Perceived safety and effectiveness of electronic cigarettes among Malaysian adults and public support for regulation
Bibliographic record
Abstract
Introduction: Electronic cigarettes have been used as \na harm reduction method towards tobacco cessation. \nMalaysian government has enforced a strict policy to \nregulate the sale of electronic cigarette products because \nits liquid contains nicotine. \nObjectives: This study aimed to explore the general public’s perception towards electronic cigarette use. Public support towards electronic cigarette regulation was also examined. \nMaterials and Methods: Data were obtained from the National E-Cigarette Survey (NECS) 2016, which used a multi-stage stratified cluster sampling household survey representing all Malaysian adults aged 18 years old. A cross-sectional survey was conducted among a total of 4,288 adults. \nResults: Majority were aged 25–44 years old (44%), completed at least secondary education (69%), of Malay \nethnicity (73%), and married (68%). Majority (88.1%) have \nnever used electronic cigarette. A quarter (25.5%) perceived electronic cigarette helps people quit cigarette smoking, while 20.3% perceived electronic cigarette helps people to maintain cigarette abstinence. About 85% believed that electronic cigarette use do not help in improving breathing and coughing. Majority (91.8%) disagreed that electronic cigarettes should be allowed in places where tobacco smoking is banned. Thus, 63.4% agreed that electronic cigarette should be banned completely rather than regulated. \nConclusion: Majority of general public had negative perception about electronic cigarette use.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".