Suspicion and Communication

Last registered on December 06, 2023


Trial Information

General Information

Suspicion and Communication
Initial registration date
November 22, 2023

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
December 06, 2023, 7:49 AM EST

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


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Primary Investigator

University of Potsdam

Other Primary Investigator(s)

PI Affiliation
University of Potsdam
PI Affiliation
University of Potsdam

Additional Trial Information

In development
Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
In this paper, we study how communication shapes suspicion. We propose an experimental Sender-Receiver setup where Senders have a low probability of having misaligned incentives with Receivers. We focus on the impact of open communication on the Receivers' suspicion, i.e., the deviation from the Senders' recommendation. Open communication might enhance or offset suspicion. On the one hand, communication may reassure Receivers that their Sender is truthful and trustworthy. On the other hand, they might give their suspicion more consideration or react to suspicious messages from the Sender, such that suspicion intensifies as a result of open chat. We aim to disentangle these effects by looking at suspicion in combination with the text analysis of chat logs.
External Link(s)

Registration Citation

Bruttel, Lisa, Friedericke Fromme and Vasilisa Petrishcheva. 2023. "Suspicion and Communication." AEA RCT Registry. December 06.
Experimental Details


Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
Suspicion (from 0 to 10)
Primary Outcomes (explanation)
We define suspicion as the Receiver's deviation from the recommendation given by their matched Sender. The more the Receiver diverges from what the Sender has recommended, the more suspicious they are.

Secondary Outcomes

Secondary Outcomes (end points)
1. Sender's recommendation.
2. Receiver's choice to what degree to follow the Sender's recommendation.
Secondary Outcomes (explanation)
To define suspicion as described above, we need the following two variables.
1. Sender's recommendation. The Sender has to make a binary recommendation from two options.
2. Receiver's choice to what degree to follow the Sender's recommendation. The Receiver can make one or two continuous choices between two options (0-10). We explain the details in the "Experimental design" section.
In addition to the presence or absence of open communication (treatment variation, see details in the ''Experimental design'' section as well), we will also look at the communication characteristics, i.e., use the chat logs.

Experimental Design

Experimental Design
People are randomly matched into pairs and assigned one of two roles: Sender and Receiver (Called persons A and B in the experiment). Each player observes two boxes on their screen. One of the boxes is red, the other box is blue. It is common knowledge that each one of these two boxes contains 10 identical cards. Each card gives a certain amount of points to the Sender and a certain amount of points to
the Receiver. Importantly, the Sender can observe what points are written on the cards in the two boxes while the Receiver cannot.

In the instructions, we explain to both players that the two boxes can contain the following cards:
"With a probability of 75%, i.e., on average in 3 of 4 cases,
one of the boxes contains 10 cards that each give
10 points to person A and 10 points to person B,
and the other box contains 10 cards that each give
15 points to person A and 15 points to person B.
With a probability of 25%. i.e., on average in 1 of 4 cases,
one of the boxes contains 10 cards that each give
10 points to person A and 10 points to person B,
and the other box contains 10 cards that each give
20 points to person A and 0 points to person B."

First, person A will be asked to recommend to person B one of the two boxes to pick 10 cards from. They can either recommend the blue or the red box.''

The Sender is asked which one of the two boxes to recommend to the Receiver. The recommendation of the Sender is not binding and is displayed to both players for the remainder of the experiment. The Receiver then has to choose how many cards to pick from which box. They are aware that they will pick 10 cards in total.


We have a between-subject design with two treatments: NOCOMM and COMM.

In both treatments, the Sender recommends one of the boxes to the Receiver. The Receiver observes the recommendation and makes their choice of 10 cards (from all cards from the red box to all cards from the blue box, with any possible integer combination in between).

