Canakinumab reduces the risk of acute gouty arthritis flares during initiation of allopurinol treatment: results of a double-blind, randomised study.

Objective This study assessed the efficacy and safety of canakinumab, a fully human anti-interleukin 1 beta monoclonal antibody, for prophylaxis against acute gouty arthritis flares in patients initiating urate-lowering treatment.Methods In this double-blind, double-dummy, dose-ranging study, 432 patients with gouty arthritis initiating allopurinol treatment were randomised 1:1:1:1:1:1:2 to receive: a single dose of canakinumab, 25, 50, 100, 200, or 300 mg subcutaneously; 4 x 4-weekly doses of canakinumab (50 + 50 + 25 + 25 mg subcutaneously); or daily colchicine 0.5 mg orally for 16 weeks. Patients recorded details of flares in diaries. The study aimed to determine the canakinumab dose having equivalent efficacy to colchicine 0.5 mg at 16 weeks.Results A dose-response for canakinumab was not apparent with any of the four predefined dose-response models. The estimated canakinumab dose with equivalent efficacy to colchicine was below the range of doses tested. At 16 weeks, there was a 62% to 72% reduction in the mean number of flares per patient for canakinumab doses >= 50 mg versus colchicine based on a negative binomial model (rate ratio: 0.28-0.38, p <= 0.0083), and the percentage of patients experiencing >= 1 flare was significantly lower for all canakinumab doses (15% to 27%) versus colchicine (44%, p<0.05). There was a 64% to 72% reduction in the risk of experiencing >= 1 flare for canakinumab doses >= 50 mg versus colchicine at 16 weeks (hazard ratio (HR): 0.28-0.36, p <= 0.05). The incidence of adverse events was similar across treatment groups.Conclusions Single canakinumab doses >= 50 mg or four 4-weekly doses provided superior prophylaxis against flares compared with daily colchicine 0.5 mg.

Do political factors matter in explaining under- and overweight outcomes in developing countries?

We construct a rich dataset covering 47 developing countries over the years 1990-2007, combining several micro and macro level data sources to explore the link between political factors and body mass index (BMI). We implement a heteroskedastic generalized ordered logit model allowing for different covariate effects across the BMI distribution and accounting for the unequal BMI dispersion by geographical area. We find that systems with democratic qualities are more likely to reduce under-weight, but increase overweight/obesity, whereas effective political competition does entail double-benefits in the form of reducing both under-weight and obesity. Our results are robust to the introduction of country fixed effects.

