Investigating the protective effects of mindfulness-based attention training on mind wandering in applied settings

IntroductionMind wandering, a phenomenon in which attention drifts away from the task-at-hand, is associated with deleterious effects on performance and well-being. As such, efforts to curb mind wandering are warranted. Recently, mindfulness training (MT) has been found to protect against mind wandering. Yet, many MT programs are at risk of falling off the implementation cliff due to challenges implementing these programs in applied settings. To mitigate against this, early-stage research in small convenience samples may be necessary to spur stakeholder engagement and collaboration. Herein, the effects of MT on mind wandering were examined via an internal meta-analysis of early-stage studies of a manualized, context-adaptable short-form MT program, referred to as Mindfulness-Based Attention Training (MBAT).MethodsFive longitudinal studies (N = 304) were conducted in a variety of organizational cohorts. Self-reported mind wandering and meta-awareness, as well as accuracy (A’) and response time variability (intra-individual coefficient of variation, ICV) during performance of the sustained attention to response task (SART) were assessed at baseline (T1) and 4 weeks later (T2) in MBAT and no-training participants.ResultsStandardized mean change (SMC) from T1 to T2 significantly differed between MBAT and no-training groups for mind wandering (ΔSMC = −0.387, p < 0.001), meta-awareness (ΔSMC = −0.374, p < 0.001), and ICV (ΔSMC = −0.376, p = 0.043), suggesting potential protective effects in self-reported and performance-based metrics of mind wandering.DiscussionThese results serve as preliminary proof-of-concept support for MBAT’s protective effects on mind wandering. Further, they suggest that MBAT is amenable to implementation across a variety of applied and organizational settings and warrants additional research employing larger sample sizes in randomized controlled designs

Enhanced response inhibition during intensive meditation training predicts improvements in self-reported adaptive socioemotional functioning.

We examined the impact of training-induced improvements in self-regulation, operationalized in terms of response inhibition, on longitudinal changes in self-reported adaptive socioemotional functioning. Data were collected from participants undergoing 3 months of intensive meditation training in an isolated retreat setting (Retreat 1) and a wait-list control group that later underwent identical training (Retreat 2). A 32-min response inhibition task (RIT) was designed to assess sustained self-regulatory control. Adaptive functioning (AF) was operationalized as a single latent factor underlying self-report measures of anxious and avoidant attachment, mindfulness, ego resilience, empathy, the five major personality traits (extroversion, agreeableness, conscientiousness, neuroticism, and openness to experience), diffi-culties in emotion regulation, depression, anxiety, and psychological well-being. Participants in Retreat 1 improved in RIT performance and AF over time whereas the controls did not. The control participants later also improved on both dimensions during their own retreat (Retreat 2). These improved levels of RIT performance and AF were sustained in follow-up assessments conducted approximately 5 months after the training. Longitudinal dynamic models with combined data from both retreats showed that improvement in RIT performance during training influenced the change in AF over time, which is consistent with a key claim in the Buddhist literature that enhanced capacity for self-regulation is an important precursor of changes in emotional well-being

Self-reported mindfulness and cortisol during a Shamatha meditation retreat.

Objective: Cognitive perseverations that include worry and rumination over past or future events may prolong cortisol release, which in turn may contribute to predisease pathways and adversely affect physical health. Meditation training may increase self-reported mindfulness, which has been linked to reductions in cognitive perseverations. However, there are no reports that directly link self-reported mindfulness and resting cortisol output. Here, the authors investigate this link. Methods: In an observational study, we measured self-reported mindfulness and p.m. cortisol near the beginning and end of a 3-month meditation retreat (N = 57). Results: Mindfulness increased from pre- to post-retreat, F(1, 56) = 36.20, p < .001. Cortisol did not significantly change. However, mindfulness was inversely related to p.m. cortisol at pre-retreat, r(53) = −.31, p < .05, and post-retreat, r(53) = −.30, p < .05, controlling for age and body mass index. Pre to postchange in mindfulness was associated with pre to postchange in p.m. cortisol, β = −.37, t(49) = 2.30, p < .05: Larger increases in mindfulness were associated with decreases in p.m. cortisol, whereas smaller increases (or slight decreases) in mindfulness were associated with an increase in p.m. cortisol. Conclusions: These data suggest a relation between self-reported mindfulness and resting output of the hypothalamic-pituitary-adrenal system. Future work should aim to replicate this finding in a larger cohort and determine stronger inference about causality by using experimental designs that include control-group conditions

