A Mindfulness-Based Intervention Pilot Feasibility Study for Elementary School Students With Severe Learning Difficulties: Effects on Internalized and Externalized Symptoms From an Emotional Regulation Perspective
Bibliographic record
Abstract
Objective. Students with severe learning disabilities often show signs of anxiety, depression, and problem behaviors such as inattention and conduct problems. Mindfulness-based interventions (MBIs) in school settings constitute a promising option to alleviate these co-occurring symptoms. This pilot study aimed to evaluate the impact of an MBI on symptoms and behaviors of elementary school students with severe learning disabilities. Method. A one-group pretest-posttest design was used. The sample comprised 14 students aged 9 to 12 years with special education needs. Both student-report and teacher-report of the Behavior Assessment System for Children, Second Edition were used. Results. Repeated-measures analyses of variance revealed a significant impact of the MBI on symptoms and behaviors such as anxiety, depression, inattention, aggression, and conduct problems. Effect sizes for all variables were considered large (partial η 2 = .31-.61). Conclusion. These preliminary results indicate that MBIs can reduce the frequency of symptoms and problem behaviors often found in children with learning disabilities in elementary schools. Further multiple baseline experimental trials with a long-term follow-up are warranted to establish more robustly the effect of MBIs for children with learning disabilities.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".