Level and determinants of contraceptive uptake among women attending facilities with abortion‐related complications in East and Southern Africa
Bibliographic record
Abstract
OBJECTIVE: To investigate the level and determinants of nonreceipt of contraception among women admitted to facilities with abortion-related complications in East and Southern Africa. METHODS: Cross-sectional data from Kenya, Malawi, Mozambique, and Uganda collected as part of the World Health Organization (WHO) Multi-Country Survey on Abortion-related morbidity. Medical record review and the audio computer-assisted self-interviewing system were used to collect information on women's demographic and clinical characteristics and their experience of care. The percentage of women who did not receive a contraceptive was estimated and the methods of choice for different types of contraceptives were identified. Potential determinants of nonreceipt of contraception were grouped into three categories: sociodemographic, clinical, and service-related characteristics. Generalized estimating equations were used to identify the determinants of nonreceipt of a contraceptive following a hierarchical approach. RESULTS: A total of 1190 women with abortion-related complications were included in the analysis, of which 33.9% (n = 403) did not receive a contraceptive. We found evidence that urban location of facility, no previous pregnancy, and not receiving contraceptive counselling were risk factors for nonreceipt of a contraceptive. Women from nonurban areas were less likely not to receive a contraceptive than those in urban areas (AOR 0.52; 95% CI, 0.30-0.91). Compared with women who had a previous pregnancy, women who had no previous pregnancy were 60% more likely to not receive a contraceptive (95% CI, 1.14-2.24). Women who did not receive contraceptive counselling were over four times more likely to not receive a contraceptive (AOR 4.01; 95% CI, 2.88-5.59). CONCLUSION: Many women leave postabortion care having not received contraceptive counselling and without a contraceptive method. There is a clear need to ensure all women receive high-quality contraceptive information and counselling at the facility to increase contraceptive acceptance and informed decision-making.
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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".