Finding My Way: Protocol of a randomised controlled trial evaluating an internet self-help program for cancer-related distress

Background A cancer diagnosis elicits greater distress than any other medical diagnosis, and yet very few studies have evaluated the efficacy of structured online self-help therapeutic programs to alleviate this distress. This study aims to assess the efficacy over time of an internet Cognitive Behaviour Therapy (iCBT) intervention (‘Finding My Way’) in improving distress, coping and quality of life for individuals with a recent diagnosis of early stage cancer of any type. Methods/Design The study is a multi-site Randomised Controlled Trial (RCT) seeking to enrol 188 participants who will be randomised to either the Finding My Way Intervention or an attention-control condition. Both conditions are delivered online; with 6 modules released once per week, and an additional booster module released one month after program-completion. Participants complete online questionnaires on 4 occasions: at baseline (immediately prior to accessing the modules); post-treatment (immediately after program-completion); then three and six months later. Primary outcomes are general distress and cancer-specific distress, with secondary outcomes including Health-Related Quality of Life (HRQoL), coping, health service utilisation, intervention adherence, and user satisfaction. A range of baseline measures will be assessed as potential moderators of outcomes. Eligible participants are individuals recently diagnosed with any type of cancer, being treated with curative intent, aged over 18 years with sufficient English language literacy, internet access and an active email account and phone number. Participants are blinded to treatment group allocation. Randomisation is computer generated and stratified by gender. Discussion Compared to the few prior published studies, Finding My Way will be the first adequately powered trial to offer an iCBT intervention to curatively treated patients of heterogeneous cancer types in the immediate post-diagnosis/treatment period. If found efficacious, Finding My Way will assist with overcoming common barriers to face-to-face therapy in a cost-effective and accessible way, thus helping to reduce distress after cancer diagnosis and consequently decrease the cancer burden for individuals and the health system. Trial registration Australian New Zealand Clinical Trials Registry ACTRN12613000001​796 16.10.13

Struggles over resources and representations in territorial conflicts in the Northern Autonomous Atlantic Region (RAAN), Nicaragua

Territoriality is a central issue in indigenous peoples struggles. The territorial struggles involve struggles over the control of natural resources and over political participation and representation, but also over the perception of territorial rights and the symbolic representation of the territory. These struggles are carried through both in material and symbolic ways through recurring to different discourses and representations that provide legitimation for the territorial claims of the group. The study is located in the Northern Autonomous Atlantic Region of Nicaragua. The study concerns the territorial strategies, conceptions and practices of the indigenous people and other actors. Territorial conflicts exist between the autonomous region and the central government of Nicaragua, between mestizo settlers and indigenous people, between different indigenous groups, and between these and development agents such as conservation projects. The study focuses on how territorial discourses and representations are used to legitimate territorial control. Environmental, historical and cartographical discourses are the most important discourses recurred to. The influence of discourses and representations on the territorial practices and policies of the different actors, the links between the local struggles and global processes, and the broader structural factors impacting on the territorial struggles are also analysed. Among the structural factors are the problems related to land tenure and management and the use of natural resources, the advance of the agricultural frontier, the institutional weaknesses of the central and regional governments and the legislative processes. The territorial discourses are both recurred to in a strategic way and also grounded in local ideals and practices. The discourses have produced real effects for example in legislation, land tenure systems, political representation and environmental practices. Although the use of discourses and representations are an important power tool in territorial struggles, territorial control cannot be effectively accomplished merely through representing territorial claims in a legitimate way or through reforming legislation, as the conflicts are also largely a result of structural factors affecting the region. The fieldwork was carried out during a total of twelve months between 2000 and 2002. The research methods used were semi-structured interviews, participant observation and participatory research methods. A broad range of literary sources were also used to collect data. The study is located within the field of critical political geography with a discursive political ecology approach. It can be called a critical realist approach to the discursive analysis of indigenous territoriality.

The use of neurocognitive methods in assessing health communication messages: A systematic review

We review 20 studies that examined persuasive processing and outcomes of health messages using neurocognitive measures. The results suggest that cognitive processes and neural activity in regions thought to reflect self-related processing may be more prominent in the persuasive process of self-relevant messages. Furthermore, activity in the medial prefrontal cortex (MPFC), the superior temporal gyrus, and the middle frontal gyrus were identified as predictors of message effectiveness, with the MPFC accounting for additional variance in behaviour change beyond that accounted for by self-report measures. Incorporating neurocognitive measures may provide a more comprehensive understanding of the processing and outcomes of health messages.

