Knowledge and Attitudes about Contraception and Abortion in Canada, US, UK, France and Australia
Bibliographic record
Abstract
Objectives: 1) To describe and compare knowledge and attitudes about contraception and abortion of women in Canada, US, UK, France and Australia. 2) To assess usefulness and validity of online panels to conduct this type of research. Method: We used Survey Monkey Audience to obtain a sample of women aged 18-44 to administer a survey about knowledge and attitude to contraception and abortion. We assessed the representativeness of our samples by comparing the demographics and attitudes to relevant data in each country. Results: 1117 surveys were completed in January 2013: 233 in Canada, 223 in the US, 230 in the UK, 221 in France and 210 in Australia. The majority of women incorrectly believed abortion and contraception were more risky than births. About half (47.1%) of the participants were classified as pro-choice because they indicated that women should be allowed to have an abortion for any reason in the first 3 months: 38.7% in Canada, 37.1% in USA, 42.0% in UK, 68.7% in France and 53.6% in Australia (p<.001). Women who believed that abortion should be restricted were more likely to provide incorrect answers to all 10 knowledge questions about abortion and contraception (p=<.001) and this pattern was similar in all five countries. Based on comparisons with census data from each country, the Survey Monkey Audience participants appear to be broadly representative of the reproductive age women in the five countries surveyed. Conclusion: Women from these five countries were similar in terms of their knowledge about the risks of abortion and contraception. The majority of women gave incorrect answers to the knowledge questions. Women who favored restrictions to abortion access, in all five countries, were more likely to incorrectly overestimate the risks of both abortion and contraception. On-line panels can be a useful, rapid and inexpensive method of conducting surveys across multiple jurisdictions.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".