“We Don’t Get Drugs Targeted for Us:” Applying the Integrated Behavioral Model to Understand Why Black Women Chose to Participate in a Breast Cancer Clinical Trial
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
= 14) who had participated in a breast cancer clinical trial. This study aimed to better understand what may motivate Black women to engage in medical research and decide to participate in medical research. Findings revealed that Black women's altruistic desires to serve others and their communities are greatly influenced by the need to leave a "legacy" of better treatment for other Black women. The participants mostly learned about clinical trials through communicating with friends, family, or other breast cancer patients and survivors, rather than from their physicians. Many were influenced to participate by other Black breast cancer patients they knew, suggesting that social norms messaging may help alert other Black women about the continuing disparity in clinical trial participation. Finally, the participants in this study demonstrated high levels of involvement not only in seeking out clinical trials, but also in engaging in informed and shared decision-making with their providers about participating in the trials. The findings from this work illuminate important reasons Black women chose to participate in breast cancer clinical trials. Additionally, we offer robust and valuable theoretical and practical implications for researchers, so they can work toward successfully increasing Black women's participation in clinical trials.
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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 | 0.014 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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