A Person-Centered Approach in Investigating a Mindfulness-Based Program for Adolescents with Autism Spectrum Disorder
Bibliographic record
Abstract
Abstract Objectives Adolescents with autism often experience comorbid internalizing disorders such as anxiety disorders or depression but the available evidence-based treatments to support the mental health of adolescents with autism are limited. The aim of this study was to investigate if and how MYmind, a mindfulness-based program (MBP) for youth with autism, could benefit adolescents with comorbid internalizing disorder(s). Methods A person-centered approach with a multiple baseline design was used to investigate the effects of MYmind. Five adolescents with autism and an internalizing disorder took part in the 9-week MYmind program. The adolescents and their parents completed a daily questionnaire on their personal goals during a baseline phase, the intervention, a 2-month follow-up phase, and a 1-year follow-up phase. We analyzed the effects on their personal goals using visual inspection and statistical analysis for single-case designs. Also, we investigated potential processes of change by analyzing how changes were related over time. Results Findings indicated that most, but not all, adolescents benefitted from the MBP. Four out of five adolescents showed medium-sized improvement in some of their personal goals. However, one adolescent reported a deterioration during the intervention and 2-month follow-up phase. Decreased worry preceded behavioral improvements in two adolescents, whereas other potential mechanisms of change showed inconclusive results. Conclusion The findings indicated that most of the adolescents with autism and a comorbid internalizing disorder partially benefitted from the MBP.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".