Predicting states of elevated negative affect in adolescents from smartphone sensors: a novel personalized machine learning approach.

BACKGROUND: Adolescence is characterized by profound change, including increases in negative emotions. Approximately 84% of American adolescents own a smartphone, which can continuously and unobtrusively track variables potentially predictive of heightened negative emotions (e.g. activity levels, location, pattern of phone usage). The extent to which built-in smartphone sensors can reliably predict states of elevated negative affect in adolescents is an open question. METHODS: Adolescent participants (n = 22; ages 13-18) with low to high levels of depressive symptoms were followed for 15 weeks using a combination of ecological momentary assessments (EMAs) and continuously collected passive smartphone sensor data. EMAs probed negative emotional states (i.e. anger, sadness and anxiety) 2-3 times per day every other week throughout the study (total: 1145 EMA measurements). Smartphone accelerometer, location and device state data were collected to derive 14 discrete estimates of behavior, including activity level, percentage of time spent at home, sleep onset and duration, and phone usage. RESULTS: A personalized ensemble machine learning model derived from smartphone sensor data outperformed other statistical approaches (e.g. linear mixed model) and predicted states of elevated anger and anxiety with acceptable discrimination ability (area under the curve (AUC) = 74% and 71%, respectively), but demonstrated more modest discrimination ability for predicting states of high sadness (AUC = 66%). CONCLUSIONS: To the extent that smartphone data could provide reasonably accurate real-time predictions of states of high negative affect in teens, brief 'just-in-time' interventions could be immediately deployed via smartphone notifications or mental health apps to alleviate these states.

Multi-modal assessment of reward functioning in adolescent anhedonia.

BACKGROUND: Anhedonia is a core symptom of depression that predicts worse treatment outcomes. Dysfunction in neural reward circuits is thought to contribute to anhedonia. However, whether laboratory-based assessments of anhedonia and reward-related neural function translate to adolescents' subjective affective experiences in real-world contexts remains unclear. METHODS: We recruited a sample of adolescents (n = 82; ages 12-18; mean = 15.83) who varied in anhedonia and measured the relationships among clinician-rated and self-reported anhedonia, behaviorally assessed reward learning ability, neural response to monetary reward and loss (as assessed with functional magnetic resonance imaging), and repeated ecological momentary assessment (EMA) of positive affect (PA) and negative affect (NA) in daily life. RESULTS: Anhedonia was associated with lower mean PA and higher mean NA across the 5-day EMA period. Anhedonia was not related to impaired behavioral reward learning, but low PA was associated with reduced nucleus accumbens response during reward anticipation and reduced medial prefrontal cortex (mPFC) response during reward outcome. Greater mean NA was associated with increased mPFC response to loss outcome. CONCLUSIONS: Traditional laboratory-based measures of anhedonia were associated with lower subjective PA and higher subjective NA in youths' daily lives. Lower subjective PA and higher subjective NA were associated with decreased reward-related striatal functioning. Higher NA was also related to increased mPFC activity to loss. Collectively, these findings demonstrate that laboratory-based measures of anhedonia translate to real-world contexts and that subjective ratings of PA and NA may be associated with neural response to reward and loss.

COVID-19 Distress Impacts Adolescents' Depressive Symptoms, NSSI, and Suicide Risk in the Rural, Northeast US.

OBJECTIVE: Widespread concern exists about the impacts of COVID-19 and related public health safety measures (e.g., school closures) on adolescent mental health. Emerging research documents correlates and trajectories of adolescent distress, but further work is needed to identify additional vulnerability factors that explain increased psychopathology during the pandemic. The current study examined whether COVID-19-related loneliness and health anxiety (assessed in March 2020) predicted increased depressive symptoms, frequency of non-suicidal self-injury (NSSI), and suicide risk from pre-pandemic (late January/early February 2020) to June 2020. METHOD: Participants were 362 middle and high school adolescents in rural Maine (M age = 15.01 years; 63.4% female; 76.4% White). Data were collected during a time in which state-level COVID-19 restrictions were high and case counts were relatively low. Self-reports assessed psychopathology symptoms, and ecological momentary assessment (EMA) was used to capture COVID-19-related distress during the initial days of school closures. RESULTS: Loneliness predicted higher depressive symptoms for all adolescents, higher NSSI frequency for adolescents with low pre-pandemic frequency (but less frequent NSSI for adolescents with high pre-pandemic frequency), and higher suicide risk for adolescents with higher pre-pandemic risk. Health anxiety predicted higher NSSI frequency for adolescents with high pre-pandemic frequency, and secondary analyses suggested that this pattern may depend on adolescents' gender identity. CONCLUSIONS: Results underscore the impact of COVID-19 on adolescent mental health, with benefits for some but largely negative impacts for most. Implications for caretakers, educators, and clinicians invested in adolescent mental health are discussed.

Mental imagery of suicide and non-suicidal self-injury: A meta-analysis and systematic review.

BACKGROUND: The vast majority of research on, and clinical assessment of, cognitions related to suicide and non-suicidal self-injury (NSSI) has focused on verbal thoughts. And yet, mental imagery is more realistic and emotionally arousing than verbal thoughts. METHODS: We conducted a systematic review and meta-analysis documenting the prevalence of suicidal and NSSI mental imagery and describing the content and characteristics of suicidal and NSSI mental imagery, links between suicidal and NSSI mental imagery and suicidal and NSSI behavior, and how to intervene on suicidal and NSSI mental imagery. Studies published through December 17, 2022 were identified through a systematic search of MEDLINE and PsycINFO. RESULTS: Twenty-three articles were included. Prevalence rates of suicidal (73.56%) and NSSI (84.33%) mental imagery were high among clinical samples. Self-harm mental imagery commonly depicts engagement in self-harm behavior and is experienced as vivid, realistic, and preoccupying. When experimentally induced, self-harm mental imagery reduces physiological and affective arousal. Preliminary evidence suggests that suicidal mental imagery is associated with suicidal behavior. CONCLUSIONS: Suicidal and NSSI mental imagery are highly prevalent and may be associated with heightened risk for self-harm behavior. Assessments and interventions for self-harm should consider incorporating and addressing suicidal and NSSI mental imagery to mitigate risk.