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Record W1984811769 · doi:10.3109/00016341003592552

Tobacco use and secondhand smoke exposure during pregnancy in low‐ and middle‐income countries: the need for social and cultural research

2010· article· en· W1984811769 on OpenAlexaff
Mimi Nichter, Lorraine Greaves, Michele Bloch, Michael J. Paglia, Isabel C. Scarinci, Jorge E. Tolosa, Thomas E. Novotny

Bibliographic record

VenueActa Obstetricia Et Gynecologica Scandinavica · 2010
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsBritish Columbia Centre of Excellence for Women's Health
FundersNational Institute on Minority Health and Health Disparities
KeywordsMedicineEnvironmental healthPregnancyTobacco useWorkgroupLow and middle income countriesTobacco smokeSecondhand smokeDeveloping countryEconomic growthPopulation

Abstract

fetched live from OpenAlex

Tobacco use is a leading cause of death and of poor pregnancy outcome in many countries. While tobacco use is decreasing in many high-income countries, it is increasing in many low- and middle-income countries (LMICs), where by the year 2030, 80% of deaths caused by tobacco use are expected to occur. In many LMICs, few women smoke tobacco, but strong evidence indicates this is changing; increased tobacco smoking by pregnant women will worsen pregnancy outcomes, especially in resource-poor settings, and threatens to undermine or reverse hard-won gains in maternal and child health. To date, little research has focused on preventing pregnant women's tobacco use and secondhand smoke (SHS) exposure in LMICs. Research on social and cultural influences on pregnant women's tobacco use will greatly facilitate the design and implementation of effective prevention programs and policies, including the adaptation of successful strategies used in high-income countries. This paper describes pregnant women's tobacco use and SHS exposure and the social and cultural influences on pregnant women's tobacco exposure; it also presents a research agenda put forward by an international workgroup convened to make recommendations in this area.

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)0.002
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 score0.003
Threshold uncertainty score0.563

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.093
GPT teacher head0.357
Teacher spread0.265 · 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

Citations56
Published2010
Admission routes1
Has abstractyes

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