Greater social network complexity mitigates pandemic-related negativity

Having strong, diverse social relationships is tightly linked to myriad physical and mental health benefits by mitigating the negative impacts of adverse events. The COVID-19 pandemic brought increased uncertainty and changes to our social lives that reduced the spread of COVID-19 (e.g., social distancing), but also likely impacted emotional well-being. We investigated how one of these changes – changing social networks – relates to emotional bias (a proxy for well-being), specifically one’s tendency to interpret ambiguous stimuli as positive or negative (i.e., valence bias). Participants ( N = 614) categorized the valence of clearly (e.g., angry and happy expressions) and ambiguously valenced stimuli (e.g., surprised expressions), and were asked about their social network before and during the pandemic. Compared to before the pandemic, participants reported a decrease in overall network size ( p < .001) and number of embedded networks (i.e., a measure of network complexity represented by number of areas of social activity; p < .001). In a model with all three social network dimensions (size, complexity, diversity), network complexity uniquely predicted valence bias ( p = .02). Specifically, participants with greater social network complexity during the pandemic showed a more positive bias. Further, participants that did not experience a pandemic-related reduction in network complexity were protected from pandemic-related increases in negativity ( p < .001). In other words, having a more complex social network could act as a protective factor against adverse outcomes in times of uncertainty

Spring Break or Heart Break? Extending Valence Bias to Emotional Words

Ambiguous stimuli are useful for assessing emotional bias. For example, surprised faces could convey a positive or negative meaning, and the degree to which an individual interprets these expressions as positive or negative represents their “valence bias.” Currently, the most well- wellvalidated ambiguous stimuli for assessing valence bias include nonverbal signals (faces and scenes), overlooking an inherent ambiguity in verbal signals. This study identified 32 words with dual-valence ambiguity (i.e., relatively high intersubject variability in valence ratings and relatively slow response times) and length-matched clearly valenced words (16 positive, 16 negative). Preregistered analyses demonstrated that the words-based valence bias correlated with the bias for faces, rs(213) = .27, p \u3c .001, and scenes, rs(204) = .46, p \u3c .001. That is, the same people who interpret ambiguous faces/scenes as positive also interpret ambiguous words as positive. These findings provide a novel tool for measuring valence bias and greater generalizability, resulting in a more robust measure of this bias

Spring Break or Heart Break? Extending Valence Bias to Emotional Words

Ambiguous stimuli are useful for assessing emotional bias. For example, surprised faces could convey a positive or negative meaning, and the degree to which an individual interprets these expressions as positive or negative represents their “valence bias.” Currently, the most well- wellvalidated ambiguous stimuli for assessing valence bias include nonverbal signals (faces and scenes), overlooking an inherent ambiguity in verbal signals. This study identified 32 words with dual-valence ambiguity (i.e., relatively high intersubject variability in valence ratings and relatively slow response times) and length-matched clearly valenced words (16 positive, 16 negative). Preregistered analyses demonstrated that the words-based valence bias correlated with the bias for faces, rs(213) = .27, p \u3c .001, and scenes, rs(204) = .46, p \u3c .001. That is, the same people who interpret ambiguous faces/scenes as positive also interpret ambiguous words as positive. These findings provide a novel tool for measuring valence bias and greater generalizability, resulting in a more robust measure of this bias

Political Identity Biases Americans’ Judgments of Outgroup Emotion

Social group identity plays a central role in political polarization and inter-party conflict. Here, we use ambiguously valenced faces to measure bias in the processing of political ingroup and outgroup faces, while also accounting for interparty differences in judgments of emotion at baseline. Participants identifying as Democrats and Republicans judged happy, angry, and surprised faces as positive or negative. Whereas happy and angry faces convey positive and negative valence respectively, surprised faces are ambiguous in that they readily convey positive and negative valence. Thus, surprise is a useful tool for characterizing valence bias (i.e., the tendency to judge ambiguous stimuli as negative). Face stimuli were assigned to the participants’ political ingroup or outgroup, or a third group with an unspecified affiliation (baseline). We found a significant interaction of facial expression and group membership, such that outgroup faces were judged more negatively than ingroup and baseline, but only for surprise. There was also an interaction of facial expression and political affiliation, with Republicans judging surprise more negatively than Democrats across all group conditions. However, we did not find evidence for party differences in outgroup negativity. Our findings demonstrate the utility of judgments of surprised faces as a measure of intergroup bias, and reinforce the importance of outgroup negativity (relative to ingroup positivity) for explaining inter-party biases

