Relational regulation theory and the role of social support and organisational fairness for nurses in a general acute context

Aims and objectives. To present a novel approach to nurse stress by exploring the demand–control–support model with organisational justice through the lens of relational regulation theory. Background. Nursing is often stressful due to high demands and dissatisfaction with pay, which impacts the mental well-being and productivity of nurses. Design. A cross-sectional design. Methods. A validated questionnaire was sent to the work addresses of all nursing and midwifery staff in a medium-sized general acute hospital in Australia. A total of 190 nurses and midwives returned completed questionnaires for the analyses. Results. The multiple regression analyses demonstrated that the model applies to the prototypical context of a general acute hospital and that job control, supervisor support and outside work support improve the job satisfaction and mental health of nurses. Conclusions. Most importantly, supervisor support was found to buffer the impact of excessive work demands. Fairness of procedures, distribution of resources and the quality and consistency of information are also beneficial. Relational regulation theory is applied to these findings as a novel way to conceptualise the mechanisms of support and fairness in nursing. Relevance to clinical practice. The importance of nurses’ well-being and job satisfaction is a priority for improving clinical outcomes. Practically, this means nurse managers should be encouraging nurses in the pursuit of diverse relational activities both at work and outside work.

Worldly feelings made material : cosmopolitan aesthetics, affect and recent relational art

The openness and compassion implicit in the social transaction of recent philosophies of cosmopolitanism is reflected in the aims of the body of interpersonal, process-driven artworks commonly referred to as relational art. In attempting to bring art into life, specifically as a point of intervention in the lives of its spectators, the affective power required to realize the communal and participatory aims of many of these artworks is central. Relational art practices invite the individualising distinctiveness of the spectator yet ultimately seek the collective affect of the artwork’s formulated community. Like cosmopolitanism, this is a felt community where the obligatory affective investment is imagined as open and empathic built on mutual exchange and generosity. They suggest that it doesn’t matter so much what we feel about art but what and how we feel through art. The artworld’s public spheres have become increasingly affective worlds, where the artwork’s coerced and managed human relations are conceived as interstices for a more open exchange with art and each other. With reference to Sydney Biennale’s recent All My Relations exhibition, this paper will interrogate how worldly feelings are made material by the requisite emotional and aesthetic labour of feeling for and with others in relational art.

Bounded rationality and voting decisions over 160 years : voter behavior and increasing complexity in decision-making

Using a quasi-natural voting experiment encompassing a 160-year period (1848–2009) in Switzerland, we investigate whether a higher level of complexity leads to increased reliance on trusted parliamentary representatives. We find that when more referenda are held on the same day, constituents are more likely to refer to parliamentary recommendations when making their decisions. This finding holds true even when we narrow our focus to referenda with a relatively lower voter turnout on days on which more than one referendum is held. We also demonstrate that when constituents face a higher level of complexity, they follow the parliamentary recommendations rather than those of interest groups. "Viewed as a geometric figure, the ant’s path is irregular, complex, hard to describe. But its complexity is really a complexity in the surface of the beach, not a complexity in the ant." ([1] p. 51)

Improving work and life balance : building a multilevel model of work-life balance focusing on group structure and relational job design

One in five Australian workers believes that work doesn’t fit well with their family and social commitments. Concurrently, organisations are recognising that to stay competitive they need policies and practices that support the multiple aspects of employees’ lives. Many employees work in group environments yet there is currently little group level work-life balance research. This paper proposes a new theoretical framework developed to understand the design of work groups to better facilitate work-life balance. This new framework focuses on task and relational job designs, group structures and processes and workplace culture.

Complexity and the science of implementation in health IT — knowledge gaps and future visions

Objectives The intent of this paper is in the examination of health IT implementation processes – the barriers to and facilitators of successful implementation, identification of a beginning set of implementation best practices, the identification of gaps in the health IT implementation body of knowledge, and recommendations for future study and application. Methods A literature review resulted in the identification of six health IT related implementation best practices which were subsequently debated and clarified by participants attending the NI2012 Research Post Conference held in Montreal in the summer of 2012. Using the framework for implementation research (CFIR) to guide their application, the six best practices were applied to two distinct health IT implementation studies to assess their applicability. Results Assessing the implementation processes from two markedly diverse settings illustrated both the challenges and potentials of using standardized implementation processes. In support of what was discovered in the review of the literature, “one size fits all” in health IT implementation is a fallacy, particularly when global diversity is added into the mix. At the same time, several frameworks show promise for use as “scaffolding” to begin to assess best practices, their distinct dimensions, and their applicability for use. Conclusions Health IT innovations, regardless of the implementation setting, requires a close assessment of many dimensions. While there is no “one size fits all”, there are commonalities and best practices that can be blended, adapted, and utilized to improve the process of implementation. This paper examines health IT implementation processes and identifies a beginning set of implementation best practices, which could begin to address gaps in the health IT implementation body of knowledge.

