A Context for Normalizing Impulsiveness at Work for Adults with Attention Deficit/Hyperactivity Disorder (Combined Type)
Bibliographic record
Abstract
Impaired executive function and impulsiveness or intolerance to boredom in adult attention deficit/hyperactivity disorder (ADHD) are thought to compromise performance at work. Several task parameters help people with ADHD to perform better on computerized cognitive tasks, namely reduced response-to-stimulus interval, discriminative feedback, or a format resembling a videogame. However, still very little is known about how these contexts might be helpful in a real work environment. We developed a computerized task resembling a fast-paced videogame with no response-to-stimulus interval and constant and diverse discriminative error feedback. The task included several measurements of high-order executive function (planning, working memory, and prospective memory) formatted as a single multitask simulating occupational activities (SOA). We also administered the Continuous Performance Test-II (CPT-II), a very simple vigilance task without discriminative feedback and with long response-to-stimulus intervals. We tested 30 adults answering to DSM-IV criteria of ADHD (combined type) and 30 IQ-matched adults without ADHD. As has been reported many times, the ADHD participants made significantly more errors of commission than the control participants on the CPT-II, whereas the two groups made the same number of errors of commission on the SOA. The ADHD group also sought discriminative feedback significantly more actively on the SOA than the control group and performed at par with the control group in all respects. There was no speed/accuracy trade-off, nor was there any evidence of other costs of normalization on the SOA. Impulsiveness in adult ADHD is compensable on a task simulating the work environment.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".