Barriers and facilitators of cardiovascular disease prevention services for women with prior gestational diabetes or hypertensive disorders of pregnancy: a scoping review
Bibliographic record
Abstract
AIMS: Although CVD screening and preventive care in the early postpartum are recommended for women with prior gestational diabetes (GDM) and hypertensive disorders of pregnancy (HDP), certain barriers limit access to such services. We conducted a scoping review to summarize evidence on the barriers and facilitators of CVD prevention services among women with prior GDM or HDP. METHODS: A comprehensive search strategy was used to search articles published in three databases (Ovid Medline, CINAHL, Embase). Studies published in English or French that investigated and reported barriers or facilitators to postpartum CVD screening and preventive care among women with previous GDM and HDP were included. Out of 18,565 studies we screened, 29 studies (12 qualitative, 17 quantitative) were included. RESULTS: Main individual level barriers including lack of knowledge, health and emotional factors were identified. Competing priorities, lack of family/friend support and mistrust of healthcare providers were the most reported interpersonal level barriers, while gaps in communication was the most significant organizational barrier, and gaps in insurance coverage was the most reported system barrier. Individual level facilitators included a personal desire for better health and availability of postpartum programs, and the most reported interpersonal facilitator was women's commitment to modelling a healthy lifestyle for their children. Organizational level facilitators were access to primary care providers and follow-up visit reminders, and program availability in native languages. CONCLUSION: Women with prior GDM or HDP face significant barriers to accessing postpartum CVD prevention services. These barriers ranged from individual-level knowledge gaps to system-level healthcare disparities.
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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 | 0.012 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".