Inhabitants' and professionals' social representations of health determinants in a disadvantaged urban area in France: a qualitative analysis = représentations sociales des déterminants de santé dans une zone urbaine défavorisée en France : analyse qualitative auprès d'habitants et de professionnels

Background and objective. - Access to care in French disadvantaged urban areas remains an issue despite the implementation of local healthcare structures. To understand this contradiction, we investigated social representations held by inhabitants of such areas, as well as those of social and healthcare professionals, regarding events or behaviours that can impact low-income individuals' health. Method. - In the context of a health diagnosis, 288 inhabitants living in five disadvantaged districts of Aix-les-Bains, as well as 28 professionals working in these districts, completed an open-ended questionnaire. The two groups of respondents were asked to describe what could have an impact on health status from the inhabitants' point of view. The textual responses were analyzed using the Alceste method. Results. - We observed a number of differences in the way the inhabitants and professionals represented determinants of health in disadvantaged urban areas: the former proposed a representation mixing personal responsibility with physiological, social, familial, and professional aspects, whereas the latter associated health issues with marginalization (financial, drug, or alcohol problems) and personal responsibility. Both inhabitants and professionals mentioned control over events and lifestyle as determinants of health. Discussion. - The results are discussed regarding the consequences of these different representations on the beneficiary - healthcare-provider relationship in terms of communication and trust.

Temporal and spatial distribution of Leishmania mexicana infections in a population of Neotoma micropus

A 19-month mark-release-recapture study of Neotoma micropus with sequential screening for Leishmania mexicana was conducted in Bexar County, Texas, USA. The overall prevalence rate was 14.7% and the seasonal prevalence rates ranged from 3.8 to 26.7%. Nine incident cases were detected, giving an incidence rate of 15.5/100 rats/year. Follow-up of 101 individuals captured two or more times ranged from 14 to 462 days. Persistence of L. mexicana infections averaged 190 days and ranged from 104 to 379 days. Data on dispersal, density, dispersion, and weight are presented, and the role of N. micropus as a reservoir host for L. mexicana is discussed.

Coronary MR angiography: comparison of quantitative and qualitative data from four techniques.

OBJECTIVE: The optimal coronary MR angiography sequence has yet to be determined. We sought to quantitatively and qualitatively compare four coronary MR angiography sequences. SUBJECTS AND METHODS. Free-breathing coronary MR angiography was performed in 12 patients using four imaging sequences (turbo field-echo, fast spin-echo, balanced fast field-echo, and spiral turbo field-echo). Quantitative comparisons, including signal-to-noise ratio, contrast-to-noise ratio, vessel diameter, and vessel sharpness, were performed using a semiautomated analysis tool. Accuracy for detection of hemodynamically significant disease (> 50%) was assessed in comparison with radiographic coronary angiography. RESULTS: Signal-to-noise and contrast-to-noise ratios were markedly increased using the spiral (25.7 +/- 5.7 and 15.2 +/- 3.9) and balanced fast field-echo (23.5 +/- 11.7 and 14.4 +/- 8.1) sequences compared with the turbo field-echo (12.5 +/- 2.7 and 8.3 +/- 2.6) sequence (p < 0.05). Vessel diameter was smaller with the spiral sequence (2.6 +/- 0.5 mm) than with the other techniques (turbo field-echo, 3.0 +/- 0.5 mm, p = 0.6; balanced fast field-echo, 3.1 +/- 0.5 mm, p < 0.01; fast spin-echo, 3.1 +/- 0.5 mm, p < 0.01). Vessel sharpness was highest with the balanced fast field-echo sequence (61.6% +/- 8.5% compared with turbo field-echo, 44.0% +/- 6.6%; spiral, 44.7% +/- 6.5%; fast spin-echo, 18.4% +/- 6.7%; p < 0.001). The overall accuracies of the sequences were similar (range, 74% for turbo field-echo, 79% for spiral). Scanning time for the fast spin-echo sequences was longest (10.5 +/- 0.6 min), and for the spiral acquisitions was shortest (5.2 +/- 0.3 min). CONCLUSION: Advantages in signal-to-noise and contrast-to-noise ratios, vessel sharpness, and the qualitative results appear to favor spiral and balanced fast field-echo coronary MR angiography sequences, although subjective accuracy for the detection of coronary artery disease was similar to that of other sequences.

Machine learning algorithms for spatial data. Case studies: Environmental pollution, natural hazards, renewable resources

This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.

Patients' spontaneous discourse on the importance of significant others in the course of transplantation: A qualitative study

Background: This study explores significant ones' implication before and after transplantation. Methods: Longitudinal semi-structured interviews were conducted in 64 patients awaiting all-organ transplantation. Among them, 58 patients spontaneously discussed the importance of their significant other in their daily support. Discourse analysis was applied. Findings: During the pre-transplantation period renal patients reported that significant others took part in dialysis treatment and participated to regimen adherence. After transplantation, quality of life improved and the couple dynamics returned to normal. Patients awaiting lung or heart transplantation were more heavily impaired. Significant others had to take over abandoned roles. After transplantation resuming normal life became gradually possible, but after one year either transplantation health benefits relieved physical, emotional and social loads, or complications maintained the level of stress on significant others. Discussion: Patients reported that significant others had to take over various responsibilities and were concerned about long-term stress that should be adequately supported.

