Understanding the Perceived Relationship between Sun Exposure and Melanoma in Atlantic Canada: A Consensual Qualitative Study Highlighting a “Sunscreen Paradox”
Bibliographic record
Abstract
Globally, cutaneous melanoma (CM) incidence is increasing, with sun exposure identified as a key modifiable risk factor. The Atlantic provinces of Canada display varied CM incidence rates: New Brunswick aligns with the national average, while Nova Scotia and Prince Edward Island exceed it, and Newfoundland and Labrador fall below this benchmark. We investigated the relationship between sun exposure and CM in these provinces. Twenty-two focus groups encompassing 95 Atlantic Canada residents were conducted and transcribed. A thematic analysis was conducted in MAXQDA using the social-ecological model as a framework. Residents of high-CM incidence provinces demonstrated greater sun exposure awareness, consulting UV indices, and using sunscreen and sun-protective clothing. However, they received greater UV exposure due to warmer climates and outdoor work and cultural activities. Conversely, those in low-incidence provinces used sunscreen and sun-protective clothing less often, engaged in occupations and hobbies affording less sun exposure, and lived in cooler climates. Our data supports a possible "sunscreen paradox", whereby increased sunscreen use is correlated with augmented sun exposure, leading to a deceptive sense of security. Public health initiatives in Atlantic Canada promoting sun safety must address this paradox while integrating community-specific behaviors and norms in order to develop tailored campaigns.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.008 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".