Continuity of Cancer Care: Female Participants’ Report of Healthcare Experiences After Conclusion of Primary Treatment
Bibliographic record
Abstract
BACKGROUND: Understanding patient perceptions of cancer care is crucial for improving treatment experiences and health outcomes. This study explores female patient-reported experiences with cancer care. Our aim was to identify areas for improvement and enhance patient-centered approaches in specialty and primary care settings. METHODS: This was a prospective observational study using ResearchMatch. Our eligibility criteria were 40 years or older adult cancer diagnosis, female, and treated for cancer in the United States. RESULTS: = 1224), 64 responded to the invitation and 57 completed the survey (89% participation proportion). The majority of the respondents were not receiving treatment during the study period (68%). Of those, 89% completed the recommended treatment, and 10% stopped the treatment before completion. Nearly 80% of respondents saw the same oncologist during the treatment at every appointment, and only 8% reported changing clinicians during their primary cancer treatment. Over 63% of respondents were not seeing the same primary care clinician as they did when they were first diagnosed. Respondents reported facing challenges with employment and ability to return to work (26%), being able to afford medication (21%), and paying medical bills (15%). DISCUSSION: = 57) identified strengths and challenges in cancer care. Consistent oncologist involvement and proximity to care centers was consistently reported during active treatment. Discontinuity with primary care, however, may warrant further inquiry. Reported financial, employment and access issues support previous studies that identified these as major challenges during and after active cancer treatment. Our study underscored the need to enhance patient-centered coordination and support to improve cancer and survivorship care outcomes.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".