The Patientʼs Perception of Eosinophilic Esophagitis Related Symptoms: a Qualitative Content Analysis

Background and Aims: The international EEsAI study group is currently developing an activity index for Eosinophilic Esophagitis (EoE). A potential discrepancy between patient and physician reported EoE symptoms has not been assessed yet. Therefore, we aimed to evaluate patient reported items describing their EoE activity and to compare these with the physicianʼs perception. Methods: A questionnaire was sent to 100 EoE patients in Switzerland. EoE-related symptoms dependent and independent of food intake were reported by patients. Results were analyzed using a qualitative content analysis and compared with symptoms reported by international EoE experts in Delphi rounds. Results: The questionnaire response rate was 64/100. The following items were developed by combining categories based on patients answers: food-consistency related dysphagia, frequency and severity of dysphagia, food impaction, strategies to avoid food impaction, food allergy, drinking-related retrosternal pain. The following food categories associated with dysphagia were identified: meat, rice, dry bread, French fries, raw, fibrous foods, others. Sports and psychological stress were identified as triggers for non-food intake related EoE symptoms. A good correlation was found between patient and physicianʼs reported EoE related symptoms. Conclusions: There is a good correlation between patient reported symptoms and the physicianʼs perception of clinical items as reported by international EoE experts. These patient reported outcomes will now be incorporated into the EEsAI questionnaire that measures EoE activity.

Empirical determination of the very high energy heavy quark cross section from nonaccelerator data

To cosmic rays incident near the horizon the Earth's atmosphere represents a beam dump with a slant depth reaching 36 000 g cm-2 at 90. The prompt decay of a heavy quark produced by very high energy cosmic ray showers will leave an unmistakable signature in this dump. We translate the failure of experiments to detect such a signal into an upper limit on the heavy quark hadroproduction cross section in the energy region beyond existing accelerators. Our results disfavor any rapid growth of the cross section or the gluon structure function beyond conservative estimates based on perturbative QCD.

L'insertion sociale plurielle des femmes cadres supérieurs en Suisse : contribution à l'étude du bien-être subjectif au quotidien : approche qualitative intégrative

