Relationship between ADHD Markers and Self-Perceived Stress: Influences on Academic Performance in Preadolescents
Bibliographic record
Abstract
The symptoms associated with Attention Deficit with Hyperactivity Disorder (ADHD), included in its different specific subtypes involves cognitive, emotional and behavioral changes leading to relationship and learning difficulties in school settings. Likewise, the impact of stress on academic performance, perceived by the students themselves on various life aspects, has been detected. A sampling of primary school pupils underwent the following tests: Testing Perception of Differences (Faces-R), Children Daily Stress Inventory (CDEI), and Assessment of Attention Deficit Hyperactivity Disorder (ADHD). At the same time, the academic outcomes provided were gathered by the education center management team by selecting Mathematics and Spanish Language grades as curricular points of reference. Among the data gathered, we can stand out the correlation among the different stress indexes and ADHD symptoms estimated from teachers and gathered from objective parameters. At the same time, the relation of these factors over academic performance is therefore confirmed. Finally, the attention estimation data validate the judgment rendered by teachers, which is consistent with the objective performance shown by pupils.
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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 | 0.002 |
| 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".