51 research outputs found

    From theory to 'measurement' in complex interventions: methodological lessons from the development of an e-health normalisation instrument

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    <b>Background</b> Although empirical and theoretical understanding of processes of implementation in health care is advancing, translation of theory into structured measures that capture the complex interplay between interventions, individuals and context remain limited. This paper aimed to (1) describe the process and outcome of a project to develop a theory-based instrument for measuring implementation processes relating to e-health interventions; and (2) identify key issues and methodological challenges for advancing work in this field.<p></p> <b>Methods</b> A 30-item instrument (Technology Adoption Readiness Scale (TARS)) for measuring normalisation processes in the context of e-health service interventions was developed on the basis on Normalization Process Theory (NPT). NPT focuses on how new practices become routinely embedded within social contexts. The instrument was pre-tested in two health care settings in which e-health (electronic facilitation of healthcare decision-making and practice) was used by health care professionals.<p></p> <b>Results</b> The developed instrument was pre-tested in two professional samples (N = 46; N = 231). Ratings of items representing normalisation 'processes' were significantly related to staff members' perceptions of whether or not e-health had become 'routine'. Key methodological challenges are discussed in relation to: translating multi-component theoretical constructs into simple questions; developing and choosing appropriate outcome measures; conducting multiple-stakeholder assessments; instrument and question framing; and more general issues for instrument development in practice contexts.<p></p> <b>Conclusions</b> To develop theory-derived measures of implementation process for progressing research in this field, four key recommendations are made relating to (1) greater attention to underlying theoretical assumptions and extent of translation work required; (2) the need for appropriate but flexible approaches to outcomes measurement; (3) representation of multiple perspectives and collaborative nature of work; and (4) emphasis on generic measurement approaches that can be flexibly tailored to particular contexts of study

    Discriminating neutrino mass models using Type II seesaw formula

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    In this paper we propose a kind of natural selection which can discriminate the three possible neutrino mass models, namely the degenerate, inverted hierarchical and normal hierarchical models, using the framework of Type II seesaw formula. We arrive at a conclusion that the inverted hierarchical model appears to be most favourable whereas the normal hierarchical model follows next to it. The degenerate model is found to be most unfavourable. We use the hypothesis that those neutrino mass models in which Type I seesaw term dominates over the Type II left-handed Higgs triplet term are favoured to survive in nature.Comment: No change in the results, a few references added, some changes in Type[IIB] calculation

    A Meta-analysis of Gene Expression Signatures of Blood Pressure and Hypertension

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    Genome-wide association studies (GWAS) have uncovered numerous genetic variants (SNPs) that are associated with blood pressure (BP). Genetic variants may lead to BP changes by acting on intermediate molecular phenotypes such as coded protein sequence or gene expression, which in turn affect BP variability. Therefore, characterizing genes whose expression is associated with BP may reveal cellular processes involved in BP regulation and uncover how transcripts mediate genetic and environmental effects on BP variability. A meta-analysis of results from six studies of global gene expression profiles of BP and hypertension in whole blood was performed in 7017 individuals who were not receiving antihypertensive drug treatment. We identified 34 genes that were differentially expressed in relation to BP (Bonferroni-corrected p<0.05). Among these genes, FOS and PTGS2 have been previously reported to be involved in BP-related processes; the others are novel. The top BP signature genes in aggregate explain 5%–9% of inter-individual variance in BP. Of note, rs3184504 in SH2B3, which was also reported in GWAS to be associated with BP, was found to be a trans regulator of the expression of 6 of the transcripts we found to be associated with BP (FOS, MYADM, PP1R15A, TAGAP, S100A10, and FGBP2). Gene set enrichment analysis suggested that the BP-related global gene expression changes include genes involved in inflammatory response and apoptosis pathways. Our study provides new insights into molecular mechanisms underlying BP regulation, and suggests novel transcriptomic markers for the treatment and prevention of hypertension

    Genetic associations at 53 loci highlight cell types and biological pathways relevant for kidney function.

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    Reduced glomerular filtration rate defines chronic kidney disease and is associated with cardiovascular and all-cause mortality. We conducted a meta-analysis of genome-wide association studies for estimated glomerular filtration rate (eGFR), combining data across 133,413 individuals with replication in up to 42,166 individuals. We identify 24 new and confirm 29 previously identified loci. Of these 53 loci, 19 associate with eGFR among individuals with diabetes. Using bioinformatics, we show that identified genes at eGFR loci are enriched for expression in kidney tissues and in pathways relevant for kidney development and transmembrane transporter activity, kidney structure, and regulation of glucose metabolism. Chromatin state mapping and DNase I hypersensitivity analyses across adult tissues demonstrate preferential mapping of associated variants to regulatory regions in kidney but not extra-renal tissues. These findings suggest that genetic determinants of eGFR are mediated largely through direct effects within the kidney and highlight important cell types and biological pathways

    Atrial fibrillation genetic risk differentiates cardioembolic stroke from other stroke subtypes

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    AbstractObjectiveWe sought to assess whether genetic risk factors for atrial fibrillation can explain cardioembolic stroke risk.MethodsWe evaluated genetic correlations between a prior genetic study of AF and AF in the presence of cardioembolic stroke using genome-wide genotypes from the Stroke Genetics Network (N = 3,190 AF cases, 3,000 cardioembolic stroke cases, and 28,026 referents). We tested whether a previously-validated AF polygenic risk score (PRS) associated with cardioembolic and other stroke subtypes after accounting for AF clinical risk factors.ResultsWe observed strong correlation between previously reported genetic risk for AF, AF in the presence of stroke, and cardioembolic stroke (Pearson’s r=0.77 and 0.76, respectively, across SNPs with p &lt; 4.4 × 10−4 in the prior AF meta-analysis). An AF PRS, adjusted for clinical AF risk factors, was associated with cardioembolic stroke (odds ratio (OR) per standard deviation (sd) = 1.40, p = 1.45×10−48), explaining ∼20% of the heritable component of cardioembolic stroke risk. The AF PRS was also associated with stroke of undetermined cause (OR per sd = 1.07, p = 0.004), but no other primary stroke subtypes (all p &gt; 0.1).ConclusionsGenetic risk for AF is associated with cardioembolic stroke, independent of clinical risk factors. Studies are warranted to determine whether AF genetic risk can serve as a biomarker for strokes caused by AF.</jats:sec
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