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Based on previous literature, we expected that measures of interoception would show a positive relationship with emotional intensity and arousal, whereas measures of emotional conceptualization would show a positive association with emotional intensity, arousal, and granularity ( Pollatos et al., 2007; Lindquist and Barrett, 2014). Imi Lo is a consultant and published author with extensive and international experience in mental health and psychotherapy. A total of 130 participants (99% of the included sample) performed the DRM ( Table 3). Correlational analysis between emotional intensity and granularity scores showed that emotional intensity did not correlate with emotional granularity for positive [ r(128) = 0.13, p = 0.13] or negative words [ r(117) = −0.03, p = 0.74]. Additionally, no association was observed between emotional granularity for positive and negative words, r(116) = 0.13, p = 0.17. Sensibility and Monitoring predict lower emotional intensity Overall, the results showed a significant improvement in face expression recognition with age for the three tasks. More specifically, the 5-year-olds had lower performances on the three tasks than the 6-year-olds, then a linear improvement from age 6 to adulthood was observed. A different developmental pattern for the emotion matching task was observed, showing that the children aged 4, 6, and 7 had significantly lower performances than on emotion identification and FDT. Finally, the 5-year-olds performed better on identification than matching and FDT, but no difference between emotion matching and FDT was observed. The differences among the three tasks disappeared from age 8 to adulthood. The absence of difference between identification and FDT could be explained by the task condition. In both tasks the emotion expression was named by the experimenter and the participants had to choose the corresponding expression among three faces (identification task) or among three labeled propositions made by the experimenter (FDT). According to the literature, success on these two tasks depends more on semantic representation, which develops early, while matching facial expressions depends more on visual-perception processing, which takes a longer maturation course [ 4, 7, 10].
In summary, in the current study, we used self-report measures of interoception and emotional conceptualization to investigate how they interact in moderating different aspects of the emotional experience, namely, emotional intensity, arousal, and granularity. The interrelation between interoception and emotional conceptualization scales revealed two latent constructs that differently moderate the emotional experience. The Sensibility factor, which reflects beliefs of the accuracy of an individual in detecting internal (i.e., physiological and emotional) states, predicted higher granularity for negative words. The Monitoring factor, interpreted as the tendency to focus on the internal states of an individual, was negatively related to emotional granularity, intensity, and diminished psychological well-being. Additionally, the two factors showed differential associations with measures of well-being and adaptability. Sensibility scores were more strongly associated with greater well-being and adaptability than Monitoring scores. Thus, within inference accounts of emotion, these two factors could be interpreted as part of the intertwined components t Frijda, N. H., Ortony, A., Sonnemans, J., & Clore, G. (1992). The complexity of intensity. In M. S. Clark (Ed.), Emotion. Review of personality and social psychology (pp. 66–89). Newbury Park: Sage. Granularity scores for negative emotions were differently moderated by Monitoring and Sensibility. Whereas Monitoring predicted lower granularity scores, t(78) = −2.96, p = 0.004, β = −0.31, Sensibility was associated with higher granularity, t(78) = 2.59, p = 0.011, β = 0.27. No interaction effects were observed, t(78) = 0.07, p = 0.94, β = 0.001 ( Figure 2). Association Between Principal Component Analysis Factors and Adaptability and Well-Being ScalesNeither granularity scores for positive nor negative emotions showed a significant association with the factor scores. For positive emotions: Monitoring: t(84) = −1.0, p = 0.31, β = −0.109; Sensibility: t(84) = −0.50, p = 0.61, β = −0.056; Monitoring × Sensibility: t(84) = −0.05, p = 0.96, β = −0.01. For negative emotions: Monitoring: t(84) = −0.5, p = 0.61, β = −0.054; Sensibility: t(84) = 0.45, p = 0.65, β = 0.05; Monitoring × Sensibility: t(84) = 0.89, p = 0.39, β = 0.09. Day Reconstruction Method (DRM) Waugh, C. E., Hamilton, J. P., & Gotlib, I. H. (2010). The neural temporal dynamics of the intensity of emotional experience. NeuroImage, 49(2), 1699–1707. https://doi.org/10.1016/j.neuroimage.2009.10.006. Olofsson, J. K., Nordin, S., Sequeira, H., & Polich, J. (2008). Affective picture processing: An integrative review of ERP findings. Biological Psychology, 77(3), 247–265. https://doi.org/10.1016/j.biopsycho.2007.11.006. Because the conceptualization component is involved in the categorization of emotions during a particular event, it is expected that a more efficient conceptualization is reflected by higher accuracy in perceiving and understanding emotions. To evaluate individual differences in conceptualization, we selected a series of questionnaires that assess how (in)accurately one perceives their own emotions ( Bagby et al., 1994; Swinkels and Giuliano, 1995; Kang and Shaver, 2004). Toronto Alexithymia Scale (TAS-20) Nevertheless, a few studies that assessed the identification of lower intensity emotion expressions in children offer more nuanced comprehension of developmental trends of emotion recognition abilities during childhood. The sensitivity to a more subtle intensity of emotion expressions could help children to infer others’ feelings more precisely, which could be predictive of success in encoding emotion information [ 2, 15, 16].
