Resting EEG Periodic and Aperiodic Components Predict Cognitive Decline Over 10 Years.

Measures of intrinsic brain function at rest show promise as predictors of cognitive decline in humans, including EEG metrics such as individual α peak frequency (IAPF) and the aperiodic exponent, reflecting the strongest frequency of α oscillations and the relative balance of excitatory/inhibitory neural activity, respectively. Both IAPF and the aperiodic exponent decrease with age and have been associated with worse executive function and working memory. However, few studies have jointly examined their associations with cognitive function, and none have examined their association with longitudinal cognitive decline rather than cross-sectional impairment. In a preregistered secondary analysis of data from the longitudinal Midlife in the United States (MIDUS) study, we tested whether IAPF and aperiodic exponent measured at rest predict cognitive function (N = 235; age at EEG recording M = 55.10, SD = 10.71) over 10 years. The IAPF and the aperiodic exponent interacted to predict decline in overall cognitive ability, even after controlling for age, sex, education, and lag between data collection time points. Post hoc tests showed that "mismatched" IAPF and aperiodic exponents (e.g., higher exponent with lower IAPF) predicted greater cognitive decline compared to "matching" IAPF and aperiodic exponents (e.g., higher exponent with higher IAPF; lower IAPF with lower aperiodic exponent). These effects were largely driven by measures of executive function. Our findings provide the first evidence that IAPF and the aperiodic exponent are joint predictors of cognitive decline from midlife into old age and thus may offer a useful clinical tool for predicting cognitive risk in aging.

Resting state functional connectivity changes following mindfulness-based stress reduction predict improvements in disease control for patients with asthma.

BACKGROUND: The staggering morbidity associated with chronic inflammatory diseases can be reduced by psychological interventions, including Mindfulness-Based Stress Reduction (MBSR). Proposed mechanisms for MBSR's beneficial effects include changes in salience network function. Salience network perturbations are also associated with chronic inflammation, including airway inflammation in asthma, a chronic inflammatory disease affecting approximately 10% of the population. However, no studies have examined whether MBSR-related improvements in disease control are related to changes in salience network function. METHODS: Adults with asthma were randomized to 8 weeks of MBSR or a waitlist control group. Resting state functional connectivity was measured using fMRI before randomization, immediately post-intervention, and 4 months post-intervention. Using key salience network regions as seeds, we calculated group differences in change in functional connectivity over time and examined whether functional connectivity changes were associated with increased mindfulness, improved asthma control, and decreased inflammatory biomarkers. RESULTS: The MBSR group showed greater increases in functional connectivity between salience network regions relative to the waitlist group. Improvements in asthma control correlated with increased functional connectivity between the salience network and regions important for attention control and emotion regulation. Improvements in inflammatory biomarkers were related to decreased functional connectivity between the salience network and other networks. CONCLUSIONS: Increased resting salience network coherence and connectivity with networks that subserve attention and emotion regulation may contribute to the benefits of MBSR for patients with asthma. Understanding the neural underpinnings of MBSR-related benefits in patients is a critical step towards optimizing brain-targeted interventions for chronic inflammatory disease management.

Time-resolved dynamic computational modeling of human EEG recordings reveals gradients of generative mechanisms for the MMN response.

Despite attempts to unify the different theoretical accounts of the mismatch negativity (MMN), there is still an ongoing debate on the neurophysiological mechanisms underlying this complex brain response. On one hand, neuronal adaptation to recurrent stimuli is able to explain many of the observed properties of the MMN, such as its sensitivity to controlled experimental parameters. On the other hand, several modeling studies reported evidence in favor of Bayesian learning models for explaining the trial-to-trial dynamics of the human MMN. However, direct comparisons of these two main hypotheses are scarce, and previous modeling studies suffered from methodological limitations. Based on reports indicating spatial and temporal dissociation of physiological mechanisms within the timecourse of mismatch responses in animals, we hypothesized that different computational models would best fit different temporal phases of the human MMN. Using electroencephalographic data from two independent studies of a simple auditory oddball task (n = 82), we compared adaptation and Bayesian learning models' ability to explain the sequential dynamics of auditory deviance detection in a time-resolved fashion. We first ran simulations to evaluate the capacity of our design to dissociate the tested models and found that they were sufficiently distinguishable above a certain level of signal-to-noise ratio (SNR). In subjects with a sufficient SNR, our time-resolved approach revealed a temporal dissociation between the two model families, with high evidence for adaptation during the early MMN window (from 90 to 150-190 ms post-stimulus depending on the dataset) and for Bayesian learning later in time (170-180 ms or 200-220ms). In addition, Bayesian model averaging of fixed-parameter models within the adaptation family revealed a gradient of adaptation rates, resembling the anatomical gradient in the auditory cortical hierarchy reported in animal studies.