Comparative analysis of ten assesment grids of quality criteria in qualitative research

The authors present 10 grids which are widely used in Health Sciences for the assessment of quality in research. They proceed through a comparative thematic analysis of these grids and show which points of view are preferred. They insist on the issues that differentiate these grids from each other and suggest the analysis of their differences by distinguishing the theoretical perspectives that underpin each one of these grids. Whilst the authors of the assessment grids rarely refer to the implicit theoretical backgrounds that guide their work, findings show that these grids convey varied epistemologies and research models. This gap renders the comparison of quality assessment in qualitative research a very difficult task, unless we shift our focus on the relationship between the grids, their theoretical backgrounds and their specific research subjects.

A Mind of their Own. A Qualitative Study of Drug Education from a Young Person's Perspective: Exploring their Experiences, Views and Opinions

The main aims of the research are to explore young people's experiences and opinions of drug education and to discover whether it is, in their opinion, meeting their needs. The study was conducted with twenty young people aged fifteen to nineteen years in two towns in North County Dublin. The principal school teachers from three secondary schools in the area were also interviewed. The findings reveal there is a lack of planned drug education in the schools mainly, according to principal school teachers, due to timetable constraints. Another key finding is the need expressed by the young people for accurate and balanced drug education. The study also shows that there is a conflict between young people's negative opinion of teachers as drug educators and that of the literature and research, which identifies teachers as the most appropriate drug educators. In view of these findings the following recommendations are recommendations are suggested. Firstly, the role of teachers as drug educators needs further research. Secondly, the Substance Abuse Prevention Programme needs to be extended to include the over fifteen year's age group with a harm reduction/safety module as part of the programme. Thirdly, the Social, Personal and Health Education as a core subject needs to be fully implemented in the schools. Finally, the inclusion of young peoples' views in the form of a 'reference' or 'representative' group in each school would be a positive recommendation. This would give young consumers of drug education programmes some input into drug policy within the schools they attend.This resource was contributed by The National Documentation Centre on Drug Use.

Spatial analysis of the distribution of leprosy in the State of Ceará, Northeast Brazil

The aim of this study was to describe spatial patterns of the distribution of leprosy and to investigate spatial clustering of incidence rates in the state of Ceará, Northeast Brazil. The average incidence rate of leprosy for the period of 1991 to 1999 was calculated for each municipality of Ceará. Maps were used to describe the spatial distribution of the disease, and spatial statistics were applied to explore large- and small-scale variations of incidence rates. Three regions were identified in which the incidence of leprosy was particularly high. A spatial gradient in the incidence rates was identified, with a tendency of high rates to be concentrated on the North-South axis in the middle region of the state. Moran's I statistic indicated that a significant spatial autocorrelation also existed. The spatial distribution of leprosy in Ceará is heterogeneous. The reasons for spatial clustering of disease rates are not known, but might be related to an heterogeneous distribution of other factors such as crowding, social inequality, and environmental characteristics which by themselves determine the transmission of Mycobacterium leprae.

Fine-scale spatial genetic structure and gene dispersal in Silene latifolia.

Plants are sessile organisms, often characterized by limited dispersal. Seeds and pollen are the critical stages for gene flow. Here we investigate spatial genetic structure, gene dispersal and the relative contribution of pollen vs seed in the movement of genes in a stable metapopulation of the white campion Silene latifolia within its native range. This short-lived perennial plant is dioecious, has gravity-dispersed seeds and moth-mediated pollination. Direct measures of pollen dispersal suggested that large populations receive more pollen than small isolated populations and that most gene flow occurs within tens of meters. However, these studies were performed in the newly colonized range (North America) where the specialist pollinator is absent. In the native range (Europe), gene dispersal could fall on a different spatial scale. We genotyped 258 individuals from large and small (15) subpopulations along a 60 km, elongated metapopulation in Europe using six highly variable microsatellite markers, two X-linked and four autosomal. We found substantial genetic differentiation among subpopulations (global F(ST)=0.11) and a general pattern of isolation by distance over the whole sampled area. Spatial autocorrelation revealed high relatedness among neighboring individuals over hundreds of meters. Estimates of gene dispersal revealed gene flow at the scale of tens of meters (5-30 m), similar to the newly colonized range. Contrary to expectations, estimates of dispersal based on X and autosomal markers showed very similar ranges, suggesting similar levels of pollen and seed dispersal. This may be explained by stochastic events of extensive seed dispersal in this area and limited pollen dispersal.