-based Residents in Need of Assistance in Evacuation and terrain characteristics, providing a practical decision support framework for local governments in disaster response planning and resource allocation.
{"title":"Development of an evacuation transport model for residents in need of assistance in evacuation during nuclear disasters","authors":"Haruka Ohba , Shinya Mizuno","doi":"10.1016/j.ssci.2026.107110","DOIUrl":"10.1016/j.ssci.2026.107110","url":null,"abstract":"<div><div>This study proposes a mathematical optimization model based on the Capacitated Vehicle Routing Problem to support the efficient transport of ”Residents in Need of Assistance in Evacuation” — such as the elderly and persons with disabilities — during nuclear disasters. The target area is Omaezaki City, Shizuoka Prefecture in Japan, where geographic open data — including census data, elevation data from the Geospatial Information Authority of Japan, and OpenStreetMap — were integrated to construct realistic road networks reflecting road accessibility during disasters. In particular, assuming tsunami-induced road flooding, we evaluated the impact of elevation-based road access restrictions on evacuation plans and identifying Residents in Need of Assistance in Evacuation in areas difficult to access. The model was optimized using both a Mixed-Integer Linear Programming approach and a genetic algorithm, and the results showed that Gurobi outperformed Genetic Algorithm in terms of both solution quality and computation time. The proposed model enables the quantitative identification of regions with limited accessibility based on the spatial distribution of home-based Residents in Need of Assistance in Evacuation and terrain characteristics, providing a practical decision support framework for local governments in disaster response planning and resource allocation.</div></div>","PeriodicalId":21375,"journal":{"name":"Safety Science","volume":"196 ","pages":"Article 107110"},"PeriodicalIF":5.4,"publicationDate":"2026-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145925863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-09DOI: 10.1016/j.ssci.2025.107106
O. Lounsbury , L. Pickup , Riccardo Patriarca , Marit S. de Vos , Kate Preston , Mark Sujan
The Functional Resonance Analysis Method (FRAM) is a valuable tool for understanding and improving complex socio-technical healthcare systems. This Focused Mapping Review and Synthesis (FMRS) explores how the FRAM is used to produce knowledge and create insight about healthcare systems across three scientific communities: safety/engineering, human factors/cognitive science, and healthcare/health services research. We examined 33 included studies and identified key themes in how FRAM is applied within and across communities. The review highlights the critical role of knowledge brokers and boundary spanners in fostering interdisciplinary collaboration and knowledge transfer. There is limited epistemological clarity in most studies, which complicates cross-study comparisons and practical application. In addition, most studies are descriptive and do not develop actionable and robust interventions. We argue for greater transparency in epistemological positioning, methodological reflexivity, and the development of reporting guidelines to enhance the consistency and utility of FRAM studies. This review is a conceptual synthesis rather than a proof of concept. Future empirical studies should test whether explicit articulation of epistemological assumptions improves FRAM analyses, using the probes identified in this review as a starting point.
{"title":"The functional resonance analysis method in healthcare: How knowledge is produced within and across scientific communities","authors":"O. Lounsbury , L. Pickup , Riccardo Patriarca , Marit S. de Vos , Kate Preston , Mark Sujan","doi":"10.1016/j.ssci.2025.107106","DOIUrl":"10.1016/j.ssci.2025.107106","url":null,"abstract":"<div><div>The Functional Resonance Analysis Method (FRAM) is a valuable tool for understanding and improving complex socio-technical healthcare systems. This Focused Mapping Review and Synthesis (FMRS) explores how the FRAM is used to produce knowledge and create insight about healthcare systems across three scientific communities: safety/engineering, human factors/cognitive science, and healthcare/health services research. We examined 33 included studies and identified key themes in how FRAM is applied within and across communities. The review highlights the critical role of knowledge brokers and boundary spanners in fostering interdisciplinary collaboration and knowledge transfer. There is limited epistemological clarity in most studies, which complicates cross-study comparisons and practical application. In addition, most studies are descriptive and do not develop actionable and robust interventions. We argue for greater transparency in epistemological positioning, methodological reflexivity, and the development of reporting guidelines to enhance the consistency and utility of FRAM studies. This review is a conceptual synthesis rather than a proof of concept. Future empirical studies should test whether explicit articulation of epistemological assumptions improves FRAM analyses, using the probes identified in this review as a starting point.</div></div>","PeriodicalId":21375,"journal":{"name":"Safety Science","volume":"196 ","pages":"Article 107106"},"PeriodicalIF":5.4,"publicationDate":"2026-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145925865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-06DOI: 10.1016/j.ssci.2025.107108
Riana Steen , Stig O. Johnsen
Causality is central to accident investigation, shaping how events are reconstructed, accountability is assigned, and systemic improvements are identified. However, conventional investigations often emphasise procedural and technical sequences, overlooking relational and interpretive dynamics crucial for understanding how systems drift towards failure through the gradual erosion of shared understanding. To examine what this framing may overlook, we revisit the 2018 collision between the Norwegian frigate Helge Ingstad and the tanker Sola TS. We first used FRAM to reconstruct Work-as-Imagined (WAI) and then conducted a sensemaking-informed content analysis to examine Work-as-Done (WAD) based on official reports. While FRAM effectively clarified system function coupling and where variability arose, it offered limited insight into how interpretations diverged or why shared understanding was difficult to sustain. This two-stage analysis revealed critical discrepancies between formal expectations and actual meaning-making. These insights, together with theoretical considerations, informed the development of a four-layer maturity model. The four-layer maturity model, consisting of (i) technical causality, (ii) human performance, (iii) socio-technical interdependencies, and (iv) relational sensemaking grounded in Human Readiness Levels (HRL). This model, with its distinctive fourth analytical layer (iv), shifts attention from functional interactions to how coherence forms—or fails—under pressure. The case was then revisited solely to illustrate how the model reveals relational and interpretive dynamics not captured by functional analysis, thereby avoiding methodological circularity. It highlights silence, saturation, and fragmentation as indicators of a system losing its capacity to adapt its understanding, even when information is available and routines continue.
