2 resultados para Work Healthy
em Universidad de Alicante
Resumo:
Background: An association between spontaneous abortions and shift work has been suggested, but present research results are conflicting. The aim of the study is to evaluate the relationship between spontaneous abortions among nurses, shift schedules, and nights worked. Methods: This is a longitudinal study where we identified 914 females from a cohort of nurses in Norway who had worked the same type of shift schedule 2008-2010; either permanent day shift, three-shift rotation or permanent night shift. Information on age, work and life-style factors, as well as spontaneous abortions during lifetime and the past three years (2008-2010) was obtained by annual questionnaires. Results: A higher prevalence of experienced spontaneous abortions before study start (2008) was found among nurses working permanent night shift compared to other nurses. In a linear regression analysis, a risk of 1.3 was found for experienced spontaneous abortions before study start among permanent night shift nurses, with day shift as reference, when adjusting for age, smoking, caffeine and job strain, but the finding was not statistical significant (95 per cent confidence interval 0.8-2.1). Permanent night shift workers had a risk of 1.5 experiencing spontaneous abortions in 2008-2010 compared to day shift nurses, although not statistical significant (95 per cent confidence interval 0.7-3.5). The number of night shifts the past three years was not associated with experiencing spontaneous abortions 2008-2010, but associated with a reduced risk of experiencing spontaneous abortions during lifetime. The results must be interpreted in the light of a possible selection bias; both selections into the occupation of nursing and into the different shift types of the more healthy persons may have occurred in this population. Conclusion: No significant increased risk of spontaneous abortion among permanent night shift nurses compared to day-time nurses was found in this study, and no association was found between spontaneous abortions and the number of worked night shifts.
Resumo:
The construction industry is characterised by fragmentation and suffers from lack of collaboration, often adopting adversarial working practices to achieve deliverables. For the UK Government and construction industry, BIM is a game changer aiming to rectify this fragmentation and promote collaboration. However it has become clear that there is an essential need to have better controls and definitions of both data deliverables and data classification. Traditional methods and techniques for collating and inputting data have shown to be time consuming and provide little to improve or add value to the overall task of improving deliverables. Hence arose the need in the industry to develop a Digital Plan of Work (DPoW) toolkit that would aid the decision making process, providing the required control over the project workflows and data deliverables, and enabling better collaboration through transparency of need and delivery. The specification for the existing Digital Plan of Work (DPoW) was to be, an industry standard method of describing geometric, requirements and data deliveries at key stages of the project cycle, with the addition of a structured and standardised information classification system. However surveys and interviews conducted within this research indicate that the current DPoW resembles a digitised version of the pre-existing plans of work and does not push towards the data enriched decision-making abilities that advancements in technology now offer. A Digital Framework is not simply the digitisation of current or historic standard methods and procedures, it is a new intelligent driven digital system that uses new tools, processes, procedures and work flows to eradicate waste and increase efficiency. In addition to reporting on conducted surveys above, this research paper will present a theoretical investigation into usage of Intelligent Decision Support Systems within a digital plan of work framework. Furthermore this paper will present findings on the suitability to utilise advancements in intelligent decision-making system frameworks and Artificial Intelligence for a UK BIM Framework. This should form the foundations of decision-making for projects implemented at BIM level 2. The gap identified in this paper is that the current digital toolkit does not incorporate the intelligent characteristics available in other industries through advancements in technology and collation of vast amounts of data that a digital plan of work framework could have access to and begin to develop, learn and adapt for decision-making through the live interaction of project stakeholders.