Conformal Field Theory Methods for Variants of Schramm-Loewner Evolutions

This thesis consists of an introduction, four research articles and an appendix. The thesis studies relations between two different approaches to continuum limit of models of two dimensional statistical mechanics at criticality. The approach of conformal field theory (CFT) could be thought of as the algebraic classification of some basic objects in these models. It has been succesfully used by physicists since 1980's. The other approach, Schramm-Loewner evolutions (SLEs), is a recently introduced set of mathematical methods to study random curves or interfaces occurring in the continuum limit of the models. The first and second included articles argue on basis of statistical mechanics what would be a plausible relation between SLEs and conformal field theory. The first article studies multiple SLEs, several random curves simultaneously in a domain. The proposed definition is compatible with a natural commutation requirement suggested by Dubédat. The curves of multiple SLE may form different topological configurations, ``pure geometries''. We conjecture a relation between the topological configurations and CFT concepts of conformal blocks and operator product expansions. Example applications of multiple SLEs include crossing probabilities for percolation and Ising model. The second article studies SLE variants that represent models with boundary conditions implemented by primary fields. The most well known of these, SLE(kappa, rho), is shown to be simple in terms of the Coulomb gas formalism of CFT. In the third article the space of local martingales for variants of SLE is shown to carry a representation of Virasoro algebra. Finding this structure is guided by the relation of SLEs and CFTs in general, but the result is established in a straightforward fashion. This article, too, emphasizes multiple SLEs and proposes a possible way of treating pure geometries in terms of Coulomb gas. The fourth article states results of applications of the Virasoro structure to the open questions of SLE reversibility and duality. Proofs of the stated results are provided in the appendix. The objective is an indirect computation of certain polynomial expected values. Provided that these expected values exist, in generic cases they are shown to possess the desired properties, thus giving support for both reversibility and duality.

Renormalization methods in KAM theory

It is well known that an integrable (in the sense of Arnold-Jost) Hamiltonian system gives rise to quasi-periodic motion with trajectories running on invariant tori. These tori foliate the whole phase space. If we perturb an integrable system, the Kolmogorow-Arnold-Moser (KAM) theorem states that, provided some non-degeneracy condition and that the perturbation is sufficiently small, most of the invariant tori carrying quasi-periodic motion persist, getting only slightly deformed. The measure of the persisting invariant tori is large together with the inverse of the size of the perturbation. In the first part of the thesis we shall use a Renormalization Group (RG) scheme in order to prove the classical KAM result in the case of a non analytic perturbation (the latter will only be assumed to have continuous derivatives up to a sufficiently large order). We shall proceed by solving a sequence of problems in which theperturbations are analytic approximations of the original one. We will finally show that the approximate solutions will converge to a differentiable solution of our original problem. In the second part we will use an RG scheme using continuous scales, so that instead of solving an iterative equation as in the classical RG KAM, we will end up solving a partial differential equation. This will allow us to reduce the complications of treating a sequence of iterative equations to the use of the Banach fixed point theorem in a suitable Banach space.

Bayesian Inference for Retrospective Population Genetics Models Using Markov Chain Monte Carlo Methods

Genetics, the science of heredity and variation in living organisms, has a central role in medicine, in breeding crops and livestock, and in studying fundamental topics of biological sciences such as evolution and cell functioning. Currently the field of genetics is under a rapid development because of the recent advances in technologies by which molecular data can be obtained from living organisms. In order that most information from such data can be extracted, the analyses need to be carried out using statistical models that are tailored to take account of the particular genetic processes. In this thesis we formulate and analyze Bayesian models for genetic marker data of contemporary individuals. The major focus is on the modeling of the unobserved recent ancestry of the sampled individuals (say, for tens of generations or so), which is carried out by using explicit probabilistic reconstructions of the pedigree structures accompanied by the gene flows at the marker loci. For such a recent history, the recombination process is the major genetic force that shapes the genomes of the individuals, and it is included in the model by assuming that the recombination fractions between the adjacent markers are known. The posterior distribution of the unobserved history of the individuals is studied conditionally on the observed marker data by using a Markov chain Monte Carlo algorithm (MCMC). The example analyses consider estimation of the population structure, relatedness structure (both at the level of whole genomes as well as at each marker separately), and haplotype configurations. For situations where the pedigree structure is partially known, an algorithm to create an initial state for the MCMC algorithm is given. Furthermore, the thesis includes an extension of the model for the recent genetic history to situations where also a quantitative phenotype has been measured from the contemporary individuals. In that case the goal is to identify positions on the genome that affect the observed phenotypic values. This task is carried out within the Bayesian framework, where the number and the relative effects of the quantitative trait loci are treated as random variables whose posterior distribution is studied conditionally on the observed genetic and phenotypic data. In addition, the thesis contains an extension of a widely-used haplotyping method, the PHASE algorithm, to settings where genetic material from several individuals has been pooled together, and the allele frequencies of each pool are determined in a single genotyping.

