Willingness to take drugs to prevent serious chronic diseases (自愿服用药物以预防严重的慢性疾病)
Bibliographic record
Abstract
BACKGROUND: The aim of this study was to determine an individual's willingness to take a preventive therapy for each of two chronic diseases (type 2 diabetes [T2D] and dementia) when provided with varying likelihoods of acquiring the disease. METHODS: After reading a description of two chronic diseases (i.e. T2D and dementia), 345 student volunteers at McMaster University rated their likelihood of taking a drug that could halve their chance of developing each disease, assuming a 1-year risk of developing the disease of 50%, 25%, and 10%. A five-point Likert scale was used to collect responses. RESULTS: Assuming an annual incidence of 50%, 27% of respondents were neither likely nor very likely to take a therapy that halved the annual incidence of T2D and 13% were neither likely nor very likely to take a therapy that halved the annual incidence of dementia. Higher quoted incidence rates of the disease and a personal history of a chronic illness significantly increased willingness to take such therapy. CONCLUSIONS: A high proportion of young educated adults have ambivalent or negative attitudes regarding the use of pharmacological therapy to prevent serious health outcomes even when the absolute 1-year risk of these outcomes is very high.
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How this classification was reachedexpand
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 | 0.000 |
| 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) | 0.002 | 0.001 |
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; both teacher heads agree on what is shown here.
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".