Cannabis use in a Swiss male prison: qualitative study exploring detainees' and staffs' perspectives.

BACKGROUND: Several studies suggest a high prevalence of cannabis use before and during imprisonment, but subjective perspectives of detainees and staff towards its use in prison are lacking. This issue was explored in the framework of an observational study addressing tobacco use in three Swiss prisons in 2009 and 2010 that involved multiple strands (quantitative and qualitative components). This article presents qualitative data on cannabis use collected in one of the settings. METHODS: We used in-depth semi-structured interviews with both detainees and staff to explore their attitudes towards cannabis in one post-trial male Swiss prison. We performed specific coding and thematic analysis for cannabis with the support of ATLAS.ti, compared detainees' and staff's opinions, and considered the results with regard to drug policy in prison in general. RESULTS: 58 participants (31 male offenders, mean age 35 years, and 27 prison staff, mean age 46 years, 33% female) were interviewed. Detainees estimated the current use of cannabis use to be as high as 80%, and staff 50%. Participants showed similar opinions on effects of cannabis use that were described both at individual and institutional levels: analgesic, calming, self-help to go through the prison experience, relieve stress, facilitate sleep, prevent violence, and social pacifier. They also mentioned negative consequences of cannabis use (sleepiness, decreased perception of danger and social isolation), and dissatisfaction regarding the ongoing ambiguous situation where cannabis is forbidden but detection in the urine was not sanctioned. However, the introduction of a more restrictive regulation induced fear of violence, increased trafficking and a shift to other drug use. CONCLUSION: Although illegal, cannabis use is clearly involved in daily life in prison. A clearer and comprehensive policy addressing cannabis is needed, including appropriate measures tailored to individual users. To sustain a calm and safe environment in prison, means other than substance or medication use are required.

Robust Factor Analysis for Compositional Data

Factor analysis as frequent technique for multivariate data inspection is widely used also for compositional data analysis. The usual way is to use a centered logratio (clr)transformation to obtain the random vector y of dimension D. The factor model istheny = Λf + e (1)with the factors f of dimension k & D, the error term e, and the loadings matrix Λ.Using the usual model assumptions (see, e.g., Basilevsky, 1994), the factor analysismodel (1) can be written asCov(y) = ΛΛT + ψ (2)where ψ = Cov(e) has a diagonal form. The diagonal elements of ψ as well as theloadings matrix Λ are estimated from an estimation of Cov(y).Given observed clr transformed data Y as realizations of the random vectory. Outliers or deviations from the idealized model assumptions of factor analysiscan severely effect the parameter estimation. As a way out, robust estimation ofthe covariance matrix of Y will lead to robust estimates of Λ and ψ in (2), seePison et al. (2003). Well known robust covariance estimators with good statisticalproperties, like the MCD or the S-estimators (see, e.g. Maronna et al., 2006), relyon a full-rank data matrix Y which is not the case for clr transformed data (see,e.g., Aitchison, 1986).The isometric logratio (ilr) transformation (Egozcue et al., 2003) solves thissingularity problem. The data matrix Y is transformed to a matrix Z by usingan orthonormal basis of lower dimension. Using the ilr transformed data, a robustcovariance matrix C(Z) can be estimated. The result can be back-transformed tothe clr space byC(Y ) = V C(Z)V Twhere the matrix V with orthonormal columns comes from the relation betweenthe clr and the ilr transformation. Now the parameters in the model (2) can beestimated (Basilevsky, 1994) and the results have a direct interpretation since thelinks to the original variables are still preserved.The above procedure will be applied to data from geochemistry. Our specialinterest is on comparing the results with those of Reimann et al. (2002) for the Kolaproject data

Performing masculinity, influencing health: a qualitative mixed-methods study of young Spanish men

Background: The literature shows how gender mandates contribute to differences in exposure and vulnerability to certain health risk factors. This paper presents the results of a study developed in the south of Spain, where research aimed at understanding men from a gender perspective is still limited. Objective: The aim of this paper is to explore the lay perceptions and meanings ascribed to the idea of masculinity, identifying ways in which gender displays are related to health. Design: The study is based on a mixed-methods data collection strategy typical of qualitative research. We performed a qualitative content analysis focused on manifest and latent content. Results: Our analysis showed that the relationship between masculinity and health was mainly defined with regard to behavioural explanations with an evident performative meaning. With regard to issues such as driving, the use of recreational drugs, aggressive behaviour, sexuality, and body image, important connections were established between manhood acts and health outcomes. Different ways of understanding and performing the male identity also emerged from the results. The findings revealed the implications of these aspects in the processes of change in the identity codes of men and women. Conclusions: The study provides insights into how the category ‘man’ is highly dependent on collective practices and performative acts. Consideration of how males perform manhood acts might be required in guidance on the development of programmes and policies aimed at addressing gender inequalities in health in a particular local context.

