Examination of relationships and mediating effects of self-efficacy, locus of control, coping and the practice environment on caring efficacy and job satisfaction in Australian registered nurses

Background to the Problem: Improving nurses' self-efficacy and job satisfaction may improve the quality of nursing care to patients. Moreover, to work effectively and consistently with professional nursing standards, nurses have to believe they are able to make decisions about their practice. In order to identify what strategies and professional development programmes should be developed and implemented for registered nurses in the Australian context, a comprehensive profile of registered nurses and factors that affect nursing care in Australia needs to be available. However, at present, there is limited information available on a) the perceived caring efficacy and job satisfaction of registered nurses in Australia, and b) the relationships between the demographic variables general self-efficacy, work locus of control, coping styles, the professional nursing practice environment and caring efficacy and job satisfaction of registered nurses in Australia. This is the first study to 1) investigate relationships between caring efficacy and job satisfaction with factors such as general self-efficacy, locus of control and coping, 2) the nursing practice environment in the Australian context and 3) conceptualise a model of caring efficacy and job satisfaction in the Australian context. Research Design and Methods: This study used a two-phase cross-sectional survey design. A pilot study was conducted in order to determine the validity and reliability of the survey instruments and to assess the effectiveness of the participant recruitment process. The second study of the research involved investigating the relationships between the socio-demographic, dependent and independent variables. Socio-demographic variables included age, gender, level of education, years of experience, years in current job, employment status, geographical location, specialty area, health sector, state and marital status. Other independent variables in this study included general self-efficacy, work locus of control, coping styles and the professional nursing practice environment. The dependent variables were job satisfaction and caring efficacy. Results: A confirmatory factor analysis of the Brisbane Practice Environment Measure (B-PEM) was conducted. A five-factor structure of the B-PEM was confirmed. Relationships between socio-demographic variables, caring efficacy and job satisfaction, were identified at the bivariate and multivariable levels. Further, examination using structural equation modelling revealed general self-efficacy, work locus of control, coping style and the professional nursing practice environment contributed to caring efficacy and job satisfaction of registered nurses in Australia. Conclusion: This research contributes to the literature on how socio-demographic, personal and environmental variables (work locus of control, general self-efficacy and the nursing practice environment) influence caring efficacy and job satisfaction in registered nurses in Australia. Caring efficacy and job satisfaction may be improved if general self-efficacy is high in those that have an internal work locus of control. The study has also shown that practice environments that provide the necessary resources improve job satisfaction in nurses. The results have identified that the development and implementation of strategies for professional development and orientation programmes that enhance self-efficacy and work locus of control may contribute to better quality nursing practice and job satisfaction. This may further assist registered nurses towards focusing on improving their practice abilities. These strategies along with practice environments that provide the necessary resources for nurses to practice effectively may lead to better job satisfaction. This information is important for nursing leaders, healthcare organisations and policymakers, as the development and implementation of these strategies may lead to better recruitment and retention of nurses. The study results will contribute to the national and international literature on self-efficacy, job satisfaction and nursing practice.

Neuromuscular imbalances in the track sprinter

Athletic coaching can involve observation of a motor control task and then proposing guidance to an athlete about how the task performance can be developed. Coaches can identify the technique elements that seem to hinder performance and then provide instruction. Recently, a variety of training methods were proposed to enhance sprint performance, however a number of authors have identified these methods as characterised by low scientific evaluation or support (Brown & Vescovi, 2012; Jones, Bezodis, & Thompson, 2009). This article will outline a scientifically robust neuromuscular theory underlying poor movement techniques that may be visible when coaches observe sprint performance. The goal of this article is to inform the sprint coach of a method to identify and correct suboptimal biomechanics to enhance athletic performance.

