Prevalence and correlates of skin self-examination behaviors among melanoma survivors: a systematic review
Bibliographic record
Abstract
Melanoma is the most common cause of skin cancer deaths, and individuals who have had melanoma have an increased risk of developing new melanomas. Doing regular self-examinations of skin enables one to detect thinner melanomas earlier when the disease is more treatable. The aim of this systematic review is to characterize and evaluate the existing literature on the prevalence and correlates of skin self-examination (SSE) behaviors among adult melanoma survivors in the USA and Canada. A computerized literature search was performed using PubMed, Google Scholar, and ScienceDirect. The inclusion criteria for the studies were: (a) reported results for adult melanoma survivors in the USA or Canada, (b) papers described empirical research, (c) assessed SSE and related behaviors, and (d) papers were published in a peer-reviewed journal in the past 20 years. Key phrases such as "skin self-examination/SSE in melanoma survivors in the United States" and "correlates of skin self-examination/SSE" were used. Based on the inclusion criteria, 30 studies were included in the systematic review. SSE prevalence varied depending on how SSE was defined. Demographics and factors (gender, education level, patient characteristics, partner assistance, and physician support) associated with SSE were identified. Findings of this review show evidence for the need to have a consistent way to assess SSE and suggest different types of correlates on which to focus in order to promote SSE and reduce the risk of melanoma recurrence in survivors. This systematic review and its protocol have been registered in the international database of prospectively registered systematic reviews in health and social care (PROSPERO; ID: 148878).
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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 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".