Determinants of breast cancer knowledge among newly diagnosed, low‐income, medically underserved women with breast cancer
Bibliographic record
Abstract
BACKGROUND: Among women with breast cancer (BC), greater BC knowledge has been associated with greater participation in treatment decision-making, patient satisfaction, and survival. The objective of this study was to identify modifiable determinants associated with BC knowledge. METHODS: Data were collected from a telephone survey of medically underserved women with BC in California (n = 909). The dependent variable for analysis was BC knowledge. The modifiable determinants that were assessed included 1) physician-patient discussion of BC topics, 2) receipt of written BC-related material, 3) self-efficacy in interacting with physicians, 4) physician emotional support, 5) discussions with a BC survivor, and 6) office visit support by relatives/friends. Multivariate linear regression was used to examine the effect of those determinants on BC knowledge while controlling for socioeconomic factors, clinical characteristics, and treatment received. RESULTS: The average knowledge score was 6.9 (standard deviation, 2.3; range, 0-10). In multivariate analyses among women with less physician emotional support, those with the greatest self-efficacy had higher knowledge scores than those with the least self-efficacy (8.2 vs 5.4; P < .001). For women with low self-efficacy, those with more physician emotional support had higher knowledge scores than those with less physician emotional support when the analysis was controlled for confounding factors (6.3 vs 5.4; P < .001); physician information-giving had no effect on BC knowledge. CONCLUSIONS: The study findings suggested significant associations of patient self-efficacy and physician emotional support with BC knowledge; physician emotional support appeared to be more important than physician informational support. Further research will be needed to investigate whether interventions that target these 2 domains may be effective in increasing BC knowledge in disadvantaged populations.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".