Emotions, Psychological Structure of

Shuman, Vera; Scherer, Klaus R.

doi:10.1016/b978-0-08-097086-8.25007-1

Cited by 24 publications

(8 citation statements)

References 32 publications

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“…Emotions have been distinguished from moods based on the cause or triggering event, duration, intensity, and action tendencies (Beedie, Terry, & Lane, 2005;Ekkekakis, 2012;Shuman & Scherer, 2015). Theorists agree that emotions have an identifiable cause, are short term and more intense, have specific tendencies for action and a differentiated subjective feeling, while moods do not have an object, last longer in time, have broader approachavoidance tendencies, and are more diffuse.…”

Section: Emotions and Affective Phenomenamentioning

confidence: 99%

“…Physiological or bodily responses usually include changes in heart rate, blood pressure, and visceral functioning, and further reactions in the autonomic nervous system. Behavioral expressions triggered by emotions are usually associated with approach-avoidance tendencies (Elliot, Eder, & Harmon-Jones, 2013; see Shuman & Scherer, 2015, for a review). These emotion components, which originate from distinct methodological approaches (e.g., self-reports, physiological measures, behavioral observation), do not seem to provide comprehensive information about emotional experiences.…”

Section: Emotions and Affective Phenomenamentioning

confidence: 99%

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Emotional Self-Regulation in Sport and Performance

Robazza¹,

Ruiz²

2018

Oxford Research Encyclopedia of Psychology

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Emotions are multifaceted subjective feelings that reflect expected, current, or past interactions with the environment. They involve sets of interrelated psychological processes, encompassing affective, cognitive, motivational, physiological, and expressive or behavioral components. Emotions play a fundamental role in human adaptation and performance by improving sensory intake, detection of relevant stimuli, readiness for behavioral responses, decision-making, memory, and interpersonal interactions. These beneficial effects enhance human health and performance in any endeavor, including sport, work, and the arts. However, emotions can also be maladaptive. Their beneficial or maladaptive effects depend on their content, time of occurrence, and intensity level. Emotional self-regulation refers to the processes by which individuals modify the type, quality, time course, and intensity of their emotions. Individuals attempt to regulate their emotions to attain beneficial effects, to deal with unfavorable circumstances, or both. Emotional self-regulation occurs when persons monitor the emotions they are experiencing and try to modify or maintain them. It can be automatic or effortful, conscious or unconscious. The process model of emotion regulation provides a framework for the classification of antecedent- and response-focused regulation processes. These processes are categorized according to the point at which they have their primary impact in the emotion generative process: situation selection (e.g., confrontation and avoidance), situation modification (e.g., direct situation modification, support-seeking, and conflict resolution), attentional deployment (e.g., distraction, concentration, and mindfulness), cognitive change (e.g., self-efficacy appraisals, challenge/threat appraisals, positive reappraisal, and acceptance), and response modulation (e.g., regulation of experience, arousal regulation, and expressive suppression). In addition to the process model of emotion regulation, other prominent approaches provide useful insights to the study of adaptation and self-regulation for performance enhancement. These include the strength model of self-control, the dual-process theories, the biopsychosocial model, the attentional control theory, and the individual zones of optimal functioning model. Based on the latter model, emotion-centered and action-centered interrelated strategies have been proposed for self-regulation in sport. Within this framework, performers identify, regulate, and optimize their functional and dysfunctional emotions and their most relevant components of functional performance patterns.

