The Effect of Self-awareness on Dishonesty (Wave 2)

Last registered on April 26, 2021


Trial Information

General Information

The Effect of Self-awareness on Dishonesty (Wave 2)
Initial registration date
July 16, 2020

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
July 16, 2020, 3:30 PM EDT

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

Last updated
April 26, 2021, 9:21 AM EDT

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



Primary Investigator

University of Warwick

Other Primary Investigator(s)

PI Affiliation
University of Warwick

Additional Trial Information

Start date
End date
Secondary IDs
This project is a follow-up to an earlier study. In the earlier study (details on we focused on the relationship between self-awareness and dishonesty. We ran an experiment involving around 800 subjects who face different treatments designed to heighten their self-awareness of their own level of honesty. After the treatments subjects played games designed to reveal their level of (dis)honesty. In this follow-up study we intend to follow the basic structure of our earlier study but we will vary the costs and benefits of (dis)honesty in one key experimental task. Our aim is to better understand how different features (such as competition, salience, ego, etc.) alter the costs and benefits of (dis)honesty which in turn alters behavior through interaction with our treatments. In short, we hope to understand the contexts in which self-awareness plays a role in deciding whether to be honest.

Registration Citation

Cibik, Ceren Bengu and Daniel Sgroi. 2021. "The Effect of Self-awareness on Dishonesty (Wave 2)." AEA RCT Registry. April 26.
Experimental Details


We will recruit Amazon MTurk workers who will be randomized among multiple treatments. Each treatment requires the subject to write a description of a real-life event involving honesty or dishonesty which entailed different combinations of benefit and cost to themselves and/or others. There is also a control group who do not write descriptions. After this, they all face a series of tasks designed to reveal attitudes towards honesty. The structure of the basic design is almost identical to that in an earlier study ( however we will be varying the dishonesty task is a very precise way as described in the experimental design section below.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
Honesty, measures of self-awareness (personality, integrity, fairness), other-regarding preferences, text.
Primary Outcomes (explanation)
The key honesty measure will be decisions made during the updated matrix puzzle game (that is described in the experimental design section and the included Analysis Plan in detail) in which subjects have the opportunity to lie. Personality is derived from the Big Five Inventory test. We use a separate questionnaire for integrity and fairness. The main other-regarding preference to be assessed is altruism using a dictator game. We will also analyse the text used in the descriptions to reveal other psychological and linguistic variables relevant to dishonesty and self-awareness.

Secondary Outcomes

Secondary Outcomes (end points)
Demographics, risk preferences.
Secondary Outcomes (explanation)
Basic demographics (gender, age, education, etc.).

Experimental Design

Experimental Design
In the MTurk experiment, we first ask subjects to complete a number of questions that reveal information about their risk preferences, personality and attitudes as well as demographics. Next, we randomize subjects into different groups each of which requires the subject to write a description about a real-life event involving honesty or dishonesty. After this, they all face a task designed to reveal dishonesty. There is also a control group who do not write a description but face the same subsequent task. We also examine the scope for the demand effect. More detail about the tasks and our predictions about behavior are also provided in advance but will become available only on completion of the study.
Experimental Design Details
Here we note details of the design and provide some behavioral predictions and contrast our earlier experiment, which was referred to as wave 1 (and is detailed in and summarized below), with this new experiment, which we refer to as wave 2. There is much more detail provided in the included Analysis Plan. Our earlier experiment (wave 1) included a matrix puzzle task that required subjects to assess the number of pairs that total to 10: and then to report the number of pairs that they saw. They were paid based on the total number reported and were free to lie or tell the truth. In the wave 2 version of the matrix puzzle task, we maintain the same average payment in expectation but apply a mean-preserving spread which gives a bonus to those in the top half of the distribution. This shifts the payoffs in such a way that the psychological cost of lying is reduced in accordance with our hypothesis (which is based on Rabin, JEBO 1994). For the matrix puzzle task, we predict that the changes made in the wave 2 version should reduce the cost of lying and so we would expect an increase in dishonesty compared with wave 1.
Randomization Method
By computer.
Randomization Unit
At the individual level.
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
Sample size: planned number of observations
400-800 subjects.
Sample size (or number of clusters) by treatment arms
100-200 per treatment (there are 3 treatments and one control group)
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Since we have already run one wave we elected to use the average effect size derived from Wave 1, but to adjust it as follows. First, we take the average of the effect sizes of different treatments that we calculated in the first wave of the study. For the matrix task, the average effect size was 0.72. Assuming that the variance of the population in the Wave 2 is the same as the Wave 1 of the study, we expect to observe an effect size of 0.72 in the modified version of the matrix puzzle. Technically this means we need only 32 subjects per treatment. However, last time data cleaning necessitated removing 20% of the data. Second, we wish to maintain comparability with wave 1 which featured two games, one of which featured a much lower average effects size (0.11). Therefore we plan to have 100 subjects per treatment which easily satisfies our initial average effect size calculation, then, after gaining a better idea of the variance of the underlying Wave 2 population (which might differ from Wave 1), we will potentially follow up with a larger sample size (rising to 200) if needed.

Institutional Review Boards (IRBs)

IRB Name
Internal Department of Economics Approval Process
IRB Approval Date
IRB Approval Number
Analysis Plan

Analysis Plan Documents


MD5: ace7173d098756624414db9b87450740

SHA1: b93cfba25e86ba94e9fa20a5de41f2735c8c40af

Uploaded At: July 16, 2020


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Is the intervention completed?
Intervention Completion Date
July 23, 2020, 12:00 +00:00
Data Collection Complete
Data Collection Completion Date
July 23, 2020, 12:00 +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
Clustering at the individual level (see below)
Was attrition correlated with treatment status?
Final Sample Size: Total Number of Observations
1260: 892 in wave 1 (see and 368 in wave 2.
Final Sample Size (or Number of Clusters) by Treatment Arms
Of the 892 in wave 1: 284 in control group, 205 in honesty group, 208 low dishonesty, 195 high dishonesty. Of the 368 in wave 2: 101 in control group, 76 in the honesty group, 104 low dishonesty, 87 high dishonesty.
Data Publication

Data Publication

Is public data available?

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

We provide the first investigation of the relationship between self-awareness and dis-honesty in a multi-wave pre-registered experiment with 1,260 subjects. In the first wave we vary the level of awareness of subjects' past dishonesty and explore the impact on behaviour in tasks that include the scope to lie. In the second wave we vary the degree of competitiveness in one of our core tasks to further explore the interactions between self-awareness, (dis)honesty and competition. We also test for the experimental demand effect in order to rule it out. Our results suggest that in non-interactive tasks, self-awareness helps to lower dishonesty in the future. However, in tasks that are competitive in nature becoming more aware of past dishonesty raises the likelihood of dishonesty in the future. In other words, we show when making people aware of their own past dishonesty can help to reduce dishonesty and when it might back-fire.
Ceren Bengu Cibik and Daniel Sgroi, The Effect of Self-Awareness and Competition on Dishonesty, IZA DP No. 14256, 2020.

Reports & Other Materials