Emotion Generation and Emotion Regulation: One or Two Depends on Your Point of View

Stanford University.
Emotion Review (Impact Factor: 2.9). 01/2011; 3(1):8-16. DOI: 10.1177/1754073910380974
Source: PubMed


Emotion regulation has the odd distinction of being a wildly popular construct whose scientific existence is in considerable doubt. In this article, we discuss the confusion about whether emotion generation and emotion regulation can and should be distinguished from one another. We describe a continuum of perspectives on emotion, and highlight how different (often mutually incompatible) perspectives on emotion lead to different views about whether emotion generation and emotion regulation can be usefully distinguished. We argue that making differences in perspective explicit serves the function of allowing researchers with different theoretical commitments to collaborate productively despite seemingly insurmountable differences in terminology and methods.

Download full-text


Available from: Lisa Feldman Barrett
  • Source
    • "Emotions are considered by theorists and researchers to fall within the broader concept of affect, but are distinct from other affective phenomena, such as moods, in that they are more intense, have a clearer object-focus, a more salient cause (linked to an event and situation), and are experienced for a shorter duration (Scherer, 2005 ; Shuman & Scherer, 2014 ). A rich history of scholarly interest in emotions (e.g., Darwin, 1872 ; James, 1890 ) has produced a number of theories of emotion (for review see Gendron & Barrett, 2009 ; Gross & Barrett, 2011 ) including theories of basic emotions (e.g., Ekman, 1992 ; Ekman & Cordar, 2011 ; Izard, 1993 ), psychological construction (e.g., Barrett, 2009 ; Russell, 2003 ), and appraisal theories (e.g., Frijda, 1986 ; Lazarus, 1991 ; Scherer, 1984 ). For the purposes of this "
    [Show abstract] [Hide abstract]
    ABSTRACT: Emotions serve an important role in learning and performance, yet their role in medical education has been largely overlooked. In this chapter, we examine how multiple research methodologies and measures can be used to detect and analyze emotions within authentic medical learning environments. Our goal is to highlight conceptual, methodological, and practical considerations that should be attended to by researchers, educators, and medical professionals interested in examining the role of emotions within medical education. Findings from our literature review and empirical work suggest that appraisal models that treat emotions as multi-componential (e.g., control-value theory) can provide a fruitful framework for examining links between emotions and learning. In terms of measuring emotions, self-report can be useful with respect to scalability and capturing subjective experience, whereas behavioral and physiological measures provide continuous data streams and are less susceptible to cognitive or memory biases. Other factors researchers and health sciences professionals should take into consideration when selecting a measure of emotion include: efficiency; level of granularity; and person-centered versus group-level analyses. Recent work suggests that multiple measures of emotions can be integrated into affect-aware learning technologies to aid instructional design by detecting, tracing, and modeling emotional processes during learning.
    Full-text · Chapter · Jan 2016
  • Source
    • "Gross [6] proposed an important theoretical framework that describes how individuals regulate emotions they have, when they have them and how they experience and express them. According to this emotion regulation framework there are two major categories of emotion regulation strategies: the first category concerns strategies that are used before an emotion has an effect on the behavior (antecedent-focused strategies) and the second category concerns strategies that are used when the emotional response is already coming into effect in the sense of expression or behavior after an emotion is generated (response-focused strategy) [13], [15], [20]. "
    [Show abstract] [Hide abstract]
    ABSTRACT: In this paper a cognitive model is introduced which integrates a model for emotion generation with models for three different emotion regulation strategies. Given a stressful situation, humans often apply multiple emotion regulation strategies. The presented computational model has been designed based on principles from recent neurological theories on brain imaging, and psychological and emotion regulation theories. More specifically, the model involves emotion generation and integrates models for three emotion regulation strategies: reappraisal, expressive suppression, and situation modification. The model was designed as a dynamical system. Simulation experiments are reported showing the role of three emotion regulation strategies. The simulation results show how a potential stressful situation in principle could lead to emotional strain and how this can be avoided by applying the three emotion regulation strategies decreasing the stressful effects.
    Full-text · Conference Paper · Nov 2015
  • Source
    • "Statebased assessments of emotion regulation difficulties would also have utility in the context of psychological treatments. Maladaptive efforts to modulate unwanted or aversive emotional experiences are theorized to play a central role in numerous forms of psychopathology (e.g., eating disorders, mood and anxiety disorders, borderline personality disorder, posttraumatic stress disorder, substance use disorders; e.g., Baker, Piper, McCarthy, Majeskie, & Fiore, 2004; Boden, Kulkarni, Shurick, Bonn-Miller, & Gross, 2014; Haynos & Fruzzetti, 2011; Hofmann, Sawyer, Fang, & Asnaani, 2012; Linehan, 1993; Mennin, Heimberg, Turk, & Fresco, 2002) and, as such, are an important target of interventions for these disorders (see, Gratz, Weiss, & Tull, 2015). The development of an empirically supported measure of state emotion regulation difficulties would have utility for both research (e.g., in studies investigating emotion regulation as an outcome or mechanism of psychological treatments, or seeking to examine the factors that contribute to the use of maladaptive emotion regulation strategies) and clinical practice (e.g., providing a way to track changes in emotion regulation difficulties in response to specific stimuli over the course of treatment). "
    [Show abstract] [Hide abstract]
    ABSTRACT: Existing measures of emotion dysregulation typically assess dispositional tendencies and are therefore not well suited for study designs that require repeated assessments over brief intervals. The aim of this study was to develop and validate a state-based multidimensional measure of emotion dysregulation. Psychometric properties of the State Difficulties in Emotion Regulation Scale (S-DERS) were examined in a large representative community sample of young adult women drawn from four sites (N = 484). Exploratory factor analysis suggested a four-factor solution, with results supporting the internal consistency, construct validity, and predictive validity of the total scale and the four subscales: Nonacceptance (i.e., nonacceptance of current emotions), Modulate (i.e., difficulties modulating emotional and behavioral responses in the moment), Awareness (i.e., limited awareness of current emotions), and Clarity (i.e., limited clarity about current emotions). S-DERS scores were significantly associated with trait-based measures of emotion dysregulation, affect intensity/reactivity, experiential avoidance, and mindfulness, as well as measures of substance use problems. Moreover, significant associations were found between the S-DERS and state-based laboratory measures of emotional reactivity, even when controlling for the corresponding original DERS scales. Results provide preliminary support for the reliability and validity of the S-DERS as a state-based measure of emotion regulation difficulties. © The Author(s) 2015.
    Full-text · Article · Aug 2015 · Assessment
Show more