Status of tobacco and electronic nicotine delivery systems use among health science students in low- and middle-income countries: A scoping review
Bibliographic record
Abstract
Background: The prevalence of tobacco use is high among health science students in low- and middle-income countries. This population participates in tobacco and nicotine delivery systems prevention strategies. We sought to determine the status of tobacco and nicotine delivery systems used among health sciences students in low- and middle-income countries. Methods: A scoping review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We included original research articles published in the last 10 years in indexed journals, written in Spanish and English, that focused on populations of healthcare students in low- and middle-income countries and provided information on the use of tobacco or nicotine delivery systems. Eleven databases were searched, and data were extracted using inductive analysis and thematic synthesis. Results: Thirty-four articles were reviewed. Asia was the continent that produced the most literature on the subject, and most studies had a quantitative cross-sectional methodological design. Information on social and cultural issues related to drug use, mental health, healthcare, smoking cessation, and policies and programs is presented in narrative form. Conclusions: Little information exists about the social and cultural aspects associated with the use of nicotine delivery systems, and the needs of health science students in this regard. This issue requires research through participatory, qualitative, or mixed-method approaches, focusing on analyzing participants' needs and identifying ways to transform their reality.
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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 | 0.019 | 0.068 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.023 | 0.026 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".