Rural-urban differences in provider practice related to preconception counselling and fetal alcohol spectrum disorders.
Bibliographic record
Abstract
OBJECTIVE: Fetal alcohol spectrum disorders (FASDs) are the most common form of nongenetic birth defect in North America with devastating, long-term consequences. Physicians are the primary providers of medical care for pregnant women and they play an important role in the prevention and diagnosis of FASD. We sought to determine whether differences exist between rural and urban health care providers in knowledge of, attitudes about and awareness of FASD and preconception counselling. METHODS: Surveys were mailed to a national, random sample of Canadian health care providers (n = 5361) between October 2001 and May 2002. Bivariate data analysis was completed using SPSS 14.0. RESULTS: Compared with their urban counterparts, rural providers were more likely to report being prepared to access resources related to alcohol use and dependency, yet they were less likely to agree that it was the physician's role to manage these issues (78.4% v. 82.8%, p < 0.05). Rural providers were more likely than urban providers to use a standardized tool to screen patients for alcohol use, to ask all pregnant women if they were drinking, to have cared for a patient with an FASD (56.7% v. 48.8%), to agree that providers do not make a diagnosis because of lack of time and training, and to recognize legal issues and inappropriate behaviour as secondary outcomes of FASD. Rural and urban providers were similar in their diagnostic knowledge of FASD. CONCLUSION: Few differences between rural and urban providers exist with regard to knowledge and diagnosis of FASD; however, rural providers are more prepared to access resources for women with addiction issues and are more likely to care for patients with an FASD.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".