Sequencing Stimulant Medication and Behavioral Parent Training in Multiplex ADHD Families
Bibliographic record
Abstract
To examine the effects of treatment sequence of parent stimulant medication (MED) and behavioral parent training (BPT) on child, maternal, and parenting outcomes among multiplex attention-deficit/hyperactivity disorder (ADHD) families using a pilot Sequential Multiple Assignment Randomized Trial (SMART) design. diagnostic criteria for ADHD, and their children had to have elevated ADHD symptoms. Thirty-five mother-child dyads were randomized at baseline and again at week 8. The resulting 4 sequences were MED MED, BPT-BPT, MED-BPT, and BPT MED. Outcomes included child ADHD symptoms, child impairment, maternal ADHD symptoms, and parenting at week 16. Data were collected from September 2012 to December 2016. The BPT-MED sequence demonstrated the most favorable outcomes for child ADHD symptoms (effect size= -0.36) and child impairment (effect sizes -0.33 to -0.51). All 3 sequences involving medication demonstrated similar impact on maternal ADHD symptoms (effect sizes ranged from -0.32 to -0.48). The BPT-MED (effect sizes ranged from 0.30 to 0.35) had the most favorable effects on positive parenting outcomes. For negative parenting outcomes, BPT-MED (effect size= -0.50 for self report) and BPT-BPT (effect size= -0.08 for observation) had the most favorable outcomes. Overall, based on this pilot SMART, combination treatment may be helpful for most multiplex ADHD families, and sequencing treatments with BPT first followed by stimulant medication for the mother may be the most promising approach to improve child ADHD symptoms, impairment, and parenting. These results require replication with a fully powered SMART design. We conclude with considerations for implementing a model of care for multiplex ADHD families. ClinicalTrials.gov identifier: NCT01816074.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".