RESUME« L'insertion sociale plurielle des femmes cadres supérieurs en Suisse. Contribution à l'étude du bien-être subjectif au quotidien. Approche intégrative qualitative. »Depuis une quarantaine d'années, nombreux sont les travaux qui étudient les relations entre les différents milieux de vie au quotidien et, plus particulièrement, l'impact de leurs articulations singulières sur la santé. Nous y identifions deux axes principaux : l'un aborde ce phénomène selon une perspective de « conflit travail-famille » en termes de « stress », l'autre se focalise davantage sur la promotion du « bien-être » au travers d'une approche d'« équilibre travail-vie ». Or, l'ensemble de ces recherches considère comme «pathogènes» les désajustements, les contradictions et les tensions vécus au quotidien. Selon cette tendance, le « bien-être » apparaît comme un état d'équilibre ultime indépendant du contexte de vie du sujet. Toutefois, peu de recherches portent sur la dimension située du bien-être dans son rapport à l'activité concrète au sein des milieux deNotre étude s'intéresse à cette question auprès des femmes cadres supérieurs, selon une perspective critique et développementale en psychologie de la santé (Lyons & Chamberlain, 2006 ; Santiago-Delefosse, 2002,2011 ; Malrieu, 1989 ; Vygotski, 1985). En effet, cette population constitue un terrain privilégié pour comprendre le sens donné à l'activité à partir des contraintes, responsabilités et demandes perçues dans des contextes parfois contradictoires, et pour analyser le rôle de ces derniers dans un bien-être subjectif.En cohérence avec notre positionnement théorique, nous avons mené des entretiens qualitatifs focalisés sur l'activité quotidienne auprès de 20 femmes, et ceci en deux temps (T1-T2) (40 entretiens). Les résultats issus des analyses du contenu des discours permettent de définir le vécu de l'articulation des milieux de vie chez nos participantes, selon trois axes à la fois interdépendants et autonomes. Chaque axe se définit par une série de supports spécifiques jouant un rôle structurant dans leur bien-être subjectif. Ainsi, le premier axe se caractérise par des supports de maîtrise subjective, ainsi que par l'appropriation de contraintes sociales et corporelles, selon un rythme de l'activité soutenu. Le deuxième s'accompagne de supports qui favorisent la prise de distance au travers du relâchement du rythme et du lâcher prise de la maîtrise, par la création d'espaces personnels et sociaux « pour soi ». Enfin, le troisième porte sur le positionnement de soi par rapport à autrui en termes de « personnalisation ».Construits en rapport à la corporéité et à autrui au sein de contextes spécifiques, ces différents supports prennent leur sens au sein d'un système de pratiques global, unique pour chaque femme. Selon cette conception critique, le bien-être subjectif chez les femmes cadres se définit comme le fruit d'un processus mouvant issu des tensions vécues entre les trois axes de l'articulation des milieux de vie. Il est par conséquent social, corporel et psychologique.Nos résultats ouvrent des perspectives de recherche et d'intervention, notamment en santé et travail. Ces ouvertures sont orientées vers une approche intégrative en psychologie de la santé, c'est-à-dire, de la prise en compte dans des questions de santé et de bien-être du processus de construction du sujet en relation à son insertion sociale plurielle.ABSTRACT« Plural social participation among women senior managers in Switzerland. Contribution to the study of subjective well-being in everyday life. An integrative and qualitativeapproach.»For the last forty years, a large body of literature has studied the relationships between different social realms in everyday life and, more particularly, the impact of their singular intertwinements with health. We identify two main trends : The first one focuses on this phenomenon through the « work-family conflict » perspective in terms of « stress » whilst the second one is more concerned by the promotion of « well-being » through a « work-life balance » approach. However, both of these trends consider disadjustments, contradictions and tensions in everyday life as « pathogenic ». According to this conception, « well- being » appears as an ultimate state of balance which is indépendant from the subject's life context. Nevertheless, few studies have examined the situated dimension of well-being in its link to concrete activity in social realms.Our research is concerned with this issue among women senior managers from a critical and developmental perspective in Health Psychology (Lyons & Chamberlain, 2006 ; Santiago-Delefosse, 2002, 2011 ; Malrieu, 1989 ; Vygotski, 1985). In fact, this population represents a favourable field so as to study : how the meaning of daily activity is constructed accross different and often conflictive social realms ; to understand the many ways in which this population deals with perceived constraints, responsibilities and requests, and to analyse the role of situated plural activity in subjective well-being.Consitent with our theoretical framework, we have designed a qualitative method. We have conducted two-time (T1-T2) interviews with 20 women by focusing on their daily activity (40 interviews). The Thematic Content Analysis reveals that four different social realms are articulated among our participants through three main axes, which are at the same time interdependent and autonomous. Each one of these axis is defined by a certain number of specific supports that play an important role in these women's subjective well- being. The first axis is concerned by several supports that signify a « feeling of control » along with the appropriation of social and body constraints by means of a rapid pace of activity. The second one regards the use of supports that contribute to « put things into perspective » by means of the slowing down of the pace of activity and through letting go of the feeling of control. This mechanism includes the creation of personal and social spaces of « one's own ». The third axis is defined by the positioning of the self in regard to others through a process of « personnalization ».Developed in specific contexts through the intertwinnements between the body and social others, supports belonging to these axes acquire significance and meaning on the basis of their relationship to a global system of activities of which they are part. However, this articulation is uniquely defined for each participant. According to this critical approach, subjective well-being among women senior managers emerges as a meaningful and changing process, situated in a plural social context. This is, it appears as the result of conflictual interactions defining the three different axis that we have identified. Subjective well-being is hence a social, embodied and psychological phenomena that is closely linked to the articulation of different social realms. Our findings open new research and practice perspectives, especially concerning health and work issues. These perspectives convey an integrative approach in Health Psychology by considering health and well-being by taking into account the process of construction of the subject in regard to his or her plural social participation.

