Bifocals in Down syndrome study (BiDS): analysis of video recorded sessions of literacy and visual perceptual skills
Bibliographic record
Abstract
PURPOSE: In this longitudinal study, a group of school children with Down syndrome (DS) and reduced accommodation were prescribed bifocals and followed to investigate the impact of bifocal spectacles on early literacy and visual perceptual skills. The natural progression of early literacy skills in this population along with the changes with bifocals, described by monthly subtest scores and the time taken to complete literacy and visual perceptual tasks, are reported. METHODS: Fourteen children with DS, aged eight to 18 years, were followed for five months with single vision lenses; 11 were prescribed bifocals based on their accommodative ability and followed for another five months. A battery of reading and visual perceptual tests was administered before and after prescription of bifocals. Monthly subtests of similar tasks were administered to measure progress. All the visits were videotaped to determine the time taken for the child to complete each task. RESULTS: There was no significant measurable natural progression of early literacy skills in this group of participants on the Word Identification (WI) subtest (Repeated Measures ANOVA, F [4, 24]=1.377, p = 0.271) and Dolch sight words (RMANOVA F [4, 24]= 0.344, p = 0.846). In contrast, once bifocals were prescribed there was significant improvement in the scores of the monthly subtests (p = 0.050, 0.025 and 0.023 for WI, Dolch sight words and numbers, respectively) and the rate of progress in monthly scores improved for WI (p = 0.008). Repeated measures Analysis of Variance showed a significant decrease in the completion times with bifocals for the WI test in the full battery of tests (p = 0.0015). There was significant correlation between the improvement in focus with bifocals and the decrease in completion time for the WI task (p = 0.004). CONCLUSIONS: This study demonstrates no significant natural progression over a five-month period in the group of participants with Down syndrome; however, with bifocals, faster and improved performance on some literacy skills was observed. We recommend that bifocals be considered in children with Down syndrome presenting with inadequate accommodation to optimise their educational potential.
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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 | 0.000 | 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".