A year in the social life of a teenager: Within-person fluctuations in stress, phone communication, and anxiety and depression

Longitudinal relationships across emotional distress, perceived emotion regulation, and social connections during early adolescence: A developmental cascades investigation

Early adolescence is a vulnerable period for emotional distress. Both emotion regulation and social connection to peers and family adults are understood to be associated with distress. However, existing longitudinal work has not explored these constructs jointly in a way that estimates their reciprocal relationships over adolescence. We present a three-wave random-intercepts cross-lagged panel model of reciprocal relationships between emotional distress, perceived emotion regulation, and social connections during early adolescence, among 15,864 participants from education settings in disadvantaged areas of England, over three annual waves (at ages 11/12, 12/13, and 13/14 years). Findings showed that emotional distress and perceived emotion regulation share a negative relationship over time, and that higher perceived emotion regulation predicts greater family connection in the initial stages of early adolescence (from age 11-12 to 12-13 years). Findings also indicated that connection to peers is positively associated with family connection, but also positively predicts slightly greater distress in the later stages of early adolescence (from age 12-13 to 13-14 years). Findings indicate a risk of negative spiral between emotional distress and perceived emotion regulation in early adolescence, and that social connection may not necessarily play the role we might expect in reducing distress.

A collaborative realist review of remote measurement technologies for depression in young people

Digital mental health is becoming increasingly common. This includes use of smartphones and wearables to collect data in real time during day-to-day life (remote measurement technologies, RMT). Such data could capture changes relevant to depression for use in objective screening, symptom management and relapse prevention. This approach may be particularly accessible to young people of today as the smartphone generation. However, there is limited research on how such a complex intervention would work in the real world. We conducted a collaborative realist review of RMT for depression in young people. Here we describe how, why, for whom and in what contexts RMT appear to work or not work for depression in young people and make recommendations for future research and practice. Ethical, data protection and methodological issues need to be resolved and standardized; without this, RMT may be currently best used for self-monitoring and feedback to the healthcare professional where possible, to increase emotional self-awareness, enhance the therapeutic relationship and monitor the effectiveness of other interventions.

A precision neuroscience approach to estimating reliability of neural responses during emotion processing: Implications for task-fMRI

Recent work demonstrating low test-retest reliability of neural activation during fMRI tasks raises questions about the utility of task-based fMRI for the study of individual variation in brain function. Two possible sources of the instability in task-based BOLD signal over time are noise or measurement error in the instrument, and meaningful variation across time within-individuals in the construct itself-brain activation elicited during fMRI tasks. Examining the contribution of these two sources of test-retest unreliability in task-evoked brain activity has far-reaching implications for cognitive neuroscience. If test-retest reliability largely reflects measurement error, it suggests that task-based fMRI has little utility in the study of either inter- or intra-individual differences. On the other hand, if task-evoked BOLD signal varies meaningfully over time, it would suggest that this tool may yet be well suited to studying intraindividual variation. We parse these sources of variance in BOLD signal in response to emotional cues over time and within-individuals in a longitudinal sample with 10 monthly fMRI scans. Test-retest reliability was low, reflecting a lack of stability in between-person differences across scans. In contrast, within-person, within-session internal consistency of the BOLD signal was higher, and within-person fluctuations across sessions explained almost half the variance in voxel-level neural responses. Additionally, monthly fluctuations in neural response to emotional cues were associated with intraindividual variation in mood, sleep, and exposure to stressors. Rather than reflecting trait-like differences across people, neural responses to emotional cues may be more reflective of intraindividual variation over time. These patterns suggest that task-based fMRI may be able to contribute to the study of individual variation in brain function if more attention is given to within-individual variation approaches, psychometrics-beginning with improving reliability beyond the modest estimates observed here, and the validity of task fMRI beyond the suggestive associations reported here.

Linking video chatting, phone calling, text messaging, and social media with peers to adolescent connectedness

For 14 days three times per day (6072 observations), adolescents (N = 207, Mage  = 15.45 years) reported their digital (i.e., video chatting, texting, social media, and phone calling) communication with peers and their social connectedness. Controlling for in-person interactions, adolescents felt more connected in hours when they had communicated with peers by video chatting, texting, or social media, but not phone calling. Girls communicated with peers via text and social media more than boys, and boys talked on the phone more than girls. Boys who talked, texted, or video chatted more on average reported higher connectedness on average, whereas girls did not. As the links with connectedness were only found at the hourly- and not the daily level, results highlight that a sense of connectedness from digital media may be fleeting in nature.

Adolescent Social Communication Through Smartphones: Linguistic Features of Internalizing Symptoms and Daily Mood

The increasing use of smartphone technology by adolescents has led to unprecedented opportunities to identify early indicators of shifting mental health. This intensive longitudinal study examined the extent to which differences in mental health and daily mood are associated with digital social communication in adolescence. In a sample of 30 adolescents (ages 11-15 years), we analyzed 22,152 messages from social media, email, and texting across one month. Lower daily mood was associated with linguistic features reflecting self-focus and reduced temporal distance. Adolescents with lower daily mood tended to send fewer positive emotion words on a daily basis, and more total words on low mood days. Adolescents with lower daily mood and higher depression symptoms tended to use more future focus words. Dynamic linguistic features of digital social communication that relate to changes in mental states may represent a novel target for passive detection of risk and early intervention in adolescence.