Methods to improve gene signal: Application to cDNA microarrays

Microarrays are high throughput biological assays that allow the screening of thousands of genes for their expression. The main idea behind microarrays is to compute for each gene a unique signal that is directly proportional to the quantity of mRNA that was hybridized on the chip. A large number of steps and errors associated with each step make the generated expression signal noisy. As a result, microarray data need to be carefully pre-processed before their analysis can be assumed to lead to reliable and biologically relevant conclusions. This thesis focuses on developing methods for improving gene signal and further utilizing this improved signal for higher level analysis. To achieve this, first, approaches for designing microarray experiments using various optimality criteria, considering both biological and technical replicates, are described. A carefully designed experiment leads to signal with low noise, as the effect of unwanted variations is minimized and the precision of the estimates of the parameters of interest are maximized. Second, a system for improving the gene signal by using three scans at varying scanner sensitivities is developed. A novel Bayesian latent intensity model is then applied on these three sets of expression values, corresponding to the three scans, to estimate the suitably calibrated true signal of genes. Third, a novel image segmentation approach that segregates the fluorescent signal from the undesired noise is developed using an additional dye, SYBR green RNA II. This technique helped in identifying signal only with respect to the hybridized DNA, and signal corresponding to dust, scratch, spilling of dye, and other noises, are avoided. Fourth, an integrated statistical model is developed, where signal correction, systematic array effects, dye effects, and differential expression, are modelled jointly as opposed to a sequential application of several methods of analysis. The methods described in here have been tested only for cDNA microarrays, but can also, with some modifications, be applied to other high-throughput technologies. Keywords: High-throughput technology, microarray, cDNA, multiple scans, Bayesian hierarchical models, image analysis, experimental design, MCMC, WinBUGS.

Medication incident reporting in residential aged care facilities: Limitations and risks to residents' safety

Background Medication incident reporting (MIR) is a key safety critical care process in residential aged care facilities (RACFs). Retrospective studies of medication incident reports in aged care have identified the inability of existing MIR processes to generate information that can be used to enhance residents’ safety. However, there is little existing research that investigates the limitations of the existing information exchange process that underpins MIR, despite the considerable resources that RACFs’ devote to the MIR process. The aim of this study was to undertake an in-depth exploration of the information exchange process involved in MIR and identify factors that inhibit the collection of meaningful information in RACFs. Methods The study was undertaken in three RACFs (part of a large non-profit organisation) in NSW, Australia. A total of 23 semi-structured interviews and 62 hours of observation sessions were conducted between May to July 2011. The qualitative data was iteratively analysed using a grounded theory approach. Results The findings highlight significant gaps in the design of the MIR artefacts as well as information exchange issues in MIR process execution. Study results emphasized the need to: a) design MIR artefacts that facilitate identification of the root causes of medication incidents, b) integrate the MIR process within existing information systems to overcome key gaps in information exchange execution, and c) support exchange of information that can facilitate a multi-disciplinary approach to medication incident management in RACFs. Conclusions This study highlights the advantages of viewing MIR process holistically rather than as segregated tasks, as a means to identify gaps in information exchange that need to be addressed in practice to improve safety critical processes.

Design challenges for electronic medication administration record systems in residential aged care facilities: A formative evaluation

Introduction Electronic medication administration record (eMAR) systems are promoted as a potential intervention to enhance medication safety in residential aged care facilities (RACFs). The purpose of this study was to conduct an in-practice evaluation of an eMAR being piloted in one Australian RACF before its roll out, and to provide recommendations for system improvements. Methods A multidisciplinary team conducted direct observations of workflow (n=34 hours) in the RACF site and the community pharmacy. Semi-structured interviews (n=5) with RACF staff and the community pharmacist were conducted to investigate their views of the eMAR system. Data were analysed using a grounded theory approach to identify challenges associated with the design of the eMAR system. Results The current eMAR system does not offer an end-to-end solution for medication management. Many steps, including prescribing by doctors and communication with the community pharmacist, are still performed manually using paper charts and fax machines. Five major challenges associated with the design of eMAR system were identified: limited interactivity; inadequate flexibility; problems related to information layout and semantics; the lack of relevant decision support; and system maintenance issues.We suggest recommendations to improve the design of the eMAR system and to optimize existing workflows. Discussion Immediate value can be achieved by improving the system interactivity, reducing inconsistencies in data entry design and offering dedicated organisational support to minimise connectivity issues. Longer-term benefits can be achieved by adding decision support features and establishing system interoperability requirements with stakeholder groups (e.g. community pharmacies) prior to system roll out. In-practice evaluations of technologies like eMAR system have great value in identifying design weaknesses which inhibit optimal system use.

