scholarly journals The influence of face masks on emotion recognition and the role of individual differences

2021 ◽  
Author(s):  
Sarah McCrackin ◽  
Francesca Capozzi ◽  
Florence Mayrand ◽  
Jelena Ristic

With widespread adoption of mask wearing, the 2020 Covid-19 pandemic highlighted a need for a deeper understanding of how facial feature obstruction affects emotion recognition. Here we asked participants (n=120) to identify disgusted, angry, sad, neutral, surprised, happy, and fearful emotions from faces with and without masks, and examined if recognition performance was related to their level of social competence and personality traits. Performance was reduced for all masked relative to unmasked emotions. Masks impacted recognition of expressions with diagnostic lower face features the most (disgust, anger) and those with diagnostic upper face features the least (fear, surprise). Recognition performance also varied at the individual level. Persons with higher overall social competence were better at identifying unmasked expressions, while persons with lower trait extraversion and higher trait agreeableness were better at recognizing masked expressions. These results reveal novel insights about the role of face features in emotion recognition and show that obscuring facial features affects social communication differently as a function of individual social competence and personality traits.

2021 ◽  
Author(s):  
Sarah McCrackin ◽  
Jelena Ristic ◽  
Florence Mayrand ◽  
Francesca Capozzi

With the widespread adoption of masks, there is a need for understanding how facial obstruction affects emotion recognition. We asked 120 participants to identify emotions from faces with and without masks. We also examined if recognition performance was related to autistic traits and personality. Masks impacted recognition of expressions with diagnostic lower face features the most and those with diagnostic upper face features the least. Persons with higher autistic traits were worse at identifying unmasked expressions, while persons with lower extraversion and higher agreeableness were better at recognizing masked expressions. These results show that different features play different roles in emotion recognition and suggest that obscuring features affects social communication differently as a function of autistic traits and personality.


2019 ◽  
Author(s):  
Emmanuel Kwasi Mensah ◽  
Lawrence Adu Asamoah ◽  
Vahid Jafari Sadeghi

<p> </p><div> <div> <div> <p>Entrepreneurship research on decision making under uncertainty has focused largely on the effect of uncertainty on the entrepreneurial actions while attempt at the individual level particularly, from the cognitive framework seeks to explain why actions differ. Scholarly efforts have also been made on what informs entrepreneurial actions from the perspective of the entrepreneur’s personal attributes. However, no integrated approach is offered in the literature to study how cognitive skills and personality traits complement each other. In this paper, we consider how cognitive skills and personality traits affect an entrepreneur’s decision to discover or create opportunities under uncertainty. Specifically, we examine the complementary role of personality traits and cognitive skills towards opportunity decisions. We provide a conceptual basis for a broader perspective on behaviors and cognitions that motivate or hinder entrepreneurial actions while at the same time positioning the entrepreneur’s decision at the core of the decision theory. Propositions regarding the application of some selected personality traits and cognitive skills and their complementarity are presented and discussed. </p> </div> </div> </div><br><p></p>


2019 ◽  
Author(s):  
Emmanuel Kwasi Mensah ◽  
Lawrence Adu Asamoah ◽  
Vahid Jafari Sadeghi

<p> </p><div> <div> <div> <p>Entrepreneurship research on decision making under uncertainty has focused largely on the effect of uncertainty on the entrepreneurial actions while attempt at the individual level particularly, from the cognitive framework seeks to explain why actions differ. Scholarly efforts have also been made on what informs entrepreneurial actions from the perspective of the entrepreneur’s personal attributes. However, no integrated approach is offered in the literature to study how cognitive skills and personality traits complement each other. In this paper, we consider how cognitive skills and personality traits affect an entrepreneur’s decision to discover or create opportunities under uncertainty. Specifically, we examine the complementary role of personality traits and cognitive skills towards opportunity decisions. We provide a conceptual basis for a broader perspective on behaviors and cognitions that motivate or hinder entrepreneurial actions while at the same time positioning the entrepreneur’s decision at the core of the decision theory. Propositions regarding the application of some selected personality traits and cognitive skills and their complementarity are presented and discussed. </p> </div> </div> </div><br><p></p>


2020 ◽  
Author(s):  
Christopher James Hopwood ◽  
Ted Schwaba ◽  
Wiebke Bleidorn

Personal concerns about climate change and the environment are a powerful motivator of sustainable behavior. People’s level of concern varies as a function of a variety of social and individual factors. Using data from 58,748 participants from a nationally representative German sample, we tested preregistered hypotheses about factors that impact concerns about the environment over time. We found that environmental concerns increased modestly from 2009-2017 in the German population. However, individuals in middle adulthood tended to be more concerned and showed more consistent increases in concern over time than younger or older people. Consistent with previous research, Big Five personality traits were correlated with environmental concerns. We present novel evidence that increases in concern were related to increases in the personality traits neuroticism and openness to experience. Indeed, changes in openness explained roughly 50% of the variance in changes in environmental concerns. These findings highlight the importance of understanding the individual level factors associated with changes in environmental concerns over time, towards the promotion of more sustainable behavior at the individual level.


