Survivorship Care Plans for Breast Cancer Patients: Understanding the Quality of the Available Evidence
Bibliographic record
Abstract
AIM: The overall goal of the present study was to contribute to consistency in the provincial approach to survivorship care planning through knowledge synthesis and exchange. Our review focused on the research concerning the physical and emotional challenges of breast cancer (bca) patients and survivors and the effects of the interventions that have been used for lessening those challenges. METHODS: The psychosocial topics identified in bca survivorship care plans created by two different initiatives in our province provided the platform for our search criteria: quality of life (qol), sexual function, fatigue, and lifestyle behaviours. We conducted an umbrella review to retrieve the best possible evidence, and only reviews investigating the intended outcomes in bca survivors and having moderate-to-high methodologic quality scores were included. RESULTS: Of 486 reports retrieved, 51 reviews met the inclusion criteria and form part of the synthesis. Our results indicate that bca patients and survivors experience numerous physical and emotional challenges and that interventions such as physical activity, psychoeducation, yoga, and mindfulness-based stress reduction are beneficial in alleviating those challenges. CONCLUSIONS: Our study findings support the existing survivorship care plans in our province with respect to the physical and emotional challenges that bca survivors often face. However, the literature concerning cancer risks specific to bca survivors is scant. Although systematic reviews are considered to be the "gold standard" in knowledge synthesis, our findings suggest that much remains to be done in the area of synthesis research to better guide practice in cancer survivorship.
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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 | 0.129 | 0.452 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.017 | 0.017 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.018 | 0.014 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".