Major depressive disorder (MDD) among adolescents is recurrent and characterized by persistent emotion-processing biases. Adolescents (N=161; ages 13-18-years-old; remitted MDD=90, healthy controls=71) completed baseline and 6-month clinical assessments. Additionally, at baseline, participants completed the Facial Recognition Task while EEG data were recorded. The late positive potential (LPP) and effective connectivity during negative emotion processing were examined in relation to 6-month depressive symptoms and behavioral withdrawal (homestay from passive GPS). No group differences in LPP emerged. However, remitted MDD showed stronger right precuneus-superior frontal gyrus (theta-alpha) to sad faces and weaker left precuneus-SFG (alpha-beta) to angry faces relative to controls. Greater right precuneus-SFG connectivity during sad faces predicted depressive symptom severity (b=0.221, p=.025) and increased homestay (b=242.78, p=.048). Thus, altered precuneus-SFG connectivity during sad face processing may serve as a neural marker of depression risk, which could support early identification approaches and personalized interventions.

Major depressive disorder is a leading cause of disability among adolescents. Perseverative negative self-referential thoughts are a promising treatment target. Mindfulness-based real-time fMRI neurofeedback (mbNF), which guides mindfulness practice with feedback to train the downregulation of the default mode network (DMN), is an intervention targeting such negative self-referential thoughts. This study builds on a registered NIMH-supported trial testing the optimal dosing of mbNF on downregulating DMN activation among depressed adolescents. Adolescents (N=90), ages 13-18-years-old, with major depressive disorder will be randomized to receive either a 15- or 30-minute mbNF session. Before and after mbNF, participants will complete a self-referential encoding fMRI task, wherein they categorize whether trait adjectives describe themselves or a friend. It is hypothesized that a 30-minute versus 15-minute mbNF dose will relate to: (1) larger decreases in behavioral negative self-referential biases and (2) larger decreases in DMN activation during self-referential processing.

BACKGROUND: Robust correction for head motion during functional magnetic resonance imaging is critical to avoid across a range of diagnoses and covariates has not yet been evaluated. We tested 4 preregistered hypotheses: 1) externalizing disorder diagnoses will associate with more head motion during scanning; 2) internalizing disorder diagnoses will associate with less motion; 3) among children without attention-deficit/hyperactivity disorder, externalizing disorders will associate with more motion; and 4) among children with attention-deficit/hyperactivity disorder, comorbid internalizing disorders will associate with less motion. METHODS: Healthy Brain Network data releases 1.0-7.0 (n = 971) were analyzed in a discovery phase, and additional data released by February 29, 2024 (n = 437) were used in confirmatory analyses. Linear mixed-effects models were fitted with in-scanner head motion as the dependent variable. Binary independent variables of interest assessed for the presence or absence of externalizing or internalizing disorders. RESULTS: The confirmatory sample did not show significant associations between head motion and externalizing or internalizing disorders or support for the preregistered hypotheses. Across samples, there was a consistent interaction between age and neurodevelopmental diagnoses such that age-related decreases in head motion were attenuated in children with neurodevelopmental disorders. CONCLUSIONS: Head motion remains an important confound in pediatric neuroimaging that may be associated with many factors, including neuropsychiatric symptoms, age, cognitive and physical attributes, and interactions among these variables. This work takes a step toward parsing these complex associations, focusing on neuropsychiatric diagnoses, age, and their interaction.

