Occupational injuries among construction workers at the Chep Lap Kok Airport construction site, Hong Kong : analysis of accident rates, and the association between injuries, error types and their contributing factors : a thesis presented in partial fulfilment of the requirements for the degree of Master of Aviation at Massey University, Palmerston North, New Zealand

Accidents on construction sites are a major cause of morbidity and mortality in Hong Kong. This study investigated the likely causes of occupational injuries that were present among the construction workers during the construction of the new Chep Lap Kok (CLK) Airport in Hong Kong. In order to accumulate the requisite information, 1648 accident investigation reports in a four-year period (1993-1996) were reviewed. The first part of the study described the pattern and magnitude of occupational injuries among the CLK construction workers and compared the accident rates of the CLK workers with those of the construction industry as a whole in Hong Kong. The study examined the effects of the workplace infrastructure at CLK in order to explain why this site presented fewer work place injuries and accidents than other workplaces. The second part of the research used these injury and accident occurrences as the basis to construct the causes of accidents and injuries within an error causation classification system. The results showed that at CLK, the commonest workplace injury was contusion & crushing which appeared to be due to mistakes made through lapses in memory often caused by pressure of work being imposed on the employee. This section also indicated what types of errors were most closely associated with what kinds of injuries and what conditions were most likely to trigger these types of events. Among the major associations were links between contusion and crushing and violation error, perceptual error; between memory lapse and work pressure, equipment deficiencies, poor working environment, fatigue, and between violation error and work pressure. The research suggested that work pressure was an important contributing factor to construction injury and it increased the prevalence of a human error type namely, memory lapse many fold. The outcomes from this study provide important new information on the causes and types of errors which have led to occupational injuries among construction workers in Hong Kong. A better understanding of the human factors-based causes of accidents and injuries in the construction industry and an inculcation of a safety culture on construction sites are critically important in the reduction of the rate of construction accidents and improvement of workers' human performance. The results should assist the construction industry in the designing accident prevention training and education strategies, estimating human error probabilities, and the monitoring organizational safety performance

A meta-analytic review of stand-alone interventions to improve body image

Objective Numerous stand-alone interventions to improve body image have been developed. The present review used meta-analysis to estimate the effectiveness of such interventions, and to identify the specific change techniques that lead to improvement in body image. Methods The inclusion criteria were that (a) the intervention was stand-alone (i.e., solely focused on improving body image), (b) a control group was used, (c) participants were randomly assigned to conditions, and (d) at least one pretest and one posttest measure of body image was taken. Effect sizes were meta-analysed and moderator analyses were conducted. A taxonomy of 48 change techniques used in interventions targeted at body image was developed; all interventions were coded using this taxonomy. Results The literature search identified 62 tests of interventions (N = 3,846). Interventions produced a small-to-medium improvement in body image (d+ = 0.38), a small-to-medium reduction in beauty ideal internalisation (d+ = -0.37), and a large reduction in social comparison tendencies (d+ = -0.72). However, the effect size for body image was inflated by bias both within and across studies, and was reliable but of small magnitude once corrections for bias were applied. Effect sizes for the other outcomes were no longer reliable once corrections for bias were applied. Several features of the sample, intervention, and methodology moderated intervention effects. Twelve change techniques were associated with improvements in body image, and three techniques were contra-indicated. Conclusions The findings show that interventions engender only small improvements in body image, and underline the need for large-scale, high-quality trials in this area. The review identifies effective techniques that could be deployed in future interventions

A proposed psychological model of driving automation

This paper considers psychological variables pertinent to driver automation. It is anticipated that driving with automated systems is likely to have a major impact on the drivers and a multiplicity of factors needs to be taken into account. A systems analysis of the driver, vehicle and automation served as the basis for eliciting psychological factors. The main variables to be considered were: feed-back, locus of control, mental workload, driver stress, situational awareness and mental representations. It is expected that anticipating the effects on the driver brought about by vehicle automation could lead to improved design strategies. Based on research evidence in the literature, the psychological factors were assembled into a model for further investigation

Evolving Non-Dominated Parameter Sets for Computational Models from Multiple Experiments

