The primacy of vital signs – Acute care nurses’ and midwives’ use of physical assessment skills: A cross sectional study

BACKGROUND: Registered nurses and midwives play an essential role in detecting patients at risk of deterioration through ongoing assessment and action in response to changing health status. Yet, evidence suggests that clinical deterioration frequently goes unnoticed in hospitalised patients. While much attention has been paid to early warning and rapid response systems, little research has examined factors related to physical assessment skills. OBJECTIVES: To determine a minimum data set of core skills used during nursing assessment of hospitalised patients and identify nurse and workplace predictors of the use of physical assessment to detect patient deterioration. DESIGN: The study used a single-centre, cross-sectional survey design. SETTING and PARTICIPANTS: The study included 434 registered nurses and midwives (Grades 5-7) involved in clinical care of patients on acute care wards, including medicine, surgery, oncology, mental health and maternity service areas, at a 929-bed tertiary referral teaching hospital in Southeast Queensland, Australia. METHODS: We conducted a hospital-wide survey of registered nurses and midwives using the 133-item Physical Assessment Skills Inventory and the 58-item Barriers to Registered Nurses’ Use of Physical Assessment scale. Median frequency for each physical assessment skill was calculated to determine core skills. To explore predictors of core skill utilisation, backward stepwise general linear modelling was conducted. Means and regression coefficients are reported with 95% confidence intervals. A p value < .05 was considered significant for all analyses. RESULTS: Core skills used by most nurses every time they worked included assessment of temperature, oxygen saturation, blood pressure, breathing effort, skin, wound and mental status. Reliance on others and technology (F = 35.77, p < .001), lack of confidence (F = 5.52, p = .02), work area (F = 3.79, p = .002), and clinical role (F = 44.24, p < .001) were significant predictors of the extent of physical assessment skill use. CONCLUSIONS: The increasing acuity of the acute care patient plausibly warrants more than vital signs assessment; however, our study confirms nurses’ physical assessment core skill set is mainly comprised of vital signs. The focus on these endpoints of deterioration as dictated by early warning and rapid response systems may divert attention from and devalue comprehensive nursing assessment that could detect subtle changes in health status earlier in the patient's hospitalisation.

Simultaneous underwater visibility assessment, enhancement and improved stereo

Vision-based underwater navigation and obstacle avoidance demands robust computer vision algorithms, particularly for operation in turbid water with reduced visibility. This paper describes a novel method for the simultaneous underwater image quality assessment, visibility enhancement and disparity computation to increase stereo range resolution under dynamic, natural lighting and turbid conditions. The technique estimates the visibility properties from a sparse 3D map of the original degraded image using a physical underwater light attenuation model. Firstly, an iterated distance-adaptive image contrast enhancement enables a dense disparity computation and visibility estimation. Secondly, using a light attenuation model for ocean water, a color corrected stereo underwater image is obtained along with a visibility distance estimate. Experimental results in shallow, naturally lit, high-turbidity coastal environments show the proposed technique improves range estimation over the original images as well as image quality and color for habitat classification. Furthermore, the recursiveness and robustness of the technique allows implementation onboard an Autonomous Underwater Vehicle for improving navigation and obstacle avoidance performance.

Automated counting of the Northern Pacific Sea Star in the Derwent using shape recognition

A novel shape recognition algorithm was developed to autonomously classify the Northern Pacific Sea Star (Asterias amurenis) from benthic images that were collected by the Starbug AUV during 6km of transects in the Derwent estuary. Despite the effects of scattering, attenuation, soft focus and motion blur within the underwater images, an optimal joint classification rate of 77.5% and misclassification rate of 13.5% was achieved. The performance of algorithm was largely attributed to its ability to recognise locally deformed sea star shapes that were created during the segmentation of the distorted images.

Automated sensory data alignment for environmental and epidermal change monitoring

In this paper we present research adapting a state of the art condition-invariant robotic place recognition algorithm to the role of automated inter- and intra-image alignment of sensor observations of environmental and skin change over time. The approach involves inverting the typical criteria placed upon navigation algorithms in robotics; we exploit rather than attempt to fix the limited camera viewpoint invariance of such algorithms, showing that approximate viewpoint repetition is realistic in a wide range of environments and medical applications. We demonstrate the algorithms automatically aligning challenging visual data from a range of real-world applications: ecological monitoring of environmental change, aerial observation of natural disasters including flooding, tsunamis and bushfires and tracking wound recovery and sun damage over time and present a prototype active guidance system for enforcing viewpoint repetition. We hope to provide an interesting case study for how traditional research criteria in robotics can be inverted to provide useful outcomes in applied situations.

