Validity and reliability of the TED-QOL: a new three-item questionnaire to assess quality of life in thyroid eye disease
Bibliographic record
Abstract
AIM: To develop and test a user-friendly questionnaire for rapidly assessing quality of life (QOL) in thyroid eye disease (TED). METHODS: A three-item questionnaire, the TED-QOL, was designed and compared to the 16-item Graves Ophthalmopathy (GO)-QOL and the nine-item GO-Quality of Life Scale (QLS). 100 patients with TED were administered all three questionnaires on two occasions. Results were compared to clinical severity scores (Vision, Inflammation, Strabismus, Appearance (VISA) classification). Main outcomes were construct and criterion validity, test-retest reliability, duration, comprehension and completion rates. TED-QOL correlated strongly with the other questionnaires for corresponding items (Pearson correlation: appearance 0.71, 0.62; functioning 0.69, 0.66; overall QOL 0.53). Test-retest analysis demonstrated good reliability for all three questionnaires (intraclass correlations: TED-QOL 0.81, 0.74, 0.87; GO-QOL 0.81, 0.82; GO-QLS 0.74, 0.86, 0.67). TED-QOL was significantly faster to complete (1.6 min vs GO-QOL 3.1 min, GO-QLS 2.7 min, p<0.0001) and had a higher completion rate (100% vs GO-QOL 78%, GO-QLS 94%). There was only moderate correlation between items on all three questionnaires and VISA scores. CONCLUSION: The TED-QOL is rapid and easy to complete and analyse and has similar validity and reliability to longer questionnaires. All questionnaires showed only moderate correlation with disease severity, emphasising the discrepancy between objective and subjective assessments and the importance of measuring both.
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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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".