Using Metacognitive Methods to Examine Emotion Recognition in Children With ADHD
Bibliographic record
Abstract
Objective: This study investigated confidence accuracy associations for emotion recognition (ER) in children with ADHD and typically developing children (TD). Method: Thirty-nine children with ADHD and 42 TD ( M = 9 years, 11 months, SD = 14.92 months, 26 females) completed an ER task. Intelligence and executive function task performance were also measured. Results: The ADHD group was more confident on ER compared with TD, but no group differences were found on their overall accuracy. Specifically, the ADHD group was more confident in its recognition of sad and angry faces compared with the TD group. On a metacognitive index, the ADHD group displayed lower resolution, suggesting that the TD group was better at discriminating correct from incorrect responses. Higher resolution was associated with lower ADHD symptoms. Conclusion: Confidence ratings with reference to performance on a specific task can provide an index of social-cognition in children with ADHD.
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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 | 0.001 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".