Can Psychedelic Use Benefit Meditation Practice? Examining Individual, Psychedelic, and Meditation-Related Factors.

Introduction: Meditation practice and psychedelic use have attracted increasing attention in the public sphere and scientific research. Both methods induce non-ordinary states of consciousness that may have significant therapeutic benefits. Thus, there is growing scientific interest in potential synergies between psychedelic use and meditation practice with some research suggesting that psychedelics may benefit meditation practice. The present study examined individual, psychedelic-related, and meditation-related factors to determine under what conditions meditators perceive psychedelic use as beneficial for their meditation practice. Method: Participants (N = 863) who had reported psychedelic use and a regular meditation practice (at least 3 times per week during the last 12 months) were included in the study. To accommodate a large number of variables, machine learning (i.e., elastic net, random forest) was used to analyze the data. Results: Most participants (n = 634, 73.5%) found psychedelic use to have a positive influence on their quality of meditation. Twenty-eight variables showed significant zero-order associations with perceived benefits even following a correction. Elastic net had the best performance (R2 = .266) and was used to identify the most important features. Across 53 variables, the model found that greater use of psychedelics, intention setting during psychedelic use, agreeableness, and exposure to N,N-Dimethyltryptamine (N,N-DMT) were most likely to be associated with the perception that psychedelics benefit meditation practice. The results were consistent across several different approaches used to identify the most important variables (i.e., Shapley values, feature ablation). Discussion: Results suggest that most meditators found psychedelic use to have a positive influence on their meditation practice, with: 1) regularity of psychedelic use, 2) the setting of intentions for psychedelic use, 3) having an agreeable personality, and 4) reported use of N,N-DMT being the most likely predictors of perceiving psychedelic use as beneficial. Longitudinal designs and randomized trials manipulating psychedelic use are needed to establish causality.

Brain mechanisms of rumination and negative self-referential processing in adolescent depression.

BACKGROUND: Depression is linked to cognitive biases towards more negative and less positive self-relevant information. Rumination, perseverative negative thinking about the past and the self, may contribute to these biases. METHODS: 159 adolescents (12-18 years), with a range of depression symptoms, completed the SRET during fMRI. Multiple regressions tested associations between conventional self-report and ecological momentary assessment (EMA) measured rumination, and neural and behavioral responses during a self-referent encoding task (SRET). RESULTS: Higher rumination (conventional self-report and EMA) was associated with more negative and fewer positive words endorsed and recalled. Higher self-reported (but not EMA) rumination was associated with higher accuracy in recognizing negative words and greater insula and dorsal anterior cingulate activity to negative versus positive words. LIMITATIONS: The sample included mostly non-Hispanic White participants with household incomes above the national average, highlighting the need for replication in more diverse samples. Word endorsement discrepancies required fMRI analyses to model neural response to viewing negative versus positive words. CONCLUSIONS: Adolescents with higher rumination endorsed and recalled more negative and fewer positive words and recognized more negative words during the SRET. Higher insula reactivity, a key region for modulating externally-oriented attention and internally-oriented self-referential processes, may contribute to links between rumination and negative memory biases. These findings provide insight into neurocognitive mechanisms underlying depression.

Neural and behavioral markers of inhibitory control predict symptom improvement during internet-delivered cognitive behavioral therapy for depression.

Poor inhibitory control contributes to deficits in emotion regulation, which are often targeted by treatments for major depressive disorder (MDD), including cognitive behavioral therapy (CBT). Brain regions that contribute to inhibitory control and emotion regulation overlap; thus, inhibitory control might relate to response to CBT. In this study, we examined whether baseline inhibitory control and resting state functional connectivity (rsFC) within overlapping emotion regulation-inhibitory control regions predicted treatment response to internet-based CBT (iCBT). Participants with MDD were randomly assigned to iCBT (N = 30) or a monitored attention control (MAC) condition (N = 30). Elastic net regression was used to predict post-treatment Patient Health Questionnaire-9 (PHQ-9) scores from baseline variables, including demographic variables, PHQ-9 scores, Flanker effects (interference, sequential dependency, post-error slowing), and rsFC between the dorsal anterior cingulate cortex, bilateral anterior insula (AI), and right temporoparietal junction (TPJ). Essential prognostic predictor variables retained in the elastic net regression included treatment group, gender, Flanker interference response time (RT), right AI-TPJ rsFC, and left AI-right AI rsFC. Prescriptive predictor variables retained included interactions between treatment group and baseline PHQ-9 scores, age, gender, Flanker RT, sequential dependency effects on accuracy, post-error accuracy, right AI-TPJ rsFC, and left AI-right AI rsFC. Inhibitory control and rsFC within inhibitory control-emotion regulation regions predicted reduced symptom severity following iCBT, and these effects were stronger in the iCBT group than in the MAC group. These findings contribute to a growing literature indicating that stronger inhibitory control at baseline predicts better outcomes to psychotherapy, including iCBT.

