Objective: We sought to address a growing debate regarding the adverse and salutary impact of unusual, extraordinary or intense subjective experiences during meditation-based interventions. To do so, we empirically characterized such peak experiences during an intensive meditation intervention and their impact postintervention.
Method: We conducted a preregistered prospective intervention study among 96 adults who registered for 6-day insight (Vipassana) mindfulness meditation retreats and 47 matched controls. Controls were selected from a pool of 543 people recruited from the same community of meditators as retreat participants and systematically matched to retreat participants on age and lifetime meditation experience. Measures included the novel Peak Meditative Experience Scale and the Impact of PMES.
Results: Seventeen peak experiences that were primarily pleasant (e.g., deep and unusual peace, aha! Moment) occurred more frequently among retreat participants than among matched controls in daily living (ps < .05; mean ϕ = .33). In contrast, 14 peak experiences that were mostly unpleasant (e.g., flashbacks, overwhelming sadness) occurred at similar rates in both groups (ps > .05). At 2-week follow-up, the perceived impact of all pleasant and most unpleasant peak experiences was more salutary than adverse (ps ≤ .015; M Cohen's = 1.61).
Conclusions: Peak experiences that resulted from meditation retreats were primarily pleasant and had a large salutary impact postretreat. Inconsistent with conclusions from uncontrolled retrospective studies, findings document that intensive insight mindfulness meditation training in retreats may not contribute to unpleasant peak experiences and even when they occurred their impact was typically more salutary than adverse. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
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Front Psychol
December 2024
Departent of Learning, Data-Analytics and Technology, Faculty of Behavioural, Management and Social Sciences, University of Twente, Enschede, Netherlands.
Learning experiences are intertwined with emotions, which in turn have a significant effect on learning outcomes. Therefore, digital learning environments can benefit from taking the emotional state of the learner into account. To do so, the first step is real-time emotion detection which is made possible by sensors that can continuously collect physiological and eye-tracking data.
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Department of Anesthesiology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand. Electronic address:
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Sci Rep
December 2024
School of Ecology, Hainan University, Haikou, 570228, China.
Climate change and human activities are the primary drivers influencing changes in runoff dynamics. However, current understanding of future hydrological processes under scenarios of gradual climate change and escalating human activities remains uncertain, particularly in tropical regions affected by deforestation. Based on this, we employed the SWAT model coupled with the near future (2021-2040) and middle future (2041-2060) global climate models (GCMs) under four shared socioeconomic pathways (SSP1-2.
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Unidad de Fisiología del Ejercicio, Centro de Innovación, Clínica MEDS, Santiago 7550615, Chile.
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