Affective science最新文献

Psychological well-being tends to increase throughout adulthood, but age-related differences in emotion dynamics have been less explored. By examining patterns of emotion dynamics across age, we can gain deeper insight into potential areas where age-related emotional advantages do and do not exist. In the present study, an adult lifespan sample (N = 290, aged 25–85) completed an experience sampling protocol in which they reported their current emotional experiences six times a day for ten days. We examined age as a predictor of composites of mean-level, intensity, frequency, instability, and inertia of positive emotions (PA: excited, enthusiastic, happy, grateful, peaceful, relaxed) and negative emotions (NA: stressed, nervous, angry, disgusted, sad, sluggish, bored), as well as discrete emotions. Age predicted lower mean-level, intensity, and frequency of NA and this pattern generally replicated across discrete negative emotions. Age was not associated with mean-level or intensity of PA, but it predicted higher PA frequency. Regarding discrete positive emotions, age predicted higher mean-level happiness, higher mean-level and intensity of peacefulness and relaxation, and lower intensity of excitement. Age predicted less inertia of PA, peacefulness, and relaxation (but not NA) and less instability of both NA and PA. This work highlights the value of considering multiple indices of emotion dynamics in age-diverse samples. While older adults demonstrated lower levels of NA, their NA carried over from one time point to the next similarly to young adults. On the other hand, PA was more frequently experienced by older adults but more inert for young adults.

Alexithymia is characterised by difficulties identifying and describing feelings, as well as a lack of focus on feelings. Alexithymia is a transdiagnostic risk factor for developing a wide array of psychopathologies, such as anxiety and depression, with a key hypothesised mechanism being the impairing impact of alexithymia on emotion regulation competency. However, no study has tested whether difficulties with emotion regulation mediate the link between alexithymia and psychopathological symptoms using longitudinal designs. The present study aimed to address this limitation by collecting data from 164 Iranian high school students (73% male; aged 13–18 years old) at two time points, 7 months apart. The results revealed that baseline alexithymia levels not only related to future emotion regulation difficulties but predicted increased emotion regulation difficulties in the future. Furthermore, these increased difficulties in emotion regulation mediated the relationship between baseline alexithymia and worsening of psychological distress (i.e., depression, anxiety, and stress symptoms) over time. This study helps link alexithymia and emotion regulation difficulties and highlights the critical role that alexithymia plays in emotional health and illness during adolescence.

The voice is a powerful social signal and a primary channel for communicating emotions when speakers are out of view. When we hear an emotional voice, we quickly form an impression of the person behind it. Neurocognitive models emphasize the multi-step dynamic operations that occur when listeners decode emotional information from vocal sounds. However, these models have primarily focused on stimulus quality, often neglecting the perception of other relevant person characteristics (e.g., gender, age, personal identity) evolving on different timescales. How do the emerging details about the speaker affect how listeners decode emotional information? And how are these different types of information integrated into a comprehensive impression of the speaker? This review examines recent data highlighting multiple stages of vocal expression analysis and the interplay between distinct types of nonverbal information revealed in the speaker’s voice. It serves as a starting point for broader research examining how distinct person characteristics, perceived simultaneously or in close succession, interact and affect the decoding of vocal emotions.

We all get angry. And some of us get angrier than others. But are such differences systematic across groups? Affective scientists often make claims about group differences in emotional intensity by comparing group averages on labeled (e.g. Likert) scales. For example, prominent research has used such scales to claim, perhaps counterintuitively, that women experience anger more intensely than men. Despite their ubiquity, these measures are susceptible to a subtle but notorious problem: the El Greco fallacy. (El Greco famously painted elongated figures. Could this be because he experienced a stretched-out world, due to a type of astigmatism? No, since then he would also have experienced a stretched-out canvas, and the effects would necessarily cancel out.) Here, across four experiments, we replicate the apparent finding with labeled scales that women experience anger more intensely than men. But we then go on to show that this finding reliably disappears when tested with a general Labeled Magnitude Scale (gLMS) — a psychophysical measure designed to detect such differences, avoiding the El Greco fallacy. This demonstrates how insights from sensory psychophysics can be usefully employed in affective science, and supports skepticism about purported group differences in emotional intensity based on labeled scales. The deep lesson for psychological measurement: the most obvious tools are not always the best.

Standardized image datasets play an essential role in emotion research, but conventional creation methods often demand extensive manual effort and are thereby limited in scope. Recent advancements in Artificial Intelligence (AI), especially the Text-to-Image Synthesis (TIS) technique combined with prompt engineering, could offer a promising alternative for generating emotional images for psychological research. The present study introduces a novel procedure for emotional image generation, consisting of Seed Prompt Formation, Prompt Set Generation, and TIS to generate emotional images. Using Midjourney and ChatGPT as tools, we evaluated the effectiveness of this procedure through the creation of an AI-Generated Emotional Image Set (AGEIS), which encompasses seven emotion categories (sadness, disgust, amusement, inspiration, fear, tenderness, and neutral). Human evaluations revealed that the AI-generated images in AGEIS induced target emotions effectively and specifically. Additionally, AGEIS images in general were perceived as comparably authentic to real photos in terms of their likelihood of being AI-generated, although AGEIS images depicting disgust and tenderness were more likely to be identified as AI-generated. Taken together, this procedure offers a cost-effective and scalable method for emotional image generation, potentially advancing emotion research into new directions such as large-scale and longitudinal studies.

