Effectiveness of a Mobile App to Increase Risk Perception of Tobacco, Alcohol, and Marijuana Use in Mexican High School Students: Quantitative Study
Bibliographic record
Abstract
BACKGROUND: Young people have the highest rate of drug use worldwide. Recent data from Mexico in this population show that the prevalence of illicit drug use doubled between 2011 and 2016 (2.9%-6.2%), with marijuana being the one with the highest increase (2.4%-5.3%), but also point out that alcohol and tobacco use have remained steady or decreased. Mexican adolescents are at high risk for drug use owing to a low perception of risk and the availability of drugs. Adolescence is an ideal period to reduce or prevent risky behaviors using evidence-based strategies. OBJECTIVE: In this study, we aimed to test the short-term effectiveness of a mobile intervention app ("What Happens if you Go Too Far?" ["¿Qué pasa si te pasas?"]) that seeks to increase risk perception of tobacco, alcohol, and marijuana use in a sample of Mexican high school students. METHODS: A nonexperimental evaluation based on pretest-posttest design was used to measure the effectiveness of a preventive intervention using a mobile app, "What Happens If You Go Too Far?" The dimensions analyzed were knowledge of drugs and their effects, life skills, self-esteem, and risk perception. The intervention was conducted on a high school campus with 356 first-year students. RESULTS: =15.3; P<.001). There was no significant difference in the perception that it is dangerous to smoke 5 cigarettes, and there was a marginal difference in the perception that it is very dangerous to smoke 1 cigarette or to use alcohol or marijuana. We used a generalized estimating equation method to determine the impact of the variables on risk perception. The results showed that knowledge about smoking increased the risk perception of smoking 1 cigarette (odds ratio [OR] 1.1065, 95% CI 1.013-1.120; P=.01), and that knowledge about marijuana use (OR 1.109, 95% CI 1.138-1.185; P=.002) and self-esteem (OR 1.102, 95% CI 1.007-1.206; P=.04) produced significant increases in the risk perception of consuming 5 cigarettes. Resistance to peer pressure and assertiveness also increased the perceived risk of using tobacco and alcohol. CONCLUSIONS: The intervention has the potential to increase the perception of risk toward drug use in high school students by providing knowledge about the effects and psychosocial risks of drug use and by strengthening life skills that are associated with increased risk perception. The use of mobile technologies in intervention processes may broaden the scope of preventive work for adolescents.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".