A study on the performance of flexible pavements on mature soil subgrades

The country has witnessed tremendous increase in the vehicle population and increased axle loading pattern during the last decade, leaving its road network overstressed and leading to premature failure. The type of deterioration present in the pavement should be considered for determining whether it has a functional or structural deficiency, so that appropriate overlay type and design can be developed. Structural failure arises from the conditions that adversely affect the load carrying capability of the pavement structure. Inadequate thickness, cracking, distortion and disintegration cause structural deficiency. Functional deficiency arises when the pavement does not provide a smooth riding surface and comfort to the user. This can be due to poor surface friction and texture, hydro planning and splash from wheel path, rutting and excess surface distortion such as potholes, corrugation, faulting, blow up, settlement, heaves etc. Functional condition determines the level of service provided by the facility to its users at a particular time and also the Vehicle Operating Costs (VOC), thus influencing the national economy. Prediction of the pavement deterioration is helpful to assess the remaining effective service life (RSL) of the pavement structure on the basis of reduction in performance levels, and apply various alternative designs and rehabilitation strategies with a long range funding requirement for pavement preservation. In addition, they can predict the impact of treatment on the condition of the sections. The infrastructure prediction models can thus be classified into four groups, namely primary response models, structural performance models, functional performance models and damage models. The factors affecting the deterioration of the roads are very complex in nature and vary from place to place. Hence there is need to have a thorough study of the deterioration mechanism under varied climatic zones and soil conditions before arriving at a definite strategy of road improvement. Realizing the need for a detailed study involving all types of roads in the state with varying traffic and soil conditions, the present study has been attempted. This study attempts to identify the parameters that affect the performance of roads and to develop performance models suitable to Kerala conditions. A critical review of the various factors that contribute to the pavement performance has been presented based on the data collected from selected road stretches and also from five corporations of Kerala. These roads represent the urban conditions as well as National Highways, State Highways and Major District Roads in the sub urban and rural conditions. This research work is a pursuit towards a study of the road condition of Kerala with respect to varying soil, traffic and climatic conditions, periodic performance evaluation of selected roads of representative types and development of distress prediction models for roads of Kerala. In order to achieve this aim, the study is focused into 2 parts. The first part deals with the study of the pavement condition and subgrade soil properties of urban roads distributed in 5 Corporations of Kerala; namely Thiruvananthapuram, Kollam, Kochi, Thrissur and Kozhikode. From selected 44 roads, 68 homogeneous sections were studied. The data collected on the functional and structural condition of the surface include pavement distress in terms of cracks, potholes, rutting, raveling and pothole patching. The structural strength of the pavement was measured as rebound deflection using Benkelman Beam deflection studies. In order to collect the details of the pavement layers and find out the subgrade soil properties, trial pits were dug and the in-situ field density was found using the Sand Replacement Method. Laboratory investigations were carried out to find out the subgrade soil properties, soil classification, Atterberg limits, Optimum Moisture Content, Field Moisture Content and 4 days soaked CBR. The relative compaction in the field was also determined. The traffic details were also collected by conducting traffic volume count survey and axle load survey. From the data thus collected, the strength of the pavement was calculated which is a function of the layer coefficient and thickness and is represented as Structural Number (SN). This was further related to the CBR value of the soil and the Modified Structural Number (MSN) was found out. The condition of the pavement was represented in terms of the Pavement Condition Index (PCI) which is a function of the distress of the surface at the time of the investigation and calculated in the present study using deduct value method developed by U S Army Corps of Engineers. The influence of subgrade soil type and pavement condition on the relationship between MSN and rebound deflection was studied using appropriate plots for predominant types of soil and for classified value of Pavement Condition Index. The relationship will be helpful for practicing engineers to design the overlay thickness required for the pavement, without conducting the BBD test. Regression analysis using SPSS was done with various trials to find out the best fit relationship between the rebound deflection and CBR, and other soil properties for Gravel, Sand, Silt & Clay fractions. The second part of the study deals with periodic performance evaluation of selected road stretches representing National Highway (NH), State Highway (SH) and Major District Road (MDR), located in different geographical conditions and with varying traffic. 8 road sections divided into 15 homogeneous sections were selected for the study and 6 sets of continuous periodic data were collected. The periodic data collected include the functional and structural condition in terms of distress (pothole, pothole patch, cracks, rutting and raveling), skid resistance using a portable skid resistance pendulum, surface unevenness using Bump Integrator, texture depth using sand patch method and rebound deflection using Benkelman Beam. Baseline data of the study stretches were collected as one time data. Pavement history was obtained as secondary data. Pavement drainage characteristics were collected in terms of camber or cross slope using camber board (slope meter) for the carriage way and shoulders, availability of longitudinal side drain, presence of valley, terrain condition, soil moisture content, water table data, High Flood Level, rainfall data, land use and cross slope of the adjoining land. These data were used for finding out the drainage condition of the study stretches. Traffic studies were conducted, including classified volume count and axle load studies. From the field data thus collected, the progression of each parameter was plotted for all the study roads; and validated for their accuracy. Structural Number (SN) and Modified Structural Number (MSN) were calculated for the study stretches. Progression of the deflection, distress, unevenness, skid resistance and macro texture of the study roads were evaluated. Since the deterioration of the pavement is a complex phenomena contributed by all the above factors, pavement deterioration models were developed as non linear regression models, using SPSS with the periodic data collected for all the above road stretches. General models were developed for cracking progression, raveling progression, pothole progression and roughness progression using SPSS. A model for construction quality was also developed. Calibration of HDM–4 pavement deterioration models for local conditions was done using the data for Cracking, Raveling, Pothole and Roughness. Validation was done using the data collected in 2013. The application of HDM-4 to compare different maintenance and rehabilitation options were studied considering the deterioration parameters like cracking, pothole and raveling. The alternatives considered for analysis were base alternative with crack sealing and patching, overlay with 40 mm BC using ordinary bitumen, overlay with 40 mm BC using Natural Rubber Modified Bitumen and an overlay of Ultra Thin White Topping. Economic analysis of these options was done considering the Life Cycle Cost (LCC). The average speed that can be obtained by applying these options were also compared. The results were in favour of Ultra Thin White Topping over flexible pavements. Hence, Design Charts were also plotted for estimation of maximum wheel load stresses for different slab thickness under different soil conditions. The design charts showed the maximum stress for a particular slab thickness and different soil conditions incorporating different k values. These charts can be handy for a design engineer. Fuzzy rule based models developed for site specific conditions were compared with regression models developed using SPSS. The Riding Comfort Index (RCI) was calculated and correlated with unevenness to develop a relationship. Relationships were developed between Skid Number and Macro Texture of the pavement. The effort made through this research work will be helpful to highway engineers in understanding the behaviour of flexible pavements in Kerala conditions and for arriving at suitable maintenance and rehabilitation strategies. Key Words: Flexible Pavements – Performance Evaluation – Urban Roads – NH – SH and other roads – Performance Models – Deflection – Riding Comfort Index – Skid Resistance – Texture Depth – Unevenness – Ultra Thin White Topping

