Validity of the time trade-off and standard gamble methods of utility assessment in retinal patients
Bibliographic record
Abstract
AIM: To assess the validity of the time trade-off (TTO) and standard reference gamble (SRG) techniques of utility assessment in patients with retinal disease. A cross section of eligible patients was studied and validity was determined through their relation with two logical constructs, visual acuity and scores from the Visual Function 14 (VF-14) index. METHODS: The study consisted of eligible patients presenting to a tertiary retinal facility who completed an interview. All patients had best corrected vision of 20/40 or worse in at least one eye. TTO and SRG utilities, as well as a VF-14 questionnaire, were administered through a standardised interview. Demographic and clinical (including Snellen visual acuity) information was also collected. RESULTS: 323 patients met these study criteria. Significant predictors of TTO utilities in the multivariate analysis were vision in the better seeing eye (p<0.01) and VF-14 scores (p<0.01). Significant predictors of standard gamble utilities were also vision in the better seeing eye (p<0.01) and VF-14 scores (p<0.05). CONCLUSION: Both the standard gamble and TTO methods demonstrate strong validity when evaluated against visual acuity in the better seeing eye and the VF-14 score.
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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 | 0.018 | 0.111 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".