“If I use family planning, I may have trouble getting pregnant next time I want to”: A multicountry survey-based exploration of perceived contraceptive-induced fertility impairment and its relationship to contraceptive behaviors
Bibliographic record
Abstract
Objectives: We aim to assess women's perceptions regarding contraceptive effects on fertility across a diversity of settings in sub-Saharan Africa and how they vary by women's characteristics. We also aim to examine how such beliefs relate to women's contraceptive practices and intentions. Study design: This study uses cross-sectional survey data among women aged 15 to 49 in nine sub-Saharan African geographies from the Performance Monitoring for Action project. Our main measure of interest assessed women's perceptions of contraceptive-induced fertility impairment. We examined factors related to this belief and explored the association between perceptions of contraceptive-induced fertility impairment and use of medicalized contraception (intrauterine device, implant, injectable, pills, emergency contraception) and intention to use contraception (among nonusers). Results: Between 20% and 40% of women across study sites agreed or strongly agreed that contraception would lead to later difficulties becoming pregnant. Women at risk of an unintended pregnancy who believed contraception could cause fertility impairment had reduced odds of using medicalized contraception in five sites; aORs ranged from 0.07 to 0.62. Likewise, contraceptive nonusers who wanted a/another child and perceived contraception could cause fertility impairment were less likely to intend to use contraception in seven sites, with aORs between 0.34 and 0.66. Conclusions: Our multicountry study findings indicate women's perception of contraceptive-induced fertility impairment is common across diverse sub-Saharan African settings, likely acting as a deterrent to using medicalized contraceptive methods. Implications: Findings from this study can help improve reproductive health programs by addressing concerns about contraception to help women achieve their reproductive goals.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".