The perception of emotional expressions is affected by our knowledge and experience, and the context in which they are presented. Social interactions are a natural context in which expressions are viewed, yet we are only beginning to understand how they impact our perception. In three online studies, we investigated whether social interaction contexts impact on the perceived valence intensity of emotional whole-body stimuli. We manipulated whether the dyads were presented within a social interaction or not by changing their arrangement (face-to-face, and back-to-back, respectively). Emotionally expressive dyads were presented, where both individuals expressed the same basic emotion (happy-happy, angry-angry, or neutral–neutral), and we measured the perceived intensity of the interactants’ valence. In Experiment 1, participants (N = 68) perceived happy and angry bodies to be more intensely positive and negative, respectively, when presented face-to-face than back-to-back for an unlimited duration. In Experiment 2, we limited the presentation duration to 500ms, and found that participants (N = 65) perceived angry bodies as more intensely negative when presented face-to-face than back-to-back. In Experiment 3, we replaced one of the interactants with an arrow, and manipulated their arrangement. Participants (N = 64) rated the intensity of the bodies similarly irrespective of their arrangement with the arrows. Our findings show that interaction contexts influence the perception of interactants’ valence intensity, and the effects are not driven by attentional cueing. These results have implications for how interactions are perceived, which may inform how we respond when we encounter groups of people in everyday life.

Laboratory experiments and daily life approaches for examining emotion regulation (ER) success each have their advantages. The former allows researchers to isolate causal mechanisms and the latter provides an externally valid way to understand how effective people are at managing emotions. However, these methodologies sometimes find different patterns. We theorize that the degree to which perceived ER success in the laboratory and in daily life are related depends on features of the regulation context (e.g., in situations where individuals hold greater pro-hedonic motives) and characteristics of the regulator (e.g., age). In the present study, 211 adults (n = 66 younger adults; n = 87 cognitively normal [CN] older adults; n = 58 older adults with mild cognitive impairment [MCI]) completed a lab-based paradigm of ER and experience sampling of ER in daily contexts (7 × for 9 days). Overall, ER success in the laboratory had minimal associations with ER success in daily life. The associations between ER success in the laboratory and in daily life did not vary based on daily pro-hedonic motive or group membership. Pro-hedonic ER motivation was linked to less daily ER success. There were age-related advantages in daily ER success, even among older adults with MCI. Altogether, our findings suggest that laboratory assessments may capture distinct aspects of ER ability compared to daily life assessments. More work is needed to test the robustness of this effect and consider other factors that may strengthen or weaken the connection between findings in the laboratory and in daily life.

Cognitive reappraisal is one of the most commonly used and effective emotion regulation strategies. This is partly because reappraisal targets a key characteristic of emotion – namely, what an emotion is about (i.e., intentionality). It is commonly assumed that whereas emotions have intentionality because they are about something, mood states do not have intentionality because they are typically not about anything in particular. Given that reappraisal targets intentionality, and mood states theoretically lack intentionality, we hypothesized that reappraisal would be less effective in regulating moods than in regulating emotions. We tested this hypothesis in two studies, one in which we assessed naturally occurring experiences and regulation in daily life (Study 1, N = 184), and another in which we manipulated experiences and regulation in a controlled experiment (Study 2, N = 65). In both studies, we compared the effects of cognitive reappraisal with those of distraction, which is another effective emotion regulation strategy that does not target intentionality. As expected, cognitive reappraisal, but not distraction, was more effective in regulating emotions than moods. These findings suggest that the regulation of emotions may differ from the regulation of moods and that strategies that may be effective in regulating one type of affective state may be less effective in regulating another.

Does upward social mobility shape how individuals navigate emotion-laden experiences? The current study examined this question in the context of academic achievement in a sample of first-generation college students. As the first in their families to attend university, this is a group that finds themselves in university environments that encourage open expression of individual achievement, but who typically come from sociocultural backgrounds where there is wariness of the social distancing that can be created by open expression of individual achievement. Qualitative methodology, which allows for in-depth exploration that can generate novel insights and advance theory, was used to study how first-generation college students at the graduate level (N = 32) navigate the emotions that come with academic achievements across academic and family contexts. Thematic analysis of the participant qualitative interview corpus revealed two novel findings. First, participants expressed feelings of both pride and gratitude that included appreciation for those who helped them reach their achievements. Second, participants engaged in capitalization regulation—a term that we introduce to describe the thoughtful consideration of how and with whom to share good news with across one’s different social contexts so as to not evoke negative social consequences. These findings contribute to the field’s growing understanding of emotion and social class in an important context, first-generation college students, in which these factors are salient. Implications for understanding the complex emotional experiences associated with upward social mobility are discussed.