"If we have the knowledge, then that is power to help our expectant moms": Northern Ontario health care students' knowledge and attitudes addressing alcohol consumption during pregnancy.
Bibliographic record
Abstract
The current document is a paper-based dissertation investigating health care professionals’ knowledge, attitudes, and self-efficacy regarding fetal alcohol spectrum disorder (FASD) and alcohol consumption during pregnancy. This dissertation incorporates findings from a secondary data analysis of health care professionals in Ontario, as well as original data from health care students training in Northern Ontario. While previous research has demonstrated that health care professionals remain under-educated concerning FASD and alcohol use during pregnancy, limited research has investigated the knowledge and experiences of health care students. The first paper included is a secondary data analysis of the 2001-2002 Fetal Alcohol Syndrome Survey for Health Professionals. Ontario-specific data (N=834) were used to examine the awareness of FASD held by various provider groups in both rural and urban settings. Results from this study indicate that many physicians, midwives, and other health care professionals may have inconsistent knowledge regarding the impact of prenatal alcohol exposure, resulting in mixed messages for women of childbearing age about the safety of alcohol use during pregnancy. The second paper included is a qualitative analysis of scenario-based vignettes regarding alcohol use during pregnancy. Although almost all students (N=21) recognized that no alcohol consumption during pregnancy is the safest recommendation, many students noted that this advice is not always conveyed to pregnant women. Finally, the third paper included is also a qualitative analysis based on a thematic analysis of scenario-based vignettes and semistructured interviews. The third paper explores health care students’ (N=21) attitudes and beliefs about women who may continue to consume alcohol throughout their pregnancy and presents the often stereotypical and stigmatic perceptions of FASD and alcohol use during pregnancy held by health care professionals. Recommendations and implications for increasing students’ and professionals’ knowledge and self-efficacy regarding FASD management and prevention are discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".