How Value Co-Creation Enable AI Video Interventions in Healthcare

Last registered on April 06, 2026
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Pre-Trial

Trial Information

General Information

Title
How Value Co-Creation Enable AI Video Interventions in Healthcare
RCT ID
AEARCTR-0018265
Initial registration date
April 01, 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
April 06, 2026, 7:58 AM EDT

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

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Primary Investigator

Name
Zhensheng Li
Affiliation
Anhui University of Finance and Economics
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Other Primary Investigator(s)

Additional Trial Information

Status
On going
Start date
2026-03-01
End date
2026-06-30
Keywords
Health
Additional Keywords
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This study focuses on the impact of healthcare short-form videos on healthcare quality. It aims to design AI-generated short videos and a patient-customized AI video intervention model for healthcare delivery. We propose an intervention-based field experiment conducted in partnership with a major hospital in China and a leading AI technology firm to evaluate the impact of different interventions on health information dissemination and patient recovery outcomes.
External Link(s)

Registration Citation

Citation
Li, Zhensheng. 2026. "How Value Co-Creation Enable AI Video Interventions in Healthcare." AEA RCT Registry. April 06. https://doi.org/10.1257/rct.18265-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2026-05-01
Intervention End Date
2026-05-31

Primary Outcomes

Primary Outcomes (end points)
Following a one-month intervention period, we will assess two categories of outcome measures. First, to capture the impact of AI-generated video interventions on operational outcomes in healthcare delivery, we will measure patient recovery status, operationalized as the 30-day hospital readmission rate. Second, to evaluate the effect of AI-enabled value co-creation on health information dissemination, we will assess patient engagement levels, measured through video view and sharing metrics, as well as the adoption rate of the intervention protocol.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
This study will propose an intervention-based field experiment. Specifically, we will recruit chronic disease patients and randomly assign them to one of four experimental conditions: (1) Standard Care Control Group: Patients receive conventional follow-up care through routine clinical consultations during their recovery process, serving as the baseline comparator. (2) Practitioner-Generated Video Group: Practitioners create and regularly distribute health-focused short videos to patients, replacing traditional follow-up communications. (3) AI-Generated Video Group: Practitioners leverage AI video tools to generate personalized, high-fidelity digital avatars for content creation, which is then disseminated to patients. (4) AI-Co-Created Video Group: Patients actively participate in the content creation process by interacting with a video interface, enabling them to co-create AI-generated short videos with their practitioners based on individual preferences (e.g., avatar appearance, communication style). Following a one-month intervention period, we will assess specific indicators related to short-video dissemination and patient recovery.
Experimental Design Details
Not available
Randomization Method
The subjects were stratified and grouped by computer based on their characteristics.
Randomization Unit
Individual
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
The subjects will be randomly divided into 4 groups to ensure that their basic characteristics have no significant impact on the main results.
Sample size: planned number of observations
240-320 individuals.
Sample size (or number of clusters) by treatment arms
Standard Care Control Group: 60-80 individuals. Practitioner-Generated Video Group:60-80 individuals. AI-Generated Video Group: 60-80 individuals. AI-Co-Created Video Group: 60-80.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
The First Affiliated Hospital of Bengbu Medical University
IRB Approval Date
2026-03-31
IRB Approval Number
N/A
Analysis Plan