Affective science最新文献

A developmental psychobiologist commented on the role of dynamic systems theory in the future of affective science and proposed an alternative paradigm.

While research has shown mixed effects of social media on mental health and well-being, little is known about the association between social media attitudes and objective measures of social interaction, such as linguistic authenticity. This study examined the relationship between self-reported social anxiety, linguistic authenticity, and Instagram contingent self-worth (ICSW). A total of 149 adults with active Instagram accounts completed online questionnaires and shared their Instagram comment data. Automated linguistic analysis of authenticity was performed on participants’ comment data using validated algorithms. Multiple linear regression showed that ICSW significantly moderated the relationship between social anxiety and linguistic authenticity, whereby higher levels of social anxiety marginally predicted lower linguistic authenticity at high levels of ICSW. As social media use continues to rise, this study emphasizes the need to explore the impact of social media interactions on emotional and social well-being.

The Future of Affective Science Special Issues illuminate where the field of Affective Science is headed in coming years, highlighting exciting new directions for research. Many of the articles in the issues emphasized the importance of studying emotion regulation, and specifically, social emotion regulation. This commentary draws on these articles to argue that future research needs to more concretely focus on the social aspects of social emotion regulation, which have been underexplored in affective science. Specifically, we discuss the importance of focusing on social goals, strategies and tactics, and outcomes relevant to social emotion regulation interactions, more closely considering these processes for all individuals involved. To do so, we draw on research from neighboring subdisciplines of psychology that have focused on the social aspects of interactions. Moreover, we underscore the need to better integrate components of the process model of social emotion regulation and approach empirical inquiry more holistically, in turn illuminating how piecemeal investigations of these processes might lead to an incomplete or incorrect understanding of social emotion regulation. We hope this commentary supplements the research in the special issues, further highlighting ways to advance the field.

When learning about stimuli comprised of multiple cues, humans and other animals tend to form stronger cue-outcome associations for more salient cues than for less salient cues. This phenomenon, termed overshadowing, has typically been demonstrated between cues that vary in salience because of differences in physical intensity. In this study, we investigated whether differences in the emotional valence of cues in a compound stimulus similarly led to differences in the strength of cue-outcome learning. Using a probabilistic categorisation task in which stimuli were compounds consisting of pairs of emotional or non-emotional cue images, we found consistent evidence for emotional overshadowing across both an initial exploratory study (N = 50) and a confirmatory preregistered replication study (N = 200). Specifically, both pleasant and unpleasant cue images tended to overshadow neutral cue images, but pleasant and unpleasant cue images did not overshadow one another. Moreover, across stimuli, the magnitude of differences in learning between cues was proportional to differences in their absolute emotional valence, suggesting that attentional capture by both positively and negatively valenced emotions drives overshadowing. These findings have implications for understanding associative learning in natural environments, where stimuli are frequently imbued with emotional valence prior to learning.

The recent Special Issue of Affective Science considered “The Future of Affective Science,” offering new directions for the field. One recurring theme was the need to consider the social nature of emotional experiences. In this article, we take an interdisciplinary approach toward studies of social connection that builds upon current theoretical foundations to address an important public health issue – loneliness. Loneliness is an affective state that is characterized by feelings of isolation and has widespread adverse effects on mental and physical health. Recent studies have established links between loneliness, social connection, and well-being, but most of this work has been siloed in separate fields. We bridge these themes, leveraging advances in technology, such as artificial intelligence-based voice assistants (e.g., Alexa), to illuminate new avenues for detecting and intervening against loneliness “in the wild.” Recognizing the power of connection among individuals as social beings and among researchers with shared goals, affective science can advance our understanding of loneliness and provide tangible benefits to society at large.

Affective science has taken up the challenge of building a bridge between basic affective science and practical applications. The articles in the Future of Affective Science issue lay out methodological and conceptual frameworks that allow us to expand affective science into real-world settings and to handle naturalistic methods. Along with these advances, accomplishing this goal will require additionally refocusing the types of experiences we study, and the measures of experience we are interested in. This paper explores the necessity for basic affective science to embrace the messy and complex nature of human emotion in order to bridge the gap between theoretical concepts and real-world applicability. Specifically, this involves studying experiences that do not fit as neatly into dominant conceptual frameworks, such as valenced scales and the most common discrete emotion categories, and that may be more difficult to measure or experimentally control. This makes the gap between affective science and real-world feelings larger. To move the field towards incorporating emotional complexity in an empirical manner, I propose measurement standards that err on the side of less fixed-choice options and using stimuli chosen for their potential to elicit highly complex responses over time within the same individual. Designing studies that can measure these experiences will push emotion theories to explain data they were not originally designed for, likely leading to refinement and collaboration. These approaches will help capture the full spectrum of human emotional experience, leading to a more nuanced and applicable understanding of affective science.

