Indoor Tanning Trends Among US Adults, 2007–2018
Bibliographic record
Abstract
Objectives. To examine indoor tanning trends among US adults, and the relation to indoor tanning youth access legislation. Methods. This study analyzed the Health Information National Trends Survey (HINTS), a mailed survey, from the years 2007, 2011, 2013, 2014, 2017, and 2018 (combined n = 20 2019). Results. Indoor tanning prevalence decreased significantly over time among all US adults from 2007 (10%) to 2018 (4%; P < .001), among young adults aged 18 to 34 years (14% to 4%; P < .001), and among both women (14% to 4%; P < .001) and men (5% to 4%; P < .05). Indoor tanning significantly decreased in states that enacted youth access legislation by 2018, but did not significantly decrease for other states. Frequent indoor tanning was common in 2018; about one quarter of respondents who reported any indoor tanning did so 25 times or more in the past year. Conclusions. This study identifies several challenges in continuing to reduce indoor tanning in the United States. Youth access legislation may be effective for reducing tanning among the broader population of tanners; however, there remains a need for focus on highly frequent tanners, as well as men.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".