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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.
The study was conducted between April 2014 and December 2015 in two private maternity clinics in Nairobi’s informal settlements (Kiambu County). These densely populated areas are characterised by high poverty rates, poor access to water and sanitation and food insecurity.25 26 Total fertility rates for women in Nairobi’s urban poor regions are slightly higher than that of Nairobi (3.1 compared with 2.8) yet still lower than rural areas and the national average of 4.6.26 27 We recruited pregnant women attending antenatal care (ANC) at Jacaranda Health, a private-sector social enterprise providing maternal and newborn healthcare to poor urban women. At the start of the study, Jacaranda operated one maternity facility with a second facility opening in September 2014. Women were eligible to participate in the study if they attended ANC services at Jacaranda, were between 18 years and 40 years old, had a gestational age of at least 7 months at the time of enrolment and could provide a valid phone number by which they could be reached in the postpartum period. Six hundred and eighty-six women attending ANC were consented and enrolled over that time period. Pregnant women were randomly assigned with equal probability to a ‘standard voucher arm’, a ‘deadline voucher’ arm or a control group. Both voucher arms received a voucher for free contraceptive methods to be redeemed at a Jacaranda Health facility, including condoms, injectables, implants, IUDs, combined and progestin-only oral contraceptives and counselling on effective use of the lactational amenorrhoea method (LAM). The value of the voucher ranged from US$0.92–US$6.45 depending on the method choice, with the largest value for the LARC methods of implants and IUDs. The ‘deadline voucher’ voucher expired 8 weeks after estimated date of delivery (EDD) and the ‘standard voucher’ expired 1 year after it was issued. A sample of each voucher is provided in online supplementary figure 1. The expiry date was made highly salient in the deadline voucher but not in the standard voucher. We used the EDD to determine the deadline date because the delivery date was unknown at the time of enrolment. Partway through the study, additional funding was received, which allowed us to expand the study (we refer to these periods as study phase 1 and phase 2). Around the same time, Jacaranda Health opened another maternity clinic, allowing for a larger potential sample size for the study. During the initial study period, we had observed unexpectedly low rates of redemptions of vouchers. Motivated in part by this observation, we designed an additional intervention to remind households of the opportunity to take up postpartum family planning. In November 2014, a cross-randomised additional treatment arm was added to the study design. Of the 686 total of women enrolled in the study, 339 were enrolled after November 2014 and, in addition to being randomly assigned with equal probability to one of three voucher arms, were also cross-randomised with equal probability into an arm that received a postpartum (5 weeks) SMS reminder or an arm receiving no SMS message, resulting in six treatment arms. Additional details about the study design and randomisation method are provided in the online supplementary appendix. Flow into experimental treatment arms is illustrated for each study phase in online supplementary figure 2a and bonline supplementary figure 2abonline supplementary material 1. bmjgh-2018-000888supp001.pdf All participants, including the control group, received counselling and educational materials on postpartum family planning, including information on appropriate methods for the postpartum period and a recommendation to initiate postpartum family planning 6 weeks after delivery. Because some women in the no-voucher group also got the SMS reminder and because some households share access to cell phones and may have wanted to maintain privacy around decisions about family planning, the SMS did not specifically refer to the voucher but instead read: ‘Don’t forget to review your family planning materials from Jacaranda Health’. Participants were recruited in the waiting room of Jacaranda’s antenatal clinics. Eligible participants were consented into the study by providing their written consent. Participants completed a baseline survey at the antenatal clinic with questions about basic demographic characteristics and fertility preferences. Survey timing and outcome measures are defined with respect to the EDD rather than the actual delivery date in order to be consistent with the deadline and SMS intervention, which were scheduled with respect to EDD during pregnancy. Follow-up surveys were conducted by phone at 9, 12, 22, 36 and 52 weeks after EDD to assess timing of postpartum contraceptive take-up and method choice. Enumerators made multiple attempts to contact participants within a period of 3–4 weeks. Enumerators were trained to probe on the timing of contraceptive take-up if the participant did not remember the exact date with the enumerator providing assistance in estimating the date of contraceptive use. Everyone who participated in a phone survey was sent phone credit worth between US$0.46 and US$0.92 as an appreciation for participation. Data were also extracted on utilisation of care at Jacaranda from Jacaranda’s administrative database from the start of the study through June 2016 (ensuring at least 7 months of follow-up administrative data for all participants) including all information on visits to Jacaranda for family planning, any contraceptive methods received and any payments made for family planning. Finally, we kept programmatic data on the vouchers that were provided to study participants, whether vouchers were redeemed and information on when SMS reminders were sent. Additional details on data collection procedures are provided in the online supplementary technical appendix. Our primary outcome was self-reported current use of a modern contraceptive method. Modern contraception was defined as including IUDs and intrauterine systems, implants, oral contraceptive pills, emergency contraceptive pills, condoms, injectables, patches, diaphragms/cervical caps, spermicides, vaginal rings, vaginal sponges and sterilisation. While the World Health Organization (WHO) includes LAM in their definition of modern