The Meaning Behind the Scar: Anonymous Live Liver Donors’ Perceptions of Their Surgical Scars
Bibliographic record
Abstract
BACKGROUND: Scarring can greatly impact quality of life for individuals (ie, causing depression posttraumatic stress disorder and body image issues). Those who wish to be anonymous live liver donors are warned of the potential negative psychological impacts associated with the large scar left from liver donation surgery. Given the unique degree of autonomy that these patients have over their surgery, we explore whether a sample of 26 anonymous live liver donors experience a unique relationship with their scar. METHODS: Anonymous donors participated in a semistructured qualitative interview examining their experience with donation. Interviews were audio-recorded, transcribed, and analyzed using the constant comparison method for themes pertaining, to participants' perception of their scar. RESULTS: Five main themes were identified-a marker of satisfaction about the donation experience, a physical reminder of donation, a trigger for recipient-related thoughts, an awareness tool, and a potential threat to anonymity. Donors did not voice any body image or cosmetic concerns due to their scars. Instead, discussions about the negative aspects of scarring centered around the identifying nature of their scar. CONCLUSIONS: These findings help underscore the distinctiveness of anonymous living liver donors as a patient population. Preparing anonymous living liver donors for different types of cosmetic issues relating to their scar (ie, as a possible threat to their desired anonymity) may be more appropriate than preparing them in the same way as other donor populations.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".