Experiences of adult cancer survivors receiving cancer survivorship care from primary care providers: An integrative review
Bibliographic record
Abstract
Cancer is a disease of increasing global prevalence, resulting in a rising need for cancer survivorship care (CSC; World Health Organization [WHO], 2024). While definitions of CSC vary, primary care providers (PCPs) are increasingly required to care for cancer survivors (Nekhlyudov et al., 2017). The purpose of this integrative review is to appraise existing literature to gain an understanding of the experiences of cancer survivors who receive CSC from a PCP. This review was guided by the research question: for adult cancer survivors, what is the experience of cancer survivorship care provided by a PCP? A systematic literature search was conducted, followed by an appraisal of the selected eight studies. The findings reveal the complexity and potential scope of CSC, revealing inconsistency and wide variability in patient experiences of receiving CSC from a PCP. While some study participants reported positive experiences of accessing CSC and the overall quality of their CSC from a PCP, others expressed dissatisfaction in these areas. Some consistency in cancer survivor experience was found in the areas of PCP knowledge levels and organization of CSC, with the overall perception being one of inadequacy. Given the numerous benefits of improving the care of cancer survivors, and the need to increase the role of PCPs in CSC provision, researchers, policymakers, and educators need to take note of these patient experiences to make positive improvements to CSC.,
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".