Social and emotional determinants of health

- describe what is meant by socioeconomic differences in health, and the social and emotional determinants of health - understand how health inequalities are affected by the social and economic circumstances that people experience throughout their lives - discuss how factors such as living and working conditions, income, place and education can impact on health - identify actions for public health policy-makers that have the potential to make a difference in improving health outcomes within populations - appreciate the concept of social cohesion and social capital, and their role as potential protective factors in health - understand conceptual models that can assist in analysing these issues.

Sustaining a healthy workforce

The changing demographics of the mining workforce and the increasing demand for skilled workers increases the importance of sustaining a healthy workforce now and for the future. Although health is strongly related to safety, the two areas are not well integrated and the relationship is poorly understood. As such there is an important need to raise the profile of health within the Occupational Health and Safety (OH&S) domain. The mining industry carries health and safety risks, often greater than other occupations. Whilst the mining industry is regulated by stringent OH&S controls, the very nature of the work and environmental influences expose employees to a greater number of injury risk factors than many other industries. In contrast to its excellent safety record, compared to most other industries, the mining workforce has a high proportion of chronic health problems. These problems can be exacerbated by the ageing of the workforce, regional location of sites and organisational issues influencing work demands. A major focus has been on the treatment of these conditions with relatively limited attention to prevention strategies. An important prevention strategy is the raising of awareness among the workforce of health issues and the significant increase in the volume of health related information has provided an excellent opportunity to access relevant information. Unfortunately, this information is of varying quality, may not be evidence based, and may provide the wrong guidance to the development of interventions designed to improve health. Limited time of most employees and potential lack of knowledge of ability to differentiate quality information presents additional problems or barriers to increasing awareness of health issues...

An estimation of crash risks using a log-linear model and the induced exposure technique

Prevention and safety promotion programmes. Traditionally, in-depth investigations of crash risks are conducted using exposure controlled study or case-control methodology. However, these studies need either observational data for control cases or exogenous exposure data like vehicle-kilometres travel, entry flow or product of conflicting flow for a particular traffic location, or a traffic site. These data are not readily available and often require extensive data collection effort on a system-wide basis. Aim: The objective of this research is to propose an alternative methodology to investigate crash risks of a road user group in different circumstances using readily available traffic police crash data. Methods: This study employs a combination of a log-linear model and the quasi-induced exposure technique to estimate crash risks of a road user group. While the log-linear model reveals the significant interactions and thus the prevalence of crashes of a road user group under various sets of traffic, environmental and roadway factors, the quasi-induced exposure technique estimates relative exposure of that road user in the same set of explanatory variables. Therefore, the combination of these two techniques provides relative measures of crash risks under various influences of roadway, environmental and traffic conditions. The proposed methodology has been illustrated using Brisbane motorcycle crash data of five years. Results: Interpretations of results on different combination of interactive factors show that the poor conspicuity of motorcycles is a predominant cause of motorcycle crashes. Inability of other drivers to correctly judge the speed and distance of an oncoming motorcyclist is also evident in right-of-way violation motorcycle crashes at intersections. Discussion and Conclusions: The combination of a log-linear model and the induced exposure technique is a promising methodology and can be applied to better estimate crash risks of other road users. This study also highlights the importance of considering interaction effects to better understand hazardous situations. A further study on the comparison between the proposed methodology and case-control method would be useful.

Development and feasibility of a smartphone, ECG and GPS based system for remotely monitoring exercise in cardiac rehabilitation

Background Despite its efficacy and cost-effectiveness, exercise-based cardiac rehabilitation is undertaken by less than one-third of clinically eligible cardiac patients in every country for which data is available. Reasons for non-participation include the unavailability of hospital-based rehabilitation programs, or excessive travel time and distance. For this reason, there have been calls for the development of more flexible alternatives. Methodology and Principal Findings We developed a system to enable walking-based cardiac rehabilitation in which the patient's single-lead ECG, heart rate, GPS-based speed and location are transmitted by a programmed smartphone to a secure server for real-time monitoring by a qualified exercise scientist. The feasibility of this approach was evaluated in 134 remotely-monitored exercise assessment and exercise sessions in cardiac patients unable to undertake hospital-based rehabilitation. Completion rates, rates of technical problems, detection of ECG changes, pre- and post-intervention six minute walk test (6 MWT), cardiac depression and Quality of Life (QOL) were key measures. The system was rated as easy and quick to use. It allowed participants to complete six weeks of exercise-based rehabilitation near their homes, worksites, or when travelling. The majority of sessions were completed without any technical problems, although periodic signal loss in areas of poor coverage was an occasional limitation. Several exercise and post-exercise ECG changes were detected. Participants showed improvements comparable to those reported for hospital-based programs, walking significantly further on the post-intervention 6 MWT, 637 m (95% CI: 565–726), than on the pre-test, 524 m (95% CI: 420–655), and reporting significantly reduced levels of cardiac depression and significantly improved physical health-related QOL. Conclusions and Significance The system provided a feasible and very flexible alternative form of supervised cardiac rehabilitation for those unable to access hospital-based programs, with the potential to address a well-recognised deficiency in health care provision in many countries. Future research should assess its longer-term efficacy, cost-effectiveness and safety in larger samples representing the spectrum of cardiac morbidity and severity.

