Predictors of skin self-examination before and after a melanoma diagnosis: the role of medical advice and patient’s level of education
Bibliographic record
Abstract
BACKGROUND: Cutaneous melanoma is the fastest growing tumor of the skin and the median life span of patients with advanced disease is less than a year. Melanoma-related mortality can be reduced through early detection via clinical skin exams and patient self-examination. Despite the potential to reducing the medical burden associated with clinical skin exams, systematic and regular skin self-examinations (SSE) are rarely performed. The current study examined psychosocial predictors of SSE and changes in SSE behavior from pre- to post-diagnosis in order to guide future melanoma prevention initiatives. FINDINGS: A consecutive sample of 47 melanoma survivors was drawn from a tertiary care clinic. Most melanomas had been detected by patients, spouses and other laypersons. Higher education was related to more frequent SSE at pre-diagnosis, more thorough SSE at post-diagnosis, and more frequent reports of having been advised to perform SSE at post-diagnosis. SSE behaviors increased significantly from pre- to post-diagnosis. CONCLUSIONS: These findings suggest that different patient subgroups display varied knowledge base, readiness for change, and receptiveness for medical advice. Thus, interventions seeking to enhance skin self-exam practice may be most effective when the individual's psychosocial characteristics are taken into account.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".