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Record W4285727371 · doi:10.1136/tc-2022-057332

The smoking population is not hardening in South Korea: a study using the Korea Community Health Survey from 2010 to 2018

2022· article· en· W4285727371 on OpenAlexaff
Boyoung Jung, Jung Ah Lee, Ye‐Jee Kim, Hong‐Jun Cho

Bibliographic record

VenueTobacco Control · 2022
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsWorkplace Health, Safety and Compensation Commission
Fundersnot available
KeywordsKorean populationEnvironmental healthPopulationMedicineTraditional medicineFamily medicineAdvertisingBusiness

Abstract

fetched live from OpenAlex

INTRODUCTION: The hardening hypothesis proposes that the proportion of hardcore smokers increases when smoking prevalence declines. To evaluate whether such hardening occurs in South Korea, we examined the association between quitting behaviours, the number of cigarettes smoked per day and the proportion of hardcore smokers and smoking prevalence among local districts in South Korea. METHODS: This study used the cross-sectional data from the Korea Community Health Survey (2010-2018) to examine local district-level associations between smoking prevalence and quit attempts, quit plans, quit ratios, cigarettes smoked per day and the proportion of hardcore smokers. Panel regression analysis was performed using the indicators of hardcore smoking (quit attempts, quit plans, quit ratios, cigarettes smoked per day and proportion of hardcore smokers) as the outcome variables, and prevalence of smoking, local districts, age and sex as predictor variables. RESULTS: When the smoking prevalence of the districts decreased by 1%, quit attempts, quit plans and quit ratios increased by 0.24% (95% CI 0.11 to 0.37), 0.37% (95% CI 0.26 to 0.47) and 1.71% (95% CI 1.65 to 1.76), respectively. Cigarette consumption decreased by 0.17 cigarettes per day (95% 0.15 to 0.19), and the prevalence of hardcore smokers decreased by 0.88% (95% CI 0.78 to 0.98) when smoking prevalence decreased by 1%. CONCLUSION: Hardening of smoking did not occur in South Korea when smoking prevalence declined, which suggests tobacco control policies in South Korea have been effective in reducing smoking prevalence without increasing the proportion of hardcore smokers.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.188
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.098
GPT teacher head0.349
Teacher spread0.251 · 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.

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

Citations3
Published2022
Admission routes1
Has abstractyes

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