Mindfulness-Based Cognitive Behavioral Interventions to Enhance Academic Buoyancy: A Meta-Analytic Study
Bibliographic record
Abstract
This study explores the effectiveness of mindfulness-based cognitive behavioral interventions in developing academic buoyancy among students, defined as their capacity to overcome daily academic challenges such as stress, time pressure, and minor failures. Using a meta-analytic approach, the research synthesizes findings from 15 independent studies involving 4,509 participants across diverse educational contexts, including the United States, Canada, Iran, and the United Kingdom. The random effects model revealed a significant positive correlation between mindfulness interventions and academic buoyancy, with a high effect size. The findings underscore the potential of mindfulness integrated with cognitive behavioral therapy to enhance students' resilience by reducing stress and improving executive functions such as emotional regulation, attention, and decision-making. Despite its demonstrated effectiveness, heterogeneity in study designs, intervention durations, and measurement tools suggests the need for further research to refine and standardize these interventions. This study provides evidence-based insights for educators and counselors aiming to integrate mindfulness practices into academic settings, contributing to the broader discourse on mental health and educational resilience.
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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 | 0.011 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.013 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".