{"title":"A maturity model for accident investigation: beyond technical and functional analysis","authors":"Riana Steen , Stig O. Johnsen","doi":"10.1016/j.ssci.2025.107108","DOIUrl":"10.1016/j.ssci.2025.107108","url":null,"abstract":"<div><div>Causality is central to accident investigation, shaping how events are reconstructed, accountability is assigned, and systemic improvements are identified. However, conventional investigations often emphasise procedural and technical sequences, overlooking relational and interpretive dynamics crucial for understanding how systems drift towards failure through the gradual erosion of shared understanding. To examine what this framing may overlook, we revisit the 2018 collision between the Norwegian frigate Helge Ingstad and the tanker Sola TS. We first used FRAM to reconstruct Work-as-Imagined (WAI) and then conducted a sensemaking-informed content analysis to examine Work-as-Done (WAD) based on official reports. While FRAM effectively clarified system function coupling and where variability arose, it offered limited insight into how interpretations diverged or why shared understanding was difficult to sustain. This two-stage analysis revealed critical discrepancies between formal expectations and actual meaning-making. These insights, together with theoretical considerations, informed the development of a four-layer maturity model. The four-layer maturity model, consisting of (i) technical causality, (ii) human performance, (iii) socio-technical interdependencies, and (iv) relational sensemaking grounded in Human Readiness Levels (HRL). This model, with its distinctive fourth analytical layer (iv), shifts attention from functional interactions to how coherence forms—or fails—under pressure. The case was then revisited solely to illustrate how the model reveals relational and interpretive dynamics not captured by functional analysis, thereby avoiding methodological circularity. It highlights silence, saturation, and fragmentation as indicators of a system losing its capacity to adapt its understanding, even when information is available and routines continue.</div></div>","PeriodicalId":21375,"journal":{"name":"Safety Science","volume":"196 ","pages":"Article 107108"},"PeriodicalIF":5.4,"publicationDate":"2026-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145925862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-02DOI: 10.1016/j.ssci.2025.107099
Jeff M. Barrett, Jack P. Callaghan
Musculoskeletal injury risk is often assessed using models that assume damage accumulates linearly with loading. However, biological tissues may exhibit history-dependent changes in tolerance, particularly under repeated or variable loading. In this study, we propose a nonlinear cumulative damage model grounded in a mechanistic description of collagen fibril engagement and failure. The model predicts the evolving tissue tolerance over time, with damage rates governed by a Tobolsky-Eyring-type law modulated by prior damage history.
The model was calibrated using experimental fatigue data from functional spinal units and evaluated through a series of simulations designed to reflect common ergonomic exposures. These included constant-load cycling, variable-load sequences, and heavy-tailed loading distributions. Notably, the model predicts that tissue already compromised by prior loading is more susceptible to additional damage, even under identical external conditions—a form of path dependence not captured by the classical Miner-Palmgren rule.
Perturbation analysis reveals that commonly used fatigue models can be recovered as successive approximations of the proposed framework, offering a formal connection between linear cumulative load theory, including ergonomics tools like LiFFT, and our nonlinear formulation. This unifying perspective helps reconcile chronic and acute injury risk models and highlights the importance of accounting for load history and variability in injury risk assessments.
These findings suggest that ergonomic models should be sensitive not only to cumulative load, but also to its temporal structure and variability. Incorporating such nonlinearities could improve predictions of tissue failure and inform guidelines for safer task design.
