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Record W2903140050 · doi:10.1016/j.jogn.2018.10.007

Tailored Intervention for Smoking Reduction and Cessation for Young and Socially Disadvantaged Women During Pregnancy

2018· article· en· W2903140050 on OpenAlexfundaboutno aff
Lorraine Greaves, Nancy Poole, Natalie Hemsing

Bibliographic record

VenueJournal of Obstetric, Gynecologic & Neonatal Nursing · 2018
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsnot available
FundersPublic Health AgencyRegistered Nurses' Association of OntarioAlberta Health Services
KeywordsDisadvantagedOperationalizationPsychological interventionHarm reductionPovertyPregnancySmoking cessationPublic healthMedicineHarmPsychologyIntervention (counseling)NursingPsychiatrySocial psychologyPolitical science

Abstract

fetched live from OpenAlex

Rates of smoking during pregnancy remain high in Canada, and cessation rates are low among women who are younger than 24 years and who are socially disadvantaged, that is, have few social and economic resources because of poverty, violence, or mental health issues. On the basis of findings from literature reviews and consultation with policy makers, we developed and operationalized four approaches that can be used by health care providers to tailor interventions for tobacco use in pregnancy. These four approaches are woman centered, trauma informed, harm reducing, and equitable. Public health initiatives that address smoking in young and socially disadvantaged women could be more sharply focused by shifting to such tailored approaches that are grounded in social justice aims, span pre- and postpregnancy periods, and can be used to address women's social contexts and concerns.

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)0.002
metaresearch head score (Gemma)0.006
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 score0.016
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.022
GPT teacher head0.313
Teacher spread0.292 · 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

Citations16
Published2018
Admission routes2
Has abstractyes

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Same venueJournal of Obstetric, Gynecologic & Neonatal NursingSame topicSmoking Behavior and CessationFrench-language works237,207