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Tobacco is responsible for 66,000 deaths per year in France, which makes it one of the most important national public health priorities. Preadolescents, at the age where this addiction usually begins, are a particularly interesting target group for the implementation of prevention activities. It is for this reason that in 1990, the French National League against Cancer established a set of non-smoking youth clubs (“Pataclope”) of which the main objective is to prevent adolescents from starting to smoke. An evaluation programme was put into place in 1999 in order to better understand the impact of these clubs on the prevalence of smoking in 15 year olds, which corresponds to the age of former participants one year after leaving the clubs.A comparison between a group of youth having participated in the Pataclope clubs and a group of adolescents taken from the general population was carried out at the national level. Those selected were 15 years of age and were in high school. An anonymous self-questionnaire on their tobacco habits and factors of addiction was distributed to the two groups. The analysis involved a total of 3274 questionnaires, 899 of which were from Pataclope participants and 2375 from the sample population.The primary results show that the prevalence rates according to sex essentially mirror those of the Baromètre santé 2000, among other accepted statistics (25.5% for girls and 19.9% for boys versus 31.6% for girls and 18.1% for boys in the Baromètre santé 2000). One year after leaving the clubs, the former Pataclope members see their risk of becoming a smoker reduced by 26% with respect to those who were not club members (OR = .74 adjusted for the factors of addiction), within a model which regroups smokers and ex-smokers versus non-smokers. In utilising this model which takes into account the ex-smokers and smokers as two distinct categories (the reference always being non-smokers), the reduction of risk in being a smoker is always significant, and goes up to 50% less risk (OR= 0.5) for members of Pataclope. The probability of being an ex-smoker is identical in the two groups: given that once one has taken up smoking, the Pataclope members present the same smoking behaviours as the general population (same consumption, same age of quitting, and the same frequency of quitting).The activity of the Pataclope clubs has been encouraging in at least slowing or hindering the commencement of smoking in youth aged 15 years. However, these results require a confirmation in the long term. The lack of impact on the ex-smokers tends to demonstrate that the mesSAGE of clubs reinforces a non-smoking behaviour but remains ineffective on quitting, once smoking has been taken up.

The goal of intensive care is to provide the highest quality care to achieve the best outcomes for patients. Although the random allocation of patients to receive intensive care as part of a randomized controlled trial might in theory be the best method to evaluate its effectiveness, the practical application of such a study design is deemed unethical. The alternative in such a situation is to use observational methods in which the outcome of care patients receive as part of their “natural” treatment is studied. Before drawing inferences from the outcomes of treatment for such groups of patients, the characteristics of the patients admitted to intensive care must be taken into account. The purpose of scoring systems in intensive care, as for many other areas of health care, is to take into account the characteristics of patients that could affect their risk of a particular outcome, irrespective of the effect of the care they receive. Clearly, accounting for such factors, which are outside the control of those providing the care, is essential before any comparison of the outcome of care is possible. For each scoring system, the association between the independent variables (patient characteristics) and the dependent variable (death before discharge from hospital after intensive care) is described in the form of a mathematical model, known as a multiple logistic regression model. To assess any scoring system and model, four steps must be undertaken. First, the goodness-of-fit of the model should be assessed on the development dataset. Second, the goodness-of-fit of the model should be assessed on a subset of the dataset different from the subset used to develop the model. Third, the goodness-of-fit of the model should be assessed on an entirely new dataset. Fourth, the given model should be compared with other existing models on the same dataset. This article briefly describes the concept of scoring systems and their roles, and outlines the requirements for assessment in terms of model validation and goodness-of-fit. It concludes with the outstanding methodological issues in this area.