Bayesian hierarchical models in statistical quality control methods to improve healthcare in hospitals

Quality oriented management systems and methods have become the dominant business and governance paradigm. From this perspective, satisfying customers’ expectations by supplying reliable, good quality products and services is the key factor for an organization and even government. During recent decades, Statistical Quality Control (SQC) methods have been developed as the technical core of quality management and continuous improvement philosophy and now are being applied widely to improve the quality of products and services in industrial and business sectors. Recently SQC tools, in particular quality control charts, have been used in healthcare surveillance. In some cases, these tools have been modified and developed to better suit the health sector characteristics and needs. It seems that some of the work in the healthcare area has evolved independently of the development of industrial statistical process control methods. Therefore analysing and comparing paradigms and the characteristics of quality control charts and techniques across the different sectors presents some opportunities for transferring knowledge and future development in each sectors. Meanwhile considering capabilities of Bayesian approach particularly Bayesian hierarchical models and computational techniques in which all uncertainty are expressed as a structure of probability, facilitates decision making and cost-effectiveness analyses. Therefore, this research investigates the use of quality improvement cycle in a health vii setting using clinical data from a hospital. The need of clinical data for monitoring purposes is investigated in two aspects. A framework and appropriate tools from the industrial context are proposed and applied to evaluate and improve data quality in available datasets and data flow; then a data capturing algorithm using Bayesian decision making methods is developed to determine economical sample size for statistical analyses within the quality improvement cycle. Following ensuring clinical data quality, some characteristics of control charts in the health context including the necessity of monitoring attribute data and correlated quality characteristics are considered. To this end, multivariate control charts from an industrial context are adapted to monitor radiation delivered to patients undergoing diagnostic coronary angiogram and various risk-adjusted control charts are constructed and investigated in monitoring binary outcomes of clinical interventions as well as postintervention survival time. Meanwhile, adoption of a Bayesian approach is proposed as a new framework in estimation of change point following control chart’s signal. This estimate aims to facilitate root causes efforts in quality improvement cycle since it cuts the search for the potential causes of detected changes to a tighter time-frame prior to the signal. This approach enables us to obtain highly informative estimates for change point parameters since probability distribution based results are obtained. Using Bayesian hierarchical models and Markov chain Monte Carlo computational methods, Bayesian estimators of the time and the magnitude of various change scenarios including step change, linear trend and multiple change in a Poisson process are developed and investigated. The benefits of change point investigation is revisited and promoted in monitoring hospital outcomes where the developed Bayesian estimator reports the true time of the shifts, compared to priori known causes, detected by control charts in monitoring rate of excess usage of blood products and major adverse events during and after cardiac surgery in a local hospital. The development of the Bayesian change point estimators are then followed in a healthcare surveillances for processes in which pre-intervention characteristics of patients are viii affecting the outcomes. In this setting, at first, the Bayesian estimator is extended to capture the patient mix, covariates, through risk models underlying risk-adjusted control charts. Variations of the estimator are developed to estimate the true time of step changes and linear trends in odds ratio of intensive care unit outcomes in a local hospital. Secondly, the Bayesian estimator is extended to identify the time of a shift in mean survival time after a clinical intervention which is being monitored by riskadjusted survival time control charts. In this context, the survival time after a clinical intervention is also affected by patient mix and the survival function is constructed using survival prediction model. The simulation study undertaken in each research component and obtained results highly recommend the developed Bayesian estimators as a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances as well as industrial and business contexts. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The empirical results and simulations indicate that the Bayesian estimators are a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The advantages of the Bayesian approach seen in general context of quality control may also be extended in the industrial and business domains where quality monitoring was initially developed.

Nonlinear H_infinity control of UAVs for collision avoidance in gusty environments

This paper proposes a nonlinear H_infinity controller for stabilization of velocities, attitudes and angular rates of a fixed-wing unmanned aerial vehicle (UAV) in a windy environment. The suggested controller aims to achieve a steady-state flight condition in the presence of wind gusts such that the host UAV can be maneuvered to avoid collision with other UAVs during cruise flight with safety guarantees. This paper begins with building a proper model capturing flight aerodynamics of UAVs. Then a nonlinear controller is developed with gust attenuation and rapid response properties. Simulations are conducted for the Shadow UAV to verify performance of the proposed con- troller. Comparative studies with the proportional-integral-derivative (PID) controllers demonstrate that the proposed controller exhibits great performance improvement in a gusty environment, making it suitable for integration into the design of flight control systems for cruise flight of UAVs.

Optimising weed control by considering disturbance

Mounting scientific evidence suggests newly imposed disturbance and/or alterations to existing disturbances facilitate invasion. Several empirical studies have explored the role of disturbance in invasion, but little work has been done to fit current understanding into a format useful for practical control efforts. We are working towards addressing this shortcoming by developing a metapopulation model couched in a decision theory framework. This approach has allowed us to investigate how incorporating the negative effects of disturbance on native vegetation into decision-making can change optimal control measures. In this paper, we present some preliminary results.