COVID-19 and worker mental distress.

BACKGROUND: This analysis posits that COVID-19-related worker mental distress may be different for those continuously employed and for those who faced temporary job loss. METHODS: Mental distress during COVID-19 is characterized using two nationally representative surveys, the American Trend Panel (ATP) and the Household Pulse Survey (HPS). Using a probit model, we examine workplace perceptions for the mentally distressed in the ATP sample. We use graphical analysis to identify barriers to seeking mental healthcare using the 2021-22 HPS sample. RESULTS: In October 2020, the probability of mental distress increased between 7.1 and 9.1 percentage points in response to worsening work-life balance, lowered job security, lowered work productivity and lowered work satisfaction. Workers' perception of advancement denial and poor connectivity with coworkers increased the probability of mental distress by 3.0-5.8 percentage points. In October 2021, over 40% of workers who had experienced job loss reported mental distress as compared to 20% of those with jobs. Only 25% of those with mental distress sought counseling. These high levels of mental distress continued into October 2022. CONCLUSIONS: Mitigation strategies for worker mental health should include prosocial nudges, attention to employment history, managerial sensitivity and worker resilience training.

How often should I meditate? A randomized trial examining the role of meditation frequency when total amount of meditation is held constant.

Meditation apps are the most commonly used mental health apps. However, the optimal dosing of app-delivered meditation practice has not been established. We examined whether the distribution of meditation practices across a day impacted outcomes in a distressed population. We investigated the effects of meditation practice frequency in a 2-week compassion-based meditation intervention delivered via the Healthy Minds Program app. Undergraduates with clinically elevated depression and/or anxiety (N = 351) were randomized to a massed (one 20-min meditation per day) or distributed condition (two 10-min meditations per day). Psychological distress (primary outcome; composite of depression and anxiety), experiential avoidance, fear of missing out, loneliness, and self-compassion were assessed pre- and post-intervention. Psychological distress, loneliness, and informal meditation practice were also assessed daily. Practice time and frequency were assessed using app data. Results support feasibility of the study design, success of the manipulation, and acceptability of the intervention. Pooled across conditions, participants exhibited pre-post improvements on all outcomes (absolute value of ds = 0.12-0.63, p ≤ .010) and trajectories of improvement on daily distress and loneliness (p ≤ .010). No between-group differences were observed on changes in pre-post or daily measures (ps = .158-.729). When total amount of meditation practice per day is held constant, the distribution of practice may not influence outcomes for distressed beginners. Although only a first test of dose frequency effects, findings support flexibility in the distribution of meditation throughout the day, which may increase accessibility. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Neuroimaging-based classification of PTSD using data-driven computational approaches: A multisite big data study from the ENIGMA-PGC PTSD consortium.

BACKGROUND: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group. METHODS: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality. RESULTS: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60 % test AUC for s-MRI, 59 % for rs-fMRI and 56 % for d-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75 % AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance. CONCLUSION: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable.

Inverse association between stress induced cortisol elevations and negative emotional reactivity to stress in humans.

Greater cortisol reactivity to stress is often assumed to lead to heightened negative affective reactivity to stress. Conversely, a growing body of evidence demonstrates mood-protective effects of cortisol elevations in the context of acute stress. We administered a laboratory-based stressor, the Trier Social Stress Test (TSST), and measured cortisol and emotional reactivity in 68 adults (48 women) between the ages of 25 and 65. In accordance with our pre-registered hypothesis (https://osf.io/t8r3w) and prior research, negative affective reactivity was inversely related to cortisol reactivity assessed immediately after the stressor. We found that greater cortisol response to acute stress is associated with smaller increases in negative affect, consistent with mood-protective effects of cortisol elevations in response to acute stress.

White matter microstructure predicts individual differences in infant fear (But not anger and sadness).

