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Record W2614708989 · doi:10.1177/2333393617707663

“No Alcohol Is Recommended, But . . .”: Health Care Students’ Attitudes About Alcohol Consumption During Pregnancy

2017· article· en· W2614708989 on OpenAlexaffabout
Kelly D. Coons, Shelley L. Watson, Nicole Yantzi, Nancy Lightfoot, Sylvie Larocque

Bibliographic record

VenueGlobal Qualitative Nursing Research · 2017
Typearticle
Languageen
FieldMedicine
TopicPrenatal Substance Exposure Effects
Canadian institutionsLaurentian University
Fundersnot available
KeywordsPregnancyVignetteMedicineAlcohol consumptionAlcoholFetal Alcohol Spectrum DisorderHealth educationHealth carePrenatal carePublic healthFamily medicineEnvironmental healthPsychiatryNursingPsychologyPopulationSocial psychology

Abstract

fetched live from OpenAlex

Canadian findings suggest that health care providers require further training and education to support their work preventing fetal alcohol spectrum disorder (FASD). However, the knowledge and training of health care students in relation to FASD remains largely unexplored. The purpose of this study was to understand the attitudes and beliefs of health care students about alcohol use during pregnancy. Twenty-one health care students participated in a scenario-based vignette about alcohol consumption during pregnancy. Although almost all students recognized that no alcohol consumption during pregnancy is the safest recommendation, many students recounted that this advice is not always conveyed during encounters with their pregnant patients. Three primary themes related to students' attitudes concerning alcohol use during pregnancy were identified. Health care professionals in training need further education about the risks of alcohol consumption during pregnancy and the potential health outcomes associated with prenatal alcohol exposure.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.286
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.196
GPT teacher head0.566
Teacher spread0.371 · 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.

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
Published2017
Admission routes2
Has abstractyes

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