A Comprehensive Analysis of Skin Cancer Concerns and Protective Practices in Manitoba, Canada, Highlights Lack of Skin Cancer Awareness and Predominance of High-Risk Sun Exposure Behaviors
Bibliographic record
Abstract
The rapidly increasing skin cancer rates in Canada are alarming, with current data estimating that 1/3 of Canadians will be affected in their lifetime. Thus, deeper understanding of high-risk sun exposure behaviors is needed to help counter this trend. Only limited action has been taken by federal/provincial governments to reduce skin cancer incidence. A cross-sectional survey study was conducted in Manitoba, with frequency counts, means, and percentages used to encapsulate responses. Age- and gender-adjusted odds ratios were calculated using logistic regression analyses. Our study identified worrying inadequacies in sun protective behaviors and attitudes, with the threat of such high-risk behaviors amplified by a lack of skin cancer awareness. Alarming elements were noted in participants' sun exposure history (>65% reported a history of sunburns, >50% previously used a tanning bed, and >75% recently tanned for pleasure), beliefs and attitudes (>50% believe that they look better/healthier with a tan, and >40% believe that having a base tan is protective against further sun damage), and sun protection efforts (sun protective clothing was used <60% of the time, sunscreen was used by <50%, and there was a lack of knowledge about sunscreen characteristics in ~30% of respondents), in addition to significant differences being established between demographic subgroups (based on gender, age, skin phototype, income, and education attained). This study provides worrisome insight onto the grim landscape of sun protective behaviors and attitudes in Manitoba, which will inevitably translate into higher skin cancer rates and should serve as a call to action to promote targeted public health messaging in this jurisdiction and beyond.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".