The kinetics of thermal generation of flavour

Control and optimization of flavor is the ultimate challenge for the food and flavor industry. The major route to flavor formation during thermal processing is the Maillard reaction, which is a complex cascade of interdependent reactions initiated by the reaction between a reducing sugar and an amino compd. The complexity of the reaction means that researchers turn to kinetic modeling in order to understand the control points of the reaction and to manipulate the flavor profile. Studies of the kinetics of flavor formation have developed over the past 30 years from single- response empirical models of binary aq. systems to sophisticated multi-response models in food matrixes, based on the underlying chem., with the power to predict the formation of some key aroma compds. This paper discusses in detail the development of kinetic models of thermal generation of flavor and looks at the challenges involved in predicting flavor.

The role of sky conditions on gross primary production in a mixed deciduous forest

The role of different sky conditions on diffuse PAR fraction (ϕ), air temperature (Ta), vapor pressure deficit (vpd) and GPP in a deciduous forest is investigated using eddy covariance observations of CO2 fluxes and radiometer and ceilometer observations of sky and PAR conditions on hourly and growing season timescales. Maximum GPP response occurred under moderate to high PAR and ϕ and low vpd. Light response models using a rectangular hyperbola showed a positive linear relation between ϕ and effective quantum efficiency (α = 0.023ϕ + 0.012, r2 = 0.994). Since PAR and ϕ are negatively correlated, there is a tradeoff between the greater use efficiency of diffuse light and lower vpd and the associated decrease in total PAR available for photosynthesis. To a lesser extent, light response was also modified by vpd and Ta. The net effect of these and their relation with sky conditions helped enhance light response under sky conditions that produced higher ϕ. Six sky conditions were classified from cloud frequency and ϕ data: optically thick clouds, optically thin clouds, mixed sky (partial clouds within hour), high, medium and low optical aerosol. The frequency and light responses of each sky condition for the growing season were used to predict the role of changing sky conditions on annual GPP. The net effect of increasing frequency of thick clouds is to decrease GPP, changing low aerosol conditions has negligible effect. Increases in the other sky conditions all lead to gains in GPP. Sky conditions that enhance intermediate levels of ϕ, such as thin or scattered clouds or higher aerosol concentrations from volcanic eruptions or anthropogenic emissions, will have a positive outcome on annual GPP, while an increase in cloud cover will have a negative impact. Due to the ϕ/PAR tradeoff and since GPP response to changes in individual sky conditions differ in sign and magnitude, the net response of ecosystem GPP to future sky conditions is non-linear and tends toward moderation of change.

Bayesian inference for a skew-normal IRT model under the centred parameterization

