e-Health and Health literacy: a revision of research methods

E-health provides powerful tools to improve health, but users’ health literacy – their ability to obtain, process, and act appropriately on health information – plays a role in their ability to make the most of e-health applications. This project reviewed research focused on e-health and health literacy, coding 94 articles to provide an overview of the field including use of theory and research methods. Findings indicate a lack of theory and use of established health literacy measures.

Methods and resources for climate impacts research: achieving synergy

The prediction of climate variability and change requires the use of a range of simulation models. Multiple climate model simulations are needed to sample the inherent uncertainties in seasonal to centennial prediction. Because climate models are computationally expensive, there is a tradeoff between complexity, spatial resolution, simulation length, and ensemble size. The methods used to assess climate impacts are examined in the context of this trade-off. An emphasis on complexity allows simulation of coupled mechanisms, such as the carbon cycle and feedbacks between agricultural land management and climate. In addition to improving skill, greater spatial resolution increases relevance to regional planning. Greater ensemble size improves the sampling of probabilities. Research from major international projects is used to show the importance of synergistic research efforts. The primary climate impact examined is crop yield, although many of the issues discussed are relevant to hydrology and health modeling. Methods used to bridge the scale gap between climate and crop models are reviewed. Recent advances include large-area crop modeling, quantification of uncertainty in crop yield, and fully integrated crop–climate modeling. The implications of trends in computer power, including supercomputers, are also discussed.

RES 012. Research methods in the arts and humanities. First edition

A training course that forms part of Epigeum's Research Skills Master Programme.

Integrating socio-economics and ecology: a taxonomy of quantitative methods and a review of their use in agro-ecology

Answering many of the critical questions in conservation, development and environmental management requires integrating the social and natural sciences. However, understanding the array of available quantitative methods and their associated terminology presents a major barrier to successful collaboration. We provide an overview of quantitative socio-economic methods that distils their complexity into a simple taxonomy. We outline how each has been used in conjunction with ecological models to address questions relating to the management of socio-ecological systems. We review the application of social and ecological quantitative concepts to agro-ecology and classify the approaches used to integrate the two disciplines. Our review included all published integrated models from 2003 to 2008 in 27 journals that publish agricultural modelling research. Although our focus is on agro-ecology, many of the results are broadly applicable to other fields involving an interaction between human activities and ecology. We found 36 papers that integrated social and ecological concepts in a quantitative model. Four different approaches to integration were used, depending on the scale at which human welfare was quantified. Most models viewed humans as pure profit maximizers, both when calculating welfare and predicting behaviour. Synthesis and applications. We reached two main conclusions based on our taxonomy and review. The first is that quantitative methods that extend predictions of behaviour and measurements of welfare beyond a simple market value basis are underutilized by integrated models. The second is that the accuracy of prediction for integrated models remains largely unquantified. Addressing both problems requires researchers to reach a common understanding of modelling goals and data requirements during the early stages of a project.

Research methods in TESOL and digital literacies

One of the biggest challenges of integrating research in TESOL with research in digital literacies is that the research methodologies of these two traditions have developed out of different ontological and episte- mological assumptions about what is being researched (the object of study), where the research is located (the research site), and who is being researched (the research participants).

LiLEDDA – a six step forum-based netnographic research method for nursing and caring sciences

Internet research methods in nursing science are less developed than in other sciences. We choose to present an approach to conducting nursing research on an internet-based forum. This paper presents LiLEDDA, a six-step forum-based netnographic research method for nursing science. The steps consist of: 1. Literature review and identification of the research question(s); 2. Locating the field(s) online; 3. Ethical considerations; 4. Data gathering; 5. Data analysis and interpretation; and 6. Abstractions and trustworthiness. Traditional research approaches are limiting when studying non-normative and non-mainstream life-worlds and their cultures. We argue that it is timely to develop more up-to-date research methods and study designs applicable to nursing science that reflect social developments and human living conditions that tend to be increasingly online-based.