MORM--a Petri net based model for assessing OH&S risks in industrial processes: modeling qualitative aspects.

Because of the increase in workplace automation and the diversification of industrial processes, workplaces have become more and more complex. The classical approaches used to address workplace hazard concerns, such as checklists or sequence models, are, therefore, of limited use in such complex systems. Moreover, because of the multifaceted nature of workplaces, the use of single-oriented methods, such as AEA (man oriented), FMEA (system oriented), or HAZOP (process oriented), is not satisfactory. The use of a dynamic modeling approach in order to allow multiple-oriented analyses may constitute an alternative to overcome this limitation. The qualitative modeling aspects of the MORM (man-machine occupational risk modeling) model are discussed in this article. The model, realized on an object-oriented Petri net tool (CO-OPN), has been developed to simulate and analyze industrial processes in an OH&S perspective. The industrial process is modeled as a set of interconnected subnets (state spaces), which describe its constitutive machines. Process-related factors are introduced, in an explicit way, through machine interconnections and flow properties. While man-machine interactions are modeled as triggering events for the state spaces of the machines, the CREAM cognitive behavior model is used in order to establish the relevant triggering events. In the CO-OPN formalism, the model is expressed as a set of interconnected CO-OPN objects defined over data types expressing the measure attached to the flow of entities transiting through the machines. Constraints on the measures assigned to these entities are used to determine the state changes in each machine. Interconnecting machines implies the composition of such flow and consequently the interconnection of the measure constraints. This is reflected by the construction of constraint enrichment hierarchies, which can be used for simulation and analysis optimization in a clear mathematical framework. The use of Petri nets to perform multiple-oriented analysis opens perspectives in the field of industrial risk management. It may significantly reduce the duration of the assessment process. But, most of all, it opens perspectives in the field of risk comparisons and integrated risk management. Moreover, because of the generic nature of the model and tool used, the same concepts and patterns may be used to model a wide range of systems and application fields.

A Qualitative Exploration of the Psychological Contents and Dynamics of Momentum in Sport

While studies on triggers and outcomes of Psychological Momentum (PM) exist, little is known about the dynamics by which PM emerges and develops over time. Based on video-assisted recalls of PM experiences in table tennis and swimming competitions, this research qualitatively explored the triggering processes, contents, and the development of PM over time. PM was found to be triggered by mechanisms of dissonance, consonance, or fear of not winning. During the PM experience, participants reported a variety of perceptions, affects and emotions, cognitions, and behaviors, and PM was found to develop through processes of amplification that sometimes ended with a reduction of efforts when the victory or defeat was perceived as certain. These findings are discussed in light of theories on self-regulation and reactance-helplessness. From a practical standpoint, achievement goal-based strategies are suggested, since mastery-approach goals were found to be endorsed to maintain positive PM and overcome negative PM

