Nudging in complex environments

Last registered on August 23, 2022

Pre-Trial

Trial Information

General Information

Title
Nudging in complex environments
RCT ID
AEARCTR-0007932
Initial registration date
November 16, 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
November 21, 2021, 3:29 PM EST

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

Last updated
August 23, 2022, 8:52 AM EDT

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

Locations

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Primary Investigator

Affiliation
Aarhus University

Other Primary Investigator(s)

PI Affiliation
Aarhus University
PI Affiliation
Aarhus University

Additional Trial Information

Status
In development
Start date
2021-11-18
End date
2022-12-31
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
We study the effects of nudges in complex environments using a novel experimental approach based on a computer game. The game environment allows us to expose subjects to a complex environment and to study a range of novel questions. First, how effective are reminder nudges for getting people to change targeted behaviors in the short run? What effects do these nudges have on non-targeted behaviors — do (positive or negative) spillovers on other behaviors occur? What are the effects of implementing multiple nudges at the same time? Can nudges foster habit formation to create lasting behavior change even when nudges are withdrawn? We study these questions using the specific context of a home cooking situation. To avoid food borne illness, when cooking at home, people need to know about and apply a range of food safety actions.
External Link(s)

Registration Citation

Citation
Koch, Alexander K, Dan Mønster and Julia Nafziger. 2022. "Nudging in complex environments." AEA RCT Registry. August 23. https://doi.org/10.1257/rct.7932-2.0
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Experimental Details

Interventions

Intervention(s)
Subjects play through a series of modules of a computer game that is about preparing food in a home kitchen setting. The goal of the game is to prepare a dish under hygienic circumstances, subject to time pressure and disturbances. We measure performance in the game based on a number of important food safety actions. Subjects are recruited on the crow working platform Prolific.
Intervention Start Date
2021-11-18
Intervention End Date
2022-11-30

Primary Outcomes

Primary Outcomes (end points)
The number of correctly applied important food safety actions (IFSA).
Primary Outcomes (explanation)
IFSAS are actions that the decision maker takes at pre-defined check points (when this check point is reached for the first time in a recipe). For each recipe, there are 12 or 13 IFSAs (every 2nd recipe on average has the bread dropping to the floor when a decision maker tries to put it on the cutting board), which are the following:
1. Wash hands at start of recipe
2. Rinse vegetable/fruit
3. Wash hands after raw chicken handled
4. Wash hands after unwashed vegetable/fruit handled
5. Clean the knife after raw chicken cut
6. Clean the cutting board after raw chicken cut
7. Clean the knife after vegetable/fruit cut
8. Clean the cutting board after vegetable/fruit cut
9. Clean worktop after chicken cut
10. Clean worktop after vegetable/fruit cut
11. Check with thermometer if chicken reached 74°C
12. Do not rinse raw chicken
13. Throw out dropped bread (only relevant in recipes where bread drops)

Depending on the hypothesis, we distinguish between actions about which the decision maker is reminded in game module 3 (hand washing in Reminder; hand washing, cleaning the worktop, and checking the meat temperature in ManyReminders) and actions about which the decision maker is not reminded. Next to the overall number of correct actions, we also aggregate the correctly applied actions in the respective categories (reminded vs. non-reminded).

Secondary Outcomes

Secondary Outcomes (end points)
We use secondary outcome variables to assess the robustness of our results, explore the mechanisms behind our results, and to conduct further exploratory data analysis.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Our between-subject experiment consists of two studies with three different conditions each (2 treatments, 1 control) and is run online with UK residents using the Prolific crowd working platform. In all conditions, subjects play through a series of modules of a computer game that is about preparing food in a home kitchen setting.
Experimental Design Details
Not available
Randomization Method
Randomization (stratified to achieve gender balance across treatments) done using the randomizer feature of Qualtrics.
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
The treatments are not clustered
Sample size: planned number of observations
We plan for a minimum of 750 individuals who complete both parts of the study. As we expect some attrition between parts 1 and 2 of this two-part study, we plan to initially recruit 1000 individuals. We will continue sampling with random allocation to treatments until one of the following holds: at least 250 individuals completed both parts in every treatment, we exhaust our budget, or we reach January 31, 2022. Additional treatments We again plan for a minimum of 750 individuals who complete both parts of the study. As we expect some attrition between parts 1 and 2 of this two-part study, we plan to initially recruit 1000 individuals. We will continue sampling with random allocation to treatments until one of the following holds: at least 250 individuals completed both parts in every treatment, we exhaust our budget, or we reach November 30, 2022.
Sample size (or number of clusters) by treatment arms
A minimum of 250 individuals in Control, a minimum of 250 individuals in Reminder, and a minimum of 250 individuals in ManyReminders.