Social media (SM) groups can connect users to similar others and may be particularly valuable for marginalized populations who lack support in their offline lives. Prior research highlights substantial heterogeneity in users’ engagement with and experience in SM groups, which may relate to social and emotional health in important ways. The current study used a cross-sectional survey of users of Facebook groups for multiracial people (N = 424) to identify user profiles and test how profiles relate to depressive symptoms and global sense of belonging. Latent profile analysis identified three profiles: (1) casual users (62% of users), who engaged more passively yet experienced moderate levels of belonging in the group; (2) invested users (21%), who reported high active participation, self-disclosure, belonging, and perceived similarity; and (3) dissatisfied users (17%), who reported moderate active and passive use and self-disclosure, yet low belonging and high negative experiences. Invested users reported significantly greater depressive symptoms compared to dissatisfied users (d = .46) and significantly lower global belonging compared to casual users (d =  − .33). Men were more likely to be dissatisfied users, and LGBTQIA + individuals were more likely to be invested users. Findings support the social compensation hypothesis of SM use and the importance of considering gender and sexual orientation in the realm of online group participation. Although further research is needed to clarify causal pathways, findings suggest the potential value of SM groups as a source of connection and support for those who are distressed or lack access to offline support.

This data donation study explores how adolescents express emotions on social media, and how this expression varies by platform (Instagram, Snapchat, and TikTok) and posting modality (permanent and ephemeral content). Adolescents from Belgium (n = 115), France (n = 146), and Slovenia (n = 119) “donated” screenshots from their social media accounts, including their bios, most recent posts, and most recent stories. These screenshots were coded for both textual references to positive and negative emotion words and emojis, and visual expressions of positive and negative emotion. This data was then linked to the adolescents’ survey responses about their life satisfaction. The results showed a prevalence of positive emotional displays, both in text and visuals. Gender differences were evident, with girls more likely than boys to reference and express positive emotions. Additionally, a marginal difference was observed among countries: Slovenian participants showed fewer positive emotional references compared to Belgian and French participants. No significant links were found between online emotional expressions and life satisfaction. While this study offers initial insights into adolescents’ real online emotional behavior, future research should explore motivations and sociocultural influences, addressing gaps in understanding how individual and contextual factors impact social media use among adolescents.

When studying emotion and emotion regulation, typical approaches focus on intrapersonal processes. Although this emphasis clarifies what transpires within a person, it does not capture that much of emotional experience and regulation occurs between people. In this commentary, we highlight how the Cognitive-Affective Processing System (CAPS) approach—originally developed by Mischel and Shoda and extended to dyadic interactions by Zayas, Shoda, and Ayduk—can provide a unifying framework for understanding the complexity of everyday affective experiences. We discuss how this framework can be fruitfully applied to the study of emotion and emotion regulation broadly, and particularly to interpersonal emotion regulation, by considering both the mediating psychological processes within individuals, as well as the behavioral processes that transpire between individuals. To illustrate these points, we discuss some of the thought-provoking work in the special double issue on the Future of Affective Science edited by Shiota et al. (2023), and we offer forward-thinking suggestions and propose future research directions informed by the CAPS approach. By employing the CAPS framework, we can better capture the complexity of everyday affective experiences and synthesize the growing body of research in affective science.

The Future of Affective Science special issue covered a broad range of topics, ranging from the valuation and experience of emotions to their expression and regulation. Despite the breadth of these topics, consideration of diverse contexts was limited in that most studies relied on Western, Educated, Industrialized, Rich, and Democratic (WEIRD) samples and/or failed to explore the rich diversity present in those countries with vast population heterogeneity. We argue that a more systematic approach is essential to advance theory and research on how diverse contexts impact and interact with different components of emotion processes. Specifically, future research should compare a wider range of cultures; examine the interplay between culture, individual, and situation; and transcend the traditional Eastern/Western or WEIRD/non-WEIRD dichotomy and other group comparisons by embracing a dimensional approach to diverse contexts. We provide concrete examples of how leveraging these three approaches to expand the scope of diverse contexts can benefit the future development of affective science, a field heavily impacted by sociocultural context.