213 resultados para Behavior Setting


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In this article, we show how the use of state-of-the-art methods in computer science based on machine perception and learning allows the unobtrusive capture and automated analysis of interpersonal behavior in real time (social sensing). Given the high ecological validity of the behavioral sensing, the ease of behavioral-cue extraction for large groups over long observation periods in the field, the possibility of investigating completely new research questions, and the ability to provide people with immediate feedback on behavior, social sensing will fundamentally impact psychology.

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The question of how to quantify insufficient coping behavior under chronic stress is of major clinical relevance. In fact, chronic stress increasingly dominates modern work conditions and can affect nearly every system of the human body, as suggested by physical, cognitive, affective and behavioral symptoms. Since freshmen students experience constantly high levels of stress due to tight schedules and frequent examinations, we carried out a 3-center study of 1,303 students from Italy, Spain and Argentina in order to develop socioculturally independent means for quantifying coping behavior. The data analysis relied on 2 self-report questionnaires: the Coping Strategies Inventory (COPE) for the assessment of coping behavior and the Zurich Health Questionnaire which assesses consumption behavior and general health dimensions. A neural network approach was used to determine the structural properties inherent in the COPE instrument. Our analyses revealed 2 highly stable, socioculturally independent scales that reflected basic coping behavior in terms of the personality traits activity-passivity and defeatism-resilience. This replicated previous results based on Swiss and US-American data. The percentage of students exhibiting insufficient coping behavior was very similar across the study sites (11.5-18.0%). Given their stability and validity, the newly developed scales enable the quantification of basic coping behavior in a cost-efficient and reliable way, thus clearing the way for the early detection of subjects with insufficient coping skills under chronic stress who may be at risk of physical or mental health problems.

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Nonverbal behavior coding is typically conducted by "hand". To remedy this time and resource intensive undertaking, we illustrate how nonverbal social sensing, defined as the automated recording and extracting of nonverbal behavior via ubiquitous social sensing platforms, can be achieved. More precisely, we show how and what kind of nonverbal cues can be extracted and to what extent automated extracted nonverbal cues can be validly obtained with an illustrative research example. In a job interview, the applicant's vocal and visual nonverbal immediacy behavior was automatically sensed and extracted. Results show that the applicant's nonverbal behavior can be validly extracted. Moreover, both visual and vocal applicant nonverbal behavior predict recruiter hiring decision, which is in line with previous findings on manually coded applicant nonverbal behavior. Finally, applicant average turn duration, tempo variation, and gazing best predict recruiter hiring decision. Results and implications of such a nonverbal social sensing for future research are discussed.

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Understanding the basis on which recruiters form hirability impressions for a job applicant is a key issue in organizational psychology and can be addressed as a social computing problem. We approach the problem from a face-to-face, nonverbal perspective where behavioral feature extraction and inference are automated. This paper presents a computational framework for the automatic prediction of hirability. To this end, we collected an audio-visual dataset of real job interviews where candidates were applying for a marketing job. We automatically extracted audio and visual behavioral cues related to both the applicant and the interviewer. We then evaluated several regression methods for the prediction of hirability scores and showed the feasibility of conducting such a task, with ridge regression explaining 36.2% of the variance. Feature groups were analyzed, and two main groups of behavioral cues were predictive of hirability: applicant audio features and interviewer visual cues, showing the predictive validity of cues related not only to the applicant, but also to the interviewer. As a last step, we analyzed the predictive validity of psychometric questionnaires often used in the personnel selection process, and found that these questionnaires were unable to predict hirability, suggesting that hirability impressions were formed based on the interaction during the interview rather than on questionnaire data.

