Degree of value alignment : a grounded theory of rural nurse resignations

INTRODUCTION: The shortage of nurses willing to work in rural Australian healthcare settings continues to worsen. Australian rural areas have a lower retention rate of nurses than metropolitan counterparts, with more remote communities experiencing an even higher turnover of nursing staff. When retention rates are lower, patient outcomes are known to be poorer. This article reports a study that sought to explore the reasons why registered nurses resign from rural hospitals in the state of New South Wales, Australia. METHODS: Using grounded theory methods, this study explored the reasons why registered nurses resigned from New South Wales rural hospitals. Data were collected from 12 participants using semi-structured interviews; each participant was a registered nurse who had resigned from a rural hospital. Nurses who had resigned due to retirement, relocation or maternity leave were excluded. Interviews were transcribed verbatim and imported into NVivo software. The constant comparative method of data collection and analysis was followed until a core category emerged. RESULTS: Nurses resigned from rural hospitals when their personal value of how nursing should occur conflicted with the hospital's organisational values driving the practice of nursing. These conflicting values led to a change in the degree of value alignment between the nurse and hospital. The degree of value alignment occurred in three dynamic stages that nurses moved through prior to resigning. The first stage, sharing values, was a time when a nurse and a hospital shared similar values. The second stage was conceding values where, due to perceived changes in a hospital's values, a nurse felt that patient care became compromised and this led to a divergence of values. The final stage was resigning, a stage where a nurse 'gave up' as they felt that their professional integrity was severely compromised. The findings revealed that when a nurse and organisational values were not aligned, conflict was created for a nurse about how they could perform nursing that aligned with their internalised professional values and integrity. Resignation occurred when nurses were unable to realign their personal values to changed organisational values - the organisational values changed due to rural area health service restructures, centralisation of budgets and resources, cumbersome hierarchies and management structures that inhibited communication and decision making, out-dated and ineffective operating systems, insufficient and inexperienced staff, bullying, and a lack of connectedness and shared vision. CONCLUSIONS: To fully comprehend rural nurse resignations, this study identified three stages that nurses move through prior to resignation. Effective retention strategies for the nursing workforce should address contributors to a decrease in value alignment and work towards encouraging the coalescence of nurses' and hospitals' values. It is imperative that strategies enable nurses to provide high quality patient care and promote a sense of connectedness and a shared vision between nurse and hospital. Senior managers need to have clear ways to articulate and imbue organisational values and be explicit in how these values accommodate nurses' values. Ward-level nurse managers have a significant responsibility to ensure that a hospital's values (both explicit and implicit) are incorporated into ward culture.

Deriving a preference-based utility measure for cancer patients from the European Organisation for the Research and Treatment of Cancer's Quality of Life Questionnaire C30 : a confirmatory versus exploratory approach

Background Multi attribute utility instruments (MAUIs) are preference-based measures that comprise a health state classification system (HSCS) and a scoring algorithm that assigns a utility value to each health state in the HSCS. When developing a MAUI from a health-related quality of life (HRQOL) questionnaire, first a HSCS must be derived. This typically involves selecting a subset of domains and items because HRQOL questionnaires typically have too many items to be amendable to the valuation task required to develop the scoring algorithm for a MAUI. Currently, exploratory factor analysis (EFA) followed by Rasch analysis is recommended for deriving a MAUI from a HRQOL measure. Aim To determine whether confirmatory factor analysis (CFA) is more appropriate and efficient than EFA to derive a HSCS from the European Organisation for the Research and Treatment of Cancer’s core HRQOL questionnaire, Quality of Life Questionnaire (QLQ-C30), given its well-established domain structure. Methods QLQ-C30 (Version 3) data were collected from 356 patients receiving palliative radiotherapy for recurrent/metastatic cancer (various primary sites). The dimensional structure of the QLQ-C30 was tested with EFA and CFA, the latter informed by the established QLQ-C30 structure and views of both patients and clinicians on which are the most relevant items. Dimensions determined by EFA or CFA were then subjected to Rasch analysis. Results CFA results generally supported the proposed QLQ-C30 structure (comparative fit index =0.99, Tucker–Lewis index =0.99, root mean square error of approximation =0.04). EFA revealed fewer factors and some items cross-loaded on multiple factors. Further assessment of dimensionality with Rasch analysis allowed better alignment of the EFA dimensions with those detected by CFA. Conclusion CFA was more appropriate and efficient than EFA in producing clinically interpretable results for the HSCS for a proposed new cancer-specific MAUI. Our findings suggest that CFA should be recommended generally when deriving a preference-based measure from a HRQOL measure that has an established domain structure.