We examine neural correlates of discrete expressions of negative emotionality in infants to determine whether the microstructure of white matter tracts at 1 month of age foreshadows the expression of specific negative emotions later in infancy. Infants (n = 103) underwent neuroimaging at 1-month, and mothers reported on infant fear, sadness, and anger at 6, 12, and 18 months using the Infant Behavior Questionnaire-Revised. Levels and developmental change in fear, sadness, and anger were estimated from mother reports. Relations between MRI and infant emotion indicated that 1-month white matter microstructure was differentially associated with level and change in infant fear, but not anger or sadness, in the left stria terminalis (p < 0.05, corrected), a tract that connects frontal and tempo-parietal regions and has been implicated in emerging psychopathology in adults. More relaxed constraints on significance (p < 0.10, corrected) revealed that fear was associated with lower white matter microstructure bilaterally in the inferior portion of the stria terminalis and regions within the sagittal stratum. Results suggest the neurobehavioral uniqueness of fear as early as 1 month of age in regions that are associated with potential longer-term outcomes. This work highlights the early neural precursors of fearfulness, adding to literature explaining the psychobiological accounts of affective development. HIGHLIGHTS: Expressions of infant fear and anger, but not sadness, increase from 6 to 18 months of age. Early neural architecture in the stria terminalis is related to higher initial levels and increasing fear in infancy. After accounting for fear, anger and sadness do not appear to be associated with differences in early white matter microstructure. This work identifies early neural precursors of fearfulness as early as 1-month of age.

Behavioral adjustment moderates the effect of neuroticism on brain volume relative to intracranial volume.

OBJECTIVE: The present study examined whether the effect of neuroticism on brain structure is moderated by behavioral adjustment. BACKGROUND: Neuroticism is widely thought to be harmful to health. However, recent work using proinflammatory biomarkers showed that this effect depends on behavioral adjustment, the willingness and ability to adjust and cope with environmental contingencies, such as different opinions of others or unpredictable life situations. Here, we sought to extend this observation to "brain health" by testing total brain volume (TBV). METHOD: Using a community sample of 125 Americans, we examined structural magnetic resonance imaging of the brain and quantified TBV. We tested whether the effect of neuroticism on TBV was moderated by behavioral adjustment, net of intracranial volume, age, sex, educational achievement, and race. RESULTS: Behavioral adjustment significantly moderated the effect of neuroticism on TBV, such that neuroticism was associated with lower TBV only when behavioral adjustment was low. There was no such effect when behavioral adjustment was high. CONCLUSION: The present findings suggest that neuroticism is not debilitating to those who constructively cope with stress. Implications are further discussed.

The plasticity of well-being: A training-based framework for the cultivation of human flourishing.

Research indicates that core dimensions of psychological well-being can be cultivated through intentional mental training. Despite growing research in this area and an increasing number of interventions designed to improve psychological well-being, the field lacks a unifying framework that clarifies the dimensions of human flourishing that can be cultivated. Here, we integrate evidence from well-being research, cognitive and affective neuroscience, and clinical psychology to highlight four core dimensions of well-being-awareness, connection, insight, and purpose. We discuss the importance of each dimension for psychological well-being, identify mechanisms that underlie their cultivation, and present evidence of their neural and psychological plasticity. This synthesis highlights key insights, as well as important gaps, in the scientific understanding of well-being and how it may be cultivated, thus highlighting future research directions.

Neuroimaging and biomarker evidence of neurodegeneration in asthma.

BACKGROUND: Epidemiologic studies have shown that Alzheimer's disease (AD) and related dementias (ADRD) are seen more frequently with asthma, especially with greater asthma severity or exacerbation frequency. OBJECTIVE: To examine the changes in brain structure that may underlie this phenomenon, we examined diffusion-weighted magnetic resonance imaging (dMRI) and blood-based biomarkers of AD (phosphorylated tau 181, p-Tau181), neurodegeneration (neurofilament light chain, NfL), and glial activation (glial fibrillary acidic protein, GFAP). METHODS: dMRI data were obtained in 111 individuals with asthma, ranging in disease severity from mild to severe, and 135 healthy controls. Regression analyses were used to test the relationships between asthma severity and neuroimaging measures, as well as AD pathology, neurodegeneration, and glial activation, indexed by plasma p-Tau181, NfL, and GFAP, respectively. Additional relationships were tested with cognitive function. RESULTS: Asthma participants had widespread and large-magnitude differences in several dMRI metrics, which were indicative of neuroinflammation and neurodegeneration, and which were robustly associated with GFAP and, to a lesser extent, NfL. The AD biomarker p-Tau181 was only minimally associated with neuroimaging outcomes. Further, asthma severity was associated with deleterious changes in neuroimaging outcomes, which in turn were associated with slower processing speed, a test of cognitive performance. CONCLUSIONS: Asthma, particularly when severe, is associated with characteristics of neuroinflammation and neurodegeneration, and may be a potential risk factor for neural injury and cognitive dysfunction. There is a need to determine how asthma may affect brain health and whether treatment directed toward characteristics of asthma associated with these risks can mitigate these effects.

