Mindfulness Training for Adults with Attention-Deficit/Hyperactivity Disorder: Implementation of Mindful Awareness Practices in a French-Speaking Attention-Deficit/Hyperactivity Disorder Unit
Bibliographic record
Abstract
Introduction: Mindfulness-based programs are a promising option for patients with attention-deficit/hyperactivity disorder (ADHD), who face attention, hyperactivity, and emotion dysregulation issues in their daily life. Objective: To examine the implementation and impact of specific mindfulness training for adults with ADHD in a French-speaking unit. Methods: Thirty-eight adults with ADHD were included in an 8-week Mindful Awareness Practices (MAPs) program. Patients were assessed for ADHD symptoms, anxiety, depression, and mindfulness skills, before (T1) and after (T2) the eight sessions, and then 2 months later (T3). Results: The patients adhered to the program as the majority of them completed it. A significant decrease in ADHD, depression, and anxiety symptoms was found between T1 and T2. Regarding mindfulness skills, a significant increase was observed between T1 and T2 in Observing, Describing and Nonreactivity to inner experience cores, but not Acting with awareness and Nonjudging of inner experience scores. There was no significant change between T2 and T3. Conclusion: The MAPs program was successfully implemented and showed promising effects on ADHD symptomatology and related symptoms.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".