Multi-method assessment of suicidal thoughts and behaviors among patients in treatment for OCD and related disorders.

Obsessive-compulsive and related disorders (OCRDs) are associated with increased risk of suicidal thoughts and behaviors (STBs), yet research characterizing suicidality in OCRDs remains limited. A major challenge in assessing STBs is the reliance on explicit self-report. This study utilized multi-method assessment to examine changes in both implicit and explicit STBs in 31 adults receiving partial/residential treatment for OCRDs. Assessments were administered at admission and weekly during treatment. Approximately three-quarters of participants reported lifetime suicidal thoughts, with 16 % reporting a prior suicide attempt. OCD severity was significantly correlated with lifetime suicidal thoughts, and was significantly higher for those with lifetime suicidal thoughts and prior attempts compared to those without. Implicit biases towards death were not associated with OCD severity, and did not predict explicitly endorsed STBs. This is the first study to measure both explicit and implicit STBs in adults with OCRDs. Limitations included small sample size and lack of racial/ethnic diversity. Given the majority had recent suicidal thoughts and one in six had a prior attempt, we emphasize the importance of STB assessment in OCD treatment settings.

Revealing subgroup-specific mechanisms of change via moderated mediation: A meditation intervention example.

OBJECTIVE: Effective psychosocial interventions exist for numerous mental health conditions. However, despite decades of research, limited progress has been made in clarifying the mechanisms that account for their beneficial effects. We know that many treatments work, but we know relatively little about why they work. Mechanisms of change may be obscured due to prior research collapsing across heterogeneous subgroups of patients with differing underlying mechanisms of response. Studies identifying baseline individual characteristics that predict differential response (i.e., moderation) may inform research on why (i.e., mediation) a particular subgroup has better outcomes to an intervention via tests of moderated mediation. METHOD: In a recent randomized controlled trial comparing a 4-week meditation app with a control condition in school system employees (N = 662), we previously developed a "Personalized Advantage Index" (PAI) using baseline characteristics, which identified a subgroup of individuals who derived relatively greater benefit from meditation training. Here, we tested whether the effect of mindfulness acquisition in mediating group differences in outcome was moderated by PAI scores. RESULTS: A significant index of moderated mediation (IMM = 1.22, 95% CI [0.30, 2.33]) revealed that the effect of mindfulness acquisition in mediating group differences in outcome was only significant among those individuals with PAI scores predicting relatively greater benefit from the meditation app. CONCLUSIONS: Subgroups of individuals may differ meaningfully in the mechanisms that mediate their response to an intervention. Considering subgroup-specific mediators may accelerate progress on clarifying mechanisms of change underlying psychosocial interventions and may help inform which specific interventions are most beneficial for whom. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Identifying who benefits most from supportive versus expressive techniques in psychotherapy for depression: Moderators of within- versus between-individual effects.

OBJECTIVE: A recent randomized controlled trial (RCT) indicated that individuals with higher levels of attachment anxiety exhibited better treatment outcomes in supportive-expressive therapy (SET) relative to supportive therapy (ST). But to gain insight into within-patient therapeutic changes, a within-individual design is required. The present study contrasts previous findings based on theory-driven between-patient moderators with data-driven moderators of within-patient processes to investigate whether findings converge or diverge across these two approaches. METHOD: We used data of 118 patients from the pilot and active phases of a recent RCT for patients with major depressive disorder, comparing ST with SET, a time-limited psychodynamic therapy. The predefined primary outcome measure was the Hamilton Rating Scale for Depression. Supportive versus expressive techniques were rated based on patients' end-of-session perspective. We compared previous findings based on moderators of between-patient effects with a data-driven approach for identifying moderators of within-patient effects of techniques on subsequent outcome. RESULTS: After false discovery rate corrections, of 10 preselected moderators, patients' attachment anxiety and domineering style remained significant. Of these, bootstrap resampling revealed significant differences between ST and SET techniques for the attachment anxiety moderator: Those with higher attachment anxiety benefited more from greater use of ST than SET techniques in a particular session, as evidenced by lower levels of symptoms at the subsequent session. CONCLUSIONS: Our within-individual findings diverge from previously published between-individual analyses. This proof-of-concept study demonstrates the importance of complementing between-individuals with within-individual analyses to achieve better understanding of who benefits most from specific treatment techniques. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Reward Behavior Disengagement, a Neuroeconomic Model-Based Objective Measure of Reward Pathology in Depression: Findings from the EMBARC Trial.

