Saving Maternal and Infant Lives with Affordable Technology

Last registered on November 08, 2022

Pre-Trial

Trial Information

General Information

Title
Saving Maternal and Infant Lives with Affordable Technology
RCT ID
AEARCTR-0010356
Initial registration date
November 04, 2022

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
November 08, 2022, 2:54 PM EST

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

Primary Investigator

Affiliation
Georgia State University (formerly)

Other Primary Investigator(s)

PI Affiliation
Georgia State University
PI Affiliation
Khyber Medical University

Additional Trial Information

Status
Completed
Start date
2015-02-06
End date
2018-03-02
Secondary IDs
Prior work
This trial is based on or builds upon one or more prior RCTs.
Abstract
The study seeks to provide access to healthcare information and maternal and infant care services to rural women, a population subset known for low utilization of antenatal care and postnatal care, suboptimal hygiene and nutritional practices, susceptibility to cultural taboos affecting maternal and infant health and preference for traditional remedies of low efficacy over available treatment of ailments affecting their and their infant’s health. Technology will serve as two bridges for rural women. First, it will work as a bridge across low literacy barriers and provide healthcare information in a timely manner to rural women. Voice messages will be readily accessible to women in areas where female literacy is very low. Second, access to healthcare solutions and rural health workers over phone will bridge the barriers to access healthcare, including transport and cultural constraints. In order to study the efficacy of the solution for wider adoption in the public health system in Pakistan, the research will use a randomized controlled trial of application of voice message nudges, cellphone delivered healthcare messages to spur timely action to improve mother and infant health outcomes and document uptake of maternal health services.

The study chooses Pakistan as it has several attributes where such a behavioral economics intervention can be useful. In rural Pakistan, pregnancy-specific healthcare utilization from skilled professionals and facility delivery rates are pretty low. According to the most recent Pakistan Demographic Health Survey 2012-2013, prior to our intervention, more than two-thirds of pregnant women (73%) received at least one antenatal care during their pregnancy; however, only 36% of pregnant women had the recommended at least four antenatal care visits with dramatic differences between urban and rural areas, 62% and 26%, respectively. On the other hand, less than half of births (48%) took place in a health facility, with a wide gap between urban and rural 68% vs. 40%. Likewise, only 44% of rural births were delivered at a hospital or health clinic, whereas the ratio was 71% in urban births. Lastly, while 44% of rural women did not have any postnatal visits in the first two days after birth, the corresponding ratio was only 23% among urban women.

Care-seeking behaviors and pregnancy outcomes among rural Pakistani women are similar to those observed in other developing countries, making our findings immediately relevant to large parts of the world. For example, according to Demographic Health Surveys from 28 African countries,75% of pregnant women received at least one antenatal care, on average; and antenatal care utilization was even less than 50% in some countries such as Zimbabwe, Burkina Faso, and Ethiopia. Moreover, 38% of pregnant women received the recommended four or more antenatal care visits in Africa. Likewise, only 43% of births took place in a facility in sub-Saharan countries, where neonatal mortality rates are the highest in the world Finally, in low-income countries worldwide, only 37% of women received postnatal care within the first two days after birth.

Delayed recognition of pregnancy complications, inadequate antenatal and postnatal care as well as eschewing facility deliveries are among the major factors leading to high maternal and neonatal mortality ratios in South Asia and sub-Saharan Africa However, these deaths could largely be prevented through behavioral modifications to health-seeking behaviors, including antenatal and postnatal care use from skilled professionals and facility deliveries. In this line, our intervention aims to advance pregnancy-related healthcare utilization via informational voice nudges among pregnant women in rural Pakistan with potential applicability to similar populations elsewhere.