Class participation as a learning and assessment strategy in law : facilitating students’ engagement, skills development and deep learning

Assessment has widely been described as being ‘at the centre of the student experience’. It would be difficult to conceive of the modern teaching university without it. Assessment is accepted as one of the most important tools that an educator can deploy to influence both what and how students learn. Evidence suggests that how students allocate time and effort to tasks and to developing an understanding of the syllabus is affected by the method of assessment utilised and the weighting it is given. This is particularly significant in law schools where law students may be more preoccupied with achieving high grades in all courses than their counterparts from other disciplines. However, well-designed assessment can be seen as more than this. It can be a vehicle for encouraging students to learn and engage more broadly than with the minimums required to complete the assessment activity. In that sense assessment need not merely ‘drive’ learning, but can instead act as a catalyst for further learning beyond what a student had anticipated. In this article we reconsider the potential roles and benefits in legal education of a form of interactive classroom learning we term assessable class participation (‘ACP’), both as part of a pedagogy grounded in assessment and learning theory, and as a platform for developing broader autonomous approaches to learning amongst students. We also consider some of the barriers students can face in ACP and the ways in which teacher approaches to ACP can positively affect the socio-emotional climates in classrooms and thus reduce those barriers. We argue that the way in which a teacher facilitates ACP is critical to the ability to develop positive emotional and learning outcomes for law students, and for teachers themselves.

Valuable learning, unwelcome assessment : what LLB and JD students really think about group work

This article contributes to current debates about the appropriate role of group work in legal curricula by providing insights into the attitudes of Bachelor of Laws (‘LLB’) and Juris Doctor (‘JD’) students towards such tasks. It begins by reviewing arguments for incorporating group work in legal education, both as a result of the recognition of its educational benefits, and as a response to increasing regulatory expectations regarding student collaboration skills. The article then reports the findings of a UNSW Law School Student Assessment Survey designed to determine how law students perceive group work and its assessment in law. One of the most striking findings is that many of the law students surveyed recognise and appreciate the learning and skills development benefits of group tasks, but are resistant to summative assessment of group work. Moreover, there are marked differences in attitude between LLB and JD students, and across year cohorts within those degrees. These findings suggest that further thought needs to be directed towards the specific purposes underpinning the choice of group work as a pedagogical tool, and assessment that is congruent with those purposes, taking into account the varying needs and experiences of different cohorts of students. The article concludes by considering whether meaningful group work can exist without summative assessment.

Development of a climate assessment tool for hybrid air conditioner

Australian climate is highly suitable for using outdoor air for free building cooling. In order to evaluate the suitability of hybrid cooler for specific applications, a pre-design climate assessment tool is developed and presented in this paper. In addition to the consideration of the local climate, comfort zone proposed by ASHRAE handbook and specific design of building and operation of hybrid cooler, possible influence from environmental factors (e.g. air humidity and air velocity), as well as personal factors (e.g. activity level and clothing insulation) on occupant’s thermal comfort are also considered in this tool. It is demonstrated that with the input of climatic data for a particular location and the associated design data for a specific application, the developed climate assessment tool is able to not only sort outdoor air conditions into the different process regions but also project them onto the psychrometric chart. It can also be used to estimate the hours for an individual operational mode under various climate conditions and summarize them in a table “Results”.

Assessment and application of clustering techniques to atmospheric particle number size distribution for the purpose of source apportionment

Long-term measurements of particle number size distribution (PNSD) produce a very large number of observations and their analysis requires an efficient approach in order to produce results in the least possible time and with maximum accuracy. Clustering techniques are a family of sophisticated methods which have been recently employed to analyse PNSD data, however, very little information is available comparing the performance of different clustering techniques on PNSD data. This study aims to apply several clustering techniques (i.e. K-means, PAM, CLARA and SOM) to PNSD data, in order to identify and apply the optimum technique to PNSD data measured at 25 sites across Brisbane, Australia. A new method, based on the Generalised Additive Model (GAM) with a basis of penalised B-splines, was proposed to parameterise the PNSD data and the temporal weight of each cluster was also estimated using the GAM. In addition, each cluster was associated with its possible source based on the results of this parameterisation, together with the characteristics of each cluster. The performances of four clustering techniques were compared using the Dunn index and Silhouette width validation values and the K-means technique was found to have the highest performance, with five clusters being the optimum. Therefore, five clusters were found within the data using the K-means technique. The diurnal occurrence of each cluster was used together with other air quality parameters, temporal trends and the physical properties of each cluster, in order to attribute each cluster to its source and origin. The five clusters were attributed to three major sources and origins, including regional background particles, photochemically induced nucleated particles and vehicle generated particles. Overall, clustering was found to be an effective technique for attributing each particle size spectra to its source and the GAM was suitable to parameterise the PNSD data. These two techniques can help researchers immensely in analysing PNSD data for characterisation and source apportionment purposes.

Balancing the books : an assessment of financial stress associated with social work and human service student placements

This report presents the findings from a study of the financial impact of work-integrated learning commonly referred to as 'placement' among social work and human services students. Based on a survey of 214 respondants, 14 in-depth interviews and two focus groups, the findings indicate that two thirds of the surveyed group felt tired and anxious about their experience of balancing paid work and placement, with 2 in 5 reporting their learning experience was compromised as a result. The significant implications and potential solutions are also discussed.

