A Study on the Efficiency in the Children Suffering from Attention Deficit Hyperactivity Disorder
Bibliographic record
Abstract
The present study aims at investigating the efficiency of the children suffering from hyperactivity disorder in the continuous function test of auditory and visual stimuli (IVA) in order to improve and promote the mental health of these kinds of people. This is of descriptive-comparative type of study. The 30 participants of the present study are the students of Tehran schools which have been chosen through cluster sampling among two groups of hyperactive and normal boys and girls who aged from 12 to 18. The Connors questionnaires and IVA+AE test were used to achieve the goal. The data were analyzed using SPSS-20 and multivariable statistical analyses method. The findings showed that there is a significant correlation among the focused attention, attention distraction, divided attention and selective attention of auditory aspect of normal and hyperactive students and the scores of the focused attention, attention distraction, divided attention and selective attention of the auditory aspect of normal students are higher than the hyperactive students (P<0.05). Furthermore, the same correlation exists in the visual aspect of the normal and hyperactive students and the scores of the focused attention, attention distraction, divided attention and selective attention of the visual aspect of normal students are higher than the hyperactive students (P<0.05).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".