Attention and music : understanding young children's attention and the potential of music to increase attention
Bibliographic record
Abstract
This study examined three areas related to attention in primary school-aged children to answer the following questions: Are there a distinct neuropsychological differences for young children referred by teachers as lacking in attention compared to those not lacking in attention? Are there advantages to using neuropsychological measures of attention over behaviour rating scales and observations in preschool or early grade school population? Can these same neuropsychological tools evaluate the effectiveness of music with children that have attention problems? There were 24 participants in this study, 12 children rated as having attention problems by their teacher and 12 children in the control group. Participants age ranged from 5 years 0 months to 6 years 11 months. All the children were of average intelligence, and were attending an English school or preschool within the greater Montreal Area. Participants served as their own controls for the music conditions. Participants were nested within group and order for the four treatment conditions. Findings indicated that attention difficulties not only affect behaviour, attention, and inhibition, but also influence cognitive processes in language, memory, and visual perceptual abilities especially visual motor precision. Neuropsychological tests were useful in the assessment of children's attention difficulties and could be used to differentiate attention problems that are strictly behavioural from those that are more likely the result of neuropsychological deficits. For children with attention problems environment and music had limited effects on neuropsychological variables. Rock and roll increased children's ability to sustain visual attention if they were classified as having an attention problem. It did not have this effect for children without attention problems. Gross motor inhibition is also affected by rock and roll, but only for boys who have attention problems. Higher level interactions with gender were found in overall neuropsychological functioning and with respect to music. School based interventions must be based not only on behaviour but also on cognitive deficits; early intervention is important to this process.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".