Nursing care for the families of the dying child/infant in paediatric and neonatal ICU: Nurses’ emotional talk and sources of discomfort. A mixed methods study

BACKGROUND: The majority of in-hospital deaths of children occur in paediatric and neonatal intensive care units. For nurses working in these settings, this can be a source of significant anxiety, discomfort and sense of failure.

OBJECTIVES: The objectives of this study were to explore how NICU/PICU nurses care for families before and after death; to explore the nurses' perspectives on their preparedness/ability to provide family care; and to determine the emotional content of language used by nurse participants.

METHODS: Focus group and individual interviews were conducted with 22 registered nurses from neonatal and paediatric intensive care units of two major metropolitan hospitals in Australia. All data were audio recorded and transcribed verbatim. Transcripts were then analysed thematically and using Linguistic Inquiry to examine emotional content.

RESULTS: Four core themes were identified: preparing for death; communication challenges; the nurse-family relationship and resilience of nurses. Findings suggested that continuing to provide aggressive treatment to a dying child/infant whilst simultaneously caring for the family caused discomfort and frustration for nurses. Nurses sometimes delayed death to allow families to prepare, as evidenced in the Linguistic Inquiry analysis, which enabled differentiation between types of emotional talk such as anger talk, anxiety talk and sadness talk. PICU nurses had significantly more anxiety talk (p=0.018) than NICU nurses.

CONCLUSION: This study provided rich insights into the experiences of nurses who are caring for dying children including the nurses' need to balance the often aggressive treatments with preparation of the family for the possibility of their child's death. There is some room for improvement in nurses' provision of anticipatory guidance, which encompasses effective and open communication, focussed on preparing families for the child's death.

Assessment of an established dialysis nurse practitioner model of care using mixed methods research

AIMS AND OBJECTIVES: To assess a dialysis nurse practitioner (NP) model of care by examining satisfaction, quality of life (QOL) and clinical outcomes of haemodialysis patients and explore experiences of dialysis nurses.

DESIGN: Mixed methods.

METHODS: Database analyses of dialysis indices amongst a sample (n = 45) of haemodialysis patients; a survey (n = 27) examining patient experience, satisfaction and QOL; and in-depth interviews with a sample (n = 10) of nurses.

RESULTS: Nurses commended the NP role, with five themes emerging: "managing and co-ordinating", "streamlining and alleviating", "developing capability", "supporting innovation and quality" and "connecting rurally". Patients' average age was 66 years and 71% were male. Patients' satisfaction with the care they received was rated 3.5/4 or higher across seven parameters and the average QOL score was 7.9/10.

CONCLUSION: The NP model of care is effective in enhancing patient care within a collaborative framework. The challenge is to sustain, and enhance the model, through mentorship programs for potential candidates.

New Rigorous Decomposition Methods for Mixed-integer Linear and Nonlinear Programming

Process systems design, operation and synthesis problems under uncertainty can readily be formulated as two-stage stochastic mixed-integer linear and nonlinear (nonconvex) programming (MILP and MINLP) problems. These problems, with a scenario based formulation, lead to large-scale MILPs/MINLPs that are well structured. The first part of the thesis proposes a new finitely convergent cross decomposition method (CD), where Benders decomposition (BD) and Dantzig-Wolfe decomposition (DWD) are combined in a unified framework to improve the solution of scenario based two-stage stochastic MILPs. This method alternates between DWD iterations and BD iterations, where DWD restricted master problems and BD primal problems yield a sequence of upper bounds, and BD relaxed master problems yield a sequence of lower bounds. A variant of CD, which includes multiple columns per iteration of DW restricted master problem and multiple cuts per iteration of BD relaxed master problem, called multicolumn-multicut CD is then developed to improve solution time. Finally, an extended cross decomposition method (ECD) for solving two-stage stochastic programs with risk constraints is proposed. In this approach, a CD approach at the first level and DWD at a second level is used to solve the original problem to optimality. ECD has a computational advantage over a bilevel decomposition strategy or solving the monolith problem using an MILP solver. The second part of the thesis develops a joint decomposition approach combining Lagrangian decomposition (LD) and generalized Benders decomposition (GBD), to efficiently solve stochastic mixed-integer nonlinear nonconvex programming problems to global optimality, without the need for explicit branch and bound search. In this approach, LD subproblems and GBD subproblems are systematically solved in a single framework. The relaxed master problem obtained from the reformulation of the original problem, is solved only when necessary. A convexification of the relaxed master problem and a domain reduction procedure are integrated into the decomposition framework to improve solution efficiency. Using case studies taken from renewable resource and fossil-fuel based application in process systems engineering, it can be seen that these novel decomposition approaches have significant benefit over classical decomposition methods and state-of-the-art MILP/MINLP global optimization solvers.

