Unpacking the Black Box of Mindfulness: The Psychological Mechanisms of Mindfulness
Bibliographic record
Abstract
Whereas some people consider mindfulness a tool that allows individuals to step fully into their lives and approach their daily challenges more successfully, some consider mindfulness a tool that simply helps individuals not to be overly reactive to and overwhelmed by their daily experiences, and others even criticize it as being a practice that promotes passivity and numbness towards experiences. These contradictory views are also reflected in scholarly research on mindfulness, as there are theoretical claims asserting that mindfulness allows individuals to better respond to life situations whereas the definition of mindfulness characterizes it as being a neutral, non-evaluative state of mind. This raises the question of whether mindfulness makes individuals more active and agentic or more passive and neutral instead. To unravel the seemingly paradoxical effects of mindfulness, we systematically review empirical research on mindfulness to identify the psychological mechanisms of mindfulness. Then, based on the findings, we develop an organizing framework that identifies the major categories of mechanisms, and we put forward an integrative theoretical model to explain the psychological processes generated by mindfulness. Specifically, we posit that the mechanisms of mindfulness occur in a sequence of three overarching processes that unfold over time: dereification producing non-evaluative experiences in the very short run; reorientation producing positive modulated experiences in the short run; and internalization producing durable changes in one’s self-determined behavior in the long run. Finally, we explain how the model can inform future research.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.026 |
| Scholarly communication | 0.007 | 0.012 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".