Practical issues in assisting shared decision‐making
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
To facilitate treatment decision-making, one aims to provide information, present it in a way that makes it as easy as possible to understand, and to help the decision-maker through the cognitive processes that result in a treatment decision. Decision aids aim to accomplish just these goals and this paper identifies practical issues that we have encountered in creating a decision aid for men with early stage prostate cancer. We highlight the results of studies we carried out to provide an empirical basis for the decision aid that we were developing. Several of the studies were designed to identify what information key players (health professionals, patients and family members) thought was important for the decision-making process. Another investigation studied methodological considerations in identifying important information. The final study focused on presentation issues. These studies, designed to explore what information was considered important, found great variability among both health care professionals involved in treating patients with prostate cancer (urologists, radiation oncologists, nurses in cancer clinics, and radiation technologists) and among the patients, themselves. The studies also showed that not all information contained within a typical category is of equal importance. A methodological study showed that the information that patients deem to be important to their decision depends on whether they are rating the information that could be provided, or questions that could be answered. Finally, presentation studies showed that the various formats used in presenting quantitative information are processed with differing degrees of accuracy and ease. Each of the above results has implications for those creating decision aids; these implications are highlighted.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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 it