Cognitive resilience in Emergency Room operations: A theoretical framework.

System resilience implies practitioners\u2019 capacity to cope with unexpected events, i.e. cognitive resilience. To address it, we outline a framework based on the Skill-Rule-Knowledge model grounding it in the operators\u2019 sensitivity to the variety that normally occurs in complex systems activities. This variety can hide information enabling the organization to be proactive and to manage unexpected events. Each situation can be described with a SRK profile, according to the cognitive processes necessary to control it. Operators\u2019 reliability can therefore be analyzed by evaluating the match between their cognitive SRK profile and that demanded by the current situation. System resilience is ensured by the capacity of operators to: (i) choose the most suitable cognitive level; (ii) freely move along these levels according to the situation; (iii) be mindful towards variety; (iv) transfer their personal mindfulness into group dynamic adaptation. The outcome of these behaviors is a balance of mindfulness (constant attention to anomalous signals) and dynamic adaptation (organizational adjustment of existing rules according to the new information). This continuous equilibrium between chaos and order is the strategy followed by adaptive complex systems in order to evolve and can be successfully applied to high-risk organizations to enhance the emergence of resilient behaviors

The role of media in community resilience: Hindsight bias in media narratives after the 2014 Genoa flood

Aim: A massive flood due to exceptional rainfalls devastated the town of Genoa on 9 October2014. Media reports focused on the disaster, its causes and the political accountabilities. Reading facts after the event is commonly biased by the hindsight perspective and the aim of the paper is to investigate the amount and the potential effects of hindsight bias in terms of citizens risk perception and community resilience.Method:We performed a qualitative analysis of the narratives in the national and local news reports during the aftermath to investigate occurrences of a blaming attitude and cognitive biases. Results: The results showed a considerable amount of sentences that were focused on blaming the forecasters, the Civil Protection System, and the local administration. Many narratives were affected by hindsight bias and described the events as simple and linear chain reactions. This led to counterfactual biases, assuming that a simple intervention on a single factor could have prevented the tragic outcome. Conclusion: We claim that the biased nature of the media narratives could affect the citizens\u2019 risk perception and their attitude towards the institutions, increasing their exposure to future flood-related threats. We propose the appropriate language would generate correct cognitive frames and, therefore, safer behaviou

L’homo errans nell’era dell’infallibilità tecnica

In this paper the phenomenon of human error will be described in relationship to human performance in complex high-technology systems. Misconceptions could lie behind the terms “human error” at several levels: cognitive, emotional, moral, and cultural. From the cognitive perspective, human error has been widely investigated and proper theoretical models can accurately describe its nature and functions. From the emotional perspective, making a mistake could lead to feelings such as guilt and shame, which could have relevant effects on how people cope with the situation and try to remedy the error. Concerning the moral perspective on human error, we describe a dangerous mix of cognitive biases and the judgment of the person. The cognitive biases frame the mistake as something that was predictable and avoidable, and the severity of the blame is correlated with the gravity of the outcomes. These distortions critically move the perspective from an analysis of behavior to moral judgment of the person, a typical effect of the so called “blame culture”. Finally, from the cultural perspective, human behavior is superficially compared to the reliability of technology. Blaming humans for not being like machines is just a symptom of current technology-centered culture. Given the complexity of today’s socio-technical systems, the challenge is to harmonize human and automation characteristics. The goal is not to make humans less prone to errors, but to make complex systems safer

Music ensemble as a resilient system. Managing the unexpected through group interaction

The present contribution provides readers from diverse fields of psychology with a new and comprehensive model for the understanding of the characteristics of music ensembles. The model is based on a novel heuristic approach whose key construct is resilience, intended here as the ability of a system to adapt to external perturbations and anticipate future events. The paper clarifies the specificity of music ensemble as an original social and creative activity, and how some mechanisms, at an individual (cognitive) and group (coordination) level, are enacted in a particular way that endows these groups with exceptional capacity for resilience. There is now a wealth of evidence isolating the psychological mechanisms involved in these processes. However, there is much less focus on conditions in which the group has to face unexpected and potentially performance-disruptive events. The resilience approach offers a more thorough explanation of the regulatory strategies that musicians may resort to in order to maintain their performance at an optimal level. Music ensembles of different size are presented as case studies of how such systems (and their individual members) resist error and maintain joint performance. Three hypothetical scenarios are further proposed that epitomize resilient or non-resilient musical teams. The present contribution further proposes hypotheses and formulates predictions on which combinations of individual and group factors foster team resilience. This model further accommodates the most recent findings in neuroscience and experimental psychology. Besides highlighting the potential of music ensemble for psychological research, it offers hints about how resilience could be trained

