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The primary objective is to understand how individuals may differentially use intra- and inter-personal regulation strategies to cope with isolation and sheltering in place during COVID-19. Because of the nature of self-quarantine, are there individual differences in the extent to which individuals seek others to help them regulate their emotions?

Social anhedonia refers to reduced self-reported feelings of pleasure or motivation to engage in social interactions (Kwapil, 1998). Individuals high in social anhedonia may have a greater disinterest in needing to belong (Silva & Kwapil, 2011). Social anhedonia may be prevalent in individuals without any current or previous clinical disorders (Brown et al., 2007). It is considered a negative symptom of schizophrenia and a potential predictor for the onset of schizophrenia spectrum disorders (Kwapil, 1998; Kwapil, Barrantes-Vidal, & Silvia, 2008) as well as other forms of psychopathology (Leentjens, et al., 2008; Blanchard, Horan, & Brown, 2001). Studies have shown that social anhedonia is associated with lower social functioning; individuals high in social anhedonia were rated as less socially skilled, less affiliative and report less willingness to engage in future interactions with their partner in a lab setting (Llerena, Park, Couture, & Blanchard, 2012; Blanchard, Park, Catalano, & Bennett, 2015). Because it is so prevalent in the spectrum of mental health, it is important to consider interventions that may help to reduce social anhedonia. One pilot study tested a positive emotion intervention and found that their intervention was both feasible and significantly reduced anhedonia (Favrod, et al., 2015). Another study found that a loving-kindness intervention was helpful in reducing negative symptoms of schizophrenia, including anhedonia (Johnson et al., 2011). Although these studies examine the effectiveness of positive emotion interventions in reducing negative symptoms, there are few studies that examine whether an intervention could influence specific aspects of social functioning or motivated engagement particularly in individuals with social anhedonia. This study aims to integrate previous findings and address gaps in the literature regarding social anhedonia and social interventions by experimentally manipulating a savoring intervention. Savoring is a construct defined primarily as attending, focusing, and extending the experience retrospectively, presently, or in anticipation of positive moments (Bryant, 2003; Bryant & Veroff, 2017). Through the process of savoring, individuals can amplify or increase positive thoughts and feelings. This exercise has been linked to a variety of outcomes including increased positive affect and happiness and lower neuroticism, depression, and anhedonia (Bryant, 2003). In particular, relational savoring refers to the savoring of positive interpersonal connections with others (Borelli, Rasmussen, Burkhart, & Sbarra, 2015); individuals recall both temporal, physical, and emotional details of a positive social interaction with another individual (Borelli, Rasmussen, Burkhart, & Sbarra, 2015). To our knowledge, there are no studies utilizing relational savoring as an intervention in individuals with social anhedonia. The current study will (1) evaluate the effectiveness of a relational savoring intervention in a sample of individuals with social anhedonia, (2) examine if this intervention will impact social motivation and willingness to engage in social interaction compared to a control condition, and (3) compare changes in emotion and social motivation of individuals with social anhedonia with healthy controls.

