Suboptimal decision making by children with ADHD in the face of risk: Poor risk adjustment and delay aversion rather than general proneness to taking risks.
Bibliographic record
Abstract
OBJECTIVE: Suboptimal decision making in the face of risk (DMR) in children with attention-deficit hyperactivity disorder (ADHD) may be mediated by deficits in a number of different neuropsychological processes. We investigated DMR in children with ADHD using the Cambridge Gambling Task (CGT) to distinguish difficulties in adjusting to changing probabilities of choice outcomes (so-called risk adjustment) from general risk proneness, and to distinguish these 2 processes from delay aversion (the tendency to choose the least delayed option) and impairments in the ability to reflect on choice options. Based on previous research, we predicted that suboptimal performance on this task in children with ADHD would be primarily relate to problems with risk adjustment and delay aversion rather than general risk proneness. METHOD: Drug naïve children with ADHD (n = 36), 8 to 12 years, and an age-matched group of typically developing children (n = 34) performed the CGT. RESULTS: As predicted, children with ADHD were not more prone to making risky choices (i.e., risk proneness). However, they had difficulty adjusting to changing risk levels and were more delay aversive-with these 2 effects being correlated. CONCLUSIONS: Our findings add to the growing body of evidence that children with ADHD do not favor risk taking per se when performing gambling tasks, but rather may lack the cognitive skills or motivational style to appraise changing patterns of risk effectively. (PsycINFO Database Record
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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 | 0.000 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".