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Record W2419256890 · doi:10.1177/084456211304500308

Smoking Prevention among Youth: A Multipronged Approach Involving Parents, Schools, and Society

2013· article· en· W2419256890 on OpenAlexaffvenue
Sandra P. Small, Kaysi Eastlick Kushner, Anne Neufeld

Bibliographic record

VenueCanadian Journal of Nursing Research · 2013
Typearticle
Languageen
FieldHealth Professions
TopicSchool Health and Nursing Education
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsPsychological interventionCurriculumMedical educationPsychologyQualitative researchTobacco controlPublic healthMedicineNursingPedagogySociologySocial science

Abstract

fetched live from OpenAlex

The purpose of this research was to examine the perspectives of professionals on youth smoking prevention. The researchers used a qualitative descriptive design with a purposive sample of 9 professionals consisting of elementary school teachers, public health nurses, and tobacco control experts from non-governmental organizations. Data were collected through semi-structured interviews and were analyzed for themes. The view of the participants was that although parents have the main responsibility for educating their children about smoking, a multipronged approach, which also includes school and society more generally, will have the greatest effect. The need for a comprehensive, multifaceted, multichannel approach might explain why single smoking prevention interventions are often ineffective. Public health nurses are in a prime position to foster and support parents' smoking prevention interventions with their children and to advocate for strong tobacco control social policy and best practice for smoking prevention curricula in schools.

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)0.016
metaresearch head score (Gemma)0.007
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.992
Threshold uncertainty score0.083

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0130.010
Scholarly communication0.0090.008
Open science0.0010.011
Research integrity0.0020.003
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 head0.264
GPT teacher head0.493
Teacher spread0.230 · 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

Citations5
Published2013
Admission routes2
Has abstractyes

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