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Field
Last Published
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Before
February 02, 2026 03:51 PM
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After
June 29, 2026 11:54 AM
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Intervention (Public)
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Before
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.
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After
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.
We are running a follow-up intervention with 336 treatment group students who consented to MindMitra during the first round of deployment. We use these sign-ups to predict take-up in the control group. We keep the predicted users in the control group with above median prediction (logit). We then randomly select 336 control group students. We offer both the treatment and control group students a free introductory online session with three therapists.
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Intervention End Date
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Before
March 04, 2026
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After
March 11, 2026
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Primary Outcomes (End Points)
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Before
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).
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After
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).
For the follow-up therapist intervention, we are interested in the following outcomes:
1. Do they click on the Calendly links of any therapist (we will include this as an outcome variable if the majority of students' email accounts do not block this feature)?
2. Do they book a session?
3. Do they show up for the booked session?
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Experimental Design (Public)
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Before
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.
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After
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.
We move to an individual randomization for the follow-up therapist intervention.
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Planned Number of Observations
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Before
4,452 students
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After
4,452 students. We rely on self-administered surveys and will do our best to reach all students who filled out the Baseline survey. However, some students have shared fake email addresses and phone numbers, which has led to uncertainty about the final sample size.
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Sample size (or number of clusters) by treatment arms
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Before
90 control classrooms and 143 treatment classrooms
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After
90 control classrooms and 143 treatment classrooms. For the follow-up therapist intervention, we use the number of sign-ups (336) in the main intervention and select an equal number of students from the control group.
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Intervention (Hidden)
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Before
The main intervention gives students access to an AI-powered chatbot called MindMitra (meaning “friend” in Hindi). 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. Classrooms are randomized into either a control group or a treatment group. Students in control classrooms receive no access to the chatbot during the initial intervention period.
Students in treatment classrooms receive four weeks of access to MindMitra, beginning at the start of the spring semester. Each treated student receives a personalized login code. To encourage initial take-up and sustained engagement, all treated students are offered: 1) a sign-up incentive of INR 100 upon first registration, and 2) an engagement incentive of INR 100 for using the chatbot for at least 15 days.
Within treatment classrooms, students are further cross-randomized at the individual level into two additional intervention components designed to study mechanisms affecting adoption and engagement:
Alumni Endorsement (Role-Modeling Intervention)
Some students receive messages indicating that both male and female alumni from their university have used or support mental health care and therapy. These endorsements are intended to normalize help-seeking behavior, reduce perceived stigma, and lower the social cost of first use.
Engagement Streaks (Habit Formation Intervention)
Some students see a visible “streak” feature that tracks consecutive days of meaningful chatbot interaction (defined as more than one text per day). The streak is displayed in a scoreboard-style format to encourage repeated engagement and habit formation.
Students may receive neither, one, or both of these features depending on random assignment.
The intervention lasts for an initial four-week period, at the end of which students complete a midline survey. Following midline data collection, treatment-group students regain access to MindMitra for the remainder of the semester, allowing the study to observe longer-term engagement patterns and downstream outcomes.
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After
The main intervention gives students access to an AI-powered chatbot called MindMitra (meaning “friend” in Hindi). 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. Classrooms are randomized into either a control group or a treatment group. Students in control classrooms receive no access to the chatbot during the initial intervention period.
Students in treatment classrooms receive four weeks of access to MindMitra, beginning at the start of the spring semester. Each treated student receives a personalized login code. To encourage initial take-up and sustained engagement, all treated students are offered: 1) a sign-up incentive of INR 100 upon first registration, and 2) an engagement incentive of INR 100 for using the chatbot for at least 15 days.
Within treatment classrooms, students are further cross-randomized at the individual level into two additional intervention components designed to study mechanisms affecting adoption and engagement:
Alumni Endorsement (Role-Modeling Intervention)
Some students receive messages indicating that both male and female alumni from their university have used or support mental health care and therapy. These endorsements are intended to normalize help-seeking behavior, reduce perceived stigma, and lower the social cost of first use.
Engagement Streaks (Habit Formation Intervention)
Some students see a visible “streak” feature that tracks consecutive days of meaningful chatbot interaction (defined as more than one text per day). The streak is displayed in a scoreboard-style format to encourage repeated engagement and habit formation.
Students may receive neither, one, or both of these features depending on random assignment.
The intervention lasts for an initial four-week period, at the end of which students complete a midline survey. Following midline data collection, treatment-group students regain access to MindMitra for the remainder of the semester, allowing the study to observe longer-term engagement patterns and downstream outcomes.
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