Evaluating <i>The Real Cost</i> Digital and Social Media Campaign: Longitudinal Effects of Campaign Exposure on E-cigarette Beliefs
Bibliographic record
Abstract
INTRODUCTION: Over the past decade, youth e-cigarette use has risen exponentially. At the same time, digital media use increased markedly while the use of traditional broadcast TV declined. In response, the U.S. Food and Drug Administration's The Real Cost public education campaign shifted to communicating the harms of e-cigarette via primarily digital and social platforms. This study evaluated longitudinal associations between exposure to campaign advertisements and changes in campaign-specific beliefs among US youth. METHODS: A nationally representative longitudinal cohort of youth (aged 11-16 years at baseline) was surveyed five times. Building on earlier work, we analyzed data from the last three waves (April-July 2020; January-April 2021; and August-October 2021; N = 2625). We assessed self-reported exposure to six ads and agreement with 11 beliefs that were each targeted by one or more ads. Eleven weighted panel regression models assessed whether ad exposure predicted changes in campaign-specific beliefs over time. RESULTS: We observed significant associations between ad exposure and increases in at least one campaign-specific belief for five of the six ads. Across the 11 beliefs, we observed associations between increased exposure and increases in 6 beliefs related to e-cigarettes and toxic metals, lung damage, dangerous ingredients, anxiety, cigarette use, and disappointing important people. CONCLUSIONS: We found evidence that self-reported exposure to this digital and social media campaign was successful at influencing youth, providing support for the effectiveness of the campaign's adaption to address youth's changes in tobacco and media use habits. IMPLICATIONS: The Food and Drug Administration's The Real Cost public education campaign educates youth about the dangers of e-cigarette use. This study evaluates longitudinal associations between exposure to The Real Cost's advertisements and changes in campaign-specific beliefs among youth. Considering evolving trends in youth media consumption, the campaign adapted its media approach to increase delivery across digital and social media platforms. Our findings indicate that the campaign reached its intended audience and increased youth beliefs around the harm of e-cigarettes and the consequences of e-cigarette use, offering evidence for the effectiveness of digital and social media youth prevention efforts within a fragmented digital environment.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".