533 research outputs found

    Post-consent assessment of dental subjects' understanding of informed consent in oral health research in Nigeria

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    Abstract Background Research participants may not adequately understand the research in which they agree to enroll. This could be due to a myriad of factors. Such a missing link in the informed consent process contravenes the requirement for an "informed" consent prior to the commencement of research. This study assessed the post consent understanding of Nigerian study participants of the oral health research they were invited to join. Methods A descriptive cross sectional study with research participants who had just consented to one of three ongoing research studies on oral health. Study sites included two centers, one in the northern and one in the southern part of Nigeria. Data were collected using a combination of quantitative and qualitative methods. Results A total of 113 research participants were interviewed. The southern part of the country had 58 respondents with the north having 55. The age range was 21 – 80 years. Mean age was 46.1 (SD16.3). The sample was predominantly male (69.9%) and married (64.6%). There was poor understanding of some key elements of the informed consent process such as involvement in research, benefits, contacts, confidentiality and voluntariness. Some identified factors potentially compromising understanding were poverty, illiteracy, therapeutic misconception and confusion about the dual roles of the Dentist and the researcher. Conclusion The participants recruited into the oral health research in Nigeria did not adequately understand the studies they were invited to join nor do they understand their rights as research participants. Measures should be taken to include research bioethics into the curricula of Dental schools and to train oral health researchers in the country on research ethics.</p

    Organizational readiness to change assessment (ORCA): Development of an instrument based on the Promoting Action on Research in Health Services (PARIHS) framework

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    <p>Abstract</p> <p>Background</p> <p>The Promoting Action on Research Implementation in Health Services, or PARIHS, framework is a theoretical framework widely promoted as a guide to implement evidence-based clinical practices. However, it has as yet no pool of validated measurement instruments that operationalize the constructs defined in the framework. The present article introduces an Organizational Readiness to Change Assessment instrument (ORCA), organized according to the core elements and sub-elements of the PARIHS framework, and reports on initial validation.</p> <p>Methods</p> <p>We conducted scale reliability and factor analyses on cross-sectional, secondary data from three quality improvement projects (n = 80) conducted in the Veterans Health Administration. In each project, identical 77-item ORCA instruments were administered to one or more staff from each facility involved in quality improvement projects. Items were organized into 19 subscales and three primary scales corresponding to the core elements of the PARIHS framework: (1) Strength and extent of evidence for the clinical practice changes represented by the QI program, assessed with four subscales, (2) Quality of the organizational context for the QI program, assessed with six subscales, and (3) Capacity for internal facilitation of the QI program, assessed with nine subscales.</p> <p>Results</p> <p>Cronbach's alpha for scale reliability were 0.74, 0.85 and 0.95 for the evidence, context and facilitation scales, respectively. The evidence scale and its three constituent subscales failed to meet the conventional threshold of 0.80 for reliability, and three individual items were eliminated from evidence subscales following reliability testing. In exploratory factor analysis, three factors were retained. Seven of the nine facilitation subscales loaded onto the first factor; five of the six context subscales loaded onto the second factor; and the three evidence subscales loaded on the third factor. Two subscales failed to load significantly on any factor. One measured resources in general (from the context scale), and one clinical champion role (from the facilitation scale).</p> <p>Conclusion</p> <p>We find general support for the reliability and factor structure of the ORCA. However, there was poor reliability among measures of evidence, and factor analysis results for measures of general resources and clinical champion role did not conform to the PARIHS framework. Additional validation is needed, including criterion validation.</p

    The association between clinical integration of care and transfer of veterans with acute coronary syndromes from primary care VHA hospitals

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    BACKGROUND: Few studies report on the effect of organizational factors facilitating transfer between primary and tertiary care hospitals either within an integrated health care system or outside it. In this paper, we report on the relationship between degree of clinical integration of cardiology services and transfer rates of acute coronary syndrome (ACS) patients from primary to tertiary hospitals within and outside the Veterans Health Administration (VHA) system. METHODS: Prospective cohort study. Transfer rates were obtained for all patients with ACS diagnoses admitted to 12 primary VHA hospitals between 1998 and 1999. Binary variables measuring clinical integration were constructed for each primary VHA hospital reflecting: presence of on-site VHA cardiologist; referral coordinator at the associated tertiary VHA hospital; and/or referral coordinator at the primary VHA hospital. We assessed the association between the integration variables and overall transfer from primary to tertiary hospitals, using random effects logistic regression, controlling for clustering at two levels and adjusting for patient characteristics. RESULTS: Three of twelve hospitals had a VHA cardiologist on site, six had a referral coordinator at the tertiary VHA hospital, and four had a referral coordinator at the primary hospital. Presence of a VHA staff cardiologist on site and a referral coordinator at the tertiary VHA hospital decreased the likelihood of any transfer (OR 0.45, 95% CI 0.27–0.77, and 0.46, p = 0.002, CI 0.27–0.78). Conversely, having a referral coordinator at the primary VHA hospital increased the likelihood of transfer (OR 6.28, CI 2.92–13.48). CONCLUSIONS: Elements of clinical integration are associated with transfer, an important process in the care of ACS patients. In promoting optimal patient care, clinical integration factors should be considered in addition to patient characteristics

    Development of the interRAI Pressure Ulcer Risk Scale (PURS) for use in long-term care and home care settings

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    <p>Abstract</p> <p>Background</p> <p>In long-term care (LTC) homes in the province of Ontario, implementation of the Minimum Data Set (MDS) assessment and The Braden Scale for predicting pressure ulcer risk were occurring simultaneously. The purpose of this study was, using available data sources, to develop a bedside MDS-based scale to identify individuals under care at various levels of risk for developing pressure ulcers in order to facilitate targeting risk factors for prevention.</p> <p>Methods</p> <p>Data for developing the interRAI Pressure Ulcer Risk Scale (interRAI PURS) were available from 2 Ontario sources: three LTC homes with 257 residents assessed during the same time frame with the MDS and Braden Scale for Predicting Pressure Sore Risk, and eighty-nine Ontario LTC homes with 12,896 residents with baseline/reassessment MDS data (median time 91 days), between 2005-2007. All assessments were done by trained clinical staff, and baseline assessments were restricted to those with no recorded pressure ulcer. MDS baseline/reassessment samples used in further testing included 13,062 patients of Ontario Complex Continuing Care Hospitals (CCC) and 73,183 Ontario long-stay home care (HC) clients.</p> <p>Results</p> <p>A data-informed Braden Scale cross-walk scale using MDS items was devised from the 3-facility dataset, and tested in the larger longitudinal LTC homes data for its association with a future new pressure ulcer, giving a c-statistic of 0.676. Informed by this, LTC homes data along with evidence from the clinical literature was used to create an alternate-form 7-item additive scale, the interRAI PURS, with good distributional characteristics and c-statistic of 0.708. Testing of the scale in CCC and HC longitudinal data showed strong association with development of a new pressure ulcer.</p> <p>Conclusions</p> <p>interRAI PURS differentiates risk of developing pressure ulcers among facility-based residents and home care recipients. As an output from an MDS assessment, it eliminates duplicated effort required for separate pressure ulcer risk scoring. Moreover, it can be done manually at the bedside during critical early days in an admission when the full MDS has yet to be completed. It can be calculated with established MDS instruments as well as with the newer interRAI suite instruments designed to follow persons across various care settings (interRAI Long-Term Care Facilities, interRAI Home Care, interRAI Palliative Care).</p

    Personality Predicts Mortality Risk: An Integrative Data Analysis of 15 International Longitudinal Studies