Computational Methods for Reconstruction and Analysis of Genome-Scale Metabolic Networks

Metabolism is the cellular subsystem responsible for generation of energy from nutrients and production of building blocks for larger macromolecules. Computational and statistical modeling of metabolism is vital to many disciplines including bioengineering, the study of diseases, drug target identification, and understanding the evolution of metabolism. In this thesis, we propose efficient computational methods for metabolic modeling. The techniques presented are targeted particularly at the analysis of large metabolic models encompassing the whole metabolism of one or several organisms. We concentrate on three major themes of metabolic modeling: metabolic pathway analysis, metabolic reconstruction and the study of evolution of metabolism. In the first part of this thesis, we study metabolic pathway analysis. We propose a novel modeling framework called gapless modeling to study biochemically viable metabolic networks and pathways. In addition, we investigate the utilization of atom-level information on metabolism to improve the quality of pathway analyses. We describe efficient algorithms for discovering both gapless and atom-level metabolic pathways, and conduct experiments with large-scale metabolic networks. The presented gapless approach offers a compromise in terms of complexity and feasibility between the previous graph-theoretic and stoichiometric approaches to metabolic modeling. Gapless pathway analysis shows that microbial metabolic networks are not as robust to random damage as suggested by previous studies. Furthermore the amino acid biosynthesis pathways of the fungal species Trichoderma reesei discovered from atom-level data are shown to closely correspond to those of Saccharomyces cerevisiae. In the second part, we propose computational methods for metabolic reconstruction in the gapless modeling framework. We study the task of reconstructing a metabolic network that does not suffer from connectivity problems. Such problems often limit the usability of reconstructed models, and typically require a significant amount of manual postprocessing. We formulate gapless metabolic reconstruction as an optimization problem and propose an efficient divide-and-conquer strategy to solve it with real-world instances. We also describe computational techniques for solving problems stemming from ambiguities in metabolite naming. These techniques have been implemented in a web-based sofware ReMatch intended for reconstruction of models for 13C metabolic flux analysis. In the third part, we extend our scope from single to multiple metabolic networks and propose an algorithm for inferring gapless metabolic networks of ancestral species from phylogenetic data. Experimenting with 16 fungal species, we show that the method is able to generate results that are easily interpretable and that provide hypotheses about the evolution of metabolism.

Computational Methods for Detecting Large-Scale Chromosome Rearrangements in SNP Data

Large-scale chromosome rearrangements such as copy number variants (CNVs) and inversions encompass a considerable proportion of the genetic variation between human individuals. In a number of cases, they have been closely linked with various inheritable diseases. Single-nucleotide polymorphisms (SNPs) are another large part of the genetic variance between individuals. They are also typically abundant and their measuring is straightforward and cheap. This thesis presents computational means of using SNPs to detect the presence of inversions and deletions, a particular variety of CNVs. Technically, the inversion-detection algorithm detects the suppressed recombination rate between inverted and non-inverted haplotype populations whereas the deletion-detection algorithm uses the EM-algorithm to estimate the haplotype frequencies of a window with and without a deletion haplotype. As a contribution to population biology, a coalescent simulator for simulating inversion polymorphisms has been developed. Coalescent simulation is a backward-in-time method of modelling population ancestry. Technically, the simulator also models multiple crossovers by using the Counting model as the chiasma interference model. Finally, this thesis includes an experimental section. The aforementioned methods were tested on synthetic data to evaluate their power and specificity. They were also applied to the HapMap Phase II and Phase III data sets, yielding a number of candidates for previously unknown inversions, deletions and also correctly detecting known such rearrangements.

Statistical and Information-Theoretic Methods for Data-Analysis

In this Thesis, we develop theory and methods for computational data analysis. The problems in data analysis are approached from three perspectives: statistical learning theory, the Bayesian framework, and the information-theoretic minimum description length (MDL) principle. Contributions in statistical learning theory address the possibility of generalization to unseen cases, and regression analysis with partially observed data with an application to mobile device positioning. In the second part of the Thesis, we discuss so called Bayesian network classifiers, and show that they are closely related to logistic regression models. In the final part, we apply the MDL principle to tracing the history of old manuscripts, and to noise reduction in digital signals.