Perceptual and response-dependent profiles of attention in children with ADHD.
Bibliographic record
Abstract
OBJECTIVE: Attention-deficit hyperactivity disorder (ADHD) is a complex developmental neuropsychiatric disorder, characterized by inattentiveness, impulsivity, and hyperactivity. Recent literature suggests a potential core deficit underlying these behaviors may involve inefficient processing when contextual stimulation is low. In order to specify this inefficiency, the aim of the present study was to disentangle perceptual and response-based deficits of attention by supplementing classic reaction time (RT) measures with an accuracy-only test. Moreover, it was explored whether ADHD symptom severity was systematically related to perceptual and response-based processes. METHOD: We applied an RT-independent paradigm (Bundesen, 1990) and a sustained attention task (Dockree et al., 2006) to test visual attention in 24 recently diagnosed, medication-naïve children with ADHD, 14 clinical controls with pervasive developmental disorder, and 57 healthy controls. Outcome measures included perceptual processing speed, capacity of visual short-term memory, and errors of commission and omission. RESULTS: Children with ADHD processed information abnormally slow (d = 0.92), and performed poorly on RT variability and response stability (d's ranging from 0.60 to 1.08). In the ADHD group only, slowed visual processing speed was significantly related to response lapses (omission errors). This correlation was not explained by behavioral ratings of ADHD severity. CONCLUSIONS: Based on combined assessment of perceptual and response-dependent variables of attention, the present study demonstrates a specific cognitive profile in children with ADHD. This profile distinguishes the disorder at a basic level of attentional functioning, and may define subgroups of children with ADHD in a way that is more sensitive than clinical rating scales. (PsycINFO Database Record
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".