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Record W3096785173 · doi:10.1017/jsc.2020.28

Free, easy and effective: how young adults used 8 weeks of mailed nicotine patches and to what effect

2020· article· en· W3096785173 on OpenAlexaff
Kelli-an Lawrance, Amanda Kirkwood, Heather E. Travis, Peter Selby

Bibliographic record

VenueThe Journal of Smoking Cessation · 2020
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental HealthBrock University
Fundersnot available
KeywordsAbstinenceConfidence intervalOdds ratioSmoking cessationDemographyMedicineOddsLogistic regressionNicotineYoung adultNicotine replacement therapyPopulationPsychiatryInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

Abstract Introduction Research shows the mass distribution of free nicotine replacement therapy (NRT) is a high-impact, population-level strategy for smoking cessation; but underrepresentation of younger, and/or lighter, smokers challenges generalisability of findings to young adult smokers. Aims This naturalistic study examined how and with what effect young adult smokers used free nicotine patches provided through a mass mailout programme. Methods In total, 5,025 eligible 18–29 year-old smokers who accessed an online ordering platform received self-help materials and an 8-week course of patches matched to their consumption level (<10 cigarettes per day (cpd); ≥10 cpd). No other behavioural support occurred. Whether participants used patches correctly and achieved 30-day continuous abstinence at 6-month follow-up were assessed. Results Among 694 participants with complete data: 89% used some patches; 8% used the patches correctly for 8 weeks; 31.0% (95% confidence interval (CI) = 27.6, 34.7) achieved abstinence. Adjusted logistic regression analysis showed the highest odds of abstinence was associated with the correct use of patches (odds ratio = 2.8, 95% CI = 1.5, 5.1). Conclusions Mass distribution of free patches may be an effective public health measure for supporting younger, lighter smokers to attempt cessation, reduce consumption, or achieve abstinence. Emphasising why and how to use NRT for the entire treatment course may enhance outcomes.

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)0.001
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 score0.035
Threshold uncertainty score0.338

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.014
GPT teacher head0.261
Teacher spread0.247 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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