Development of a method to assess the quality of ankle joint reduction in 3D

This project developed a quantitative method for determining the quality of the surgical alignment of the bone fragments after an ankle fracture. The research examined the feasibility of utilising MRI-based bone models versus the gold standard CT-based bone models in order to reduce the amount of ionising radiation the patient is exposed to. In doing so, the thesis reports that there is potential for MRI to be used instead of CT depending on the scanning parameters used to obtain the medical images, the distance of the implant relative to the joint surface, and the implant material.

Essays on Corporate Governance and the Quality of Disclosed Earnings: Across Transitional Europe

A growing body of empirical research examines the structure and effectiveness of corporate governance systems around the world. An important insight from this literature is that corporate governance mechanisms address the excessive use of managerial discretionary powers to get private benefits by expropriating the value of shareholders. One possible way of expropriation is to reduce the quality of disclosed earnings by manipulating the financial statements. This lower quality of earnings should then be reflected by the stock price of firm according to value relevance theorem. Hence, instead of testing the direct effect of corporate governance on the firm’s market value, it is important to understand the causes of the lower quality of accounting earnings. This thesis contributes to the literature by increasing knowledge about the extent of the earnings management – measured as the extent of discretionary accruals in total disclosed earnings - and its determinants across the Transitional European countries. The thesis comprises of three essays of empirical analysis of which first two utilize the data of Russian listed firms whereas the third essay uses data from 10 European economies. More specifically, the first essay adds to existing research connecting earnings management to corporate governance. It testifies the impact of the Russian corporate governance reforms of 2002 on the quality of disclosed earnings in all publicly listed firms. This essay provides empirical evidence of the fact that the desired impact of reforms is not fully substantiated in Russia without proper enforcement. Instead, firm-level factors such as long-term capital investments and compliance with International financial reporting standards (IFRS) determine the quality of the earnings. The result presented in the essay support the notion proposed by Leuz et al. (2003) that the reforms aimed to bring transparency do not correspond to desired results in economies where investor protection is lower and legal enforcement is weak. The second essay focuses on the relationship between the internal-control mechanism such as the types and levels of ownership and the quality of disclosed earnings in Russia. The empirical analysis shows that the controlling shareholders in Russia use their powers to manipulate the reported performance in order to get private benefits of control. Comparatively, firms owned by the State have significantly better quality of disclosed earnings than other controllers such as oligarchs and foreign corporations. Interestingly, market performance of firms controlled by either State or oligarchs is better than widely held firms. The third essay provides useful evidence on the fact that both ownership structures and economic characteristics are important factors in determining the quality of disclosed earnings in three groups of countries in Europe. Evidence suggests that ownership structure is a more important determinant in developed and transparent countries, while economic determinants are important determinants in developing and transitional countries.

iPBA: a tool for protein structure comparison using sequence alignment strategies

With the immense growth in the number of available protein structures, fast and accurate structure comparison has been essential. We propose an efficient method for structure comparison, based on a structural alphabet. Protein Blocks (PBs) is a widely used structural alphabet with 16 pentapeptide conformations that can fairly approximate a complete protein chain. Thus a 3D structure can be translated into a 1D sequence of PBs. With a simple Needleman-Wunsch approach and a raw PB substitution matrix, PB-based structural alignments were better than many popular methods. iPBA web server presents an improved alignment approach using (i) specialized PB Substitution Matrices (SM) and (ii) anchor-based alignment methodology. With these developments, the quality of similar to 88% of alignments was improved. iPBA alignments were also better than DALI, MUSTANG and GANGSTA(+) in > 80% of the cases. The webserver is designed to for both pairwise comparisons and database searches. Outputs are given as sequence alignment and superposed 3D structures displayed using PyMol and Jmol. A local alignment option for detecting subs-structural similarity is also embedded. As a fast and efficient `sequence-based' structure comparison tool, we believe that it will be quite useful to the scientific community. iPBA can be accessed at http://www.dsimb.inserm.fr/dsimb_tools/ipba/.

mulPBA: an efficient multiple protein structure alignment method based on a structural alphabet

The increasing number of available protein structures requires efficient tools for multiple structure comparison. Indeed, multiple structural alignments are essential for the analysis of function, evolution and architecture of protein structures. For this purpose, we proposed a new web server called multiple Protein Block Alignment (mulPBA). This server implements a method based on a structural alphabet to describe the backbone conformation of a protein chain in terms of dihedral angles. This sequence-like' representation enables the use of powerful sequence alignment methods for primary structure comparison, followed by an iterative refinement of the structural superposition. This approach yields alignments superior to most of the rigid-body alignment methods and highly comparable with the flexible structure comparison approaches. We implement this method in a web server designed to do multiple structure superimpositions from a set of structures given by the user. Outputs are given as both sequence alignment and superposed 3D structures visualized directly by static images generated by PyMol or through a Jmol applet allowing dynamic interaction. Multiple global quality measures are given. Relatedness between structures is indicated by a distance dendogram. Superimposed structures in PDB format can be also downloaded, and the results are quickly obtained. mulPBA server can be accessed at www.dsimb.inserm.fr/dsimb_tools/mulpba/.

