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Record W2113893987 · doi:10.1093/heapro/15.3.227

Addressing the costs of quitting' smoking: a health promotion issue for adolescent girls in Canada

2000· article· en· W2113893987 on OpenAlexaffabout
Marilyn Seguire

Bibliographic record

VenueHealth Promotion International · 2000
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsPromotion (chess)GirlHealth promotionPsychological interventionSmoking cessationQualitative researchIntervention (counseling)MedicinePsychologyCigarette smokingYoung adultEnvironmental healthDevelopmental psychologyPsychiatryPublic healthNursingPolitical science

Abstract

fetched live from OpenAlex

While intense efforts have been implemented to address the problem of cigarette smoking, the prevalence of tobacco use among adolescents, in particular young women, remains high. Older adolescent girls are joining their younger counterparts in taking up the smoking habit. The literature has examined the reasons for young people starting to smoke; however, little is known about the smoking cessation process in adolescents. This paper reports findings from an in-depth qualitative study of 25 girls ages 18 and 19 which uncovered the struggles young women experience as they attempt to quit smoking. These struggles and losses are referred to as the 'costs' of quitting smoking. The 'costs' reflect not only their 'real' experiences when attempting to quit smoking, but also reflect 'anticipated' struggles and losses. The study addressed the 'costs' in relation to the social, emotional and physiological domains of the adolescent girl's life. Findings from this research project provide theoretical direction for the development of comprehensive health promotion interventions. If health care professionals are to assist in reducing cigarette smoking among young women, the 'costs' which girls see to quitting smoking must be considered.

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 score0.409
Threshold uncertainty score0.954

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)0.0010.000

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 head0.147
GPT teacher head0.421
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

Citations16
Published2000
Admission routes2
Has abstractyes

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