Trait impulsivity in Juvenile Myoclonic Epilepsy
Bibliographic record
Abstract
Abstract Objective Impulsivity is a multidimensional construct that can predispose to psychopathology. Meta‐analysis demonstrates an association between response impulsivity and Juvenile Myoclonic Epilepsy (JME), a common genetic generalized epilepsy. Here, we test the hypotheses that trait impulsivity is (i) elevated in JME compared to controls; (ii) moderated by specific seizure characteristics; and (iii) associated with psychiatric adverse effects of antiepileptic drugs (AEDs). Methods 322 participants with JME and 126 age and gender‐matched controls completed the Barratt's Impulsiveness Scale (BIS‐brief) alongside information on seizure history and AED use. We compared group BIS‐brief scores and assessed associations of JME BIS‐brief scores with seizure characteristics and AED adverse effects. Results The mean BIS‐brief score in JME was 18.1 ± 4.4 compared with 16.2 ± 4.1 in controls ( P = 0.0007). Elevated impulsivity was associated with male gender ( P = 0.027), frequent absence seizures ( P = 0.0004) and lack of morning predominance of myoclonus ( P = 0.008). High impulsivity significantly increased the odds of a psychiatric adverse event on levetiracetam ( P = 0.036), but not any other psychiatric or somatic adverse effects. Interpretation Trait impulsivity is elevated in JME and comparable to scores in personality and neurotic disorders. Increased seizure frequency and absence of circadian seizure pattern moderate BIS score, suggesting disruption of both cortico‐striatal and thalamocortical networks as a shared mechanism between seizures and impulsivity in JME. These findings warrant consideration of impulsivity as a distinct target of intervention, and as a stratifying factor for AED treatment in JME, and perhaps other types of epilepsy. The role of impulsivity in treatment adherence and psychosocial outcome requires further investigation.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".