A Qualitative Assessment of the Journey to Delayed Breast Reconstruction
Bibliographic record
Abstract
BACKGROUND: Canada has low immediate breast reconstruction (IBR) rates compared to the United States and Europe. Breast cancer survivors live with mastectomy defects sometimes for years, and this represents an area for improvement in cancer care. PURPOSE: This study qualitatively assessed (1) information provided about breast reconstruction at the time of cancer diagnosis among women seeking delayed breast reconstruction (DBR) and (2) referral practices for plastic surgery consultation for DBR. METHODS: Fifty-two consecutive patients seen in consultation for DBR at a single Canadian tertiary care centre completed questionnaires regarding their experience in seeking breast reconstruction. Seven semi-structured interviews were conducted to further explore themes identified through questionnaires. Questionnaire responses and interview transcripts were analyzed for recurring themes using standard qualitative techniques. RESULTS: A significant portion of women (43%) was interested in reconstruction prior to mastectomy, yet IBR was infrequently discussed (14%) or discouraged by their oncologic surgeons (33%). Common patient reasons for not pursuing IBR were referring physician objection and not having adequate knowledge. Women expressed wanting to discuss reconstruction at the time of cancer diagnosis. Half of the patients had attended another consultation, but the initial plastic surgeon either did not offer procedures for which these women were candidates or had prohibitively long surgical wait times. CONCLUSION: Lack of information about reconstructive options at the time of cancer diagnosis and perceived access barriers to plastic surgeons may contribute to underutilization of IBR in Canada. Access to breast reconstruction can be improved by reducing inefficiencies in plastic surgery referrals.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".