Feasibility of Using a Computer-assisted Intervention to Enhance the Way Women With Breast Cancer Communicate With Their Physicians
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
This study was conducted to evaluate the feasibility of using a computer intervention to enhance communication between healthcare professionals and women with breast cancer. Additional aims were to measure the extent to which women achieved their preferred decisional roles and satisfaction with the clinical medical appointment. This two-arm randomized clinical trial design included a convenience sample of 749 women with breast cancer attending 3 urban Canadian outpatient oncology clinics. Most women were older than 50 years and had a high school diploma or greater (57%). Women in the control group completed measures of decision preference before their clinic appointments. Women in the intervention group were encouraged to use the information and decision preference profiles generated by the computer program at their clinic appointments. Levels of involvement in decision making and satisfaction were measured after the clinic appointments. Results showed that although the majority of women in both groups did assume their preferred roles in decision making, a significantly higher proportion of women in the intervention group reported playing a more passive role than originally planned. Both groups reported high satisfaction levels. Future research is required to study how this computer intervention could be used by clinicians to provide information and decision support to these women.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it