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De nombreuses études ont mis en évidence le fait que les individus étaient prêts à commettre des actes discriminatoires pour autant qu'ils puissent les justifier (Crandall & Eshleman, 2003). Nous proposons de contribuer à la compréhension de ce phénomène grâce au concept de désengagement moral pour des actes discriminatoires (DMD). Nous définissons le désengagement moral comme le fait de justifier ses propres actes immoraux de manière à les rendre acceptable. Ce concept trouve ses origines dans les travaux de Bandura et al. (1996) portant sur les comportements agressifs chez des enfants. Il se compose de huit mécanismes (p.ex. le déplacement de responsabilité). Notre recherche dépasse le cadre théorique développé par Bandura et al. pour inscrire le désengagement moral dans le champ de la discrimination intergroupe. De plus, en conceptualisant le désengagement moral comme une différence individuelle, nous proposons également de présenter les premières étapes du développement d'une échelle permettant de mesurer le DMD. L'échelle de DMD a été développée en trois étapes en suivant la procédure proposée par Hinkin (1998). Tout d'abord, une liste de 72 items a été générée suivant une méthode déductive. Puis, suite à une étude (n = 13) portant sur la cohérence des items vis-à-vis du concept et de ses mécanismes, cette liste a été réduite à 40 items (5 par mécanisme). Enfin, 118 étudiants universitaires ont participé à une étude dans le but de mener des analyses factorielles (exploratoire et confirmatoire), ainsi que de tester les validités convergente, divergente et prédictive de l'échelle. La première partie de cette étude se composait de différentes échelles (p.ex. mesure de personnalité, préjugés anti-immigrés, etc.). La seconde partie de l'étude était une expérience portant sur l'évaluation d'idées de méthodes de sélection (discriminatoire versus méritocratique) des étudiants suisses et étrangers à l'université, ayant pour but de réduire la surpopulation dans les salles de cours. Les résultats obtenus sont prometteurs pour le développement de l'échelle, autant du point de vue de sa structure (p.ex. α = .82) que de sa validité. Par exemple, plus le niveau de DMD des participants était élevé, plus ils étaient favorables à une méthode de sélection discriminatoire des étudiants à l'université. L'ensemble des résultats sera présenté durant la conférence. Nous discuterons également des potentielles contributions de cette échelle pour de futurs projets de recherche. Référence : Bandura, A., Barbaranelli, C., Caprara, G. V., & Pastorelli, C. (1996). Mechanisms of moral disengagement of the exercise of moral agency. Journal of Personality and Social Psychology, 71 (2), 364-374. Crandall, C. S., & Eshleman, A. (2003). The Justification-suppression model of the expression and experience of prejudice. Psychological Bulletin, 129 (3), 414-446. Hinkin, T. R. (1998). A brief tutorial on the development of measures for use un survey questionnaires. Organizational Research Methods, 1 (1), 104.121.

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A long-standing question in biology and economics is whether individual organisms evolve to behave as if they were striving to maximize some goal function. We here formalize this "as if" question in a patch-structured population in which individuals obtain material payoffs from (perhaps very complex multimove) social interactions. These material payoffs determine personal fitness and, ultimately, invasion fitness. We ask whether individuals in uninvadable population states will appear to be maximizing conventional goal functions (with population-structure coefficients exogenous to the individual's behavior), when what is really being maximized is invasion fitness at the genetic level. We reach two broad conclusions. First, no simple and general individual-centered goal function emerges from the analysis. This stems from the fact that invasion fitness is a gene-centered multigenerational measure of evolutionary success. Second, when selection is weak, all multigenerational effects of selection can be summarized in a neutral type-distribution quantifying identity-by-descent between individuals within patches. Individuals then behave as if they were striving to maximize a weighted sum of material payoffs (own and others). At an uninvadable state it is as if individuals would freely choose their actions and play a Nash equilibrium of a game with a goal function that combines self-interest (own material payoff), group interest (group material payoff if everyone does the same), and local rivalry (material payoff differences).

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The fact that individuals learn can change the relationship between genotype and phenotype in the population, and thus affect the evolutionary response to selection. Here we ask how male ability to learn from female response affects the evolution of a novel male behavioral courtship trait under pre-existing female preference (sensory drive). We assume a courtship trait which has both a genetic and a learned component, and a two-level female response to males. With individual-based simulations we show that, under this scenario, learning generally increases the strength of selection on the genetic component of the courtship trait, at least when the population genetic mean is still low. As a consequence, learning not only accelerates the evolution of the courtship trait, but also enables it when the trait is costly, which in the absence of learning results in an adaptive valley. Furthermore, learning can enable the evolution of the novel trait in the face of gene flow mediated by immigration of males that show superior attractiveness to females based on another, non-heritable trait. However, rather than increasing monotonically with the speed of learning, the effect of learning on evolution is maximized at intermediate learning rates. This model shows that, at least under some scenarios, the ability to learn can drive the evolution of mating behaviors through a process equivalent to Waddington's genetic assimilation.

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Neurophysiology is an essential tool for clinicians dealing with patients in the intensive care unit. Because of consciousness disorders, clinical examination is frequently limited. In this setting, neurophysiological examination provides valuable information about seizure detection, treatment guidance, and neurological outcome. However, to acquire reliable signals, some technical precautions need to be known. EEG is prone to artifacts, and the intensive care unit environment is rich in artifact sources (electrical devices including mechanical ventilation, dialysis, and sedative medications, and frequent noise, etc.). This review will discuss and summarize the current technical guidelines for EEG acquisition and also some practical pitfalls specific for the intensive care unit.

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Communication between trainer and trainee plays a central role in teaching and learning in the clinical environment. There are various strategies to frame the dialogue between trainee and trainer. These strategies allow trainers to be more effective in their supervision, which is important in our busy clinical environment. Communication strategies are well adapted to both in- and out-patient settings, to both under- and postgraduate contexts. This article presents three strategies that we think are particularly useful. They are meant to give feedback, to ask questions and to present a case.