Engaging in adaptive emotion regulation (ER) strategies has been linked to beneficial outcomes, such as increased positive affect, greater well-being and interpersonal functioning (Gross & John, 2003). While there are numerous studies indicating the importance of engaging in emotion regulation (ER) strategies, few studies have explored factors related to regulation success - the amount of actual increase or decrease in emotion reactivity after regulation (McRae, 2013). A majority of the literature examining ER have assigned individuals to implement certain ER strategies and compare differences in reactivity within these strategies. However, there may be differences with engaging in ER strategies and the actual amount of emotion regulated. Individuals may use a strategy but not implement it successfully as intended. In particular, it is unclear what factors may allow individuals to be more successful at regulating their emotional reactivity than others (Giles et al., 2017). The purpose of this study is to examine whether emotional clarity is associated with ER success as indicated by a reduction in LPP amplitude. Emotional clarity (EC) is a key construct of emotional intelligence, and is important for successful ER. Broadly, greater knowledge of emotions and the contexts in which they are felt may allow individuals to engage more flexibly in a wider range of ER strategies (Gross & Jazieri, 2014). Low levels of EC have been associated with worse outcomes related to affect such as depression and anxiety (Thompson et al., 2017). Despite this, the literature regarding EC and ER has been limited, with mixed findings regarding their association. Studies examining EC and self-reported cognitive reappraisal use in undergraduates (Gross & John, 2003), individuals with PTSD (Boden et al., 2012), and cannabis-users found no correlation between the two constructs (Boden et al., 2013); alternatively, a study examining the association between EC and depression through an mTurk sample found positive associations between EC and reappraisal use (Boden & Thompson, 2015). Many of these studies have used the Emotion Regulation Questionnaire (ERQ; trait self-report measure) which assesses how frequently people use two ER strategies (reappraisal and suppression) but does not tap into ability or success. This may be problematic in our understanding of the relation between EC and ER because there may be a discrepancy between an individual’s self-perceived frequency of using ER strategies and their actual success in up-regulating or down-regulating emotion. Individuals with greater EC may use multiple ER strategies aside from reappraisal and suppression. Preliminary findings using a modified ERQ scale assessing an individual’s perception of regulation ability did find that people with greater EC showed greater ability to use reappraisal, but not suppression (Lai et al, 2019). Although preliminary, this is important to consider, as an individual’s ability to regulate may then be relevant in how successful they are, linking greater EC with greater ER success. Thus, further examination is necessary to examine the relation between EC and ER success using both objective and subjective measures. Many studies that have focused on distinct ER strategies often compare reappraisal and suppression, yet these two strategies differ with regard to when they are implemented during the emotion generation process (Gross, 1998). ER may be implemented prior to the emotional response (antecedent-focused) or after an emotional response has been generated (response-focused). Because reappraisal is an antecedent-focused strategy whereas suppression is a response- focused strategy, it may be important to compare two antecedent-focused strategies and assess differences in how these strategies are associated with reductions in emotional reactivity. Of the few studies that have examined antecedent-focused strategies, the two strategies that are examined are reappraisal and distraction (Sheppes et al., 2011; 2014; Thiruchselvam et al., 2011). Distraction is considered an attentional deployment strategy, in which individuals can shift their attention to up-regulate or down-regulate their emotions. Given the numerous findings indicating the benefits of engaging in ER earlier on in the emotion generation process, further examination of other antecedent-focused strategies such as distraction may help to investigate how EC and other factors relate to the successful engagement in ER prior to the full development of an emotional response. Self-reports of ER success may reflect an individual’s perceived ability to successfully engage in regulation strategies (e.g., trait-level) whereas lab-based paradigms may capture state-levels of physiological or self-reported changes in emotion as an indicator of successful regulation (e.g., state-level). Often self-report and objective measures do not always converge, with mixed findings in the literature regarding emotional coherence across self-report, behavioral, and physiological indices of emotional reactivity. Thus, it is important to assess whether subjective and objective measures of ER success converge, and whether lack of convergence is linked with EC. Of the many ways to assess ER objectively, electroencephalogram (EEG) methods can capture neural activity related to emotion and engagement of regulation strategies (Hajcak et al., 2006; Hajcak et al., 2010). EEG can also be used in lab-paradigms to capture neural activity tied to event-specific triggers, known as event-related potentials (ERPs). One ERP used in understanding emotion processing is the late positive potential (LPP), which is related to attention of arousing stimuli. A unique feature of the LPP is that the magnitude does not habituate after repeated exposure to the same emotional stimuli (Codispoti et al., 2006). Studies that have examined reappraisal have found that when reappraising positive and negative emotional stimuli, the LPP amplitude is reduced compared to the passive viewing of these emotional stimuli (Hajcak & Nieuwenhuis, 2006). Thus, comparing passive viewing with regulation trials to examine changes in LPP topography and activity over time (e.g., at on-set and off-set of stimuli) may be an indication of ER success.

Monitoring and understanding affective states are important aspects of healthy functioning and treatment of mood-based disorders. Recent advancements of ubiquitous wearable technologies have increased the reliability of such tools in detecting and accurately estimating mental states (e.g., mood, stress, etc.), offering comprehensive and continuous monitoring of individuals over time. Previous attempts to model an individual's mental state were limited to subjective approaches or the inclusion of only a few modalities (i.e., phone, watch). Thus, the goal of our study was to investigate the capacity to more accurately predict affect through a fully automatic and objective approach using multiple commercial devices. Longitudinal physiological data and daily assessments of emotions were collected from a sample of college students using smart wearables and phones for over a year. Results showed that our model was able to predict next-day affect with accuracy comparable to state of the art methods.

