Affective science最新文献

In this commentary, we expand on the special issue themes of applied affective science, ecologically valid data and application, and the need for transdisciplinary collaboration by discussing and exemplifying how affective science can inform behavioral public policy.

Affective science has increasingly sought to represent emotional experiences multimodally, measuring affect through a combination of self-report ratings, linguistic output, physiological measures, and/or nonverbal expressions. However, despite widespread recognition that non-facial nonverbal cues are an important facet of expressive behavior, measures of nonverbal expressions commonly focus solely on facial movements. This Commentary represents a call for affective scientists to integrate a larger range of nonverbal cues—including gestures, postures, and vocal cues—alongside facial cues in efforts to represent the experience of emotion and its communication. Using the measurement and analysis of vocal cues as an illustrative case, the Commentary considers challenges, potential solutions, and the theoretical and translational significance of working to integrate multiple nonverbal channels in the study of affect.

People with larger body sizes often face underrepresentation in popular media. However, the rise of social media has led to increased visibility for this demographic group. Our research, encompassing five studies, investigated how audiences react to social media images featuring individuals with larger body sizes, focusing on affective responses and social transmission dynamics. We identified a gender-specific gap in sharing behavior such that male viewers show lower sharing intentions for such images (Study 1), mediated by stereotypic perceptions of low competence in larger-sized people and decreased positive affect (Study 2). This pattern holds for images with both female and male models (Study 3) and extends to contexts where body size is not a central factor (Study 4). To address this, we developed social norm-based interventions that effectively increase sharing intentions evoked by images of people with larger bodies, mediated by social perceptions and affective responses (Study 5). Overall, our findings shed light on the psychological factors that influence the spread of body-related imagery on social media, demonstrating how stereotypes can shape affective responses and subsequent actions like social media sharing. Beyond theoretical insights, our research offers practical strategies for amplifying societal focus on underrepresented groups and promoting more diverse and inclusive representations of body image in digital spaces.

Social media (SM) is widely used among adolescents, making the relationship between SM and affect in this population important to understand. However, previous research has largely used methods that do not capture the dynamic and variable nature of SM or measure the consistency of effects across global affect and specific emotions. The current study examined the momentary relationship between positive and negative SM experiences and global positive affect (PA) and negative affect (NA), as well as specific affective states of PA and NA. Adolescents (N = 62; 14–17 years old) were recruited from SM platforms to participate in an eight-week ecological momentary assessment study. Participants reported three times per day on PA and NA and positive and negative SM experiences. Random intercept and random slope models were used to examine within-person associations between momentary positive and negative SM experiences and affect after controlling for between-person differences. At prompts when participants reported greater-than-usual positive SM experiences, they reported higher global PA and lower global NA. At prompts when participants reported greater than their average negative SM experiences, they endorsed lower global PA and higher global NA. These results were consistent across same-valence specific affective states. The current study highlights proximal associations between SM experiences and affect, highlighting potential avenues of short-term risk and protection. 

With the rise and ubiquity of social media (SM), the context for peer interactions has changed drastically for adolescents, yet, little is known about how digital peer interactions compare to in-person interactions in their impact on adolescents’ emotional experiences. Adolescents employ various emotion regulation (ER) strategies to navigate the complexities of peer interactions, with varying strategy adaptiveness and efficacy. This study delves into the prevalence of ER strategies following daily negative peer interactions on SM, exploring to what extent context (SM or in-person) influences the selection of ER strategies. Over 16 days, 106 U.S. adolescent girls, aged 11–13 (half at high risk for developing an affective disorder), participated in ecological momentary assessments, detailing their worst recent peer interactions, the context (SM or in-person), and the subsequent ER strategies employed. Multilevel models revealed that teens were more prone to rumination after negative peer interactions on SM than in-person (OR = 2.08, p = .031), after adjusting for the overall prevalence of SM and in-person interactions. No other significant differences emerged in ER strategy selection based on the context of the interaction. Findings highlight that although adolescents may adapt their ER strategy selection to suit the demands of specific interpersonal situations across contexts, negative peer interactions on SM may lead to more rumination, potentially contributing to the link between SM use and depression. We discuss how unique features of SM might elicit rumination, such as SM’s lack of physical social cues and its permanent, public, and asynchronous nature.

