Establishing research in a palliative care clinical setting : perceived barriers and implemented strategies

There are many challenges in developing research projects in research-naïve clinical settings, especially palliative care where resistance to participate in research has been identified. These challenges to the implementation of research are common in nursing practice and are associated with attitudes towards research participation, and some lack of understanding of research as a process to improve clinical practice. This is despite the professional nursing requirement to conduct research into issues that influence palliative care practice. The purpose of this paper is to describe the process of implementing a clinical research project in collaboration with the clinicians of a palliative care community team and to reflect on the strategies implemented to overcome the challenges involved. The challenges presented here demonstrate the importance of proactively implementing engagement strategies from the inception of a research project in a clinical setting.

Challenges of recruiting hospice patients with advanced cancer to research : reflections on a delirium screening study

Introduction Delirium research in palliative care, particularly in the dying phase, is possible but is frequently met with ethical and methodological challenges. This paper describes the challenges faced in a previous delirium screening study. Methods Within 72 hours of admission to an acute inpatient specialist palliative care unit one hundred consecutive patients over 18 years of age with advanced cancer were invited to be screened for delirium using validated screening tools. Results Of the 100 consecutive admissions 49 patients were unable to participate including seven who did not meet the inclusion criteria and nine (six families and three patients) who withheld consent. The remaining 33 patients were more unwell and closer to death than those who were recruited. Reasons for non- participation included being too unwell (ten), unresponsive (nine), died (two) or discharged (three) before recruitment and exceeding the 72hour time limit (nine). Conclusion Gate keeping and physical condition of patients were the main obstacles to recruitment and is consistent with barriers faced in previous studies involving palliative care and dying patients. While it is possible and necessary to conduct studies in palliative care, including the terminal phase, as reflective practitioners we must maintain the balance between the demands for evidence-based practice and our compassion and respect for our most vulnerable of patients.

Towards a methodology for examining Twitter follower accession

The analysis of content and meta–data has long been the subject of most Twitter studies, however such research only tells part of the story of the development of Twitter as a platform. In this work, we introduce a methodology to determine the growth patterns of individual users of the platform, a technique we refer to as follower accession, and through a number of case studies consider the factors which lead to follower growth, and the identification of non–authentic followers. Finally, we consider what such an approach tells us about the history of the platform itself, and the way in which changes to the new user signup process have impacted upon users.

Automated classification of limb fractures from free-text radiology reports using a clinician-informed gazetteer methodology

Background Timely diagnosis and reporting of patient symptoms in hospital emergency departments (ED) is a critical component of health services delivery. However, due to dispersed information resources and a vast amount of manual processing of unstructured information, accurate point-of-care diagnosis is often difficult. Aims The aim of this research is to report initial experimental evaluation of a clinician-informed automated method for the issue of initial misdiagnoses associated with delayed receipt of unstructured radiology reports. Method A method was developed that resembles clinical reasoning for identifying limb abnormalities. The method consists of a gazetteer of keywords related to radiological findings; the method classifies an X-ray report as abnormal if it contains evidence contained in the gazetteer. A set of 99 narrative reports of radiological findings was sourced from a tertiary hospital. Reports were manually assessed by two clinicians and discrepancies were validated by a third expert ED clinician; the final manual classification generated by the expert ED clinician was used as ground truth to empirically evaluate the approach. Results The automated method that attempts to individuate limb abnormalities by searching for keywords expressed by clinicians achieved an F-measure of 0.80 and an accuracy of 0.80. Conclusion While the automated clinician-driven method achieved promising performances, a number of avenues for improvement were identified using advanced natural language processing (NLP) and machine learning techniques.

Linking research and practice

Understanding the key factors that influence the evidentiary basis for practice and using skills in retrieving evidence that informs practice change are essential to the development of a health professional's career, regardless of the discipline. This chapter focuses on the key links between research and practice, particularly how health professionals use various sources of evidence and new knowledge to inform and improve the effectiveness of their practice in order to benefit the health of clients. Evidence-based practice and research utilisation are two major global research/practice initiatives that form the basis for this chapter. Examples that illustrate the real-world application of these initiatives are included in the Research Alive and Case Study sections. How practice change can be facilitated within health organisations is also briefly introduced.

