A randomized trial of a bottom-up intervention on children with auditory processing disorders
Bibliographic record
Abstract
Background: The inability of children with auditory processing disorders (APDs) to localize the sources of sounds, led to the study. Aims and Objectives: The study aimed to determine the effectiveness of dichotic listening training (DLT) on their listening ability. Methods: A randomized control trial was adopted as a design, using audiometric instruments of otoscope, audiometer, electrophysiological assessment of tympanometer, intellectual assessment of Wechsler Intelligence Scale for Children, fourth edition, and other standardized tests of Canadian ADHD resource checklist, Informal graded word recognition test to identify 40 single-profiled pupils with APD (male and female, 8 years 0 months– 10 years 11 months), randomly put into DLT, or placebo control group, and exposed to 10 weeks of therapeutic sessions which includes 10-min session of listening to a story through a compact disc player with an earphone in the stronger ear, while the weaker ear was exposed to typical environmental noise in the school environment; 1 week of pretest, and a week of posttest on their sound localization ability. The data gathered were tested on three null hypotheses, at 0.05 level of significance, and analyzed with analysis of covariance, and Bonferroni post hoc test. Results: DLT was effective in the sound localization ability of pupils with APD. Conclusions: Thus, management of children with APD should include sound localization training, and classrooms should be sound-proof to prevent environmental noise filters.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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".