Doctor contraceptive-prescribing behaviour and women's attitudes towards contraception: two European surveys
Bibliographic record
Abstract
RATIONALE, AIMS AND OBJECTIVES: Many women are prescribed oestrogen-containing contraceptives for whom oestrogen-containing methods may be less suitable. METHODS: Two surveys examining contraceptive prescription practices among doctors (n = 419) and attitudes towards contraception among women (n = 1623) in France, Germany, Spain, Italy and Russia were evaluated. RESULTS: Progestin-only pills and hormone-free intrauterine devices were the most commonly prescribed contraceptives for women with medical conditions for which oestrogen-containing methods are not preferred (40% and 20%, respectively), those suffering from oestrogen-related side effects (32% and 21%) and those with concerns about the safety of oestrogen-containing methods (28% and 24%). Combined oral contraceptives (COC) were prescribed to ≥ 10% in these two groups. One-quarter of contraceptive users had asked to be switched from one COC to another because of oestrogen-related side effects; a similar proportion had been switched by their doctor for this reason. Half of the women surveyed did not want or had concerns about foreign/additional oestrogen, and about 80% said that they would consider switching to a different hormonal contraceptive to minimize oestrogen exposure. Although most doctors were aware of the World Health Organization medical eligibility criteria for contraceptive use, they still prescribed COCs or other oestrogen-containing contraceptives to women with medical conditions for which oestrogen-containing options are not favoured, suggesting a need for additional education. CONCLUSION: By complying with guidelines and heeding women's concerns, doctors can individualize their contraceptive recommendation to improve safety, acceptance and compliance and, ultimately, reduce the risk of an unintended pregnancy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".