Preconception care interventions among adolescents and young adults to prevent adverse maternal, perinatal and child health outcomes: An evidence gap map
Bibliographic record
Abstract
OBJECTIVE: To identify gaps in existing evidence on preconception health interventions to improve the health outcomes of adolescents, young adults, and their offspring. STUDY DESIGN: Evidence gap map (EGM) METHODS: Following the Campbell guidelines, we included reviews and interventional studies identified through searches on Medline and other electronic databases from 2010 to July 18th, 2023. Dual screening of titles/abstracts and full texts was conducted on Covidence software, followed by quality assessment and development of 2D-EGM using the EPPI-Reviewer and Mapper software. RESULTS: A total of 18 studies (124 papers) were identified, of which most of the studies were from higher- and upper-middle-income countries, with limited evidence from low-middle-income countries. More than half focused on females with limited evidence on men. The monitoring of adverse events of human papillomavirus (HPV) vaccination was the most well-evidenced area, with very little evidence on the herpes simplex virus candidate vaccine and other behavioural interventions. Perinatal outcomes were the most frequently reported outcomes followed by maternal and child health outcomes. Healthcare facilities (mostly clinical trials) were the most utilised delivery platforms, with limited or no evidence on communities, schools, and digital platforms. The overall quality of the systematic reviews was moderate while most of the trials had some concerns. CONCLUSION: The study highlights a well-evidenced area in the safety of HPV vaccination with significant gaps in research on other key health interventions, particularly in non-healthcare settings. EGM suggests further research to evaluate the effectiveness of a broad range of preconception interventions, among adolescents and youth for improving long-term health outcomes.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".