Association of Psychopharmacological Medication Preference with Autistic Traits and Emotion Regulation in ADHD
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: This study intends to evaluate the relationship between medication switching and autistic traits, emotion dysregulation, and methylphenidate side effects in children with attention deficit hyperactivity disorder (ADHD). Methods: Children with ADHD, ages 9-18, treated with methylphenidate (MTP) (n = 23), and switched to atomoxetine (ATX) (n = 20) were included. All participants were interviewed with K-SADS-PL to confirm ADHD diagnosis and exclude comorbid psychiatric disorders. The participants then completed Difficulty in Emotion Regulation Scale (DERS) and Autism-Spectrum Quotient (AQ) and their parents completed Autism Spectrum Screening Questionnaire (ASSQ) and Barkley Stimulant Side Effect Rating Scale(BSSERS). Results: The MTP group scored higher than the ATX group in ASSQ, AQ, and the lack of emotional clarity subscale of DERS, while the ATX group had higher scores in the emotional non-acceptance subscale of DERS. No differences were found between the MTP and ATX groups in methylphenidate side-effect severity. Multiple regression analyses revealed that non-acceptance of emotions predicted the switch to ATX while lack of emotional clarity predicted the maintenance of MTP therapy, rather than autistic traits. Conclusions: This study highlights emotion regulation difficulties and how different emotional profiles may influence medication selection in children with ADHD.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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 it