Assessing the Effects of Standardized School-Based Educational Cessation Programs for Adolescent Smokers
Bibliographic record
Abstract
Introduction: Cigarette smoking is a significant public health issue, and the primary cause of preventable health problems in the Greater Toronto Area (GTA). Nevertheless, the prevalence of adolescent smoking remains high. Our proposed study aims to investigate the effectiveness of school-based educational programs in reducing adolescent smoking rates in the GTA. It will compare the results of weekly integrated education sessions offered throughout a school term to more focused, discrete sessions offered at two different points in the term at 10 secondary schools in the GTA. The findings will help inform potential policy and curricular changes to promote smoking cessation among current and future youth. Methods: This study utilizes an experimental quantitative research design. Multi-stage cluster sampling will be used. 10 schools will be selected, with 20 students being recruited per school. The intervention group will receive a school-based education program for smoking cessation, lasting an academic semester. The control group will receive an educational session at the beginning and end of the semester. The inclusion criteria is as follows: participants must be (a) adolescents aged 12-17 and attending an accredited primary or secondary school, (b) living in the GTA, and (c) current daily smokers. The Fagerström Test for Nicotine Dependence (FTND) and biochemical tests will be used to collect pertinent data about smoking cessation rates. Abstinence will also be assessed using the Russell Standard. Results: The study will use statistical tests to compare the proportion of students in the intervention group who quit smoking to the control group. The primary outcome measures will be 4-week and 6-month abstinence counts and nicotine dependency as measured by the FTND. The analysis will be conducted using IBM SPSS ver. 29. Discussion: The results of this study will provide valuable insight into the effectiveness of educational programs in promoting smoking cessation among youth, which will inform the design of future school-based interventions. Additionally, the study will help to understand adolescent smoking patterns, which can be used to guide public health policies. Conclusion: The results will have the potential to inform future education and public health strategies for encouraging adolescent smoking cessation.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".