Youth's Awareness of and Reactions to The Real Cost National Tobacco Public Education Campaign
Bibliographic record
Abstract
In 2014, the Food and Drug Administration (FDA) launched its first tobacco-focused public education campaign, The Real Cost, aimed at reducing tobacco use among 12- to 17-year-olds in the United States. This study describes The Real Cost message strategy, implementation, and initial evaluation findings. The campaign was designed to encourage youth who had never smoked but are susceptible to trying cigarettes (susceptible nonsmokers) and youth who have previously experimented with smoking (experimenters) to reassess what they know about the "costs" of tobacco use to their body and mind. The Real Cost aired on national television, online, radio, and other media channels, resulting in high awareness levels. Overall, 89.0% of U.S. youth were aware of at least one advertisement 6 to 8 months after campaign launch, and high levels of awareness were attained within the campaign's two targeted audiences: susceptible nonsmokers (90.5%) and experimenters (94.6%). Most youth consider The Real Cost advertising to be effective, based on assessments of ad perceived effectiveness (mean = 4.0 on a scale from 1.0 to 5.0). High levels of awareness and positive ad reactions are requisite proximal indicators of health behavioral change. Additional research is being conducted to assess whether potential shifts in population-level cognitions and/or behaviors are attributable to this campaign. Current findings demonstrate that The Real Cost has attained high levels of ad awareness which is a critical first step in achieving positive changes in tobacco-related attitudes and behaviors. These data can also be used to inform ongoing message and media strategies for The Real Cost and other U.S. youth tobacco prevention campaigns.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".