Mindful awareness and resilience skills for adolescents (MARS-A): a mixed-methods study of a mindfulness-based intervention for a heterogeneous adolescent clinical population
Bibliographic record
Abstract
OBJECTIVES: Mindful Awareness and Resilience Skills for Adolescents (MARS-A) is a mindfulness-based intervention adapted for the adolescent population. While previous studies have explored the benefits of MARS-A in various single-diagnosis populations, the aim of this study was to assess MARS-A for a heterogenous clinical adolescent population with mental health and/or chronic diagnoses, focusing on the underlying suffering present in all these conditions rather than its effects on a single diagnosis itself. METHODS: Qualitative data was collected through interviews to understand post-intervention participant perspectives and experiences. Quantitative data was collected through measures to investigate preliminary secondary outcomes. RESULTS: After participating in MARS-A, participants reported qualitative benefits in enhanced well-being, including coping with difficult emotions and managing sleep and/or pain. Quantitative results showed a reduction in functional disability, psychological distress, perceived stress, and depressive symptoms; increase in positive affect; and benefit in coping with pain and chronic conditions. CONCLUSIONS: MARS-A shows great potential in a heterogeneous clinical adolescent population.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".