Methods and strategies to identify the mode of action of phytoactive compounds

Small molecules affecting biological processes in plants are widely used in agricultural practice as herbicides or plant growth regulators and in basic plant sciences as probes to study the physiology of plants. Most of the compounds were identified in large screens by the agrochemical industry, as phytoactive natural products and more recently, novel phytoactive compounds originated from academic research by chemical screens performed to induce specific phenotypes of interest. The aim of the present PhD thesis is to evaluate different approaches used for the identification of the primary mode of action (MoA) of a phytoactive compound. Based on the methodologies used for MoA identification, three approaches are discerned: a phenotyping approach, an approach based on a genetic screen and a biochemical screening approach.rnFour scientific publications resulting from my work are presented as examples of how a phenotyping approach can successfully be applied to describe the plant MoA of different compounds in detail.rnI. A subgroup of cyanoacrylates has been discovered as plant growth inhibitors. A set of bioassays indicated a specific effect on cell division. Cytological investigations of the cell division process in plant cell cultures, studies of microtubule assembly with green fluorescent protein marker lines in vivo and cross resistant studies with Eleusine indica plants harbouring a mutation in alpha-tubulin, led to the description of alpha-tubulin as a target site of cyanoacrylates (Tresch et al., 2005).rnII. The MoA of the herbicide flamprop-m-methyl was not known so far. The studies described in Tresch et al. (2008) indicate a primary effect on cell division. Detailed studies unravelled a specific effect on mitotic microtubule figures, causing a block in cell division. In contrast to other inhibitors of microtubule rearrangement such as dinitroanilines, flamprop-m-methyl did not influence microtubule assembly in vitro. An influence of flamprop-m-methyl on a target within the cytoskeleton signalling network could be proposed (Tresch et al., 2008).rnIII. The herbicide endothall is a protein phosphatase inhibitor structurally related to the natural product cantharidin. Bioassay studies indicated a dominant effect on dark-growing cells that was unrelated to effects observed in the light. Cytological characterisation of the microtubule cytoskeleton in corn tissue and heterotrophic tobacco cells showed a specific effect of endothall on mitotic spindle formation and ultrastructure of the nucleus in combination with a decrease of the proliferation index. The observed effects are similar to those of other protein phosphatase inhibitors such as cantharidin and the structurally different okadaic acid. Additionally, the observed effects show similarities to knock-out lines of the TON1 pathway, a protein phosphatase-regulated signalling pathway. The data presented in Tresch et al. (2011) associate endothall’s known in vitro inhibition of protein phosphatases with in vivo-effects and suggest an interaction between endothall and the TON1 pathway.rnIV. Mefluidide as a plant growth regulator induces growth retardation and a specific phenotype indicating an inhibition of fatty acid biosynthesis. A test of the cuticle functionality suggested a defect in the biosynthesis of very-long-chain fatty acids (VLCFA) or waxes. Metabolic profiling studies showed similarities with different groups of VLCFA synthesis inhibitors. Detailed analyses of VLCFA composition in tissues of duckweed (Lemna paucicostata) indicated a specific inhibition of the known herbicide target 3 ketoacyl-CoA synthase (KCS). Inhibitor studies using a yeast expression system established for plant KCS proteins verified the potency of mefluidide as an inhibitor of plant KCS enzymes. It could be shown that the strength of inhibition varied for different KCS homologues. The Arabidopsis Cer6 protein, which induces a plant growth phenotype similar to mefluidide when knocked out, was one of the most sensitive KCS enzymes (Tresch et al., 2012).rnThe findings of my own work were combined with other publications reporting a successful identification of the MoA and primary target proteins of different compounds or compound classes.rnA revised three-tier approach for the MoA identification of phytoactive compounds is proposed. The approach consists of a 1st level aiming to address compound stability, uniformity of effects in different species, general cytotoxicity and the effect on common processes like transcription and translation. Based on these findings advanced studies can be defined to start the 2nd level of MoA characterisation, either with further phenotypic characterisation, starting a genetic screen or establishing a biochemical screen. At the 3rd level, enzyme assays or protein affinity studies should show the activity of the compound on the hypothesized target and should associate the in vitro effects with the in vivo profile of the compound.

