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The timing and content of moral reminders – An online study of the dynamics of dishonesty
Last registered on September 09, 2020


Trial Information
General Information
The timing and content of moral reminders – An online study of the dynamics of dishonesty
Initial registration date
September 09, 2020
Last updated
September 09, 2020 11:21 AM EDT
Primary Investigator
Other Primary Investigator(s)
PI Affiliation
Additional Trial Information
On going
Start date
End date
Secondary IDs
An increasing body of studies investigates if moral reminders can prevent dishonesty. It has been shown that their effectiveness varies with their content and that they are sent before rather than after actions are taken. However, most studies focus on one-shot decision making. Little is known about the effectiveness of moral reminders across time. Reminding individuals about being honest early on, e.g., when a contract is started, may be ineffective if individuals forget about the reminder. If individuals make multiple decisions, it may be more effective to remind them after they have gathered experience with the task and possibly even gave in to the temptation to cheat. The effectiveness of moral reminders might also increase if it is signaled that observing behavior across multiple instances allows assessing if someone was dishonest. The goal of our study is to investigate how moral reminders send at different times and with different content affect dishonesty. The study will be implemented as an online experiment, participants will be recruited using Amazon Mturk.
External Link(s)
Registration Citation
Le Maux, Benoit and Sarah Necker. 2020. "The timing and content of moral reminders – An online study of the dynamics of dishonesty." AEA RCT Registry. September 09. https://doi.org/10.1257/rct.6416-1.0.
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Experimental Details
Intervention Start Date
Intervention End Date
Primary Outcomes
Primary Outcomes (end points)
Whether a subject reported to have guessed correctly in the cheating game in one round; how many times a subject reported having guessed correctly in the first and last five rounds of the cheating game; how many times a subject reported having guessed correctly in all ten rounds.
Primary Outcomes (explanation)
The five and ten period counts of correct guesses will be constructed by summing the number of times that a subject reported to having guessed correctly in the respective period.
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
In our study, individuals participate in ten rounds of a wheel of fortune game. The wheel of fortune shows the first 6 letters of the alphabet, from A to F. The task is to guess which letter the wheel of fortune will show and report if the guess was correct. In each round, individuals that report “Yes” receive 20ct while those that report “No” receive 0ct. Thus, individuals have a financial incentive to always report that they guessed correctly. As is common in the literature, dishonesty is not observable but can be inferred from deviations from chance. We vary the timing and content of a moral reminder in six treatments (between-subjects design). The study will be implemented online using Amazon Mturk.
Experimental Design Details
The procedure of the experiment is as follows. Before the experiment starts, subjects will have to pass a bot control (captcha) and sign an informed consent form. They will then participate in two games. The first game is a memory game which has the purpose to focus people’s attention on memorizing letters. The second game is the cheating game as described above. Subjects have to answer control questions to assure that they understood the instructions. After the two games, they are asked to fill in a follow-up survey, inquiring their risk aversion, shame and guilt proneness, perception of the game, and socio-demographic information (e.g., age, gender, education, country of origin). After completing all steps of the experiment, they receive a completion code which allows them to collect their payment from Amazon Mturk.
Randomization Method
Randomization done by Qualtrics (survey software)
Randomization Unit
Was the treatment clustered?
Experiment Characteristics
Sample size: planned number of clusters
Design is not clustered
Sample size: planned number of observations
1500 (including 300 from pilot)
Sample size (or number of clusters) by treatment arms
300 (including 50 from pilot)
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB Name
German Association for Experimental Economic Research e.V.
IRB Approval Date
IRB Approval Number
Post Trial Information
Study Withdrawal
Is the intervention completed?
Is data collection complete?
Data Publication
Data Publication
Is public data available?
Program Files
Program Files
Reports, Papers & Other Materials
Relevant Paper(s)