Methodology for developing real-time motorway traffic risk identification models using individual-vehicle data

Most of existing motorway traffic safety studies using disaggregate traffic flow data aim at developing models for identifying real-time traffic risks by comparing pre-crash and non-crash conditions. One of serious shortcomings in those studies is that non-crash conditions are arbitrarily selected and hence, not representative, i.e. selected non-crash data might not be the right data comparable with pre-crash data; the non-crash/pre-crash ratio is arbitrarily decided and neglects the abundance of non-crash over pre-crash conditions; etc. Here, we present a methodology for developing a real-time MotorwaY Traffic Risk Identification Model (MyTRIM) using individual vehicle data, meteorological data, and crash data. Non-crash data are clustered into groups called traffic regimes. Thereafter, pre-crash data are classified into regimes to match with relevant non-crash data. Among totally eight traffic regimes obtained, four highly risky regimes were identified; three regime-based Risk Identification Models (RIM) with sufficient pre-crash data were developed. MyTRIM memorizes the latest risk evolution identified by RIM to predict near future risks. Traffic practitioners can decide MyTRIM’s memory size based on the trade-off between detection and false alarm rates. Decreasing the memory size from 5 to 1 precipitates the increase of detection rate from 65.0% to 100.0% and of false alarm rate from 0.21% to 3.68%. Moreover, critical factors in differentiating pre-crash and non-crash conditions are recognized and usable for developing preventive measures. MyTRIM can be used by practitioners in real-time as an independent tool to make online decision or integrated with existing traffic management systems.

AUSPRAC : The Nurse Practitioner Research Toolkit

Chapter 1: Introduction Overview and background Chapter 2: Conducting clinical audit of nurse practitioner practice The nature and purpose of clinical audit-- Data collection tools for clinical audit-- References and readings Chapter 3: Researching nurse practitioner practice The nature and purpose of clinical practice research-- Data collection tools for researching practice-- References and readings Chapter 4: Researching nurse practitioner service Principles and purpose of health services research-- Data collection tools for researching health services-- References and readings Chapter 5: Researching nurse practitioner patient outcomes Principles and purpose of researching patient outcomes-- Data collection tools for researching patient outcomes-- References and readings Chapter 6: Conducting a nurse practitioner census National workforce census-- Data collection tools for National/State census of nurse practitioners--References and readings

Management of project knowledge in a project-based organisation : a case study of research enterprise

Knowledge Management (KM) is vital factor to successfully undertake projects. The temporary nature of projects necessitates employing useful KM practices to reduce any issues such as knowledge leakiness and rework. The Project Management Office (PMO) is a unit within organisations to facilitate and oversee organisational projects. Project Management Maturity Models (PMMM) show the development of PMOs from immature to mature levels. The existing PMMMs have focused on discussing Project Management (PM) practices, however, the management of project knowledge is yet to be addressed, at various levels of maturity. A research project was undertaken to investigate the mentioned gap for addressing KM practices at the existing PMMMs. Due to the exploratory and inductive nature of this research, qualitative methods using case studies were chosen as the research methodology to investigate the problem in the real world. In total, three cases selected from different industries: research; mining and government organisations, to provide broad categories for research and research questions were examined using the developed framework. This paper presents the findings from the investigation of the research organisation with the lowest level of maturity. From KM process point of view, knowledge creation and capturing are the most important processes, while knowledge transferring and reusing received less attention. In addition, it was revealed that provision of “knowledge about client” and “project management knowledge” are the most important types of knowledge that are required at this level of maturity. The results also revealed that PMOs with higher maturity level have better knowledge management, however, some improvement is needed. In addition, the importance of KM processes varies at different levels of maturity. In conclusion, the outcomes of this paper could provide powerful guidance to PMOs at lowest level of maturity from KM point of view.

Development of gas sensing technology for ground and airborne applications powered by solar energy : methodology and experimental results

