Building research capacity in the nursing workforce : the design and evaluation of the nurse researcher role

Objectives: The Nurse Researcher Project (NRP) was initiated to support development of a nursing research and evidence based practice culture in Cancer Care Services (CCS) in a large tertiary hospital in Australia. The position was established and evaluated to inform future directions in the organisation.---------- Background: The demand for quality cancer care has been expanding over the past decades. Nurses are well placed to make an impact on improving health outcomes of people affected by cancer. At the same time, there is a robust body of literature documenting the barriers to undertaking and utilising research by and for nurses and nursing. A number of strategies have been implemented to address these barriers including a range of staff researcher positions but there is scant attention to evaluating the outcomes of these strategies. The role of nurse researcher has been documented in the literature with the aim to provide support to nurses in the clinical setting. There is, to date, little information in relation to the design, implementation and evaluation of this role.---------- Design: The Donabedian’s model of program evaluation was used to implement and evaluate this initiative.---------- Methods: The ‘NRP’ outlined the steps needed to implement the nurse researcher role in a clinical setting. The steps involved the design of the role, planning for the support system for the role, and evaluation of outcomes of the role over two years.---------- Discussion: This paper proposes an innovative and feasible model to support clinical nursing research which would be relevant to a range of service areas.---------- Conclusion: Nurse researchers are able to play a crucial role in advancing nursing knowledge and facilitating evidence based practice, especially when placed to support a specialised team of nurses at a service level. This role can be implemented through appropriate planning of the position, building a support system and incorporating an evaluation plan.

Validating the functional capacity index : a comparison of predicted versus observed total body scores

Background: The Functional Capacity Index (FCI) was designed to predict physical function 12 months after injury. We report a validation study of the FCI. Methods: This was a consecutive case series registered in the Queensland Trauma Registry who consented to the prospective 12-month telephone-administered follow-up study. FCI scores measured at 12 months were compared with those originally predicted. Results: Complete Abbreviated Injury Scale score information was available for 617 individuals, of whom 587 (95%) could be assigned at least one FCI score (range, 1-17). Agreement between the largest predicted FCI and observed FCI score was poor ([kappa] = 0.05; 95% confidence interval, 0.00-0.10) and explained only 1% of the variability in observed FCI. Using an encompassing model that included all FCI assignments, agreement remained poor ([kappa] = 0.05; 95% confidence interval, -0.02-0.12), and the model explained only 9% of the variability in observed FCI. Conclusion: The predicted functional capacity poorly agrees with actual functional outcomes. Further research should consider including other (noninjury) explanatory factors in predicting FCI at 12 months.

Building climate change resilience and adaptive capacity in Australia’s community sector using social media and technology innovation

Public and private sector organisations worldwide are putting strategies in place to manage the commercial and operational risks of climate change. However, community organisations are lagging behind in their understanding and preparedness, despite them being among the most exposed to the effects of climate change impacts and regulation. This poster presents a proposal for a multidisciplinary study that addresses this issue by developing, testing and applying a novel climate risk assessment methodology that is tailored to the needs of Australia’s community sector and its clients. Strategies to mitigate risks and build resilience and adaptive capacity will be identified including new opportunities afforded by urban informatics, social media, and technologies of scale making.

Building Indigenous research capacity : a personal perspective

The International Network of Indigenous Health Knowledge and Development (INIHKD) Conference was held from Monday 24 May to Friday 28 May 2010 at Kiana Lodge, Port Madison Indian Reservation, Suquamish Nation, Washington State, United States of America. The overall theme for the 4th Biennial Conference was ‘Knowing Our Roots: Indigenous Medicines, Health Knowledges and Best Practices’.

The carrying capacity imperative : assessing regional carrying capacity methodologies for sustainable land-use planning

The global impact of an ever-increasing population-base combined with dangerously depleted natural resources highlights the urgent need for changes in human lifestyles and land-use patterns. To achieve more equitable and sustainable land use, it is imperative that populations live within the carrying capacity of their natural assets in a manner more accountable to and ethically responsible for the land which sustains them. Our society’s very survival may well depend on worldwide acceptance of the carrying capacity imperative as a principle of personal, political, economic, educational and planning responsibility. This theoretically-focused research identifies, examines and compares a range of methodological approaches to carrying capacity assessment and considers their relevance to future spatial planning. It also addresses existing gaps in current methodologies and suggests avenues for improvement. A set of eleven key criteria are employed to compare various existing carrying capacity assessment models. These criteria include whole-systems analysis, dynamic responses, levels of impact and risk, systemic constraints, applicability to future planning and the consideration of regional and local boundary delineation. This research finds that while some existing methodologies offer significant insights into the assessment of population carrying capacities, a comprehensive model is yet to be developed. However, it is suggested that by combining successful components from various authors, and collecting a range of interconnected data, a practical and workable systems-based model may be achievable in the future.

