AI-Supported Sexual and Reproductive Health Information and Care-Seeking among Women in India

Last registered on March 16, 2026

Pre-Trial

Trial Information

General Information

Title
AI-Supported Sexual and Reproductive Health Information and Care-Seeking among Women in India
RCT ID
AEARCTR-0018088
Initial registration date
March 12, 2026

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
March 16, 2026, 6:56 AM EDT

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

Locations

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Primary Investigator

Affiliation

Other Primary Investigator(s)

PI Affiliation
Imperial College London

Additional Trial Information

Status
On going
Start date
2026-03-02
End date
2026-09-30
Secondary IDs
Prior work
This trial is based on or builds upon one or more prior RCTs.
Abstract
This study evaluates how access to an AI-based conversational tool affects women’s health-related information-seeking, decision-making, and care-seeking behavior in urban India. The intervention is delivered in the context of sexual and reproductive health, a domain in which stigma, privacy concerns, social constraints, and limited access to timely guidance may shape whether and how women seek support. The study examines whether a private, anonymous, conversational, and always-available tool changes patterns of engagement, knowledge, symptom interpretation, and use of formal and informal sources of care. We conduct a randomized evaluation among women in low-income communities in Mumbai, India, and also study whether additional support changes how participants respond to the tool. The project aims to generate evidence on how AI-based tools affect support-seeking and health-related behavior in settings where privacy, convenience, and responsiveness may be especially important.
External Link(s)

Registration Citation

Citation
Jalota, Suhani and Jasmin Moshfegh. 2026. "AI-Supported Sexual and Reproductive Health Information and Care-Seeking among Women in India." AEA RCT Registry. March 16. https://doi.org/10.1257/rct.18088-1.0
Sponsors & Partners

Sponsors

Partner

Experimental Details

Interventions

Intervention(s)
In this study, women are provided access to a digital health-support tool focused on sexual and reproductive health, delivered through mobile phones. The core intervention is Myna Bolo, an AI-enabled conversational tool that allows women to ask questions and receive responses in a private, anonymous, and on-demand format. The tool is designed to lower barriers to asking sensitive questions by allowing women to seek guidance at any time, without needing to immediately approach a family member, provider, or in-person service.

Depending on study assignment, women may receive different forms of support built around this core tool, including informational messages, access to an interactive text-based chatbot, and/or access to a more proactive voice-based AI system. The intervention is designed to study how privacy, anonymity, responsiveness, conversational interaction, and modality shape women’s information-seeking, support-seeking, and care-seeking behavior in the context of sexual and reproductive health.
Intervention Start Date
2026-03-03
Intervention End Date
2026-09-30

Primary Outcomes

Primary Outcomes (end points)
The primary outcomes are:
(1) engagement and health-related information-seeking;
(2) health knowledge and symptom interpretation; and
(3) support-seeking and healthcare utilization.
Primary Outcomes (explanation)
Primary outcomes will be measured using a combination of survey-based measures and administrative data from the intervention platforms.

The first primary outcome family, engagement and health-related information-seeking, will include measures such as whether the participant used the tool where applicable, intensity or frequency of engagement, and whether the participant sought information or guidance for a health concern during the study period.

The second primary outcome family, health knowledge and symptom interpretation, will be constructed from survey questions assessing knowledge of women’s health topics, correction of common misperceptions, recognition or interpretation of symptoms, and understanding of whether and when additional support or care may be needed. Where appropriate, related variables may be standardized and combined into composite indices.

The third primary outcome family, support-seeking and healthcare utilization, will include measures of whether the participant took action in response to a health concern, including use of formal healthcare, telehealth, informal support, online support, or other problem-solving behavior. This family may include indicators such as any attempt to solve a health concern, any formal care use, and specific care channels where applicable. Where multiple measures reflect a common underlying construct, variables may be standardized and combined into summary indices.

Higher values for constructed indices will be coded to reflect more engagement, greater knowledge or more accurate symptom interpretation, and more support-seeking or healthcare utilization. This follows the design documents, which organize outcomes around utilization, health-seeking, knowledge/misperceptions, and related behavioral responses.

Secondary Outcomes

Secondary Outcomes (end points)
Secondary outcomes include attitudes, stigma, and norms related to women’s health; comfort discussing health concerns; perceived privacy and trust in the support channel; agency-related measures; health expenditure and time costs; telehealth take-up; informal care use; condition-specific health issue measures; hemoglobin and anemia indicators; and IFA / iron-pill compliance.
Secondary Outcomes (explanation)
Secondary outcomes will be measured using survey responses, administrative platform data, and, where relevant, linked telehealth or referral records. Some outcomes may be analyzed as individual variables, while others may be standardized and aggregated into summary indices.

Attitudes, stigma, and norms outcomes will be based on pre-specified survey items related to menstrual myths, reproductive-health beliefs, and related social perceptions. Agency-related outcomes will capture whether and how women take action around health concerns and other relevant survey-based dimensions of decision-making or locus of control. Informal care and expenditure outcomes will capture whether women rely on home remedies, chemists, or social networks, and the time or money spent addressing health concerns.

Hemoglobin testing will be treated as an objective secondary outcome measured across arms where feasible, and IFA compliance will be measured with a standardized compliance threshold where appropriate.

Experimental Design

Experimental Design
Participants in this study are randomly assigned to receive different forms of access to an AI-based conversational support tool in the context of women’s sexual and reproductive health in urban India. The tool allows users to ask questions and receive responses through a private, anonymous, and always-available messaging-based interface. Some study arms also receive additional forms of support alongside access to the tool. The intervention is designed to study how AI-based tools affect information-seeking, symptom interpretation, and care-seeking behavior in a setting where privacy, stigma, and convenience may be especially important.
Experimental Design Details
Not available
Randomization Method
Randomization is done by computer at the individual participant level, with eligible women assigned in equal proportions across four study arms before the baseline or activation of any intervention arm. Randomization is done on the listing sample collected before the baseline study.
Randomization Unit
Individual woman / individual participant.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
NA
Sample size: planned number of observations
3,000-4,000 women.
Sample size (or number of clusters) by treatment arms
Around 4,000 women total, allocated equally across four arms: 1,000 control; 1,000 notifications only; 1,000 notifications + text chatbot; 1,000 notifications + text chatbot + proactive voice AI.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
Stanford University Institutional Review Board
IRB Approval Date
2025-12-15
IRB Approval Number
79634
Analysis Plan

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