Physical access control administration using building information models

Physical access control systems play a central role in the protection of critical infrastructures, where both the provision of timely access and preserving the security of sensitive areas are paramount. In this paper we discuss the shortcomings of existing approaches to the administration of physical access control in complex environments. At the heart of the problem is the current dependency on human administrators to reason about the implications of the provision or the revocation of staff access to an area within these facilities. We demonstrate how utilising Building Information Models (BIMs) and the capabilities they provide, including 3D representation of a facility and path-finding can reduce possible intentional or accidental errors made by security administrators.

Reducing actuator switchings for motion control of autonomous underwater vehicles

A priority when designing control strategies for autonomous underwater vehicles is to emphasize their cost of implementation on a real vehicle and at the same time to minimize a prescribed criterion such as time, energy, payload or combination of those. Indeed, the major issue is that due to the vehicles' design and the actuation modes usually under consideration for underwater platforms the number of actuator switchings must be kept to a small value to ensure feasibility and precision. This constraint is typically not verified by optimal trajectories which might not even be piecewise constants. Our goal is to provide a feasible trajectory that minimizes the number of switchings while maintaining some qualities of the desired trajectory, such as optimality with respect to a given criterion. The one-sided Lipschitz constant is used to derive theoretical estimates. The theory is illustrated on two examples, one is a fully actuated underwater vehicle capable of motion in six degrees-of-freedom and one is minimally actuated with control motions constrained to the vertical plane.

Rough fuzzy control of SVC for power system stability enhancement

This paper presents a new approach to the design of a rough fuzzy controller for the control loop of the SVC (static VAR system) in a two area power system for stability enhancement with particular emphasis on providing effective damping for oscillatory instabilities. The performances of the rough fuzzy and the conventional fuzzy controller are compared with that of the conventional PI controller for a variety of transient disturbances, highlighting the effectiveness of the rough fuzzy controller in damping the inter-area oscillations. The effect of the rough fuzzy controller in improving the CCT (critical clearing time) of the two area system is elaborated in this paper as well.

Videogame control device impact on the play experience

New types of control devices for videogames have emerged and expanded the demographics of the game playing public, yet little is known about which populations of gamers prefer which style of interaction and why. This paper presents data from a study that seeks to clarify the influence the control interface has on the play experience. Three commercial control devices were categorised using an existing typology, according to how the interface maps physical control inputs with the virtual gameplay actions. The devices were then used in a within-groups experimental design aimed at measuring differences in play experience across 64 participants. Descriptive analysis is undertaken on the performance, play experience and preference results for each device. Potential explanations for these results are discussed, as well as the direction of future work.

A review of the effectiveness of speed control measures in roadwork zones

Noncompliance with speed limits is one of the major safety concerns in roadwork zones. Although numerous studies have attempted to evaluate the effectiveness of safety measures on speed limit compliance, many report inconsistent findings. This paper aims to review the effectiveness of four categories of roadwork zone speed control measures: Informational, Physical, Enforcement, and Educational measures. While informational measures (static signage, variable message signage) evidently have small to moderate effects on speed reduction, physical measures (rumble strips, optical speed bars) are found ineffective for transient and moving work zones. Enforcement measures (speed camera, police presence) have the greatest effects, while educational measures also have significant potential to improve public awareness of roadworker safety and to encourage slower speeds in work zones. Inadequate public understanding of roadwork risks and hazards, failure to notice signs, and poor appreciation of safety measures are the major causes of noncompliance with speed limits.

Risk control in transmission system expansion planning with wind generators

With the advent of large-scale wind farms and their integration into electrical grids, more uncertainties, constraints and objectives must be considered in power system development. It is therefore necessary to introduce risk-control strategies into the planning of transmission systems connected with wind power generators. This paper presents a probability-based multi-objective model equipped with three risk-control strategies. The model is developed to evaluate and enhance the ability of the transmission system to protect against overload risks when wind power is integrated into the power system. The model involves: (i) defining the uncertainties associated with wind power generators with probability measures and calculating the probabilistic power flow with the combined use of cumulants and Gram-Charlier series; (ii) developing three risk-control strategies by specifying the smallest acceptable non-overload probability for each branch and the whole system, and specifying the non-overload margin for all branches in the whole system; (iii) formulating an overload risk index based on the non-overload probability and the non-overload margin defined; and (iv) developing a multi-objective transmission system expansion planning (TSEP) model with the objective functions composed of transmission investment and the overload risk index. The presented work represents a superior risk-control model for TSEP in terms of security, reliability and economy. The transmission expansion planning model with the three risk-control strategies demonstrates its feasibility in the case study using two typical power systems

