International Journal of Occupational Safety and Ergonomics最新文献

Drawing on protection motivation theory (PMT), this study investigates how employees respond cognitively and behaviorally to layoff threats in China's megacity Internet sector. Study 1 employed a cross-sectional survey of 423 employees from Beijing Internet firms, and Study 2 conducted a scenario-based experiment to strengthen causal inference. Structural equation modeling and path analysis were conducted to test a mediation model linking threat and coping appraisals to extra-role behavior (ERB) via protection motivation. Results show that perceived severity, vulnerability, response efficacy and self-efficacy jointly enhance protection motivation, which in turn promotes adaptive ERB. Perceived organizational support moderates this link, weakening the effect of protection motivation on ERB. These findings extend PMT from explaining defensive reactions to adaptive behaviors, highlighting how employees transform employment threats into proactive engagement. Practical implications emphasize fostering efficacy and balanced support to channel anxiety into constructive motivation.

Objectives. Ensuring safety in high-risk occupations is challenging when human performance is influenced by organizational, technical and environmental factors. This study aims to analyze the causal mechanisms of accidents in high-risk work systems, using China's general aviation (GA) as a case study. Methods. A novel data-driven tree-augmented naive Bayesian network (TAN-BN) model was developed, integrating variables across human, organizational, regulatory, technical and environmental domains. The model was applied to 186 GA accident reports from China (1996-2024), with sensitivity analysis and validation assessing its robustness. Results. Human, technical and environmental factors significantly influence pilot behavior, while preconditions for pilot unsafe acts are shaped by organizational and regulatory oversight. Sensitivity analysis further identified distinct risk patterns: regulatory deficiencies dominate serious accidents, whereas technical failures are more critical in minor and major accidents. The TAN-BN model demonstrated strong predictive accuracy. Conclusions. This study quantitatively maps how context-specific regulatory and organizational conditions shape human performance under pressure and reveals universal risk propagation mechanisms in high-risk work systems. The findings provide a data-informed basis for human-centered safety interventions, highlighting the need to strengthen organizational management, regulatory oversight and environmental risk management in GA.

Icons play a critical role in human-machine interaction scenarios such as autonomous driving. Although icons can effectively overcome language barriers, existing research on icon design for such contexts remains limited. In particular, icon classification methods lack consistency, and prior studies often focus on preference or attention while overlooking underlying cognitive mechanisms. Grounded in cognitive load theory, this study classifies icons based on visual features and investigates their effects on recognition and memory using an electroencephalography-based rapid interaction experiment. Data were collected from 43 participants to compare recognizability and memory load across different icon categories. Results show that visual features do not significantly influence recognition accuracy but have a significant effect on memory load. Specifically, line-based icons perform better under low memory load conditions, whereas plane-based icons demonstrate advantages in high memory load tasks. These findings provide empirical guidance for icon design in automotive user interface.

Safety instrumented systems (SISs) play a crucial role in preventing major accidents in the petrochemical industry. This study investigates the impact of new technologies and artificial intelligence on SIS maintenance in the petrochemical industry, with particular attention to the mediating roles of safety, supervision and organizational support. Data were collected from 84 professionals involved in SIS maintenance in the Iranian petrochemical industry. A structured questionnaire was developed based on prior literature and expert validation, and the proposed research model was analyzed using partial least squares structural equation modeling (PLS-SEM). New technologies and artificial intelligence have a significant positive effect on SIS maintenance. Moreover, safety and supervision/support were found to play significant mediating roles. New technologies and artificial intelligence investments alone are insufficient; organizations must simultaneously reinforce safety management, supervision and support to fully realize the maintenance benefits of emerging technologies in high-risk industrial environments.

Work-related musculoskeletal disorder (WMSD) rates are increasing among sonographers, with high worker populations reporting pain and discomfort. Upper extremity physical demands and exposures in this cohort are largely unknown, requiring attention to enact changes that mitigate future injury risk. The purpose of this study was to quantify the effects of patient size and scan location on upper extremity postures and joint moment capability of sonographers. An a priori survey was completed by local sonographer staff. Digital human modeling (DHM) of 18 patient avatars and eight scan locations produced 144 scan scenarios. Sonographer exposure assessments were completed using rapid upper limb assessment (RULA) and the arm force field (AFF). The AFF demonstrated that a large subset of scenarios exceeded strength capabilities for 99% of the population. RULA scores of 3 or greater were present across all scans, indicating need for further investigation regardless of patient size and scan location.

