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Record W4407748680 · doi:10.20882/adicciones.1995

Razones por las que los consumidores duales de cigarrillo electrónico y tabaco convencional inician o mantienen el consumo dual. Una revisión sistemática

2024· review· es· W4407748680 on OpenAlexaboutno aff
Maria Velasco-Pardo, Cristina Candal‐Pedreira, Guadalupe García, Mónica Pérez‐Ríos, Nerea Mourino, Leonor Varela‐Lema, Alberto Ruano‐Raviña, Julia Rey‐Brandariz

Bibliographic record

VenueAdicciones · 2024
Typereview
Languagees
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhysicsPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.050
metaresearch head score (Gemma)0.080
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.050
Threshold uncertainty score0.266

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0500.080
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.006
Bibliometrics0.0070.004
Science and technology studies0.0010.003
Scholarly communication0.0050.007
Open science0.0030.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0070.002

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.

Opus teacher head0.038
GPT teacher head0.367
Teacher spread0.329 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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