Linking Amygdala Persistence to Real-World Emotional Experience and Psychological Well-Being.

Neural dynamics in response to affective stimuli are linked to momentary emotional experiences. The amygdala, in particular, is involved in subjective emotional experience and assigning value to neutral stimuli. Because amygdala activity persistence following aversive events varies across individuals, some may evaluate subsequent neutral stimuli more negatively than others. This may lead to more frequent and long-lasting momentary emotional experiences, which may also be linked to self-evaluative measures of psychological well-being (PWB). Despite extant links between daily affect and PWB, few studies have directly explored the links between amygdala persistence, daily affective experience, and PWB. To that end, we examined data from 52 human adults (67% female) in the Midlife in the United States study who completed measures of PWB, daily affect, and functional MRI (fMRI). During fMRI, participants viewed affective images followed by a neutral facial expression, permitting quantification of individual differences in the similarity of amygdala representations of affective stimuli and neutral facial expressions that follow. Using representational similarity analysis, neural persistence following aversive stimuli was operationalized as similarity between the amygdala activation patterns while encoding negative images and the neutral facial expressions shown afterward. Individuals demonstrating less persistent activation patterns in the left amygdala to aversive stimuli reported more positive and less negative affect in daily life. Further, daily positive affect served as an indirect link between left amygdala persistence and PWB. These results clarify important connections between individual differences in brain function, daily experiences of affect, and well-being.SIGNIFICANCE STATEMENT At the intersection of affective neuroscience and psychology, researchers have aimed to understand how individual differences in the neural processing of affective events map onto to real-world emotional experiences and evaluations of well-being. Using a longitudinal dataset from 52 adults in the Midlife in the United States (MIDUS) study, we provide an integrative model of affective functioning: less amygdala persistence following negative images predicts greater positive affect (PA) in daily life, which in turn predicts greater psychological well-being (PWB) seven years later. Thus, day-to-day experiences of PA comprise a promising intermediate step that links individual differences in neural dynamics to complex judgements of PWB.

Long-term Meditation Training Is Associated with Enhanced Subjective Attention and Stronger Posterior Cingulate-Rostrolateral Prefrontal Cortex Resting Connectivity.

Mindfulness meditation has been shown to increase resting-state functional connectivity (rsFC) between the posterior cingulate cortex (PCC) and dorsolateral prefrontal cortex (DLPFC), which is thought to reflect improvements in shifting attention to the present moment. However, prior research in long-term meditation practitioners lacked quantitative measures of attention that would provide a more direct behavioral correlate and interpretational anchor for PCC-DLPFC connectivity and was inherently limited by small sample sizes. Moreover, whether mindfulness meditation primarily impacts brain function locally, or impacts the dynamics of large-scale brain networks, remained unclear. Here, we sought to replicate and extend prior findings of increased PCC-DLPFC rsFC in a sample of 40 long-term meditators (average practice = 3759 hr) who also completed a behavioral assay of attention. In addition, we tested a network-based framework of changes in interregional connectivity by examining network-level connectivity. We found that meditators had stronger PCC-rostrolateral prefrontal cortex (RLPFC) rsFC, lower connector hub strength across the default mode network, and better subjective attention, compared with 124 meditation-naive controls. Orienting attention positively correlated with PCC-RLPFC connectivity and negatively correlated with default mode network connector hub strength. These findings provide novel evidence that PCC-RLPFC rsFC may support attention orienting, consistent with a role for RLPFC in the attention shifting component of metacognitive awareness that is a core component of mindfulness meditation training. Our results further demonstrate that long-term mindfulness meditation may improve attention and strengthen the underlying brain networks.