The probabilistic reward task (PRT) has identified reward learning impairments in those with major depressive disorder (MDD), as well as anhedonia-specific reward learning impairments. However, attempts to validate the anhedonia-specific impairments have produced inconsistent findings. Thus, we seek to determine whether the Reward Behavior Disengagement (RBD), our proposed economic augmentation of PRT, differs between MDD participants and controls, and whether there is a level at which RBD is high enough for depressed participants to be considered objectively disengaged. Data were gathered as part of the Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study, a double-blind, placebo-controlled clinical trial of antidepressant response. Participants included 195 individuals with moderate to severe MDD (Quick Inventory of Depressive Symptomatology (QIDS-SR) score ≥ 15), not in treatment for depression, and with complete PRT data. Healthy controls (n = 40) had no history of psychiatric illness, a QIDS-SR score < 8, and complete PRT data. Participants with MDD were treated with sertraline or placebo for 8 weeks (stage I of the EMBARC trial). RBD was applied to PRT data using discriminant analysis, and classified MDD participants as reward task engaged (n = 137) or reward task disengaged (n = 58), relative to controls. Reward task engaged/disengaged groups were compared on sociodemographic features, reward-behavior, and sertraline/placebo response (Hamilton Depression Rating Scale scores). Reward task disengaged MDD participants responded only to sertraline, whereas those who were reward task engaged responded to sertraline and placebo (F(1293) = 4.33, p = 0.038). Reward task engaged/disengaged groups did not differ otherwise. RBD was predictive of reward impairment in depressed patients and may have clinical utility in identifying patients who will benefit from antidepressants.

Predicting Fear Extinction in Posttraumatic Stress Disorder.

Fear extinction is the basis of exposure therapies for posttraumatic stress disorder (PTSD), but half of patients do not improve. Predicting fear extinction in individuals with PTSD may inform personalized exposure therapy development. The participants were 125 trauma-exposed adults (96 female) with a range of PTSD symptoms. Electromyography, electrocardiogram, and skin conductance were recorded at baseline, during dark-enhanced startle, and during fear conditioning and extinction. Using a cross-validated, hold-out sample prediction approach, three penalized regressions and conventional ordinary least squares were trained to predict fear-potentiated startle during extinction using 50 predictor variables (5 clinical, 24 self-reported, and 21 physiological). The predictors, selected by penalized regression algorithms, were included in multivariable regression analyses, while univariate regressions assessed individual predictors. All the penalized regressions outperformed OLS in prediction accuracy and generalizability, as indexed by the lower mean squared error in the training and holdout subsamples. During early extinction, the consistent predictors across all the modeling approaches included dark-enhanced startle, the depersonalization and derealization subscale of the dissociative experiences scale, and the PTSD hyperarousal symptom score. These findings offer novel insights into the modeling approaches and patient characteristics that may reliably predict fear extinction in PTSD. Penalized regression shows promise for identifying symptom-related variables to enhance the predictive modeling accuracy in clinical research.

Dynamic processes in behavioral activation therapy for anhedonic adolescents: Modeling common and patient-specific relations.