Road trauma perceptions and the potential influence of the media

The United Nations Decade of Action for Road Safety (2011-2020) recognises the urgency of addressing global road trauma. Road crashes and attempts to reduce risky driving, including public education campaigns, receive media attention in many countries. In Australia, road fatalities have declined significantly. However, the extent of awareness about this success and of fatalities overall is unclear. A survey of 833 Australian drivers revealed the majority of participants under-estimated fatalities. Unexpectedly, some under-estimates appear based on recollections of media reports. The findings suggest lack of awareness of the extent of road deaths and that, paradoxically, media reports might contribute to underestimations. This represents a major public health challenge. Engaging community support for road safety, relative to other health/safety messages, may prove difficult if the extent of road trauma is misunderstood. Misperceptions about fatality levels may be a barrier to road users adopting safety precautions or supporting further road safety countermeasures.

Risk management and injury prevention : competencies, behaviours, and attitudes to safety in the construction industry

Work in the Australian construction industry is fraught with risk and the potential for serious harm. The industry is consistently placed within the three most hazardous industries to work along with other industries such as mining and transport (National Occupational Health and Safety Commission, 2003). In the 2001 to 2002 period, construction work killed 39 people and injured 13,250 more. Hence, more effort is required to reduce the injury rate and maximise the value of the rehabilitation/back-to-work process.

Integrated health prediction of bridge systems using dynamic object oriented Bayesian networks (DOOBNS)

The serviceability and safety of bridges are crucial to people’s daily lives and to the national economy. Every effort should be taken to make sure that bridges function safely and properly as any damage or fault during the service life can lead to transport paralysis, catastrophic loss of property or even casualties. Nonetheless, aggressive environmental conditions, ever-increasing and changing traffic loads and aging can all contribute to bridge deterioration. With often constrained budget, it is of significance to identify bridges and bridge elements that should be given higher priority for maintenance, rehabilitation or replacement, and to select optimal strategy. Bridge health prediction is an essential underpinning science to bridge maintenance optimization, since the effectiveness of optimal maintenance decision is largely dependent on the forecasting accuracy of bridge health performance. The current approaches for bridge health prediction can be categorised into two groups: condition ratings based and structural reliability based. A comprehensive literature review has revealed the following limitations of the current modelling approaches: (1) it is not evident in literature to date that any integrated approaches exist for modelling both serviceability and safety aspects so that both performance criteria can be evaluated coherently; (2) complex system modelling approaches have not been successfully applied to bridge deterioration modelling though a bridge is a complex system composed of many inter-related bridge elements; (3) multiple bridge deterioration factors, such as deterioration dependencies among different bridge elements, observed information, maintenance actions and environmental effects have not been considered jointly; (4) the existing approaches are lacking in Bayesian updating ability to incorporate a variety of event information; (5) the assumption of series and/or parallel relationship for bridge level reliability is always held in all structural reliability estimation of bridge systems. To address the deficiencies listed above, this research proposes three novel models based on the Dynamic Object Oriented Bayesian Networks (DOOBNs) approach. Model I aims to address bridge deterioration in serviceability using condition ratings as the health index. The bridge deterioration is represented in a hierarchical relationship, in accordance with the physical structure, so that the contribution of each bridge element to bridge deterioration can be tracked. A discrete-time Markov process is employed to model deterioration of bridge elements over time. In Model II, bridge deterioration in terms of safety is addressed. The structural reliability of bridge systems is estimated from bridge elements to the entire bridge. By means of conditional probability tables (CPTs), not only series-parallel relationship but also complex probabilistic relationship in bridge systems can be effectively modelled. The structural reliability of each bridge element is evaluated from its limit state functions, considering the probability distributions of resistance and applied load. Both Models I and II are designed in three steps: modelling consideration, DOOBN development and parameters estimation. Model III integrates Models I and II to address bridge health performance in both serviceability and safety aspects jointly. The modelling of bridge ratings is modified so that every basic modelling unit denotes one physical bridge element. According to the specific materials used, the integration of condition ratings and structural reliability is implemented through critical failure modes. Three case studies have been conducted to validate the proposed models, respectively. Carefully selected data and knowledge from bridge experts, the National Bridge Inventory (NBI) and existing literature were utilised for model validation. In addition, event information was generated using simulation to demonstrate the Bayesian updating ability of the proposed models. The prediction results of condition ratings and structural reliability were presented and interpreted for basic bridge elements and the whole bridge system. The results obtained from Model II were compared with the ones obtained from traditional structural reliability methods. Overall, the prediction results demonstrate the feasibility of the proposed modelling approach for bridge health prediction and underpin the assertion that the three models can be used separately or integrated and are more effective than the current bridge deterioration modelling approaches. The primary contribution of this work is to enhance the knowledge in the field of bridge health prediction, where more comprehensive health performance in both serviceability and safety aspects are addressed jointly. The proposed models, characterised by probabilistic representation of bridge deterioration in hierarchical ways, demonstrated the effectiveness and pledge of DOOBNs approach to bridge health management. Additionally, the proposed models have significant potential for bridge maintenance optimization. Working together with advanced monitoring and inspection techniques, and a comprehensive bridge inventory, the proposed models can be used by bridge practitioners to achieve increased serviceability and safety as well as maintenance cost effectiveness.

