A Study Investigating How the Characteristics of High Reliability Organisations Can Be Measured in the Construction Industry in Australia.

Construction activities involve a lot of risk as workers are exposed to a wide range of job hazards, such as working at height, moving vehicles, toxic substances, and confined spaces. The hazards related to a construction project are mostly unpredictable because construction projects move quickly due to project deadlines, and changing work environments. As a result of this, the industry accounts for one of the highest numbers of work-related claims, and the fourth highest incidence rate of serious claims in Australia. This research investigates how key safety management factors can measure the characteristics of high reliability organisations (HROs) in the construction industry in New South Wales Australia. To address the problem, a model is presented that can predict characteristics of HRO in construction (CHC). Using structural equation modeling (SEM), and confirmatory factor analysis (CFA), the model and measurement instruments are tested and validated from data collected from construction workers. The results identified the factors that effectively measure CHC, and the findings can also be used as a safety management strategy and will contribute to the body of knowledge in research.

Resilience Engineering Indicators and Safety Management: A Systematic Review.

A safe work environment is crucial in high-risk industries, such as construction refurbishment. Safety incidents caused by uncertainty and unexpected events in construction refurbishment systems are difficult to control using conventional safety management techniques. Resilience engineering (RE) is proposed as an alternative to traditional safety management approaches. It presents a successful safety management methodology designed to deal with uncertainty in high-risk work environments. Despite the fact that RE resides in the safety domain, there is no common set of RE indicators to measure and assess resilient in the work environment. The main aim of this research is to explore RE indicators that have been identified as important in developing and assessing the resilient work environment in high-risk industries, particularly in construction refurbishment. Indicators have been attained through a systematic literature review of research and scholarly articles published between the years 2004 and 2019. The literature review explored RE indicators in various industries. Descriptive analysis and co-occurrence-based network visualization were used for data analysis. The findings revealed 28 RE indicators in 11 different high-risk industries. The results show that the four commonly used indicators were: top-management commitment, awareness, learning, and flexibility, all of which have a strong relationship with RE. The findings of this study are useful for stakeholders when making decisions concerning the most important RE indicators in the context of their research or practice as this would avoid the ambiguity and disparity in the identification of RE indicators.

A Systematic Review of Healthcare-Associated Infectious Organisms in Medical Radiation Science Departments.

Healthcare-associated infections (HAIs) pose a significant occupational risk to medical radiation science (MRS) professionals, who have a high degree of patient contact. Current research largely focusses on HAIs in patients, with limited attention given to infectious organisms that MRS professionals are exposed to. This is a significant gap that this systematic review seeks to address by summarizing current literature to determine the infectious organisms within MRS departments, their reservoirs, and transmission modes. Reporting of this systematic review follows the preferred reporting items for systematic reviews and meta-analyses guidelines. Five databases were searched (Scopus, Medical Literature Analysis and Retrieval System Online (MEDLINE), the Cochrane Library, EMBASE, and Cumulative Index to Nursing and Allied Health Literature (CINAHL)) for relevant studies published between 1983 and 2018. Quality assessment was performed using checklists from the Johanna Briggs Institute. Nineteen studies were included in the review; twelve of which were set in diagnostic radiography departments, two in radiotherapy departments, and five in non-MRS departments. No studies were set in nuclear medicine departments, indicating a gap in the available literature. A total of 19 genera of infectious organisms were identified in the literature, with Staphylococcus, Escherichia, Bacillus, and Corynebacterium reported in all MRS departments. Infectious organisms were identified in all observational studies, indicating a need for better infection control methods and/or compliance training within MRS to minimize the risk of infections.

Using a psychological contract of safety to predict safety climate on construction sites.

INTRODUCTION: The fact that safety climate impacts safety behavior and delivers better safety outcomes is well established in construction. However, the way workers safety perception is inclined and developed is still unclear. METHOD: In this research, the influence of supervisors' developing safety climate and its impact on workers' safety behavior and their conceptualization of safety is explored through the lens of the 'Psychological Contract' (PC). More specifically, it is argued that 'Psychological Contract of Safety' (PCS) is a vital factor in explaining how workers attach meaning to a supervisor behavior. Extant research suggests: (a) safety climate is based on the perception of workers regarding safety; and (b) PCS is based on perceived mutual obligations between workers and supervisors. As a result, this research argues that if PCS or mutual obligations between workers and supervisors are fulfilled, then safety climate of the workers will be positively influenced. A model is presented depicting PCS as an alternative intervention in understanding how safety climate could be influenced and predicted by the level of fulfillment of mutual safety obligations. Using Structural Equation Modeling (SEM) the model of the PCS is validated with data collected from a mega-construction project in Australia. RESULTS: The results suggest that to have a positive and strong safety climate, top-level managers must ensure that mutual safety obligations between supervisor and workers are fulfilled. This enables the PCS to be introduced as a new 'predictor' of safety climate. Practical applications: The novel outcome of the research could be considered as a management intervention to modify supervisors' behavior to produce better safety outcomes.