OBJECTIVE: Behavioral activation (BA) is a brief intervention for depression encouraging gradual and systematic re-engagement with rewarding activities and behaviors. Given this treatment focus, BA may be particularly beneficial for adolescents with prominent anhedonia, a predictor of poor treatment response and common residual symptom. We applied group iterative multiple model estimation (GIMME) to ecological momentary assessment (EMA) treatment data to investigate common and person-specific processes during BA for anhedonic adolescents. METHOD: Thirty-nine adolescents (Mage = 15.7 years old, 67% female, 81% White) with elevated anhedonia (Snaith-Hamilton Pleasure Scale) were enrolled in a 12-week BA trial, with weekly anhedonia assessments. EMA surveys were triggered every other week (2-3 surveys per day) throughout treatment assessing current positive affect (PA) and negative affect (NA), engagement in pleasurable activities and social interactions, anticipatory pleasure, rumination, and recent pleasurable and stressful experiences. RESULTS: A multilevel model revealed significant decreases in anhedonia, t(25.5) = -4.76, p < .001, over the 12-week trial. GIMME results indicated substantial heterogeneity in variable networks across patients. PA was the variable with the greatest number (22% of all paths vs. 11% for NA) of predictive paths to other symptoms (i.e., highest out-degree). Higher PA (but not NA) out-degree was associated with greater anhedonia improvement, t(25.8) = -2.22, p = .035. CONCLUSIONS: Results revealed substantial heterogeneity in variable relations across patients, which may obscure the search for common processes of change in BA. PA may be a particularly important treatment target for anhedonic adolescents in BA. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Social Safety Theory: Conceptual foundation, underlying mechanisms, and future directions.

Classic theories of stress and health are largely based on assumptions regarding how different psychosocial stressors influence biological processes that, in turn, affect human health and behavior. Although theoretically rich, this work has yielded little consensus and led to numerous conceptual, measurement, and reproducibility issues. Social Safety Theory aims to address these issues by using the primary goal and regulatory logic of the human brain and immune system as the basis for specifying the social-environmental situations to which these systems should respond most strongly to maximize reproductive success and survival. This analysis gave rise to the integrated, multi-level formulation described herein, which transforms thinking about stress biology and provides a biologically based, evolutionary account for how and why experiences of social safety and social threat are strongly related to health, well-being, aging, and longevity. In doing so, the theory advances a testable framework for investigating the biopsychosocial roots of health disparities as well as how health-relevant biopsychosocial processes crystalize over time and how perceptions of the social environment interact with childhood microbial environment, birth cohort, culture, air pollution, genetics, sleep, diet, personality, and self-harm to affect health. The theory also highlights several interventions for reducing social threat and promoting resilience.

Randomized Controlled Trial of a Mindfulness Mobile Application for Ruminative Adolescents.

OBJECTIVE: Rumination is a risk factor for the development of internalizing psychopathology that often emerges during adolescence. The goal of the present study was to test a mindfulness mobile app intervention designed to reduce rumination. METHOD: Ruminative adolescents (N = 152; 59% girls, 18% racial/ethnic minority, Mage = 13.72, SD = .89) were randomly assigned to use a mobile app 3 times per day for 3 weeks that delivered brief mindfulness exercises or a mood monitoring-only control. Participants reported on rumination, depressive symptoms and anxiety symptoms at baseline, post-intervention and at 3 follow-up timepoints: 6 weeks, 12 weeks, and 6 months post-intervention. Parents reported on internalizing symptoms. RESULTS: There was a significant Time X Condition effect at post-intervention for rumination, depressive symptoms, and anxiety symptoms, such that participants in the mindfulness intervention showed improvements relative to those in the control condition. The effect for rumination lasted through the 6-week follow-up period; however, group differences were generally not observed throughout the follow-up period, which may indicate that continued practice is needed for gains to be maintained. CONCLUSIONS: This intervention may have the potential to prevent the development of psychopathology and should be tested in a longitudinal study assessing affective disorder onset, especially in populations with limited access to conventional, in person mental health care.This study was registered with Clinicaltrials.gov (Identifier NCT03900416).

Reward-related predictors of symptom change in behavioral activation therapy for anhedonic adolescents: a multimodal approach.

Anhedonia is a cardinal characteristic of depression which predicts worse treatment outcome and is among the most common residual symptoms following treatment. Behavioral Activation (BA) has been shown to be an effective treatment for depressed adults, and more recently, depressed adolescents. Given its emphasis on systematically and gradually increasing exposure to and engagement with rewarding activities and experiences, BA may be a particularly effective intervention for adolescents experiencing anhedonia and associated reward system dysfunction. In the present study, anhedonic adolescents (AA; n = 39) received 12 weekly sessions of BA and completed a multimodal (i.e., neural, behavioral, and self-report [ecological momentary assessment]) assessment of reward function at pre-treatment and post-treatment (as well as weekly self-report assessments of anhedonia). Typically developing adolescents (TDA; n = 41) completed the same measures at corresponding timepoints. Multilevel models tested pre-treatment reward-related predictors of anhedonia improvement, as well as change in reward measures over the course of BA. Analyses revealed significant reductions in anhedonia following BA treatment. Enhanced pre-treatment neural (striatal) reward responsiveness predicted greater anhedonia improvement. In contrast, baseline self-report and behavioral reward measures did not predict treatment outcome. A group x time interaction revealed greater increases in both reward- and loss-related neural responsiveness among AA relative to TDA adolescents. Consistent with a capitalization (rather than compensatory) model, pre-treatment neural - but not self-report or behavioral - measures of relatively enhanced reward responsiveness predicted better BA outcome. In addition to alleviating anhedonia, successful BA may also increase neural sensitivity to affectively salient (e.g., reward- and loss-related) stimuli among anhedonic youth.