BackgroundSupporting mental health and wellness is of increasing interest due to a growing recognition of the prevalence and burden of mental health issues. Mood is a central aspect of mental health, and several technologies, especially mobile apps, have helped people track and understand it. However, despite formative work on and dissemination of mood-tracking apps, it is not well understood how mood-tracking apps used in real-world contexts might benefit people and what people hope to gain from them.ObjectiveTo address this gap, the purpose of this study was to understand motivations for and experiences in using mood-tracking apps from people who used them in real-world contexts.MethodsWe interviewed 22 participants who had used mood-tracking apps using a semistructured interview and card sorting task. The interview focused on their experiences using a mood-tracking app. We then conducted a card sorting task using screenshots of various data entry and data review features from mood-tracking apps. We used thematic analysis to identify themes around why people use mood-tracking apps, what they found useful about them, and where people felt these apps fell short.ResultsUsers of mood-tracking apps were primarily motivated by negative life events or shifts in their own mental health that prompted them to engage in tracking and improve their situation. In general, participants felt that using a mood-tracking app facilitated self-awareness and helped them to look back on a previous emotion or mood experience to understand what was happening. Interestingly, some users reported less inclination to document their negative mood states and preferred to document their positive moods. There was a range of preferences for personalization and simplicity of tracking. Overall, users also liked features in which their previous tracked emotions and moods were visualized in figures or calendar form to understand trends. One gap in available mood-tracking apps was the lack of app-facilitated recommendations or suggestions for how to interpret their own data or improve their mood.ConclusionsAlthough people find various features of mood-tracking apps helpful, the way people use mood-tracking apps, such as avoiding entering negative moods, tracking infrequently, or wanting support to understand or change their moods, demonstrate opportunities for improvement. Understanding why and how people are using current technologies can provide insights to guide future designs and implementations.

BackgroundThe year 2020 has been challenging for many, particularly for young adults who have been adversely affected by the COVID-19 pandemic. Emerging adulthood is a developmental phase with significant changes in the patterns of daily living; it is a risky phase for the onset of major mental illness. College students during the pandemic face significant risk, potentially losing several protective factors (eg, housing, routine, social support, job, and financial security) that are stabilizing for mental health and physical well-being. Individualized multiple assessments of mental health, referred to as multimodal personal chronicles, present an opportunity to examine indicators of health in an ongoing and personalized way using mobile sensing devices and wearable internet of things.ObjectiveTo assess the feasibility and provide an in-depth examination of the impact of the COVID-19 pandemic on college students through multimodal personal chronicles, we present a case study of an individual monitored using a longitudinal subjective and objective assessment approach over a 9-month period throughout 2020, spanning the prepandemic period of January through September.MethodsThe individual, referred to as Lee, completed psychological assessments measuring depression, anxiety, and loneliness across 4 time points in January, April, June, and September. We used the data emerging from the multimodal personal chronicles (ie, heart rate, sleep, physical activity, affect, behaviors) in relation to psychological assessments to understand patterns that help to explicate changes in the individual's psychological well-being across the pandemic.ResultsOver the course of the pandemic, Lee's depression severity was highest in April, shortly after shelter-in-place orders were mandated. His depression severity remained mildly severe throughout the rest of the months. Associations in positive and negative affect, physiology, sleep, and physical activity patterns varied across time periods. Lee's positive affect and negative affect were positively correlated in April (r=0.53, P=.04) whereas they were negatively correlated in September (r=-0.57, P=.03). Only in the month of January was sleep negatively associated with negative affect (r=-0.58, P=.03) and diurnal beats per minute (r=-0.54, P=.04), and then positively associated with heart rate variability (resting root mean square of successive differences between normal heartbeats) (r=0.54, P=.04). When looking at his available contextual data, Lee noted certain situations as supportive coping factors and other situations as potential stressors.ConclusionsWe observed more pandemic concerns in April and noticed other contextual events relating to this individual's well-being, reflecting how college students continue to experience life events during the pandemic. The rich monitoring data alongside contextual data may be beneficial for clinicians to understand client experiences and offer personalized treatment plans. We discuss benefits as well as future directions of this system, and the conclusions we can draw regarding the links between the COVID-19 pandemic and college student mental health.