Patient experiences and outcomes following facial skin cancer surgery: A qualitative study
Bibliographic record
Abstract
Early melanoma and non-melanoma skin cancer of the facial area are primarily treated with surgery. Little is known about the outcomes of treatment for facial skin cancer patients. The objective of the study was to identify concerns about aesthetics, procedures and health from the patients' perspective after facial skin surgery. Semi-structured in-depth interviews were conducted with 15 participants. Line-by-line coding was used to establish categories and develop themes. We identified five major themes on the impact of skin cancer surgery: appearance-related concerns; psychological (e.g., fear of new cancers or recurrence); social (e.g. impact on social activities and interaction); physical (e.g. pain and swelling) concerns and satisfaction with the experience of care (e.g., satisfaction with surgeon). The priority of participants was the removal of the facial skin cancer, as this reduced their overall worry. The aesthetic outcome was secondary but important, as it had important implications on the participants' social and psychological functioning. The participants' experience with the care provided by the surgeon and staff also contributed to their satisfaction with their treatment. This conceptual framework provides the basis for the development of a new patient-reported outcome instrument.
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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 | 0.015 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".