Coverage of skin cancer and recreational tanning in North American magazines before and after the landmark 2006 International Agency for Research on Cancer report
Bibliographic record
Abstract
BACKGROUND: Skin cancer is an increasingly important global public health problem. Mass media is a key source of skin cancer information. We examined how media coverage of skin cancer has changed over time as a consequence of the release of a key public health report from the International Agency for Research on Cancer (IARC) in 2006, which linked ultraviolet (UV) radiation from indoor tanning and skin cancer. METHODS: A directed content analysis of skin cancer and tanning coverage in 29 popular North American magazines (2001-2012) examined reporting of skin cancer risk factors, UV behaviors, and early detection in article text (n = 761) and images (n = 1267). Chi-square and correlational analyses were used determine whether coverage changed in relation to the 2006 IARC report. RESULTS: The total volume of articles about skin cancer and tanning increased modestly after the IARC report (χ (2) = 4.57, df = 1, p < .05); however, key IARC report messages (e.g., avoid indoor tanning, UV as a risk factor) were no more likely to be reported after compared to before the report. There were virtually no changes in the percentage of coverage for both risk factors and early detection information over time. There were some changes in the percentage of coverage about UV behaviors after the IARC report, but these variables were not directly related to the report. Magazines were more likely to encourage sunscreen use (χ (2) = 11.55, df = 1, p < .01) and less likely to promote the tanned look as attractive (χ (2) = 9.72, df = 1, p < .01) after the IARC report. It also became less common for magazines to promote sun avoidance (χ (2) = 6.82, df = 1, p < .01) and use of sunless tanners (χ (2) = 7.46, df = 1, p < .01) after the report. CONCLUSIONS: Despite a modest increase in volume of coverage post-IARC report, key messages from the report were not taken up by the media. While there have been some improvements in magazine reporting, there is a need for more effective dissemination of public health messages about skin cancer and tanning.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".