Our design aims to test the efficacy of informational nudges in improving maternal health knowledge and care uptake using voice messages as the medium of communication. We manipulate call frequency, message timing, and the provision of small financial incentives. Participants received voice messages for up to 26 weeks, depending on the time of the recruitment. All treatments are implemented at the cluster level to minimize spillover effects across treatment arms. In this village-level cluster randomized controlled trial, we compare the outcomes of the four treatment arms, A, B, C, and D, to the control arm, E. We summarize the experimental design as follows:
• Treatment Arm A: High-Frequency Informational Nudges Timed to Gestational Age. This group received two weekly messages timed to gestational age.
• Treatment Arm B: Low-Frequency Informational Nudges Timed to Gestational Age. This group received one weekly message timed to gestational age.
• Treatment Arm C: Low-Frequency Informational Nudges + Small Cash Incentives. This group received one weekly message timed to gestational age. In addition, at the end of the weekly voice calls pertaining to the maternal healthcare literacy messages, the participants were offered a small financial incentive (20 Rupees) if they agreed to listen to a general health message by pressing ‘1’ on the keypad, displayed in Message Content Appendix B. If they accessed the additional information, it would give them a phone balance transfer of 20 Rupees (~USD 0.20). Therefore, Arm C assesses the value of financial incentives in boosting the efficacy of informational voice nudges.
• Treatment Arm D: Random Order Informational Messages. This group received one message per week in a random order, i.e., the message content was not synchronized to the gestational age.
Our experimental design aims to answer several important questions not explored by large-scale RCTs conducted exclusively in the countryside of poor nations. The key question we investigate is whether and to what extent mobile phone-based informational nudges can help address behavioral impediments to pregnant women's maternity-specific care-seeking in such localities. Relatedly, arms A and B allow us to examine whether high- versus low-frequency informational messages have differential impacts on knowledge and behavioral outcomes.

We hired rural female community health workers, known as Lady Health Workers (LHW), to administer the recruitment protocol to the rural women in the study villages. We deployed them to visit every household in their locality to identify and register pregnant women. In each village (cluster) of the sample, we targeted to reach all the pregnant women who were in the first trimester of pregnancy.
Participation was voluntary and obtained by the use of approved and standard informed consent procedures. Accordingly, a printed informed consent form was read and explained in the local language to the women. Individuals who granted consent were registered. Given that LHWs have been institutionalized and reasonably acceptable in rural Pakistan (Douthwaite and Ward, 2005), we did not face any resistance to participation in our study. Initially, 1556 women were recruited in 403 villages in Pakistan's Chakwal and Swabi districts. Following this, the villages (clusters) were randomly assigned to five arms, four treatment (A, B, C, D) arms, and a control group.
To eliminate the possibility of sample selection bias, we provided free mobile phones to 300 participants who did not have one because our interventions required access to a mobile phone. If any participant had access to another family member’s cellphone, that number was recorded for women who reported that they could receive calls on it. In addition to the phone number of the participants, their preferred times, and days to receive calls throughout the week were recorded to increase the likelihood that women, including those having partial access to shared phones, could listen to the messages.
We managed to register nearly all pregnant women in the first trimester of their pregnancy at the time of recruitment and provided a mobile phone to those who did not have one. Thus, we are confident that our sample is representative of the study population at hand and is scalable to hundreds of millions of women in similar conditions in South Asia and Sub-Saharan Africa.
A baseline survey, aiming to elicit participant demographic information, household characteristics, and maternal history, was administered by LHWs in person to each of the 1556 subjects at the time of recruitment.
Then, to administer data collection at the endline, we contracted Lady Health Visitors (LHVs), trained as skilled birth attendants, to ensure the accuracy of the endline information as more specific information on delivery and conditions around it was needed. The LHVs collected data using an Android cellphone application developed to ensure the accurate and standardized administration of the endline survey. It was successfully administered to 1,399 participants, gathering pregnancy-specific health knowledge and care utilization, such as prenatal care, facility delivery, and postnatal care.
Through our work, we aim to demonstrate that beyond creating the choice of modern maternal care in the close vicinities of pregnant women, women in rural areas need to be equipped with health literacy, without which the available healthcare choices may not be appropriately legible to them. Health literacy is likely to change malformed opinions and manifests healthcare choices in bold relief, allowing women to adopt health behaviors beneficial to them and their newborns. In some ways, health literacy can allow for accurate reading of the choice architecture available to pregnant mothers, otherwise seen through the translucency of free-flowing opinions.
External Link(s)

