Association between education and quality of diabetes care in Switzerland

PURPOSE: Low socioeconomic status is associated with higher prevalence of diabetes, worse outcomes, and worse quality of care. We explored the relationship between education, as a measure of socioeconomic status, and quality of care in the Swiss context. PATIENTS AND METHODS: Data were drawn from a population-based survey of 519 adults with diabetes during fall 2011 and summer 2012 in a canton of Switzerland. We assessed patients and diabetes characteristics. Eleven indicators of quality of care were considered (six of process and five of outcomes of care). After bivariate analyses, regression analyses adjusted for age, sex, and diabetic complications were performed to assess the relationship between education and quality of care. RESULTS: Of 11 quality-of-care indicators, three were significantly associated with education: funduscopy (patients with tertiary versus primary education were more likely to get the exam: odds ratio, 1.8; 95% confidence interval [CI], 1.004-3.3) and two indicators of health-related quality of life (patients with tertiary versus primary education reported better health-related quality of life: Audit of Diabetes-Dependent Quality of Life: β=0.6 [95% CI, 0.2-0.97]; SF-12 mean physical component summary score: β=3.6 [95% CI, 0.9-6.4]). CONCLUSION: Our results suggest the presence of educational inequalities in quality of diabetes care. These findings may help health professionals focus on individuals with increased needs to decrease health inequalities.

A review of malaria vaccine clinical projects based on the WHO rainbow table.

Development and Phase 3 testing of the most advanced malaria vaccine, RTS,S/AS01, indicates that malaria vaccine R&D is moving into a new phase. Field trials of several research malaria vaccines have also confirmed that it is possible to impact the host-parasite relationship through vaccine-induced immune responses to multiple antigenic targets using different platforms. Other approaches have been appropriately tested but turned out to be disappointing after clinical evaluation. As the malaria community considers the potential role of a first-generation malaria vaccine in malaria control efforts, it is an apposite time to carefully document terminated and ongoing malaria vaccine research projects so that lessons learned can be applied to increase the chances of success for second-generation malaria vaccines over the next 10 years. The most comprehensive resource of malaria vaccine projects is a spreadsheet compiled by WHO thanks to the input from funding agencies, sponsors and investigators worldwide. This spreadsheet, available from WHO's website, is known as "the rainbow table". By summarizing the published and some unpublished information available for each project on the rainbow table, the most comprehensive review of malaria vaccine projects to be published in the last several years is provided below.

Patterns of Subject Mix in Higher Education Institutions : A First Empirical Analysis Using the AQUAMETH Database

Teaching and research are organised differently between subject domains: attempts to construct typologies of higher education institutions, however, often do not include quantitative indicators concerning subject mix which would allow systematic comparisons of large numbers of higher education institutions among different countries, as the availability of data for such indicators is limited. In this paper, we present an exploratory approach for the construction of such indicators. The database constructed in the AQUAMETH project, which includes also data disaggregated at the disciplinary level, is explored with the aim of understanding patterns of subject mix. For six European countries, an exploratory and descriptive analysis of staff composition divided in four large domains (medical sciences, engineering and technology, natural sciences and social sciences and humanities) is performed, which leads to a classification distinguishing between specialist and generalist institutions. Among the latter, a further distinction is made based on the presence or absence of a medical department. Preliminary exploration of this classification and its comparison with other indicators show the influence of long term dynamics on the subject mix of individual higher education institutions, but also underline disciplinary differences, for example regarding student to staff ratios, as well as national patterns, for example regarding the number of PhD degrees per 100 undergraduate students. Despite its many limitations, this exploratory approach allows defining a classification of higher education institutions that accounts for a large share of differences between the analysed higher education institutions.

Contribution of physical education to overall physical activity.

For many children, physical activity (PA) during physical education (PE) lessons provides an important opportunity for being physically active. Although PA during PE has been shown to be low, little is known about the contribution of PA during PE to overall PA. The aim was therefore to assess children's PA during PE and to determine the contribution of PE to overall PA with special focus on overweight children. Accelerometer measurements were done in 676 children (9.3 ± 2.1 years) over 4-7 days in 59 randomly selected classes. Moderate-and-vigorous PA (MVPA; ≥ 2000 counts/min) during PE (MVPA(PE) ), overall MVPA per day (MVPA(DAY) ), and a comparison of days with and without PE were calculated by a regression model with gender, grade, and weight status (normal vs overweight) as fixed factors and class as a random factor. Children spent 32.8 ± 15.1% of PE time in MVPA. Weight status was not associated to MVPA(PE) . MVPA(PE) accounted for 16.8 ± 8.5% of MVPA(DAY) , and 17.5 ± 8.2% in overweight children. All children were more active on days with PE than on days without PE (differences: 16.1 ± 29.0 min of MVPA(DAY) ; P ≤ 0.001; 13.7 ± 28.0 min for overweight children). Although MVPA(PE) was low, PE played a considerable role in providing PA and was not compensated by reducing extracurricular MVPA.

