Barriers and facilitators of adherence to medical advice on skin self-examination during melanoma follow-up care
Bibliographic record
Abstract
BACKGROUND: Melanoma is the fastest growing tumor of the skin, which disproportionately affects younger and middle-aged adults. As melanomas are visible, recognizable, and highly curable while in early stages, early diagnosis is one of the most effective measures to decrease melanoma-related mortality. Skin self-examination results in earlier detection and removal of the melanoma. Due to the elevated risk of survivors for developing subsequent melanomas, monthly self-exams are strongly recommended as part of follow-up care. Yet, only a minority of high-risk individuals practices systematic and regular self-exams. This can be improved through patient education. However, dermatological education is effective only in about 50% of the cases and little is known about those who do not respond. In the current literature, psychosocial variables like distress, coping with cancer, as well as partner and physician support are widely neglected in relation to the practice of skin self-examination, despite the fact that they have been shown to be essential for other health behaviors and for adherence to medical advice. Moreover, the current body of knowledge is compromised by the inconsistent conceptualization of SSE. The main objective of the current project is to examine psychosocial predictors of skin self-examination using on a rigorous and clinically sound methodology. METHODS/DESIGN: The longitudinal, mixed-method study examines key psychosocial variables related to the acquisition and to the long-term maintenance of skin self-examination in 200 patients with melanoma. Practice of self-exam behaviors is assessed at 3 and 12 months after receiving an educational intervention designed based on best-practice standards. Examined predictors of skin self-exam behaviors include biological sex, perceived self-exam efficacy, distress, partner and physician support, and coping strategies. Qualitative analyses of semi-structured interviews will complement and enlighten the quantitative findings. DISCUSSION: The identification of short and long-term predictors of skin self-examination and an increased understanding of barriers will allow health care professionals to better address patient difficulties in adhering to this life-saving health behavior. Furthermore, the findings will enable the development and evaluation of evidence-based, comprehensive intervention strategies. Ultimately, these findings could impact a wide range of outreach programs and secondary prevention initiatives for other populations with increased melanoma risk.
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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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".