Item response theory (IRT) comprises a set of statistical models which are useful in many fields, especially when there is interest in studying latent variables. These latent variables are directly considered in the Item Response Models (IRM) and they are usually called latent traits. A usual assumption for parameter estimation of the IRM, considering one group of examinees, is to assume that the latent traits are random variables which follow a standard normal distribution. However, many works suggest that this assumption does not apply in many cases. Furthermore, when this assumption does not hold, the parameter estimates tend to be biased and misleading inference can be obtained. Therefore, it is important to model the distribution of the latent traits properly. In this paper we present an alternative latent traits modeling based on the so-called skew-normal distribution; see Genton (2004). We used the centred parameterization, which was proposed by Azzalini (1985). This approach ensures the model identifiability as pointed out by Azevedo et al. (2009b). Also, a Metropolis Hastings within Gibbs sampling (MHWGS) algorithm was built for parameter estimation by using an augmented data approach. A simulation study was performed in order to assess the parameter recovery in the proposed model and the estimation method, and the effect of the asymmetry level of the latent traits distribution on the parameter estimation. Also, a comparison of our approach with other estimation methods (which consider the assumption of symmetric normality for the latent traits distribution) was considered. The results indicated that our proposed algorithm recovers properly all parameters. Specifically, the greater the asymmetry level, the better the performance of our approach compared with other approaches, mainly in the presence of small sample sizes (number of examinees). Furthermore, we analyzed a real data set which presents indication of asymmetry concerning the latent traits distribution. The results obtained by using our approach confirmed the presence of strong negative asymmetry of the latent traits distribution. (C) 2010 Elsevier B.V. All rights reserved.

Bayesian Estimation of the Logistic Positive Exponent IRT Model

A Bayesian inference approach using Markov Chain Monte Carlo (MCMC) is developed for the logistic positive exponent (LPE) model proposed by Samejima and for a new skewed Logistic Item Response Theory (IRT) model, named Reflection LPE model. Both models lead to asymmetric item characteristic curves (ICC) and can be appropriate because a symmetric ICC treats both correct and incorrect answers symmetrically, which results in a logical contradiction in ordering examinees on the ability scale. A data set corresponding to a mathematical test applied in Peruvian public schools is analyzed, where comparisons with other parametric IRT models also are conducted. Several model comparison criteria are discussed and implemented. The main conclusion is that the LPE and RLPE IRT models are easy to implement and seem to provide the best fit to the data set considered.

Knowledge disclosure as a weapon in technological change battles: straight shot or backfire?

This work aims at evaluating how effective is knowledge disclosure in attenuating institutional negative reactions caused by uncertainties brought by firms’ new strategies that respond to novel technologies. The empirical setting is from an era of technological ferment, the period of the introduction of the voice over internet protocol (VoIP) in the USA in the early 2000’s. This technology led to the convergence of the wireline telecommu- nications and cable television industries. The Institutional Brokers’ Estimate System (also known as the I/B/E/S system) was used to capture reactions of securities analysts, a revealed important source of institutional pressure on firms’ strategies. For assessing knowledge disclosure, a coding technique and a established content analysis framework were used to quantitatively measure the non-numerical and unstructured data of transcripts of business events occurred at that time. Eventually, several binary response models were tested in order to assess the effect of knowledge disclosure on the probability of institutional positive reactions. The findings are that the odds of favorable institutional reactions increase when a specific kind of knowledge is disclosed. It can be concluded that knowledge disclosure can be considered as a weapon in technological changes situations, attenuating adverse institutional reactions to the companies’ strategies in environments of technological changes.

Respostas funcionais de diferentes tamanhos de Tilápia do Nilo; Oreochromis niloticus; predando zooplâncton

The Nile tilapia, Oreochromis niloticus, is an important omnivorous fish in the reservoirs of the semi-arid region of Brazil. Throughout its growth tilapia s feeding behavior changes from a visual predator of zooplankton to a filter-feeder, collecting suspended particulate matter, including planktonic organisms, through pumping. This feature results in different impacts of tilapia on plankton community as the fish grows. Aiming to quantify the functional response of different sizes of Nile tilapia on zooplankton experiments in microcosms scale in the laboratory and in mesocosm scale in the field were carried out. The data were fitted to four different models of functional response. The best fits were obtained for nonlinear models in laboratory experiments. While the experiments in mesocosms were the best settings for responses of type I (juvenile and adult tilapia) and type III (fry). The Manly's alpha index was used to evaluate the feeding selectivity of tilapia on the three main groups of the zooplankton in the experiments in mesocosms. The results show that: (i) rotifers were the preferred prey of fingerlings,(ii) copepods were rejected by fry and juvenile tilapia and (iii) adult fish fed non-selectively on copepods, cladocerans and rotifers. The functional response models obtained in this research can be applied to population models and help in modeling the dynamics of interactions between Nile tilapia and the planktonic communities in the reservoirs of the semi-arid

