142 resultados para Education - Prison
Resumo:
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.
Resumo:
Background: The number of older prisoners entering and ageing in prison has increased in the last few decades. Ageing prisoners pose unique challenges to the prison administration as they have differentiated social, custodial and healthcare needs than prisoners who are younger and relatively healthier. Objective: The goal of this study was to explore and compare the somatic disease burden of old and young prisoners, and to examine whether it can be explained by age group and/or time served in prison. Methods: Access to prisoner medical records was granted to extract disease and demographic information of older (>50 years) and younger (≤49 years) prisoners in different Swiss prisons. Predictor variables included the age group and the time spent in prison. The dependent variable was the total number of somatic diseases as reported in the medical records. Results were analysed using descriptive statistics and a negative binomial model. Results: Data of 380 male prisoners from 13 different prisons in Switzerland reveal that the mean ages of older and younger prisoners were 58.78 and 34.26 years, respectively. On average, older prisoners have lived in prison for 5.17 years and younger prisoners for 2.49 years. The average total number of somatic diseases reported by older prisoners was 2.26 times higher than that of prisoners below 50 years of age (95% CI 1.77-2.87, p < 0.001). Conclusion: This study is the first of its kind to capture national disease data of prisoners with a goal of comparing the disease burden of older and younger prisoners. Study findings indicate that older inmates suffer from more somatic diseases and that the number of diseases increases with age group. Results clearly illustrate the poorer health conditions of those who are older, their higher healthcare burden, and raises questions related to the provision of healthcare for inmates growing old in prison. © 2014 S. Karger AG, Basel.
Resumo:
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.
Resumo:
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.
Resumo:
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.