Learning Methods and Algorithms for Semantic Text Classification across Multiple Domains

Information is nowadays a key resource: machine learning and data mining techniques have been developed to extract high-level information from great amounts of data. As most data comes in form of unstructured text in natural languages, research on text mining is currently very active and dealing with practical problems. Among these, text categorization deals with the automatic organization of large quantities of documents in priorly defined taxonomies of topic categories, possibly arranged in large hierarchies. In commonly proposed machine learning approaches, classifiers are automatically trained from pre-labeled documents: they can perform very accurate classification, but often require a consistent training set and notable computational effort. Methods for cross-domain text categorization have been proposed, allowing to leverage a set of labeled documents of one domain to classify those of another one. Most methods use advanced statistical techniques, usually involving tuning of parameters. A first contribution presented here is a method based on nearest centroid classification, where profiles of categories are generated from the known domain and then iteratively adapted to the unknown one. Despite being conceptually simple and having easily tuned parameters, this method achieves state-of-the-art accuracy in most benchmark datasets with fast running times. A second, deeper contribution involves the design of a domain-independent model to distinguish the degree and type of relatedness between arbitrary documents and topics, inferred from the different types of semantic relationships between respective representative words, identified by specific search algorithms. The application of this model is tested on both flat and hierarchical text categorization, where it potentially allows the efficient addition of new categories during classification. Results show that classification accuracy still requires improvements, but models generated from one domain are shown to be effectively able to be reused in a different one.

Randomization in clinical trials in orthodontics: its significance in research design and methods to achieve it

Randomization is a key step in reducing selection bias during the treatment allocation phase in randomized clinical trials. The process of randomization follows specific steps, which include generation of the randomization list, allocation concealment, and implementation of randomization. The phenomenon in the dental and orthodontic literature of characterizing treatment allocation as random is frequent; however, often the randomization procedures followed are not appropriate. Randomization methods assign, at random, treatment to the trial arms without foreknowledge of allocation by either the participants or the investigators thus reducing selection bias. Randomization entails generation of random allocation, allocation concealment, and the actual methodology of implementing treatment allocation randomly and unpredictably. Most popular randomization methods include some form of restricted and/or stratified randomization. This article introduces the reasons, which make randomization an integral part of solid clinical trial methodology, and presents the main randomization schemes applicable to clinical trials in orthodontics.

What do case-control studies estimate? Survey of methods and assumptions in published case-control research

To evaluate strategies used to select cases and controls and how reported odds ratios are interpreted, the authors examined 150 case-control studies published in leading general medicine, epidemiology, and clinical specialist journals from 2001 to 2007. Most of the studies (125/150; 83%) were based on incident cases; among these, the source population was mostly dynamic (102/125; 82%). A minority (23/125; 18%) sampled from a fixed cohort. Among studies with incident cases, 105 (84%) could interpret the odds ratio as a rate ratio. Fifty-seven (46% of 125) required the source population to be stable for such interpretation, while the remaining 48 (38% of 125) did not need any assumptions because of matching on time or concurrent sampling. Another 17 (14% of 125) studies with incident cases could interpret the odds ratio as a risk ratio, with 16 of them requiring the rare disease assumption for this interpretation. The rare disease assumption was discussed in 4 studies but was not relevant to any of them. No investigators mentioned the need for a stable population. The authors conclude that in current case-control research, a stable exposure distribution is much more frequently needed to interpret odds ratios than the rare disease assumption. At present, investigators conducting case-control studies rarely discuss what their odds ratios estimate.

Knowledge-Production Processes in Practice Research - Outcomes and Critical Elements

The welfare sector has seen considerable changes in its operational context. Welfare services respond to an increasing number of challenges as citizens are confronted with life’s uncertainties and a variety of complex situations. At the same time the service-delivery system is facing problems of co-operation and the development of staff competence, as well as demands to improve service effectiveness and outcomes. In order to ensure optimal user outcomes in this complex, evolving environment it is necessary to enhance professional knowledge and skills, and to increase efforts to develop the services. Changes are also evident in the new emergent knowledge-production models. There has been a shift from knowledge acquisition and transmission to its construction and production. New actors have stepped in and the roles of researchers are subject to critical discussion. Research outcomes, in other words the usefulness of research with respect to practice development, is a topical agenda item. Research is needed, but if it is to be useful it needs to be not only credible but also useful in action. What do we know about different research processes in practice? What conceptions, approaches, methods and actor roles are embedded? What is the effect on practice? How does ‘here and now’ practice challenge research methods? This article is based on the research processes conducted in the institutes of practice research in social work in Finland. It analyses the different approaches applied by elucidating the theoretical standpoints and the critical elements embedded in them, and reflects on the outcomes in and for practice. It highlights the level of change and progression in practice research, arguing for diverse practice research models with a solid theoretical grounding, rigorous research processes, and a supportive infrastructure.