Monitoring gases for environmental, industrial and agricultural fields is a demanding task that requires long periods of observation, large quantity of sensors, data management, high temporal and spatial resolution, long term stability, recalibration procedures, computational resources, and energy availability. Wireless Sensor Networks (WSNs) and Unmanned Aerial Vehicles (UAVs) are currently representing the best alternative to monitor large, remote, and difficult access areas, as these technologies have the possibility of carrying specialised gas sensing systems, and offer the possibility of geo-located and time stamp samples. However, these technologies are not fully functional for scientific and commercial applications as their development and availability is limited by a number of factors: the cost of sensors required to cover large areas, their stability over long periods, their power consumption, and the weight of the system to be used on small UAVs. Energy availability is a serious challenge when WSN are deployed in remote areas with difficult access to the grid, while small UAVs are limited by the energy in their reservoir tank or batteries. Another important challenge is the management of data produced by the sensor nodes, requiring large amount of resources to be stored, analysed and displayed after long periods of operation. In response to these challenges, this research proposes the following solutions aiming to improve the availability and development of these technologies for gas sensing monitoring: first, the integration of WSNs and UAVs for environmental gas sensing in order to monitor large volumes at ground and aerial levels with a minimum of sensor nodes for an effective 3D monitoring; second, the use of solar energy as a main power source to allow continuous monitoring; and lastly, the creation of a data management platform to store, analyse and share the information with operators and external users. The principal outcomes of this research are the creation of a gas sensing system suitable for monitoring any kind of gas, which has been installed and tested on CH4 and CO2 in a sensor network (WSN) and on a UAV. The use of the same gas sensing system in a WSN and a UAV reduces significantly the complexity and cost of the application as it allows: a) the standardisation of the signal acquisition and data processing, thereby reducing the required computational resources; b) the standardisation of calibration and operational procedures, reducing systematic errors and complexity; c) the reduction of the weight and energy consumption, leading to an improved power management and weight balance in the case of UAVs; d) the simplification of the sensor node architecture, which is easily replicated in all the nodes. I evaluated two different sensor modules by laboratory, bench, and field tests: a non-dispersive infrared module (NDIR) and a metal-oxide resistive nano-sensor module (MOX nano-sensor). The tests revealed advantages and disadvantages of the two modules when used for static nodes at the ground level and mobile nodes on-board a UAV. Commercial NDIR modules for CO2 have been successfully tested and evaluated in the WSN and on board of the UAV. Their advantage is the precision and stability, but their application is limited to a few gases. The advantages of the MOX nano-sensors are the small size, low weight, low power consumption and their sensitivity to a broad range of gases. However, selectivity is still a concern that needs to be addressed with further studies. An electronic board to interface sensors in a large range of resistivity was successfully designed, created and adapted to operate on ground nodes and on-board UAV. The WSN and UAV created were powered with solar energy in order to facilitate outdoor deployment, data collection and continuous monitoring over large and remote volumes. The gas sensing, solar power, transmission and data management systems of the WSN and UAV were fully evaluated by laboratory, bench and field testing. The methodology created to design, developed, integrate and test these systems was extensively described and experimentally validated. The sampling and transmission capabilities of the WSN and UAV were successfully tested in an emulated mission involving the detection and measurement of CO2 concentrations in a field coming from a contaminant source; the data collected during the mission was transmitted in real time to a central node for data analysis and 3D mapping of the target gas. The major outcome of this research is the accomplishment of the first flight mission, never reported before in the literature, of a solar powered UAV equipped with a CO2 sensing system in conjunction with a network of ground sensor nodes for an effective 3D monitoring of the target gas. A data management platform was created using an external internet server, which manages, stores, and shares the data collected in two web pages, showing statistics and static graph images for internal and external users as requested. The system was bench tested with real data produced by the sensor nodes and the architecture of the platform was widely described and illustrated in order to provide guidance and support on how to replicate the system. In conclusion, the overall results of the project provide guidance on how to create a gas sensing system integrating WSNs and UAVs, how to power the system with solar energy and manage the data produced by the sensor nodes. This system can be used in a wide range of outdoor applications, especially in agriculture, bushfires, mining studies, zoology, and botanical studies opening the way to an ubiquitous low cost environmental monitoring, which may help to decrease our carbon footprint and to improve the health of the planet.

Studying refugee settlement through longitudinal research : methodological and ethical insights from the Good Starts study

Research involving resettled refugees raises methodological and ethical complexities. These complexities typically emerge within cross-sectional research that focuses on refugee experiences at a specific point in time. Given the long term and dynamic nature of refugee settlement, longitudinal research is valuable, yet it raises distinct complexities within the research process. This article focuses on the methodological and ethical insights that emerged in a longitudinal study of settlement and wellbeing with a cohort of young people from refugee backgrounds in Australia. It considers: engagement and retention of a cohort over time; the need to adapt research tools to changing settlement contexts and life stages; participants’ experiences of long-term involvement in the study; and the challenge of timely translation of findings into evidence for policy and practice. The article contributes to a growing understanding of the practical, ethical and epistemological challenges and opportunities presented by longitudinal research, in this case, with resettled refugee background youth.

