E-Cigarettes are More Addictive than Traditional Cigarettes—A Study in Highly Educated Young People
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
E-cigarettes are often considered less addictive than traditional cigarettes. This study aimed to assess patterns of e-cigarette use and to compare nicotine dependence among cigarette and e-cigarette users in a group of highly educated young adults. From 3002 healthy adults, a representative group of 30 cigarette smokers, 30 exclusive e-cigarette users, and 30 dual users were recruited. A 25-item questionnaire was used to collect information related to the patterns and attitudes towards the use of cigarettes and e-cigarettes. The Fagerström test for nicotine dependence (FTND) and its adapted version for e-cigarettes were used to analyze nicotine dependence in each of the groups. The nicotine dependence levels measured with FTND were over two times higher among e-cigarette users (mean 3.5) compared to traditional tobacco smokers (mean 1.6; p < 0.001). Similarly, among dual users, nicotine dependence levels were higher when using an e-cigarette (mean 4.7) compared to using traditional cigarettes (mean 3.2; p = 0.03). Habits and behaviors associated with the use of e-cigarettes did not differ significantly (p > 0.05) between exclusive e-cigarette users and dual users. The findings suggest that e-cigarettes may have a higher addictive potential than smoked cigarettes among young adults.
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.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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 it