Respondent Demographics and Contraceptive Use Patterns in the United States: A National Survey of Family Growth Analysis
Bibliographic record
Abstract
Introduction: Contraception is an important tool for helping to prevent both unintended pregnancies and sexually transmitted infections (STIs). Medical costs related to STIs are high and impose a large burden on both patients and the healthcare system. In addition, unintended pregnancies account for a large portion of pregnancies in the United States (US) and are associated with adverse maternal and infant health outcomes. Both STIs and unintended pregnancies are continuous public health concerns, and this study aims to identify patterns in contraceptive method use in relation to specific social determinants of health. Methods: Utilizing the Centers for Disease Control and Prevention (CDC)’s 2017-2019 National Survey of Family Growth report on current contraceptive status, we isolated data from 3,572 respondents who reported using one of the following contraceptive methods: oral contraceptive pills (OCPs), male condoms, partner’s vasectomy, female sterilization, withdrawal, medroxyprogesterone acetate injections (Depo-Provera), hormonal implant, or an intrauterine device (IUD). We analyzed these contraceptive methods among age, race, education, marital status, and insurance status. Data were analyzed in RStudio 2022.02.0 (RStudio Team, RStudio: Integrated Development for R. RStudio, PBC, Boston, MA) through a test of equal proportions for a significance of P < 0.05. A concurrent Yates' continuity correction was performed in order to limit erroneous significant findings based on small sample sizes where applicable. The study conception and data analysis were performed independently with oversight from our preceptor at HCA Florida Brandon Hospital, Brandon, Florida. Results: There were statistically significant differences for all our selected methods of contraception across different age groups. There were statistically significant differences for OCPs, male condoms, partner’s vasectomy, female sterilization, Depo-Provera, hormonal implant, and IUD across different race groups and different insurance statuses. There were statistically significant differences for OCPs, male condoms, partner’s vasectomy, female sterilization, withdrawal, hormonal implant, and IUD across different education levels and different marital statuses. Conclusion: This analysis highlights gaps that are present in female reproductive autonomy through the statistical differences in contraceptive methods across various demographics and warrants continued focus on the role that social determinants of health play in the prevention of unintended pregnancies and STIs. In order to promote fairness and equality in healthcare, it is essential to increase education on these topics both within and beyond medical settings. This effort aims to provide patients with equitable access to healthcare and attempt to address health disparities that are prevalent in multiple different sectors.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".