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Section: Emotions and Affective Phenomenamentioning

confidence: 99%

Section: Emotions and Affective Phenomenamentioning

confidence: 99%

Emotional Self-Regulation in Sport and Performance

Robazza¹,

Ruiz²

2018

Oxford Research Encyclopedia of Psychology

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“…That is, individuals are driven by their experienced emotions. Emotions are multi-componential phenomena (Shuman and Scherer, 2015 ); they include several paralleled psychological processes. Emotions consist of affective, cognitive, physiological, motivational, and expressive constituents (Burić et al, 2017 ).…”

Section: Literature Reviewmentioning

confidence: 99%

Measuring Language Teacher Emotion Regulation: Development and Validation of the Language Teacher Emotion Regulation Inventory at Workplace (LTERI)

et al. 2021

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Educational context is a pool of various emotional demands asking for competent teachers who are capable enough to regulate and manage them. The language teacher emotion regulation focuses on the strategies that language teachers implement to regulate their emotions. Considering the paucity of a psychometrically sound instrument in language teacher emotion regulation, this realm has received scant research attention. Thus, the present study was an attempt to develop and validate a conceptually meaningful and psychometrically sound instrument to capture language teacher emotion regulation strategies at workplace. This study is composed of three phases. In the first phase, based on a comprehensive consideration of the existing literature and the results of a semi-structured interview, a six-component model of the language teacher emotion regulation was designed. In the second phase, the results of exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and reliability estimates confirmed the validity and reliability of the instrument. The results of CFA refined the final version of the instrument. The Language Teacher Emotion Regulation Inventory (LTERI) includes 27 items with six dimensions on a 5-point Likert scale. Each dimension assesses a discrete language teacher emotion regulation strategy at workplace: situation selection, situation modification, attention deployment, reappraisal, suppression, and seeking social support. In the third phase, the validated instrument, LTERI was utilized across two different milieus of language teaching in Iran, namely school and university. To do so, an independent samples t-test was applied. As the findings of this phase demonstrated, there is a statistically significant difference between English as a foreign language (EFL) teachers in the two contexts regarding the employed emotion regulation strategies in their professional lives. The implications of the current study can open new perspectives in educational psychology and teacher well-being. Furthermore, the Language Teacher Emotion Regulation Inventory (LTERI) contributes to the field of teacher education by filling the measurement lacuna and advancing quantitative studies in this regard. More significantly, the implications of this study may uncover new prospects for effective teaching and learning, especially during the COVID-19 pandemic, which can provoke various emotional demands for both teachers and learners.

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“…Researchers derive emotions from expressions of face, speech and various physiological signals. The analysis of facial expressions is a great way to find emotions [25][26][27][28][29] since human face displays emotions very aptly even without a single word uttered. Voice recordings are potentially important for expressing the speakers' mental state and their intentions.…”

Section: A Speech Emotion and Classificationmentioning

confidence: 99%

Big Data Classification for the Analysis MEL Scale Features Using KNN Parameterization

Osadchyy¹,

Skuratovskii

2020

International Journal of Circuits, Systems and Signal Processing

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The role of human speech is intensified by the emotion it conveys. The parameterization of the vector obtained from the sentence divided into the containing emotional-informational part and the informational part is effectively applied. There are several characteristics and features of speech that differentiate it among utterances, i.e. various prosodic features like pitch, timbre, loudness and vocal tone which categorize speech into several emotions. They were supplemented by us with a new classification feature of speech, which consists in dividing a sentence into an emotionally loaded part of the sentence and a part that carries only informational load. Therefore, the sample speech is changed when it is subjected to various emotional environments. As the identification of the speaker’s emotional states can be done based on the Mel scale, MFCC is one such variant to study the emotional aspects of a speaker’s utterances. In this work, we implement a model to identify several emotional states from MFCC for two datasets, classify emotions for them on the basis of MFCC features and give the comparison of both. Overall, this work implements the classification model based on dataset minimization that is done by taking the mean of features for the improvement of the classification accuracy rate in different machine learning algorithms.

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Emotions, Psychological Structure of

Cited by 24 publications

References 32 publications

Emotional Self-Regulation in Sport and Performance

Emotional Self-Regulation in Sport and Performance

Measuring Language Teacher Emotion Regulation: Development and Validation of the Language Teacher Emotion Regulation Inventory at Workplace (LTERI)

Big Data Classification for the Analysis MEL Scale Features Using KNN Parameterization

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