Detection of right-to-left Atrial communication using agitated saline contrast imaging : experience with 1162 patients and recommendations for echocardiography

Background: Right-to-left shunting via a patent foramen ovale (PFO) has a recognized association with embolic events in younger patients. The use of agitated saline contrast imaging (ASCi) for detecting atrial shunting is well documented, however optimal technique is not well described. The purpose of this study is to assess the efficacy and safety of ASCi via TTE for assessment of right-to-left atrial communication in a large cohort of patients. Method: A retrospective review was undertaken of 1162 consecutive transthoracic (TTE) ASCi studies, of which 195 had also undergone clinically indicated transesophageal (TEE) echo. ASCi shunt results were compared with color flow imaging (CFI) and the role of provocative maneuvers (PM) assessed. Results: 403 TTE studies (35%) had paradoxical shunting seen during ASCi. Of these, 48% were positive with PM only. There was strong agreement between TTE ASCi and reported TEE findings (99% sensitivity, 85% specificity), with six false positive and two false negative results. In hindsight, the latter were likely due to suboptimal right atrial opacification, and the former due to transpulmonary shunting. TTE CFI was found to be insensitive (22%) for the detection of a PFO compared with TTE ASCi. Conclusions: TTE ASCi is minimally invasive and highly accurate for the detection of right-to-left atrial communication when PM are used. TTE CFI was found to be insensitive for PFO screening. It is recommended that TTE ASCi should be considered the initial diagnostic tool for the detection of PFO in clinical practice. A dedicated protocol should be followed to ensure adequate agitated saline contrast delivery and performance of provocative maneuvers.

Employment and industrial law in paramedic practice

This chapter will provide you with the some of the information you may need to make information on decisions in cases such as the one given above. In particular it will help you answer questions such as: 1. As Molly and Vikram are approaching the end of their shift, to attend will force them into overtime; could they refuse to attend the job on the basis of the refusal to do overtime outside of contracted hours? 2. Would their refusal be viewed as a breach of contract and therefore a disciplinary issue? 3. Why? 4. Does the need to attend this possibly gravely ill patient outweigh the demands of the paramedics to finish on time?

When the right to be counted doesn’t count : the politics and challenges of researching the health of asylum seekers

A fundamental prerequisite of population health research is the ability to establish an accurate denominator. This in turn requires that every individual in the study population is counted. However, this seemingly simple principle has become a point of conflict between researchers whose aim is to produce evidence of disparities in population health outcomes and governments whose policies promote(intentionally or not) inequalities that are the underlying causes of health disparities. Research into the health of asylum seekers is a case in point. There is a growing body of evidence documenting the adverse affects of recent changes in asylum-seeking legislation, including mandatory detention. However, much of this evidence has been dismissed by some governments as being unsound, biased and unscientific because, it is argued, evidence is derived from small samples or from case studies. Yet, it is the policies of governments that are the key barrier to the conduct of rigorous population health research on asylum seekers. In this paper, the authors discuss the challenges of counting asylum seekers and the limitations of data reported in some industrialized countries. They argue that the lack of accurate statistical data on asylum seekers has been an effective neo-conservative strategy for erasing the health inequalities in this vulnerable population, indeed a strategy that renders invisible this population. They describe some alternative strategies that may be used by researchers to obtain denominator data on hard-to-reach populations such as asylum seekers.