Parameter recovery for a skew-normal IRT model under a Bayesian approach: hierarchical framework, prior and kernel sensitivity and sample size

Item response theory (IRT) comprises a set of statistical models which are useful in many fields, especially when there is an interest in studying latent variables (or latent traits). Usually such latent traits are assumed to be random variables and a convenient distribution is assigned to them. A very common choice for such a distribution has been the standard normal. Recently, Azevedo et al. [Bayesian inference for a skew-normal IRT model under the centred parameterization, Comput. Stat. Data Anal. 55 (2011), pp. 353-365] proposed a skew-normal distribution under the centred parameterization (SNCP) as had been studied in [R. B. Arellano-Valle and A. Azzalini, The centred parametrization for the multivariate skew-normal distribution, J. Multivariate Anal. 99(7) (2008), pp. 1362-1382], to model the latent trait distribution. This approach allows one to represent any asymmetric behaviour concerning the latent trait distribution. Also, they developed a Metropolis-Hastings within the Gibbs sampling (MHWGS) algorithm based on the density of the SNCP. They showed that the algorithm recovers all parameters properly. Their results indicated that, in the presence of asymmetry, the proposed model and the estimation algorithm perform better than the usual model and estimation methods. Our main goal in this paper is to propose another type of MHWGS algorithm based on a stochastic representation (hierarchical structure) of the SNCP studied in [N. Henze, A probabilistic representation of the skew-normal distribution, Scand. J. Statist. 13 (1986), pp. 271-275]. Our algorithm has only one Metropolis-Hastings step, in opposition to the algorithm developed by Azevedo et al., which has two such steps. This not only makes the implementation easier but also reduces the number of proposal densities to be used, which can be a problem in the implementation of MHWGS algorithms, as can be seen in [R.J. Patz and B.W. Junker, A straightforward approach to Markov Chain Monte Carlo methods for item response models, J. Educ. Behav. Stat. 24(2) (1999), pp. 146-178; R. J. Patz and B. W. Junker, The applications and extensions of MCMC in IRT: Multiple item types, missing data, and rated responses, J. Educ. Behav. Stat. 24(4) (1999), pp. 342-366; A. Gelman, G.O. Roberts, and W.R. Gilks, Efficient Metropolis jumping rules, Bayesian Stat. 5 (1996), pp. 599-607]. Moreover, we consider a modified beta prior (which generalizes the one considered in [3]) and a Jeffreys prior for the asymmetry parameter. Furthermore, we study the sensitivity of such priors as well as the use of different kernel densities for this parameter. Finally, we assess the impact of the number of examinees, number of items and the asymmetry level on the parameter recovery. Results of the simulation study indicated that our approach performed equally as well as that in [3], in terms of parameter recovery, mainly using the Jeffreys prior. Also, they indicated that the asymmetry level has the highest impact on parameter recovery, even though it is relatively small. A real data analysis is considered jointly with the development of model fitting assessment tools. The results are compared with the ones obtained by Azevedo et al. The results indicate that using the hierarchical approach allows us to implement MCMC algorithms more easily, it facilitates diagnosis of the convergence and also it can be very useful to fit more complex skew IRT models.

Modelagem de dados de resposta ao item sob efeito de speededness

Em testes nos quais uma quantidade considerável de indivíduos não dispõe de tempo suciente para responder todos os itens temos o que é chamado de efeito de Speededness. O uso do modelo unidimensional da Teoria da Resposta ao Item (TRI) em testes com speededness pode nos levar a uma série de interpretações errôneas uma vez que nesse modelo é suposto que os respondentes possuem tempo suciente para responder todos os itens. Nesse trabalho, desenvolvemos uma análise Bayesiana do modelo tri-dimensional da TRI proposto por Wollack e Cohen (2005) considerando uma estrutura de dependência entre as distribuições a priori dos traços latentes a qual modelamos com o uso de cópulas. Apresentamos um processo de estimação para o modelo proposto e fazemos um estudo de simulação comparativo com a análise realizada por Bazan et al. (2010) na qual foi utilizada distribuições a priori independentes para os traços latentes. Finalmente, fazemos uma análise de sensibilidade do modelo em estudo e apresentamos uma aplicação levando em conta um conjunto de dados reais proveniente de um subteste do EGRA, chamado de Nonsense Words, realizado no Peru em 2007. Nesse subteste os alunos são avaliados por via oral efetuando a leitura, sequencialmente, de 50 palavras sem sentidos em 60 segundos o que caracteriza a presença do efeito speededness.

