| Literature DB >> 35386478 |
Kirti Sharma1, A Gabriella Wernicke2, Husneara Rahman3, Louis Potters2, Gopesh Sharma4, Bhupesh Parashar2.
Abstract
Objective The goal of this study is to compare the effectiveness of three different meditation techniques (two internal focus techniques and one external focus technique) using a low-cost portable electroencephalography (EEG) device, namely, MUSE, for an objective comparison. Methods This is an IRB-approved retrospective study. All participants in the study were healthy adults. Each study participant (n = 34) was instructed to participate in three meditation sessions: mantra (internal), breath (internal), and external point. The MUSE brain-sensing headband (EEG) was used to document the "total time spent in the calm state" and the "total time spent in the calm or neutral state" (outcomes) in each three-minute session to conduct separate analyses for the meditation type. Separate generalized linear models (GLM) with unstructured covariance structures were used to examine the association between each outcome and the explanatory variable (meditation type). For all models, if there was a significant association between the outcome and the explanatory variable, pairwise comparisons were carried out using the Tukey-Kramer correction. Results The median time (in seconds) spent in the calm state while practicing mantra meditation was 131.5 (IQR: 94-168), while practicing breath meditation was 150 (IQR: 113-164), and while practicing external-point meditation was 100 (IQR: 62-126). Upon analysis, there was a significant association between the meditation type and the time spent in the calm state (p-value = 0.0006). Conclusion This is the first study comparing "internal" versus "external" meditation techniques using an objective measure. Our study shows the breath and mantra technique as superior to the external-point technique as regards time spent in the calm state. Additional research is needed using a combination of "EEG" and patient-reported surveys to compare various meditative practices. The findings from this study can help incorporate specific meditation practices in future mindfulness-based studies that are focused on healthcare settings and on impacting clinical outcomes, such as survival or disease outcomes.Entities:
Keywords: breath; focused attention meditation; mantra; meditation; mindfulness; muse
Year: 2022 PMID: 35386478 PMCID: PMC8967094 DOI: 10.7759/cureus.23589
Source DB: PubMed Journal: Cureus ISSN: 2168-8184
Figure 1MUSE brain-sensing EEG headband
Participant demographics
| Participant characteristics | N (%) |
| Gender | |
| Male | 12 (35.29) |
| Female | 22 (64.71) |
| Age groups (years) | |
| 18-28 | 5 (14.71) |
| 29-38 | 8 (23.53) |
| 39-48 | 10 (29.41) |
| 49-58 | 7 (20.59) |
| 59-68 | 4 (11.76) |
| Ethnicity | |
| Asian | 22 (64.71) |
| Caucasian | 12 (35.29) |
| Level of practice (participant reported) | |
| Beginner | 13 (38.24) |
| Intermediate | 14 (41.18) |
| Advanced | 7 (30.59) |
Figure 2Time spent (seconds) in the calm state by meditation type
Figure 3Time spent (seconds) in the calm or neutral state by meditation type
Time spent in the calm or neutral state and level of practice
p-value = 0.030
| Level of practice | Time spent in the neutral or calm state (mean in seconds) | Time spent in the neutral or calm state (lower level in seconds) | Time spent in the neutral or calm state (upper level in seconds) |
| Beginner | 178.64 | 177.56 | 179.72 |
| Intermediate | 174.31 | 171.56 | 177.07 |
| Advanced | 172.95 | 164.37 | 181.54 |