Does Mindfulness Meditation Improve Anxiety and Mood Symptoms? A Review of the Controlled Research
Bibliographic record
Abstract
OBJECTIVE: To review the impact of mindfulness-based stress reduction (MBSR) on symptoms of anxiety and depression in a range of clinical populations. METHOD: Our review included any study that was published in a peer-reviewed journal, used a control group, and reported outcomes related to changes in depression and anxiety. We extracted the following key variables from each of the 15 studies identified: anxiety or depression outcomes after the MBSR program, measurement of compliance with MBSR instructions, type of control group included, type of clinical population studied, and length of follow-up. We also summarized modifications to the MBSR program. RESULTS: Measures of depression and anxiety were included as outcome variables for a broad range of medical and emotional disorders. Evidence for a beneficial effect of MBSR on depression and anxiety was equivocal. When active control groups were used, MBSR did not show an effect on depression and anxiety. Adherence to the MBSR program was infrequently assessed. Where it was assessed, the relation between practising mindfulness and changes in depression and anxiety was equivocal. CONCLUSIONS: MBSR does not have a reliable effect on depression and anxiety.
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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 | 0.007 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".