The Occurrence of Psychologically Profound, Meaningful, and Mystical Experiences during a Month-long Meditation Retreat

Objectives: Contemplative practice can occasion powerful psychological experiences. Yet few empirical studies have investigated whether their occurrence is associated with intensive meditation-based interventions. Here we assess the prevalence of profound, meaningful, and mystical experiences in experienced meditators during a month-long insight meditation retreat compared to a control group of similarly-experienced meditators. Methods: Participants completed the 100-item States of Consciousness Questionnaire (SOCQ) and the Mysticism Scale before and after a 3-week period of intensive retreat or daily life. Multivariate distance matrix regression was used to compare multivariate profiles of responses on the SOCQ and to describe which items contributed most to differences between groups at the end of retreat. Changes in self-reported mystical dimensions of experience were also directly compared between retreat and control participants. Results: The retreat and control groups differed over the training period in their multivariate profile of individual experiences. Retreat group participants reported a greater extent of profound insights, powerful emotional experiences, and non-ordinary sensory or perceptual events compared to experienced meditators not on retreat. Retreatants also reported greater levels of specific dimensions of mystical experience, including internal unity, transcendence, sacredness, noetic quality, and deeply felt positive affect, relative to control participants. Conclusions: These findings support the idea that intensive periods of meditation training are associated with a range of profound and mystical-type experiences. Increased access to these experiences may be one path by which immersive periods of contemplative training contribute to psychological or spiritual development, though the long-term consequences of such experiences remain to be fully understood

Within and Between-person Correlates of the Temporal Dynamics of Resting EEG Microstates

Microstates reflect transient brain states resulting from the activity of synchronously active brain networks that predominate in the broadband EEG time series. Despite increasing interest in understanding how the functional organization of the brain varies across individuals, or the extent to which its spatiotemporal dynamics are state dependent, comparatively little research has examined within and between-person correlates of microstate temporal parameters in healthy populations. In the present study, neuroelectric activity recorded during eyes-closed rest and during simple visual fixation was segmented into a time series of transient microstate intervals. It was found that five data-driven microstate configurations explained the preponderance of topographic variance in the EEG time series of the 374 recordings (from 187 participants) included in the study. We observed that the temporal dynamics of microstates varied within individuals to a greater degree than they differed between persons, with within-person factors explaining a large portion of the variance in mean microstate duration and occurrence rate. Nevertheless, several individual differences were found to predict the temporal dynamics of microstates. Of these, age and gender were the most reliable. These findings suggest that not only do the rich temporal dynamics of whole-brain neuronal networks vary considerably within-individuals, but that microstates appear to differentiate persons based on trait individual differences. The current findings suggest that rather than focusing exclusively on between-person differences in microstates as measures of brain function, researchers should turn their attention towards understanding the factors contributing to within-person variation

