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Record W2547759076

Discourse / Discours - Supporting Fathers' Efforts to Be Smoke-Free: Program Principles

2012· article· en· W2547759076 on OpenAlexvenueno aff
John L. Oliffe, Joan L. Bottorff, Gayl Sarbit

Bibliographic record

VenueCanadian Journal of Nursing Research · 2012
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsnot available
Fundersnot available
KeywordsShamePsychological interventionHealth promotionPsychologyPromotion (chess)AutonomySocial psychologyBlamePrivilege (computing)NursingMedicinePublic healthPolitical science
DOInot available

Abstract

fetched live from OpenAlex

There is limited empirical evidence on effective ways to develop, distribute, and evaluate men-centred, gender-sensitive health promotion programs. The purpose of this research was to transition qualitative findings on men's smoking into father-centred cessation interventions. Men's perspectives were gathered in 4 group sessions with 24 new fathers who smoked. The data led to the identification of 3 principles for men's health promotion programs: use positive messaging to promote change without amplifying stigma, guilt, shame, and blame; foster connections between masculine ideals (e.g., strength, decisiveness, resilience, autonomy) and being smoke-free; and privilege the testimonials of potential end-users (e.g., fathers who smoke and want to quit). Experiences drawn from the design and pilot-testing of a booklet and a group program based on these principles are described. The findings can be used to guide nurses in the design and/or delivery of men's health promotion programs.

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)0.018
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.098

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0050.009
Scholarly communication0.0040.003
Open science0.0020.005
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.200
GPT teacher head0.488
Teacher spread0.289 · 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 designNot applicable
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

Citations2
Published2012
Admission routes1
Has abstractyes

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