contraceptive methods, LAM is sometimes distinguished from other modern methods28 as it can be effectively practised with no costs, facility visits or products. Evidence suggests that practice of LAM often lacks the reliability of other methods and many mothers who report practising LAM are not actually protected against pregnancy.29 The exclusion of LAM from our primary outcome of current use of modern contraception is consistent with our preregistered study outcome. In order to understand the behavioural response to treatments, we also reported post hoc analysis on an outcome constructed from administrative data: take-up of a modern contraceptive method at Jacaranda. Self-reported survey data about take-up of contraception was preregistered as our primary outcome instead of using administrative data from the study facility because our treatments sought to increase the salience of desires around postpartum family planning, which may have led participants to seek family planning in whatever clinic was most convenient (not necessarily in the clinic where they received ANC). We report on modern contraceptive use in the ‘short-term’ and ‘medium term’, which we define as 9 weeks and 22 weeks after EDD. These time points were chosen to be as close as possible to our first two waves of data collection in order to minimise recall bias. If we were unable to complete one of the surveys, we inferred use at that time-point from future surveys whenever possible. So, for example, for a respondent who did not complete a 9-week survey but did complete a 22-week survey, we constructed her use of modern contraception at 9 weeks based on whether she was using a method at the 22 week survey and her report about when that method use started. This method avoided losing data for inference but cannot account for discontinuation. Short-term modern contraceptive method use corresponds to a period shortly after the WHO recommendation of contraceptive take-up by 6 weeks and allowed us to observe the immediate effects of the SMS and deadline treatments. In order to understand how interventions influenced method choice, we consider a secondary post hoc analysis not included in our preregistered outcomes that examines whether study participants are using a LARC method (defined as use of an implant, intrauterine system or IUD). We estimate risk differences between treatment arms and the control group using ordinary least squares (OLS) with robust standard errors (SEs.) We use a linear model for ease of interpretation30 and estimate heteroscedasticity robust SEs to avoid bias.31 In our first model, we include a control for study phase and enrolment facility (stratification variables) in order to maximise power.32 In the fully adjusted model, we included the following additional covariates: maternal age (continuous), a binary variable indicating whether a mother was multiparous, a binary variable indicating some secondary education or higher, a binary variable indicating previous use of modern contraception, a binary variables indicating that the mother did not want future children and a binary variable indicating that her partner did not want future children, a binary variable for intention to use postpartum FP in the short-term, a continuous variable for the days between enrolment and the EDD, a continuous variable indicating travel cost to a study health facility, a binary variable indicating that the participant’s residence was in the same sublocation as a study facility and a continuous variable indicating the date of study enrolment. We used case deletion for missing data and dummy-variable adjustment to account for missing covariates.33 In order to further explore patterns in our results, we construct a forest plot that compares the relationship between take-up of family planning and (1) our main interventions: receiving any SMS and receiving any voucher and (2) participant characteristics including education, self-reported intentions during ANC about take-up of postpartum family planning in the short-term. Coefficients were generated from OLS regressions of the variable of interest on the primary outcome of self-reported use of a modern method in the medium-term controlling for stratification variables (study phase and facility) with robust SEs. Descriptive statistics on covariates were presented for the randomised sample and the sample followed to short-term and medium-term outcomes and p-values were reported for the test of differences in means between the randomised sample and the short-term and medium-term analysis samples. We report on two measures of treatment fidelity using programmatic data: whether the voucher that was randomly assigned was provided to the study participant and whether an SMS was sent within 1 week of the scheduled time (5 weeks after EDD). We also presented descriptive statistics on voucher redemptions, the monetary value of methods received using the voucher and the timing of voucher redemptions using programmatic data. We also presented descriptive statistics on method type, location, cost and timing for the first modern method initiated among the sample of participants ever reporting that they initiated a modern method in any of our surveys. We presented robustness checks in online supplementary tables, including separate estimates for the two study phases of data collection, estimation of our main results with LAM included in the definition of modern method use and estimation of our main results using multiple imputation for individuals with missing outcome data. In order to understand concordance between self-reported survey data and administrative data, we report comparisons of the rates of agreement between survey and administrative data for the primary outcomes among the short-term and medium-term analysis samples, including an analysis of the reported location where care was received among those reporting use of a modern method. We also present the distribution of methods obtained in each treatment arm for those self-reporting use of modern method in the medium term using a stacked bar graph. This study was approved by Institutional Review Boards at Harvard T. H. Chan School of Public Health and the Ethical and Scientific Review Committee of Amref Health Africa (AMREF) in Nairobi, Kenya. The study design was registered at socialscienceregistry.org with identification number AEARCTR-0000320.
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