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.

Reduced anhedonia following internet-based cognitive-behavioral therapy for depression is mediated by enhanced reward circuit activation.

BACKGROUND: Major depressive disorder (MDD) is a highly prevalent psychiatric condition, yet many patients do not receive adequate treatment. Novel and highly scalable interventions such as internet-based cognitive-behavioral-therapy (iCBT) may help to address this treatment gap. Anhedonia, a hallmark symptom of MDD that refers to diminished interest and ability to experience pleasure, has been associated with reduced reactivity in a neural reward circuit that includes medial prefrontal and striatal brain regions. Whether iCBT can reduce anhedonia severity in MDD patients, and whether these therapeutic effects are accompanied by enhanced reward circuit reactivity has yet to be examined. METHODS: Fifty-two MDD patients were randomly assigned to either 10-week iCBT (n = 26) or monitored attention control (MAC, n = 26) programs. All patients completed pre- and post-treatment assessments of anhedonia (Snaith-Hamilton Pleasure Scale; SHAPS) and reward circuit reactivity [monetary incentive delay (MID) task during functional magnetic resonance imaging (fMRI)]. Healthy control participants (n = 42) also underwent two fMRI scans while completing the MID task 10 weeks apart. RESULTS: Both iCBT and MAC groups exhibited a reduction in anhedonia severity post-treatment. Nevertheless, only the iCBT group exhibited enhanced nucleus accumbens (Nacc) and subgenual anterior cingulate cortex (sgACC) activation and functional connectivity from pre- to post-treatment in response to reward feedback. Enhanced Nacc and sgACC activations were associated with reduced anhedonia severity following iCBT treatment, with enhanced Nacc activation also mediating the reduction in anhedonia severity post-treatment. CONCLUSIONS: These findings suggest that increased reward circuit reactivity may contribute to a reduction in anhedonia severity following iCBT treatment for depression.

Personalized Prediction of Response to Smartphone-Delivered Meditation Training: Randomized Controlled Trial.

BACKGROUND: Meditation apps have surged in popularity in recent years, with an increasing number of individuals turning to these apps to cope with stress, including during the COVID-19 pandemic. Meditation apps are the most commonly used mental health apps for depression and anxiety. However, little is known about who is well suited to these apps. OBJECTIVE: This study aimed to develop and test a data-driven algorithm to predict which individuals are most likely to benefit from app-based meditation training. METHODS: Using randomized controlled trial data comparing a 4-week meditation app (Healthy Minds Program [HMP]) with an assessment-only control condition in school system employees (n=662), we developed an algorithm to predict who is most likely to benefit from HMP. Baseline clinical and demographic characteristics were submitted to a machine learning model to develop a "Personalized Advantage Index" (PAI) reflecting an individual's expected reduction in distress (primary outcome) from HMP versus control. RESULTS: A significant group × PAI interaction emerged (t658=3.30; P=.001), indicating that PAI scores moderated group differences in outcomes. A regression model that included repetitive negative thinking as the sole baseline predictor performed comparably well. Finally, we demonstrate the translation of a predictive model into personalized recommendations of expected benefit. CONCLUSIONS: Overall, the results revealed the potential of a data-driven algorithm to inform which individuals are most likely to benefit from a meditation app. Such an algorithm could be used to objectively communicate expected benefits to individuals, allowing them to make more informed decisions about whether a meditation app is appropriate for them. TRIAL REGISTRATION: ClinicalTrials.gov NCT04426318; https://clinicaltrials.gov/ct2/show/NCT04426318.

Which adolescents are well-suited to app-based mindfulness training? A randomized clinical trial and data-driven approach for personalized recommendations.