Development and Validation of the Facial Expression Recognition Test (FERT)

Detecting the emotional state of others from facial expressions is a key ability in emotional competence and several instruments have been developed to assess it. Typical emotion recognition tests are assumed to be unidimensional, use pictures or videos of emotional portrayals as stimuli, and ask the participant which emotion is depicted in each stimulus. However, using actor portrayals adds a layer of difficulty in developing such a test: the portrayals may fail to be convincing and may convey a different emotion than intended. For this reason, evaluating and selecting stimuli is of crucial importance. Existing tests typically base item evaluation on consensus or expert judgment, but these methods could favor items with high agreement over items that better differentiate ability levels and they could not formally test the item pool for unidimensionality. To address these issues, the authors propose a new test, named Facial Expression Recognition Test (FERT), developed using an item response theory two-parameter logistic model. Data from 1,002 online participants were analyzed using both a unidimensional and a bifactor model, and showed that the item pool could be considered unidimensional. The selection was based on the items' discrimination parameters, retaining only the most informative items to investigate the latent ability. The resulting 36-item test was reliable and quick to administer. The authors found both a gender difference in the ability to recognize emotions and a decline of such ability with age. The PsychoPy implementation of the test and the scoring script are available on a Github repository

A New Approach for Human Factor Integration into Ship Design Process

Ship safety and operations are driving issues of ship design and it is well recognized that such performances are strongly related to Human Factor (HF). In the paper a methodology to integrate HF into the ship design process since an early stage is envisaged, with the aim to improve the overall ship resilience when dealing with uncertainty of performance implied by HF element. The System-Theoretic Accident Model Process (STAMP, Leveson 2003) is investigated as a suitable methodology able to provide a significant asset in such perspective. The approach is widely applied in many industrial and transportation fields but in order to better understand its application into the marine context, a specific application will be briefly commented. In the attempt to define a comprehensive procedure, as a preliminary overview, some selected models suitable to classify the human behavior will be considered with specific focus on the reasons for performance degrade and/or uncertainty

Implicit evidence on the dissociation of identity and emotion recognition

Recognition of identity and of emotional facial expressions of individuals are both based on processing of the human face. While most studies show these abilities to be dissociated, some others find evidence of a connection. One possible explanation for these contradictory results comes from neurological evidence, which points to identity recognition being mostly based on holistic processing, while emotion recognition seems to be based on both an explicit, fine-grained process, and an implicit, mostly-holistic one. Our main hypothesis, that would explain the contradictory findings, is that holistic implicit emotion recognition, specifically, would be related to identity recognition, while explicit emotion recognition would be a process separate to identity recognition. To test this hypothesis, we employed an experimental paradigm in which spatial frequencies of visual stimuli are manipulated so that automatic, holistic-based, implicit emotion recognition influences perceived friendliness of unfamiliar faces. We predicted the effect to be related to identity recognition ability, since they both require holistic face processing. After a successful replication study, we employed the paradigm with 140 participants, measuring also identity recognition ability and explicit emotion recognition ability. Results showed that the effect is not moderated by these two variables (p = .807 and .373, respectively), suggesting that the independence of identity and emotion recognition holds even when considering, specifically, implicit emotion recognition

Erratum to "Validity of Mental Workload Measures in a Driving Simulation Environment"

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Human- or object-like? Cognitive anthropomorphism of humanoid robots

Across three experiments (N = 302), we explored whether people cognitively elaborate humanoid robots as human- or object-like. In doing so, we relied on the inversion paradigm, which is an experimental procedure extensively used by cognitive research to investigate the elaboration of social (vs. non-social) stimuli. Overall, mixed-model analyses revealed that full-bodies of humanoid robots were subjected to the inversion effect (body-inversion effect) and, thus, followed a configural processing similar to that activated for human beings. Such a pattern of finding emerged regardless of the similarity of the considered humanoid robots to human beings. That is, it occurred when considering bodies of humanoid robots with medium (Experiment 1), high and low (Experiment 2) levels of human likeness. Instead, Experiment 3 revealed that only faces of humanoid robots with high (vs. low) levels of human likeness were subjected to the inversion effects and, thus, cognitively anthropomorphized. Theoretical and practical implications of these findings for robotic and psychological research are discussed