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    This study examined the Big Five personality traits as predictors of mortality risk, and smoking as a mediator of that association. Replication was built into the fabric of our design: we used a Coordinated Analysis with 15 international datasets, representing 44,094 participants. We found that high neuroticism and low conscientiousness, extraversion, and agreeableness were consistent predictors of mortality across studies. Smoking had a small mediating effect for neuroticism. Country and baseline age explained variation in effects: studies with older baseline age showed a pattern of protective effects (HR<1.00) for openness, and U.S. studies showed a pattern of protective effects for extraversion. This study demonstrated coordinated analysis as a powerful approach to enhance replicability and reproducibility, especially for aging-related longitudinal research.Funding support for this project was provided by the National Institute on Aging: P01-AG043362 (Integrative Analysis of Longitudinal Studies of Aging (IALSA), [Scott M. Hofer (PI)]), and Daniel K. Mroczek (CoInvestigator and Project Leader of the IALSA Personality & Health Project, as well as R01-AG018436 [Personality & Well-Being Trajectories in Adulthood, Daniel K. Mroczek, PI])

    New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk.

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    Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes

    Small group interventions for children aged 5-9 years old with mathematical learning difficulties

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    The research related to educational interventions for children with mathematical learning difficulties has been increasing steadily. In this chapter I focus on small group interventions for children aged 5–9 years old with learning difficulties in mathematics. First, I describe the important issues: (1) who are the children having problems in mathematics, (2) what do we mean with (special) education intervention, (3) what does Responsiveness to Intervention mean, and (4) what intervention features have been found effective for children aged 5–9 years with learning difficulties in mathematics. Then, I describe the research and developmental work that has been done in Finland on designing web services which provide evidence-based information and materials for educators. The two web services are LukiMat and ThinkMath. Together, these two web services include the knowledge base, assessment batteries and intervention tools to be used in relation to mathematical learning difficulties in the age group 5–9 years.Peer reviewe

    Genetic Variation Stimulated by Epigenetic Modification

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    Homologous recombination is essential for maintaining genomic integrity. A common repair mechanism, it uses a homologous or homeologous donor as a template for repair of a damaged target gene. Such repair must be regulated, both to identify appropriate donors for repair, and to avoid excess or inappropriate recombination. We show that modifications of donor chromatin structure can promote homology-directed repair. These experiments demonstrate that either the activator VP16 or the histone chaperone, HIRA, accelerated gene conversion approximately 10-fold when tethered within the donor array for Ig gene conversion in the chicken B cell line DT40. VP16 greatly increased levels of acetylated histones H3 and H4, while tethered HIRA did not affect histone acetylation, but caused an increase in local nucleosome density and levels of histone H3.3. Thus, epigenetic modification can stimulate genetic variation. The evidence that distinct activating modifications can promote similar functional outcomes suggests that a variety of chromatin changes may regulate homologous recombination, and that disregulation of epigenetic marks may have deleterious genetic consequences

    Malaria in Africa: Vector Species' Niche Models and Relative Risk Maps

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    A central theoretical goal of epidemiology is the construction of spatial models of disease prevalence and risk, including maps for the potential spread of infectious disease. We provide three continent-wide maps representing the relative risk of malaria in Africa based on ecological niche models of vector species and risk analysis at a spatial resolution of 1 arc-minute (9 185 275 cells of approximately 4 sq km). Using a maximum entropy method we construct niche models for 10 malaria vector species based on species occurrence records since 1980, 19 climatic variables, altitude, and land cover data (in 14 classes). For seven vectors (Anopheles coustani, A. funestus, A. melas, A. merus, A. moucheti, A. nili, and A. paludis) these are the first published niche models. We predict that Central Africa has poor habitat for both A. arabiensis and A. gambiae, and that A. quadriannulatus and A. arabiensis have restricted habitats in Southern Africa as claimed by field experts in criticism of previous models. The results of the niche models are incorporated into three relative risk models which assume different ecological interactions between vector species. The “additive” model assumes no interaction; the “minimax” model assumes maximum relative risk due to any vector in a cell; and the “competitive exclusion” model assumes the relative risk that arises from the most suitable vector for a cell. All models include variable anthrophilicity of vectors and spatial variation in human population density. Relative risk maps are produced from these models. All models predict that human population density is the critical factor determining malaria risk. Our method of constructing relative risk maps is equally general. We discuss the limits of the relative risk maps reported here, and the additional data that are required for their improvement. The protocol developed here can be used for any other vector-borne disease
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