ImportanceSuicide rates among adolescents continue to rise, but there are a lack of clinical tools to predict when youths may be at risk for suicidal behaviors.ObjectiveTo identify whether geolocation metrics, assessed through an app installed on adolescents’ personal smartphones, could detect the risk of next-week suicidal events and clinically meaningful suicidal ideation.Design, Setting, and ParticipantsThis case series study included high-risk adolescents aged 13 to 18 years reporting a current affective and/or substance use disorder, oversampled for suicidal thoughts and behaviors (STB). Participants were recruited from the greater New York City and Pittsburgh communities through psychiatric outpatient programs, emergency departments, medical center research registries, and social media. Participants installed the Effortless Assessment Research System (EARS) software application onto their personal smartphones, which obtained passive sensor data, including geolocation metrics (via the global positioning system [GPS]), as well as weekly experience sampling data probing STB for the duration of the 6-month study. Adolescents also completed clinical assessments at baseline as well as during the 1-, 3-, and 6-month follow-up assessments. Statistical analysis was performed from March 2023 to November 2024.Main Outcomes and MeasuresRepeated measures mixed-effects logistic models estimated whether weekly aggregates of geolocation features (ie, entropy, homestay, distance traveled) were associated with next-week suicidal events (ie, suicide attempts, psychiatric hospitalizations, emergency department visits for suicide concerns) and clinically meaningful ideation (via weekly experience sampling).ResultsOverall, 186 participants were included in this study (148 [79.6%] female; 19 [10.2%] Asian, 23 [12.4%] Black, and 106 [57.0%] White), with a mean (SD) age of 16.4 (1.7) years. Greater homestay (amount of time spent at home) on a given week, relative to one’s own mean, was associated with 2-fold greater odds of suicidal events during the subsequent week (odds ratio, 1.99 [95% CI, 1.15-3.45]). Results were not significant for entropy and distance traveled metrics. However, using leave-future-out validation, the accuracy of the homestay model was modest (area under the receiver operating characteristic curve, 0.64 [95% CI, 0.50-0.78]).Conclusions and RelevanceAdvancements in smartphone technology afford unique opportunities to capture affective and behavioral dynamics that presage suicide risk. This case series study found that greater homestay obtained through smartphone GPS data over the course of a week, relative to one’s own mean, was associated with greater odds of a suicidal event in the subsequent week. Although accuracy was modest, these findings offer a novel starting point for suicide prevention research, particularly as smartphone sensor data may have the capacity to identify who is at risk while also providing an opportunity to deliver clinical tools when that risk is greatest.

Adolescent suicide is a public health emergency with interpersonal factors playing a critical role in risk for suicidal thoughts and behaviors (STB). This study examined whether smartphone-based ecological momentary assessment (EMA) surveys capturing stress and social context could enhance the identification of youth at risk for STB. Adolescents ages 13-18-years-old (N = 207, 166 female sex) reporting depressive, anxiety, and/or substance use disorders were recruited from psychiatric outpatient programs, emergency departments, medical research registries, and social media. Participants with STB history were oversampled; 66 % reported current suicidal ideation and 27 % had a past-year attempt. Assessments of suicidal events (attempts, emergency department visits, hospitalizations for suicide concerns) were completed at baseline, 1-, 3-, and 6-month follow-up assessments. EMA probed momentary stress severity, affect, and recent social context (time spent with peers, family, or alone) 4-7×/day. Compared to psychiatric controls (N = 64), adolescents with STB history (N = 143) were more likely to report spending time alone (aOR = 1.75, 95 % CI = [1.15, 2.39]), less time with family (aOR = 0.59, 95 % CI = [0.31, 0.91]), and higher stress (d = 0.28). Further, EMA of stress (aOR = 1.86, 95 % CI = [1.11, 3.26]) and negative affect (aOR = 2.32, 95 % CI = [1.34, 4.36]) were prospectively associated with suicidal events above and beyond prior STB history. Broadly, results were similar between EMA measures of stress and negative affect, indicating such responses may reflect shared underlying processes. These findings underscore the importance of evaluating dynamic family and peer contact among adolescents at risk for STB and highlight EMA as a potential tool for assessing interpersonal exposures related to STB risk. Preprint link: doi:10.31234/osf.io/kepxw.

Intensive longitudinal research–including experience sampling and smartphone sensor monitoring–has potential for identifying proximal risk factors for psychopathology, including suicidal thoughts and behaviors (STB). Yet, missing data can complicate analysis and interpretation. This study aimed to address whether clinical and study design factors are associated with missing data, and whether missingness predicts changes in symptom severity or STB. Adolescents ages 13-18-years-old (N=179) reporting depressive, anxiety, and/or substance use disorders were enrolled; 65% reported current suicidal ideation and 29% indicated a past-year attempt. Passively acquired smartphone sensor data (e.g., GPS, accelerometer, keyboard inputs), daily mood surveys, and weekly suicidal ideation surveys were collected during the 6-month study period using the Effortless Assessment Research System (EARS) smartphone app. First, acquisition of passive smartphone sensor data (with data on ~80% of days across the whole sample) was strongly associated with survey data acquisition the same day (~44% of days). Second, STB and psychiatric symptoms were largely not associated with missing data. Rather, temporal features (e.g., length of time in study, weekends, summer) explained more missingness of survey and passive smartphone sensor data. Last, within-participant changes in missing data over time neither followed nor predicted subsequent change in suicidal ideation and psychiatric symptoms. Findings indicate that considering technical and study design factors impacting missingness is critical and highlight several factors that should be addressed to maximize the validity of clinical interpretations in intensive longitudinal research.

