Effects of Line Spacing on Reading Performance of Normally Sighted and Simulated Visually-Impaired Subjects: A Pilot Study Using Arabic Words
Bibliographic record
Abstract
The study aims to evaluate the role of line spacing during reading in normal and visually-impaired persons. A total of 225 normally-sighted participants with mean age of 23.7 years were asked to read Arabic sentences in a randomized order. Each Arabic sentence contains 7 lines with and without simulated cataract. The words were printed with black letters on white background to enhance contrast and fonts were in Times New Roman and of N12 letter size. The reading pages were placed on reading stand situated 25 cm away from the subject’s eyes. The simulated cataract was created by using a Bernell Cling Patch Occluder. This reduced the visual acuity of all subjects to 20/60. Each line of the text was separated by different line spacing namely: single space, 1.5, 2.0, 2.5, 3.0 and 4.0 which represents, 0.5 cm, 0.8 cm, 1.1 cm, 1.4 cm, 1.7 cm and 2.0 cm, respectively. The sheets were presented randomly and participants’ voices were recorded as they read under a controlled time. The tape was analysed later and reading rate was calculated. There was a significant difference (p<0.0001) in reading rates between the normal sighted persons and the visually impaired persons for all line spacing. Modifying the spacing between lines in prints had a significant impact (p<0.0001) on the reading rate of the visually impaired but not in normally-sighted persons (p˃0.05). Intermediate line spacing (2 and 2.5) increased the reading rate of the visually impaired persons significantly more (p<0.001) than other line spacing, but smaller or larger line spacing slowed their reading rate, significantly (p<0.001). The visually-impaired persons reported that they felt the difference in reading prints with larger line spacing as compared with normal sighted participants who did not. It is beneficial to adequately modify the line spacing in prints commonly read by low vision persons. For Arab subjects the optimum line spacing to significantly improve reading in the visually impaired should range from 0.8 to 1.1 cm. This finding may be a useful for publishers of Arab prints targeting the visually impaired persons. Thus, the implication of the study in the field of health is that by establishing the least common line spacing visualized optimally among normal and simulated visually impaired persons would be fixed as default line spacing for Arab printing to achieve better reading performance.
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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 | 0.000 | 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) | 0.002 | 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".