Test of Consequence Information on Insurance Choices

Last registered on September 14, 2021

View Trial History

Pre-Trial

Trial Information

General Information

Title

Test of Consequence Information on Insurance Choices

RCT ID

AEARCTR-0008229

Initial registration date

September 13, 2021

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

September 14, 2021, 4:23 PM EDT

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

Justin Sydnor

Affiliation

University of Wisconsin, Madison

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Anya Samek

PI Affiliation

University of California, San Diego

Contact Investigator

Additional Trial Information

Status

Completed

Start date

2016-01-01

End date

2017-12-31

Keywords

Finance & Microfinance

Additional Keywords

Insurance choice, decision aid

JEL code(s)

Secondary IDs

AsPredicted.org Pre-registration Plan 5372

Prior work

This trial does not extend or rely on any prior RCTs.

Abstract

This study investigates the impact of "consequence graphs" on decisions about insurance plans. Participants in our experiments are presented with menus of health insurance options and randomized into different information treatments. In the baseline treatment, participants see "feature-based" information about options, which describe contract features such as premiums, deductibles, and copays. In our primary experimental treatment, participants either or in addition see a "consequence graph", which is a visual representation of the distribution of total financial consequences the individual could expect to have with a give plan. In some of our trials there is a third experimentally assigned treatment condition which combines feature-based information with an expected-spending projection (i.e., projected average) but not the full distribution from the consequence graph. For some of the menus there are dominant options and our primary outcome metric is the share choosing the dominant option under different information displays. In some menus there is no dominant option and we instead investigate simply whether the information treatments lead to different distributions of choices.

External Link(s)

Registration Citation

Citation

Samek, Anya and Justin Sydnor. 2021. "Test of Consequence Information on Insurance Choices." AEA RCT Registry. September 14. https://doi.org/10.1257/rct.8229-1.0

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

Intervention Start Date

2016-01-01

Intervention End Date

2017-12-31

Primary Outcomes

Primary Outcomes (end points)

Choice of dominated health insurance option
Choice of high deductible vs. low deductible health insurance option

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

Secondary Outcomes (explanation)

Experimental Design

This study was conducted with two separate but related experiments.

Experiment 1:
Was conducted at the BRITE Lab at the University of Wisconsin, Madison recruiting a largely university student population.
Subjects choose a preferred health insurance plan in each of 4 menus of options. This set of choices was repeated twice, once under each of our two information treatments, with the order randomized. This randomization allows us to conduct both between-subjects comparisons, by comparing the decisions made under the first information treatment assignment, and within subject analysis comparing across the two sets of decisions.
They were incentivized for their choice by having one of their decisions randomly selected for payment. Payment was based on both a random draw of possible medical bills and the health plan the individual selected.
There were two information treatments: a) feature-based menu (control) and b) consequence-graph display (treatment).
Participants also completed an incentivized question testing their ability to do an insurance calculation and an Eckle-Grossman risk-aversion elicitation.

Experiment 2:
The second experiment was a hypothetical-choice survey experiment conducted with the Understanding America Study panel. This portion of the experiment was pre-registered at AsPredicted.org under pre-registration plan #5372, which can be accessed at https://aspredicted.org/blind.php?x=m9ni37
For this study subjects answered a few questions about their health risks that allowed us to place them into one of 50 health-risk groups. We then randomly assigned subjects to one of three information-treatment groups: a) feature-based table display only (control), b) feature-based table plus consequence graph (primary treatment), c) feature-based table plus expected-spending projection (secondary treatment).
Subjects made choices between a lower-deductible and higher-deductible health plan option in 10 separate menus (i.e., pairs) of options.

Experimental Design Details

Randomization Method

Computerized randomization within the survey/online experiment software.

Randomization Unit

Individual level

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

201 individuals (lab experiment) + 692 individuals (UAS survey) = 893 individuals

Sample size: planned number of observations

201 individuals (lab experiment) + 692 individuals (UAS survey) = 893 individuals

Sample size (or number of clusters) by treatment arms

Lab study: 110 received feature-table for their first display and 91 received the graphical display for their first display.
UAS study: 246 Received the feature-table only, 225 received the feature table plus consequence graph, 221 received the feature table plus expected spending projection.

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Supporting Documents and Materials

IRB