2020 ◽  
Vol 56 (2) ◽  
pp. 143-165 ◽  
Author(s):  
Angeliki Papachroni ◽  
Loizos Heracleous

Following the turn to practice in organization theory and the emerging interest in the microfoundations of ambidexterity, understanding the role of individuals in realizing ambidexterity approaches becomes crucial. Drawing insights from Greek philosophy on paradoxes, and practice theory on paradoxes and ambidexterity, we propose a view of individual ambidexterity grounded in paradoxical practices. Existing conceptualizations of ambidexterity are largely based on separation strategies. Contrary to this perspective, we argue that individual ambidexterity can be accomplished via paradoxical practices that renegotiate or transcend boundaries of exploration and exploitation. We identify three such paradoxical practices at the individual level that can advance understanding of ambidexterity: engaging in “hybrid tasks,” capitalizing cumulatively on previous learning, and adopting a mindset of seeking synergies between the competing demands of exploration and exploitation.


2021 ◽  
Vol 24 ◽  
Author(s):  
Sander van der Linden ◽  
Jon Roozenbeek ◽  
Rakoen Maertens ◽  
Melisa Basol ◽  
Ondřej Kácha ◽  
...  

Abstract In recent years, interest in the psychology of fake news has rapidly increased. We outline the various interventions within psychological science aimed at countering the spread of fake news and misinformation online, focusing primarily on corrective (debunking) and pre-emptive (prebunking) approaches. We also offer a research agenda of open questions within the field of psychological science that relate to how and why fake news spreads and how best to counter it: the longevity of intervention effectiveness; the role of sources and source credibility; whether the sharing of fake news is best explained by the motivated cognition or the inattention accounts; and the complexities of developing psychometrically validated instruments to measure how interventions affect susceptibility to fake news at the individual level.


Foods ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 1024
Author(s):  
Sharon Puleo ◽  
Paolo Masi ◽  
Silvana Cavella ◽  
Rossella Di Monaco

The study aimed to investigate the role of sensitivity to flowability on food liking and choice, the relationship between sensitivity to flowability and food neophobia, and its role in food liking. Five chocolate creams were prepared with different levels of flowability, and rheological measurements were performed to characterise them. One hundred seventy-six subjects filled in the Food Neophobia Scale and a food choice questionnaire (FCq). The FCq was developed to evaluate preferences within a pair of food items similar in flavour but different in texture. Secondly, the subjects evaluated their liking for creams (labelled affective magnitude (LAM) scale) and the flowability intensity (generalised labelled magnitude (gLM) scale). The subjects were clustered into three groups of sensitivity and two groups of choice preference. The effect of individual flowability sensitivity on food choice was investigated. Finally, the subjects were clustered into two groups according to their food neophobia level. The sensitivity to flowability significantly affected the liking of chocolate creams and the solid food choice. The liking of chocolate creams was also affected by the individual level of neophobia (p = 0.01), which, in turn, was not correlated to flowability sensitivity. These results confirm that texture sensitivity and food neophobia affect what a person likes and drives what a person chooses to eat.


2022 ◽  
pp. 105984052110681
Author(s):  
Ashwini R. Hoskote ◽  
Emily Croce ◽  
Karen E. Johnson

School nurses are crucial to addressing adolescent mental health, yet evidence concerning their evolving role has not been synthesized to understand interventions across levels of practice (i.e., individual, community, systems). We conducted an integrative review of school nurse roles in mental health in the U.S. related to depressive symptoms, anxiety, and stress. Only 18 articles were identified, published from 1970 to 2019, and primarily described school nurses practicing interventions at the individual level, yet it was unclear whether they were always evidence-based. Although mental health concerns have increased over the years, the dearth of rigorous studies made it difficult to determine the impact of school nurse interventions on student mental health outcomes and school nurses continue to feel unprepared and under supported in this area. More research is needed to establish best practices and systems to support school nursing practice in addressing mental health at all levels of practice.


2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Muhammad Sajid ◽  
Nouman Ali ◽  
Saadat Hanif Dar ◽  
Naeem Iqbal Ratyal ◽  
Asif Raza Butt ◽  
...  

Recently, face datasets containing celebrities photos with facial makeup are growing at exponential rates, making their recognition very challenging. Existing face recognition methods rely on feature extraction and reference reranking to improve the performance. However face images with facial makeup carry inherent ambiguity due to artificial colors, shading, contouring, and varying skin tones, making recognition task more difficult. The problem becomes more confound as the makeup alters the bilateral size and symmetry of the certain face components such as eyes and lips affecting the distinctiveness of faces. The ambiguity becomes even worse when different days bring different facial makeup for celebrities owing to the context of interpersonal situations and current societal makeup trends. To cope with these artificial effects, we propose to use a deep convolutional neural network (dCNN) using augmented face dataset to extract discriminative features from face images containing synthetic makeup variations. The augmented dataset containing original face images and those with synthetic make up variations allows dCNN to learn face features in a variety of facial makeup. We also evaluate the role of partial and full makeup in face images to improve the recognition performance. The experimental results on two challenging face datasets show that the proposed approach can compete with the state of the art.


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