Les pratiques d’intervention policières auprès des personnes en crise ou atteintes de troubles mentaux : le cas des agents de réponse en intervention de crise du Service de police de la Ville de Montréal

Cette recherche porte sur les pratiques d’intervention des agents de réponse en intervention de crise (RIC), de leur partenaire fixe et des agents en attente de la formation du Service de police de la Ville de Montréal (SPVM) auprès des personnes en crise ou atteintes de troubles mentaux. Les agents RIC sont des patrouilleurs de première ligne qui ont reçu une formation complète sur les principes d’intervention en contexte de crise ou de santé mentale. Ce modèle de réponse spécialisée est une solution proactive qui a pour but d’améliorer l’action policière en situation de crise et de veiller à une meilleure prise en charge de ces personnes par les ressources institutionnelles. La désinstitutionnalisation des soins et des services psychiatriques a eu pour effet une augmentation du nombre de personnes atteintes de troubles mentaux dans la communauté. Par conséquent, cet accroissement a engendré des rapports plus fréquents entre les services policiers et cette clientèle. Les interventions en contexte de crise ou de santé mentale sont particulières et complexes, de même qu’elles requièrent un niveau supérieur de compréhension des crises humaines. Les autorités policières ont admis que ces interventions représentent une part significative de leur travail et que la formation policière traditionnelle ne les prépare pas suffisamment pour intervenir adéquatement auprès de cette population. En réponse à ces considérations et dans l’objectif d’améliorer leur capacité d’agir, les forces policières se sont dotées de modèles de réponse policière spécialisée en intervention de crise. L’approche la plus répandue est l’équipe d’intervention de crise (« crisis intervention team » ou « CIT »), aussi appelée le modèle de Memphis. Il existe plusieurs variantes de ce modèle, mais les composantes principales, c’est-à-dire la formation avancée et la consolidation d’un partenariat avec le système de santé demeurent dans l’ensemble de ces structures. L’objectif de cette recherche consiste à sonder les perceptions des agents RIC, de leur partenaire fixe et des agents en attente de la formation afin de comprendre et de contraster leurs visions et leurs pratiques d’intervention en contexte de crise ou de santé mentale. Chaque groupe a apporté des précisions intéressantes. Nous avons conduit 12 entrevues qualitatives avec des policiers du SPVM. De façon générale, les participants rapportent que leurs pratiques d’intervention auprès des personnes en crise ou atteintes de troubles mentaux sont davantage ancrées dans une perspective de relation d’aide. Ils mentionnent également que la communication, l’écoute et la confiance doivent être privilégiées avant tout autre stratégie dans les situations qui les permettent et que la force doit être employée seulement lorsqu’elle est nécessaire, c’est-à-dire lorsque leur sécurité ou celle d’autrui est en péril ou lorsque la communication n’est pas possible. Puis, ils admettent que le recours à l’expertise des intervenants en santé mentale permet une analyse plus approfondie de la situation et de l’état mental de la personne visée par l’intervention. D’autre part, en ce qui concerne les limites de la formation policière traditionnelle, les candidats ont soulevé qu’il y a un manque de connaissances en matière de santé mentale ainsi qu’une difficulté associée à l’évaluation de l’état de la personne et du besoin de transport ont été soulevés. Sur le plan des apprentissages, les agents RIC disent avoir une compréhension plus globale de la problématique de santé mentale, de meilleures habiletés communicationnelles, une analyse plus approfondie de la situation, de plus grandes connaissances juridiques, une compréhension du fonctionnement des services hospitaliers ainsi qu’une appréciation particulière pour le partage de savoirs et les principes d’endiguement. Ils font part également de l’importance des rapports pour documenter l’évolution de l’état mental d’une personne et ils ajoutent que la dimension temporelle joue un rôle clé dans la résolution définitive de la problématique. Au sujet des partenaires, ils évoquent des retombées similaires. Toutefois, à la suite de la formation, ils reconnaissent davantage l’importance de leur rôle dans la sécurité de leur partenaire et ils y accordent dorénavant une attention marquée lors de ces interventions. Enfin, les agents non formés formulent des attentes relatives au développement d’outils et de compétences, ce qui leur sera rendu dans la formation RIC. Globalement, les agents RIC et les partenaires interviewés ont modifié leurs pratiques pour les arrimer avec la philosophie des interventions en contexte de crise ou de santé mentale. Ils ont également davantage confiance en leurs capacités et habiletés d’intervention auprès des personnes en crise ou atteintes de troubles mentaux grâce aux connaissances acquises dans la formation.

