75 resultados para Coach education programmes


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PURPOSE: Not in Education, Employment, or Training (NEET) youth are youth disengaged from major social institutions and constitute a worrying concern. However, little is known about this subgroup of vulnerable youth. This study aimed to examine if NEET youth differ from other contemporaries in terms of personality, mental health, and substance use and to provide longitudinal examination of NEET status, testing its stability and prospective pathways with mental health and substance use. METHODS: As part of the Cohort Study on Substance Use Risk Factors, 4,758 young Swiss men in their early 20s answered questions concerning their current professional and educational status, personality, substance use, and symptomatology related to mental health. Descriptive statistics, generalized linear models for cross-sectional comparisons, and cross-lagged panel models for longitudinal associations were computed. RESULTS: NEET youth were 6.1% at baseline and 7.4% at follow-up with 1.4% being NEET at both time points. Comparisons between NEET and non-NEET youth showed significant differences in substance use and depressive symptoms only. Longitudinal associations showed that previous mental health, cannabis use, and daily smoking increased the likelihood of being NEET. Reverse causal paths were nonsignificant. CONCLUSIONS: NEET status seemed to be unlikely and transient among young Swiss men, associated with differences in mental health and substance use but not in personality. Causal paths presented NEET status as a consequence of mental health and substance use rather than a cause. Additionally, this study confirmed that cannabis use and daily smoking are public health problems. Prevention programs need to focus on these vulnerable youth to avoid them being disengaged.

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BACKGROUND: The second Swiss Multicenter Adolescent Survey on Health (SMASH02) was conducted among a representative sample (n = 7428) of students and apprentices aged 16 to 20 from the three language areas of Switzerland during the year 2002. This paper reports on health needs expressed by adolescents and their use of health care services over the 12 months preceding the survey. METHODS: Nineteen cantons representing 80% of the resident population agreed to participate. A complex iterative random cluster sample of 600 classes was drawn with classes as primary sampling unit. The participation rate was 97.7% for the classes and 99.8% for the youths in attendance. The self-administered questionnaire included 565 items. The median rate of item non-response was 1.8%. Ethical and legal requirements applying to surveys of adolescent populations were respected. RESULTS: Overall more than 90% of adolescents felt in good to excellent health. Suffering often or very often from different physical complaints or pain was also reported such as headache (boys: 15.9%, girls: 37.4%), stomach-ache (boys: 9.7%, girls: 30.0%), joint pain (boys: 24.7%, girls: 29.5%) or back pain (boys: 24.3%, girls: 34.7%). Many adolescents reported a need for help on psychosocial and lifestyle issues, such as stress (boys: 28.5%, girls: 47.7%) or depression (boys: 18.9%, girls: 34.4%). Although about 75% of adolescents reported having consulted a general practitioner and about one-third having seen another specialist, reported reasons for visits do not correspond to the expressed needs. Less than 10% of adolescents had visited a psychiatrist, a family planning centre or a social worker. CONCLUSIONS: The reported rates of health services utilisation by adolescents does not match the substantial reported needs for help in various areas. This may indicate that the corresponding problems are not adequately detected and/or addressed by professionals from the health and social sectors.

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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.

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Le présent cahier documente les différents programmes informatiques nécessaires à l'adaptation suisse des DRG.

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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.

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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.