Barriers to contraception access and use among youth: A scoping review in high‐income countries
Bibliographic record
Abstract
BACKGROUND: The United Nations (UN) has a target for universal contraception access by 2030. Youth (aged 15-29) still have limited contraception access and lower usage. A unified understanding of the barriers youth face in high-income countries (HIC) remains unclear. OBJECTIVES: Synthesized evidence on youth contraception barriers across HIC to identify continued healthcare inaccessibility and knowledge gaps. SEARCH STRATEGY: A search strategy, including terms like "youth" and "barriers," was applied to three databases, identifying articles published between January 2013-September 2024. SELECTION CRITERIA: Primary peer-reviewed quantitative, qualitative, and mixed-methods studies were included if they focused on youth and contraception barriers. DATA COLLECTION AND ANALYSIS: Following the Joanna Briggs Institute, articles were screened for inclusion, and data was extracted. Analyses included descriptive statistics and summarizing findings for quantitative and qualitative results. All articles were subjected to inductive and deductive content analysis to map barriers. Article quality was appraised by the Mixed Methods Appraisal Tool. MAIN RESULTS: A total of 41 articles were included, of which 88% were from the USA. Youth struggled to receive quality contraception care from multiple access points from health systems and youth perspectives. Barriers included youth minimal knowledge, poor approachability and care appropriateness, physical barriers, costs, stigma, confidentiality concerns, and service gatekeeping. Youth experiences varied by social identities with those from lower economic, rural, and of younger age facing more obstacles. CONCLUSIONS: Contraception was inaccessible for many. To meet UN targets, efforts need to address described barriers to ensure accessible and equitable contraception care that respects and supports youth's choices.
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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 | 0.015 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.012 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| 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".