Inaccurate or Imprecise? Examining the Positive Illusory Bias in Youth with ADHD's Academic Self-appraisals
Bibliographic record
Abstract
Children and youth with ADHD show a positive illusory bias (PIB), where they overestimate their academic competencies (AC) relative to other performance and informant indicators. It is unclear whether the PIB renders self-views inaccurate (i.e., non-predictive of external indicators) or just imprecise (i.e., inflated, but predictive). This study examined the predictive accuracy of academic self-appraisals in 102 adolescents aged 13-17 (51 with ADHD; 51 typically-developing), and whether EFs could predict the PIB size. Youth completed math and EF tests, and self-rated their AC. Parents rated their youth’s AC and EF. Youth with ADHD performed more poorly on the math task (vs. comparison group) but showed a larger AC PIB relative to parents’ ratings, partly accounted for by EFs. However, all youths’ AC-ratings were more predictive of math performance than their parents’ AC-ratings. In all, youth with ADHD appear self-aware despite a modest PIB, but nuanced self-appraisals may depend on EFs.
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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 | 0.006 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".