The complexity of preschool children’s dramatic play behaviour and play styles in Australia: a mixed methods study

Dramatic play is recognised as an important source of learning and development for preschool children, yet there are increasing reports that the quality of dramatic play is declining. This paper aims to report on the findings of a mixed method study that examined the constructs of Australian preschool children’s dramatic play behaviour. Video observations and the Smilansky Scale for the Evaluation of Dramatic and Socio-Dramatic Play (Smilanksy & Shefatya, 1990) were used with 101 preschool children aged 4 to 6 years in selected early childhood educational settings in Melbourne, Australia. Findings reveal that the overall level of children’s dramatic play behaviour was low. A typology of four play styles will be presented. Implications on educators’ pedagogy are discussed.

Academics’ opinions and practices of education for sustainable development : reflections on a nation-wide, mixed-methods, multidisciplinary study

The Routledge International Handbook of Higher Education for Sustainable Development gives a systematic and comprehensive overview of existing and upcoming research approaches for higher education for sustainable development.

Concerns and worries in people living with inflammatory bowel disease (IBD): A mixed methods study.

OBJECTIVE: This mixed-methods study aimed to explore concerns and worries related to living with inflammatory bowel disease (IBD). METHODS: Overall, 294 patients with a clinically established diagnosis of IBD were enrolled in this cross-sectional study. Concerns and worries were measured with one open-ended question. Measures of anxiety and depressive symptoms and disease activity were also administered. A thematic analysis was conducted and thematic map created. Spearman's rho was used to identify univariate correlations between predictors and the main themes. Binary logistic regression was used to test the predictors of the main themes. RESULTS: Despite the majority of study participants being in IBD remission (74%, n=217), all but 11 reported significant IBD-related concerns. Twenty two percent reported symptoms of depression and 41% of anxiety. Four themes were identified: Quality of life (51%); Unpredictability (35%); Symptoms (34%) and Treatments (19%). Males and older people were less concerned about Quality of life (OR=.597, 95% CI: .363-.980 and OR=.980, 95% CI: .965-.995, respectively). Those in remission were less concerned about Symptoms (OR=.510, 95% CI: .281- .926) while those with longer disease duration worried more about the Symptoms (OR=1.035, 95% CI: 1.010-1.061). Males were less concerned about Treatments (OR=.422, 95% CI: .229-.777). CONCLUSION: IBD patients report significant disease-related concerns even when in remission. Further exploration of what predicts patient concerns may help in shaping health-care delivery so that it better addresses patient needs.

Mixed genotype Hepatitis C virus infections: incidence in Scotland and methods for detection

The diagnosis of mixed genotype hepatitis C virus (HCV) infection is rare and information on incidence in the UK, where genotypes 1a and 3 are the most prevalent, is sparse. Considerable variations in the efficacies of direct-acting antivirals (DAAs) for the HCV genotypes have been documented and the ability of DAAs to treat mixed genotype HCV infections remains unclear, with the possibility that genotype switching may occur. In order to estimate the prevalence of mixed genotype 1a/3 infections in Scotland, a cohort of 512 samples was compiled and then screened using a genotype-specific nested PCR assay. Mixed genotype 1a/3 infections were found in 3.8% of samples tested, with a significantly higher prevalence rate of 6.7% (p<0.05) observed in individuals diagnosed with genotype 3 infections than genotype 1a (0.8%). An analysis of the samples using genotypic-specific qPCR assays found that in two-thirds of samples tested, the minor strain contributed <1% of the total viral load. The potential of deep sequencing methods for the diagnosis of mixed genotype infections was assessed using two pan-genotypic PCR assays compatible with the Illumina MiSeq platform that were developed targeting the E1-E2 and NS5B regions of the virus. The E1-E2 assay detected 75% of the mixed genotype infections, proving to be more sensitive than the NS5B assay which identified only 25% of the mixed infections. Studies of sequence data and linked patient records also identified significantly more neurological disorders in genotype 3 patients. Evidence of distinctive dinucleotide expression within the genotypes was also uncovered. Taken together these findings raise interesting questions about the evolutionary history of the virus and indicate that there is still more to understand about the different genotypes. In an era where clinical medicine is frequently more personalised, the development of diagnostic methods for HCV providing increased patient stratification is increasingly important. This project has shown that sequence-based genotyping methods can be highly discriminatory and informative, and their use should be encouraged in diagnostic laboratories. Mixed genotype infections were challenging to identify and current deep sequencing methods were not as sensitive or cost-effective as Sanger-based approaches in this study. More research is needed to evaluate the clinical prognosis of patients with mixed genotype infection and to develop clinical guidelines on their treatment.

