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Narrative Belief Updating

Last registered on April 04, 2025
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Pre-Trial

Trial Information

General Information

Title
Narrative Belief Updating
RCT ID
AEARCTR-0015672
Initial registration date
April 01, 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
April 04, 2025, 10:01 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
Andrea Albertazzi
Affiliation
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Other Primary Investigator(s)

PI Name
Paolo Pin
PI Affiliation
University of Siena
Contact Investigator
PI Name
Marco Stimolo
PI Affiliation
University of Siena
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PI Name
Alessandro Stringhi
PI Affiliation
University of Siena
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Additional Trial Information

Status
In development
Start date
2025-04-02
End date
2026-04-09
Keywords
Behavior, Lab
Additional Keywords
belief updating, Bayesian, experiment, narratives, belief formation, information processing, uninformative signals, Bayes’ theorem
JEL code(s)
C91; D81; D83; D91
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
In this project, we aim to explore how narratives influence the incorporation of new information into individuals’ beliefs. Specifically, we will replicate a classic Bayesian problem in a controlled experiment, where individuals face uncertainty and use new information to update their beliefs about the world. To do this, we will randomly assign participants to one of two conditions. In the baseline treatment, participants will engage with an abstract problem of identifying which urn a series of drawn balls comes from. In the narrative treatment, participants will instead receive a made-up story—framed around identifying a culprit—which mirrors the same uncertainty and signals as the baseline but embeds them in a more emotionally and contextually rich framework. By comparing how participants update their beliefs in these two conditions, we aim to assess whether the presence of a narrative systematically alters the way new informative and uninformative evidence is interpreted.
External Link(s)

Registration Citation

Citation
Albertazzi, Andrea et al. 2025. "Narrative Belief Updating." AEA RCT Registry. April 04. https://doi.org/10.1257/rct.15672-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2025-04-02
Intervention End Date
2026-04-09

Primary Outcomes

Primary Outcomes (end points)
We are interested in if and how a narrative changes the way people update new information. For this reason, we will primarily focus on deviations of beliefs from their Bayesian benchmark. We will do this for both experimental treatments.
We will also look at whether uninformative signals affect belief updating.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
In both treatments, participants will be presented with an initial "story". In the baseline, the story concerns two urns containing balls of three different colours. In the narrative treatment, the story is about two possible culprits. Subjects are asked to state their prior belief about which one between the two urns/culprits is the correct one. Then, participants play 10 rounds in which they receive new information every time. The new information can be in favour of one of the two alternatives or uninformative. The ex-ante probabilities of receiving each piece of new information are public knowledge. Subjects are asked to state their posterior belief in every round upon receiving the new information..
Experimental Design Details
Not available
Randomization Method
At the beginning of each experimental session, a computer will randomly assign each participant to one of the two treatments.
Randomization Unit
The randomization is at the individual level.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
We plan to run 24 lab sessions of 15 subjects each. We will continue collecting data until subjects show up. We plan to collect at least 90 observations per treatment. This means that at least 180 participants must complete the experiment.
In case of funding availability, we will also run an online version of the experiment to increase the robustness of the lab results. In this case, we plan to collect at least 300 observations.
Sample size: planned number of observations
We plan to run 24 lab sessions of 15 subjects each. We will continue collecting data until subjects show up. We plan to collect at least 90 observations per treatment. This means that at least 180 participants must complete the experiment. In case of funding availability, we will also run an online version of the experiment to increase the robustness of the lab results. In this case, we plan to collect at least 300 observations.
Sample size (or number of clusters) by treatment arms
We plan to run 24 lab sessions of 15 subjects each. We will continue collecting data until subjects show up. We plan to collect at least 90 observations per treatment. This means that at least 180 participants must complete the experiment.
In case of funding availability, we will also run an online version of the experiment to increase the robustness of the lab results. In this case, we plan to collect at least 300 observations.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials

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IRB

Institutional Review Boards (IRBs)

IRB Name
Comitato per la RicercA Etica nelle scienze Umane e Sociali – CAREUS
IRB Approval Date
2024-03-04
IRB Approval Number
n. 17/2024
Analysis Plan

Analysis Plan Documents

Analysis plan

MD5: 73ed563530565fdd2de7a15afb6de4cc

SHA1: ade6235eaa7b0b62e61b13138b81c5afd1d702c4

Uploaded At: March 31, 2025