Additional treatments
A minimum of 250 individuals in each of the three additional treatments.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Power calculations are based on pilot data for the Control condition. Using the program "pc_simulate" by Burlig, Preonas, and Woerman (2017), we conducted simulation-based power calculations in STATA for ANCOVA regressions with 7 pre-treatment periods and 4 post-treatment periods, a Type-I error rate of alpha=0.01 or alpha=0.05, power 0.8, 1000 simulations per effect size, and assuming pairwise treatment comparisons with 250 observations per treatment (i.e. a total sample size of 500). 1. Total number of correct IFSAs per recipe (also referred to as number of correct actions) - Range {0,1,...,12} or {0,1,...,13} depending on the recipe - Values in pilot for Control and Minimum Detectable Effect Size (MDE): * First four recipes of game module 3: Mean 7.19 (std.dev 3.45) MDE (one-sided): 0.33 (alpha=0.01)/ 0.27 (alpha=0.05) MDE (two-sided): 0.35 (alpha=0.01)/ 0.30 (alpha=0.05) * First four recipes of game module 4: Mean 7.89 (std.dev 2.57) MDE (one-sided): 0.28 (alpha=0.01)/ 0.34 (alpha=0.05) MDE (two-sided): 0.35 (alpha=0.01)/ 0.32 (alpha=0.05) 2. The correct IFSAs per recipe for which a reminder is given in the Reminder treatment (handwashing): - Range {0,1,2,3} - Values in pilot for Control and Minimum Detectable Effect Size (MDE): * First four recipes of game module 3: Mean 1.89 (std.dev 0.93) MDE (one-sided): 0.15 (alpha=0.01)/ 0.12 (alpha=0.05) * First four recipes of game module 4: Mean 2.00 (std.dev 0.71) MDE (one-sided): 0.12 (alpha=0.01)/ 0.09 (alpha=0.05) 3. The correct IFSAs per recipe about which no reminders are given in Reminder (i.e. total number of correct IFSAs – correct handwashing IFSAs) - Values in pilot for Control and Minimum Detectable Effect Size (MDE): * First four recipes of game module 3: Mean 5.89 (std.dev 2.42) MDE (two-sided): 0.23 (alpha=0.01)/ 0.20 (alpha=0.05) * First four recipes of game module 4: Mean 5.89 (std.dev 2.15) MDE (two-sided): 0.29 (alpha=0.01)/ 0.24 (alpha=0.05) 4. The correct IFSAs per recipe for which a reminder is given in the ManyReminders treatment (handwashing, cleaning the worktop, and checking the meat temperature): - Range {0,1,…,6} - Values in pilot for Control and Minimum Detectable Effect Size (MDE): * First four recipes of game module 3: Mean 3.44 (std.dev 1.33) MDE (one-sided): 0.23 (alpha=0.01)/ 0.19 (alpha=0.05) * First four recipes of game module 4: Mean 3.33 (std.dev 1.22) MDE (one-sided): 0.17 (alpha=0.01)/ 0.14 (alpha=0.05)
Supporting Documents and Materials

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IRB

Institutional Review Boards (IRBs)

IRB Name
Human Subject Committee, Cognition and Behavior Lab, Aarhus University
IRB Approval Date
2020-12-14
IRB Approval Number
303
Analysis Plan

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