The effects of family support and smartphone-derived homestay on daily mood and depression among sexual and gender minority adolescents.

Sexual and gender minority (SGM) adolescents are at elevated risk for depression. This risk is especially pronounced among adolescents whose home environment is unsupportive or nonaffirming, as these adolescents may face familial rejection due to their identity. Therefore, it is critical to better understand the mechanisms underlying this risk by probing temporally sensitive associations between negative mood and time spent in potentially hostile home environments. The current study included adolescents (N = 141; 43% SGM; 13-18 years old), oversampled for depression history, who completed clinical interviews assessing lifetime psychiatric history and depression severity as well as self-report measures of social support. Participants also installed an app on their personal smartphones, which assessed their daily mood and geolocation-determined mobility patterns over a 6-month follow-up period. Over the 6-month follow-up period, SGM adolescents reported elevated depression severity and lower daily mood relative to non-SGM youth. Interestingly, SGM adolescents who reported low family support experienced lower daily mood than non-SGM adolescents, particularly on days when they spent more time at home. Current findings reinforce evidence for disparities in depression severity among SGM adolescents and highlight family support as a key factor. Specifically, more time spent in home environments with low family support was associated with worse mood among SGM adolescents. These results underscore the need for clinical interventions to support SGM youth, particularly interventions that focus on familial relationships and social support within the home environment. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Neurophysiological responses to emotional faces predict dynamic fluctuations in affect in adolescents.

The ability to accurately identify and interpret others' emotions is critical for social and emotional functioning during adolescence. Indeed, previous research has identified that laboratory-based indices of facial emotion recognition and engagement with emotional faces predict adolescent mood states. Whether socioemotional information processing relates to real-world affective dynamics using an ecologically sensitive approach, however, has rarely been assessed. In the present study, adolescents (N = 62; ages 13-18) completed a Facial Recognition Task, including happy, angry, and sad stimuli, while EEG data were acquired. Participants also provided ecological momentary assessment (EMA) data probing their current level of happiness, anger, and sadness for 1-week, resulting in indices of emotion (mean-level, inertia, instability). Analyses focused on relations between (1) accuracy for and (2) prolonged engagement with (LPP) emotional faces and EMA-reported emotions. Greater prolonged engagement with happy faces was related to less resistance to changes in happiness (i.e., less happiness inertia), whereas greater prolonged engagement with angry faces associated with more resistance to changes in anger (i.e., greater anger inertia). Results suggest that socioemotional processes captured by laboratory measures have real-world implications for adolescent affective states and highlight potentially actionable targets for novel treatment approaches (e.g., just-in-time interventions). Future studies should continue to assess relations among socioemotional informational processes and dynamic fluctuations in adolescent affective states.

Detecting adolescent depression through passive monitoring of linguistic markers in smartphone communication.

BACKGROUND: Cross sectional studies have identified linguistic correlates of major depressive disorder (MDD) in smartphone communication. However, it is unclear whether monitoring these linguistic characteristics can detect when an individual is experiencing MDD, which would facilitate timely intervention. METHODS: Approximately 1.2 million messages typed into smartphone social communication apps (e.g. texting, social media) were passively collected from 90 adolescents with a range of depression severity over a 12-month period. Sentiment (i.e. positive vs. negative valence of text), proportions of first-person singular pronouns (e.g. 'I'), and proportions of absolutist words (e.g. 'all') were computed for each message and converted to weekly aggregates temporally aligned with weekly MDD statuses obtained from retrospective interviews. Idiographic, multilevel logistic regression models tested whether within-person deviations in these linguistic features were associated with the probability of concurrently meeting threshold for MDD. RESULTS: Using more first-person singular pronouns in smartphone communication relative to one's own average was associated with higher odds of meeting threshold for MDD in the concurrent week (OR = 1.29; p = .007). Sentiment (OR = 1.07; p = .54) and use of absolutist words (OR = 0.99; p = .90) were not related to weekly MDD. CONCLUSIONS: Passively monitoring use of first-person singular pronouns in adolescents' smartphone communication may help detect MDD, providing novel opportunities for early intervention.