Meditation Benefits and Drawbacks: Empirical Codebook and Implications for Teaching
Open accessAbstract
Meditation has become a cultural phenomenon, and modern scientific research on the topic has exploded. Thousands of scientific articles report various benefits of meditation including clinical, physiological and well-being outcomes. Despite these benefits, drop-out rates in mindfulness-based interventions remain a problem and little work has studied the drawbacks of meditation. Reports of adverse reactions to meditation have emerged and critical voices have begun advocating caution, rather than enthusiasm, for meditation training. Furthermore, the experiences of meditators outside interventions and conventional lab studies are not well understood. Here we develop an empirical codebook of and framework for meditation benefits and drawbacks (MBDs), discussing the actionable implications for meditation training in the real world. These data reveal the major drawbacks hindering real-world meditators, including several less intuitive drawbacks. We also report the major benefits of meditation and generate a structural framework from which they can be understood in parallel with drawbacks. We investigate whether meditation styles affect MBDs and report comparisons between current and former meditators. These results bring cogent structure to the variety of meditation outcomes laypeople experience. As the number of meditators continues to increase, we need such structures to inform how meditation is taught, ensuring ethically informed consent and optimizing practice-fit. Mixed-methods research such as this study allows a greater practical understanding of how meditation is experienced in situ. This work complements the literature on the clinical benefits and neurophysiological mechanisms of meditation and this framework will inform clinicians, researchers and meditation teachers as best practices are reviewed in the coming years.
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There is no reasonable doubt that meditation can cause challenging experiences.
“There is no reasonable doubt that meditation can cause challenging experiences.”
From Prevalence of meditation-related adverse effects in a population-based sample in the United States (2022) · cites this paper as Anderson et al., 2019
The prevalence of unpleasant meditation-related experiences found in this study is in line with rates found in previous studies using a similar open-ended question format, whereas studies using systematic monitoring found higher rates.
“Those numbers are in line with rates found in previous studies that used a similar open-ended question format,6,25–28 whereas studies using systematic monitoring of unpleasant experiences found higher rates.7,8”
From Prevalence, predictors and types of unpleasant and adverse effects of meditation in regular meditators: international cross-sectional study (2022) · cites this paper as [25]
Experiential challenges during mindfulness practice include affective demands such as cognitive effort and frustration, task demands introduced by the physical environment such as noisy surroundings and people, and negative emotional or psychological outcomes such as boredom, upsetting thoughts, and emotions.
“Anderson et al [10] recently summarized a range of experiential challenges that can arise during mindfulness practice. These include affective demands such as cognitive effort and frustration, task demands introduced by the physical environment (eg, noisy surroundings and people), and negative emotional or psychological outcomes, such as boredom, upsetting thoughts, and emotions.”
From Understanding How Virtual Reality Can Support Mindfulness Practice: Mixed Methods Study (2020) · cites this paper as [10]
Being engaged in the VE was beneficial in that it maintained interest across the practice, and the VE itself was neither overwhelming nor burdensome on concentration for most participants-a challenge often reported with conventional mindfulness practice.
“Being engaged in the VE was beneficial in that it maintained interest across the practice, and the VE itself was neither overwhelming nor burdensome on concentration for most participants—a challenge often reported with conventional mindfulness practice [10].”
From Understanding How Virtual Reality Can Support Mindfulness Practice: Mixed Methods Study (2020) · cites this paper as [10]
Demands introduced by the physical environment have been discussed in previous research as a prominent challenge in conventional meditation practice.
“Demands introduced by the physical environment have been discussed in previous research as a prominent challenge in conventional meditation practice [10]”
From Understanding How Virtual Reality Can Support Mindfulness Practice: Mixed Methods Study (2020) · cites this paper as [10]
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- Authors
- Anderson, T., Suresh, M., & Farb, N. A.
- Affiliations
- University of Toronto (CA)
- Corresponding author
- Anderson, Thomas
- Venue
- Journal of Cognitive Enhancement
- Published
- 2019-01-14
- Volume
- 3
- Issue
- 2
- Pages
- 207-220
- ISSN
- 2509-3290 (ISSN-L)
- 2509-3304
- OpenAlex
- W2910469383
- Semantic Scholar
- b49c5579e64816ae09f6afbc1ee20fb1aed3d4f0
- Cited by
- 55
- References
- 49
- Citations by year
- 2026: 1 · 2025: 14 · 2024: 11 · 2023: 5 · 2022: 7 · 2021: 7 · 2020: 3 · 2019: 5 · 2018: 2
- FWCI
- 6.43
- Type
- journal article
- Language
- en
- Open access
- green
- osf.io
- Licence
- Locations
- Journal of Cognitive Enhancement (publishedVersion)
- OSF Preprints (OSF Preprints) (submittedVersion, cc-by)
- Funders
- Social Sciences and Humanities Research Council of Canada
- Canadian Foundation for Innovation
- Topics
- Social Sciences › Psychology › Clinical Psychology › Mindfulness and Compassion Interventions
- Social Sciences › Health › Religion, Spirituality, and Psychology
- Social Sciences › Psychology › Social Psychology › Psychological Well-being and Life Satisfaction
- Keywords
- meditation, mindfulness-based interventions
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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