More than one way to say I love you: An Internet-based intervention for training flexible thinking in romantic relationships.

OBJECTIVES: This study developed and pilot-tested an adaptation of Cognitive Bias Modification (CBM) to target two aspects of relational flexibility in couples: the ability to generate alternative perspectives, and the ability to respond nondefensively when alternative partner perspectives are raised within challenging relationship situations (referred to as flexibility in partner perspectives). METHODS: CBM-FlexC training materials were developed in Phase 1, and expert users (N = 4) and end-point users (N = 7) provided qualitative feedback. Feasibility and preliminary efficacy of CBM-FlexC were evaluated in Phase 2, using an online sample of distressed couples (N = 18). Using a multiple baseline design, participants completed three baseline assessments, six CBM-FlexC sessions over 2 weeks, and a 1-month follow-up. RESULTS: CBM-FlexC training resulted in greater flexibility in partner perspectives, relationship satisfaction, and general psychological flexibility compared to baseline, and improvements were maintained 1-month after training when using mixed-effects models. However, analyses of reliable change (based on graphical inspection and the Reliable Change Index) indicated that most participants did not experience reliable improvement in flexibility in partner perspectives, or relationship satisfaction. CONCLUSION: This pilot study provides some positive signals regarding the potential efficacy of CBM-FlexC, while pointing to the need for further development to strengthen its effects.

Using Mobile Sensing to Test Clinical Models of Depression, Social Anxiety, State Affect, and Social Isolation Among College Students.

BACKGROUND: Research in psychology demonstrates a strong link between state affect (moment-to-moment experiences of positive or negative emotionality) and trait affect (eg, relatively enduring depression and social anxiety symptoms), and a tendency to withdraw (eg, spending time at home). However, existing work is based almost exclusively on static, self-reported descriptions of emotions and behavior that limit generalizability. Despite adoption of increasingly sophisticated research designs and technology (eg, mobile sensing using a global positioning system [GPS]), little research has integrated these seemingly disparate forms of data to improve understanding of how emotional experiences in everyday life are associated with time spent at home, and whether this is influenced by depression or social anxiety symptoms. OBJECTIVE: We hypothesized that more time spent at home would be associated with more negative and less positive affect. METHODS: We recruited 72 undergraduate participants from a southeast university in the United States. We assessed depression and social anxiety symptoms using self-report instruments at baseline. An app (Sensus) installed on participants' personal mobile phones repeatedly collected in situ self-reported state affect and GPS location data for up to 2 weeks. Time spent at home was a proxy for social isolation. RESULTS: We tested separate models examining the relations between state affect and time spent at home, with levels of depression and social anxiety as moderators. Models differed only in the temporal links examined. One model focused on associations between changes in affect and time spent at home within short, 4-hour time windows. The other 3 models focused on associations between mean-level affect within a day and time spent at home (1) the same day, (2) the following day, and (3) the previous day. Overall, we obtained many of the expected main effects (although there were some null effects), in which higher social anxiety was associated with more time or greater likelihood of spending time at home, and more negative or less positive affect was linked to longer homestay. Interactions indicated that, among individuals higher in social anxiety, higher negative affect and lower positive affect within a day was associated with greater likelihood of spending time at home the following day. CONCLUSIONS: Results demonstrate the feasibility and utility of modeling the relationship between affect and homestay using fine-grained GPS data. Although these findings must be replicated in a larger study and with clinical samples, they suggest that integrating repeated state affect assessments in situ with continuous GPS data can increase understanding of how actual homestay is related to affect in everyday life and to symptoms of anxiety and depression.

Remembering or knowing how we felt: Depression and anxiety symptoms predict retrieval processes during emotional self-report.

Researchers and clinicians routinely rely on patients' retrospective emotional self-reports to guide diagnosis and treatment, despite evidence of impaired autobiographical memory and retrieval of emotional information in depression and anxiety. To clarify the nature and specificity of these impairments, we conducted two large online data collections (Study 1, N = 1,983; Study 2, N = 900) examining whether depression and/or anxiety symptoms would uniquely predict the use of self-reported episodic (i.e., remembering) and/or semantic (i.e., knowing) retrieval when rating one's positive and negative emotional experiences over different time frames. Participants were randomly assigned to one of six time frames (ranging from at this moment to last few years) and were asked to rate how intensely they felt each of four emotions, anxious, sad, calm, and happy, over that period. Following each rating, they were asked several follow-up prompts assessing their perceived reliance on episodic and/or semantic information to rate how they felt, using procedures adapted from the traditional "remember/know" paradigm (Tulving, 1985). Across both studies, depression and anxiety symptoms each uniquely predicted increased likelihood of remembering across emotion types, and decreased likelihood of knowing how one felt when rating positive emotion types. Implications for the theory and treatment of emotion-related memory disturbances in depression and anxiety, and for dual-process theories of memory retrieval more generally, are discussed. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Predicting Social Anxiety From Global Positioning System Traces of College Students: Feasibility Study.

