Perceived discrimination based on the symptoms of covid-19, mental health, and emotional responses–the international online COVISTRESS survey

Background Despite the potential detrimental consequences for individuals’ health and discrimination from covid-19 symptoms, the outcomes have received little attention. This study examines the relationships between having personally experienced discrimination based on the symptoms of covid-19 (during the first wave of the pandemic), mental health, and emotional responses (anger and sadness). It was predicted that covid-19 discrimination would be positively related to poor mental health and that this relationship would be mediated by the emotions of anger and sadness. Methods The study was conducted using an online questionnaire from January to June 2020 (the Covistress network; including 44 countries). Participants were extracted from the COVISTRESS database (Ntotal = 280) with about a half declaring having been discriminated due to covid-19 symptoms (N = 135). Discriminated participants were compared to non-discriminated participants using ANOVA. A mediation analysis was conducted to examine the indirect effect of emotional responses and the relationships between perceived discrimination and self-reported mental health. Results The results indicated that individuals who experienced discrimination based on the symptoms of covid-19 had poorer mental health and experienced more anger and sadness. The relationship between covid-19 personal discrimination and mental health disappeared when the emotions of anger and sadness were statistically controlled for. The indirect effects for both anger and sadness were statistically significant. Discussion This study suggests that the covid-19 pandemic may have generated discriminatory behaviors toward those suspected of having symptoms and that this is related to poorer mental health via anger and sadness.publishedVersio

R. Aufrère

In this article, we present a method of nonmarked road following that is based on images coming from an onboard monochromatic camera. The principle is based first on a segmentation stage that makes it possible to locate the road area in the image, managing, if possible, the shadows on the roadway. The method is original since the algorithm must be running day as well as night (infrared camera) so it does not use color images. Furthermore, a single constant threshold is used whatever the analyzed sequence. Then, a localization stage estimates the vehicle’s location on the roadway. The estimate of the parameters L (road width) and α (camera inclination angle) (assumed known and constant for certain existing approaches) ensures a greater robustness of the other estimated parameters. Finally, a filtering stage is applied onto the previous data and predicts the position of the vehicle in the next image. Results are shown for each stage on both a normal nonmarked road and a forest lane sequence. The computational times are very low and will permit a real-time implementation on an experimental vehicle. KEY WORDS—autonomous navigation, computer vision, road-following, lane boundary detection, pixel classificatio

Automatisation par intelligence artificielle des conditions d'anthropomorphisation d'un robot socio-humanoïde

International audienceNous proposons d’étudier les conditions d’anthropomorphisation psychologiques du robot socio-humanoïde NAO par le biais d’une interaction sociale automatisée, pour en saisir l’influence subséquente sur les performances des sujets impliqués dans cette interaction. Plusieurs études issues de la psychologie sociale et cognitive montrent en effet l’influence de la présence des congénères (observateurs ou coacteurs) sur l’exécution de tâches cognitives impliquant un contrôle de l’attention. Cette même influence a été observée plus récemment en présence de robots socio-humanoïdes, à la condition que ces derniers fassent l’objet d’un processus d’anthropomorphisation (basé notamment sur une interaction verbale homme/robot). Dans l’expérience proposée, cette interaction est basée sur le jeu du Memory. Une intelligence artificielle reposant sur de l’apprentissage profond permet au robot de jouer de façon autonome contre un humain. Les effets de la présence du robot anthropomorphisé sont ensuite testés en matière de contrôle de l’attention dans ce nouveau protocole qui permet des interactions humain/robot socio-humanoïde plus réalistes qu’auparavant

Impact of social presence of humanoid robots: does competence matter?

International audienceAn emerging research trend associating social robotics and social-cognitive psychology offers preliminary evidence that the mere presence of humanoid robots may have the same effects as human presence on human performance, provided the robots are anthropomorphized to some extent (attribution to mental states to the robot being present). However, whether these effects also depend on the evaluation potential of the robot remains unclear. Here, we investigated this critical issue in the context of the Stroop task allowing the estimation of robotic presence effects on participants' reaction times (RTs) to simple and complex stimuli. Participants performed the Stroop task twice while being randomly assigned to one of three conditions: alone then in the presence of a robot presented as competent versus incompetent on the task at hand ("evaluative" vs. "nonevaluative" robot condition), or systematically alone (control condition). Whereas the presence of the incompetent robot did not change RTs (compared to the control condition), the presence of the competent robot caused longer RTs on both types of Stroop stimuli. The robot being exactly the same in both conditions, to the notable exception of its evaluation potential, these findings indicate that the presence of humanoid robots with such a potential may divert attention away from the central task in humans

Impact of social presence of humanoid robots: does competence matter?

International audienceAn emerging research trend associating social robotics and social-cognitive psychology offers preliminary evidence that the mere presence of humanoid robots may have the same effects as human presence on human performance, provided the robots are anthropomorphized to some extent (attribution to mental states to the robot being present). However, whether these effects also depend on the evaluation potential of the robot remains unclear. Here, we investigated this critical issue in the context of the Stroop task allowing the estimation of robotic presence effects on participants' reaction times (RTs) to simple and complex stimuli. Participants performed the Stroop task twice while being randomly assigned to one of three conditions: alone then in the presence of a robot presented as competent versus incompetent on the task at hand ("evaluative" vs. "nonevaluative" robot condition), or systematically alone (control condition). Whereas the presence of the incompetent robot did not change RTs (compared to the control condition), the presence of the competent robot caused longer RTs on both types of Stroop stimuli. The robot being exactly the same in both conditions, to the notable exception of its evaluation potential, these findings indicate that the presence of humanoid robots with such a potential may divert attention away from the central task in humans

Joint action with human and robotic co-actors: Self-other integration is immune to the perceived humanness of the interacting partner

International audienceWhen performing a joint action task, we automatically represent the action and/or task constraints of the co-actor with whom we are interacting. Current models suggest that, not only physical similarity, but also abstract, conceptual features shared between self and the interacting partner play a key role in the emergence of joint action effects. Across two experiments, we investigated the influence of the perceived humanness of a robotic agent on the extent to which we integrate the action of that agent into our own action/task representation, as indexed by the Joint Simon Effect (JSE). The presence (vs. absence) of a prior verbal interaction was used to manipulate robot’s perceived humanness. In Experiment 1, using a within-participant design, we had participants perform the joint Go/No-go Simon task with two different robots. Before performing the joint task, one robot engaged in a verbal interaction with the participant and the other robot did not. In Experiment 2, we employed a between-participants design to contrast these two robot conditions as well as a human partner condition. In both experiments, a significant Simon effect emerged during joint action and its amplitude was not modulated by the humanness of the interacting partner. Experiment 2 further showed that the JSE obtained in robot conditions did not differ from that measured in the human partner condition. These findings contradict current theories of joint action mechanisms according to which perceived self-other similarity is a crucial determinant of self-other integration in shared task settings