Association between HIV status and HIV knowledge in the population attending Non-Governmental Organizations to perform the rapid HIV test in Catalonia

Human Immunodeficiency Virus continues to be a pandemic. Spain is one of the European countries with the highest incidence of HIV. Within Catalonia, Spain many projects have been implemented with the intention of improving HIV knowledge and lowering the incidence. HIV knowledge is also known to have a positive effect on lowering stigma and discrimination of the people living with HIV. However, few studies study the distribution of HIV knowledge and its association to HIV status, age, sex, geographical zone of origin and level of education within the same study. Objectives: To identify if HIV knowledge is associated with HIV status, age, sex, geographical zone of origin and level of education. Method: Quantitative, cross-sectional, centre-based study comprising of people receiving an HIV test in Catalonia, Spain. Data will be collected from the 11 HIV Non-Governmental Organisations in Catalonia, Spain. The Brief HIV Knowledge Scale will be used to assess HIV knowledge; information from the HIV test session will be used to assess HIV status, age, sex, geographic zone of origin and level of education. The association between HIV knowledge and the afore mentioned variables will then be calculated.

Development and validation of a risk score predicting substantial weight gain over 5 years in middle-aged European men and women.

BACKGROUND Identifying individuals at high risk of excess weight gain may help targeting prevention efforts at those at risk of various metabolic diseases associated with weight gain. Our aim was to develop a risk score to identify these individuals and validate it in an external population. METHODS We used lifestyle and nutritional data from 53°758 individuals followed for a median of 5.4 years from six centers of the European Prospective Investigation into Cancer and Nutrition (EPIC) to develop a risk score to predict substantial weight gain (SWG) for the next 5 years (derivation sample). Assuming linear weight gain, SWG was defined as gaining ≥ 10% of baseline weight during follow-up. Proportional hazards models were used to identify significant predictors of SWG separately by EPIC center. Regression coefficients of predictors were pooled using random-effects meta-analysis. Pooled coefficients were used to assign weights to each predictor. The risk score was calculated as a linear combination of the predictors. External validity of the score was evaluated in nine other centers of the EPIC study (validation sample). RESULTS Our final model included age, sex, baseline weight, level of education, baseline smoking, sports activity, alcohol use, and intake of six food groups. The model's discriminatory ability measured by the area under a receiver operating characteristic curve was 0.64 (95% CI = 0.63-0.65) in the derivation sample and 0.57 (95% CI = 0.56-0.58) in the validation sample, with variation between centers. Positive and negative predictive values for the optimal cut-off value of ≥ 200 points were 9% and 96%, respectively. CONCLUSION The present risk score confidently excluded a large proportion of individuals from being at any appreciable risk to develop SWG within the next 5 years. Future studies, however, may attempt to further refine the positive prediction of the score.

Electronic voting system for computer supported collaborative learning

The EVS4CSCL project starts in the context of a Computer Supported Collaborative Learning environment (CSCL). Previous UOC projects created a CSCL generic platform (CLPL) to facilitate the development of CSCL applications. A discussion forum (DF) was the first application developed over the framework. This discussion forum was different from other products on the marketplace because of its focus on the learning process. The DF carried out the specification and elaboration phases from the discussion learning process but there was a lack in the consensus phase. The consensus phase in a learning environment is not something to be achieved but tested. Common tests are done by Electronic Voting System (EVS) tools, but consensus test is not an assessment test. We are not evaluating our students by their answers but by their discussion activity. Our educational EVS would be used as a discussion catalyst proposing a discussion about the results after an initial query or it would be used after a discussion period in order to manifest how the discussion changed the students mind (consensus). It should be also used by the teacher as a quick way to know where the student needs some reinforcement. That is important in a distance-learning environment where there is no direct contact between the teacher and the student and it is difficult to detect the learning lacks. In an educational environment, assessment it is a must and the EVS will provide direct assessment by peer usefulness evaluation, teacher marks on every query created and indirect assessment from statistics regarding the user activity.

Effective diagnosis of Alzheimer's disease by means of large margin-based methodology.

BACKGROUND Functional brain images such as Single-Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET) have been widely used to guide the clinicians in the Alzheimer's Disease (AD) diagnosis. However, the subjectivity involved in their evaluation has favoured the development of Computer Aided Diagnosis (CAD) Systems. METHODS It is proposed a novel combination of feature extraction techniques to improve the diagnosis of AD. Firstly, Regions of Interest (ROIs) are selected by means of a t-test carried out on 3D Normalised Mean Square Error (NMSE) features restricted to be located within a predefined brain activation mask. In order to address the small sample-size problem, the dimension of the feature space was further reduced by: Large Margin Nearest Neighbours using a rectangular matrix (LMNN-RECT), Principal Component Analysis (PCA) or Partial Least Squares (PLS) (the two latter also analysed with a LMNN transformation). Regarding the classifiers, kernel Support Vector Machines (SVMs) and LMNN using Euclidean, Mahalanobis and Energy-based metrics were compared. RESULTS Several experiments were conducted in order to evaluate the proposed LMNN-based feature extraction algorithms and its benefits as: i) linear transformation of the PLS or PCA reduced data, ii) feature reduction technique, and iii) classifier (with Euclidean, Mahalanobis or Energy-based methodology). The system was evaluated by means of k-fold cross-validation yielding accuracy, sensitivity and specificity values of 92.78%, 91.07% and 95.12% (for SPECT) and 90.67%, 88% and 93.33% (for PET), respectively, when a NMSE-PLS-LMNN feature extraction method was used in combination with a SVM classifier, thus outperforming recently reported baseline methods. CONCLUSIONS All the proposed methods turned out to be a valid solution for the presented problem. One of the advances is the robustness of the LMNN algorithm that not only provides higher separation rate between the classes but it also makes (in combination with NMSE and PLS) this rate variation more stable. In addition, their generalization ability is another advance since several experiments were performed on two image modalities (SPECT and PET).