BACKGROUND: Social anxiety is highly prevalent among college students. Current methodologies for detecting symptoms are based on client self-report in traditional clinical settings. Self-report is subject to recall bias, while visiting a clinic requires a high level of motivation. Assessment methods that use passively collected data hold promise for detecting social anxiety symptoms and supplementing self-report measures. Continuously collected location data may provide a fine-grained and ecologically valid way to assess social anxiety in situ. OBJECTIVE: The objective of our study was to examine the feasibility of leveraging noninvasive mobile sensing technology to passively assess college students' social anxiety levels. Specifically, we explored the different relationships between mobility and social anxiety to build a predictive model that assessed social anxiety from passively generated Global Positioning System (GPS) data. METHODS: We recruited 228 undergraduate participants from a Southeast American university. Social anxiety symptoms were assessed using self-report instruments at a baseline laboratory session. An app installed on participants' personal mobile phones passively sensed data from the GPS sensor for 2 weeks. The proposed framework supports longitudinal, dynamic tracking of college students to evaluate the relationship between their social anxiety and movement patterns in the college campus environment. We first extracted the following mobility features: (1) cumulative staying time at each different location, (2) the distribution of visits over time, (3) the entropy of locations, and (4) the frequency of transitions between locations. Next, we studied the correlation between these features and participants' social anxiety scores to enhance the understanding of how students' social anxiety levels are associated with their mobility. Finally, we used a neural network-based prediction method to predict social anxiety symptoms from the extracted daily mobility features. RESULTS: Several mobility features correlated with social anxiety levels. Location entropy was negatively associated with social anxiety (during weekdays, r=-0.67; and during weekends, r=-0.51). More (vs less) socially anxious students were found to avoid public areas and engage in less leisure activities during evenings and weekends, choosing instead to spend more time at home after school (4 pm-12 am). Our prediction method based on extracted mobility features from GPS trajectories successfully classified participants as high or low socially anxious with an accuracy of 85% and predicted their social anxiety score (on a scale of 0-80) with a root-mean-square error of 7.06. CONCLUSIONS: Results indicate that extracting and analyzing mobility features may help to reveal how social anxiety symptoms manifest in the daily lives of college students. Given the ubiquity of mobile phones in our society, understanding how to leverage passively sensed data has strong potential to address the growing needs for mental health monitoring and treatment.

I Did OK, but Did I Like It? Using Ecological Momentary Assessment to Examine Perceptions of Social Interactions Associated With Severity of Social Anxiety and Depression.

Socially anxious and depressed individuals tend to evaluate their social interactions negatively, but little is known about the specific real-time contributors to these negative perceptions. The current study examined how affect ratings during social interactions predict later perceptions of those interactions, and whether this differs by social anxiety and depression severity. Undergraduate participants (N = 60) responded to a smartphone application that prompted participants to answer short questions about their current affect and social context up to 6 times a day for 2 weeks. At the end of each day, participants answered questions about their perceptions of their social interactions from that day. Results indicated that the link between negative affective experiences reported during social interactions and the end-of-day report of enjoyment (but not effectiveness) of those experiences was more negative when social anxiety was more severe. The link between negative affective experiences rated during social interactions and the end-of-day report of effectiveness (but not enjoyment) during those social encounters was more negative when depression was more severe. These findings demonstrate the importance of examining self-perceptions of social interactions based both on the extent to which individuals think that they met the objective demands of an interaction (i.e., effectiveness, mastery) and the extent to which they liked or disliked that interaction (i.e., enjoyment, pleasure). These findings also highlight how real-time assessments of daily social interactions may reveal the key experiences that contribute to negative self-evaluations across disorders, potentially identifying critical targets for therapy.

Dynamically tracking anxious individuals' affective response to valenced information.

Past research has shown that an individual's feelings at any given moment reflect currently experienced stimuli as well as internal representations of similar past experiences. However, anxious individuals' affective reactions to streams of interrelated valenced information (vs. reactions to static stimuli that are arguably less ecologically valid) are rarely tracked. The present study provided a first examination of the newly developed Tracking Affect Ratings Over Time (TAROT) task to continuously assess anxious individuals' affective reactions to streams of information that systematically change valence. Undergraduate participants (N = 141) completed the TAROT task in which they listened to narratives containing positive, negative, and neutral physically- or socially-relevant events, and indicated how positive or negative they felt about the information they heard as each narrative unfolded. The present study provided preliminary evidence for the validity and reliability of the task. Within scenarios, participants higher (vs. lower) in anxiety showed many expected negative biases, reporting more negative mean ratings and overall summary ratings, changing their pattern of responding more quickly to negative events, and responding more negatively to neutral events. Furthermore, individuals higher (vs. lower) in anxiety tended to report more negative minimums during and after positive events, and less positive maximums after negative events. Together, findings indicate that positive events were less impactful for anxious individuals, whereas negative experiences had a particularly lasting impact on future affective responses. The TAROT task is able to efficiently capture a number of different cognitive biases, and may help clarify the mechanisms that underlie anxious individuals' biased negative processing. (PsycINFO Database Record