A conceptualization of complexity in IS-driven organizational transformations

Organizational transformations reliant on successful ICT system developments (continue to) fail to deliver projected benefits even when contemporary governance models are applied rigorously. Modifications to traditional program, project and systems development management methods have produced little material improvement to successful transformation as they are unable to routinely address the complexity and uncertainty of dynamic alignment of IS investments and innovation. Complexity theory provides insight into why this phenomenon occurs and is used to develop a conceptualization of complexity in IS-driven organizational transformations. This research-in-progress aims to identify complexity formulations relevant to organizational transformation. Political/power based influences, interrelated business rules, socio-technical innovation, impacts on stakeholders and emergent behaviors are commonly considered as characterizing complexity while the proposed conceptualization accommodates these as connectivity, irreducibility, entropy and/or information gain in hierarchically approximation and scaling, number of states in a finite automata and/or dimension of attractor, and information and/or variety.

Integration of sentiment analysis into customer relational model : the importance of feature ontology and synonym

Online business or Electronic Commerce (EC) is getting popular among customers today, as a result large number of product reviews have been posted online by the customers. This information is very valuable not only for prospective customers to make decision on buying product but also for companies to gather information of customers’ satisfaction about their products. Opinion mining is used to capture customer reviews and separated this review into subjective expressions (sentiment word) and objective expressions (no sentiment word). This paper proposes a novel, multi-dimensional model for opinion mining, which integrates customers’ characteristics and their opinion about any products. The model captures subjective expression from product reviews and transfers to fact table before representing in multi-dimensions named as customers, products, time and location. Data warehouse techniques such as OLAP and Data Cubes were used to analyze opinionated sentences. A comprehensive way to calculate customers’ orientation on products’ features and attributes are presented in this paper.

Ghost hunting with lollies, chess and Lego : appreciating the ‘messy’ complexity (and costs) of doing difficult research in education

This paper contributes to conversations about the funding and quality of education research. The paper proceeds in two parts. Part I sets the context by presenting an historical analysis of funding allocations made to Education research through the ARC’s Discovery projects scheme between the years 2002 and 2014, and compares these trends to allocations made to another field within the Social, Behavioural and Economic Sciences assessment panel: Psychology and Cognitive Science. Part II highlights the consequences of underfunding education research by presenting evidence from an Australian Research Council Discovery project that is tracking the experiences of disaffected students who are referred to behaviour schools. The re-scoping decisions that became necessary and the incidental costs that accrue from complications that occur in the field are illustrated and discussed through vignettes of research with “ghosts” who don’t like school but who do like lollies, chess and Lego.

Reducing complexity of large EPCs

Business processes are an important instrument for understanding and improving how companies provide goods and services to customers. Therefore, many companies have documented their business processes well, often in the Event-driven Process Chains (EPC). Unfortunately, in many cases the resulting EPCs are rather complex, so that the overall process logic is hidden in low level process details. This paper proposes abstraction mechanisms for process models that aim to reduce their complexity, while keeping the overall process structure. We assume that functions are marked with efforts and splits are marked with probabilities. This information is used to separate important process parts from less important ones. Real world process models are used to validate the approach.

A low-complexity flight controller for Unmanned Aircraft Systems with constrained control allocation

In this paper, we propose a framework for joint allocation and constrained control design of flight controllers for Unmanned Aircraft Systems (UAS). The actuator configuration is used to map actuator constraint set into the space of the aircraft generalised forces. By constraining the demanded generalised forces, we ensure that the allocation problem is always feasible; and therefore, it can be solved without constraints. This leads to an allocation problem that does not require on-line numerical optimisation. Furthermore, since the controller handles the constraints, and there is no need to implement heuristics to inform the controller about actuator saturation. The latter is fundamental for avoiding Pilot Induced Oscillations (PIO) in remotely operated UAS due to the rate limit on the aircraft control surfaces.