Registration Citation

Citation
Cyan, Musharraf, Hamid Hussain and Richard Rothenberg. 2022. "Saving Maternal and Infant Lives with Affordable Technology." AEA RCT Registry. November 08. https://doi.org/10.1257/rct.10356-1.0
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Experimental Details

Interventions

Intervention(s)
The intervention comprises informational nudges as recorded messages. The content of the maternal healthcare literacy messages provide information about pregnancy-specific health with a heavy emphasis on proper maternal medical care utilization from skilled healthcare professionals as well as information on diet and hygiene practices. Depending on the timing of recruitment, participants in any of the treatment arms could get up to 26 different messages.

We prepared a second set of voice recordings to provide additional health information to one of the treatment arms. These messages providing information on a broad spectrum of health topics, including infant health in utero, household hygiene, child vaccinations, and infectious diseases. All messages were recorded in local languages and in a female voice.
Participants received voice messages for up to 26 weeks, depending on the time of the recruitment. All treatments are implemented at the cluster level to minimize spillover effects across treatment arms. In this village-level cluster randomized controlled trial, we compare the outcomes of the four treatment arms, A, B, C, and D, to the control arm, E. We summarize the experimental design as follows:
• Treatment Arm A: High-Frequency Informational Nudges Timed to Gestational Age. This group received two weekly messages timed to gestational age.
• Treatment Arm B: Low-Frequency Informational Nudges Timed to Gestational Age. This group received one weekly message timed to gestational age.
• Treatment Arm C: Low-Frequency Informational Nudges + Small Cash Incentives. This group received one weekly message timed to gestational age. In addition, at the end of the weekly voice calls pertaining to the maternal healthcare literacy messages, the participants were offered a small financial incentive (20 Rupees) if they agreed to listen to a general health message by pressing ‘1’ on the keypad, displayed in Message Content Appendix B. If they accessed the additional information, it would give them a phone balance transfer of 20 Rupees (~USD 0.20). Therefore, Arm C assesses the value of financial incentives in boosting the efficacy of informational voice nudges.
• Treatment Arm D: Random Order Informational Messages. This group received one message per week in a random order, i.e., the message content was not synchronized to the gestational age.
Intervention Start Date
2015-04-01
Intervention End Date
2016-05-31

Primary Outcomes

Primary Outcomes (end points)
The first set of outcomes, reflecting maternity-related health literacy, comes from answers to the following questions:
If your pregnant friend suffers from any pregnancy-related complications, under whose supervision would you recommend she deliver? (Possible answers: a = Nurse; b = Traditional birth attendant; c = Lady Health Worker; d = Lady Doctor).

Consider any pregnant women you know who suffered from pregnancy complications last month. Her current test results and reports are normal. Will you recommend that she delivers under the supervision of a traditional birth attendant? (Possible answers: a = Yes; b = No).

If your pregnant friend suffers from any pregnancy-related complications, which of the following hospitals is the best place for the delivery? (Possible answers: a = Nearest health facility; b = Public hospital in the city; c = Private hospital in the city).

Which of the following complications requires hospital delivery? (Possible answers: a = Fever; b = High blood pressure; c = Child pulling legs in the abdomen).

During the initial days of pregnancy, the child’s position was accurate, but now it is noticed that the baby is suddenly repositioned, what should you do first? (Possible answers: a = Nothing should be done; b = Should consult with the traditional birth attendant; c = Should consult with a nurse or lady health worker; d = Should consult with a lady doctor).

Which of the following could be the first nutrition for a newborn? (Possible answers: a = Milk (of any kind); b = Mother’s milk; c = Honey; c = Nothing; e = Any food).

During pregnancy, a proper diet is essential. Whom would you consult for dietary advice? (Possible answers: a = Traditional birth attendant; b = Nurse; c = Lady health worker; d = Lady doctor).

