Skin cancer knowledge and photoprotective practices of organ transplant recipients
Bibliographic record
Abstract
BACKGROUND: Long-term use of immunosuppressive medications by organ transplant recipients (OTRs) leads to an increased risk of non-melanoma skin cancers (NMSCs). The objective of this study was to assess photoprotective knowledge and practices among OTRs and to identify predictors of poor sunscreen adherence and barriers to photoprotection. METHODS: A written survey was administered to 300 solid OTRs attending the Southern Alberta Transplant Program. Demographics, transplant and NMSC history, ultraviolet radiation (UVR) exposure, photoprotective knowledge and practices, and barriers to implementing photoprotection were collected. Relevant statistical analyses and univariate and multivariable regression models on sunscreen use were performed. RESULTS: One hundred and seventy-nine of the 300 respondents reported not using sunscreen most days despite 79.3% recalling have received photoprotection education. Of the surveyed OTRs, 45.7% reported no barriers to implementing photoprotective practices. On average, respondents scored 74.5% on a commonly used tool to assess photoprotective knowledge (SD 30.6%). In multivariable analyses, older age, male gender, and lack of post-secondary education were associated with lower rates of self-reported sunscreen use. The most commonly patient-reported barriers to photoprotection were "hassle/time consuming" (16.7%) and "sunscreen is uncomfortable or unpleasant" (10.0%). CONCLUSIONS: Despite OTRs self-reporting having received sufficient sun-protective knowledge and demonstrating reasonable recollection of photoprotective education on assessment, implementation of sun protection in the studied OTRs remains suboptimal.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".