Estimation of jump-diffusion processes via empirical characteristic functions

Preface The starting point for this work and eventually the subject of the whole thesis was the question: how to estimate parameters of the affine stochastic volatility jump-diffusion models. These models are very important for contingent claim pricing. Their major advantage, availability T of analytical solutions for characteristic functions, made them the models of choice for many theoretical constructions and practical applications. At the same time, estimation of parameters of stochastic volatility jump-diffusion models is not a straightforward task. The problem is coming from the variance process, which is non-observable. There are several estimation methodologies that deal with estimation problems of latent variables. One appeared to be particularly interesting. It proposes the estimator that in contrast to the other methods requires neither discretization nor simulation of the process: the Continuous Empirical Characteristic function estimator (EGF) based on the unconditional characteristic function. However, the procedure was derived only for the stochastic volatility models without jumps. Thus, it has become the subject of my research. This thesis consists of three parts. Each one is written as independent and self contained article. At the same time, questions that are answered by the second and third parts of this Work arise naturally from the issues investigated and results obtained in the first one. The first chapter is the theoretical foundation of the thesis. It proposes an estimation procedure for the stochastic volatility models with jumps both in the asset price and variance processes. The estimation procedure is based on the joint unconditional characteristic function for the stochastic process. The major analytical result of this part as well as of the whole thesis is the closed form expression for the joint unconditional characteristic function for the stochastic volatility jump-diffusion models. The empirical part of the chapter suggests that besides a stochastic volatility, jumps both in the mean and the volatility equation are relevant for modelling returns of the S&P500 index, which has been chosen as a general representative of the stock asset class. Hence, the next question is: what jump process to use to model returns of the S&P500. The decision about the jump process in the framework of the affine jump- diffusion models boils down to defining the intensity of the compound Poisson process, a constant or some function of state variables, and to choosing the distribution of the jump size. While the jump in the variance process is usually assumed to be exponential, there are at least three distributions of the jump size which are currently used for the asset log-prices: normal, exponential and double exponential. The second part of this thesis shows that normal jumps in the asset log-returns should be used if we are to model S&P500 index by a stochastic volatility jump-diffusion model. This is a surprising result. Exponential distribution has fatter tails and for this reason either exponential or double exponential jump size was expected to provide the best it of the stochastic volatility jump-diffusion models to the data. The idea of testing the efficiency of the Continuous ECF estimator on the simulated data has already appeared when the first estimation results of the first chapter were obtained. In the absence of a benchmark or any ground for comparison it is unreasonable to be sure that our parameter estimates and the true parameters of the models coincide. The conclusion of the second chapter provides one more reason to do that kind of test. Thus, the third part of this thesis concentrates on the estimation of parameters of stochastic volatility jump- diffusion models on the basis of the asset price time-series simulated from various "true" parameter sets. The goal is to show that the Continuous ECF estimator based on the joint unconditional characteristic function is capable of finding the true parameters. And, the third chapter proves that our estimator indeed has the ability to do so. Once it is clear that the Continuous ECF estimator based on the unconditional characteristic function is working, the next question does not wait to appear. The question is whether the computation effort can be reduced without affecting the efficiency of the estimator, or whether the efficiency of the estimator can be improved without dramatically increasing the computational burden. The efficiency of the Continuous ECF estimator depends on the number of dimensions of the joint unconditional characteristic function which is used for its construction. Theoretically, the more dimensions there are, the more efficient is the estimation procedure. In practice, however, this relationship is not so straightforward due to the increasing computational difficulties. The second chapter, for example, in addition to the choice of the jump process, discusses the possibility of using the marginal, i.e. one-dimensional, unconditional characteristic function in the estimation instead of the joint, bi-dimensional, unconditional characteristic function. As result, the preference for one or the other depends on the model to be estimated. Thus, the computational effort can be reduced in some cases without affecting the efficiency of the estimator. The improvement of the estimator s efficiency by increasing its dimensionality faces more difficulties. The third chapter of this thesis, in addition to what was discussed above, compares the performance of the estimators with bi- and three-dimensional unconditional characteristic functions on the simulated data. It shows that the theoretical efficiency of the Continuous ECF estimator based on the three-dimensional unconditional characteristic function is not attainable in practice, at least for the moment, due to the limitations on the computer power and optimization toolboxes available to the general public. Thus, the Continuous ECF estimator based on the joint, bi-dimensional, unconditional characteristic function has all the reasons to exist and to be used for the estimation of parameters of the stochastic volatility jump-diffusion models.

DEA does not like positive discrimination : a comparison of alternative models based on empirical data