Positive impacts of environmental characteristics on health and wellbeing in health-care facilities : a review

Well-designed indoor environments can support people’s health and welfare. In this literature review, we identify the environmental features that affect human health and wellbeing. Environmental characteristics found to influence health outcomes and/or wellbeing included: environmental safety; indoor air quality (e.g. odour and temperature); sound and noise; premises and interior design (e.g. construction materials, viewing nature and experiencing nature, windows versus no windows, light, colours, unit layout and placement of the furniture, the type of room, possibilities to control environmental elements, environmental complexity and sensory simulations, cleanliness, ergonomics and accessibility, ‛‛wayfinding’’); art, and music, among others. Indoor environments that incorporate healing elements can, for instance, reduce anxiety, lower blood pressure, lessen pain and shorten hospital stays.

The interaction between exercise, appetite and food intake : implications for weight control

Exercise could indirectly affect body weight by exerting changes on various components of appetite control, including nutrient and taste preferences, meal size and frequency, and the drive to eat. This review summarizes the evidence on how exercise affects appetite and eating behavior and in particular answers the question, “Does exercise induce an increase in food intake to compensate for the increase in energy expenditure?” Evidence will be presented to demonstrate that there is no automatic increase in food intake in response to acute exercise and that the response to repeated exercise is variable. The review will also identify areas of further study required to explain the variability. One limitation with studies that assess the efficacy of exercise as a method of weight control is that only mean data are presented—the individual variability tends to be overlooked. Recent evidence highlights the importance of characterizing the individual variability by demonstrating exercise-induced changes in appetite. Individuals who experience lower than theoretically predicted reductions in body weight can be characterized by hedonic (eg, pleasure) and homeostatic (eg, hunger) features.

Encouraging learners to drive using game elements and smartphones

Young drivers aged 17-24 years are at a risk of death and injury from road crashes primarily due to their age and inexperience on the road. Our research aims to investigate if a gamified mobile tracking and intervention tool can help to address this issue. We aim to build a smartphone application to support the current process of logging driving hours using a physical logbook and pen in Queensland. This provides an easier way to log driving hours than recording them in a logbook. In an attempt to engage Learners and encourage them to undertake more diverse driving practice we will explore how game elements can be integrated into the experience to motivate Learners. Previous research in other domains has shown that framing tasks as game-like can help engage and motivate users, however the addition of game elements to this space provides some interesting design challenges. This paper presents an overview of the research and presents these challenges for further discussion.

Refraction in children : a comparison of two methods of accommodation control

Purpose: The prevalence of refractive errors in children has been extensively researched. Comparisons between studies can, however, be compromised because of differences between accommodation control methods and techniques used for measuring refractive error. The aim of this study was to compare spherical refractive error results obtained at baseline and using two different accommodation control methods – extended optical fogging and cycloplegia, for two measurement techniques – autorefraction and retinoscopy. Methods: Participants comprised twenty-five school children aged between 6 and 13 years (mean age: 9.52 ± 2.06 years). The refractive error of one eye was measured at baseline and again under two different accommodation control conditions: extended optical fogging (+2.00DS for 20 minutes) and cycloplegia (1% cyclopentolate). Autorefraction and retinoscopy were both used to measure most plus spherical power for each condition. Results: A significant interaction was demonstrated between measurement technique and accommodation control method (p = 0.036), with significant differences in spherical power evident between accommodation control methods for each of the measurement techniques (p < 0.005). For retinoscopy, refractive errors were significantly more positive for cycloplegia compared to optical fogging, which were in turn significantly more positive than baseline, while for autorefraction, there were significant differences between cycloplegia and extended optical fogging and between cycloplegia and baseline only. Conclusions: Determination of refractive error under cycloplegia elicits more plus than using extended optical fogging as a method to relax accommodation. These findings support the use of cycloplegic refraction compared with extended optical fogging as a means of controlling accommodation for population based refractive error studies in children.