Reliability and reproducibility of a Chinese-language visual function assessment
Bibliographic record
Abstract
OBJECTIVE: The purpose of the study was to validate a Chinese-language visual function assessment within the context of a routine cataract surgery practice and to assess the contribution of the method of questionnaire administration. DESIGN: The visual function assessment (VFA) was translated into Chinese. Two groups of study subjects were recruited: Chinese who did not speak English and Chinese conversant in English. Consecutive preoperative cataract patients of Chinese ancestry presenting to an urban ophthalmology practice were recruited. The questionnaire was administered in person or by telephone interview. Pre-operative visual acuity was recorded. Visual function scores were analyzed to assess reliability and correlation with visual acuity. RESULTS: Among the 186 potential study subjects, 155 patients completed the study The Chinese-language visual function assessment had good internal consistency (Cronbach alpha = 0.97, inter-item correlations = 0.43 to 0.96) . Reliability (with regard to the English version) and test-retest reproducibility of the Chinese questionnaire were strong with intraclass correlation coefficients greater than 0.60. The method of administration contributed to the measures of reliability and reproducibility. CONCLUSION: These results show that a Chinese-language version of the VFA questionnaire is reliable and valid. In industrialized countries with large Chinese-speaking populations and newly developed countries of East and Southeast Asia, the visual function assessment may be helpful in assisting routine clinical patient evaluation and cross-cultural outcome assessment programmes. Our findings also suggest that self-administered visual function assessments may be more reliable and valid than interview-generated assessments.
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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 | 0.022 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".