A scheme for multiple sequences alignment optimization-an improvement based on family representative mechanics features

As a basic tool of modern biology, sequence alignment can provide us useful information in fold, function, and active site of protein. For many cases, the increased quality of sequence alignment means a better performance. The motivation of present work is to increase ability of the existing scoring scheme/algorithm by considering residue–residue correlations better. Based on a coarse-grained approach, the hydrophobic force between each pair of residues is written out from protein sequence. It results in the construction of an intramolecular hydrophobic force network that describes the whole residue–residue interactions of each protein molecule, and characterizes protein's biological properties in the hydrophobic aspect. A former work has suggested that such network can characterize the top weighted feature regarding hydrophobicity. Moreover, for each homologous protein of a family, the corresponding network shares some common and representative family characters that eventually govern the conservation of biological properties during protein evolution. In present work, we score such family representative characters of a protein by the deviation of its intramolecular hydrophobic force network from that of background. Such score can assist the existing scoring schemes/algorithms, and boost up the ability of multiple sequences alignment, e.g. achieving a prominent increase (50%) in searching the structurally alike residue segments at a low identity level. As the theoretical basis is different, the present scheme can assist most existing algorithms, and improve their efficiency remarkably.

Image, Video and 3D Data Registration: Medical, Satellite and Video Processing Applications with Quality Metrics

Data registration refers to a series of techniques for matching or bringing similar objects or datasets together into alignment. These techniques enjoy widespread use in a diverse variety of applications, such as video coding, tracking, object and face detection and recognition, surveillance and satellite imaging, medical image analysis and structure from motion. Registration methods are as numerous as their manifold uses, from pixel level and block or feature based methods to Fourier domain methods.

This book is focused on providing algorithms and image and video techniques for registration and quality performance metrics. The authors provide various assessment metrics for measuring registration quality alongside analyses of registration techniques, introducing and explaining both familiar and state-of-the-art registration methodologies used in a variety of targeted applications.

Key features:
- Provides a state-of-the-art review of image and video registration techniques, allowing readers to develop an understanding of how well the techniques perform by using specific quality assessment criteria
- Addresses a range of applications from familiar image and video processing domains to satellite and medical imaging among others, enabling readers to discover novel methodologies with utility in their own research
- Discusses quality evaluation metrics for each application domain with an interdisciplinary approach from different research perspectives

Image, video and 3D data registration: medical, satellite and video processing applications with quality metrics

Data registration refers to a series of techniques for matching or bringing similar objects or datasets together into alignment. These techniques enjoy widespread use in a diverse variety of applications, such as video coding, tracking, object and face detection and recognition, surveillance and satellite imaging, medical image analysis and structure from motion. Registration methods are as numerous as their manifold uses, from pixel level and block or feature based methods to Fourier domain methods. This book is focused on providing algorithms and image and video techniques for registration and quality performance metrics. The authors provide various assessment metrics for measuring registration quality alongside analyses of registration techniques, introducing and explaining both familiar and state–of–the–art registration methodologies used in a variety of targeted applications.

Benchmarking consensus model quality assessment for protein fold recognition

Background: Selecting the highest quality 3D model of a protein structure from a number of alternatives remains an important challenge in the field of structural bioinformatics. Many Model Quality Assessment Programs (MQAPs) have been developed which adopt various strategies in order to tackle this problem, ranging from the so called "true" MQAPs capable of producing a single energy score based on a single model, to methods which rely on structural comparisons of multiple models or additional information from meta-servers. However, it is clear that no current method can separate the highest accuracy models from the lowest consistently. In this paper, a number of the top performing MQAP methods are benchmarked in the context of the potential value that they add to protein fold recognition. Two novel methods are also described: ModSSEA, which based on the alignment of predicted secondary structure elements and ModFOLD which combines several true MQAP methods using an artificial neural network. Results: The ModSSEA method is found to be an effective model quality assessment program for ranking multiple models from many servers, however further accuracy can be gained by using the consensus approach of ModFOLD. The ModFOLD method is shown to significantly outperform the true MQAPs tested and is competitive with methods which make use of clustering or additional information from multiple servers. Several of the true MQAPs are also shown to add value to most individual fold recognition servers by improving model selection, when applied as a post filter in order to re-rank models. Conclusion: MQAPs should be benchmarked appropriately for the practical context in which they are intended to be used. Clustering based methods are the top performing MQAPs where many models are available from many servers; however, they often do not add value to individual fold recognition servers when limited models are available. Conversely, the true MQAP methods tested can often be used as effective post filters for re-ranking few models from individual fold recognition servers and further improvements can be achieved using a consensus of these methods.

