Care on Campus: Understanding and Responding to Student Wellbeing in India

Last registered on February 02, 2026
View Trial History

Pre-Trial

Trial Information

General Information

Title
Care on Campus: Understanding and Responding to Student Wellbeing in India
RCT ID
AEARCTR-0017634
Initial registration date
January 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
January 22, 2026, 6:08 AM EST

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

Last updated
February 02, 2026, 3:51 PM EST

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

Locations

There is information in this trial unavailable to the public. Use the button below to request access.

Request Information

Primary Investigator

Name
Anwesha Bhattacharya
Affiliation
Harvard University
Contact Primary Investigator

Other Primary Investigator(s)

PI Name
Bhavya Srivastava
PI Affiliation
World Bank Group
Contact Investigator
PI Name
Akanksha Aggarwal
PI Affiliation
Indian Statistical Institute, Delhi
Contact Investigator

Additional Trial Information

Status
On going
Start date
2025-09-15
End date
2026-08-01
Keywords
Education, Gender, Health
Additional Keywords
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This pre-analysis plan describes a randomized controlled trial evaluating an AI-powered mental health chatbot among undergraduate students in India’s public universities. Using baseline data from 4,489 students across seven colleges in Delhi, we document a high prevalence of depression, anxiety, and loneliness, and low rates of mental health care-seeking. Classrooms are randomized to a control group or to receive four weeks of access to the chatbot. Within treated classrooms, students are cross-randomized to alumni endorsements and habit-formation streaks. The plan pre-specifies intent-to-treat estimates of the effects of chatbot access and the additional interventions on adoption and engagement, care-seeking behavior, stigma (both own and perceived), willingness to pay for therapy, and trust in AI. Longer-term outcomes include academic performance, aspirations, non-cognitive skills, and gendered agency. We pre-specify hypotheses, outcome measures, power calculations, and an empirical strategy prior to observing treatment effects, providing transparent causal evidence on AI-enabled mental health support in a high-stigma, resource-constrained setting.
External Link(s)

Registration Citation

Citation
Bhattacharya, Anwesha, Akanksha Aggarwal and Bhavya Srivastava. 2026. "Care on Campus: Understanding and Responding to Student Wellbeing in India." AEA RCT Registry. February 02. https://doi.org/10.1257/rct.17634-1.1
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
This study evaluates MindMitra, an AI-powered mental health chatbot designed to reduce barriers to mental health care among undergraduate students in India’s public universities. The intervention is implemented as part of a randomized controlled trial across seven colleges within a large public university in Delhi. This is a web-based conversational chatbot that provides a private, low-cost, and low-friction entry point to mental health support. It is not a diagnostic or clinical tool. Instead, it is designed to help students reflect on emotions, normalize mental health concerns, reduce stigma, and provide information about professional mental health care.
Intervention Start Date
2026-02-04
Intervention End Date
2026-03-04

Primary Outcomes

Primary Outcomes (end points)
Primary outcomes include adoption and engagement with MindMitra, measured by login, frequency of use, number of messages, and return rates. Additionally, we focus on mental health outcomes using psychometric tests (PHQ-4, GAD-4, UCLA-3) and mental health care-seeking behavior, including actual and intended use of professional mental health services (therapists or counselors).
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary outcomes include own and perceived stigma toward peers seeking mental health care. We measure willingness to pay for therapy through a donation game and a discrete choice experiment. We will also measure trust in and acceptance of AI for mental health support. Lastly, we measure changes in gendered agency around marriage expectations, ability to push back on parental expectations, and future academic and job market aspirations.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
This study is a randomized controlled trial among undergraduate students in public universities in Delhi. Classrooms are randomly assigned to either a control group with no access to the intervention or a treatment group that receives access to an AI-powered mental health chatbot (MindMitra) for four weeks. Within treated classrooms, students are cross-randomized at the individual level to receive alumni endorsements, engagement streak features, both, or neither. Outcomes are measured using baseline, midline, and endline surveys, along with chatbot usage data.
Experimental Design Details
Not available
Randomization Method
We randomize using Stata.
Randomization Unit
Randomization is at the cluster level (classrooms) as well as individual level within the treatment clusters.
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
233 classrooms across 7 colleges and 9 majors.
Sample size: planned number of observations
4,452 students
Sample size (or number of clusters) by treatment arms
90 control classrooms and 143 treatment classrooms
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
The study is powered at 80% with a 5% significance level, accounting for classroom-level clustering. For primary care-seeking outcomes, the minimum detectable effect is approximately 4 percentage points, corresponding to about 0.08 standard deviations. For depression outcomes, the study can detect a change of approximately 0.5 points on the PHQ scale.
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Harvard University Area
IRB Approval Date
2025-12-19
IRB Approval Number
IRB25-0395
IRB Name
Monk Prayogshala
IRB Approval Date
2025-09-08
IRB Approval Number
190-025
Analysis Plan

There is information in this trial unavailable to the public. Use the button below to request access.

Request Information