Free contraception and behavioural nudges in the postpartum period: evidence from a randomised control trial in Nairobi, Kenya
Bibliographic record
Abstract
BACKGROUND: Short birth intervals are a major risk factor for poor maternal and newborn outcomes. Utilisation of modern contraceptive methods during the postpartum period can reduce risky birth intervals but contraceptive coverage during this critical period remains low. METHODS: We conducted a randomised controlled experiment to test whether vouchers for free contraception, provided with and without behavioural 'nudges', could increase modern contraceptive use in the postpartum period. 686 pregnant women attending antenatal care in two private maternity hospitals in Nairobi, Kenya, were enrolled in the study. The primary outcomes were the use of modern contraceptive methods at nearly 3 months and 6 months after expected delivery date (EDD). We tested the impact of a standard voucher that could be redeemed for free modern contraception, a deadline voucher that expired 2 months after delivery and both types of vouchers with and without a short message service (SMS) reminder, relative to a control group that received no voucher and no SMS reminder. RESULTS: By nearly 6 months after EDD, we find that the combination of the standard voucher with an SMS reminder increased the probability of reporting utilisation of a modern contraceptive method by 25 percentage points (pp) (95% CI 6 pp to 44 pp) compared with the control group. Estimated impacts in other treatment arms were not statistically significantly different from the control group. CONCLUSIONS: Reducing financial barriers to postpartum contraception alone may not be enough to encourage take-up. Programmes targeting the postpartum period should consider addressing behavioural barriers to take-up.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".