Statistical Analysis of Eco-Toxicologic Data of Mammals from a Polluted Area

Several eco-toxicological studies have shown that insectivorous mammals, due to theirfeeding habits, easily accumulate high amounts of pollutants in relation to other mammal species. To assess the bio-accumulation levels of toxic metals and their in°uenceon essential metals, we quantified the concentration of 19 elements (Ca, K, Fe, B, P,S, Na, Al, Zn, Ba, Rb, Sr, Cu, Mn, Hg, Cd, Mo, Cr and Pb) in bones of 105 greaterwhite-toothed shrews (Crocidura russula) from a polluted (Ebro Delta) and a control(Medas Islands) area. Since chemical contents of a bio-indicator are mainly compositional data, conventional statistical analyses currently used in eco-toxicology can givemisleading results. Therefore, to improve the interpretation of the data obtained, weused statistical techniques for compositional data analysis to define groups of metalsand to evaluate the relationships between them, from an inter-population viewpoint.Hypothesis testing on the adequate balance-coordinates allow us to confirm intuitionbased hypothesis and some previous results. The main statistical goal was to test equalmeans of balance-coordinates for the two defined populations. After checking normality,one-way ANOVA or Mann-Whitney tests were carried out for the inter-group balances

Violence against adolescents: an analysis based on the categories gender and generation

Exploratory and descriptive study based on quantitative and qualitative methods that analyze the phenomenon of violence against adolescents based on gender and generational categories. The data source was reports of violence from the Curitiba Protection Network from 2010 to 2012 and semi-structured interviews with 16 sheltered adolescents. Quantitative data were analyzed using SPSS software version 20.0 and the qualitative data were subjected to content analysis. The adolescents were victims of violence in the household and outside of the family environment, as victims or viewers of violence. The violence was experienced at home, mostly toward girls, with marked overtones of gender violence. More than indicating the magnitude of the issue, this study can give information to help qualify the assistance given to victimized people and address how to face this issue.

Supplemental nursing staff´s experiences at a Spanish hospital: Qualitative phenomenology research

The objective of this study was to describe the Supplemental Nursing Staff´s experiences at different hospital units. A qualitative phenomenological approach was conducted; a purposeful and theoretical sampling was implemented with supplemental nursing staff at Santa Barbara Hospital of Soria (Spain), to gain a more in-depth understanding of the Supplemental Nursing Staff ´s experience. Data were collected by in-depth interviews and through a field notebook. Data were analyzed using the Giorgi proposal. Twenty-one nurses with a mean age of 46 years were included. Three main topics emerged from the data analysis: building the first contact, carving out a niche and establishing interprofessional/interpersonal relationships. We conclude that the experience of hosting the supplemental nursing staff in changing clinical environments is conditioned by various factors. It is necessary for nurses and hospital managers to establish clear objectives with regard to the supplemental nursing staff´s role in the units.

Staphylococcal biofilm formation on the surface of three different calcium phosphate bone grafts: a qualitative and quantitative in vivo analysis.

Differences in physico-chemical characteristics of bone grafts to fill bone defects have been demonstrated to influence in vitro bacterial biofilm formation. Aim of the study was to investigate in vivo staphylococcal biofilm formation on different calcium phosphate bone substitutes. A foreign-body guinea-pig infection model was used. Teflon cages prefilled with β-tricalcium phosphate, calcium-deficient hydroxyapatite, or dicalcium phosphate (DCP) scaffold were implanted subcutaneously. Scaffolds were infected with 2 × 10(3) colony-forming unit of Staphylococcus aureus (two strains) or S. epidermidis and explanted after 3, 24 or 72 h of biofilm formation. Quantitative and qualitative biofilm analysis was performed by sonication followed by viable counts, and microcalorimetry, respectively. Independently of the material, S. aureus formed increasing amounts of biofilm on the surface of all scaffolds over time as determined by both methods. For S. epidermidis, the biofilm amount decreased over time, and no biofilm was detected by microcalorimetry on the DCP scaffolds after 72 h of infection. However, when using a higher S. epidermidis inoculum, increasing amounts of biofilm were formed on all scaffolds as determined by microcalorimetry. No significant variation in staphylococcal in vivo biofilm formation was observed between the different materials tested. This study highlights the importance of in vivo studies, in addition to in vitro studies, when investigating biofilm formation of bone grafts.

