Tendency to Share Positive Emotions Buffers Loneliness-Related Negativity in the Context of Shared Adversity

The hidden network: community sense, social desirability, and their protective influence on negative emotions in aging populations

Background

With aging populations, understanding mechanisms linking social factors to emotional well-being in the older adult is critical. This study examines how social capital, social support, community sense, and social desirability interact to influence negative emotions.

Methods

A cross-sectional survey of 904 older adult individuals in Liaoning, China, utilized standardized scales: GDS-10 (negative emotions), SSRS (social support), BSCS (community sense), and MCSDS (social desirability). Mediation and moderation analyses were conducted.

Results

The results demonstrated significant negative correlations between social capital/social support and negative emotions. Social support was identified as a mediating factor linking social capital to reduced negative emotions. Additionally, community sense and social desirability moderated the relationship between social support and negative emotions, with stronger community belonging and higher social desirability amplifying the protective effect of social support.

Conclusion

These findings underscore the importance of fostering social capital, strengthening social support networks, cultivating community integration, and addressing social desirability biases to alleviate negative emotions in the older adult. The study provides actionable insights for designing targeted mental health interventions aimed at improving emotional well-being in aging populations.

Loneliness and repetitive negative thinking mediate the link between social health and cardiac distress in heart disease patients

Cardiovascular diseases are the leading cause of mortality worldwide, contributing to one-third of global deaths. Beyond physical health, heart disease is associated with cardiac distress, an emotional response that can negatively impact recovery and well-being. Understanding the psychological and social mechanisms underlying cardiac distress is crucial for improving patient outcomes. This study examines how social health (social support and social isolation) influences cardiac distress, with loneliness and repetitive negative thinking as mediators. To evaluate a theoretical model linking social health to cardiac distress, mediated by loneliness and repetitive negative thinking in patients with heart disease. A cross-sectional, correlational study was conducted in 2024 with 400 cardiac patients from two hospitals and one private clinic in Amol, Iran. Participants completed validated questionnaires assessing cardiac distress, social support, social isolation, loneliness, and repetitive negative thinking. Structural equation modeling was used for data analysis. Social isolation (r = 0.47, p < 0.001) and repetitive negative thinking (r = 0.50, p < 0.001) were significantly associated with greater cardiac distress. Social support negatively predicted both loneliness (β = - 0.32, p < 0.001) and cardiac distress (β = - 0.25, p < 0.01). Indirect effects showed that social support reduced cardiac distress by decreasing loneliness and repetitive negative thinking (β = - 0.23, p < 0.01), while social isolation increased cardiac distress through its influence on loneliness and repetitive negative thinking (β = 0.18, p = 0.05). The model explained 47.4% of the variance in cardiac distress. These findings highlight the importance of social health in managing cardiac distress among heart disease patients. Strengthening social support may alleviate loneliness and reduce repetitive negative thinking, ultimately improving emotional well-being and health outcomes. Future research should explore targeted interventions addressing these psychosocial factors to effectively reduce cardiac distress.

Associations of state and chronic loneliness with interpretation bias: The role of internalizing symptoms

Loneliness is common and, while generally transient, persists in up to 22% of the population. The rising prevalence and adverse impacts of chronic loneliness highlight the need to understand its underlying mechanisms. Evolutionary models of loneliness suggest that chronically lonely individuals demonstrate negative interpretation biases towards social information. It may also be that such biases are exacerbated by momentary increases in state loneliness, or elevated anxiety or depression. Yet, little research has tested these possibilities. The current study aimed to advance understandings of loneliness by examining associations of chronic loneliness with individual differences in negative interpretation bias for social (relative to non-social) stimuli, and testing whether these associations change in the context of increased state loneliness and current levels of anxiety and depressive symptoms. These aims were explored in 591 participants who completed an interpretation bias task before and after undergoing a state loneliness induction. Participants also self-reported chronic loneliness, anxiety, and depression. Linear mixed models indicated that only state (but not chronic) loneliness was associated with more positive interpretations of non-social stimuli, with greater anxiety and depressive symptoms predicting more negative interpretations. Implications of these findings for present theoretical models of loneliness are discussed.