New dimeric supramolecular structure of mixed (phthalocyaninato)(porphyrinato)-europium(III) sandwiches : preparation and spectroscopic characteristics

The mixed double-decker Eu\[Pc(15C5)4](TPP) (1) was obtained by base-catalysed tetramerisation of 4,5-dicyanobenzo-15-crown-5 using the half-sandwich complex Eu(TPP)(acac) (acac = acetylacetonate), generated in situ, as the template. For comparative studies, the mixed triple-decker complexes Eu2\[Pc(15C5)4](TPP)2 (2) and Eu2\[Pc(15C5)4]2(TPP) (3) were also synthesised by the raise-by-one-story method. These mixed ring sandwich complexes were characterised by various spectroscopic methods. Up to four one-electron oxidations and two one-electron reductions were revealed by cyclic voltammetry (CV) and differential pulse voltammetry (DPV). As shown by electronic absorption and infrared spectroscopy, supramolecular dimers (SM1 and SM3) were formed from the corresponding double-decker 1 and triple-decker 3 in the presence of potassium ions in MeOH/CHCl3.

Alternative analytical methods for the identification of cancer-related symptom clusters

Advances in symptom management strategies through a better understanding of cancer symptom clusters depend on the identification of symptom clusters that are valid and reliable. The purpose of this exploratory research was to investigate alternative analytical approaches to identify symptom clusters for patients with cancer, using readily accessible statistical methods, and to justify which methods of identification may be appropriate for this context. Three studies were undertaken: (1) a systematic review of the literature, to identify analytical methods commonly used for symptom cluster identification for cancer patients; (2) a secondary data analysis to identify symptom clusters and compare alternative methods, as a guide to best practice approaches in cross-sectional studies; and (3) a secondary data analysis to investigate the stability of symptom clusters over time. The systematic literature review identified, in 10 years prior to March 2007, 13 cross-sectional studies implementing multivariate methods to identify cancer related symptom clusters. The methods commonly used to group symptoms were exploratory factor analysis, hierarchical cluster analysis and principal components analysis. Common factor analysis methods were recommended as the best practice cross-sectional methods for cancer symptom cluster identification. A comparison of alternative common factor analysis methods was conducted, in a secondary analysis of a sample of 219 ambulatory cancer patients with mixed diagnoses, assessed within one month of commencing chemotherapy treatment. Principal axis factoring, unweighted least squares and image factor analysis identified five consistent symptom clusters, based on patient self-reported distress ratings of 42 physical symptoms. Extraction of an additional cluster was necessary when using alpha factor analysis to determine clinically relevant symptom clusters. The recommended approaches for symptom cluster identification using nonmultivariate normal data were: principal axis factoring or unweighted least squares for factor extraction, followed by oblique rotation; and use of the scree plot and Minimum Average Partial procedure to determine the number of factors. In contrast to other studies which typically interpret pattern coefficients alone, in these studies symptom clusters were determined on the basis of structure coefficients. This approach was adopted for the stability of the results as structure coefficients are correlations between factors and symptoms unaffected by the correlations between factors. Symptoms could be associated with multiple clusters as a foundation for investigating potential interventions. The stability of these five symptom clusters was investigated in separate common factor analyses, 6 and 12 months after chemotherapy commenced. Five qualitatively consistent symptom clusters were identified over time (Musculoskeletal-discomforts/lethargy, Oral-discomforts, Gastrointestinaldiscomforts, Vasomotor-symptoms, Gastrointestinal-toxicities), but at 12 months two additional clusters were determined (Lethargy and Gastrointestinal/digestive symptoms). Future studies should include physical, psychological, and cognitive symptoms. Further investigation of the identified symptom clusters is required for validation, to examine causality, and potentially to suggest interventions for symptom management. Future studies should use longitudinal analyses to investigate change in symptom clusters, the influence of patient related factors, and the impact on outcomes (e.g., daily functioning) over time.

