Effects of a brief online mindfulness intervention on cognition and affect in university students: A randomized longitudinal design
Bibliographic record
Abstract
Dispositional mindfulness and mindfulness-based interventions (MBIs) have been extensively linked with improved cognition, affect, and wellbeing. Variability in nature and method of MBIs and mindfulness practice necessitate a consistent standard for research and applied purposes. Moreover, traditional MBIs are lengthy and resource intensive. Brief and online MBIs are effective, representing a bridge into more extensive practice – but questions of mindfulness-specific effects and methodological variety linger. The present experiment used a randomized longitudinal design to assess effects of a 31-day, 15-minute daily mindfulness program on a battery of cognitive, affective, and individual difference measures in a sample of university students. Results indicated that, over the course of the study, the MBI group found their intervention less challenging, more enjoyable, more relaxing, and more useful compared to the podcast control group. MBI subjects also increased in state and trait mindfulness following the intervention relative to the podcast group. However, both groups showed comparable improvements in cognition and affect. Taken together, the results support prior work suggesting benefits from brief online mindfulness training – however, they also suggest more work is needed to make strong claims about mindfulness-specific far-transfer effects.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".