Biodiesel production from non-edible beauty leaf (Calophyllum Inophyllum) oil : process optimization using response surface methodology (RSM)

In recent years, the beauty leaf plant (Calophyllum Inophyllum) is being considered as a potential 2nd generation biodiesel source due to high seed oil content, high fruit production rate, simple cultivation and ability to grow in a wide range of climate conditions. However, however, due to the high free fatty acid (FFA) content in this oil, the potential of this biodiesel feedstock is still unrealized, and little research has been undertaken on it. In this study, transesterification of beauty leaf oil to produce biodiesel has been investigated. A two-step biodiesel conversion method consisting of acid catalysed pre-esterification and alkali catalysed transesterification has been utilized. The three main factors that drive the biodiesel (fatty acid methyl ester (FAME)) conversion from vegetable oil (triglycerides) were studied using response surface methodology (RSM) based on a Box-Behnken experimental design. The factors considered in this study were catalyst concentration, methanol to oil molar ratio and reaction temperature. Linear and full quadratic regression models were developed to predict FFA and FAME concentration and to optimize the reaction conditions. The significance of these factors and their interaction in both stages was determined using analysis of variance (ANOVA). The reaction conditions for the largest reduction in FFA concentration for acid catalysed pre-esterification was 30:1 methanol to oil molar ratio, 10% (w/w) sulfuric acid catalyst loading and 75 °C reaction temperature. In the alkali catalysed transesterification process 7.5:1 methanol to oil molar ratio, 1% (w/w) sodium methoxide catalyst loading and 55 °C reaction temperature were found to result in the highest FAME conversion. The good agreement between model outputs and experimental results demonstrated that this methodology may be useful for industrial process optimization for biodiesel production from beauty leaf oil and possibly other industrial processes as well.

Adoption of accountable-eHealth systems by future healthcare professionals: An empirical research model based on the Australian context

This paper provides a first look at the acceptance of Accountable-eHealth systems, a new genre of eHealth systems, designed to manage information privacy concerns that hinder the proliferation of eHealth. The underlying concept of AeH systems is appropriate use of information through after-the-fact accountability for intentional misuse of information by healthcare professionals. An online questionnaire survey was utilised for data collection from three educational institutions in Queensland, Australia. A total of 23 hypothesis relating to 9 constructs were tested using a structural equation modelling technique. A total of 334 valid responses were received. The cohort consisted of medical, nursing and other health related students studying at various levels in both undergraduate and postgraduate courses. The hypothesis testing disproved 7 hypotheses. The empirical research model developed was capable of predicting 47.3% of healthcare professionals’ perceived intention to use AeH systems. A validation of the model with a wider survey cohort would be useful to confirm the current findings.

It’s Not Just a Game: Contemporary Challenges for Games Research and the Internet

In this final chapter we will raise a number of issues that we have encountered as we have put this collection of papers together. In doing this, we also reflect upon the seven challenges for video game theory that Bernard Perron and Mark Wolf(2009)put forward in the introduction to the second video game theory reader given it is probably one of the most recent assessments in the area at the time of writing. These challenges are concerned with Terminology and Accuracy, History, Methodology, Technology, Interactivity, Play and the Integration of Interdisciplinary Approaches. These issues will be brought up throughout this chapter, but not necessarily in mutually exclusive fashion...

Real or imagined? A study exploring the existence of common method variance effects in road safety research

Common method variance (CMV) has received little attention within the field of road safety research despite a heavy reliance on self-report data. Two surveys were completed by 214 motorists over a two-month period, allowing associations between social desirability and key road safety variables and relationships between scales across the two survey waves to be examined. Social desirability was found to have a strong negative correlation with the Driver Behaviour Questionnaire (DBQ) sub-scales as well as age, but not with crashes and offences. Drivers who scored higher on the social desirability scale were also less likely to report aberrant driving behaviours as measured by the DBQ. Controlling for social desirability did not substantially alter the predictive relationship between the DBQ and the crash and offences variables. The strength of the correlations within and between the two waves were also compared with the results strongly suggesting that effects associated with CMV were present. Identification of CMV would be enhanced by the replication of this study with a larger sample size and comparing self-report data with official sources.