1,886 research outputs found

    Understanding the introduction and use of a mobile device-supported health information system in Nigeria

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    Copyright @ 2014 The Authors.This paper presents an in-depth analysis of efforts to introduce a mobile health information system in Nigeria as part of a development initiative aimed at improving maternal and child health. Specifically, it examines the use of mobile devices to facilitate maternal health information accessibility and exchange among health practitioners in order to reducing maternal, newborn and child mortality. Further, it also looks at the challenges raised while introducing mobile devices into work practices in the healthcare sector. The study adopts a case study approach, relying on semi-structured interviews and document analysis as its main methods for collecting data. The specific case examined is a mobile phone-based information system introduced to support a national government effort in Nigeria, known as the midwives service scheme. The findings of this study show that this integrated approach of using mobile phones to support (health) information systems has vast potential; for instance increasing the timeliness of (health) data available to stakeholders for monitoring and planning purposes. However, we also find that over time, attaining the potential of development efforts such as this remains difficult as initiatives involving the use of mobile devices is not just about getting the technical aspect right. It is equally dependent on deep seated social-cultural influences such as poor political and financial commitment. These two mutually reinforcing influences have been identified in this study as significant impediments to efforts of this kind. Therefore, this paper argues for, first a strong political commitment across all levels of government whereby their words are backed with action. Second it is important that the government maintains financial integrity by releasing the funds budgeted to support the smooth running of these efforts, for such initiatives to thrive and ultimately contribute to development

    Determining the Efficacy of Predicting Beef Tenderness Using Proteins from Purge

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    Objective: To determine if proteins from purge can predict tenderness at different aging points as a nondestructive method

    Scraping the Social? Issues in live social research

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    What makes scraping methodologically interesting for social and cultural research? This paper seeks to contribute to debates about digital social research by exploring how a ‘medium-specific’ technique for online data capture may be rendered analytically productive for social research. As a device that is currently being imported into social research, scraping has the capacity to re-structure social research, and this in at least two ways. Firstly, as a technique that is not native to social research, scraping risks to introduce ‘alien’ methodological assumptions into social research (such as an pre-occupation with freshness). Secondly, to scrape is to risk importing into our inquiry categories that are prevalent in the social practices enabled by the media: scraping makes available already formatted data for social research. Scraped data, and online social data more generally, tend to come with ‘external’ analytics already built-in. This circumstance is often approached as a ‘problem’ with online data capture, but we propose it may be turned into virtue, insofar as data formats that have currency in the areas under scrutiny may serve as a source of social data themselves. Scraping, we propose, makes it possible to render traffic between the object and process of social research analytically productive. It enables a form of ‘real-time’ social research, in which the formats and life cycles of online data may lend structure to the analytic objects and findings of social research. By way of a conclusion, we demonstrate this point in an exercise of online issue profiling, and more particularly, by relying on Twitter to profile the issue of ‘austerity’. Here we distinguish between two forms of real-time research, those dedicated to monitoring live content (which terms are current?) and those concerned with analysing the liveliness of issues (which topics are happening?)

    Doctors are inconsistent in estimating survival after CPR and are not using such predictions consistently in determining DNACPR decisions

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    Background: It is unclear whether doctors base their resuscitation decisions solely on their perceived outcome. Through the use of theoretical scenarios, we aimed to examine the ‘do not attempt cardiopulmonary resuscitation’ (DNACPR) decision-making. Methods: A questionnaire survey was sent to consultants and specialty trainees across two Norfolk (UK) hospitals during December 2013. The survey included demographic questions and six clinical scenarios with varying prognosis. Participants were asked if they would resuscitate the patient or not. Identical scenarios were then shown in a different order and doctors were asked to quantify patients’ estimated chance of survival. Results: A total of 137 individuals (mean age 41 years (SD 7.9%)) responded. The response rate was 69%. Approximately 60% were consultants. We found considerable variation in clinician estimates of median chance of survival. In three out of six of our scenarios, the survival estimated varied from <1% to 95%. There was a statistically significant difference identified in the estimated median survival between those clinicians who would or would not resuscitate in four of the six scenarios presented. Conclusion: This study has highlighted the wide variation between clinicians in their estimates of likely survival and little concordance between clinicians over their resuscitation decisions. The diversity in clinician decision-making should be explored further

    Secret Codes: The Hidden Curriculum of Semantic Web Technologies

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    There is a long tradition in education of examination of the hidden curriculum, those elements which are implicit or tacit to the formal goals of education. This article draws upon that tradition to open up for investigation the hidden curriculum and assumptions about students and knowledge that are embedded in the coding undertaken to facilitate learning through information technologies, and emerging &lsquo;semantic technologies&rsquo; in particular. Drawing upon an empirical study of case-based pedagogy in higher education, we examine the ways in which code becomes an actor in both enabling and constraining knowledge, reasoning, representation and students. The article argues that how this occurs, and to what effect, is largely left unexamined and becomes part of the hidden curriculum of electronically mediated learning that can be more explicitly examined by positioning technologies in general, and code in particular, as actors rather than tools. This points to a significant research agenda in technology enhanced learning

