Are There Resilient Children with ADHD?
Bibliographic record
Abstract
OBJECTIVE: The adverse outcomes associated with ADHD are well known, but less is known about the minority of children with ADHD who may be flourishing despite this neurodevelopmental risk. The present multi-informant study is an initial step in this direction with the basic but unanswered question: METHOD: Reliable change analysis of the BASC-3 Resiliency subscale for a clinically evaluated sample of 206 children with and without ADHD (ages 8-13; 81 girls; 66.5% White/Non-Hispanic). RESULTS: Most children with ADHD are perceived by their parents and teachers as resilient (52.8%-59.2%), with rates that did not differ from the comorbidity-matched Non-ADHD sample. CONCLUSION: Exploratory analyses highlighted the importance of identifying factors that promote resilience for children with ADHD specifically, such that some child characteristics were promotive (associated with resilience for both groups), some were protective (associated with resilience only for children with ADHD), and some were beneficial only for children without ADHD.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".