Investigate naturalistic decision-making of a workgroup in dynamic situation. From the modelling to the design of a training virtual environment

International audienceThis thesis aims to rely on a work of activity analysis to develop a virtual training platform for firefighters (SécuRéVi). The use of this type of simulation is more and more common in the field of training, but often suffers from a lack of credibility in terms of learning content and method. To solve this problem, this project aims to model the collaborative work of firefighters during training sessions in order to provide assistance to the development of SécuRéVi. The activity analysis of these group works, relying on the EAST (Event Analysis of System Teamwork) methodology and self-confrontation interviews, is expected to highlight the particular "know-how" and to develop pedagogical scenarios essential in the design of such a training platform

Context's modeling for participative problem solving

International audienceThis paper reviews the interest of using context for participative simulation in virtual environment for training. Context is an interesting concept for at least two points: Virtual agents and humans have to collaborate ,so they must communicate and understand each other. This is the reason why we use a simplified analogy with human's decision-making. Our aim is to simulate some cognitive mechanisms in order to have credible agent's decision-making. We keep the notion of context. Agents reason with the situation's context, which is divided in social, environmental, historical and personal contexts. Another interesting aspect is the explanation needed when the learner makes a mistake. We argue, in this article, that context is a good concept to give better explanations. At last we show an example of an agent decision-making

Interactive co-construction to study dynamical collaborative situations.

International audienceThe purpose of this paper is to present the principle of our framework CoPeFoot dedicated to the study of dynamic and collaborative situations. This research work aims to instate learning by the co-construction of such situations. The article starts by recalling constraints induced by such situations. Next, it introduces interactive co-construction assumption and their implementation in CoPeFoot. In fact, this implementation is based on two steps in CoPeFoot: firstly, machine learning for behavior modeling, using imitation of real users and secondly, refining this behavior by using interaction between the user and the simulation, enhanced by additional information called augmented virtuality. In order to do that, CoPeFoot lies on context base reasoning which is presented. The article ends by a first evaluation of this work

Investigate Naturalistic Decision-Making of Football Players in Virtual Environment: Influence of Viewpoints in Recognition

International audienceIntroduction: The study of underlying processes of decision-making in dynamic situation, whether in work or in sport, is essential to the development of training tools. Virtual simulations are both key tools to study these processes and training. Method: Our work consisted in analysing the players' naturalistic decision-making in the virtual simulator CoPeFoot and the influence that changes of viewpoint can have on it. Behavioural data were recorded from six players in two different views (immersive and external), supplemented by verbal data collected during self-confrontation interviews. Results: A content analysis of the data revealed that in situations with strict time constraints, the players, to make decision, used twenty four schemata which facilitated the recognition of game situations. Discussion: These results points to the dynamic aspect of decision-making activity in the simulator and the consistency with the findings of studies in natural situations and the homogeneity for immersive and external views

PEGASE: A generic and adaptable intelligent system for virtual reality learning environments

International audienceThe context of this research is the creation of human learning environments using virtual reality. We propose the integration of a generic and adaptable intelligent tutoring system (Pegase) into a virtual environment. The aim of this environment is to instruct the learner, and to assist the instructor. The proposed system is created using a multi-agent system. This system emits a set of knowledge (actions carried out by the learner, knowledge about the field, etc.) which Pegase uses to make informed decisions. Our study focuses on the representation of knowledge about the environment, and on the adaptable pedagogical agent providing instructive assistance

Analyse de l'activité décisionnelle de joueurs de football dans un environnement virtuel. Effets des changements de point de vue

