Exploring the relationship between socioeconomic factors, method of contraception and unintended pregnancy
Bibliographic record
Abstract
BACKGROUND: It is estimated that approximately one-third of pregnancies in Canada are unintended, meaning they were either mistimed (the woman wanted to be pregnant at a different point in time) or undesired (the woman did not want to be pregnant). This study aimed to assess the impact of socioeconomic variables and method of contraception on the decision to either terminate or continue and unintended pregnancy. METHODS: Data were obtained from two contemporaneous studies in Calgary Canada--a cross-sectional study involving women seeking abortion services (n = 577) and a longitudinal cohort study involving women with continuing pregnancies (n = 3552) between 2008 and 2012. Chi square tests and logistic regression were used to examine the association between socioeconomic variables, use of contraception and pregnancy intention. RESULTS: 96.5% of women seeking an abortion and 19.6% of women with ongoing pregnancies reported having an unintended pregnancy. Women with unintended pregnancies were significantly younger (p < 0.001), less educated (p < 0.001), had a lower household income (p < 0.001), were less likely to be in a stable relationship (p < 0.001), and less likely to speak English in the home (p < 0.002). 20.2% reported not using any form of birth control despite their desire to not get pregnant. Among women with unintended pregnancies, the only significant demographic predictor of not using any form of contraception was low educational attainment (OR = 1.7, 95% CI: 1.2-2.4). CONCLUSIONS: Low educational attainment was associated with not using any form of contraception among women with unintended pregnancies. However, as unintended pregnancy occurs across all socio-demographic groups, care providers are encouraged to have an open discussion regarding fertility goals and contraception with all patients and refer them to appropriate resource materials.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".