A series of questionnaires were selected to measure individual differences in interoception and conceptualization along with psychological well-being and adaptability. Interoception Scales These provocative chapters challenge what we think we know about emotional sensitivity, intensity, and giftedness. Combining psychological theories, spiritual wisdom, and practical exercises, it brings you to new ways of thinking about yourself, so you can reclaim your unique empathic and intellectual gifts, and fulfil your creative potential. The ability to attribute low intensity emotional expressions mediates, in a complementary manner, the relationship between age and the global emotion expression score. Imi is the founder of Eggshell Therapy - a practice that is dedicated to serving emotionally intense people. Though it is based in London, her work has attracted interest and clients from all around the UK and the world.The Monitoring factor reflects a general tendency to devote attentional resources to the internal physiological and emotional states of an individual. The role of selective and executive attention is crucial in the construction and experience of emotions ( Barrett, 2017a; Smith et al., 2019). Which aspect of the ongoing processing the attention is deployed to, e.g., either to the bodily changes, or the surrounding environment, may have a strong influence on the interpretation of the current state of an individual ( Barrett et al., 2004). Emotional intensity was taken as the intensity of the emotional word with the highest rating for each trial, which was averaged across trials. Emotional arousal was extracted by averaging the experienced arousal across trials in the ED task. Because intensity and arousal scores were negatively skewed ( skewness>−0.79), they were normalized using the following formula: sqrt(max(S + 1) – S), where S refers to the mean intensity/arousal scores. Normal distribution was achieved after applying this transformation (0.06 < skewness< 0.09). Previous studies investigating how individual differences in interoception and emotional conceptualization may relate to emotional experience focused on three main aspects: emotional intensity, activation or arousal, and granularity. Emotional intensity is defined as the strength with which a particular emotion is felt, ranging from high (e.g., “extremely happy”) to low (e.g., “not happy at all”). Emotional activation or arousal is a more general term encompassing the degree of activation in a specific situation and typically ranges from calm to active or excited (e.g., Lang et al., 1990; Cacioppo and Berntson, 1994; Reisenzein, 1994; Barrett and Russell, 1999; Kuppens et al., 2013). Although emotional intensity and arousal may overlap, emotional arousal is not always associated with high intensity, for instance, emotions such as satisfaction or sadness can be experienced with high intensity under low arousal states ( Kuppens et al., 2013). Emotional granularity is defined as the ability to precisely differentiate emotions. People with high emotional granularity are able to label their emotional experience in precise terms (i.e., distinguishing between experiencing “sadness” and “compassion”) whereas those with low emotional granularity tend to use the same terms to describe different experiences (i.e., differentiating only between feeling “good” or “bad”; Lindquist and Barrett, 2008). She specializes in working with highly sensitive, intense, and gifted individuals . Her books Emotional Sensitivity and Intensity and The Gift of Intensity are available worldwide and in multiple languages. The Well-Being Questionnaire (W-BQ12; Mitchell and Bradley, 2001) consists of 12 items, evaluating psychological well-being by asking about the frequency of experiencing different feelings over the past few weeks. Each item is scored using a 4-point Likert-scale, ranging from 0 (not at all) to 3 (all the time). The W-BQ12 is divided into three 4-item subscales: Negative Well-Being (NWB; e.g., I have crying spells or feel like it), Positive Well-Being (PWB; e.g., I have lived the kind of life I wanted to) and Energy (e.g., I feel energetic, active, or vigorous). The scores for each subscale are calculated by summing the scores of each item. The general well-being score is calculated using the following formula: 12-NWB + Energy + PWB. In our sample, the W-BQ12 showed poor consistency (Cronbach’s α = 0.5). However, we decided to use this scale due to its established construct validity. Tasks
