Contraception Practices Among Women on Opioid Agonist Therapy
Bibliographic record
Abstract
OBJECTIVE: Despite increased public awareness and use of opioid agonist therapy (OAT), there is little published data on contraception among women on methadone or buprenorphine/naloxone. This study aimed to characterize patterns of contraception use among this population. METHODS: We conducted a cross-sectional survey between May 2014 and October 2015 at 6 medical clinics, pharmacies, and community organizations in British Columbia. Trained surveyors used the Canadian Sexual Health Survey (CSHS) to collect information on contraceptive practices and barriers to health care access. Descriptive analysis was performed on the subset of women on OAT who were at risk for unintended pregnancy. RESULTS: Of the 133 survey respondents, 80 (60.2%) were at risk for unintended pregnancy. Among the 46 respondents with a recent pregnancy, 44 (95.7%) reported it as unintended. Of those at risk for unintended pregnancy, the most common contraceptive methods used were "no method," male condom, and depo-medroxyprogesterone at 28.8%, 16.3%, and 12.5%, respectively. Only 5% reported dual protection with a barrier and hormonal or intrauterine method. Barriers to contraception access included difficulty booking appointments with providers and cost, although 97% of all respondents reported feeling comfortable speaking with a physician about contraception. CONCLUSION: We found that most respondents using OAT reported prior pregnancies that were unintended, and used less effective contraceptive methods. Health care professionals who provide addiction care are uniquely positioned to address their patients' concerns about contraception. Incorporating family planning discussions into OAT services may improve understanding and use of effective contraceptive methods. Addressing unmet contraceptive needs may enable women on OAT to achieve their reproductive goals.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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".