Abstract P1-15-09: What are the outcomes of importance for patient education in breast cancer?
Bibliographic record
Abstract
Abstract Background: Patient education is an important component of quality cancer care. However, there remains much debate about its effects, merits and limitations. There is a lack of consensus on the intended effects of educational interventions and a lack of standardized outcome measures to assess quality. As a result, multiple outcomes measures are used without consistency and in differing combinations in the literature making it difficult to compare relative efficacy of interventions. The primary objective of this study was to identify outcomes of importance for patient education interventions in breast cancer. Methods: A generic qualitative study using interpretive description was conducted to discover what key stakeholders in the process of patient education in breast cancer (patients, physicians and nurses) would identify as outcomes of importance. The study population included breast cancer patients, physicians and nurses caring for breast cancer patients at the Juravinski Hospital and Cancer Centre in Hamilton, Ontario. Four focus groups and one semi-structured interview was conducted using purposeful sampling and an iterative design. Results: Eight patients, five nurses and four physicians participated in this study. Five common themes to all groups with respect to outcomes of importance in patient education were discovered: improving knowledge, improving coping ability, providing an orientation to the cancer system, enabling shared decision making and impacting behaviour during cancer treatment. Conclusion: Despite the surprising variability and inconsistency of outcomes discovered in the patient education literature, this qualitative study demonstrated that patients, physicians and nurses generally agree on what constitute important outcomes and serves as a first step in the process of developing validated outcomes for patient education interventions in cancer. Citation Format: Ghazaleh Kazemi, Mark Levine, Harold Reiter, Christina Sinding. What are the outcomes of importance for patient education in breast cancer? [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P1-15-09.
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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 | 0.017 | 0.058 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".