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Record W2769354816 · doi:10.1111/add.14119

E‐cigarette price sensitivity among middle‐ and high‐school students: evidence from monitoring the future

2017· article· en· W2769354816 on OpenAlexaboutno aff
Michael F. Pesko, Jidong Huang, Lloyd D. Johnston, Frank J. Chaloupka

Bibliographic record

VenueAddiction · 2017
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsnot available
FundersNational Cancer InstituteNational Institute on Drug Abuse
KeywordsExciseConfidence intervalTobacco controlMedicineCigarette smokingDemographyMonitoring the FutureQuarter (Canadian coin)EconomicsEnvironmental healthPublic healthGeographyInternal medicine

Abstract

fetched live from OpenAlex

AIMS: We estimated associations between e-cigarette prices (both disposable and refill) and e-cigarette use among middle and high-school students in the United States. We also estimated associations between cigarette prices and e-cigarette use. DESIGN: We used regression models to estimate the associations between e-cigarette and cigarette prices and e-cigarette use. In our regression models, we exploited changes in e-cigarette and cigarette prices across four periods of time and across 50 markets. We report the associations as price elasticities. In our primary model, we controlled for socio-demographic characteristics, cigarette prices, tobacco control policies, market fixed effects and year-quarter fixed effects. SETTING: United States of America. PARTICIPANTS: A total of 24 370 middle- and high-school students participating in the Monitoring the Future Survey in years 2014 and 2015. MEASUREMENTS: Self-reported e-cigarette use over the last 30 days. Average quarterly cigarette prices, e-cigarette disposable prices and e-cigarette refill prices were constructed from Nielsen retail data (inclusive of excise taxes) for 50 US markets. FINDINGS: In a model with market fixed effects, we estimated that a 10% increase in e-cigarette disposable prices is associated with a reduction in the number of days vaping among e-cigarette users by approximately 9.7% [95% confidence interval (CI) = -17.7 to 1.8%; P = 0.02] and is associated with a reduction in the number of days vaping by the full sample by approximately 17.9% (95% CI = -31.5 to -4.2%; P = 0.01). Refill e-cigarette prices were not statistically significant predictors of vaping. Cigarette prices were not associated significantly with e-cigarette use regardless of the e-cigarette price used. However, in a model without market fixed effects, cigarette prices were a statistically significant positive predictor of total e-cigarette use. CONCLUSIONS: Higher e-cigarette disposable prices appear to be associated with reduced e-cigarette use among adolescents in the US.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.011
Threshold uncertainty score0.406

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.031
GPT teacher head0.306
Teacher spread0.274 · 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

Citations87
Published2017
Admission routes1
Has abstractyes

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