Due to the existence of free software and pedagogical guides, the use of data envelopment analysis (DEA) has been further democratized in recent years. Nowadays, it is quite usual for practitioners and decision makers with no or little knowledge in operational research to run themselves their own efficiency analysis. Within DEA, several alternative models allow for an environment adjustment. Five alternative models, each of them easily accessible to and achievable by practitioners and decision makers, are performed using the empirical case of the 90 primary schools of the State of Geneva, Switzerland. As the State of Geneva practices an upstream positive discrimination policy towards schools, this empirical case is particularly appropriate for an environment adjustment. The alternative of the majority of DEA models deliver divergent results. It is a matter of concern for applied researchers and a matter of confusion for practitioners and decision makers. From a political standpoint, these diverging results could lead to potentially opposite decisions. Grâce à l'existence de logiciels en libre accès et de guides pédagogiques, la méthode data envelopment analysis (DEA) s'est démocratisée ces dernières années. Aujourd'hui, il n'est pas rare que les décideurs avec peu ou pas de connaissances en recherche opérationnelle réalisent eux-mêmes leur propre analyse d'efficience. A l'intérieur de la méthode DEA, plusieurs modèles permettent de tenir compte des conditions plus ou moins favorables de l'environnement. Cinq de ces modèles, facilement accessibles et applicables par les décideurs, sont utilisés pour mesurer l'efficience des 90 écoles primaires du canton de Genève, Suisse. Le canton de Genève pratiquant une politique de discrimination positive envers les écoles défavorisées, ce cas pratique est particulièrement adapté pour un ajustement à l'environnement. La majorité des modèles DEA génèrent des résultats divergents. Ce constat est préoccupant pour les chercheurs appliqués et perturbant pour les décideurs. D'un point de vue politique, ces résultats divergents conduisent à des prises de décision différentes selon le modèle sur lequel elles sont fondées.

From Empirical Bayes to Full Bayes: Methods for Analysing Traffice Safety Data, October 25, 2004

Traffic safety engineers are among the early adopters of Bayesian statistical tools for analyzing crash data. As in many other areas of application, empirical Bayes methods were their first choice, perhaps because they represent an intuitively appealing, yet relatively easy to implement alternative to purely classical approaches. With the enormous progress in numerical methods made in recent years and with the availability of free, easy to use software that permits implementing a fully Bayesian approach, however, there is now ample justification to progress towards fully Bayesian analyses of crash data. The fully Bayesian approach, in particular as implemented via multi-level hierarchical models, has many advantages over the empirical Bayes approach. In a full Bayesian analysis, prior information and all available data are seamlessly integrated into posterior distributions on which practitioners can base their inferences. All uncertainties are thus accounted for in the analyses and there is no need to pre-process data to obtain Safety Performance Functions and other such prior estimates of the effect of covariates on the outcome of interest. In this slight, fully Bayesian methods may well be less costly to implement and may result in safety estimates with more realistic standard errors. In this manuscript, we present the full Bayesian approach to analyzing traffic safety data and focus on highlighting the differences between the empirical Bayes and the full Bayes approaches. We use an illustrative example to discuss a step-by-step Bayesian analysis of the data and to show some of the types of inferences that are possible within the full Bayesian framework.

From Empirical Bayes to Full Bayes: Methods for Analyzubg Traffic Safey Data, October 25, 2004

Traffic safety engineers are among the early adopters of Bayesian statistical tools for analyzing crash data. As in many other areas of application, empirical Bayes methods were their first choice, perhaps because they represent an intuitively appealing, yet relatively easy to implement alternative to purely classical approaches. With the enormous progress in numerical methods made in recent years and with the availability of free, easy to use software that permits implementing a fully Bayesian approach, however, there is now ample justification to progress towards fully Bayesian analyses of crash data. The fully Bayesian approach, in particular as implemented via multi-level hierarchical models, has many advantages over the empirical Bayes approach. In a full Bayesian analysis, prior information and all available data are seamlessly integrated into posterior distributions on which practitioners can base their inferences. All uncertainties are thus accounted for in the analyses and there is no need to pre-process data to obtain Safety Performance Functions and other such prior estimates of the effect of covariates on the outcome of interest. In this light, fully Bayesian methods may well be less costly to implement and may result in safety estimates with more realistic standard errors. In this manuscript, we present the full Bayesian approach to analyzing traffic safety data and focus on highlighting the differences between the empirical Bayes and the full Bayes approaches. We use an illustrative example to discuss a step-by-step Bayesian analysis of the data and to show some of the types of inferences that are possible within the full Bayesian framework.