Bibliographic record
Abstract
BACKGROUND: Little is known about users of electronic cigarettes, or their opinions, satisfaction or how and why they use such products. METHODS: An internet survey of 81 ever-users of ecigarettes in 2009. Participants answered open-ended questions on use of, and opinions about, ecigarettes. RESULTS: Respondents (73 current and 8 former users) lived in France, Canada, Belgium or Switzerland. Most respondents (77%) were men; 63% were former smokers and 37% were current smokers. They had used e-cigarettes for 100 days (median) and drew 175 puffs per day (median). Participants used the ecigarette either to quit smoking (53 comments), to reduce their cigarette consumption (14 comments), in order not to disturb other people with smoke (20 comments), or in smoke-free places (21 comments). Positive effects reported with ecigarettes included their usefulness to quit smoking, and the benefits of abstinence from smoking (less coughing, improved breathing, better physical fitness). Respondents also enjoyed the flavour of ecigarettes and the sensation of inhalation. Side effects included dryness of the mouth and throat. Respondents complained about the frequent technical failures of ecigarettes and had some concerns about the possible toxicity of the devices and about their future legal status. CONCLUSIONS: Ecigarettes were used mainly to quit smoking, and may be helpful for this purpose, but several respondents were concerned about potential toxicity. There are very few published studies on ecigarettes and research is urgently required, particularly on the efficacy and toxicity of these devices.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".