Employee perceptions regarding the effectiveness of occupational road safety initiatives

A range of risk management initiatives have been introduced in organisations in attempt to reduce occupational road incidents. However a discrepancy exists between the initiatives that are frequently implemented in organisations and the initiatives that have demonstrated scientific merit in improving occupational road safety. Given that employees’ beliefs may facilitate or act as a barrier to implementing initiatives, it is important to understand whether initiatives with scientific merit are perceived to be effective by employees. To explore employee perceptions pertaining to occupational road safety initiatives, a questionnaire was administered to 679 employees sourced from four Australian organisations. Participants ranged in age from 18 years to 65 years (M = 42, SD = 11). Participants rated 35 initiatives based on how effective they thought they would be in improving road safety in their organisation. The initiatives perceived by employees to be most effective in managing occupational road risks comprised: making vehicle safety features standard e.g. passenger airbags; practical driver skills training; and investigation of serious vehicle incidents. The initiatives perceived to be least effective in managing occupational road risks comprised: signing a promise card commitment to drive safely; advertising the organisation’s phone number on vehicles for complaints and compliments; and consideration of driving competency in staff selection process. Employee perceptions were analysed at a factor level and at an initiative level. The mean scores for the three extracted factors revealed that employees believed occupational road risks could best be managed by the employer implementing engineering and human resource methods to enhance road safety. Initiatives relating to employer management of identified risk factors were perceived to be more effective than feedback or motivational methods that required employees to accept responsibility for their driving safety. Practitioners can use the findings from this study to make informed decisions about how they select, manage and market occupational safety initiatives.

Asset health prediction using the explicit hazard model

The ability to estimate the asset reliability and the probability of failure is critical to reducing maintenance costs, operation downtime, and safety hazards. Predicting the survival time and the probability of failure in future time is an indispensable requirement in prognostics and asset health management. In traditional reliability models, the lifetime of an asset is estimated using failure event data, alone; however, statistically sufficient failure event data are often difficult to attain in real-life situations due to poor data management, effective preventive maintenance, and the small population of identical assets in use. Condition indicators and operating environment indicators are two types of covariate data that are normally obtained in addition to failure event and suspended data. These data contain significant information about the state and health of an asset. Condition indicators reflect the level of degradation of assets while operating environment indicators accelerate or decelerate the lifetime of assets. When these data are available, an alternative approach to the traditional reliability analysis is the modelling of condition indicators and operating environment indicators and their failure-generating mechanisms using a covariate-based hazard model. The literature review indicates that a number of covariate-based hazard models have been developed. All of these existing covariate-based hazard models were developed based on the principle theory of the Proportional Hazard Model (PHM). However, most of these models have not attracted much attention in the field of machinery prognostics. Moreover, due to the prominence of PHM, attempts at developing alternative models, to some extent, have been stifled, although a number of alternative models to PHM have been suggested. The existing covariate-based hazard models neglect to fully utilise three types of asset health information (including failure event data (i.e. observed and/or suspended), condition data, and operating environment data) into a model to have more effective hazard and reliability predictions. In addition, current research shows that condition indicators and operating environment indicators have different characteristics and they are non-homogeneous covariate data. Condition indicators act as response variables (or dependent variables) whereas operating environment indicators act as explanatory variables (or independent variables). However, these non-homogenous covariate data were modelled in the same way for hazard prediction in the existing covariate-based hazard models. The related and yet more imperative question is how both of these indicators should be effectively modelled and integrated into the covariate-based hazard model. This work presents a new approach for addressing the aforementioned challenges. The new covariate-based hazard model, which termed as Explicit Hazard Model (EHM), explicitly and effectively incorporates all three available asset health information into the modelling of hazard and reliability predictions and also drives the relationship between actual asset health and condition measurements as well as operating environment measurements. The theoretical development of the model and its parameter estimation method are demonstrated in this work. EHM assumes that the baseline hazard is a function of the both time and condition indicators. Condition indicators provide information about the health condition of an asset; therefore they update and reform the baseline hazard of EHM according to the health state of asset at given time t. Some examples of condition indicators are the vibration of rotating machinery, the level of metal particles in engine oil analysis, and wear in a component, to name but a few. Operating environment indicators in this model are failure accelerators and/or decelerators that are included in the covariate function of EHM and may increase or decrease the value of the hazard from the baseline hazard. These indicators caused by the environment in which an asset operates, and that have not been explicitly identified by the condition indicators (e.g. Loads, environmental stresses, and other dynamically changing environment factors). While the effects of operating environment indicators could be nought in EHM; condition indicators could emerge because these indicators are observed and measured as long as an asset is operational and survived. EHM has several advantages over the existing covariate-based hazard models. One is this model utilises three different sources of asset health data (i.e. population characteristics, condition indicators, and operating environment indicators) to effectively predict hazard and reliability. Another is that EHM explicitly investigates the relationship between condition and operating environment indicators associated with the hazard of an asset. Furthermore, the proportionality assumption, which most of the covariate-based hazard models suffer from it, does not exist in EHM. According to the sample size of failure/suspension times, EHM is extended into two forms: semi-parametric and non-parametric. The semi-parametric EHM assumes a specified lifetime distribution (i.e. Weibull distribution) in the form of the baseline hazard. However, for more industry applications, due to sparse failure event data of assets, the analysis of such data often involves complex distributional shapes about which little is known. Therefore, to avoid the restrictive assumption of the semi-parametric EHM about assuming a specified lifetime distribution for failure event histories, the non-parametric EHM, which is a distribution free model, has been developed. The development of EHM into two forms is another merit of the model. A case study was conducted using laboratory experiment data to validate the practicality of the both semi-parametric and non-parametric EHMs. The performance of the newly-developed models is appraised using the comparison amongst the estimated results of these models and the other existing covariate-based hazard models. The comparison results demonstrated that both the semi-parametric and non-parametric EHMs outperform the existing covariate-based hazard models. Future research directions regarding to the new parameter estimation method in the case of time-dependent effects of covariates and missing data, application of EHM in both repairable and non-repairable systems using field data, and a decision support model in which linked to the estimated reliability results, are also identified.