There is much interest in the role of social media (SM) in the current mental health crisis among teens. In this review, we focus on the question of “for whom” SM experiences have the strongest impact on emotional health, considering neural sensitivity to social evaluation as a potential vulnerability factor that makes youth more susceptible to the effects of SM. We first present behavioral evidence showing that sensitivity to social evaluation moderates the link between SM use and emotional health in youth. Next, we show that the brain’s affective salience network responds to simulated online social threats in ways that predict emotional health. Finally, we show evidence that neural sensitivity to online social evaluation moderates the effects of peer social experiences on emotional health, with implications for social media experiences. We end with recommendations for fully testing the model.

This study investigated the role of circadian rhythms in online information sharing. We gathered 416,914 posts from the social media platform X (formerly Twitter). We identified daily patterns of collective positive and negative affect in these posts, consistent with previous research on social media and circadian rhythms. We created predicted values of positive and negative affect for each post, based on the time a post was created. We then used these predicted values for each post to estimate that post’s likelihood of being reshared. We controlled for a range of possible confounders, such as the actual positive and negative affect expressed in a specific post and the number of existing followers and previous posts of the user who created the post, as well as whether the post contained hashtags, mentions, and quotes. The results support a strong relationship between the predicted positive and negative affect of a post—based on circadian patterns of collective positive and negative affect—and the likelihood of a post being shared. We further examine seasonal changes and design a natural experiment, in which we compare patterns of positive and negative affect and information sharing before and after the clocks change, i.e., “spring forward” and “fall back.” The results suggest that these daily collective patterns of positive and negative affect on social media are influenced, at least partly, by hormonal influences and not only collective daily routines.

Job boredom is one of the most common negative affective states experienced in the workplace, yet also among the least well-understood. One stream of research suggests that employees frequently react to job boredom by engaging in counterproductive work behaviors (CWB). However, recent studies show the converse—that engaging in CWB relates to job boredom. As studies on the job boredom-CWB relationship primarily have been cross-sectional and at the between-person level of analysis, the directionality between these constructs remains in question. Therefore, research examining the within-person dynamics of job boredom and CWB within a short timeframe is needed. In the current study, we explore whether job boredom influences subsequent changes in CWB and vice versa. We examined these relationships using latent change score (LCS) modeling with 10-day experience sampling data (N = 120 individuals providing 1,161 observations). Findings supported a reciprocal relationship. Employees’ level of job boredom on a given day was associated with a subsequent increase in CWB on the next day, and the level of CWB on a given day was associated with a subsequent increase in job boredom on the next day. We discuss the implications of our findings, study limitations, and future research directions.

Despite societal and empirical interest in the impact of computer-mediated communication (CMC) on anxiety in adolescents, little is known about the associations between specific aspects of CMC use and anxiety severity and the role of individual vulnerability factors. In this study, we examined the links between two contexts of CMC, preference for CMC over face-to-face interactions and perceived social media social media burden, along with an anxiety-related cognitive vulnerability factor and attention bias to threat. Participants were mildly to severely anxious 12- to 14-year-olds (N = 78, M_age = 12.89, 55% female). They self-reported on CMC preferences and social media burden and on anxiety symptoms in two domains (generalized anxiety disorder (GAD) and social anxiety) and completed an eye-tracking assessment of attention bias. We tested the hypothesis that preferring CMC over face-to-face communications and perceiving greater social media burden would predict more severe anxiety symptoms, particularly among those with greater attention bias to threat. As predicted, greater feelings of social media burden predicted more severe anxiety symptom severity (GAD only) but only among those with greater attention bias to threat. The potential role of attention bias in associations between CMC and adolescent anxiety and the specificity of effects on GAD symptom severity is discussed.

Emotion dynamics have demonstrated mixed ability to predict depressive symptoms and outperform traditional metrics like the mean and standard deviation of emotion reports. Here, we expand the types of emotion dynamic features used in prior work and apply a machine learning algorithm to predict depression symptoms. We obtained seven ecological momentary assessment (EMA) studies from previous work on depression and emotion dynamics (N = 890). These studies measured self-reported sadness, positive affect, and negative affect 5 to 10 times per day for 7 to 21 days (schedule varied across studies). These data were fed through a feature extraction routine to generate hundreds of emotion dynamic features. A gradient boosting machine (GBM) using all available emotion dynamics features was the best of all models assessed. This model’s out-of-sample prediction (R²_pred) for depression severity ranged from .20 to .44 depending on EMA interpolation method and samples included in the analysis. It also explained significantly more variance than a benchmark model of individuals’ mean emotion ratings over the assessment period, R²_pred = .089. Comprehensive feature mining of emotion dynamics obtained during EMA may be necessary to identify processes that predict depression symptoms beyond mean emotion ratings.