Maternal personality traits moderate treatment response in the Multimodal Treatment Study of attention-deficit/hyperactivity disorder
Bibliographic record
Abstract
Some mothers of children with attention-deficit/hyperactivity disorder (ADHD) present with maladaptive personality profiles (high neuroticism, low conscientiousness). The moderating effect of maternal personality traits on treatment outcomes for childhood ADHD has not been examined. We evaluate whether maternal neuroticism and conscientiousness moderated response in the Multimodal Treatment Study of Children with ADHD. This is one of the first studies of this type. In a randomized controlled trial (RCT), 579 children aged 7-10 (M = 8.5); 19.7% female; 60.8% White with combined-type ADHD were randomly assigned to systematic medication management (MedMgt) alone, comprehensive multicomponent behavioral treatment (Beh), their combination (Comb), or community comparison treatment-as-usual (CC). Latent class analysis and linear mixed effects models included 437 children whose biological mothers completed the NEO Five-Factor Inventory at baseline. A 3-class solution demonstrated best fit for the NEO: MN&MC = moderate neuroticism and conscientiousness (n = 284); HN&LC = high neuroticism, low conscientiousness (n = 83); LN&HC = low neuroticism, high conscientiousness (n = 70). Per parent-reported symptoms, children of mothers with HN&LC, but not LN&HC, had a significantly better response to Beh than to CC; children of mothers with MN&MC and LN&HC, but not HN&LC, responded better to Comb&MedMgt than to Beh&CC. Per teacher-reported symptoms, children of mothers with HN&LC, but not LN&HC, responded significantly better to Comb than to MedMgt. Children of mothers with high neuroticism and low conscientiousness benefited more from behavioral treatments (Beh vs. CC; Comb vs. MedMgt) than other children. Evaluation of maternal personality may aid in treatment selection for children with ADHD, though additional research on this topic is needed.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".