Suicide is the second leading cause of death among adolescents, and rates of suicidal thoughts and behaviors (STBs) are climbing.1 Promising interventions such as dialectical behavior therapy (DBT) are available to treat suicidal youth, and new approaches may facilitate greater intervention engagement, adherence, and effectiveness.2 Digital tools (eg, personal smartphones) are a particularly promising avenue and could enhance existing, evidence-based interventions by providing new opportunities for assessment and intervention between sessions.

Lower socioeconomic status (SES) is believed to be a risk factor for psychopathology in youth, however, the mechanisms linking SES and psychopathology are unknown. Directly addressing this gap, this study tests whether SES: (a) relates to brain activity following peer feedback (i.e., acceptance, rejection) and (b) moderates the association between brain activity following peer feedback and experience sampling assessed positive and negative affect.

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).

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 versus 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.

Background Given low base rates of suicidal thoughts and behaviors (STBs) in national samples of adolescents, clarifying the sociodemographic and clinical correlates among psychiatric inpatients may afford insights into potential risk factors that predict STBs onset. Method Adolescents (N = 970; ages 12-19 years) admitted for acute, psychiatric inpatient care completed baseline clinical interviews and self-report measures assessing demographics and early life adversity. Lifetime and 12-month STBs prevalence were obtained, allowing for the estimate of STBs persistence (i.e., rates of those with both current and past STBs) and transition rates (i.e., proportion of ideators that transition to plans or attempts). Univariate and multivariate logistic regression tested sociodemographic and clinical correlates of STBs. Results Age-of-onset for STBs occurred in early adolescence. Most patients reported suicide ideation with nearly half of patients making a plan and one-third a suicide attempt. Although relatively modest, the strongest correlates of lifetime attempts were depressive disorders, physical abuse, and non-suicidal self-injury. Knowing a peer that had attempted suicide also increased the likelihood of a suicide attempt, especially among attempters who transitioned from ideation to planned attempts. Conclusion STBs are highly prevalent among adolescents admitted for acute psychiatric inpatient treatment. The modest effects suggest that correlates, particularly those related to suicide attempts, are widely distributed. As a history of physical abuse and knowing a peer with a suicide attempt history are related to transitioning from ideation to action, these may be critical factors to target in the deployment of future suicide prevention and treatment programs.

Background Adolescence is characterized by a heightened vulnerability for Major Depressive Disorder (MDD) onset, and currently, treatments are only effective for roughly half of adolescents with MDD. Accordingly, novel interventions are urgently needed. This study aims to establish mindfulness-based real-time fMRI neurofeedback (mbNF) as a non-invasive approach to downregulate the default mode network (DMN) in order to decrease ruminatory processes and depressive symptoms. Methods Adolescents ( N = 90) with a current diagnosis of MDD ages 13–18-years-old will be randomized in a parallel group, two-arm, superiority trial to receive either 15 or 30 min of mbNF with a 1:1 allocation ratio. Real-time neurofeedback based on activation of the frontoparietal network (FPN) relative to the DMN will be displayed to participants via the movement of a ball on a computer screen while participants practice mindfulness in the scanner. We hypothesize that within-DMN (medial prefrontal cortex [mPFC] with posterior cingulate cortex [PCC]) functional connectivity will be reduced following mbNF (Aim 1: Target Engagement). Additionally, we hypothesize that participants in the 30-min mbNF condition will show greater reductions in within-DMN functional connectivity (Aim 2: Dosing Impact on Target Engagement). Aim 1 will analyze data from all participants as a single-group, and Aim 2 will leverage the randomized assignment to analyze data as a parallel-group trial. Secondary analyses will probe changes in depressive symptoms and rumination. Discussion Results of this study will determine whether mbNF reduces functional connectivity within the DMN among adolescents with MDD, and critically, will identify the optimal dosing with respect to DMN modulation as well as reduction in depressive symptoms and rumination. Trial Registration This study has been registered with clinicaltrials.gov, most recently updated on July 6, 2023 (trial identifier: NCT05617495).

