Dry Eye Symptoms Assessed by Four Questionnaires
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: To establish the relationships between commonly used questionnaires including Dry Eye Questionnaire, McMonnies Questionnaire, and Ocular Surface Disease Index, and to test the construct and face validity of the simple Subjective Evaluation of Symptom of Dryness. METHODS: Ninety-seven non-contact lens wearing subjects were enrolled in the study and classified into either a "dry" and "non-dry" group using a single score from an initially applied subjective evaluation of symptom of dryness. The four questionnaires were then completed in a random order. The unidimensionality and accuracy of the responses was assessed using Rasch and receiver (or relative) operating characteristics curve analysis and the characteristics of and association between symptoms were compared using non-parametric statistics. RESULTS: The responses from the Dry Eye Questionnaire, McMonnies Questionnaire, and Ocular Surface Disease Index met the Rasch analysis criterion of unidimensionality. Each test separated the symptomatic and asymptomatic groups well [all receiver (or relative) operating characteristics area-under-the-curve statistics at least 0.88] and there were significant associations between the results from each questionnaire (all Spearman rho at least 0.64). CONCLUSIONS: The results illustrate that different questionnaire-based instruments examining symptoms in controls and symptomatic subjects derive unidimensional data that are similar inasmuch as the overall scores are highly correlated. The data also point to the utility of a quick, three-question screening tool in dry eye research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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