Le médecin expert confronté aux confidences de la personne expertisée

During an expertise, if the expert “discovers” or is entrusted with information concerning an offence, should he report it to the authorities? Could the expert be sanctioned in the absence of denunciation of a tort or criminal act? The answer will be nuanced on a case-by-case basis. The expert confronted with the revelation of a crime or misdemeanor must decide in good conscience what he reveals in his report, or even report it to the prosecution.     

The effect of COVID-19 on home advantage in high- and low-stake situations: Evidence from the European national football competitions

The Covid-19 pandemic has significantly altered the way sporting events are observed. With the absence or limited presence of spectators in stadiums, the traditional advantage enjoyed by home teams has diminished considerably. This underscores the notion that the support of home fans can often be considered a key factor of the home advantage (HA) phenomenon, wherein teams perform better in front of their own supporters. However, the impact of reduced attendance on games with higher stakes, as opposed to low-stakes friendly matches, remains uncertain. In this study, we investigate the recently concluded European football championship (EURO 20), wherein several teams had the advantage of playing at home in high-stakes games with only one-third of the stadium capacity filled. Firstly, we demonstrate that the Covid-19 restrictions, leading to reduced fan attendance, resulted in a nearly 50% decrease in HA compared to the HA exhibited by the same teams during the qualification stage preceding EURO 20, even after accounting for team strength. Secondly, we show that while low-stakes friendly matches generally exhibit a smaller overall HA compared to high-stakes games, the absence of fans led to a similar reduction in HA during the low-stakes matches. Utilizing the recently developed Home Advantage Mediated (HAM) model (Bilalić, Gula, & Vaci, 2021, Scientific Reports, 21558), we were able to attribute the reduction in both high- and low-stakes games to poorer team performance, with no significant contribution from referee bias.     

Effect of Daily Life Reward Loop Functioning on the Course of Depression

Engagement in activities increases positive affect (Reward Path 1), which subsequently reinforces motivation (Reward Path 2), and hence future engagement in activities (Reward Path 3). Strong connections between these three reward loop components are considered adaptive, and might be disturbed in depression. Although some ecological nomentary assessment (EMA) studies have investigated the cross-sectional association between separate reward paths and individuals’ level of depression, no EMA study has looked into the association between individuals’ reward loop strength and depressive symptom course. The present EMA study assessed reward loop functioning (5x/day, 28 days) of 46 outpatients starting depression treatment at secondary mental health services and monitored with the Inventory of Depressive Symptomatology—Self-Report (IDS-SR) during a 7-month period. Results of multilevel regression analyses showed significant within-person associations for Reward Path 1 (b = 0.21, p < .001), Reward Path 2 (b = 0.43, p < .001), and Reward Path 3 (b = 0.20, p < .001). Stronger average reward loops (i.e., within-person mean of all reward paths) did not relate to participants’ improvement in depressive symptoms over time. Path-specific results revealed that Reward Paths 1 and 2 may have partly opposite effects on depressive symptom course. Together, our findings suggest that reward processes in daily life might be best studied separately and that further investigation is warranted to explore under what circumstances strong paths are adaptive or not.     

Extending exploratory diagnostic classification models: Inferring the effect of covariates

Diagnostic models provide a statistical framework for designing formative assessments by classifying student knowledge profiles according to a collection of fine-grained attributes. The context and ecosystem in which students learn may play an important role in skill mastery, and it is therefore important to develop methods for incorporating student covariates into diagnostic models. Including covariates may provide researchers and practitioners with the ability to evaluate novel interventions or understand the role of background knowledge in attribute mastery. Existing research is designed to include covariates in confirmatory diagnostic models, which are also known as restricted latent class models. We propose new methods for including covariates in exploratory RLCMs that jointly infer the latent structure and evaluate the role of covariates on performance and skill mastery. We present a novel Bayesian formulation and report a Markov chain Monte Carlo algorithm using a Metropolis-within-Gibbs algorithm for approximating the model parameter posterior distribution. We report Monte Carlo simulation evidence regarding the accuracy of our new methods and present results from an application that examines the role of student background knowledge on the mastery of a probability data set.     

A meta-analytic evaluation of diversity training outcomes across cultures

The extant literature on diversity training suggests that its effect size is small and varies across studies, calling for theorization on when and why diversity training does or does not work. In this article, we propose that the national cultural context is a critical moderator and conduct a meta-analysis to examine its influence on diversity training. Our analyses show that the average effect size of diversity training outcomes is significant both inside and outside the U.S. The effect size of specific diversity training design is contingent on such cultural values as power distance, individualism, masculinity, and uncertainty avoidance. We conclude our review by providing future directions for cross-cultural research on diversity training.     

A teaching framework for cross-cultural genetic counseling

The increasing diversity of American society has brought growing recognition of the need to bridge cultures in the delivery of genetic counseling services. New immigrants and members of diverse ethnic groups face multiple barriers to genetic counseling services. The need to train genetic counselors to deal with cultural diversity is especially crucial in the new genetic era, given the rapid expansion of available technology, with the resulting social and ethical ramifications. A framework for teaching cross-cultural issues in genetic counseling training programs is presented that can be implemented in step-wise fashion, consistent with available resources. Cross-cultural issues can be incorporated into existing teaching and training modalities by expanding the orientation from monocultural to multicultural. Relevant clinical experience, exploration of students' preconceptions and biases, reading materials, and lectures by invited speakers can all enhance students' knowledge and sensitivity. It is critically important that training programs furnish students with the basic tools necessary for the ongoing process of learning about cultural diversity.     

Amniocentesis in sociocultural perspective

This article reports on an anthropological investigation of the social impact and cultural meaning of amniocentesis conducted in New York City, illustrating how class differences, as well as sociocultural diversity, deeply affect pregnant women's acceptance, rejection, and interpretation of prenatal testing. The article also suggests the importance of recognizing how counselors' cultural backgrounds and styles affect patient-counselor communications.     

Continuous and discrete latent structure models for item response data

Relations are examined between latent trait and latent class models for item response data. Conditions are given for the two-latent class and two-parameter normal ogive models to agree, and relations between their item parameters are presented. Generalizationss are then made to continuous models with more than one latent trait and discrete models with more than two latent classes, and methods are presented for relating latent class models to factor models for dichotomized variables. Results are illustrated using data from the Law School Admission Test, previously analyzed by several authors.     

Exploring the set-theoretical structure of objects by additive trees

Arrangements of feature sets that have been proposed to represent qualitative and quantitative variation among objects are shown to generate identical sets of set-symmetric distances. The set-symmetric distances for these feature arrangements can be represented by path lengths in an additive linear tree. Imperfect versions of these feature arrangements are proposed, which also are indistinguishable by the set-symmetric distance model. The distances for the imperfect versions can be represented by path lengths in an additive imperfectly linear tree. When dissimilarities are defined by the more general contrast model and a constant may be added to proximity data, then for both the perfect and imperfect arrangements an additive tree analysis obtains a perfect fit with an imperfectly linear tree. However, in the case of the contrast model also the distinction between the perfect and imperfect arrangements disappears in that also for the perfect arrangements the resulting tree need no longer be linear.The author is grateful to Mathieu Koppen for detailed comments on an earlier version of this article.