Les pratiques d’intervention policières auprès des personnes en crise ou atteintes de troubles mentaux : le cas des agents de réponse en intervention de crise du Service de police de la Ville de Montréal

Cette recherche porte sur les pratiques d’intervention des agents de réponse en intervention de crise (RIC), de leur partenaire fixe et des agents en attente de la formation du Service de police de la Ville de Montréal (SPVM) auprès des personnes en crise ou atteintes de troubles mentaux. Les agents RIC sont des patrouilleurs de première ligne qui ont reçu une formation complète sur les principes d’intervention en contexte de crise ou de santé mentale. Ce modèle de réponse spécialisée est une solution proactive qui a pour but d’améliorer l’action policière en situation de crise et de veiller à une meilleure prise en charge de ces personnes par les ressources institutionnelles. La désinstitutionnalisation des soins et des services psychiatriques a eu pour effet une augmentation du nombre de personnes atteintes de troubles mentaux dans la communauté. Par conséquent, cet accroissement a engendré des rapports plus fréquents entre les services policiers et cette clientèle. Les interventions en contexte de crise ou de santé mentale sont particulières et complexes, de même qu’elles requièrent un niveau supérieur de compréhension des crises humaines. Les autorités policières ont admis que ces interventions représentent une part significative de leur travail et que la formation policière traditionnelle ne les prépare pas suffisamment pour intervenir adéquatement auprès de cette population. En réponse à ces considérations et dans l’objectif d’améliorer leur capacité d’agir, les forces policières se sont dotées de modèles de réponse policière spécialisée en intervention de crise. L’approche la plus répandue est l’équipe d’intervention de crise (« crisis intervention team » ou « CIT »), aussi appelée le modèle de Memphis. Il existe plusieurs variantes de ce modèle, mais les composantes principales, c’est-à-dire la formation avancée et la consolidation d’un partenariat avec le système de santé demeurent dans l’ensemble de ces structures. L’objectif de cette recherche consiste à sonder les perceptions des agents RIC, de leur partenaire fixe et des agents en attente de la formation afin de comprendre et de contraster leurs visions et leurs pratiques d’intervention en contexte de crise ou de santé mentale. Chaque groupe a apporté des précisions intéressantes. Nous avons conduit 12 entrevues qualitatives avec des policiers du SPVM. De façon générale, les participants rapportent que leurs pratiques d’intervention auprès des personnes en crise ou atteintes de troubles mentaux sont davantage ancrées dans une perspective de relation d’aide. Ils mentionnent également que la communication, l’écoute et la confiance doivent être privilégiées avant tout autre stratégie dans les situations qui les permettent et que la force doit être employée seulement lorsqu’elle est nécessaire, c’est-à-dire lorsque leur sécurité ou celle d’autrui est en péril ou lorsque la communication n’est pas possible. Puis, ils admettent que le recours à l’expertise des intervenants en santé mentale permet une analyse plus approfondie de la situation et de l’état mental de la personne visée par l’intervention. D’autre part, en ce qui concerne les limites de la formation policière traditionnelle, les candidats ont soulevé qu’il y a un manque de connaissances en matière de santé mentale ainsi qu’une difficulté associée à l’évaluation de l’état de la personne et du besoin de transport ont été soulevés. Sur le plan des apprentissages, les agents RIC disent avoir une compréhension plus globale de la problématique de santé mentale, de meilleures habiletés communicationnelles, une analyse plus approfondie de la situation, de plus grandes connaissances juridiques, une compréhension du fonctionnement des services hospitaliers ainsi qu’une appréciation particulière pour le partage de savoirs et les principes d’endiguement. Ils font part également de l’importance des rapports pour documenter l’évolution de l’état mental d’une personne et ils ajoutent que la dimension temporelle joue un rôle clé dans la résolution définitive de la problématique. Au sujet des partenaires, ils évoquent des retombées similaires. Toutefois, à la suite de la formation, ils reconnaissent davantage l’importance de leur rôle dans la sécurité de leur partenaire et ils y accordent dorénavant une attention marquée lors de ces interventions. Enfin, les agents non formés formulent des attentes relatives au développement d’outils et de compétences, ce qui leur sera rendu dans la formation RIC. Globalement, les agents RIC et les partenaires interviewés ont modifié leurs pratiques pour les arrimer avec la philosophie des interventions en contexte de crise ou de santé mentale. Ils ont également davantage confiance en leurs capacités et habiletés d’intervention auprès des personnes en crise ou atteintes de troubles mentaux grâce aux connaissances acquises dans la formation.