Interdisciplinary research for the analysis and risk assesment : the case of the municipality of Uspantan Guatemala

Short description of the proposed presentation * lees than 100 words This paper describes the interdisciplinary work done in Uspantán, Guatemala, a city vulnerable to natural hazards. We investigated local responses to landslides that happened in 2007 and 2010 and had a strong impact on the local community. We show a complete example of a systemic approach that incorporates physical, social and environmental aspects in order to understand risks. The objective of this work is to present the combination of social and geological data (mapping), and describe the methodology used for identification and assessment of risk. The article discusses both the limitations and methodological challenges encountered when conducting interdisciplinary research. Describe why it is important to present this topic at the Global Platform in less than 50 words This work shows the benefits of addressing risk in an interdisciplinary perspective, in particular how integrating social sciences can help identify new phenomena and natural hazards and assess risk. It gives a practical example of how one can integrate data from different fields. What is innovative about this presentation? * The use of mapping to combine qualitative and quantitative data. By coupling approaches, we could associate a hazard map with qualitative data gathered by interviews with the population. This map is an important document for the authorities. Indeed, it allows them to be aware of the most dangerous zones, the affected families and the places where it is most urgent to intervene.

Distributional equivalence and subcompositional coherence in the analysis of contingency tables, ratio-scale measurements and compositional data

We consider two fundamental properties in the analysis of two-way tables of positive data: the principle of distributional equivalence, one of the cornerstones of correspondence analysis of contingency tables, and the principle of subcompositional coherence, which forms the basis of compositional data analysis. For an analysis to be subcompositionally coherent, it suffices to analyse the ratios of the data values. The usual approach to dimension reduction in compositional data analysis is to perform principal component analysis on the logarithms of ratios, but this method does not obey the principle of distributional equivalence. We show that by introducing weights for the rows and columns, the method achieves this desirable property. This weighted log-ratio analysis is theoretically equivalent to spectral mapping , a multivariate method developed almost 30 years ago for displaying ratio-scale data from biological activity spectra. The close relationship between spectral mapping and correspondence analysis is also explained, as well as their connection with association modelling. The weighted log-ratio methodology is applied here to frequency data in linguistics and to chemical compositional data in archaeology.

Spatiotemporal analysis of forensic case data: a visualisation approach

Whether for investigative or intelligence aims, crime analysts often face up the necessity to analyse the spatiotemporal distribution of crimes or traces left by suspects. This article presents a visualisation methodology supporting recurrent practical analytical tasks such as the detection of crime series or the analysis of traces left by digital devices like mobile phone or GPS devices. The proposed approach has led to the development of a dedicated tool that has proven its effectiveness in real inquiries and intelligence practices. It supports a more fluent visual analysis of the collected data and may provide critical clues to support police operations as exemplified by the presented case studies.

Non-Destructive Evaluation of Iowa Pavements Phase 2: Development of a Fully Automated Software System for Rapid Analysis/Processing of the Falling Weight Deflectometer Data, 2009

The Office of Special Investigations at Iowa Department of Transportation (DOT) collects FWD data on regular basis to evaluate pavement structural conditions. The primary objective of this study was to develop a fully-automated software system for rapid processing of the FWD data along with a user manual. The software system automatically reads the FWD raw data collected by the JILS-20 type FWD machine that Iowa DOT owns, processes and analyzes the collected data with the rapid prediction algorithms developed during the phase I study. This system smoothly integrates the FWD data analysis algorithms and the computer program being used to collect the pavement deflection data. This system can be used to assess pavement condition, estimate remaining pavement life, and eventually help assess pavement rehabilitation strategies by the Iowa DOT pavement management team. This report describes the developed software in detail and can also be used as a user-manual for conducting simulation studies and detailed analyses. *********************** Large File ***********************

