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Record W2115756395 · doi:10.1177/1059840513497800

Gender Differences in Reasons to Quit Smoking Among Adolescents

2013· article· en· W2115756395 on OpenAlexafffund
L C Struik, Erin K. O’Loughlin, Erika N. Dugas, Joan L. Bottorff, Jennifer O’Loughlin

Bibliographic record

VenueThe Journal of School Nursing · 2013
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsUniversité de MontréalConcordia UniversityCentre Hospitalier de l’Université de MontréalOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersCenters for Disease Control and PreventionCanada Research Chairs
KeywordsQuit smokingPsychologyScale (ratio)Longitudinal studySmoking cessationClinical psychologyMedicineDemographyDevelopmental psychology

Abstract

fetched live from OpenAlex

It is well established that many adolescents who smoke want to quit, but little is known about why adolescents want to quit and if reasons to quit differ across gender. The objective of this study was to determine if reasons to quit smoking differ in boys and girls. Data on the Adolescent Reasons for Quitting (ARFQ) scale were collected in mailed self-report questionnaires in 2010-2011 from 113 female and 83 male smokers aged 14-19 years participating in AdoQuest, a longitudinal cohort study of the natural course of the co-occurrence of health-compromising behaviors in children. Overall, the findings indicate that reasons to quit in boys and girls appear to be generally similar, although this finding may relate to a lack of gender-oriented items in the ARFQ scale. There is a need for continued research to develop and test reasons to quit scales for adolescents that include gender-oriented items.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.055
GPT teacher head0.321
Teacher spread0.266 · 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 source (direct Gemma or distilled Codex), 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

Citations7
Published2013
Admission routes2
Has abstractyes

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