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Record W2905067783 · doi:10.1111/add.14527

Discussions between health professionals and smokers about nicotine vaping products: results from the 2016 ITC Four Country Smoking and Vaping Survey

2018· article· en· W2905067783 on OpenAlexafffundabout
Shannon Gravely, James F. Thrasher, K. Michael Cummings, Janine Ouimet, Ann McNeill, Gang Meng, Eric N. Lindblom, Ruth Loewen, Richard J. O’Connor, Mary E. Thompson, Sara C Hitchman, David Hammond, Bryan W. Heckman, Ron Borland, Hua‐Hie Yong, Tara Elton‐Marshall, Maansi Bansal‐Travers, Coral Gartner, Geoffrey T. Fong

Bibliographic record

VenueAddiction · 2018
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsOntario Institute for Cancer ResearchCentre for Addiction and Mental HealthWestern UniversityPublic Health OntarioUniversity of TorontoUniversity of Waterloo
FundersNational Institute on Drug AbuseNational Health and Medical Research CouncilNational Cancer InstituteMedical Research CouncilCanadian Institutes of Health Research
KeywordsNicotineEnvironmental healthHealth professionalsMedicineTobacco harm reductionTobacco usePsychiatryPolitical scienceHealth care

Abstract

fetched live from OpenAlex

BACKGROUND AND AIMS: Debate exists about whether health professionals (HPs) should advise smokers to use nicotine vaping products (NVPs) to quit smoking. The objectives were to examine in four countries: (1) the prevalence of HP discussions and recommendations to use an NVP; (2) who initiated NVP discussions; (3) the type of HP advice received about NVPs; and (4) smoker's characteristics related to receiving advice about NVPs. DESIGN: Cross-sectional study using multivariable logistic regression analyses on weighted data from the 2016 ITC Four Country Smoking and Vaping Survey (ITC 4CV1). SETTING: Four countries with varying regulations governing the sale and marketing of NVPs: 'most restrictive' (Australia), 'restrictive' (Canada) or 'less restrictive' (England and United States). PARTICIPANTS: A total of 6615 adult smokers who reported having visited an HP in the last year (drawn from the total sample of 12 294 4CV1 respondents, of whom 9398 reported smoking cigarettes daily or weekly). Respondents were from the United States (n = 1518), England (n = 2116), Australia (n = 1046), and Canada (n = 1935). MEASUREMENTS: Participants' survey responses indicated if they were current daily or weekly smokers and had visited an HP in the past year. Among those participants, further questions asked participants to report (1) whether NVPs were discussed, (2) who raised the topic, (3) advice received on use of NVPs and (4) advice received on quitting smoking. FINDINGS: Among the 6615 smokers who visited an HP in the last year, 6.8% reported discussing NVPs with an HP and 2.1% of smokers were encouraged to use an NVP (36.1% of those who had a discussion). Compared with Australia (4.3%), discussing NVPs with an HP was more likely in the United States [8.8%, odds ratio (OR) = 2.15, 95% confidence interval (CI) = 1.41-3.29] and Canada (7.8%, OR = 1.87, 95% CI = 1.26-2.78). Smokers in Australia were less likely to discuss NVPs than smokers in England (6.2%), although this was not statistically significant (OR = 1.47, 95% CI = 0.98-2.20). Overall, the prevalence of HPs recommending NVPs was three times more likely in the United States than in Australia (OR = 3.07, 95% CI = 1.45-6.47), and twice as likely in Canada (OR = 2.28, 95% CI = 1.06-4.87) than in Australia. Australia and England did not differ (OR = 1.76, 95% CI = 0.83-3.74). Just over half (54%) of respondents brought up NVPs themselves; there were no significant differences among countries. CONCLUSIONS: Discussions in Australia, Canada, England, and the United States between smokers and health professionals about nicotine vaping products appear to be infrequent, regardless of the regulatory environment. A low percentage of health professionals recommended vaping products. This was particularly evident in Australia, which has the most restrictive regulatory environment of the four countries studied.

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 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)0.002
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 score0.042
Threshold uncertainty score0.563

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.063
GPT teacher head0.340
Teacher spread0.276 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations25
Published2018
Admission routes3
Has abstractyes

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