Preconception health and care policies, strategies and guidelines in the UK and Ireland: a scoping review
Bibliographic record
Abstract
BACKGROUND: Preconception health has the potential to improve parental, pregnancy and infant outcomes. This scoping review aims to (1) provide an overview of the strategies, policies, guidelines, frameworks, and recommendations available in the UK and Ireland that address preconception health and care, identifying common approaches and health-influencing factors that are targeted; and (2) conduct an audit to explore the awareness and use of resources found in the scoping review amongst healthcare professionals, to validate and contextualise findings relevant to Northern Ireland. METHODS: Grey literature resources were identified through Google Advanced Search, NICE, OpenAire, ProQuest and relevant public health and government websites. Resources were included if published, reviewed, or updated between January 2011 and May 2022. Data were extracted into Excel and coded using NVivo. The review design included the involvement of the "Healthy Reproductive Years" Patient and Public Involvement and Engagement advisory panel. RESULTS: The searches identified 273 resources, and a subsequent audit with healthcare professionals in Northern Ireland revealed five additional preconception health-related resources. A wide range of resource types were identified, and preconception health was often not the only focus of the resources reviewed. Resources proposed approaches to improve preconception health and care, such as the need for improved awareness and access to care, preconceptual counselling, multidisciplinary collaborations, and the adoption of a life-course approach. Many behavioural (e.g., folic acid intake, smoking), biomedical (e.g., mental and physical health conditions), and environmental and social (e.g., deprivation) factors were identified and addressed in the resources reviewed. In particular, pre-existing physical health conditions were frequently mentioned, with fewer resources addressing psychological factors and mental health. Overall, there was a greater focus on women's, rather than men's, behaviours. CONCLUSIONS: This scoping review synthesised existing resources available in the UK and Ireland to identify a wide range of common approaches and factors that influence preconception health and care. Efforts are needed to implement the identified resources (e.g., strategies, guidelines) to support people of childbearing age to access preconception care and optimise their preconception health.
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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 | 0.087 | 0.236 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.030 | 0.030 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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".