OBJECTIVE: Rumination heightens risk for depression and anxiety, which increase substantially during adolescence. Smartphone apps offer a convenient and cost-effective means for adolescents to access mindfulness training, which may reduce rumination. Despite their increasing popularity, it is unclear which adolescents benefit from mindfulness apps. METHOD: Adolescents (n = 152) with elevated trait rumination were randomly assigned to 3 weeks of app-based mindfulness training or a mood-monitoring control. Multilevel models tested group differences in state rumination change, assessed via ecological momentary assessment. Baseline adolescent characteristics were submitted to elastic net regularization models to develop a "Personalized Advantage Index" indicating an individual's expected outcome from the mindfulness app relative to the mood-monitoring control. Finally, we translated a predictive model (developed in an external sample) for personalized recommendations of expected benefit from the mindfulness app. RESULTS: Adolescents in the mindfulness app condition reported significantly greater reductions in rumination than adolescents in the control condition. Individuals predicted to have better outcomes from the mindfulness app relative to mood monitoring had significantly greater reductions in rumination if randomly assigned to the mindfulness condition. In contrast, between-condition differences in outcome were not significant for adolescents predicted to have better outcomes in the mood-monitoring condition. CONCLUSIONS: Findings support the efficacy of a mindfulness app to reduce state rumination in adolescents, particularly among adolescents high in trait rumination. A predictive model is put forth, which could be used to objectively communicate expected mindfulness app outcomes to adolescents prior to engagement in app-based mindfulness training. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Neural substrates of emotional conflict with anxiety in major depressive disorder: Findings from the Establishing Moderators and biosignatures of Antidepressant Response in Clinical Care (EMBARC) randomized controlled trial.

BACKGROUND: The brain circuitry of depression and anxiety/fear is well-established, involving regions such as the limbic system and prefrontal cortex. We expand prior literature by examining the extent to which four discrete factors of anxiety (immediate state anxiety, physiological/panic, neuroticism/worry, and agitation/restlessness) among depressed outpatients are associated with differential responses during reactivity to and regulation of emotional conflict. METHODS: A total of 172 subjects diagnosed with major depressive disorder underwent functional magnetic resonance imaging while performing an Emotional Stroop Task. Two main contrasts were examined using whole brain voxel wise analyses: emotional reactivity and emotion regulation. We also evaluated the association of these contrasts with the four aforementioned anxiety factors. RESULTS: During emotional reactivity, participants with higher immediate state anxiety showed potentiated activation in the rolandic operculum and insula, while individuals with higher levels of physiological/panic demonstrated decreased activation in the posterior cingulate. No significant results emerged for any of the four factors on emotion regulation. When re-analyzing these statistically-significant brain regions through analyses of a subsample with (n = 92) and without (n = 80) a current anxiety disorder, no significant associations occurred among those without an anxiety disorder. Among those with an anxiety disorder, results were similar to the full sample, except the posterior cingulate was associated with the neuroticism/worry factor. CONCLUSIONS: Divergent patterns of task-related brain activation across four discrete anxiety factors could be used to inform treatment decisions and target specific aspects of anxiety that involve intrinsic processing to attenuate overactive responses to emotional stimuli.

Feasibility and Acceptability of Cognitive Bias Modification for Interpretation as an Adjunctive Treatment for OCD and Related Disorders: A Pilot Randomized Controlled Trial.

Cognitive models implicate interpretation bias in the development and maintenance of obsessive compulsive and related disorders (OCRDs), and research supports Cognitive Bias Modification for Interpretation (CBM-I) in targeting this mechanism. However, prior studies in OCRDs have been limited to nonclinical populations, adolescents, and adults in a laboratory setting. This study evaluated the feasibility and acceptability of CBM-I as an adjunctive intervention during intensive/residential treatment (IRT) for adults with OCRDs. We modified a lab-based CBM-I training for adults seeking IRT for OCRDs, and conducted a feasibility trial (N = 4) and subsequent pilot RCT; participants (N = 31) were randomized to receive CBM-I or psychoeducation. Benchmarks were met for feasibility, acceptability, and target engagement. From pre- to post-intervention, the CBM-I group showed a large effect for change in interpretation bias (d = .90), whereas this effect was trivial (d = .06) for psychoeducation. This was the first study to evaluate CBM-I in naturalistic treatment for adults seeking IRT for OCRDs. Findings support the feasibility and acceptability of CBM-I in this novel sample and setting. A larger scale RCT is needed to determine whether CBM-I can enhance OCRD treatment response.