Older drivers represent the fastest-growing segment of the driving population and are at increased risk of traffic crashes. Therefore, effective interventions are essential to maintain their driving safety. Drawing on self-determination theory, this study investigates older drivers' motivational needs for training participation and develops a psychologically grounded driving training program. A driving simulator experiment was conducted with 20 older drivers, with 20 younger drivers serving as a comparison group. All participants completed three driving tests: a baseline test (T1), an immediate post-training test (T2) and a 3-day post-training test (T3). Training effectiveness was evaluated using Kirkpatrick's four-level model. Results showed that the training significantly improved older drivers' traffic-related knowledge and driving performance. Moreover, older drivers demonstrated further performance gains at T3 relative to T2, particularly in reducing hard deceleration, hard braking and speeding events. These findings enhance understanding of older drivers' learning processes and provide empirical support for targeted interventions.

Objectives. Enhancing workers' risk perception through targeted training is crucial in reducing the likelihood of occupational accidents. Electroencephalography (EEG) is utilized as a robust tool for exploring the intricacies of how risk is processed by workers. This study proposes a procedure for recognizing workers' risk perception using EEG. Methods. Fifty-five construction workers were recruited to view the images depicting various types of hazards and the EEG signals were recorded simultaneously. Following the extraction of pertinent features, different classification models have been employed to identify the critical brain channels in risk perception. Results. The findings indicate that frontal lobe channels are particularly effective at discerning variations in risk perception. Workers with varying levels of experience and risk inclination demonstrate distinct neural responses when confronted with risk stimuli. Conclusion. These results suggest the neural dynamics underlying risk perception and the specific brain regions of construction workers that can inform targeted safety-training programs.

Objective. This study aimed to identify variables contributing to mental work overload among higher education professors. Methods. A systematic literature review was conducted using articles from the Web of Science and Scopus databases, applying a 16-year filter and following the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) and PICO (Population, Intervention, Control and Outcomes) strategies. Results. From 1096 records, 30 met all inclusion criteria. Most studies applied cross-sectional designs with online questionnaires and used the Maslach burnout inventory (MBI) to assess burnout symptoms. The most frequently reported factors were high workload, organizational problems, academic productivity pressure and work-family conflict. These variables were consistently associated with psychological impacts such as burnout, anxiety and depression. Conclusion. The findings emphasize the need for institutional actions to mitigate mental overload and promote well-being among faculty members. Additionally, the review revealed a notable gap in the literature regarding university professors, as most existing studies focus on primary and secondary education professionals.

Objectives: This study aimed to evaluate the quality, reliability and content of YouTube videos related to office ergonomics.

Methods: The descriptive study analyzed 196 English-language YouTube videos, selected from 752 videos published, using the keywords 'workplace ergonomics' or 'office ergonomics' based on the inclusion and exclusion criteria. The reliability, quality and content of the videos were assessed using the modified DISCERN (mDISCERN), the global quality score (GQS) and the office ergonomics content evaluation checklist (OE-CEC).

Results: Researcher 1 rated 71.5% as low quality, 68.4% as low reliability and 69.4% as insufficient content, while Researcher 2 rated 62.3, 59.8 and 70.9% respectively. mDISCERN and OE-CEC scores were significantly associated with uploader source, subtitle presence and video duration. Content scores were also associated with view ratio and number of comments. The GQS mean showed significant associations with uploader source, duration, view ratio, video power index and number of comments.

Conclusions: YouTube videos on office ergonomics were of low quality, low reliability and insufficient content. Public institutions produced more reliable and higher quality videos, and longer videos contained more comprehensive information. It is recommended that government agencies, universities and occupational health teams are encouraged to produce accurate and reliable videos on office ergonomics.

This study optimizes and predicts the thermal comfort performance of cut-protective fabrics produced from multicomponent hybrid yarns comprising a stainless steel (SS) core, an inner polyester sheath and an outer high-performance polyethylene (HPPE) sheath. A Box-Behnken experimental design was employed to evaluate the effects of SS fibre diameter, HPPE linear density and yarn twist on thermal conductivity and air permeability. Results demonstrated that thermal comfort properties are significantly governed by constituent filament linear density and yarn twist. Second-order regression models provided excellent fits, with R² values of 0.9605 for thermal conductivity and 0.9972 for air permeability. Optimal performance was achieved at SS fibre diameters of 35-40 µm, HPPE linear densities of 350-400 denier and yarn twist levels of 400-450 m^-1, yielding a desirability score of 1.0. Strong agreement between predicted and experimental results confirms the robustness of the developed models.