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Record W2176342060 · doi:10.1016/j.pmedr.2015.10.006

Smokers' sources of e-cigarette awareness and risk information

2015· article· en· W2176342060 on OpenAlex

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenuePreventive Medicine Reports · 2015
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsnot available
FundersNational Cancer Institute
KeywordsTrustworthinessQuarter (Canadian coin)Electronic cigaretteAdvertisingThe InternetEnvironmental healthMedicinePsychologyProduct (mathematics)BusinessSocial psychologyGeography

Abstract

fetched live from OpenAlex

INTRODUCTION: Few studies have explored sources of e-cigarette awareness and peoples' e-cigarette information needs, interests or behaviors. This study contributes to both domains of e-cigarette research. METHODS: Results are based on a 2014 e-cigarette focused survey of 519 current smokers from a nationally representative research panel. RESULTS: Smokers most frequently reported seeing e-cigarettes in stores (86.4%) and used in person (83%). Many (73%) had also heard about e-cigarettes from known users, broadcast media ads (68%), other (print, online) advertisements (71.5%), and/or from the news (60.9%); sources of awareness varied by e-cigarette experience. Most smokers (59.9%) believed e-cigarettes are less harmful than regular cigarettes, a belief attributed to "common sense" (76.4%), the news (39.2%) and advertisements (37.2%). However, 79.5% felt e-cigarette safety information was important. Over one-third said they would turn to a doctor first for e-cigarette safety information, though almost a quarter said they would turn to the Internet or product packaging first. Most (59.6%) ranked doctors as the most trustworthy risk source, and 6.8% had asked a health professional about e-cigarettes. CONCLUSIONS: Future research should explore the content of e-cigarette information sources, their potential impact, and ways they might be strengthened or changed through regulatory and/or educational efforts.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.319

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.030
GPT teacher head0.310
Teacher spread0.280 · 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