Valuation of Life With Disability: An International Comparison Study in Vietnam, Peru, and Haiti
Bibliographic record
Abstract
The authors measured perceived quality of life for 4 disabilities among 450 adults in 3 resource-limited countries, measuring mean utilities using time trade-off, and surveying participants on 35 sociocultural characteristics to compare utilities for disabilities by country and examine associated sociocultural characteristics. Mean utilities were >0 for mild and moderate, but <0 for severe and profound. Utilities differed across countries ( P = .007, .000, .017, .000 for mild, moderate, severe, profound, respectively). Vietnamese utilities correlated with residence ( P = .03, moderate), education ( P = .03, severe), and number of children ( P = .03, moderate). Peruvian utilities correlated with education ( P = .05, mild; P = .05, severe), experience with disability ( P = .001, mild), gender ( P = .04, moderate; P = .03, profound), number of hospitalizations ( P = .04, severe). In Haiti, the only correlate was rejection ( P = .02, moderate). Culture-specific variables differentially shape perceptions of disability in developing countries, thereby affecting cost-effectiveness calculations. Given substantially negative perceptions, reducing major disability would improve cost-effectiveness of health-policy decisions more than reducing mortality.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".