Estimates of use of preferred contraceptive method in the United States: a population-based study
Bibliographic record
Abstract
Background: In the U.S. and globally, dominant metrics of contraceptive access focus on the use of certain contraceptive methods and do not address self-defined need for contraception; therefore, these metrics fail to attend to person-centeredness, a key component of healthcare quality. This study addresses this gap by presenting new data from the U.S. on preferred contraceptive method use, a person-centered contraceptive access indicator. Additionally, we examine the association between key aspects of person-centered healthcare access and preferred contraceptive method use. Methods: We fielded a nationally representative survey in the U.S. in English and Spanish in 2022, surveying non-sterile 15-44-year-olds assigned female sex at birth. Among current and prospective contraceptive users (unweighted n = 2119), we describe preferred method use, reasons for non-use, and differences in preferred method use by sociodemographic characteristics. We conduct logistic regression analyses examining the association between four aspects of person-centered healthcare access and preferred contraceptive method use. Findings: A quarter (25.2%) of current and prospective users reported there was another method they would like to use, with oral contraception and vasectomy most selected. Reasons for non-use of preferred contraception included side effects (28.8%), sex-related reasons (25.1%), logistics/knowledge barriers (18.6%), safety concerns (18.3%), and cost (17.6%). In adjusted logistic regression analyses, respondents who felt they had enough information to choose appropriate contraception (Adjusted Odds Ratio [AOR] 3.31; 95% CI 2.10, 5.21), were very (AOR 9.24; 95% CI 4.29, 19.91) or somewhat confident (AOR 3.78; 95% CI 1.76, 8.12) they could obtain desired contraception, had received person-centered contraceptive counseling (AOR 1.72; 95% CI 1.33, 2.23), and had not experienced discrimination in family planning settings (AOR 1.58; 95% CI 1.13, 2.20) had increased odds of preferred contraceptive method use. Interpretation: An estimated 8.1 million individuals in the U.S. are not using a preferred contraceptive method. Interventions should focus on holistic, person-centered contraceptive access, given the implications of information, self-efficacy, and discriminatory care for preferred method use. Funding: Arnold Ventures.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".