{"title":"From cumulative exposure to failure: a unifying modelling framework for nonlinear tissue fatigue in ergonomics","authors":"Jeff M. Barrett, Jack P. Callaghan","doi":"10.1016/j.ssci.2025.107099","DOIUrl":"10.1016/j.ssci.2025.107099","url":null,"abstract":"<div><div>Musculoskeletal injury risk is often assessed using models that assume damage accumulates linearly with loading. However, biological tissues may exhibit history-dependent changes in tolerance, particularly under repeated or variable loading. In this study, we propose a nonlinear cumulative damage model grounded in a mechanistic description of collagen fibril engagement and failure. The model predicts the evolving tissue tolerance over time, with damage rates governed by a Tobolsky-Eyring-type law modulated by prior damage history.</div><div>The model was calibrated using experimental fatigue data from functional spinal units and evaluated through a series of simulations designed to reflect common ergonomic exposures. These included constant-load cycling, variable-load sequences, and heavy-tailed loading distributions. Notably, the model predicts that tissue already compromised by prior loading is more susceptible to additional damage, even under identical external conditions—a form of path dependence not captured by the classical Miner-Palmgren rule.</div><div>Perturbation analysis reveals that commonly used fatigue models can be recovered as successive approximations of the proposed framework, offering a formal connection between linear cumulative load theory, including ergonomics tools like LiFFT, and our nonlinear formulation. This unifying perspective helps reconcile chronic and acute injury risk models and highlights the importance of accounting for load history and variability in injury risk assessments.</div><div>These findings suggest that ergonomic models should be sensitive not only to cumulative load, but also to its temporal structure and variability. Incorporating such nonlinearities could improve predictions of tissue failure and inform guidelines for safer task design.</div></div>","PeriodicalId":21375,"journal":{"name":"Safety Science","volume":"196 ","pages":"Article 107099"},"PeriodicalIF":5.4,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-29DOI: 10.1016/j.ssci.2025.107107
Ömer Kaya , Nuriye Kabakuş
Micro-mobility vehicles have rapidly become widespread as a sustainable and practical alternative for urban transportation in recent years. In this study, micro-mobility vehicles refer to traditional bicycles, electric bicycles, and electric scooters, which represent the main categories of such modes involved in traffic crashes in Türkiye. Despite their growing popularity, the safety implications of these vehicles have not yet been fully understood, and comprehensive research addressing crash patterns and associated risk factors is required. To this end, this study employs an artificial intelligence-driven geospatial and statistical methodology. Crash reports involving micro-mobility vehicles in Türkiye between 2015 and 2023 were analysed. Seventeen independent variables and 102 sub-variables were identified and integrated into a GIS environment for spatial analysis. The impact levels of risk factors were assessed using six different Large Language Models (DeepSeek, GEMINI, Perplexity, ChatGPT, Copilot, and Poe). Crash risk maps and corresponding weight values were combined to produce an crash suitability map indicating the potential risk of micro-mobility crashes. Furthermore, the significance of these factors across different collision types was tested using a multinomial logistic regression model. To the best of the authors’ knowledge, this is the first study to apply a macro-scale dataset and an AI-enhanced geospatial decision-making approach to analyse micro-mobility crashes. The findings highlight the need for local governments and urban planners to implement targeted safety measures in regions with high crash potential.
{"title":"Mapping micro-mobility risk: AI-powered geospatial analysis and predictive modelling","authors":"Ömer Kaya , Nuriye Kabakuş","doi":"10.1016/j.ssci.2025.107107","DOIUrl":"10.1016/j.ssci.2025.107107","url":null,"abstract":"<div><div>Micro-mobility vehicles have rapidly become widespread as a sustainable and practical alternative for urban transportation in recent years. In this study, micro-mobility vehicles refer to traditional bicycles, electric bicycles, and electric scooters, which represent the main categories of such modes involved in traffic crashes in Türkiye. Despite their growing popularity, the safety implications of these vehicles have not yet been fully understood, and comprehensive research addressing crash patterns and associated risk factors is required. To this end, this study employs an artificial intelligence-driven geospatial and statistical methodology. Crash reports involving micro-mobility vehicles in Türkiye between 2015 and 2023 were analysed. Seventeen independent variables and 102 sub-variables were identified and integrated into a GIS environment for spatial analysis. The impact levels of risk factors were assessed using six different Large Language Models (DeepSeek, GEMINI, Perplexity, ChatGPT, Copilot, and Poe). Crash risk maps and corresponding weight values were combined to produce an crash suitability map indicating the potential risk of micro-mobility crashes. Furthermore, the significance of these factors across different collision types was tested using a multinomial logistic regression model. To the best of the authors’ knowledge, this is the first study to apply a macro-scale dataset and an AI-enhanced geospatial decision-making approach to analyse micro-mobility crashes. The findings highlight the need for local governments and urban planners to implement targeted safety measures in regions with high crash potential.</div></div>","PeriodicalId":21375,"journal":{"name":"Safety Science","volume":"196 ","pages":"Article 107107"},"PeriodicalIF":5.4,"publicationDate":"2025-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884104","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号