The role of, and key considerations for, advertising campaigns and educational awareness workshops within the work-related road safety context

Australian and international evidence suggests that, in the work-related driving context, road crashes account for a substantial number of occupational incidents. In the attempt to reduce injury and improve safety, organisations may implement an array of strategies and interventions ranging from policy development and implementation, vehicle selection and incident monitoring through to education and awareness-raising. This conceptual paper discusses aspects relating to the latter collection of interventions and, in particular, the role, and some key considerations with respect to the content and dissemination, of advertising campaigns and educational awareness workshops. In relation to advertising campaigns, this paper discusses how some of the overarching principles associated with advertising in the broader general community road safety strategy also apply within the work-related road safety context. Specifically, advertising campaigns/materials should be viewed as a key component within a dedicated organisational approach to road (driver) safety. This dedicated approach would need to comprise of a number, and varied array, of strategies. In addition, the content of, and medium/s (e.g., posters) by which to deliver such advertising campaigns, cannot be addressed by a one-size-fits all approach but, rather, requires careful consideration of the needs as well as characteristics of specific organisations and their driver fleet. The paper provides a summary of some key considerations when devising an advertising campaign, including the nature of campaign/message content as well as the processes by which to devise and refine such content. In relation to driver education awareness workshops, this paper outlines the key considerations for delivering a series of workshops specifically aimed at occupational driving within the organisational context. A case study approach will be utilised to demonstrate the manner in which educational awareness workshops can compliment successful advertising campaigns promoting safer work related driving through better risk management practice. Research underpinning the development of driver behaviour modification tools incorporated within the workshops will also be discussed along with the mechanisms utilised to encourage improvements in driver monitoring and behaviour. In an effort to assist organisations with their continual search for cost-effective approaches which may, ultimately, contribute to improvements in driver behaviour and safety, the current paper offers some clear and practical suggestions in relation to the development and dissemination of two types of interventions, advertising campaigns and education awareness workshops.

Translating vision research into policy and practice to improve visibility, and hence safety, of road workers at night

This case study report describes the stages involved in the translation of research on night-time visibility into standards for the safety clothing worn by roadworkers. Vision research demonstrates that when lights are placed on the moveable joints of the body and the person moves in a dark setting, the phenomenon known as “biological motion or biomotion” occurs, enabling rapid and accurate recognition of the human form although only the lights can be seen. QUT was successful in gaining funding from the Australian Research Council for a Linkage grant due to the support of the predecessors of the Queensland Department of Transport and Main Roads (TMR) to research the biomotion effect in on-road settings using materials that feature in roadworker clothing. Although positive results were gained, the process of translating the research results into policy, practices and standards relied strongly on the supportive efforts of TMR staff engaged in the review and promulgation of national standards. The ultimate result was the incorporation of biomotion marking into AS/NZS 4602.1 2011. The experiences gained in this case provide insights into the processes involved in translating research into practice.