Precautionary principles: a jurisdiction-free framework for decision-making under risk

Fundamental principles of precaution are legal maxims that ask for preventive actions, perhaps as contingent interim measures while relevant information about causality and harm remains unavailable, to minimize the societal impact of potentially severe or irreversible outcomes. Such principles do not explain how to make choices or how to identify what is protective when incomplete and inconsistent scientific evidence of causation characterizes the potential hazards. Rather, they entrust lower jurisdictions, such as agencies or authorities, to make current decisions while recognizing that future information can contradict the scientific basis that supported the initial decision. After reviewing and synthesizing national and international legal aspects of precautionary principles, this paper addresses the key question: How can society manage potentially severe, irreversible or serious environmental outcomes when variability, uncertainty, and limited causal knowledge characterize their decision-making? A decision-analytic solution is outlined that focuses on risky decisions and accounts for prior states of information and scientific beliefs that can be updated as subsequent information becomes available. As a practical and established approach to causal reasoning and decision-making under risk, inherent to precautionary decision-making, these (Bayesian) methods help decision-makers and stakeholders because they formally account for probabilistic outcomes, new information, and are consistent and replicable. Rational choice of an action from among various alternatives-defined as a choice that makes preferred consequences more likely-requires accounting for costs, benefits and the change in risks associated with each candidate action. Decisions under any form of the precautionary principle reviewed must account for the contingent nature of scientific information, creating a link to the decision-analytic principle of expected value of information (VOI), to show the relevance of new information, relative to the initial ( and smaller) set of data on which the decision was based. We exemplify this seemingly simple situation using risk management of BSE. As an integral aspect of causal analysis under risk, the methods developed in this paper permit the addition of non-linear, hormetic dose-response models to the current set of regulatory defaults such as the linear, non-threshold models. This increase in the number of defaults is an important improvement because most of the variants of the precautionary principle require cost-benefit balancing. Specifically, increasing the set of causal defaults accounts for beneficial effects at very low doses. We also show and conclude that quantitative risk assessment dominates qualitative risk assessment, supporting the extension of the set of default causal models.

Estimating the SCAN*PRO model of store sales: HB, FM or just OLS?

In this paper we investigate whether consideration of store-level heterogeneity in marketing mix effects improves the accuracy of the marketing mix elasticities, fit, and forecasting accuracy of the widely-applied SCAN*PRO model of store sales. Models with continuous and discrete representations of heterogeneity, estimated using hierarchical Bayes (HB) and finite mixture (FM) techniques, respectively, are empirically compared to the original model, which does not account for store-level heterogeneity in marketing mix effects, and is estimated using ordinary least squares (OLS). The empirical comparisons are conducted in two contexts: Dutch store-level scanner data for the shampoo product category, and an extensive simulation experiment. The simulation investigates how between- and within-segment variance in marketing mix effects, error variance, the number of weeks of data, and the number of stores impact the accuracy of marketing mix elasticities, model fit, and forecasting accuracy. Contrary to expectations, accommodating store-level heterogeneity does not improve the accuracy of marketing mix elasticities relative to the homogeneous SCAN*PRO model, suggesting that little may be lost by employing the original homogeneous SCAN*PRO model estimated using ordinary least squares. Improvements in fit and forecasting accuracy are also fairly modest. We pursue an explanation for this result since research in other contexts has shown clear advantages from assuming some type of heterogeneity in market response models. In an Afterthought section, we comment on the controversial nature of our result, distinguishing factors inherent to household-level data and associated models vs. general store-level data and associated models vs. the unique SCAN*PRO model specification.