International audienceL'étude des processus sous-jacents à l'activité décisionnelle dans les situations dynamiques, que se soit dans le domaine du travail ou du sport, devient un élément essentiel à la conception d'outils de formation. Les simulations virtuelles constituent à la fois des outils privilégiés d'étude de ces processus et de formation. Notre travail a consisté à analyser l'activité de joueurs au sein du simulateur virtuel CoPeFoot et l'influence du changement de point de vue sur cette dernière. Des données comportementales ont été enregistrées auprès de quatre joueurs suivant deux points de vue (immersif et global), puis complétées par des données verbales recueillies lors d'entretiens d'autoconfrontation. L'analyse du contenu des données obtenues permet d'identifier 24 schémas activés par les joueurs sur le simulateur en situation de forte pression temporelle. Ces schémas constituent des structures d'arrière-plans articulant des composantes perceptives et cognitives et qui facilitent la reconnaissance rapide de situations de jeu. La discussion de ces résultats pointe l'aspect dynamique de l'activité décisionnelle au sein du simulateur et l'homogénéité des résultats obtenus en vue immersive et globale. De plus, la concordance avec les conclusions d'études réalisées en situation naturelle permet de proposer des perspectives d'évolution vers un outil de formation à l'activité décisionnelle

Analyser l’activité décisionnelle de joueurs de football en situation d’entraînement pour développer un modèle de joueur virtuel

Notre étude s’est attachée à la description de l’activité décisionnelle de joueurs de football en situation de contre-attaque. Cette activité décisionnelle a été appréhendée à l’aide du cadre théorique de la NDM en situation aménagée à des fins d’étude. Des données comportementales ont été enregistrées auprès de douze joueurs de football, puis complétées par des données verbales recueillies lors d’un entretien d’autoconfrontation. Les données ont été analysées en 6 étapes : (a) la retranscription des données, (b) la sélection et l’identification des unités significatives, (c) le découpage du déroulement de l’activité en situations vécues, (d) l’identification des situations et des schémas, (e) la modélisation de la dynamique de l’activité décisionnelle, et (f) la validité de l’analyse. Les résultats ont permis d’identifier 16 schémas caractéristiques de l’activité décisionnelle des joueurs de football en situation de contraintes temporelles. Ces schémas constituent des structures d’arrière-plans articulant des composantes perceptives et cognitives, et qui facilitent la reconnaissance rapide de situations pendant la contre-attaque. La discussion de ces résultats pointe l’aspect dynamique de l’activité décisionnelle. L’application de ces résultats à un modèle de joueur de football virtuel est ensuite présentée et des perspectives d’évolution sont proposées

L’activité décisionnelle en phase de contre-attaque en Hockey sur glace

L’objectif de cette étude était de comprendre et de décrire les processus sous-jacents à l’activité décisionnelle dans des situations dynamiques, c’est-à-dire incertaines, évolutives, et imposant une forte pression temporelle. Notre travail a consisté à analyser l’activité de joueurs de hockey-sur-glace en phase naturelle de contre-attaque. Des données comportementales sont enregistrées auprès de six joueurs experts en hockey-sur-glace, puis complétées par des données verbales recueillies lors d’un entretien d’autoconfrontation. Six contre-attaques ont été étudiées. Les données ont été analysées en 5 étapes : a) la retranscription des données, b) la sélection et l’identification des unités significatives, c) le découpage du déroulement de l’activité en situations vécues, d) l’identification des situations et des schémas, et e) la validité de l’analyse. L’analyse du contenu des données obtenues permet d’identifier 10 schémas activés par les joueurs experts en situation de forte pression temporelle. Ces schémas constituent des structures d’arrière-plans articulant des composantes perceptives et cognitives, et qui facilitent la reconnaissance rapide de situations pendant la contre-attaque. Les résultats de cette étude éclairent en partie la complexité de l’activité décisionnelle en situation dynamique et sont discutés au regard d’autres études sur la prise de décision en situation naturelle dans le domaine du sport et de l’ergonomie cognitive.The aim of this study was to understand and describe the underlying processes of decision-making in a dynamic situation, i.e. one that was uncertain, gradual and subject to intense time pressure. Our work involved analysing ice hockey players’ activity in a natural situation of counter-attacking. Behavioural data was recorded from six high-level ice hockey players, supplemented by verbal data collected during self-confrontational interviews. Six counter-attacks were studied. The data were analysed in five stages: (1) generating counter-attack logs, (2) selecting and identifying the elementary units of meaning, (3) analysing the courses of action by dividing up the situations, (4) identifying situations and schemata, and (5) checking the validity of the analysis. An analysis of the data content identified ten schemata used by expert ice hockey players in situations with strict time constraints. These represent the underlying structures which link perceptive and cognitive elements and facilitate the recognition of situations during a counter-attack. The results of this study provide empirical support for the complexity of decision-making in dynamic situations and are discussed with regard to the literature on decision-making in natural situations in the field of sport and cognitive ergonomics

