Same-Day Breast Cancer Surgery: A Qualitative Study of Women's Lived Experiences
Bibliographic record
Abstract
PURPOSE/OBJECTIVES: To understand the experiences of women having same-day breast cancer surgery and make recommendations to assist healthcare professionals effect change to enhance quality of care. RESEARCH APPROACH: Thematic analysis of audiotaped interviews. SETTING: Outpatient departments of two city hospitals on the east coast of Canada. PARTICIPANTS: Purposive sample of 13 women who had undergone same-day breast cancer surgery. METHODOLOGIC APPROACH: A constructivist approach with in-depth interviews and comparative analysis to develop and systemically organize data into four major interrelated themes and a connecting essential thread. MAIN RESEARCH VARIABLES: Women's experiences with same-day breast cancer surgery. FINDINGS: The themes of preparation, timing, supports, and community health nursing intervention were of paramount importance for effective coping and recovery. Women who had a positive experience with same-day breast cancer surgery also reported having adequate preparation, appropriate timing of preparation, strong support systems, and sufficient community health nursing intervention. Those reporting a negative experience encountered challenges in one or more of the identified theme areas. CONCLUSIONS: Same-day surgery is a sign of the times, and the approach to it is changing. Healthcare systems need to be responsive to such changes. Although same-day surgery for breast cancer is not suitable for every patient, women undergoing this type of surgery should be assessed individually to determine whether it is appropriate for them. INTERPRETATION: Women undergoing breast cancer surgery should be screened for same-day surgery suitability. Those having same-day breast cancer surgery should be prepared adequately with timely education. Most importantly, such women should receive community health nursing follow-up for assessment, continuing education, and psychosocial support.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".