The carrying capacity imperative : assessing regional carrying capacity methodologies for sustainable land-use planning

While some existing carrying capacity methodologies offer significant insights into the assessment of population carrying capacities, a comprehensive model is yet to be developed. This research identifies, examines and compares a range of methodological approaches to carrying capacity assessment and considers their relevance to future spatial planning. A range of key criteria are employed to compare various existing carrying capacity assessment models. These criteria include integrated systems analysis, dynamic responses, levels of risk, systemic constraints, applicability to future planning and the consideration of regional boundary delineation. It is suggested that by combining successful components from various authors, and collecting a range of interconnected data, a practical and workable system-based model may be achievable in the future.

Sustainable infrastructure assets : capability for infrastructure capacity management

Building for a sustainable environment requires sustainable infrastructure assets. Infrastructure capacity management is the process of ensuring optimal provision of such infrastructure assets. Effectiveness in this process will enable the infrastructure asset owners and its stakeholders to receive full value on their investment. Business research has shown that an organisation can only achieve business value when it has the right capabilities. This paradigm can also be applied to infrastructure capacity management. With limited access to resources, the challenge for infrastructure organisations is to identify and develop core capabilities to enable infrastructure capacity management. This chapter explores the concept of capability and identifies the core capability needed in infrastructure capacity management. Through a case study of the Port of Brisbane, this chapter shows that infrastructure organisations must develop their intelligence gathering capability to effectively manage the capacity of their infrastructure assets.

Adults who lack capacity : substitute decision-making

• Mechanisms to facilitate consent to healthcare for adults who lack capacity are necessary to ensure that these adults can lawfully receive appropriate medical treatment when needed. • In Australia, the common law plays only a limited role in this context, through its recognition of advance directives and through the parens patriae jurisdiction of superior courts. • Substitute decision-making for adults who lack capacity is facilitated primarily by guardianship and other related legislation. This legislation, which has been enacted in all Australian States and Territories, permits a range of decision-makers to make different types of healthcare decisions. • Substitute decision-makers can be appointed by the adult or by a guardianship or other tribunal. Where there is no appointed decision-maker, legislation generally empowers those close to the adult to make the relevant decision. Most Australian jurisdictions have also provided for statutory advance directives. • For the most serious of decisions, such as non-therapeutic sterilisations, consent can only be provided by a Tribunal. Other decisions can generally be made by a range of substitute decision-makers. Some treatment, such as very minor treatment or that which is needed in an emergency, can be provided without consent. • Guardianship legislation generally establishes a set of principles and/or other criteria to guide healthcare decisions. Mechanisms to resolve disputes as to who is the appropriate decision-maker and how a decision should be made have also been established.

On the optimal capacity expansion of electric power systems

The analysis of investment in the electric power has been the subject of intensive research for many years. The efficient generation and distribution of electrical energy is a difficult task involving the operation of a complex network of facilities, often located over very large geographical regions. Electric power utilities have made use of an enormous range of mathematical models. Some models address time spans which last for a fraction of a second, such as those that deal with lightning strikes on transmission lines while at the other end of the scale there are models which address time horizons consisting of ten or twenty years; these usually involve long range planning issues. This thesis addresses the optimal long term capacity expansion of an interconnected power system. The aim of this study has been to derive a new, long term planning model which recognises the regional differences which exist for energy demand and which are present in the construction and operation of power plant and transmission line equipment. Perhaps the most innovative feature of the new model is the direct inclusion of regional energy demand curves in the nonlinear form. This results in a nonlinear capacity expansion model. After review of the relevant literature, the thesis first develops a model for the optimal operation of a power grid. This model directly incorporates regional demand curves. The model is a nonlinear programming problem containing both integer and continuous variables. A solution algorithm is developed which is based upon a resource decomposition scheme that separates the integer variables from the continuous ones. The decompostion of the operating problem leads to an interactive scheme which employs a mixed integer programming problem, known as the master, to generate trial operating configurations. The optimum operating conditions of each trial configuration is found using a smooth nonlinear programming model. The dual vector recovered from this model is subsequently used by the master to generate the next trial configuration. The solution algorithm progresses until lower and upper bounds converge. A range of numerical experiments are conducted and these experiments are included in the discussion. Using the operating model as a basis, a regional capacity expansion model is then developed. It determines the type, location and capacity of additional power plants and transmission lines, which are required to meet predicted electicity demands. A generalised resource decompostion scheme, similar to that used to solve the operating problem, is employed. The solution algorithm is used to solve a range of test problems and the results of these numerical experiments are reported. Finally, the expansion problem is applied to the Queensland electricity grid in Australia.