Diversity of daily activities is associated with greater hippocampal volume.

Greater engagement in a range of daily activities is associated with better cognitive functioning (Lee et al., Lee et al., 2020). The hippocampus, a subcortical brain structure implicated in learning, memory, spatial navigation and other aspects of cognitive functioning, may be structurally sensitive to exposure to and engagement with novel experiences and environments. The present study tested whether greater activity diversity, defined as the range of common daily activities engaged in and the proportion of time spent in each, is associated with larger hippocampal volume. Greater diversity of activities, as measured using daily diaries across an 8-day period, was related to greater hippocampal volume averaged across the left and right hemispheres, even when adjusting for estimated intracranial volume, total activity time, sociodemographic factors, and self-reported physical health. These findings are broadly consistent with nonhuman animal studies, demonstrating a link between enriched environments and structural changes to the hippocampus. Future longitudinal and experimental work can elucidate causal and directional relationships between diversity of daily activities and hippocampal volume.

The effects of perceived stress and anhedonic depression on mnemonic similarity task performance.

Previous research has demonstrated hippocampal alterations in individuals experiencing elevated stress. The Mnemonic Similarity Task (MST) is a hippocampal-dependent task sensitive to age-related hippocampal decline, but it is unknown how performance on this task is related to one's experience of daily stress. We conducted separate discovery and replication analyses in 510 participants who completed the MST across four different Mechanical Turk studies. We hypothesized that higher scores on the Perceived Stress Scale would be associated with poorer discrimination of "lure" items from previously seen targets - a behavioral index of pattern separation - but not with recognition memory. The zero-order relationship between perceived stress and lure discrimination was not significant in the discovery or replication sample. Exploratory analyses involving anhedonic depression symptoms (from the Mood and Anxiety Symptoms Questionnaire) revealed a robust perceived stress*anhedonic depression interaction in the discovery sample that was confirmed in the replication sample. In both samples, individuals with low but not high anhedonic depression symptoms showed an inverse association between perceived stress and lure discrimination ability. Contrary to hypotheses, a similar interaction was observed for recognition memory. The novel association between perceived stress and behavioral pattern separation suggests a candidate behavioral process associated with stress-related hippocampal deficits. The specificity of this effect for individuals with low anhedonic depression symptoms - and the lack of behavioral specificity - highlight the need for additional research to unpack the clinical and neurobiological significance of these findings.

Prevalence of harm in mindfulness-based stress reduction.

BACKGROUND: Mindfulness meditation has become a common method for reducing stress, stress-related psychopathology and some physical symptoms. As mindfulness programs become ubiquitous, concerns have been raised about their unknown potential for harm. We estimate multiple indices of harm following Mindfulness-Based Stress Reduction (MBSR) on two primary outcomes: global psychological and physical symptoms. In secondary analyses, we estimate multiple indices of harm on anxiety and depressive symptoms, discomfort in interpersonal relations, paranoid ideation and psychoticism. METHODS: Intent-to-treat analyses with multiple imputations for missing data were used on pre- and post-test data from a large, observational dataset (n = 2155) of community health clinic MBSR classes and from MBSR (n = 156) and waitlist control (n = 118) participants from three randomized controlled trials conducted contemporaneous to community classes in the same city by the same health clinic MBSR teachers. We estimate the change in symptoms, proportion of participants with increased symptoms, proportion of participants reporting greater than a 35% increase in symptoms, and for global psychological symptoms, clinically significant harm. RESULTS: We find no evidence that MBSR leads to higher rates of harm relative to waitlist control on any primary or secondary outcome. On many indices of harm across multiple outcomes, community MBSR was significantly preventative of harm. CONCLUSIONS: Engagement in MBSR is not predictive of increased rates of harm relative to no treatment. Rather, MBSR may be protective against multiple indices of harm. Research characterizing the relatively small proportion of MBSR participants that experience harm remains important.

Self-compassion and dorsolateral prefrontal cortex activity during sad self-face recognition in depressed adolescents.

