An international perspective: The role of nurse involvement in improving breast cancer control.
Bibliographic record
Abstract
152 Background: Non-Western, non-Caucasian populations comprise 90% of the world’s estimated 3.2 billion women, living mostly in low and middle income nations. While medical advances have greatly reduced breast cancer morbidity and mortality in developed nations, those are on the rise in many low and middle income nations. The purpose of the study was to identify emerging needs and challenges observed by breast cancer thought leaders in diverse regions of the world consisting mainly of lesser developed nations to identify strategies for improving breast cancer control. Methods: 225 breast cancer medical, advocacy and policy leaders from 30 countries in Latin America, Asia, the Middle East/North and South Africa, Canada and Australia participated in this study. The study sample was composed of 203 breast cancer specialists, 12 patient advocates and 10 policy makers. Results: The most salient needs and challenges identified were to: (1) develop nurses trained in breast cancer patient and family care, management, education and clinical research (48%); (2) individualize breast cancer therapy (47%); and (3) improve understanding of the reasons for apparently higher proportions of younger women presenting with more aggressive tumors among these predominantly non-Caucasian populations (45%). Analysis of these and other needs identified evolved into 4 key themes and sub-dimensions involving nurses to improve breast cancer control: Capacity, Research, Advocacy and Access. Conclusions: The most significant need identified by this study was to increase both the capacity and capability of breast cancer nurses. A comprehensive approach to doing this would include: (1) increasing capacity to educate nurses in breast cancer patient education and related care issues in nursing schools and teaching hospitals; (2) working with local medical societies, educational institutions and governmental authorities to enable nurses to work as primary care practitioners; and (3) increasing participation of nurses in breast cancer clinical research, working with clinicians and in collaboration with breast cancer research centers of excellence from around the world.
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.
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 | 0.013 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 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".