The Interaction of ADHD-Traits and Trait Anxiety on Inhibitory Control
Bibliographic record
Abstract
ADHD and anxiety frequently occur together; however, the cognitive outcomes of co-morbid anxiety and ADHD are not straightforward. A potential explanation for conflicting results in the literature may be that different core ADHD symptoms show different interactions with anxiety depending on the task processing demands. To address this question, we investigated whether different ADHD traits are related to different inhibitory outcomes, contingent upon the level of trait anxiety. The sample consists of 60 non-clinical university students (X ̅age= 20.5, 53% male). Conners’ Adult ADHD Rating Scale (CAARS-SL) and State Trait Anxiety Inventory (STAI) were used to measure ADHD-traits and anxiety, respectively. The participants completed a visual Go/NoGo task with and without distractor conditions while continuous EEG was recorded. Inhibitory control was operationalized as the frontocentral N2 maximum peak amplitude elicited in response inhibition (NoGo/No Distractor), cognitive inhibition (Go/Distractor), dual inhibition (NoGo/Distractor), and control (Go/No Distractor) conditions. We analyzed the moderating effect of trait anxiety on the prediction of inhibitory control by ADHD scores for each Go/NoGo condition with the varying inhibition demands. Results showed that trait anxiety moderated the effects of total ADHD and hyperactivity-impulsivity scores, but only in the response inhibition condition (NoGo/No Distractor). Additionally, inattentiveness was related to attenuated N2 amplitudes in the cognitive inhibition condition (Go/Distractor). These findings suggest that depending on the inhibitory demands of the task, unique cognitive outcomes may occur when different ADHD traits coexist with anxiety.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".