The Neglected Topic
Bibliographic record
Abstract
Costs are an important component of patients' decision making, but a comparatively underemphasized aspect of formal shared decision making. We hypothesized that decision aids also avoid discussion of costs, despite their being tools designed to facilitate shared decision making about patient-centered outcomes. We sought to define the frequency of cost-related information and identify the common modes of presenting cost and cost-related information in the 290 decision aids catalogued in the Ottawa Hospital Research Institute's Decision Aid Library Inventory (DALI) system. We found that 56% (n = 161) of the decision aids mentioned cost in some way, but only 13% (n = 37) gave a specific price or range of prices. We identified 9 different ways in which cost was mentioned. The most common approach was as a "pro" of one of the treatment options (e.g., "you avoid the cost of medication"). Of the 37 decision aids that gave specific prices or ranges of prices for treatment options, only 2 were about surgery decisions despite the fact that surgery decision aids were the most common. Our findings suggest that presentation of cost information in decision aids is highly variable. Evidence-based guidelines should be developed by the International Patient Decision Aid Standards (IPDAS) Collaboration.
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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 | 0.005 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.106 | 0.031 |
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".