Razones por las que los consumidores duales de cigarrillo electrónico y tabaco convencional inician o mantienen el consumo dual. Una revisión sistemática
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
Some smokers use electronic cigarettes (e-cigs) as an aid to quit smoking or as a harm reduction strategy. However, these smokers may end up using e-cigs and conventional cigarettes, becoming dual users. The main aim of this study was to assess the reasons why dual users use e-cigs. In addition, as a secondary objective, the conflicts of interest and funding of the included studies were analyzed. METHODS: A search was conducted in PubMed, EMBASE, Web of Science and PsychInfo databases until November 2023. Cross-sectional studies were selected that included dual users of conventional tobacco and e-cigs and analyzed the reasons for e-cig use. The Newcastle Ottawa Quality Assessment Scale was applied to assess the quality of the included studies. RESULTS: Fourteen studies were included. One assessed reasons for initiation, 12 for maintenance of use, and one assessed both separately. Reduction in the number of cigarettes smoked and the perception that e-cigs are less harmful were the main reasons for initiation and maintenance of use. Among the 10 studies that presented a conflict of interest statement, three had conflicts with the pharmaceutical industry. Information on funding was included in 12 studies, of which nine received public funding and one received funding from the pharmaceutical industry. CONCLUSIONS: Identifying the reasons for e-cig use among dual users of e-cigs and conventional tobacco is fundamental for the design of smoking cessation programs and programs aimed at increasing the population's knowledge of new forms of consumption.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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