Mindfulness-based programs and school adjustment: A systematic review and meta-analysis
Bibliographic record
Abstract
Mindfulness-based programs (MBPs) are increasingly used in educational institutions to enhance students' mental health and resilience. However, reviews of the literature suggest this use may have outpaced the evidence base and further research is needed to better understand the mechanisms underlying these programs' effectiveness and which outcomes are being affected. The purpose of this meta-analysis was to investigate the strength of MBPs' effects on school adjustment and mindfulness outcomes while also considering the potential influence of study and program characteristics, including the role of comparison groups, students' educational level, the type of program being used, and the facilitator's training and previous mindfulness experience. Following a systematic review of five databases, 46 studies using a randomized controlled design with students from preschool to undergraduate levels were selected. At post-program, the effect of MBPs compared to control groups was (a) small for overall school adjustment outcomes, academic performance, and impulsivity; (b) small to moderate for attention; and (c) moderate for mindfulness. No differences emerged for interpersonal skills, school functioning, or student behaviour. The effects of MBPs on overall school adjustment and mindfulness differed based on students' educational level and the type of program being delivered. Moreover, only MBPs delivered by outside facilitators with previous experience of mindfulness had significant effects on either school adjustment or mindfulness. This meta-analysis provides promising evidence of the effectiveness of MBPs in educational contexts to improve students' school adjustment outcomes beyond typically assessed psychological benefits, even when using randomized controlled designs.
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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 | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.021 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".