© Peter C. R. Lane, Fernand Gobet. This article is distributed under the terms of the Creative Commons Attribution Non-Commercial License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY-NC 3.0)Creating robust, reproducible and optimal computational models is a key challenge for theorists in many sciences. Psychology and cognitive science face particular challenges as large amounts of data are collected and many models are not amenable to analytical techniques for calculating parameter sets. Particular problems are to locate the full range of acceptable model parameters for a given dataset, and to confirm the consistency of model parameters across different datasets. Resolving these problems will provide a better understanding of the behaviour of computational models, and so support the development of general and robust models. In this article, we address these problems using evolutionary algorithms to develop parameters for computational models against multiple sets of experimental data; in particular, we propose the ‘speciated non-dominated sorting genetic algorithm’ for evolving models in several theories. We discuss the problem of developing a model of categorisation using twenty-nine sets of data and models drawn from four different theories. We find that the evolutionary algorithms generate high quality models, adapted to provide a good fit to all available data.Peer reviewedFinal Published versio

Perspectives on safety culture

Overviewing selected elements from the literature, this paper locates the notion of safety culture within its parent concept of organisational culture. A distinction is drawn between functionalist and interpretive perspectives on organisational culture. The terms ‘culture’ and ‘climate’ are clarified as they are typically applied to organisations and to safety. A contrast is drawn between strategic top down and data-driven bottom up approaches to human factors as an illustrative aspect of safety. A safety case study is used to illustrate two measurement approaches. Key issues for future study include valid measurement of safety culture and developing methods to adequately represent mechanisms through which safety culture might influence, and be influenced by, other safety factors

The economics of child well-being

This paper presents an integrated economic approach that organizes and interprets the evidence on child development. It also discusses the indicators of child well-being that are used in international comparisons. Recent evidence on child development is summarized, and policies to promote child well-being are discussed. The chapter concludes with some open questions and suggestions for future research

Risk Management in the Arctic Offshore: Wicked Problems Require New Paradigms

Recent project-management literature and high-profile disasters—the financial crisis, the BP Deepwater Horizon oil spill, and the Fukushima nuclear accident—illustrate the flaws of traditional risk models for complex projects. This research examines how various groups with interests in the Arctic offshore define risks. The findings link the wicked problem framework and the emerging paradigm of Project Management of the Second Order (PM-2). Wicked problems are problems that are unstructured, complex, irregular, interactive, adaptive, and novel. The authors synthesize literature on the topic to offer strategies for navigating wicked problems, provide new variables to deconstruct traditional risk models, and integrate objective and subjective schools of risk analysis

Building Prediction Models for Dementia: The Need to Account for Interval Censoring and the Competing Risk of Death

Indiana University-Purdue University Indianapolis (IUPUI)Context. Prediction models for dementia are crucial for informing clinical decision making in older adults. Previous models have used genotype and age to obtain risk scores to determine risk of Alzheimer’s Disease, one of the most common forms of dementia (Desikan et al., 2017). However, previous prediction models do not account for the fact that the time to dementia onset is unknown, lying between the last negative and the first positive dementia diagnosis time (interval censoring). Instead, these models use time to diagnosis, which is greater than or equal to the true dementia onset time. Furthermore, these models do not account for the competing risk of death which is quite frequent among elder adults. Objectives. To develop a prediction model for dementia that accounts for interval censoring and the competing risk of death. To compare the predictions from this model with the predictions from a naïve analysis that ignores interval censoring and the competing risk of death. Methods. We apply the semiparametric sieve maximum likelihood (SML) approach to simultaneously model the cumulative incidence function (CIF) of dementia and death while accounting for interval censoring (Bakoyannis, Yu, & Yiannoutsos, 2017). The SML is implemented using the R package intccr. The CIF curves of dementia are compared for the SML and the naïve approach using a dataset from the Indianapolis Ibadan Dementia Project. Results. The CIF from the SML and the naïve approach illustrated that for healthier individuals at baseline, the naïve approach underestimated the incidence of dementia compared to the SML, as a result of interval censoring. Individuals with a poorer health condition at baseline have a CIF that appears to be overestimated in the naïve approach. This is due to older individuals with poor health conditions having an elevated risk of death. Conclusions. The SML method that accounts for the competing risk of death along with interval censoring should be used for fitting prediction/prognostic models of dementia to inform clinical decision making in older adults. Without controlling for the competing risk of death and interval censoring, the current models can provide invalid predictions of the CIF of dementia