A More Connected Future: How Social Connection, Interdisciplinary Approaches, and New Technology Will Shape the Affective Science of Loneliness, a Commentary on the Special Issue

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.

The use of multilevel emotion regulation strategies in the context of critical public events: the more the better?

Critical public events, like COVID-19, significantly impact individuals' emotional and mental health. People tend to use multi-level emotion regulation strategies (intrapersonal, interpersonal and hyper-personal) to cope with these events, resulting in various strategy profiles. However, few studies have examined ER strategies from a multilevel perspective. Therefore, this study examines the use of multi-level strategies during COVID-19, and evaluates the effectiveness of these strategies, with a particular interest in identifying strategy profiles promoting mental health. We conducted a two-wave study (an interval of 1 week) using online questionnaires during COVID-19, with an initial sample of 1,189 participants and 895 samples completing the surveys across the two waves. Cross-lagged analysis indicated that experiential avoidance was reciprocally positively related to negative emotions while perspective-taking and humorous-meme-saving were reciprocally positively related to life satisfaction or positive emotions over time. Cluster analysis suggested that there were 9 different profiles which scored differently on mental health indicators. Specifically, the use of multi-level strategies tended to be associated with greater positive emotions and life satisfaction while with lower negative emotions and loneliness. This study revealed that the use of multi-level strategies plays a protective role in mental health when facing critical public events. These findings expanded our understanding of how multilevel emotion regulation strategies impact mental health during critical public events and identify protective profiles for mental health.

The role of trait reappraisal in response to emotional ambiguity: A systematic review and meta-analysis

Individuals exhibit a systematic valence bias-a specific form of interpretation bias-in response to emotional ambiguity. Accumulating evidence suggests most people initially respond to emotional ambiguity negatively and differ only in subsequent responses. We hypothesized that trait-level cognitive reappraisal-an emotion regulation strategy involving the reinterpretation of affective meaning of stimuli-might explain individual differences in valence bias. To answer this question, we conducted a random-effects meta-analysis of 14 effect sizes from 13 prior studies (n = 2,086), identified via Google Scholar searches. We excluded studies (a) in languages other than English, (b) from non-peer-reviewed sources, or (c) nonempirical sources. We included studies with (a) the Emotion Regulation Questionnaire, (b) a putative measure of valence bias prior to any study-specific manipulations, and (c) adult human participants (i.e., 17+). Supporting our prediction, we found individuals with higher trait reappraisal exhibited a less negative bias (r = -.18, z = -4.04, p < .001), whereas there was a smaller, opposite effect for trait expressive suppression (r = .10, z = 2.14, p = .03). The effects did, however, vary across tasks with stronger effects observed among studies using the scrambled sentences task compared to the valence bias task. Although trait reappraisal accounted for only a small amount of variance, reappraisal may be one mechanism contributing to variability in response to ambiguity. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

In the face of ambiguity: intrinsic brain organization in development predicts one's bias toward positivity or negativity

Exacerbated negativity bias, including in responses to ambiguity, represents a common phenotype of internalizing disorders. Individuals differ in their propensity toward positive or negative appraisals of ambiguity. This variability constitutes one's valence bias, a stable construct linked to mental health. Evidence suggests an initial negativity in response to ambiguity that updates via regulatory processes to support a more positive bias. Previous work implicates the amygdala and prefrontal cortex, and regions of the cingulo-opercular system, in this regulatory process. Nonetheless, the neurodevelopmental origins of valence bias remain unclear. The current study tests whether intrinsic brain organization predicts valence bias among 119 children and adolescents (6 to 17 years). Using whole-brain resting-state functional connectivity, a machine-learning model predicted valence bias (r = 0.20, P = 0.03), as did a model restricted to amygdala and cingulo-opercular system features (r = 0.19, P = 0.04). Disrupting connectivity revealed additional intra-system (e.g. fronto-parietal) and inter-system (e.g. amygdala to cingulo-opercular) connectivity important for prediction. The results highlight top-down control systems and bottom-up perceptual processes that influence valence bias in development. Thus, intrinsic brain organization informs the neurodevelopmental origins of valence bias, and directs future work aimed at explicating related internalizing symptomology.