Treatment plan complexity metrics for predicting IMRT pre-treatment quality assurance results

The planning of IMRT treatments requires a compromise between dose conformity (complexity) and deliverability. This study investigates established and novel treatment complexity metrics for 122 IMRT beams from prostate treatment plans. The Treatment and Dose Assessor software was used to extract the necessary data from exported treatment plan files and calculate the metrics. For most of the metrics, there was strong overlap between the calculated values for plans that passed and failed their quality assurance (QA) tests. However, statistically significant variation between plans that passed and failed QA measurements was found for the established modulation index and for a novel metric describing the proportion of small apertures in each beam. The ‘small aperture score’ provided threshold values which successfully distinguished deliverable treatment plans from plans that did not pass QA, with a low false negative rate.

Multi-shot person re-identification via relational stein divergence

Person re-identification is particularly challenging due to significant appearance changes across separate camera views. In order to re-identify people, a representative human signature should effectively handle differences in illumination, pose and camera parameters. While general appearance-based methods are modelled in Euclidean spaces, it has been argued that some applications in image and video analysis are better modelled via non-Euclidean manifold geometry. To this end, recent approaches represent images as covariance matrices, and interpret such matrices as points on Riemannian manifolds. As direct classification on such manifolds can be difficult, in this paper we propose to represent each manifold point as a vector of similarities to class representers, via a recently introduced form of Bregman matrix divergence known as the Stein divergence. This is followed by using a discriminative mapping of similarity vectors for final classification. The use of similarity vectors is in contrast to the traditional approach of embedding manifolds into tangent spaces, which can suffer from representing the manifold structure inaccurately. Comparative evaluations on benchmark ETHZ and iLIDS datasets for the person re-identification task show that the proposed approach obtains better performance than recent techniques such as Histogram Plus Epitome, Partial Least Squares, and Symmetry-Driven Accumulation of Local Features.

Image-guided sampling reveals increased stroma and lower glandular complexity in mammographically dense breast tissue

Mammographic density (MD) adjusted for age and body mass index (BMI) is a strong heritable breast cancer risk factor; however, its biological basis remains elusive. Previous studies assessed MD-associated histology using random sampling approaches, despite evidence that high and low MD areas exist within a breast and are negatively correlated with respect to one another. We have used an image-guided approach to sample high and low MD tissues from within individual breasts to examine the relationship between histology and degree of MD. Image-guided sampling was performed using two different methodologies on mastectomy tissues (n = 12): (1) sampling of high and low MD regions within a slice guided by bright (high MD) and dark (low MD) areas in a slice X-ray film; (2) sampling of high and low MD regions within a whole breast using a stereotactically guided vacuum-assisted core biopsy technique. Pairwise analysis accounting for potential confounders (i.e. age, BMI, menopausal status, etc.) provides appropriate power for analysis despite the small sample size. High MD tissues had higher stromal (P = 0.002) and lower fat (P = 0.002) compositions, but no evidence of difference in glandular areas (P = 0.084) compared to low MD tissues from the same breast. High MD regions had higher relative gland counts (P = 0.023), and a preponderance of Type I lobules in high MD compared to low MD regions was observed in 58% of subjects (n = 7), but did not achieve significance. These findings clarify the histologic nature of high MD tissue and support hypotheses regarding the biophysical impact of dense connective tissue on mammary malignancy. They also provide important terms of reference for ongoing analyses of the underlying genetics of MD.

Plasma nanoscience : from controlled complexity to practical simplicity

Plasma Nanoscience is a multidisciplinary research field which aims to elucidate the specific roles, purposes, and benefits of the ionized gas environment in assembling and processing nanoscale objects in natural, laboratory and technological situations. Compared to neutral gas-based routes, in low-temperature weakly-ionized plasmas there is another level of complexity related to the necessity of creating and sustaining a suitable degree of ionization and a much larger number of species generated in the gas phase. The thinner the nanotubes, the stronger is the quantum confinement of electrons and more unique size-dependent quantum effects can emerge. Furthermore, due to a very high mobility of electrons, the surfaces are at a negative potential compared to the plasma bulk. Therefore, there are non-uniform electric fields within the plasma sheath. The electric field lines start in the plasma bulk and converge to the sharp tips of the developing one-dimensional nanostructures.