Analysis and spatial modeling of the indoor radon Swiss data

The present research deals with an important public health threat, which is the pollution created by radon gas accumulation inside dwellings. The spatial modeling of indoor radon in Switzerland is particularly complex and challenging because of many influencing factors that should be taken into account. Indoor radon data analysis must be addressed from both a statistical and a spatial point of view. As a multivariate process, it was important at first to define the influence of each factor. In particular, it was important to define the influence of geology as being closely associated to indoor radon. This association was indeed observed for the Swiss data but not probed to be the sole determinant for the spatial modeling. The statistical analysis of data, both at univariate and multivariate level, was followed by an exploratory spatial analysis. Many tools proposed in the literature were tested and adapted, including fractality, declustering and moving windows methods. The use of Quan-tité Morisita Index (QMI) as a procedure to evaluate data clustering in function of the radon level was proposed. The existing methods of declustering were revised and applied in an attempt to approach the global histogram parameters. The exploratory phase comes along with the definition of multiple scales of interest for indoor radon mapping in Switzerland. The analysis was done with a top-to-down resolution approach, from regional to local lev¬els in order to find the appropriate scales for modeling. In this sense, data partition was optimized in order to cope with stationary conditions of geostatistical models. Common methods of spatial modeling such as Κ Nearest Neighbors (KNN), variography and General Regression Neural Networks (GRNN) were proposed as exploratory tools. In the following section, different spatial interpolation methods were applied for a par-ticular dataset. A bottom to top method complexity approach was adopted and the results were analyzed together in order to find common definitions of continuity and neighborhood parameters. Additionally, a data filter based on cross-validation was tested with the purpose of reducing noise at local scale (the CVMF). At the end of the chapter, a series of test for data consistency and methods robustness were performed. This lead to conclude about the importance of data splitting and the limitation of generalization methods for reproducing statistical distributions. The last section was dedicated to modeling methods with probabilistic interpretations. Data transformation and simulations thus allowed the use of multigaussian models and helped take the indoor radon pollution data uncertainty into consideration. The catego-rization transform was presented as a solution for extreme values modeling through clas-sification. Simulation scenarios were proposed, including an alternative proposal for the reproduction of the global histogram based on the sampling domain. The sequential Gaussian simulation (SGS) was presented as the method giving the most complete information, while classification performed in a more robust way. An error measure was defined in relation to the decision function for data classification hardening. Within the classification methods, probabilistic neural networks (PNN) show to be better adapted for modeling of high threshold categorization and for automation. Support vector machines (SVM) on the contrary performed well under balanced category conditions. In general, it was concluded that a particular prediction or estimation method is not better under all conditions of scale and neighborhood definitions. Simulations should be the basis, while other methods can provide complementary information to accomplish an efficient indoor radon decision making.

Informing patients about limits to confidentiality: A qualitative study in prisons.

AIM: Confidentiality is important in healthcare practice, however, under certain circumstances, confidentiality is breached. In this paper, mental health professionals' (MHPs) practices related to informing imprisoned patients about confidentiality and its limits are presented. METHODS: Twenty-four MHPs working in Swiss prisons were interviewed. Data analysis involved qualitative thematic coding and was validated by discussing results with external experts and study participants. RESULTS: For expert evaluations and court-ordered therapies, participants informed patients that information revealed during these consultations is not bound by confidentiality rules. The practice of routinely informing patients about confidentiality and its limits became more complex in voluntary therapies, for which participants described four approaches and provided justifications in favour of or against their use. CONCLUSIONS: Further training and continued education are needed to improve physicians' ethical and legal knowledge about confidentiality disclosures. In order to promote ethical practices, it is important to understand and address existing motivations, attitudes and behaviours that impede appropriate patient information. Our study adds important new knowledge about the limits to confidentiality, particularly for providers working with vulnerable populations. Results from this study reflect typical ethical and practical dilemmas faced by and of interest to physicians working in forensic medicine and other related settings.

Who's fault is it ? : An analysis of the press coverage of football betting scandals in France and the United Kingdom

Sport betting is a lucrative business for bookmakers, for the lucky (or wise) punters, but also for governments and for sport. While not new or even recent, the deviances linked to sport betting, primarily match-fixing, have gained increased media exposure in the past decade. This exploratory study is a qualitative content analysis of the press coverage of sport betting-related deviances in football in two countries (UK and France), using in each case two leading national publications over a period of five years. Data analysis indicates a mounting coverage of sport betting scandals, with teams, players and criminals increasingly framed as culprits, while authorities and federations primarily assume a positive role. As for the origin of sport betting deviances, French newspapers tend to blame the system (in an abstract way); British newspapers, in contrast, focus more on individual weaknesses, notably greed. This article contributed to the growing body of literature on the importance of these deviances and on the way they are perceived by sport organizations, legislators and the public at large.

Automatic evaluation and data generation for analytical chemistry instrumental analysis exercises

In general, laboratory activities are costly in terms of time, space, and money. As such, the ability to provide realistically simulated laboratory data that enables students to practice data analysis techniques as a complementary activity would be expected to reduce these costs while opening up very interesting possibilities. In the present work, a novel methodology is presented for design of analytical chemistry instrumental analysis exercises that can be automatically personalized for each student and the results evaluated immediately. The proposed system provides each student with a different set of experimental data generated randomly while satisfying a set of constraints, rather than using data obtained from actual laboratory work. This allows the instructor to provide students with a set of practical problems to complement their regular laboratory work along with the corresponding feedback provided by the system's automatic evaluation process. To this end, the Goodle Grading Management System (GMS), an innovative web-based educational tool for automating the collection and assessment of practical exercises for engineering and scientific courses, was developed. The proposed methodology takes full advantage of the Goodle GMS fusion code architecture. The design of a particular exercise is provided ad hoc by the instructor and requires basic Matlab knowledge. The system has been employed with satisfactory results in several university courses. To demonstrate the automatic evaluation process, three exercises are presented in detail. The first exercise involves a linear regression analysis of data and the calculation of the quality parameters of an instrumental analysis method. The second and third exercises address two different comparison tests, a comparison test of the mean and a t-paired test.