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Meditation, Absorption, Transcendent Experience, and Affect: Tying It All Together Via the Consciousness State Space (CSS) Model
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- 자료유형학술지논문
- 저자명Berkovich-Ohana, A.,Glicksohn, J.
- 학회/출판사/기관명Springer Science and Business Media
- 출판년도2017
- 언어영어
- 학술지명/학위논문주기Mindfulness
- 발행사항Vol.8No.1[2017]_x000D_
- ISBN/ISSN1868-8527
- 소개/요약In this paper, we relate meditation practice to participant trait absorption, affect, and transcendent experience. The motivation for this analysis stems from a new neurophenomenological model of consciousness which we recently published, named the consciousness state space. Here, we compare two distinct forms of meditation: mindfulness and transcendental meditation, as well as two different levels of expertise within the mindfulness group. Participants comprised 64 mindfulness practitioners, 18 transcendental meditation practitioners, and 59 healthy controls, who had no prior meditation experience. We further split our mindfulness participants into two groups, using a cutoff point of 2000 h of accumulated experience. We tested three predictions. The first prediction was that contemplative practices should result in increased first-order awareness as a trait, or trait absorption. Our findings revealed that meditators (in general) scored higher on trait absorption than comparable controls, with no difference between meditators from the two traditions. A second prediction was that contemplative practices should result in a reduced sense of regular (narrative) self; hence, transcendent experience should be enhanced for long-term practitioners of meditation. Our findings show that meditators (in general) score higher on the Mystical Scale than comparable controls, with no difference between meditators from the two traditions. We further predicted that contemplative practices should result in lower positive and negative valence, measured by Positive Affect and Negative Affect Schedule (PANAS) scores on both positive and negative affect scales, as a trait, but this hypothesis was only partly supported by the data.
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