If your pregnant friend does not suffer from any complications, what should she do about [dietary] iron tablets? (Possible Answers: a = Not necessary to take; b = Should take daily; c = Should take once a week; d = Should regularly take for three months; e = should eat mean once a week).
Primary Outcomes (explanation)
Using these questions, we create eight dichotomous maternity-specific health(care) literacy indicators and an index variable, which aggerates these items into a single variable. The first health literacy indicator, Deliver Under SBA, is a dummy variable representing the likelihood of suggesting a friend deliver her baby under the supervision of a skilled birth attendant, i.e., a nurse or a doctor, when she has birth complications. Do Not Deliver Under TBA is set equal to one for respondents who would not recommend a fellow woman to deliver under the supervision of a TBA even if she does not suffer from any current complications. If the respondent recommends hospital delivery to a friend suffering from any pregnancy-related complications, Pregnancy Complications Requires Hospital Delivery is coded equal to one, and it is set equal to zero for those who recommend delivery at the nearest health facility. The dichotomous indicator, High Blood Pressure Requires Hospital Delivery, represents the respondent’s likelihood to choose the correct answer from the available alternatives, i.e., t symptoms of fever, high blood pressure, and child pulling legs. We set Consult SHP for Malposition equal to one if the respondent would recommend a friend to see a skilled healthcare professional (SHP), i.e., maternity nurse or lady doctor, in case the baby is discovered to be repositioned in the womb nearing term, and zero when it is not the case. Breastmilk or Any Milk for Newborn is coded as one for those who answered any type of milk or mother’s milk as the appropriate first nutrition and zero otherwise. Consult SHP for Diet is a binary variable equated to one for participants who would suggest consulting an SHP for pregnancy-related diet, and it is set equal to zero otherwise. Dichotomous Take Iron Supplements Daily captures if the respondent declares advising a friend to consume iron supplements daily even with no pregnancy-related complications. Finally, we construct a Maternal Health Literacy Index, summarizing health knowledge based on the methodology of Anderson (2008). This approach generates a weighted summation of the variables described above by using the inverse covariance matrix, assigning a lower weight to indicators exhibiting higher correlation among each other. We use the standardized values of the index, with a mean of zero and a standard deviation of one, in the analysis.

Secondary Outcomes

Secondary Outcomes (end points)
Our second set of dependent variables represents maternity-specific medical care use and is constructed based on the following endline questions:
Did you visit a skilled healthcare professional for antenatal care? If the answer is yes, who did you visit? (Possible answers: a = Nurse; b = Lady Health Worker; c = Dispenser; c = Lady Doctor).

If you answered yes to the previous question, how many times did you visit skilled medical care professionals for antenatal care? (Possible answers: open-ended)

Where did you deliver your child? (Multiple answers group under home, local hospitals, district public hospitals, and district private hospitals).

After the delivery, did you get a postpartum checkup for the child from a skilled healthcare professional, such as a nurse or lady doctor? (Possible answers: a = Yes; b = No)

Since your child's birth, have you visited a skilled healthcare professional for postnatal care, such as a nurse or lady doctor? (Possible answers: a = Yes; b = No)

Secondary Outcomes (explanation)
By using answers to the first two questions above, Four Plus Skilled Antenatal Visits is coded equal to one for those who visited skilled healthcare professionals for antenatal care at least four times, and it is set equal to zero otherwise. Facility Delivery is a dummy variable indicating whether the birth occurred at a healthcare facility. If the mother visited a skilled healthcare professional after giving birth to get her post-delivery health and recovery screened, we code Postpartum Check-up equal to one, and it is set equal to zero otherwise. The dummy variable, Four Plus Skilled Postnatal Visits, represents whether the child was taken to a skilled healthcare professional at least four times for a post-natal visit. Finally, we also construct the Maternal Healthcare Utilization Index by using the Anderson (2008) method described above. In the analysis, we employ the normalized value of the index to a mean of zero and a standard deviation of one.

