Cross-sectional study on the awareness, susceptibility and use of heated tobacco products among adolescents in Guatemala City, Guatemala
Bibliographic record
Abstract
OBJECTIVES: Heated tobacco products (HTPs) are increasingly marketed worldwide, yet limited research on HTPs has been conducted in low and middle-income countries (LMICs) or among adolescents. Guatemala is one of the few LMICs where HTPs are available. This study examined prevalence and correlates of HTP awareness, susceptibility and use among adolescents in Guatemala. DESIGN, SETTING AND PARTICIPANTS: A cross-sectional survey on HTP awareness, susceptibility and use was conducted among 2870 students between the ages of 13 and 17 in private schools in Guatemala City, Guatemala. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcome was susceptibility to future use of HTP among school-aged current and never smokers in Guatemala. We also explored awareness and use of HTPs. Multivariate binomial regression models were used to explore associations between these outcomes and both sociodemographic factors and established smoking correlates. RESULTS: Of all students (n=2870), about half were aware of HTPs (52.4%) and susceptible to future or continued use (52.4%). Whereas 8.4% of students had tried HTPs in the lifetime (but not in the last month), only 2.9% used HTPs in the past month. Independent correlates of HTP susceptibility and ever-use included: use of other tobacco products (current smoking: adjusted OR (AOR)=10.53 and 6.63, respectively; current e-cigarette use: AOR=21.87 and 10.40, respectively), moderate alcohol consumption (AOR=1.49 and 1.19, respectively), marijuana use in the past 30 days (AOR=3.49 and 2.29, respectively) and having friends who use HTPs (AOR=1.83 and 7.28, respectively). CONCLUSIONS: Among this sample of adolescents in Guatemala City, where tobacco control is weak, the prevalence of HTP use was low but susceptibility to future use was high. Tobacco prevention and intervention strategies for cigarettes and e-cigarettes should now also include HTPs, which tend to be used by similar adolescent populations (ie, those who use other substances or are exposed to tobacco through family and friends).
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".