Determination of the Minimal Clinically Important Difference (MCID) for Ocular Subjective Responses
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Bibliographic record
Abstract
Purpose: To determine the minimal clinically important difference (MCID) for contact lens (CL)-related subjective responses and explore whether MCID values differ between subjective responses and study designs. Methods: This was a retrospective analysis of data from seven one-week bilateral crossover studies and 14 one-day contralateral CL studies. For comfort, dryness, vision, or ease of insertion, participants rated on a 0-100 visual analogue scale (VAS) and indicated lens preference on a five-point Likert scale featuring strong, slight, and no preferences. For each criterion, four MCID estimates were calculated and averaged: mean VAS score difference for "slight preference," lower limit of 95% confidence interval VAS score difference for "slight preference," difference in mean VAS score difference between "slight" and "no preference" and 0.5 standard deviation of VAS scores. Results: The four calculation methods generated a small range of MCID values. For bilateral studies, the averaged MCID was 7.2 (range 5.4-8.8) for comfort, 8.1 (5.2-10.6) for dryness, 7.1 (5.5-9.3) for vision and 7.6 (6.0-10.5) for ease of insertion. For contralateral studies, the averaged MCID was 6.9 (6.1-7.6) for comfort at insertion and 7.5 (6.8-8.2) for end-of-day comfort. Conclusions: This work demonstrated very similar MCID values across subjective responses and study designs, in a population of habitual soft CL wearers. In all cases, MCID values were on average seven units on a 0 to 100 VAS. Translational Relevance: This work provides MCID values which are important for interpreting ocular subjective responses and planning clinical studies.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it