Differences in perception of breast cancer treatment between patients, physicians, and nurses and unmet information needs in Japan
Bibliographic record
Abstract
PURPOSE: Discrepancies exist between healthcare provider and patient perceptions surrounding breast cancer treatment. Significant treatment changes in the last 10 years have made re-evaluation of these perceptions necessary. METHODS: Physicians and nurses involved in breast cancer treatment, and patients who had received breast cancer chemotherapy (past 5 years), were questioned using an Internet survey. Participants ranked physical concerns (treatment side effects), psychological concerns, priorities for treatment selection, and side effects to be avoided during treatment. Patients were asked about desired treatment information/information sources. Rankings were calculated using the mean value of scores. Spearman's rank correlation was used to determine the concordance of rankings among groups. RESULTS: Survey respondents included 207 patients, 185 physicians, and 150 nurses. Patients and nurses similarly ranked distressing physical concerns; physician rankings differed. Quality of life (QoL) and treatment response ranked high with physicians and patients when considering future treatment; nurses prioritized QoL. All three groups generally agreed on ranking of psychological concerns experienced during chemotherapy, explanation of treatment options, and how treatment decisions were made, although more patients thought treatment decisions should be made independently. Healthcare providers reported providing explanations of treatment side effects and information on physical/psychological support options while patients felt both were lacking. Concordance was calculated as 0.47 (patient-physician), 0.83 (patient-nurse), and 0.76 (physician-nurse). Patients desired additional information, preferring healthcare providers as the source. CONCLUSIONS: Specific areas for improvement in breast cancer patient care were identified; programs should be implemented to address unmet needs and improve treatment in these areas.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".