Evaluating information for women referred for breast screening abnormalities.
Bibliographic record
Abstract
BACKGROUND: To evaluate a plain-language guideline sent to women with abnormal screening results who attended the Manitoba Breast Screening Program (MBSP). METHODS: A plain-language guideline was mailed with a result letter to 258 randomly chosen women who had abnormal mammograms and/or abnormal clinical breast examinations. Four weeks later, a satisfaction questionnaire was mailed to these women (cases) as well as to 254 randomly chosen women with abnormal results who were not sent a guideline (controls). All cases were interviewed by telephone three weeks after the questionnaire was mailed. RESULTS: A total of 345 patient satisfaction questionnaires (67%) were returned, and 47% of the cases completed the telephone interview. There was no difference in satisfaction between the women who received the guideline and those who did not. Most found the guideline easy to read (99%), and the majority (89%) felt that it clearly explained what happens if further tests are needed. However, a fourth thought the guideline made them anxious. CONCLUSION: A plain-language guideline was useful for most women who had abnormal screening results, although it did not alter the women's satisfaction with the MBSP. The guideline did increase anxiety for some women. These women may require other help to decrease their anxiety.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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; 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".