Peer facilitation of emotion regulation in adolescence

Emotion regulation is particularly important for adolescents as they undergo normative developmental changes in affective systems and experience heightened risk for psychopathology. Despite a high need for emotion regulation during adolescence, commonly studied emotion regulation strategies like cognitive reappraisal are less beneficial for adolescents than adults because they rely on neural regions that are still developing during this period (i.e., lateral prefrontal cortex). However, adolescence is also marked by increased valuation of peer relationships and sensitivity to social information and cues. In the present review, we synthesize research examining emotion regulation and peer influence across development to suggest that sensitivity to peers during adolescence could be leveraged to improve emotion regulation for this population. We first discuss developmental trends related to emotion regulation at the level of behavior and brain in adolescents, using cognitive reappraisal as an exemplar emotion regulation strategy. Next, we discuss social influences on adolescent brain development, describing caregiver influence and increasing susceptibility to peer influence, to describe how adolescent sensitivity to social inputs represents both a window of vulnerability and opportunity. Finally, we conclude by describing the promise of social (i.e., peer-based) interventions for enhancing emotion regulation in adolescence.

Leveraging deep learning models to understand the daily experience of anxiety in teenagers over the course of a year

INTRODUCTION

Anxiety disorders are a prevalent and severe problem that are often developed early in life and can disrupt the daily lives of affected individuals for many years into adulthood. Given the persistent negative aspects of anxiety, accurate and early assessment is critical for long term outcomes. Currently, the most common method for anxiety assessment is through point-in-time measures like the GAD-7. Unfortunately, this survey and others like it can be subject to recall bias and do not fully capture the variability in an individual's day-to-day symptom experience. The current work aims to evaluate how point-in-time assessments like the GAD-7 relate to daily measurements of anxiety in a teenage population.

METHODS

To evaluate this relationship, we leveraged data collected at four separate three week intervals from 30 teenagers (age 15-17) over the course of a year. The specific items of interest were a single item anxiety severity measure collected three times per day and end-of-month GAD-7 assessments. Within this sample, 40 % of individuals reported clinical levels of generalized anxiety disorder symptoms at some point during the study. The first component of analysis was a visual inspection assessing how daily anxiety severity fluctuated around end-of-month reporting via the GAD-7. The second component was a between-subjects comparison assessing whether individuals with similar GAD-7 scores experienced similar symptom dynamics across the month as represented by latent features derived from a deep learning model. With this approach, similarity was operationalized by hierarchical clustering of the latent features.

RESULTS

The aim clearly indicated that an individual's daily experience of anxiety varied widely around what was captured by the GAD-7. Additionally, when hierarchical clustering was applied to the three latent features derived from the (LSTM) encoder (r = 0.624 for feature reconstruction), it was clear that individuals with similar GAD-7 outcomes were experiencing different symptom dynamics. Upon further inspection of the latent features, the LSTM model appeared to rely as much on anxiety variability over the course of the month as it did on anxiety severity (p < 0.05 for both mean and RMSSD) to represent an individual's experience.

DISCUSSION

This work serves as further evidence for the heterogeneity within the experience of anxiety and that more than just point-in-time assessments are necessary to fully capture an individual's experience.

Advances in stress and depression research

PURPOSE OF REVIEW

Stress plays a central role in the onset and course of depression. However, only a subset of people who encounter stressful life events go on to experience a depressive episode. The current review highlights recent advances in understanding when, why, and for whom the stress-depression link occurs, and we identify avenues for future research.

RECENT FINDINGS

In the last 18 months, researchers have taken a more nuanced perspective on the biopsychosocial mechanisms critical to the stress-depression link. For example, examination of specific facets of emotion regulation, including emotion regulation flexibility and interpersonal emotion regulation, has been critical to understanding its role in depression. Similarly, refined investigations of social support allowed researchers to identify distinct - and occasionally opposite - outcomes depending on the context or manner in which the support was provided. Researchers also documented that the stress-depression link was enhanced by dysregulation of several stress-sensitive biological systems, such as the immune system, microbiome, endocrine system, and neuroanatomical substrates.

SUMMARY

Recent studies highlight the importance of adopting a nuanced understanding of mechanisms and moderators that explain the stress-depression link. We also encourage continued engagement in collaborative, open science that uses multiple methods to study the full breadth of human diversity.

Linguistic measures of psychological distance track symptom levels and treatment outcomes in a large set of psychotherapy transcripts

Using language to “distance” ourselves from distressing situations (i.e., by talking less about ourselves and the present moment) can help us manage emotions. Here, we translate this basic research to discover that such “linguistic distancing” is a replicable measure of mental health in a large set of therapy transcripts (N = 6,229). Additionally, clustering techniques showed that language alone could identify participants who differed on both symptom severity and treatment outcomes. These findings lay the foundation for 1) tools that can rapidly identify people in need of psychological services based on language alone and 2) linguistic interventions that can improve mental health.

Using language to distance oneself from negative stimuli (e.g., by reducing use of the word “I” and present-tense verbs) is associated with effective emotion regulation. Given that internalizing disorders like anxiety and depression are characterized by maladaptive emotion regulation, stronger linguistic distance may be both a diagnostic marker of lower internalizing symptoms and a prognostic indicator of treatment progress. Here, we tested these hypotheses in a large corpus of naturalistic psychotherapeutic exchanges between clients and their therapists (>1.2 million messages from 6,229 clients). In both exploratory (n = 3,729) and validation (n = 2,500) datasets, we found that clients’ internalizing symptoms decreased over therapy, that client linguistic distance increased over therapy, and that internalizing symptoms tracked fluctuations in linguistic distance both within and between individuals. In other words, clients shifted from discussing themselves and the present moment to discussing other people and time points over treatment, and this psycholinguistic shift was related to symptom reductions. However, effect sizes for linguistic results were small, and we failed to find consistent evidence that linguistic distance statistically mediated changes in symptoms over time. Finally, clustering analyses revealed that data-driven groups of clients defined solely on the basis of their linguistic distance differed in both their symptom severity and treatment outcomes. Together, these findings provide replicable evidence that linguistic distance is a marker of internalizing symptom severity and treatment progress in real-world therapeutic interactions.