Impact of a Playful Relaxation Intervention on Children’s Well-Being: A Mixed-Methods Study in Primary School in Portugal
Bibliographic record
Abstract
Background/Objectives: Considering that current research highlights the role of well-being and play in children's development and learning, and that the few publications reflecting research into relaxation methods suggest that these create conditions for well-being, the main objective of this research was to evaluate the effects of a playful intervention based on relaxation methods on the wellbeing of children in the 1st cycle of schooling. Methods: It is a mixed study, using quantitative and qualitative methods, with a quasi-experimental design, with an intervention group (a total of 24 sessions, based on Boski and Choque's relaxation proposals for children) and a control group, with pre- and post-intervention assessment in both groups. Semi-structured interviews were conducted with teachers and focus group techniques were used with children. Sixty-three children participated in this study, with an average age of 8.79 years (M=8.79; SD= 0.676), 55.6% (35) of whom were female and 44.4% (28) male. Results: The results of the study indicate that the children developed passive limb relaxation and proprioceptive function, without altering their life satisfaction or aspects of emotional development. However, according to the children and teachers, the intervention developed positive emotions, bringing benefits to the classroom. Conclusions: This research contributes to the understanding of the effects, possibilities, and potential of relaxation for children in school settings.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".