Experimental Design

Experimental Design
Our design aims to test the efficacy of informational nudges in improving maternal health knowledge and care uptake using voice messages as the medium of communication. We manipulate call frequency, message timing, and the provision of small financial incentives. Participants received voice messages for up to 26 weeks, depending on the time of the recruitment. All treatments are implemented at the cluster level to minimize spillover effects across treatment arms. In this village-level cluster randomized controlled trial, we compare the outcomes of the four treatment arms, A, B, C, and D, to the control arm, E. We summarize the experimental design as follows:
• Treatment Arm A: High-Frequency Informational Nudges Timed to Gestational Age. This group received two weekly messages timed to gestational age.
• Treatment Arm B: Low-Frequency Informational Nudges Timed to Gestational Age. This group received one weekly message timed to gestational age.
• Treatment Arm C: Low-Frequency Informational Nudges + Small Cash Incentives. This group received one weekly message timed to gestational age. In addition, at the end of the weekly voice calls pertaining to the maternal healthcare literacy messages, the participants were offered a small financial incentive (20 Rupees) if they agreed to listen to a general health message by pressing ‘1’ on the keypad, displayed in Message Content Appendix B. If they accessed the additional information, it would give them a phone balance transfer of 20 Rupees (~USD 0.20). Therefore, Arm C assesses the value of financial incentives in boosting the efficacy of informational voice nudges.
• Treatment Arm D: Random Order Informational Messages. This group received one message per week in a random order, i.e., the message content was not synchronized to the gestational age.
Our experimental design aims to answer several important questions not explored by large-scale RCTs conducted exclusively in the countryside of poor nations. The key question we investigate is whether and to what extent mobile phone-based informational nudges can help address behavioral impediments to pregnant women's maternity-specific care-seeking in such localities. Relatedly, arms A and B allow us to examine whether high- versus low-frequency informational messages have differential impacts on knowledge and behavioral outcomes.
Arm C allows us to gauge whether small financial incentives can improve the effectiveness of informational voice nudges on learning and behavior. By comparing Arms A and B to C, we are able to measure the tradeoffs between call frequency and small financial incentives.
Arm D aims to improve health knowledge without serving as reminder nudges because the message timing is not tied to gestational age. By adding this treatment arm to our interventions, we aim to separate the impact of reminder nudges from the provision of information. Note that as all the voice calls take place during pregnancy, some of them unavoidably coincide with the associated timing of pregnancy or take a few weeks before or after it. Therefore, we acknowledge that Arm D impacts outcomes partly through information and partly through nudging. Having noted this caveat, one may consider Arm D as a customized version of (standard) mass-media-based public health information campaigns as the participants received maternal healthcare literacy messages (once a week) in a random order, i.e., independent of the gestational age.
By comparing Arms A and B to D, we are able to separate the impact of reminder nudges from that of information on care utilization.

Experimental Design Details
Randomization Method
We use computer-based randomization.
Randomization Unit
Unit or cluster is a village. All participants in the village are part of the cluster.
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
403 villages
Sample size: planned number of observations
1556
Sample size (or number of clusters) by treatment arms
Arm A:
299 women
80 villages

Arm B:
318 women
85 villages

Arm C:
280 women
79 villages

Arm D:
328 women
79 villages

Control Arm:
331 women
80 villages
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Our experiment meets power requirements and survives standards validity checks. It has adequate power to detect 13-percentage points minimum effect size on binary outcomes and 0.25 standard deviations for continuous outcomes.
Supporting Documents and Materials

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IRB

Institutional Review Boards (IRBs)

IRB Name
Study has received IRB approval. Details not available.
IRB Approval Date
Details not available
IRB Approval Number
Details not available
Analysis Plan

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Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
Yes
Intervention Completion Date
May 31, 2016, 12:00 +00:00
Data Collection Complete
Yes
Data Collection Completion Date
December 31, 2017, 12:00 +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
Arm A:
264 women
72 villages

Arm B:
278 women
78 villages

Arm C:
254 women
73 villages

Arm D:
298 women
73 villages

Control Arm:
305 women
76 villages

Was attrition correlated with treatment status?
No
Final Sample Size: Total Number of Observations
1399 women
Final Sample Size (or Number of Clusters) by Treatment Arms
Arm A: 264 women 72 villages Arm B: 278 women 78 villages Arm C: 254 women 73 villages Arm D: 298 women 73 villages Control Arm: 305 women 76 villages
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials