A randomised controlled trial to assess the effectiveness of a single session of nurse administered massage for short term relief of chronic non-malignant pain

Background: Massage is increasingly used to manage chronic pain but its benefit has not been clearly established. The aim of the study is to determine the effectiveness of a single session of nurse-administered massage for the short term relief of chronic non-malignant pain and anxiety. Methods: A randomised controlled trial design was used, in which the patients were assigned to a massage or control group. The massage group received a 15 minute manual massage and the control group a 15 minute visit to talk about their pain. Adult patients attending a pain relief unit with a diagnosis of chronic pain whose pain was described as moderate or severe were eligible for the study. An observer blind to the patients' treatment group carried out assessments immediately before (baseline), after treatment and 1, 2, 3 and 4 hours later. Pain was assessed using 100 mm visual analogue scale and the McGill Pain Questionnaire. Pain Relief was assessed using a five point verbal rating scale. Anxiety was assessed with the Spielberger short form State-Trait Anxiety Inventory. Results: 101 patients were randomised and evaluated, 50 in the massage and 51 in the control group. There were no statistically significant differences between the groups at baseline interview. Patients in the massage but not the control group had significantly less pain compared to baseline immediately after and one hour post treatment. 95% confidence interval for the difference in mean pain reduction at one hour post treatment between the massage and control groups is 5.47 mm to 24.70 mm. Patients in the massage but not the control group had a statistically significant reduction in anxiety compared to baseline immediately after and at 1 hour post treatment. Conclusion: Massage is effective in the short term for chronic pain of moderate to severe intensity

Towards environmentally sustainable human behaviour: targeting non-conscious and conscious processes for effective and acceptable policies.

Meeting climate change targets to limit global warming to 2°C requires rapid and large reductions in demand for products that most contribute to greenhouse gas (GHG) emissions. These include production of bulk materials (e.g. steel and cement), energy supply (e.g. fossil fuels) and animal source foods (particularly ruminants and their products). Effective strategies to meet these targets require transformative changes in supply as well as demand, involving changes in economic, political and legal systems at local, national and international levels, building on evidence from many disciplines. This paper outlines contributions from behavioural science in reducing demand. Grounded in dual-process models of human behaviour (involving non-conscious and conscious processes) this paper considers first why interventions aimed at changing population values towards the environment are usually insufficient or unnecessary for reducing demand although they may be important in increasing public acceptability of policies that could reduce demand. It then outlines two sets of evidence from behavioural science towards effective systems-based strategies, to identify interventions likely to be effective at: (i) reducing demand for products that contribute most to GHG emissions, mainly targeting non-conscious processes and (ii) increasing public acceptability for policy changes to enable these interventions, targeting conscious processes.This article is part of the themed issue 'Material demand reduction'

Effect of drug utilization reviews on the quality of in-hospital prescribing: a quasi-experimental study

BACKGROUND: Drug utilization review (DUR) programs are being conducted in Canadian hospitals with the aim of improving the appropriateness of prescriptions. However, there is little evidence of their effectiveness. The objective of this study was to assess the impact of both a retrospective and a concurrent DUR programs on the quality of in-hospital prescribing. METHODS: We conducted an interrupted time series quasi-experimental study. Using explicit criteria for quality of prescribing, the natural history of cisapride prescription was established retrospectively in three university-affiliated hospitals. A retrospective DUR was implemented in one of the hospitals, a concurrent DUR in another, whereas the third hospital served as a control. An archivist abstracted records of all patients who were prescribed cisapride during the observation period. The effect of DURs relative to the control hospital was determined by comparing estimated regression coefficients from the time series models and by testing the statistical significance using a 2-tailed Student's t test. RESULTS: The concurrent DUR program significantly improved the appropriateness of prescriptions for the indication for use whereas the retrospective DUR brought about no significant effect on the quality of prescribing. CONCLUSION: Results suggest a retrospective DUR approach may not be sufficient to improve the quality of prescribing. However, a concurrent DUR strategy, with direct feedback to prescribers seems effective and should be tested in other settings with other drugs

Multi-locus Test Conditional on Confirmed Effects Leads to Increased Power in Genome-wide Association Studies

Complex diseases or phenotypes may involve multiple genetic variants and interactions between genetic, environmental and other factors. Current genome-wide association studies (GWAS) mostly used single-locus analysis and had identified genetic effects with multiple confirmations. Such confirmed single-nucleotide polymorphism (SNP) effects were likely to be true genetic effects and ignoring this information in testing new effects of the same phenotype results in decreased statistical power due to increased residual variance that has a component of the omitted effects. In this study, a multi-locus association test (MLT) was proposed for GWAS analysis conditional on SNPs with confirmed effects to improve statistical power. Analytical formulae for statistical power were derived and were verified by simulation for MLT accounting for confirmed SNPs and for single-locus test (SLT) without accounting for confirmed SNPs. Statistical power of the two methods was compared by case studies with simulated and the Framingham Heart Study (FHS) GWAS data. Results showed that the MLT method had increased statistical power over SLT. In the GWAS case study on four cholesterol phenotypes and serum metabolites, the MLT method improved statistical power by 5% to 38% depending on the number and effect sizes of the conditional SNPs. For the analysis of HDL cholesterol (HDL-C) and total cholesterol (TC) of the FHS data, the MLT method conditional on confirmed SNPs from GWAS catalog and NCBI had considerably more significant results than SLT

Interaction between Plate Make and Protein in Protein Crystallisation Screening

Background: Protein crystallisation screening involves the parallel testing of large numbers of candidate conditions with the aim of identifying conditions suitable as a starting point for the production of diffraction quality crystals. Generally, condition screening is performed in 96-well plates. While previous studies have examined the effects of protein construct, protein purity, or crystallisation condition ingredients on protein crystallisation, few have examined the effect of the crystallisation plate

Visualizing 1D Regression

Regression is the study of the conditional distribution of the response y given the predictors x. In a 1D regression, y is independent of x given a single linear combination βTx of the predictors. Special cases of 1D regression include multiple linear regression, binary regression and generalized linear models. If a good estimate ˆb of some non-zero multiple cβ of β can be constructed, then the 1D regression can be visualized with a scatterplot of ˆbTx versus y. A resistant method for estimating cβ is presented along with applications

Optimizing substitution matrix choice and gap parameters for sequence alignment

<p>Abstract</p> <p>Background</p> <p>While substitution matrices can readily be computed from reference alignments, it is challenging to compute optimal or approximately optimal gap penalties. It is also not well understood which substitution matrices are the most effective when alignment accuracy is the goal rather than homolog recognition. Here a new parameter optimization procedure, POP, is described and applied to the problems of optimizing gap penalties and selecting substitution matrices for pair-wise global protein alignments.</p> <p>Results</p> <p>POP is compared to a recent method due to Kim and Kececioglu and found to achieve from 0.2% to 1.3% higher accuracies on pair-wise benchmarks extracted from BALIBASE. The VTML matrix series is shown to be the most accurate on several global pair-wise alignment benchmarks, with VTML200 giving best or close to the best performance in all tests. BLOSUM matrices are found to be slightly inferior, even with the marginal improvements in the bug-fixed RBLOSUM series. The PAM series is significantly worse, giving accuracies typically 2% less than VTML. Integer rounding is found to cause slight degradations in accuracy. No evidence is found that selecting a matrix based on sequence divergence improves accuracy, suggesting that the use of this heuristic in CLUSTALW may be ineffective. Using VTML200 is found to improve the accuracy of CLUSTALW by 8% on BALIBASE and 5% on PREFAB.</p> <p>Conclusion</p> <p>The hypothesis that more accurate alignments of distantly related sequences may be achieved using low-identity matrices is shown to be false for commonly used matrix types. Source code and test data is freely available from the author's web site at <url>http://www.drive5.com/pop</url>.</p

An Integrated Approach for the Analysis of Biological Pathways using Mixed Models

Gene class, ontology, or pathway testing analysis has become increasingly popular in microarray data analysis. Such approaches allow the integration of gene annotation databases, such as Gene Ontology and KEGG Pathway, to formally test for subtle but coordinated changes at a system level. Higher power in gene class testing is gained by combining weak signals from a number of individual genes in each pathway. We propose an alternative approach for gene-class testing based on mixed models, a class of statistical models that

Religious affiliation modulates weekly cycles of cropland burning in Sub-Saharan Africa

Research ArticleVegetation burning is a common land management practice in Africa, where fire is used for hunting, livestock husbandry, pest control, food gathering, cropland fertilization, and wildfire prevention. Given such strong anthropogenic control of fire, we tested the hypotheses that fire activity displays weekly cycles, and that the week day with the fewest fires depends on regionally predominant religious affiliation.We also analyzed the effect of land use (anthrome) on weekly fire cycle significance. Fire density (fire counts.km-2) observed per week day in each region was modeled using a negative binomial regression model, with fire counts as response variable, region area as offset and a structured random effect to account for spatial dependence. Anthrome (settled, cropland, natural, rangeland), religion (Christian, Muslim, mixed) week day, and their 2-way and 3-way interactions were used as independent variables. Models were also built separately for each anthrome, relating regional fire density with week day and religious affiliation. Analysis revealed a significant interaction between religion and week day, i.e. regions with different religious affiliation (Christian, Muslim) display distinct weekly cycles of burning. However, the religion vs. week day interaction only is significant for croplands, i.e. fire activity in African croplands is significantly lower on Sunday in Christian regions and on Friday in Muslim regions. Magnitude of fire activity does not differ significantly among week days in rangelands and in natural areas, where fire use is under less strict control than in croplands. These findings can contribute towards improved specification of ignition patterns in regional/global vegetation fire models, and may lead to more accurate meteorological and chemical weather forecastinginfo:eu-repo/semantics/publishedVersio

Five views of a secret: does cognition change during middle adulthood?

This study examined five aspects of change (or stability) in cognitive abilities in middle adulthood across a 12-year period. Data come from the Interdisciplinary Study on Adult Development. The sample consisted of N = 346 adults (43.8 years on average, 48.6% female). In total, 11 cognitive tests were administered to assess fluid and crystallized intelligence, memory, and processing speed. In a first series of analyses, strong measurement invariance was established. Subsequently, structural stability, differential stability, stability of divergence, absolute stability, and the generality of changes were examined. Factor covariances were shown to be equal across time, implying structural stability. Stability coefficients were around .90 for fluid and crystallized intelligence, and speed, indicating high, yet not perfect differential stability. The coefficient for memory was .58. Only in processing speed the variance increased across time, indicating heterogeneity in interindividual development. Significant mean-level changes emerged, with an increase in crystallized intelligence and decline in the other three abilities. A number of correlations among changes in cognitive abilities were significant, implying that cognitive change