Safety

Occupational Health and Safety (OHS) in educational settings is a vital responsibility that is often inconsistently implemented. There is a need for research to bridge the gap between policy and practice. This study employed a cross-sectional mixed-methods design in six schools in the capital city of Indonesia to identify key implementation barriers, strategies, and compliance levels in OHS. Data were collected from 217 teachers using a structured KPAP (Knowledge, Attitudes, Perceptions, Practices) survey and from an additional 38 teachers via Focus Group Discussions (FGDs). Quantitatively, teachers showed highly positive attitudes (99.4% viewing OHS as a professional duty) and generally positive perceptions but implementation practices were sub-optimal (e.g., low participation in drills and PPE usage), showing a gap between awareness and action. Qualitatively, the main barriers identified were a lack of specific OHS regulation or guidance for schools, limited resources/infrastructure, and the perception of OHS as a low priority. Management strategies focused on external collaboration and ongoing in-school initiatives. In conclusion, a significant gap exists between OHS awareness and its integration into school management, highlighting the urgent need for strengthened governance, comprehensive policies, and sustained capacity-building to ensure a proactive, safe, and sustainable school environment for staff and students.

Solar ultraviolet radiation (UVR) is classified as a Group 1 carcinogen and poses a significant occupational hazard to outdoor workers. Despite preventive guidelines, adherence to protective measures remains inconsistent. This systematic review identified the protective measures adopted by healthy outdoor workers and assessed their adherence to and the effectiveness of these measures. Following the PRISMA 2020 statement, the review searched Scopus, Web of Science, and PubMed for peer-reviewed studies published between 2015 and 2025. Eligible studies included at least 100 healthy participants and evaluated preventive or protective measures against solar UVR. Independent reviewers extracted data and assessed risk of bias using the McMaster Critical Review Form. From 17,756 records, 51 studies met the inclusion criteria after screening and a subsequent snowballing process. The identified protective strategies clustered into physical, behavioural, and organisational categories. Adherence ranged from low to moderate, with structured interventions and employer support improving compliance. Sunscreen use remained low due to perceived inconvenience and lack of provision. Overall, the evidence revealed substantial variability in implementation and effectiveness across occupations. Strengthened regulations and integrated interventions combining education, personal protective equipment, and organisational measures are essential. Future research should prioritise longitudinal designs and objective indicators such as biomarkers and dosimetry.

To identify and evaluate the failure issues in the livestock manure-to-biomethane supply chain, this study employs a Bayesian network approach with three inference analysis methods: diagnostic analysis, sensitivity analysis, and maximum causal chain inference. First, the main hazard categories affecting the failure of the supply chain are identified, establishing risk indicators for feedstock collection, pretreatment, anaerobic digestion, purification and upgrading, transportation, and biomethane end-use. Then, the half-interval method and possibility superiority comparison are used to calculate and rank the severity of related accidents, obtaining the severity ranking of secondary indicators as well as the severity ranking of work items and risk items. Finally, Bayesian forward inference is applied to investigate the failure probability of the supply chain, combined with backward inference to identify the risk factors most likely to cause supply chain failures and trace the formation of failure hazards. The Bayesian sensitivity analysis method is ultimately applied to determine the key hazards affecting supply chain failures and the correlations between accident hazards, followed by validation. The results show that the failure probability of the supply chain through causal inference is approximately 54.76%, indicating relatively high failure risk. The three factors with the highest posterior probabilities are mechanical stirring failure C₃ (88.11%), corrosion-induced ammonia leakage poisoning D6, and equipment explosion caused by excessive pressure due to overheating during dehumidification heating D₉, which are the hazards most likely to cause failures in the supply chain. Improper operations and the toxicity of related chemicals are key hazards leading to supply chain failures, with the correlation between accident hazards presented as a hazard chain by integrating severity and accident probability, and the key risk points in the supply chain are identified.