The role of the mother-in-law in the demand for maternal health services: Evidence from a field experiment in India

Last registered on October 18, 2022


Trial Information

General Information

The role of the mother-in-law in the demand for maternal health services: Evidence from a field experiment in India
Initial registration date
August 17, 2021

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
August 19, 2021, 11:11 AM EDT

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

Last updated
October 18, 2022, 2:29 PM EDT

Last updated is the most recent time when changes to the trial's registration were published.


Primary Investigator

Aix-Marseille School of Economics, Aix-Marseille University

Other Primary Investigator(s)

PI Affiliation
University of California, Berkeley

Additional Trial Information

In development
Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
The importance of health information targeting and the role of peers is being increasingly studied in low-and middle-income countries. In traditional societies like those of rural India, women continue to have limited agency over their health and decision-making due to restrictive social norms often imposed by family members such as the mother-in-law, which makes information targeting difficult. In this proposal, we propose a field experiment in the central Indian state of Madhya Pradesh to explore the role of inter-generational bargaining and communication within the household to improve the access of young married women in rural India to family planning and maternal health services. Our preliminary findings suggest that young women are unsure about good reproductive health practices and rely heavily on their mothers or mothers-in-law, who in turn rely on traditional knowledge. With this in mind, we propose randomizing whether health information is given to daughters-in-law (DIL) or mothers-in-law (MIL) and daughters-in-law in a household. Further, to understand the role of the community and peers in upholding traditional practices, we propose two more treatment arms where the information is given to DILs and MILs in groups of either only DILs or a mixed group of DILs and MILs.
External Link(s)

Registration Citation

Chawla, Anushka and Pooja Suri. 2022. "The role of the mother-in-law in the demand for maternal health services: Evidence from a field experiment in India ." AEA RCT Registry. October 18.
Experimental Details


We will conduct a baseline survey with pregnant women and their mothers-in-law. The randomization will be conducted in two steps: 1) villages will be randomly assigned to either a control group or one of two treatment arms: 1) group intervention (info is common knowledge), 2) individual intervention (info is not common knowledge). Further, households in each village in each treatment will be then randomized into one of two treatment arms: 1) information to the daughter-in-law; 2) information to the daughter-in-law and the mother-in-law together. The information would be on the importance of antenatal care and institutional delivery, as well as healthy practices during and after pregnancy. In addition, all treatment households will also receive a phone call reminder reinforcing this message.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
Maternal health outcomes: Number of antenatal care visits, consumption of iron and folic acid tablets
Knowledge and belief outcomes: knowledge of the benefits of antenatal care, beliefs related to the consumption of iron folic acid tablets, attitude towards the demand for maternal health services
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
In this study launched in March 2022, the field team will work with community health workers, the ASHA (Accredited Social Health Activist) to recruit women who are 2-6 months pregnant. A baseline survey will be conducted with the daughter-in-law (DIL) and mother-in-law (MIL) of each participating household, irrespective of treatment. A subset of husbands of the DIL will also be surveyed. We will collect data on background characteristics of the respondents, past pregnancy history, current knowledge and beliefs about maternal health and antenatal care, intra-household decision-making and social networks. We will also collect phone numbers in order to contact the respondents for follow-up surveys.

Once baseline data is collected, villages will be randomized into treatments. Within two weeks of the baseline, DILs or both DILs and MILs will receive health information regarding the importance of ANC visits and institutional delivery, based on their treatment group. In addition, they will also receive information phone call; reminders for ANC visits.

Finally, we will conduct an endline survey after the delivery date of the participating household on a number of ANC visits, knowledge of good maternal health practices, and post-delivery outcomes such as beliefs on birth spacing and vaccinations. Survey responses will be complemented by administrative data on maternal and child health.
Experimental Design Details
Randomization Method
We will randomize villages into treatment and control villages using stratified random sampling. The baseline characteristics to be considered for a balanced assignment are population by caste, literacy rates, presence of or distance to the nearest community health center/hospital, distance to nearest public transport, mobile phone network coverage, village population.
Randomization Unit
Village and household
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
400 villages
Sample size: planned number of observations
We estimate a maximum participant recruitment of 10 pregnant women households per village. Thus, the maximum number of observations should be 4000 households.
Sample size (or number of clusters) by treatment arms
A maximum of 100 villages per treatment group, and 100 villages in the control group.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Institutional Review Boards (IRBs)

IRB Name
ACE Independent Ethics Committee
IRB Approval Date
IRB Approval Number
Analysis Plan

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Post Trial Information

Study Withdrawal

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Is the intervention completed?
Data Collection Complete
Data Publication

Data Publication

Is public data available?

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials