Barriers and enablers encountered by elite athletes during preconception and pregnancy: a mixed-methods systematic review
Bibliographic record
Abstract
OBJECTIVE: To synthesise the existing literature relating to barriers and enablers encountered by elite athletes during preconception and pregnancy for the purpose of identifying key recommendations and actionable steps to inform the development of pregnancy guidelines to support preconception and pregnancy in national sporting organisations. DESIGN: Mixed-methods systematic review with thematic analysis. DATA SOURCES: Four databases (Medline, SPORTDiscus, PsycINFO and CINAHL) were systematically searched to identify relevant studies, along with reference lists of included studies until 3 April 2023. ELIGIBILITY CRITERIA: Peer-reviewed primary studies from any date, language and location which identify at least one barrier and/or enabler encountered by elite female athletes during preconception and/or pregnancy were included. Grey literature, books, conference papers and other reviews were excluded. RESULTS: A total of 29 studies met the eligibility criteria for inclusion. The most common barriers identified were attitudes, perceptions and beliefs of the athlete and society, lack of support provided by sports organisations and lack of evidence-based information available. The most common enablers were specific strategies used by athletes (eg, modified training) to manage the demands of preconception and pregnancy, attitudes, perceptions and beliefs of the athlete, and support of family. CONCLUSION: Key recommendations developed from the results are for sporting organisations to (1) develop clear, transparent and multifaceted policies to support preconception and pregnancy; (2) foster supportive environments which offer flexible training, social support and positive promotion of pregnant athletes and (3) provide clear, evidence-based education and information about preconception and pregnancy to athletes, coaches, support staff and organisational staff.
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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 | 0.043 | 0.146 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.007 |
| Bibliometrics | 0.017 | 0.016 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 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".