A Double Dissociation Between Inattentive and Impulsive Traits, on Tasks of Visual Processing and Emotion Regulation
Bibliographic record
Abstract
OBJECTIVE: To dissociate between inattentive and impulsive traits common in attention deficit hyperactivity disorder (ADHD) using a non-dichotomous measurment of these traits. METHOD: 120 university students who completed the Conner's adult ADHD rating scales (CAARS) were also tested on the Microgenesis task which requires visual attention and on the Cyber Cruiser task which requires emotion regulation. RESULTS: Results show that a measure of inattention was specifically related to a measure of effortful visual processing condition. In addition, a measure of impulsivity was specifically related to the tendency to fail in refueling one's car on time, although this relation was opposite to the predicted direction. Furthermore, by using exploratory and confirmatory factor analyses, the CAARS' factor structure was confirmed to be relevant to an Israeli population. CONCLUSION: The current experiment supports the idea that visual attention may play a part in inattentive symptoms, and that emotion regulation may play a part in impulsivity symptoms.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".