Effect of Hydrocortisone on Mortality and Organ Support in Patients With Severe COVID-19: The REMAP-CAP COVID-19 Corticosteroid Domain Randomized Clinical Trial.

Importance: Evidence regarding corticosteroid use for severe coronavirus disease 2019 (COVID-19) is limited. Objective: To determine whether hydrocortisone improves outcome for patients with severe COVID-19. Design, Setting, and Participants: An ongoing adaptive platform trial testing multiple interventions within multiple therapeutic domains, for example, antiviral agents, corticosteroids, or immunoglobulin. Between March 9 and June 17, 2020, 614 adult patients with suspected or confirmed COVID-19 were enrolled and randomized within at least 1 domain following admission to an intensive care unit (ICU) for respiratory or cardiovascular organ support at 121 sites in 8 countries. Of these, 403 were randomized to open-label interventions within the corticosteroid domain. The domain was halted after results from another trial were released. Follow-up ended August 12, 2020. Interventions: The corticosteroid domain randomized participants to a fixed 7-day course of intravenous hydrocortisone (50 mg or 100 mg every 6 hours) (n = 143), a shock-dependent course (50 mg every 6 hours when shock was clinically evident) (n = 152), or no hydrocortisone (n = 108). Main Outcomes and Measures: The primary end point was organ support-free days (days alive and free of ICU-based respiratory or cardiovascular support) within 21 days, where patients who died were assigned -1 day. The primary analysis was a bayesian cumulative logistic model that included all patients enrolled with severe COVID-19, adjusting for age, sex, site, region, time, assignment to interventions within other domains, and domain and intervention eligibility. Superiority was defined as the posterior probability of an odds ratio greater than 1 (threshold for trial conclusion of superiority >99%). Results: After excluding 19 participants who withdrew consent, there were 384 patients (mean age, 60 years; 29% female) randomized to the fixed-dose (n = 137), shock-dependent (n = 146), and no (n = 101) hydrocortisone groups; 379 (99%) completed the study and were included in the analysis. The mean age for the 3 groups ranged between 59.5 and 60.4 years; most patients were male (range, 70.6%-71.5%); mean body mass index ranged between 29.7 and 30.9; and patients receiving mechanical ventilation ranged between 50.0% and 63.5%. For the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively, the median organ support-free days were 0 (IQR, -1 to 15), 0 (IQR, -1 to 13), and 0 (-1 to 11) days (composed of 30%, 26%, and 33% mortality rates and 11.5, 9.5, and 6 median organ support-free days among survivors). The median adjusted odds ratio and bayesian probability of superiority were 1.43 (95% credible interval, 0.91-2.27) and 93% for fixed-dose hydrocortisone, respectively, and were 1.22 (95% credible interval, 0.76-1.94) and 80% for shock-dependent hydrocortisone compared with no hydrocortisone. Serious adverse events were reported in 4 (3%), 5 (3%), and 1 (1%) patients in the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively. Conclusions and Relevance: Among patients with severe COVID-19, treatment with a 7-day fixed-dose course of hydrocortisone or shock-dependent dosing of hydrocortisone, compared with no hydrocortisone, resulted in 93% and 80% probabilities of superiority with regard to the odds of improvement in organ support-free days within 21 days. However, the trial was stopped early and no treatment strategy met prespecified criteria for statistical superiority, precluding definitive conclusions. Trial Registration: ClinicalTrials.gov Identifier: NCT02735707

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570