On the optimal capacity expansion of electric power systems

The analysis of investment in the electric power has been the subject of intensive research for many years. The efficient generation and distribution of electrical energy is a difficult task involving the operation of a complex network of facilities, often located over very large geographical regions. Electric power utilities have made use of an enormous range of mathematical models. Some models address time spans which last for a fraction of a second, such as those that deal with lightning strikes on transmission lines while at the other end of the scale there are models which address time horizons consisting of ten or twenty years; these usually involve long range planning issues. This thesis addresses the optimal long term capacity expansion of an interconnected power system. The aim of this study has been to derive a new, long term planning model which recognises the regional differences which exist for energy demand and which are present in the construction and operation of power plant and transmission line equipment. Perhaps the most innovative feature of the new model is the direct inclusion of regional energy demand curves in the nonlinear form. This results in a nonlinear capacity expansion model. After review of the relevant literature, the thesis first develops a model for the optimal operation of a power grid. This model directly incorporates regional demand curves. The model is a nonlinear programming problem containing both integer and continuous variables. A solution algorithm is developed which is based upon a resource decomposition scheme that separates the integer variables from the continuous ones. The decompostion of the operating problem leads to an interactive scheme which employs a mixed integer programming problem, known as the master, to generate trial operating configurations. The optimum operating conditions of each trial configuration is found using a smooth nonlinear programming model. The dual vector recovered from this model is subsequently used by the master to generate the next trial configuration. The solution algorithm progresses until lower and upper bounds converge. A range of numerical experiments are conducted and these experiments are included in the discussion. Using the operating model as a basis, a regional capacity expansion model is then developed. It determines the type, location and capacity of additional power plants and transmission lines, which are required to meet predicted electicity demands. A generalised resource decompostion scheme, similar to that used to solve the operating problem, is employed. The solution algorithm is used to solve a range of test problems and the results of these numerical experiments are reported. Finally, the expansion problem is applied to the Queensland electricity grid in Australia

Impacts of vessel capacity reduction programs on the efficiency in fisheries. The case of Australia's multispecies in northern prawn fishery

Capacity reduction programs in the form of buybacks or decommissioning programs have had relatively widespread application in fisheries in the US, Europe and Australia. A common criticism of such programs is that they remove the least efficient vessels first, resulting in an increase in average efficiency of the remaining fleet. The effective fishing power of the fleet, therefore, does not decrease in proportion to the number of vessels removed. Further, reduced crowding may increase efficiency of the remaining vessels. In this paper, the effects of a buyback program on average technical efficiency in Australia’s Northern Prawn Fishery are examined using a multi-output distance function approach with an explicit inefficiency model. The results indicate that average efficiency of the remaining vessels was greater than that of the removed vessels, and that average efficiency of remaining vessels also increased as a result of reduced crowding.

A principal at work : a story of leadership for building sustainable capacity of a school

This study explores through a lifestream narrative how the life experiences of a female primary school principal are organised as practical knowledge, and are used to inform action that is directed towards creating a sustainable school culture. An alternative model of school leadership is presented which describes the thinking and activity of a leader as a process. The process demonstrates how a leader's practical knowledge is dynamic, broadly based in experiential life, and open to change. As such, it is described as a model of sustainable leadership-in-process. The research questions at the heart of this study are: How does a leader construct and organize knowledge in the enactment of the principal ship to deal with the dilemmas and opportunities that arise everyday in school life? And: What does this particular way of organising knowledge look like in the effort to build a sustainable school community? The sustainable leadership-in-process thesis encapsulates new ways of leading primary schools through the principalship. These new ways are described as developing and maintaining the following dimensions of leadership: quality relationships, a collective (shared vision), collaboration and partnerships, and high achieving learning environments. Such dimensions are enacted by the principal through the activities of conversations, performance development, research and data-driven action, promoting innovation, and anticipating and predicting the future. Sustainable leadership-in-process is shared, dynamic, visible and transparent and is conducted through the processes of positioning, defining, organising, experimenting and evaluating in a continuous and iterative way. A rich understanding of the specificity of the life of a female primary school principal was achieved using story telling, story listening and story creation in a collaborative relationship between the researcher and the researched participant. as a means of educational theorising. Analysis and interpretation were undertaken as a recursive process in which the immediate interpretations were shared with the researched participant. The view of theorising adopted in this research is that of theory as hermeneutic; that is, theory is generated out of the stories of experiential life, rather than discovered in the stories.