Obsessive-compulsive disorder (OCD) is an impairing psychiatric condition, which often onsets in childhood. Growing research highlights dopaminergic alterations in adult OCD, yet pediatric studies are limited by methodological constraints. This is the first study to utilize neuromelanin-sensitive MRI as a proxy for dopaminergic function among children with OCD. N = 135 youth (6–14-year-olds) completed high-resolution neuromelanin-sensitive MRI across two sites; n = 64 had an OCD diagnosis. N = 47 children with OCD completed a second scan after cognitive-behavioral therapy. Voxel-wise analyses identified that neuromelanin-MRI signal was higher among children with OCD compared to those without (483 voxels, permutation-corrected p = 0.018). Effects were significant within both the substania nigra pars compacta ( p = 0.004, Cohen’s d = 0.51) and ventral tegmental area ( p = 0.006, d = 0.50). Follow-up analyses indicated that more severe lifetime symptoms ( t = −2.72, p = 0.009) and longer illness duration ( t = −2.22, p = 0.03) related to lower neuromelanin-MRI signal. Despite significant symptom reduction with therapy ( p < 0.001, d = 1.44), neither baseline nor change in neuromelanin-MRI signal associated with symptom improvement. Current results provide the first demonstration of the utility of neuromelanin-MRI in pediatric psychiatry, specifically highlighting in vivo evidence for midbrain dopamine alterations in treatment-seeking youth with OCD. Neuromelanin-MRI likely indexes accumulating alterations over time, herein, implicating dopamine hyperactivity in OCD. Given evidence of increased neuromelanin signal in pediatric OCD but negative association with symptom severity, additional work is needed to parse potential longitudinal or compensatory mechanisms. Future studies should explore the utility of neuromelanin-MRI biomarkers to identify early risk prior to onset, parse OCD subtypes or symptom heterogeneity, and explore prediction of pharmacotherapy response.

Background: Suicide is a major public health crisis among youth. Several prominent theories, including the Interpersonal Theory of Suicide (IPTS), aim to characterize the factors leading from suicide ideation to action. These theories are largely based on findings in adults and require testing and elaboration in adolescents. Methods: Data were examined from high-risk 13-18-year-old adolescents (N = 167) participating in a multi-wave, longitudinal study; 63% of the sample exhibited current suicidal thoughts or recent behaviors (n = 105). The study included a 6-month follow-up period with clinical interviews and self-report measures at each of the four assessments as well as weekly smartphone-based assessments of suicidal thoughts and behaviors. Regression and structural equation models were used to probe hypotheses related to the core tenets of the IPTS. Results; Feelings of perceived burdensomeness were associated with more severe self-reported suicidal ideation (b = 0.58, t(158) = 7.64, p < .001). Similarly, burdensomeness was associated with more frequent ideation based on weekly smartphone ratings (b = 0.11, t(1460) = 3.41, p < .001). Contrary to IPTS hypotheses, neither feelings of thwarted belongingness, nor interactions between burdensomeness and thwarted belongingness were significantly associated with ideation (ps > .05). Only elevated depression severity was associated with greater odds of suicide events (i.e., suicide attempts, psychiatric hospitalizations, and/or emergency department visits for suicide concerns) during the follow-up period (OR = 1.83, t(158) = 2.44, p = .01). No effect of acquired capability was found. Conclusions: Perceptions of burdensomeness to others reflect a critical risk factor for suicidal ideation among high-risk adolescents. Null findings with other IPTS constructs may suggest a need to adopt more developmentally sensitive models or measures of interpersonal and acquired capability risk factors for youth. Refining methods and theoretical models of suicide risk may help improve the identification of high-risk cases and inform clinical intervention.