EEG Electric Field Topography is Stable During Moments of High Field Strength

Spontaneous broadband electroencephalography (EEG) demonstrates short moments of stability in the spatial distribution of the head-surface voltage topography. This phenomenon underlies the premise behind segmenting multichannel EEG into topographically defined brain states, known as EEG microstates. Microstate segmentation methods commonly identify representative topographical configurations based on clustering applied to a subset of voltage maps selected at the time series points of greatest strength in the neuroelectric field. These moments are well-reasoned to best represent periods of momentary stability in the voltage topography, and consequently, points of greatest signal relative to noise. Yet, more direct empirical evidence for these assumptions is warranted, and the consistency of this phenomenon across individuals has not been characterized. In the present investigation, the association between electric field strength and topographic dissimilarity of temporally adjacent samples of EEG were characterized in a large sample of healthy adults engaged in quiet rest. Samples of individuals' EEG time series high in electric field strength were found to be topographically similar relative to adjacent time series samples. The strong phase-synchronized actvity of neuronal populations therefore coincides with momentary stability in the topographic voltage configuration, providing robust empirical support for the basic premise underlying segmentation of broadband EEG into microstates

Quantifying streams of thought during cognitive task performance using sequence analysis

Streams of thoughts vary in content from one moment to the next, and these temporal patterns have been argued to be critical to understanding the wandering mind. But few analytic methods have been proposed that can account for both the content and temporal ordering of thoughts over time. In the present study, I apply sequence analysis and related methods to quantify the dynamics of thought from time series sequences of categorical experience sampling thought probes delivered across five different cognitive tasks in the same individuals (N = 545). Sequence analysis revealed a modicum of order and consistency in streams of thought within-individuals, but also demonstrated considerable variability within and between task sessions. Hierarchical clustering of sequence dissimilarities further revealed common typologies of mind wandering across individuals. These findings demonstrate the application of sequence analytic methods for quantifying the dynamics of thought over the course of task performance and show that contextual task constraints are associated with how streams of thought unfold over time. More broadly, sequence analysis provides a valuable framework for investigation of time ordered cognitive and behavioral processes across psychological domains

Quantifying streams of thought during cognitive task performance using sequence analysis

Streams of thought vary in content from one moment to the next, and these temporal patterns have been argued to be critical to understanding the wandering mind. But few analytic methods have been proposed that can account for both the content and temporal ordering of categorical experience sampling thought probes over time. In the present study, I apply sequence analytic methods to quantify the dynamics of thought from time series sequences of categorical experience sampling thought probes delivered across five different cognitive tasks in the same individuals (N = 545). Analyses revealed some patterns of consistency in streams of thought within individuals, but also demonstrated considerable variability within and between task sessions. Hierarchical clustering of sequence dissimilarities further revealed common typologies of mind wandering across individuals. These findings demonstrate the application of sequence analytic methods for quantifying the dynamics of thought over the course of task performance and show that contextual task constraints are associated with how streams of thought unfold over time. More broadly, sequence analysis provides a valuable framework for investigation of time ordered cognitive and behavioral processes across psychological domains

Mind-wandering Increases in Frequency Over Time During Task Performance: An Individual-Participant Meta-Analytic Review

This is the repository for data accompanying the article "Mind-wandering increases in frequency over time during task performance: An individual-participant meta-analytic review." in Psychological Bulletin (https://doi.org/10.1037/bul0000424)

Quantifying Streams of Thought during Cognitive Task Performance using Sequence Analysis

Streams of thoughts vary in content from one moment to the next, and these temporal patterns have been argued to be critical to understanding the wandering mind. But few analytic methods have been proposed that can account for both the content and temporal ordering of thoughts over time. In the present study, I apply sequence analysis and related methods to quantify the dynamics of thought from time series sequences of categorical experience sampling thought probes delivered across five different cognitive tasks in the same individuals (N = 545). Sequence analysis revealed a modicum of order and consistency in streams of thought within-individuals, but also demonstrated considerable variability within and between task sessions. Hierarchical clustering of sequence dissimilarities further revealed common typologies of mind wandering across individuals. These findings demonstrate the application of sequence analytic methods for quantifying the dynamics of thought over the course of task performance and show that contextual task constraints are associated with how streams of thought unfold over time. More broadly, sequence analysis provides a valuable framework for investigation of time ordered cognitive and behavioral processes across psychological domains