To investigate the relationship between interoception and emotional conceptualization questionnaires, Pearson’s correlation analyses were performed. Thereafter, Principal Component Analysis (PCA) was performed to extract the factors underlying the questionnaire scores. Initially, a PCA with varimax rotation (i.e., to maximize simple structure) was performed to identify the number of relevant underlying factors.Granularity scores for positive emotions were negatively associated with Monitoring, t(86) = −1.99, p = 0.049, β = −0.21 but not with Sensibility, t(86) = −1.17, p = 0.24, β = −0.120. No significant interaction effects were observed, t(86) = −1.07, p = 0.28, β = −0.11 ( Figure 2).
Our results could be of particular interest to professionals and researchers working in the field of socio-emotion development. Indeed, improving the abilities to detect more subtle changes in face expressions could have a positive impact on socio-emotion development. It could support young children in their abilities to discriminate between different emotion expressions and in turn, elicit more adapted responses to some social situations [ 58, 59]. It could also be interesting for older children to develop their abilities to decode low intensity expressions, as this would allow them to better identify and understand more subtle emotions. This could facilitate the development of their socio-emotion competences by supporting the development of positive peer interaction and friendship, as well as emotion regulation abilities [ 1, 58, 60]. Previous theoretical models and empirical studies suggest that two different but complementary processes influence the disposition to understand and attend to physiological and emotional states ( Boden and Thompson, 2017; Murphy et al., 2019). Our results support and extend this distinction by showing that these independent processes similarly relate to both physiological and emotional states. Within the framework of TCE, the Sensibility factor may be associated with individual differences in conceptualization, whereas Monitoring may be associated with individual differences in attentional processes. However, future studies that combine self-report measures with objective and/or physiological correlates are needed to provide more insights into the distinction between these components. Association Between Sensibility and Emotional Granularity, Well-Being, and Adaptability Greenwald, M. K., Cook, E. W., & Lang, P. J. (1989). Affective judgment and psychophysiological response: Dimensional covariation in the evaluation of pictorial stimuli. Journal of Psychophysiology, 3, 51–64.Imi has two Master’s degrees and is trained in Jungian theories, philosophical counseling, mentalization-based treatment, solution-focused coaching, trauma-informed practices, and mindfulness-based modalities. She works holistically, combining psychological insights with Eastern and Western philosophies such as Buddhism and Stoicism. She is a faculty member of an UK Council for Psychotherapy accrediting institute and delivers lectures and workshops regularly for trainee therapists seeking accreditation, as well as supervising therapists as a clinical supervisor and mentor. The factor scores did not differentiate between interoceptive sensibility and emotional conceptualization scales. Instead, they revealed overlapping variance between measures of both components. Factor 1 mostly comprised scales measuring sensibility toward perceiving physiological changes and emotion and was named “ Sensibility.” Factor 2 consisted of scales that are related to perceptions about attentional resources devoted to physiological and emotional aspects and was labeled “ Monitoring.” Table 2 shows the loading scores from each of the scales. Relation Between Principal Component Analysis Factors and Emotional Intensity and Granularity Emotion Differentiation (ED) Task Schaefer, A., Braver, T. S., Reynolds, J. R., Burgess, G. C., Yarkoni, T., & Gray, J. R. (2006). Individual differences in amygdala activity predict response speed during working memory. Journal of Neuroscience, 26(40), 10120–10128.
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