Neighborhood sustainability assessment : evaluating residential development sustainability in a developing country context

Rapid urbanization, improved quality of life, and diversified lifestyle options have collectively led to an escalation in housing demand in our cities, where residential areas, as the largest portion of urban land use type, play a critical role in the formation of sustainable cities. To date there has been limited research to ascertain residential development layouts that provide a more sustainable urban outcome. This paper aims to evaluate and compare sustainability levels of residential types by focusing on their layouts. The paper scrutinizes three different development types in a developing country context—i.e., subdivision, piecemeal, and master-planned developments. This study develops a “Neighborhood Sustainability Assessment” tool and applies it to compare their sustainability levels in Ipoh, Malaysia. The analysis finds that the master-planned development, amongst the investigated case studies, possesses the potential to produce higher levels of sustainability outcomes. The results reveal insights and evidence for policymakers, planners, development agencies and researchers; advocate further studies on neighborhood-level sustainability analysis, and; emphasize the need for collective efforts and an effective process in achieving neighborhood sustainability and sustainable city formation.

Energy use assessment of educational buildings: Toward a campus-wide sustainable energy policy

The purpose of this article is to assess the viability of blanket sustainability policies, such as Building Rating Systems in achieving energy efficiency in university campus buildings. We analyzed the energy consumption trends of 10 LEED-certified buildings and 14 non-LEED certified buildings at a major university in the US. Energy Use Intensity (EUI) of the LEED buildings was significantly higher (EUILEED= 331.20 kBtu/sf/yr) than non-LEED buildings (EUInon-LEED=222.70 kBtu/sf/yr); however, the median EUI values were comparable (EUILEED= 172.64 and EUInon-LEED= 178.16). Because the distributions of EUI values were non-symmetrical in this dataset, both measures can be used for energy comparisons—this was also evident when EUI computations exclude outliers, EUILEED=171.82 and EUInon-LEED=195.41. Additional analyses were conducted to further explore the impact of LEED certification on university campus buildings energy performance. No statistically significant differences were observed between certified and non-certified buildings through a range of robust comparison criteria. These findings were then leveraged to devise strategies to achieve sustainable energy policies for university campus buildings and to identify potential issues with portfolio level building energy performance comparisons.

Evolutionary game design : automated game design comes of age

The "Humies" awards are an annual competition held in conjunction with the Genetic and Evolutionary Computation Conference (GECCO), in which cash prizes totalling $10,000 are awarded to the most human-competitive results produced by any form of evolutionary computation published in the previous year. This article describes the gold medal-winning entry from the 2012 "Humies" competition, based on the LUDI system for playing, evaluating and creating new board games. LUDI was able to demonstrate human-competitive results in evolving novel board games that have gone on to be commercially published, one of which, Yavalath, has been ranked in the top 2.5% of abstract board games ever invented. Further evidence of human-competitiveness was demonstrated in the evolved games implicitly capturing several principles of good game design, outperforming human designers in at least one case, and going on to inspire a new sub-genre of games.

In pursuit of some appreciation: Assessment and group membership in children’s second stories

Group membership is central to social interaction. Within peer groups, social hierarchies and affiliations are matters to which members seriously attend (Corsaro, 2014). Studies of peer groups highlight how status is achieved through oppositional actions. This paper examines the way in which competition and collaboration in a children’s peer group accomplishes status during the production and management of “second stories” (Sacks 1992). We present analysis of the interaction of young boys in a preparatory year playground who are engaged in a single instance of storytelling “rounds”. Analysis highlights the pivotal role of members’ contributions, assessments and receipts in a series of second stories that enact a simultaneously competitive and collaborative local order.

Real-time assessment of GNSS observation noise with single receivers

Stochastic modelling is critical in GNSS data processing. Currently, GNSS data processing commonly relies on the empirical stochastic model which may not reflect the actual data quality or noise characteristics. This paper examines the real-time GNSS observation noise estimation methods enabling to determine the observation variance from single receiver data stream. The methods involve three steps: forming linear combination, handling the ionosphere and ambiguity bias and variance estimation. Two distinguished ways are applied to overcome the ionosphere and ambiguity biases, known as the time differenced method and polynomial prediction method respectively. The real time variance estimation methods are compared with the zero-baseline and short-baseline methods. The proposed method only requires single receiver observation, thus applicable to both differenced and un-differenced data processing modes. However, the methods may be subject to the normal ionosphere conditions and low autocorrelation GNSS receivers. Experimental results also indicate the proposed method can result on more realistic parameter precision.

The challenge of developing a fleet driving risk assessment tool: What can be learned from the process?

One of the riskiest activities in the course of a person's work is driving. By developing and testing a new work driving risk assessment measurement tool for use by organisations this research will contribute to the safety of those who drive for work purposes. The research results highlighted limitations associated with current self-report measures and provided evidence that the work driving environment is extremely complex and involves constant interactions between humans, vehicles, the road environment, and the organisational context.