Automated tertiary structure prediction with accurate local model quality assessment using the IntFOLD-TS method

The IntFOLD-TS method was developed according to the guiding principle that the model quality assessment would be the most critical stage for our template based modelling pipeline. Thus, the IntFOLD-TS method firstly generates numerous alternative models, using in-house versions of several different sequence-structure alignment methods, which are then ranked in terms of global quality using our top performing quality assessment method – ModFOLDclust2. In addition to the predicted global quality scores, the predictions of local errors are also provided in the resulting coordinate files, using scores that represent the predicted deviation of each residue in the model from the equivalent residue in the native structure. The IntFOLD-TS method was found to generate high quality 3D models for many of the CASP9 targets, whilst also providing highly accurate predictions of their per-residue errors. This important information may help to make the 3D models that are produced by the IntFOLD-TS method more useful for guiding future experimental work

Improvement of 3D protein models using multiple templates guided by single-template model quality assessment

Motivation: Modelling the 3D structures of proteins can often be enhanced if more than one fold template is used during the modelling process. However, in many cases, this may also result in poorer model quality for a given target or alignment method. There is a need for modelling protocols that can both consistently and significantly improve 3D models and provide an indication of when models might not benefit from the use of multiple target-template alignments. Here, we investigate the use of both global and local model quality prediction scores produced by ModFOLDclust2, to improve the selection of target-template alignments for the construction of multiple-template models. Additionally, we evaluate clustering the resulting population of multi- and single-template models for the improvement of our IntFOLD-TS tertiary structure prediction method. Results: We find that using accurate local model quality scores to guide alignment selection is the most consistent way to significantly improve models for each of the sequence to structure alignment methods tested. In addition, using accurate global model quality for re-ranking alignments, prior to selection, further improves the majority of multi-template modelling methods tested. Furthermore, subsequent clustering of the resulting population of multiple-template models significantly improves the quality of selected models compared with the previous version of our tertiary structure prediction method, IntFOLD-TS.

Achieving business and IT alignment from organisational learning perspectives

Business and IT alignment has continued as a top concern for business and IT executives for almost three decades. Many researchers have conducted empirical studies on the relationship between business-IT alignment and performance. Yet, these approaches, lacking a social perspective, have had little impact on sustaining performance and competitive advantage. In addition to the limited alignment literature that explores organisational learning that is represented in shared understanding, communication, cognitive maps and experiences. Hence, this paper proposes an integrated process that enables social and intellectual dimensions through the concept of organisational learning. In particular, the feedback and feed- forward process which provide a value creation across dynamic multilevel of learning. This mechanism enables on-going effectiveness through development of individuals, groups and organisations, which improves the quality of business and IT strategies and drives to performance.

Revising the Program Portfolio: Elevating Academic Program Performance and Strategic Alignment

At many institutions, program review is an underproductive exercise. Review of existing programs is often a check-the-box formality, with inconsistent criteria and little connection to institutional priorities or funding considerations. Decisions about where to concentrate resources across the portfolio can be highly politicized. This report profiles how academic planning exemplars use program review as a strategic tool, integrating data on academic quality, student demand, and resource utilization to improve the economics of challenged programs and prioritize programs for investment and expansion.

Quality of performance of the operation of sugarcane mechanized planting in day and night shifts

The sugarcane mechanized planting is becoming increasingly widespread in Brazil due to a higher operability and better working conditions offered to workers compared to other types of planting. Studies related to this topic are insufficient or scarce in Brazil. In this context, the aim of this study was to evaluate the operation quality of sugarcane mechanized planting in two operation shifts, by means of statistical process control. The mechanized planting was held on March 2012 and statistical design was completely randomized with two treatments, totaling 40 replications for the day shift and 40 replications for the night shift. The variables evaluated were: speed, engine rotation, engine oil pressure, water temperature of the engine, effective field capacity and the time consumption hourly and effective fuel. The use of statistical control charts showed that random intrinsic do not cause this process. The tractor alignment error showed outliers in the day and night shifts operations, indicating a possible delay in receiving the signal. The water temperature of the engine and the effective fuel consumption showed lower variability in nighttime operation with average values of 81°C and 22.66 L ha-1, respectively. The hourly fuel consumption had greater variability and consequently lower quality during the night of the operation, with an average consumption of 25.46 L h-1 while the day shift showed 26.86 L h-1.