BACKGROUND: Given the prevalence of adolescent depression and the modest effects of current treatments, research ought to inform development of effective intervention strategies. Self-compassion is inversely associated with depression, and self-compassion interventions have demonstrated promising effects on reducing depression. However, little is known about the neural mechanisms underlying that relationship. Maladaptive self-processing is a characteristic of depression that contributes to the onset and chronicity of depression. Because our own face is an automatic and direct cue for self-processing, this study investigated whether self-compassion was associated with neural responses during sad v. neutral self-face recognition and explore their relationship with depression severity in depressed adolescents and healthy controls (HCs). METHODS: During functional magnetic resonance imaging, 81 depressed youth and 37 HCs were instructed to identify whether morphed self or other faces with sad, happy, or neutral expressions resembled their own. RESULTS: Self-compassion correlated negatively with activity during sad v. neutral self-face recognition in the dorsal anterior cingulate cortex in the total sample, and in the right posterior cingulate cortex/precuneus in HCs, respectively. In depressed adolescents, higher self-compassion correlated with lower activity during sad v. neutral self-face recognition in the right dorsolateral prefrontal cortex (DLPFC), implying that less cognitive effort might be needed to avoid dwelling on sad self-faces and/or regulate negative affect induced by them. Moreover, higher self-compassion mediated the relationship between lower DLPFC activity and reduced depression severity. CONCLUSIONS: Our findings imply that DLPFC activity might be a biological marker of a successful self-compassion intervention as potential treatment for adolescent depression.

Cortical volume abnormalities in posttraumatic stress disorder: an ENIGMA-psychiatric genomics consortium PTSD workgroup mega-analysis.

Studies of posttraumatic stress disorder (PTSD) report volume abnormalities in multiple regions of the cerebral cortex. However, findings for many regions, particularly regions outside commonly studied emotion-related prefrontal, insular, and limbic regions, are inconsistent and tentative. Also, few studies address the possibility that PTSD abnormalities may be confounded by comorbid depression. A mega-analysis investigating all cortical regions in a large sample of PTSD and control subjects can potentially provide new insight into these issues. Given this perspective, our group aggregated regional volumes data of 68 cortical regions across both hemispheres from 1379 PTSD patients to 2192 controls without PTSD after data were processed by 32 international laboratories using ENIGMA standardized procedures. We examined whether regional cortical volumes were different in PTSD vs. controls, were associated with posttraumatic stress symptom (PTSS) severity, or were affected by comorbid depression. Volumes of left and right lateral orbitofrontal gyri (LOFG), left superior temporal gyrus, and right insular, lingual and superior parietal gyri were significantly smaller, on average, in PTSD patients than controls (standardized coefficients = -0.111 to -0.068, FDR corrected P values < 0.039) and were significantly negatively correlated with PTSS severity. After adjusting for depression symptoms, the PTSD findings in left and right LOFG remained significant. These findings indicate that cortical volumes in PTSD patients are smaller in prefrontal regulatory regions, as well as in broader emotion and sensory processing cortical regions.

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.

A Randomized Controlled Trial of a Smartphone-Based Well-Being Training in Public School System Employees During the COVID-19 Pandemic.

While the extraordinary pressures of the COVID-19 pandemic on student mental health have received considerable attention, less attention has been placed on educator well-being. School system employees play a vital role in society, and teacher levels of well-being are associated with the educational outcomes of young people. We extend extant research on the prevalence and correlates of educator distress during the pandemic by reporting on a pragmatic randomized wait-list controlled trial (N=662; 64% teachers) of an innovative mental health promotion strategy implemented during the pandemic; a free four-week smartphone-based meditation app designed to train key constituents of well-being (Healthy Minds Program; HMP). Following our preregistered analysis plan and consistent with hypotheses, assignment to the HMP predicted significantly larger reductions in psychological distress, our primary outcome, at post-intervention (Cohen's d=-0.52, 95% confidence interval [-0.68, -0.37], p<.001) and at the three-month follow-up (d=-0.33 [-0.48, -0.18], p<.001). Also consistent with hypotheses, we observed similar indications of immediate and sustained benefit following the HMP on all six preregistered secondary outcomes selected to tap skills targeted in the app (e.g., perseverative thinking, social connection, well-being; absolute ds=0.19-0.42, all ps<.031 corrected except mindful action at follow-up). We found no evidence for elevated adverse events and the HMP was equally effective among participants with elevated baseline anxiety and depressive symptoms. These data suggest that the HMP may be an effective and scalable approach to supporting the mental health and well-being of teachers and other school system employees, with implications for employee retention and performance, and student outcomes.