Evidence, Interpretation, and Qualification From Multiple Reports of Long-Term Outcomes in the Multimodal Treatment Study of Children With ADHD (MTA)
Bibliographic record
Abstract
OBJECTIVE: To review the primary and secondary findings from the Multimodal Treatment study of ADHD (MTA) published over the past decade as three sets of articles. METHOD: In a two-part article-Part I: Executive Summary (without distracting details) and Part II: Supporting Details (with additional background and detail required by the complexity of the MTA)-we address confusion and controversy about the findings. RESULTS: We discuss the basic features of the gold standard used to produce scientific evidence, the randomized clinical trial, for which was used to contrast four treatment conditions: medication management alone (MedMgt), behavior therapy alone (Beh), the combination of these two (Comb), and a community comparison of treatment "as usual" (CC). For each of the three assessment points we review three areas that we believe are important for appreciation of the findings: definition of evidence from the MTA, interpretation of the serial presentations of findings at each assessment point with a different definition of long-term, and qualification of the interim conclusions about long-term effects of treatments for ADHD. CONCLUSION: We discuss the possible clinical relevance of the MTA and present some practical suggestions based on current knowledge and uncertainties facing families, clinicians, and investigators regarding the long-term use of stimulant medication and behavioral therapy in the treatment of children with 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 | 0.472 | 0.779 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.013 |
| Bibliometrics | 0.020 | 0.015 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.015 | 0.009 |
| Open science | 0.008 | 0.008 |
| Research integrity | 0.007 | 0.005 |
| 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".