Testing an Online Digital Literacy Intervention to Improve the Ability to Spot Fake News: Evidence from a Large-Scale RCT in India

Last registered on August 21, 2023
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Pre-Trial

Trial Information

General Information

Title
Testing an Online Digital Literacy Intervention to Improve the Ability to Spot Fake News: Evidence from a Large-Scale RCT in India
RCT ID
AEARCTR-0006886
Initial registration date
December 11, 2020

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
December 14, 2020, 10:31 AM EST

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

Last updated
August 21, 2023, 12:58 PM EDT

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

Locations

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Primary Investigator

Name
Prashant Loyalka
Affiliation
Freeman Spogli Institute for International Studies, Stanford University
Contact Primary Investigator

Other Primary Investigator(s)

Additional Trial Information

Status
In development
Start date
2022-08-10
End date
2025-08-31
Keywords
Behavior, Education, Health
Additional Keywords
Fake news, digital literacy, COVID-19, RCT, science
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
While the digital revolution has greatly enhanced access to information for millions, it has simultaneously allowed unscrupulous state and non-state actors to spread misinformation online. Youth are particularly vulnerable to misinformation online or ‘fake news’. Even though they are digital natives, recent research shows that a majority of them cannot distinguish between “sponsored content” and real news. A lack of ability to evaluate information and news online (digital literacy skills) among youth puts them at risk of being misled—this can have an adverse impact on the future of democracy worldwide. In light of this global threat, we explore strategies that improve digital literacy skills. Specifically we test the effectiveness of an educational program designed to improve digital literacy skills by conducting a large-scale randomized controlled trial with approximately 4,000 low and middle-income youth in India. The study will enable us to develop and evaluate tools that will help youth navigate information in the digital age and, in the process, strengthen democracy by ensuring that future voters can identify trustworthy information about social and political issues.
External Link(s)

Registration Citation

Citation
Loyalka, Prashant. 2023. "Testing an Online Digital Literacy Intervention to Improve the Ability to Spot Fake News: Evidence from a Large-Scale RCT in India ." AEA RCT Registry. August 21. https://doi.org/10.1257/rct.6886-1.2
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Online digital literacy intervention
Intervention Start Date
2022-08-25
Intervention End Date
2022-08-31

Primary Outcomes

Primary Outcomes (end points)
Performance on digital literacy (scenario-based) tasks (total and COVID-related)
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Assessment of skepticism of news headlines
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Approximately 4,000 students are randomized 50:50 at the individual-level to either a treatment group (that receives the digital literacy intervention) or a control group. All students participate in a baseline assessment/survey as well as two follow-up assessments/surveys (one week and approximately 4 weeks after the intervention ends).
Experimental Design Details
Not available
Randomization Method
Done in office using Stata.
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
0 clusters
Sample size: planned number of observations
3,869 students
Sample size (or number of clusters) by treatment arms
1934 students in the control group and 1935 students in the treatment group
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
With power set at 0.8 and alpha conservatively set at 0.025 (Bonferonni-adjusted to test for two two-sided hypotheses at the 5% significance level), and with 3,869 individuals divided between two treatment conditions in the randomized experiment, we can estimate minimum detectable effect sizes (MDESs) of 0.085 SDs. These power calculations account for a slight increase in statistical precision gained by controlling for covariates (baseline test score and basic background characteristics including age (years), female (1/0), attended FEA in Delhi (1/0), mother past grade 10 (1/0), father past grade 10 (1/0)—estimated R-squared of 0.3). Given the short duration of the study and the strong ties of FEA with its students, we expect to lose only a small amount of statistical power due to student attrition from baseline to endline surveys (attrition of approximately 5%).
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Stanford University IRB
IRB Approval Date
2019-09-16
IRB Approval Number
51527
Analysis Plan

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