Characteristics and Predictors of Fluctuating Attention-Deficit/Hyperactivity Disorder in the Multimodal Treatment of ADHD (MTA) Study
Bibliographic record
Abstract
Recent studies report a fluctuating course of attention-deficit/ hyperactivity disorder (ADHD) across development characterized by intermittent periods of remission and recurrence. In the Multimodal Treatment of ADHD (MTA) study, we investigated fluctuating ADHD including clinical expression over time, childhood predictors, and between- and within-person associations with factors hypothesized as relevant to remission and recurrence. 483), participating in the MTA adult follow-up were assessed 9 times from baseline (mean age = 8.46) to 16-year follow-up (mean age = 25.12). The fluctuating subgroup (63.8% of sample) was compared to other MTA subgroups on variables of interest over time. SD = 1.36) with a 6- to 7-symptom within-person difference between peaks and troughs. Remission periods typically first occurred in adolescence and were associated with higher environmental demands (both between- and within-person), particularly at younger ages. Compared to other groups, the fluctuating subgroup demonstrated moderate clinical severity. In contrast, the stable persistent group (10.8%) was specifically associated with early and lasting risk for mood disorders, substance use problems in adolescence/ young adulthood, low medication utilization, and poorer response to childhood treatment. Protective factors were detected in the recovery group (9.1%; very low parental psychopathology) and the partial remission group (15.6%; higher rates of comorbid anxiety). In the absence of specific risk or protective factors, individuals with ADHD demonstrated meaningful within-individual fluctuations across development. Clinicians should communicate this expectation and monitor fluctuations to trigger as-needed return to care. During remission periods, individuals with ADHD successfully manage increased demands and responsibilities. ClinicalTrials.gov identifier: NCT00000388.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".