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A Meta-Regression of psychosocial factors associated with sleep outcomes in mindfulness-based intervention trials.

Nathaniel R Choukas, Emily C Woodworth, Heena R Manglani, Jonathan Greenberg, Ryan A Mace

Behavioral Sleep Medicine 2025 DOI: 10.1080/15402002.2024.2401457 (opens in new tab)

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AI-extracted from the abstract
Characteristics Meta-regression Randomized Longitudinal Peer reviewed
Population Healthy and clinical adult populations
Intervention Mindfulness-based interventions
Topics Meditation
Citations 2
Key points Mindfulness-based interventions significantly reduce sleep disturbance, and these reductions are associated with decreases in stress and depression.

Abstract

In this meta-regression, we aimed to explore associations between changes in psychosocial factors and changes in sleep disturbance during mindfulness-based interventions (MBIs). We also investigated participant-specific and methodological factors associated with sleep disturbance during MBIs. We utilized data from a published meta-analysis of 40 randomized controlled trials of MBIs (published from inception to 2020) with a sleep disturbance outcome measure in healthy and clinical adult populations. We conducted meta-regressions to test associations between sleep improvements following MBIs and psychosocial factors, as well as demographic and methodological factors. MBIs were associated with significant reductions in sleep disturbance (SMD = -0.523; 95% CI = -0.678 to -0.368) and psychosocial factors (SMD = -0.213 - -0.894). Reductions in sleep disturbance were associated with reductions in stress (r = 0.74, p = .02) and depression (r = 0.90, p < .001). MBIs improve sleep disturbance across a wide range of healthy and clinical populations. Stress and depression may be important psychosocial factors associated with sleep disturbance. Future RCTs should include measures of additional factors and should investigate longitudinal associations between psychosocial, demographic, and methodological factors with changes in sleep disturbance to test mechanisms and to identify "active ingredients" of MBIs.

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