Improving Immigrant Mental Health through a Digital App

Last registered on April 16, 2024
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Pre-Trial

Trial Information

General Information

Title
Improving Immigrant Mental Health through a Digital App
RCT ID
AEARCTR-0013303
Initial registration date
April 09, 2024

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
April 16, 2024, 2:41 PM 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

Name
Raissa Fabregas
Affiliation
University of Texas - Austin
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Other Primary Investigator(s)

PI Name
Antonia Vazquez
PI Affiliation
The University of Texas at Austin
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PI Name
Manuela Angelucci
PI Affiliation
The University of Texas at Austin
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Additional Trial Information

Status
In development
Start date
2024-05-01
End date
2026-05-01
Keywords
Behavior, Health
Additional Keywords
mental health, immigrant integration
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This study will experimentally examine the impacts of offering access to an AI-based emotional well-being and mental health phone app to low-income Hispanic immigrants in the U.S. The app offers a chatbot to deliver psychological support based on cognitive-behavioral therapy (CBT) techniques, among other tools.
External Link(s)

Registration Citation

Citation
Angelucci, Manuela , Raissa Fabregas and Antonia Vazquez. 2024. "Improving Immigrant Mental Health through a Digital App." AEA RCT Registry. April 16. https://doi.org/10.1257/rct.13303-1.0
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Experimental Details

Interventions

Intervention(s)
This study will experimentally assess the effects of offering access to an emotional well-being and mental health phone application, which includes an AI-powered chatbot, among Hispanic immigrants in the United States. Additionally, we will examine the impact of incentives in promoting adoption of the app.
Intervention Start Date
2024-05-20
Intervention End Date
2025-01-01

Primary Outcomes

Primary Outcomes (end points)
Symptoms of depression, anxiety, and stress, measured by the PHQ-8, GAD-7, and PSS.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
1. Parental expectations and aspiration about children’s educational attainment.
2. Migrant remittances.
3. Social connectedness and integration: integration into the U.S. (questions on social links with natives, general knowledge about US, knowledge about how to use public services), revealed-choice measures of their demand to invest in learning English (by giving them a choice between access to language apps or cash).
4. Labor outcomes: employment status,earnings, and, absenteeism

Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Access to the premium version of the app and the duration of access will be randomized among eligible individuals.

Experimental Design Details
Not available
Randomization Method
Randomization to be done in office by a computer
Randomization Unit
individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
2,100 individuals
Sample size: planned number of observations
2,100 individuals
Sample size (or number of clusters) by treatment arms
We will work with a total sample of 2,100 individuals. Individuals will be assigned to a treatment group (1,400) or a control group (700). Within the treatment arm, individuals will be cross-randomized to either receive access to the app for 2 months or 4 months (700 per group) and to receive incentives for app use (932) or not (468).

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
For pooled specifications with 1,400 individuals in the treatment arm and 700 in the control, we are powered to detect MDEs of 0.13 s.d. between treatment and control arms (power= 0.8, alpha value = 0.05). With a take-up of 90%, this would translate to MDEs of 0.14 s.d. and with a take-up of 80% to MDEs of 0.15 s.d. For comparisons between subtreatment arms for length (each n=700) we will be able to detect differences of 0.15 s.d. and for comparisons between incentives and no-incentives we will be able to detect differences of 0.16 s.d.
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
The University of Texas at Austin
IRB Approval Date
2024-03-25
IRB Approval Number
STUDY00005337
Analysis Plan

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