Dataset Information

The State- and Trait-Level Effects and Candidate Mechanisms of Four Mindfulness-Based Cognitive Therapy (MBCT) Practices: Two Exploratory Studies.

ABSTRACT:

Objectives

The primary aim was to explore state- and trait-level effects and candidate mechanisms of four Mindfulness-Based Cognitive Therapy (MBCT) practices.

Method

One hundred sixty adults self-selected from the general population were randomized to one of four mindfulness practices: body scan, mindful movement, breath and body, and befriending. Study 1 explored state-level self-compassion, mindfulness, decentering (mechanisms), and pleasantness of thoughts, emotions, and body sensations at multiple time points using two single mindfulness sessions. Study 2 explored trait-level self-compassion, mindfulness, decentering, interoceptive awareness, attentional control (mechanisms), anxiety, depression, and psychological quality of life pre-post 2 weeks of daily practice.

Results

In study 1, state-level effects were demonstrated in all candidate mechanisms and outcomes within the whole sample across time points (d = 0.27 to 0.86), except for state decentering. After controlling for pre-scores and additional covariates, no between-group effects were found (p = 0.050 to 0.973). In study 2, trait-level effects were demonstrated in psychological quality of life and most candidate mechanisms within the whole sample (d = 0.26 to 0.64) but no between-group effects were found (p = 0.080 to 0.805). Within the whole sample, after controlling for pre-scores, changes in mindfulness, self-compassion, decentering, and interoceptive awareness (i.e. body listening) were associated with improvements in psychological quality of life (r = 0.23 to 0.40) and self-led mindfulness practice (r = 0.18 to 0.23).

Conclusions

Future research should test the generated hypotheses using well-designed, adequately powered, and theory-driven studies that address universal and specific mechanisms in different populations and contexts.

Pre-registration

This study is not pre-registered.

Supplementary information

The online version contains supplementary material available at 10.1007/s12671-023-02193-6.

SUBMITTER: Maloney S

PROVIDER: S-EPMC10545571 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The State- and Trait-Level Effects and Candidate Mechanisms of Four Mindfulness-Based Cognitive Therapy (MBCT) Practices: Two Exploratory Studies.

Maloney Shannon S Surawy Christina C Martin Maryanne M Montero-Marin Jesus J Kuyken Willem W

Mindfulness 20230824 9

<h4>Objectives</h4>The primary aim was to explore state- and trait-level effects and candidate mechanisms of four Mindfulness-Based Cognitive Therapy (MBCT) practices.<h4>Method</h4>One hundred sixty adults self-selected from the general population were randomized to one of four mindfulness practices: body scan, mindful movement, breath and body, and befriending. Study 1 explored state-level self-compassion, mindfulness, decentering (mechanisms), and pleasantness of thoughts, emotions, and body ...[more]

PMID: 37795338

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Project description:Mindfulness has been described as an orienting of attention to the present moment, with openness and compassion. Individuals displaying high trait mindfulness exhibit this tendency as a more permanent personality attribute. Given the numerous physical and mental health benefits associated with mindfulness, there is a great interest in understanding the neural substrates of this trait. The purpose of the current research was to examine how individual differences in trait mindfulness associated with functional connectivity in five resting-state networks related to cognition and attention: the default mode network (DMN), the salience network (SN), the central executive network (CEN), and the dorsal and ventral attention networks (DAN and VAN). Twenty-eight undergraduate participants completed the Five-Facet Mindfulness Questionnaire (FFMQ), a self-report measure of trait mindfulness which also provides scores on five of its sub-categories (Observing, Describing, Acting with Awareness, Non-judging of Inner Experience, and Non-reactivity to Inner Experience). Participants then underwent a structural MRI scan and a 7-min resting state functional MRI scan. Resting-state data were analyzed using independent-component analyses. An analysis of covariance (ANCOVA) was performed to determine the relationship between each resting state network and each FFMQ score. These analyses indicated that: (1) trait mindfulness and its facets showed increased functional connectivity with neural regions related to attentional control, interoception, and executive function; and (2) trait mindfulness and its facets showed decreased functional connectivity with neural regions related to self-referential processing and mind wandering. These patterns of functional connectivity are consistent with some of the benefits of mindfulness-enhanced attention, self-regulation, and focus on present experience. This study provides support for the notion that non-judgmental attention to the present moment facilitates the integration of regions in neural networks that are related to cognition, attention, and sensation.

Project description:IntroductionTrait mindfulness refers to one's disposition or tendency to pay attention to their experiences in the present moment, in a non-judgmental and accepting way. Trait mindfulness has been robustly associated with positive mental health outcomes, but its neural underpinnings are poorly understood. Prior resting-state fMRI studies have associated trait mindfulness with within- and between-network connectivity of the default-mode (DMN), fronto-parietal (FPN), and salience networks. However, it is unclear how generalizable the findings are, how they relate to different components of trait mindfulness, and how other networks and brain areas may be involved.MethodsTo address these gaps, we conducted the largest resting-state fMRI study of trait mindfulness to-date, consisting of a pre-registered connectome predictive modeling analysis in 367 adults across three samples collected at different sites.ResultsIn the model-training dataset, we did not find connections that predicted overall trait mindfulness, but we identified neural models of two mindfulness subscales, Acting with Awareness and Non-judging. Models included both positive networks (sets of pairwise connections that positively predicted mindfulness with increasing connectivity) and negative networks, which showed the inverse relationship. The Acting with Awareness and Non-judging positive network models showed distinct network representations involving FPN and DMN, respectively. The negative network models, which overlapped significantly across subscales, involved connections across the whole brain with prominent involvement of somatomotor, visual and DMN networks. Only the negative networks generalized to predict subscale scores out-of-sample, and not across both test datasets. Predictions from both models were also negatively correlated with predictions from a well-established mind-wandering connectome model.ConclusionsWe present preliminary neural evidence for a generalizable connectivity models of trait mindfulness based on specific affective and cognitive facets. However, the incomplete generalization of the models across all sites and scanners, limited stability of the models, as well as the substantial overlap between the models, underscores the difficulty of finding robust brain markers of mindfulness facets.

Dataset Information

The State- and Trait-Level Effects and Candidate Mechanisms of Four Mindfulness-Based Cognitive Therapy (MBCT) Practices: Two Exploratory Studies.

Objectives

Method

Results

Conclusions

Pre-registration

Supplementary information

Publications

The State- and Trait-Level Effects and Candidate Mechanisms of Four Mindfulness-Based Cognitive Therapy (MBCT) Practices: Two Exploratory Studies.

Similar Datasets

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