Scoping review on the role of the family doctor in the prevention and care of patients with foetal alcohol spectrum disorder
Bibliographic record
Abstract
BACKGROUND: Foetal alcohol spectrum disorder (FASD) is the leading preventable cause of nongenetic mental disability. Given the patient care pathway, the General Practitioner (GP) is in the front line of prevention and identification of FASD. Acknowledging the importance of the prevalence of FASD, general practitioners are in the front line both for the detection and diagnosis of FASD and for the message of prevention to women of childbearing age as well as for the follow-up. OBJECTIVES: The main objective of the scoping review was to propose a reference for interventions that can be implemented by a GP with women of childbearing age, their partners and patients with FASD. The final aim of this review is to contribute to the improvement of knowledge and quality of care of patients with FASD. METHODS: A scoping review was performed using databases of peer-reviewed articles following PRISMA guidelines. The search strategy was based on the selection and consultation of articles on five digital resources. The advanced search of these publications was established using the keywords for different variations of FASD: "fetal alcohol syndrome," "fetal alcohol spectrum disorder," "general medicine," "primary care," "primary care"; searched in French and English. RESULTS: Twenty-three articles meeting the search criteria were selected. The interventions of GPs in the management of patients with FASD are multiple: prevention, identification, diagnosis, follow-up, education, and the role of coordinator for patients, their families, and pregnant women and their partners. FASD seems still underdiagnosed. CONCLUSION: The interventions of GPs in the management of patients with FASD are comprehensive: prevention, identification, diagnosis, follow-up, education, and the role of coordinator for patients, their families, and pregnant women and their partners. Prevention interventions would decrease the incidence of FASD, thereby reducing the incidence of mental retardation, developmental delays, and social, educational and legal issues. A further study with a cluster randomized trial with a group of primary care practitioners trained in screening for alcohol use during pregnancy would be useful to measure the impact of training on the alcohol use of women of childbearing age and on the clinical status of their children.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".