Photoaging smartphone app promoting poster campaign to reduce smoking prevalence in secondary schools: the Smokerface Randomized Trial: design and baseline characteristics
Bibliographic record
Abstract
INTRODUCTION: Smoking is the largest cause of preventable death globally. Most smokers smoke their first cigarette in early adolescence. We took advantage of the widespread availability of mobile phones and adolescents' interest in appearance to develop a free photoaging app which is promoted via a poster campaign in secondary schools. This study aims to evaluate its effectiveness regarding smoking prevalence and students' attitudes towards smoking. METHODS AND ANALYSIS: A randomised controlled trial is conducted with 9851 students of both genders with an average age of 12 years in grades 6 and 7 of 126 secondary schools in Germany. At present, cigarette smoking prevalence in our sample is 4.7%, with 4.6% of the students currently using e-cigarettes (1.6% use both). The prospective experimental study design includes measurements at baseline and at 6, 12 and 24 months postintervention via a questionnaire plus a random cotinine saliva sample at 24 months postintervention. The study groups consist of randomised schools receiving the Smokerface poster campaign and control schools with comparable baseline data (no intervention). The primary end point is the difference of change in smoking prevalence in the intervention group versus the difference in the control group at 24 months follow-up. Longitudinal changes in smoking-related attitudes, the number of new smokers and quitters and the change in the number of never-smokers will be compared between the two groups as secondary outcomes. ETHICS AND DISSEMINATION: Ethical approval was obtained from the ethics committee of the University of Gießen and the ministries of cultural affairs, both in Germany. Results will be disseminated at conferences, in peer-reviewed journals, on our websites and throughout the multinational Education Against Tobacco network. TRIAL REGISTRATION NUMBER: NCT02544360, Pre-results.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".