    Research Project as Boundary Object: negotiating the conceptual design of a tool for International Development

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    This paper reflects on the relationship between who one designs for and what one designs in the unstructured space of designing for political change; in particular, for supporting “International Development” with ICT. We look at an interdisciplinary research project with goals and funding, but no clearly defined beneficiary group at start, and how amorphousness contributed to impact. The reported project researched a bridging tool to connect producers with consumers across global contexts and show players in the supply chain and their circumstances. We explore how both the nature of the research and the tool’s function became contested as work progressed. To tell this tale, we invoke the idea of boundary objects and the value of tacking back and forth between elastic meanings of the project’s artefacts and processes. We examine the project’s role in India, Chile and other arenas to draw out ways that it functioned as a catalyst and how absence of committed design choices acted as an unexpected strength in reaching its goals

    Using MCDA to generate and interpret evidence to inform local government investment in public health

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    Smoking is the single biggest cause of preventable death in the Uited Kingdom (UK) and is a major cause of coronary heart disease, some cancers, and respiratory disease, including chronic obstructive pulmonary disease. At the time of initiating the project, smoking prevalence had not changed across four local government areas in South Yorkshire for some years. Most spending had been focussed on helping people quit, an intervention where there was clear evidence of effectiveness. A number of changes occurred in public health structures and targets, requiring a reappraisal of the range of interventions offered. This was challenging due to a lack of clear evidence for some of the areas’ alternative interventions. The aim of this paper is to describe the use of a multi-criteria decision analysis (MCDA) approach to support the health priority setting in local authorities to reduce smoking prevalence. There were three phases to this process: (1) problem structuring; (2) the multiple criteria decision analysis; (3) and using the MCDA results to influence decision making at the local government level. The MCDA approach was used to collate information in a consistent and transparent manner, using expert, stakeholder and public opinion to fill known gaps in evidence. Fifteen interventions (such as stop smoking support services, smoke-free spaces, communication and marketing exercises, and increased investment in enforcement) were ranked across eight criteria (relating to reductions in prevalence across relevant groups, as well as aspects relating to equity and feasibility), allowing a range of relevant concerns to be incorporated. Subsequent steps were taken to translate the results of this stage into workable policy options. The results differed significantly from current practice. Sensitivity analysis showed that the findings were robust to changes in preference weights. These results informed subsequent changes to the interventions offered across the four boroughs. The ability of MCDA techniques to incorporate data and both qualitative and quantitative judgements in a formal manner mean that they are well suited to support public health decision making, where evidence is often only partially available and many policies are value driven. MCDA methods, if used, should be chosen carefully based on their resource/time constraints, scientific validity, and the significance and broader context of the decision problem.This is the final version of the article. It first appeared from Springer via http://dx.doi.org/10.1007/s40070-016-0059-

    Evidence for Shared Genetic Aetiology Between Schizophrenia, Cardiometabolic, and Inflammation-Related Traits: Genetic Correlation and Colocalization Analyses.

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    Funder: MQ: Transforming Mental Health; Grant(s): MQDS17/40BACKGROUND: Schizophrenia commonly co-occurs with cardiometabolic and inflammation-related traits. It is unclear to what extent the comorbidity could be explained by shared genetic aetiology. METHODS: We used GWAS data to estimate shared genetic aetiology between schizophrenia, cardiometabolic, and inflammation-related traits: fasting insulin (FI), fasting glucose, glycated haemoglobin, glucose tolerance, type 2 diabetes (T2D), lipids, body mass index (BMI), coronary artery disease (CAD), and C-reactive protein (CRP). We examined genome-wide correlation using linkage disequilibrium score regression (LDSC); stratified by minor-allele frequency using genetic covariance analyzer (GNOVA); then refined to locus-level using heritability estimation from summary statistics (ρ-HESS). Regions with local correlation were used in hypothesis prioritization multi-trait colocalization to examine for colocalisation, implying common genetic aetiology. RESULTS: We found evidence for weak genome-wide negative correlation of schizophrenia with T2D (rg = -0.07; 95% C.I., -0.03,0.12; P = .002) and BMI (rg = -0.09; 95% C.I., -0.06, -0.12; P = 1.83 × 10-5). We found a trend of evidence for positive genetic correlation between schizophrenia and cardiometabolic traits confined to lower-frequency variants. This was underpinned by 85 regions of locus-level correlation with evidence of opposing mechanisms. Ten loci showed strong evidence of colocalization. Four of those (rs6265 (BDNF); rs8192675 (SLC2A2); rs3800229 (FOXO3); rs17514846 (FURIN)) are implicated in brain-derived neurotrophic factor (BDNF)-related pathways. CONCLUSIONS: LDSC may lead to downwardly-biased genetic correlation estimates between schizophrenia, cardiometabolic, and inflammation-related traits. Common genetic aetiology for these traits could be confined to lower-frequency common variants and involve opposing mechanisms. Genes related to BDNF and glucose transport amongst others may partly explain the comorbidity between schizophrenia and cardiometabolic disorders
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