Electronic cigarettes
Bibliographic record
Abstract

 Background: Electronic cigarettes are a widely-used, yet still emerging technology. As such, there is relatively little data regarding the reasons why people take up their use. Many claim to use them as a smoking-cessation method. Concern exists that experimentation in non-smokers may lead to nicotine addiction and subsequent smoking. The purpose of this study was to determine the primary reasons for the commencement of electronic cigarette use, and to suggest way in which these findings could affect current policies and regulations pertaining to electronic cigarettes. Methods: A survey examining electronic cigarette use was prepared. The survey contained questions respecting primary motivation for use, frequency of use, present and former smoking status as well as agreement with common perception about electronic cigarettes. Basic demographic information was also collected. The survey was posted to “www.reddit.com” and was accessible to users who used electronic cigarettes themselves via the “/r/electronic_cigarettes” sub-Reddit for a period of five days. Once responses were collected, Chi-square tests of independence were run to determine if any associations existed. Responses were also compared to previous studies of a similar nature to see if any similarities existed. Results: In total, 155 responses were received. The majority of the respondents were males (89.7%) between the ages of 19 and 28 (47.7%). 30.32% listed their occupation as “student”, and almost three-quarters of the respondents had some post-secondary experience. 78.1% of respondents were former smokers, and 61.3% identified their primary reason for electronic cigarette use as “to quit smoking.” Chi-squared tests for association between responses yielded statistically-significant associations between being a previous smoker and believing that electronic-cigarettes are healthier than conventional cigarettes, and between gender (specifically being male) and reasons for electronic cigarette use (specifically “to quit smoking”). However, the latter result was possibly skewed by a higher response rate from males as opposed to females. Conclusion: The high proportion of previous smokers among electronic cigarette users suggested that quitting smoking was the most common reason individuals take up electronic cigarette usage. It is therefore suggested that studies be done to determine if their use is less harmful than that of conventional cigarettes, and that existing legislation regarding their use in public be modified in light of this evidence. It is also suggested that they be given consideration as a legitimate means of smoking cessation.
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".