Reappraisal—but not Suppression—Tendencies Determine Negativity Bias After Laboratory and Real‑World Stress Exposure

Higher reactivity to stress exposure is associated with an increased tendency to appraise ambiguous stimuli as negative. However, it remains unknown whether tendencies to use emotion regulation strategies—such as cognitive reappraisal, which involves altering the meaning or relevance of affective stimuli—can shape individual differences regarding how stress affects perceptions of ambiguity. Here, we examined whether increased reappraisal use is one factor that can determine whether stress exposure induces increased negativity bias. In Study 1, healthy participants (n = 43) rated the valence of emotionally ambiguous (surprised) faces before and after an acute stress or control manipulation and reported reappraisal habits. Increased negativity ratings were milder for stressed individuals that reported more habitual reappraisal use. In Study 2 (n = 97), we extended this investigation to real-world perceived stress before and during the COVID-19 pandemic. We found that reappraisal tendency moderates the relationship between perceived stress and increased negativity bias. Collectively, these findings suggest that the propensity to reappraise determines negativity bias when evaluating ambiguity under stress

Face Coverings Differentially Alter Valence Judgments of Emotional Expressions

Face masks that prevent disease transmission obscure facial expressions, impairing nonverbal communication. We assessed the impact of lower (masks) and upper (sunglasses) face coverings on emotional valence judgments of clearly valenced (fearful, happy) and ambiguously valenced (surprised) expressions, the latter of which have both positive and negative meanings. Masks, but not sunglasses, impaired judgments of clearly valenced expressions compared to faces without coverings. Drift diffusion models revealed that lower, but not upper, face coverings slowed evidence accumulation and affected differences in non-judgment processes (i.e., stimulus encoding, response execution time) for all expressions. Our results confirm mask-interference effects in nonverbal communication. The findings have implications for nonverbal and intergroup communication, and we propose guidance for implementing strategies to overcome mask-related interference

Individual Differences in Appraisals of Emotional Ambiguity: Biological, Psychological, and Social Predictors

Uncertainty is ubiquitous in life, and its impacts are seen in decision-making across diverse contexts (e.g., financial, health, and interpersonal/social). As a result, individual differences in response to emotional ambiguity, a special type of uncertainty, can have far-reaching impacts. A growing literature has explored these individual differences in valence bias, or the tendency to appraise ambiguous social signals as more positive or negative. Although these appraisals are generally characterized by an initial negativity, many individuals arrive at positive appraisals through regulatory processes. Chronic negativity appears to be linked to an increased risk of mood and anxiety symptoms and has spurred research assessing predictors of valence bias at the biological, psychological, and social levels, that support the overriding of initial negativity. Here, biological predictors are probed via resting-state functional connectivity, in particular among emotion regulation (i.e., amygdala and PFC) and task performance (i.e., cingulo-opercular) brain networks, which are leveraged to predict individual differences in valence bias with machine learning algorithms. Next, psychological predictors are explored in the context of a Mindfulness-Based Stress Reduction intervention – showing a malleability of the trait-like valence bias. Then, the broad-scale uncertainty stemming from the COVID-19 pandemic and its impacts on valence bias over the period of approximately 15 months is characterized, showing a generalized increase in negativity at the start of the pandemic but individual differences in this change after the pandemic’s onset. Findings from each of these three levels of analysis are then discussed in the context of understanding sources of variability in individual differences in valence bias and improving physical and mental well-being

Spring Break or Heart Break? Extending Valence Bias to Emotional Words

Ambiguous stimuli are useful for assessing emotional bias. For example, surprised faces could convey a positive or negative meaning, and the degree to which an individual interprets these expressions as positive or negative represents their “valence bias.” Currently, the most well-validated ambiguous stimuli for assessing valence bias include nonverbal signals (faces and scenes), overlooking an inherent ambiguity in verbal signals. This study identified 32 words with dual-valence ambiguity (i.e., relatively high intersubject variability in valence ratings and relatively slow response times) and length-matched clearly valenced words (16 positive, 16 negative). Preregistered analyses demonstrated that the words-based valence bias correlated with the bias for faces, rs(213) = .27, p &lt; .001, and scenes, rs(204) = .46, p &lt; .001. That is, the same people who interpret ambiguous faces/scenes as positive also interpret ambiguous words as positive. These findings provide a novel tool for measuring valence bias and greater generalizability, resulting in a more robust measure of this bias. </jats:p