Statistical and Econometric Methods for Transportation Data Analysis, 2nd edition

Now in its second edition, this book describes tools that are commonly used in transportation data analysis. The first part of the text provides statistical fundamentals while the second part presents continuous dependent variable models. With a focus on count and discrete dependent variable models, the third part features new chapters on mixed logit models, logistic regression, and ordered probability models. The last section provides additional coverage of Bayesian statistical modeling, including Bayesian inference and Markov chain Monte Carlo methods. Data sets are available online to use with the modeling techniques discussed.

Wavelet based approaches and high resolution methods for complex process models

Many industrial processes and systems can be modelled mathematically by a set of Partial Differential Equations (PDEs). Finding a solution to such a PDF model is essential for system design, simulation, and process control purpose. However, major difficulties appear when solving PDEs with singularity. Traditional numerical methods, such as finite difference, finite element, and polynomial based orthogonal collocation, not only have limitations to fully capture the process dynamics but also demand enormous computation power due to the large number of elements or mesh points for accommodation of sharp variations. To tackle this challenging problem, wavelet based approaches and high resolution methods have been recently developed with successful applications to a fixedbed adsorption column model. Our investigation has shown that recent advances in wavelet based approaches and high resolution methods have the potential to be adopted for solving more complicated dynamic system models. This chapter will highlight the successful applications of these new methods in solving complex models of simulated-moving-bed (SMB) chromatographic processes. A SMB process is a distributed parameter system and can be mathematically described by a set of partial/ordinary differential equations and algebraic equations. These equations are highly coupled; experience wave propagations with steep front, and require significant numerical effort to solve. To demonstrate the numerical computing power of the wavelet based approaches and high resolution methods, a single column chromatographic process modelled by a Transport-Dispersive-Equilibrium linear model is investigated first. Numerical solutions from the upwind-1 finite difference, wavelet-collocation, and high resolution methods are evaluated by quantitative comparisons with the analytical solution for a range of Peclet numbers. After that, the advantages of the wavelet based approaches and high resolution methods are further demonstrated through applications to a dynamic SMB model for an enantiomers separation process. This research has revealed that for a PDE system with a low Peclet number, all existing numerical methods work well, but the upwind finite difference method consumes the most time for the same degree of accuracy of the numerical solution. The high resolution method provides an accurate numerical solution for a PDE system with a medium Peclet number. The wavelet collocation method is capable of catching up steep changes in the solution, and thus can be used for solving PDE models with high singularity. For the complex SMB system models under consideration, both the wavelet based approaches and high resolution methods are good candidates in terms of computation demand and prediction accuracy on the steep front. The high resolution methods have shown better stability in achieving steady state in the specific case studied in this Chapter.

Information transfer for multi-trauma patients on discharge from the emergency department : mixed-method narrative review

Aim. This paper is a report of a review conducted to identify (a) best practice in information transfer from the emergency department for multi-trauma patients; (b) conduits and barriers to information transfer in trauma care and related settings; and (c) interventions that have an impact on information communication at handover and beyond. Background. Information transfer is integral to effective trauma care, and communication breakdown results in important challenges to this. However, evidence of adequacy of structures and processes to ensure transfer of patient information through the acute phase of trauma care is limited. Data sources. Papers were sourced from a search of 12 online databases and scanning references from relevant papers for 1990–2009. Review methods. The review was conducted according to the University of York’s Centre for Reviews and Dissemination guidelines. Studies were included if they concerned issues that influenced information transfer for patients in healthcare settings. Results. Forty-five research papers, four literature reviews and one policy statement were found to be relevant to parts of the topic, but not all of it. The main issues emerging concerned the impact of communication breakdown in some form, and included communication issues within trauma team processes, lack of structure and clarity during handovers including missing, irrelevant and inaccurate information, distractions and poorly documented care. Conclusion. Many factors influence information transfer but are poorly identified in relation to trauma care. The measurement of information transfer, which is integral to patient handover, has not been the focus of research to date. Nonetheless, documented patient information is considered evidence of care and a resource that affects continuing care.