OBJECTIVE:Suicide is a leading cause of death among adolescents. However, there are no clinical tools to detect proximal risk for suicide. METHOD:Participants included 13- to 18-year-old adolescents (N = 103) reporting a current depressive, anxiety, and/or substance use disorder who owned a smartphone; 62% reported current suicidal ideation, with 25% indicating a past-year attempt. At baseline, participants were administered clinical interviews to assess lifetime disorders and suicidal thoughts and behaviors (STBs). Self-reports assessing symptoms and suicide risk factors also were obtained. In addition, the Effortless Assessment of Risk States (EARS) app was installed on adolescent smartphones to acquire daily mood and weekly suicidal ideation severity during the 6-month follow-up period. Adolescents completed STB and psychiatric service use interviews at the 1-, 3-, and 6-month follow-up assessments. RESULTS:K-means clustering based on aggregates of weekly suicidal ideation scores resulted in a 3-group solution reflecting high-risk (n = 26), medium-risk (n = 47), and low-risk (n = 30) groups. Of the high-risk group, 58% reported suicidal events (ie, suicide attempts, psychiatric hospitalizations, emergency department visits, ideation severity requiring an intervention) during the 6-month follow-up period. For participants in the high-risk and medium-risk groups (n = 73), mood disturbances in the preceding 7 days predicted clinically significant ideation, with a 1-SD decrease in mood doubling participants' likelihood of reporting clinically significant ideation on a given week. CONCLUSION:Intensive longitudinal assessment through use of personal smartphones offers a feasible method to assess variability in adolescents' emotional experiences and suicide risk. Translating these tools into clinical practice may help to reduce the needless loss of life among adolescents.

Most adolescents with depression remain undiagnosed and untreated-missed opportunities that are costly from both personal and public health perspectives. A promising approach to detecting adolescent depression in real-time and at a large scale is through their social communication on the smartphone (e.g., text messages, social media posts). Past research has shown that language from online social communication reliably indicates interindividual differences in depression. To move toward detecting the emergence of depression symptoms intraindividually, the present study tested whether sentiment (i.e., words connoting positive and negative affect) from smartphone social communication prospectively predicted daily mood fluctuations in 83 adolescents (Mage = 16.49, 73.5% female) with a wide range of depression severity. Participants completed daily mood ratings across a 90-day period, during which 354,278 messages were passively collected from social communication apps. Greater positive sentiment (i.e., more positive weighted composite valence score and a greater proportion of words expressing positive sentiment) predicted more positive next-day mood, controlling for previous-day mood. Moreover, greater proportions of positive and negative sentiment were, respectively, associated with lower anhedonia and greater dysphoria symptoms measured at baseline. Exploratory analyses of nonaffective linguistic features showed that greater use of social engagement words (e.g., friends and affiliation) and emojis (primarily consisting of hearts) predicted more positive changes in mood. Collectively, findings suggest that language from smartphone social communication can detect mood fluctuations in adolescents, laying the foundation for language-based tools to identify periods of heightened depression risk. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

BACKGROUND: Childhood obsessive-compulsive symptoms (OCSs) are common and can be an early risk marker for obsessive-compulsive disorder. The Adolescent Brain and Cognitive Development (ABCD) Study provides a unique opportunity to characterize OCSs in a large normative sample of school-age children and to explore corticostriatal and task-control circuits implicated in pediatric obsessive-compulsive disorder. METHODS: The ABCD Study acquired data from 9- and 10-year-olds (N = 11,876). Linear mixed-effects models probed associations between OCSs (Child Behavior Checklist) and cognition (NIH Toolbox), brain structure (subcortical volume, cortical thickness), white matter (diffusion tensor imaging), and resting-state functional connectivity. RESULTS: OCS scores showed good psychometric properties and high prevalence, and they were related to familial/parental factors, including family conflict. Higher OCS scores related to better cognitive performance (beta = .06, t(9966.60) = 6.28, p < .001, eta(2)(p) = .01), particularly verbal, when controlling for attention-deficit/hyperactivity disorder, which related to worse performance. OCSs did not significantly relate to brain structure but did relate to lower superior corticostriatal tract fractional anisotropy (beta = -.03, t = -3.07, p = .002, eta(2)(p) = .02). Higher OCS scores were related to altered functional connectivity, including weaker connectivity within the dorsal attention network (beta = -.04, t(7262.87) = -3.71, p < .001, eta(2)(p) = .002) and weaker dorsal attention-default mode anticorrelation (beta = .04, t(7251.95) = 3.94, p < .001, eta(2)(p) = .002). Dorsal attention-default mode connectivity predicted OCS scores at 1 year (beta = -.04, t(2407.61 )= -2.23, p = .03, eta(2)(p) = .03). CONCLUSIONS: OCSs are common and may persist throughout childhood. Corticostriatal connectivity and attention network connectivity are likely mechanisms in the subclinical-to-clinical spectrum of OCSs. Understanding correlates and mechanisms of OCSs may elucidate their role in childhood psychiatric risk and suggest potential utility of neuroimaging, e.g., dorsal attention-default mode connectivity, for identifying children at increased risk for obsessive-compulsive disorder.