Back to History Current Version

Mapping Narrative Complexity to Comprehension and Transmission of Information

Last registered on January 22, 2026
View Trial History

Pre-Trial

Trial Information

General Information

Title
Mapping Narrative Complexity to Comprehension and Transmission of Information
RCT ID
AEARCTR-0017232
Initial registration date
January 15, 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
January 22, 2026, 6:30 AM EST

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

Locations

Country
United States of America
Region

Primary Investigator

Name
Mustafa Kaba
Affiliation
Koç University
Contact Primary Investigator

Other Primary Investigator(s)

PI Name
Cavit Görkem Destan
PI Affiliation
TED University
Contact Investigator
PI Name
Simay Küçükkolbaşı
PI Affiliation
Vienna University of Economics and Business
Contact Investigator

Additional Trial Information

Status
In development
Start date
2026-01-16
End date
2026-02-28
Keywords
Behavior
Additional Keywords
narratives; causal diagrams, complexity
JEL code(s)
D81; D90; D91; H76; K42
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Understanding how individuals process complex information is crucial for designing effective communication strategies in public policy and economics. While recent research has highlighted the importance of narratives in shaping beliefs and behaviors (Shiller, 2017; Andre et al., 2022), little is known about the specific components that make a narrative complex and how these components affect individuals' comprehension and decision-making. This project addresses this gap by systematically dissecting narrative complexity and investigating its behavioral consequences in a large-scale online survey experiment.
External Link(s)

Registration Citation

Citation
Destan, Cavit Görkem, Mustafa Kaba and Simay Küçükkolbaşı. 2026. "Mapping Narrative Complexity to Comprehension and Transmission of Information." AEA RCT Registry. January 22. https://doi.org/10.1257/rct.17232-1.0
Sponsors & Partners

Sponsors

Experimental Details

Interventions

Intervention(s)
To causally identify the effects of narrative complexity on comprehension and transmission of information, we implement a pre-registered online survey experiment with a nationally representative sample in the US. Participants are randomly assigned to different treatment arms presenting them with narratives of varying complexity in various economically- and politically-relevant settings.

Intervention Start Date
2026-01-16
Intervention End Date
2026-02-28

Primary Outcomes

Primary Outcomes (end points)
Error rates in comprehension questions and tasks.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
- Response times in comprehension questions and tasks.
- Self-reported perceived complexity/difficulty and cognitive uncertainty
- Self-reported effort and attention
- Notes taken by participants while studying the narratives
- Audio messages recorded by participants in the narrative transmission task
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The experiment has a 3x3x2 mixed factorial design to answer this question.

1) Between-subjects factor (x3): Each participant is randomly assigned to one of four complexity levels.
a) Baseline narrative with three variables , b) State complexity narrative v1 (with %50 probability) or v2 (with %50 probability): Baseline narrative + 'one additional variable' (v1) or 'two additional variables' (v2), c) Structure complexity narrative: Baseline narrative + endogeneity.

2) Within-subjects factor (x3): Each participant is presented with narratives in three different domains in randomized order.
a) Fictional setting, b) Production Setting, c) Immigration policy setting.

3) Between-subjects factor (x2): In the 'Immigration policy setting', participants are randomly assigned to either a Democrat-leaning narrative or Republican-leaning narrative.
Experimental Design Details
Not available
Randomization Method
Randomization will be done through the internal randomizer of Qualtrics where the experimental design is implemented.
Randomization Unit
The randomization will be at the individual level.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
No clusters.
Sample size: planned number of observations
1800 to 2000 participants.
Sample size (or number of clusters) by treatment arms
Approximately: 600 participants for baseline narrative, 600 participants for state complexity narrative, 600 participants for structure complexity narrative treatments.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number
Analysis Plan