Generative AI, Digital Skills, and Mental Wellbeing

Last registered on June 16, 2025
View Trial History

Pre-Trial

Trial Information

General Information

Title
Generative AI, Digital Skills, and Mental Wellbeing
RCT ID
AEARCTR-0016225
Initial registration date
June 13, 2025

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
June 16, 2025, 7:38 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

Name
Carol McDonough
Affiliation
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Other Primary Investigator(s)

PI Name
Ben Li
PI Affiliation
Contact Investigator

Additional Trial Information

Status
On going
Start date
2024-03-01
End date
2026-05-30
Keywords
Education, Welfare
Additional Keywords
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This study examines how acquiring generative AI (hereafter, AI) skills influences the effectiveness of broader digital skill development and the mental wellbeing of trainees. The intervention is embedded in a digital training program for disadvantaged populations in Massachusetts. All participants receive baseline instruction in basic digital skills. They are randomly assigned to one of two groups, with only one receiving additional AI training. We aim to evaluate whether exposure to AI training enhances digital learning outcomes and improves mental wellbeing.
External Link(s)

Registration Citation

Citation
Li, Ben and Carol McDonough. 2025. "Generative AI, Digital Skills, and Mental Wellbeing." AEA RCT Registry. June 16. https://doi.org/10.1257/rct.16225-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
This study examines how acquiring generative AI (hereafter, AI) skills influences the effectiveness of broader digital skill development and the mental wellbeing of trainees. The intervention is embedded in a digital training program for disadvantaged populations in Massachusetts. All participants receive baseline instruction in basic digital skills. They are randomly assigned to one of two groups, with only one receiving additional AI training. We aim to evaluate whether exposure to AI training enhances digital learning outcomes and improves mental wellbeing.
Intervention Start Date
2024-03-20
Intervention End Date
2026-05-10

Primary Outcomes

Primary Outcomes (end points)
• Learning effectiveness
• Life satisfaction
• Anxiety measures
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Trainees are randomly assigned to two groups: one receives an additional AI training module, while the other does not. Both groups complete identical modules covering word processing, web browsing, email, cloud storage, online shopping, and digital security.
Experimental Design Details
Not available
Randomization Method
Randomization done by a computer
Randomization Unit
training class
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
45
Sample size: planned number of observations
500
Sample size (or number of clusters) by treatment arms
approximately 220 (treatment) to 280 (control)
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
University of Massachusetts Lowell
IRB Approval Date
2024-02-12
IRB Approval Number
#24-018-MCD-EXM
Analysis Plan