International Journal of Occupational Safety and Ergonomics最新文献

Objectives. This study aimed to compare postural assessment and postural awareness using the artificial intelligence posture evaluation and correction system (APECS) in individuals receiving posture training. Methods. Participants' physical characteristics were recorded. The participants' posture was evaluated with APECS and the New York posture rating chart test (NYPR), and their body and postural awareness was evaluated with the body awareness questionnaire (BAQ), postural awareness form (PAF) and postural habits and awareness scale (PHAS). Results. In the study, results of the PAF (p = 0.000), BAQ (p = 0.013) and PHAS (p = 0.033) were found to be different between the groups. While the groups were similar in the PHAS sub-dimension of postural habit (p = 0.331), there was a significant difference between the groups in postural awareness (p = 0.04). NYPR results of the participants in the group receiving posture training were similar to those in the group not receiving posture training (p = 0.45). Conclusion. Postural deviations measured by digital posture assessment in individuals receiving posture training were significantly different in the group receiving posture training. Postural awareness and body awareness were better in individuals who received posture training than in individuals who did not receive posture training.

Although the helicopter to ship transfer operation is rarely applied in ports around the world, some of the hub ports have encouraged it. The operational process poses challenges to safety due to the nature of the work to be completed by the ship crew. This article performs a systematic human error prediction to ensure safe helicopter to ship transfer operations under different circumstances since the human factor is becoming a significant contributor to maritime accidents. To accomplish this, the article addresses a cognitive reliability and error analysis method (CREAM) under the evidential reasoning (ER) approach. In the proposed approach, the CREAM provides a comprehensive human error prediction tool and ER is capable of supporting experts' judgment in decision-making. The findings of the research show that 'Secure the loose objects within or adjacent to the operating area' poses a high human error probability (4.50E-02) during helicopter to ship transfer operations.

Objectives. This study investigates the possibility of developing a unique model for predicting work-related injuries in Serbian underground coal mines using neural networks and fuzzy logic theory. Accidents are common due to the unique nature of underground mineral extraction involving people, machinery and limited workplaces. Methods. A universal model for predicting occupational accidents takes into account influential factors such as organizational aspects, personal and collective protective equipment, on-the-job training and leadership factors. The selected networks achieved a prediction accuracy of >90%. Results. The study successfully identifies potential risks and critical worker groups leading to injuries. The sensitivity analysis provides insights for targeted safety measures and improved organizational practices. Conclusion. This data-driven approach makes a valuable contribution to safety in the mining industry. Implementation of the predictive model can reduce injuries and machine damage, and improve worker well-being.

Objectives. In light of the profound influence of digital advancements on business management, digital leadership has emerged as an indispensable element for organizations to effectively navigate this transformative wave. While the influence of traditional leadership on safety performance has been extensively scrutinized, the impact of digital leadership on safety performance has regrettably been overlooked. Drawing from the job demand-resource model, this study analyzes the influence of digital leadership on safety performance, encompassing safety compliance and safety participation. Additionally, the study explores the mediating role of challenge appraisal and the moderating effect of role overload. Methods and Results. Using data from 341 employees at two time points, this study finds that: digital leadership promotes employees' safety performance; digital leadership enhances employees' safety performance by fostering challenge appraisal; and the positive effect of digital leadership on employees' safety performance through challenge appraisal diminishes as role overload increases. Conclusions. The findings of this study contribute to the existing body of literature concerning the antecedents of safety performance. Additionally, this study offers practical recommendations for enhancing employees' safety performance in the digital era.

With the rapid growth of the gig economy in China, millions of food delivery e-bikers are making their living by rushing on the street. Speeding is one of their most common risky riding behaviours, leading to severe traffic crashes. Based on 2-month naturalistic cycling data of 46 full-time food delivery e-bikers in Changsha, their speeding behaviour is deeply studied with the individual daily speeding proportion being taken as the speeding indicator. A beta regression model is built to identify the factors significantly influencing the indicator. The estimation results reveal that female riders, middle-aged riders and riders with a bachelor's degree are less likely to engage in speeding. The same result is indicated for those working longer or experiencing more crashes. Additionally, holidays and riding distance are found to have significantly positive influences. Finally, some countermeasures are proposed to prevent speeding among food delivery e-bikers.

Objectives. The COVID-19 pandemic, remote work and new technologies have heightened workplace pressures. Effective response and essential organizational changes require business leaders to be more adaptable, with managers' presence playing a pivotal role in successful implementation. The study assesses a brief mindfulness-based emotional regulation for managers (MBERM) intervention, to reduce workplace stress and enhance managerial well-being. Methods. An 8-week non-randomized controlled trial was conducted with a waiting list control group and an intervention group. Pre-post differences were measured by Student's t test or Wilcoxon test, and effect size calculated using the Hedge's g formula. The sample included 23 managers (17 men and six women) with average age 50 years. The study assessed anxiety and depressive symptoms, psychological flexibility, perceived self-efficacy, general work-related well-being, perceived stress and mindfulness. Results. Statistically significant changes were observed in the intervention group in depression, anxiety, work-related acceptance and action, general self-efficacy, exhaustion, alienation, stress and non-reactivity. The control group showed no statistically significant changes in any of the variables. Conclusion. The MBERM intervention could improve the emotional and work-related well-being of managers and reduce stress levels and burnout. Further study of this intervention is needed to promote adherence and ensure a long-term improvement.