Modelling and solving train scheduling problems under capacity constraints

Many large coal mining operations in Australia rely heavily on the rail network to transport coal from mines to coal terminals at ports for shipment. Over the last few years, due to the fast growing demand, the coal rail network is becoming one of the worst industrial bottlenecks in Australia. As a result, this provides great incentives for pursuing better optimisation and control strategies for the operation of the whole rail transportation system under network and terminal capacity constraints. This PhD research aims to achieve a significant efficiency improvement in a coal rail network on the basis of the development of standard modelling approaches and generic solution techniques. Generally, the train scheduling problem can be modelled as a Blocking Parallel- Machine Job-Shop Scheduling (BPMJSS) problem. In a BPMJSS model for train scheduling, trains and sections respectively are synonymous with jobs and machines and an operation is regarded as the movement/traversal of a train across a section. To begin, an improved shifting bottleneck procedure algorithm combined with metaheuristics has been developed to efficiently solve the Parallel-Machine Job- Shop Scheduling (PMJSS) problems without the blocking conditions. Due to the lack of buffer space, the real-life train scheduling should consider blocking or hold-while-wait constraints, which means that a track section cannot release and must hold a train until the next section on the routing becomes available. As a consequence, the problem has been considered as BPMJSS with the blocking conditions. To develop efficient solution techniques for BPMJSS, extensive studies on the nonclassical scheduling problems regarding the various buffer conditions (i.e. blocking, no-wait, limited-buffer, unlimited-buffer and combined-buffer) have been done. In this procedure, an alternative graph as an extension of the classical disjunctive graph is developed and specially designed for the non-classical scheduling problems such as the blocking flow-shop scheduling (BFSS), no-wait flow-shop scheduling (NWFSS), and blocking job-shop scheduling (BJSS) problems. By exploring the blocking characteristics based on the alternative graph, a new algorithm called the topological-sequence algorithm is developed for solving the non-classical scheduling problems. To indicate the preeminence of the proposed algorithm, we compare it with two known algorithms (i.e. Recursive Procedure and Directed Graph) in the literature. Moreover, we define a new type of non-classical scheduling problem, called combined-buffer flow-shop scheduling (CBFSS), which covers four extreme cases: the classical FSS (FSS) with infinite buffer, the blocking FSS (BFSS) with no buffer, the no-wait FSS (NWFSS) and the limited-buffer FSS (LBFSS). After exploring the structural properties of CBFSS, we propose an innovative constructive algorithm named the LK algorithm to construct the feasible CBFSS schedule. Detailed numerical illustrations for the various cases are presented and analysed. By adjusting only the attributes in the data input, the proposed LK algorithm is generic and enables the construction of the feasible schedules for many types of non-classical scheduling problems with different buffer constraints. Inspired by the shifting bottleneck procedure algorithm for PMJSS and characteristic analysis based on the alternative graph for non-classical scheduling problems, a new constructive algorithm called the Feasibility Satisfaction Procedure (FSP) is proposed to obtain the feasible BPMJSS solution. A real-world train scheduling case is used for illustrating and comparing the PMJSS and BPMJSS models. Some real-life applications including considering the train length, upgrading the track sections, accelerating a tardy train and changing the bottleneck sections are discussed. Furthermore, the BPMJSS model is generalised to be a No-Wait Blocking Parallel- Machine Job-Shop Scheduling (NWBPMJSS) problem for scheduling the trains with priorities, in which prioritised trains such as express passenger trains are considered simultaneously with non-prioritised trains such as freight trains. In this case, no-wait conditions, which are more restrictive constraints than blocking constraints, arise when considering the prioritised trains that should traverse continuously without any interruption or any unplanned pauses because of the high cost of waiting during travel. In comparison, non-prioritised trains are allowed to enter the next section immediately if possible or to remain in a section until the next section on the routing becomes available. Based on the FSP algorithm, a more generic algorithm called the SE algorithm is developed to solve a class of train scheduling problems in terms of different conditions in train scheduling environments. To construct the feasible train schedule, the proposed SE algorithm consists of many individual modules including the feasibility-satisfaction procedure, time-determination procedure, tune-up procedure and conflict-resolve procedure algorithms. To find a good train schedule, a two-stage hybrid heuristic algorithm called the SE-BIH algorithm is developed by combining the constructive heuristic (i.e. the SE algorithm) and the local-search heuristic (i.e. the Best-Insertion- Heuristic algorithm). To optimise the train schedule, a three-stage algorithm called the SE-BIH-TS algorithm is developed by combining the tabu search (TS) metaheuristic with the SE-BIH algorithm. Finally, a case study is performed for a complex real-world coal rail network under network and terminal capacity constraints. The computational results validate that the proposed methodology would be very promising because it can be applied as a fundamental tool for modelling and solving many real-world scheduling problems.