In COMM, both matched participants additionally enter an open chat *after* the Sender has made the recommendation and *after* the Receiver has made their first (preliminary) choice. The Sender is not informed about the Receiver's choice of cards. The Receiver thus makes their second choice during/after the communication. Both players are informed that the Receiver will have the opportunity to revise their choice. This experiment aims to compare how participants' suspicion changes with and without communication. We include the first choice in COMM to have additional information on what *exact aspects* of communication affect suspicion: the anticipation (i.e., the fact) of communication versus the contents thereof. In COMM, only the second choice is incentivized.


1. Participants read general instructions and answer control questions.

2. The Sender recommends one of two boxes.

3. The Receiver observes the Sender's recommendation.

4 The Receiver enters in integers how many cards to pick from which box. This choice is not revealed to the Sender.

5 (COMM). Participants enter an open chat. On the same screen, the Receiver enters in integers how many cards to pick from which box.

6. We elicit beliefs. Belief elicitation for the Sender is "How many cards do you think the other person has drawn from the red (blue) box?" based on whether they recommended a red (blue) box. Belief elicitation for the Receiver is
"Based on your subjective estimation - what points do you think were in the two boxes?" and "Please tell us, how likely you think it is that the other person has recommended the box with cards giving each one of you 10 points per card."

7. Participants fill out the questionnaire.


We formulate the following hypotheses.
First of all, we need to establish:

Hypothesis 1 (Suspicion). Without communication, Receivers significantly deviate from the Senders' recommendations, i.e., display significant levels of suspicion.
The focus of the paper is the impact of communication on suspicion. Two possible countervailing effects may play a role. On the one hand, communication might be beneficial, i.e., increase Senders' trustworthiness such that suspicion decreases. On the other hand, communication might result in more suspicion by making Senders' potentially misaligned incentives more salient and leading Receivers to think more about Senders' motives. Alternatively, the Sender might communicate in a way that raises suspicion, e.g., by making contradicting statements or by not giving satisfactory answers to questions by the Receiver. We, therefore, formulate a two-sided hypothesis on the difference between suspicion in NOCOMM and suspicion in COMM in the second, final decision of the Receiver.

Hypothesis 2 (Communication effect on suspicion). With communication, Receivers deviate more or less from the Senders' recommendations.
To disentangle these effects, we will use the within-subject differences in the Receivers' level of suspicion before and during/after the chat. Furthermore, we will analyze the communication content. We expect that a high level of suspicion/negativity in the chat will correspond to higher levels of suspicion in terms of the Receivers' choices and vice versa.


In preparation for this experiment, we conducted a pretest where in 100% of cases one box contains (10,10) payoffs and the other box contains (12,12) payoffs. The pretest ensures us that the noise generated by subjects' confusion and/or misunderstanding of the instructions is minimal and hence the Receivers' deviations from the Senders' recommendations indeed capture suspicion. We collected 15 independent observations (30 subjects). On average, Receivers deviated by less than one card out of ten. Importantly, 73.3% of Receivers did not deviate at all. We specifically invited newly recruited subjects who never participated in the experiments before to document the upper bound of noise in participants' behavior.

Due to the independent data structure, we will rely on two-sided Mann-Whitney U tests and regression analyses to test the hypotheses described above. For the non-parametric tests, we will use a matched pair of subjects as the unit of observation. We will analyze communication content to shed further light on communication effects on suspicion in humans. We plan to use (unsupervised) machine learning methods to analyze chat data. The specific computation method depends on the characteristics of actual data (e.g., length of the messages, number of topics within the messages, variance across the messages, etc.). Furthermore, we plan to use the regression analysis to account for the communication characteristics.
Experimental Design Details
Not available
Randomization Method
Randomization is done in the experimental laboratory by letting participants draw a cubicle number. Additionally, participants are randomly assigned the role of Senders and Receivers. Matching participants in pairs is random as well. Participants are randomly assigned to one of the two treatments.
Randomization Unit
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
100 pairs of individuals. Each matched pair of participants is considered as one independent observation.
Sample size: planned number of observations
100 pairs
Sample size (or number of clusters) by treatment arms
We will collect 40 independent observations per group in treatment NOCOMM and 60 independent observations per group in treatment COMM, i.e., (60+40)x2=200 individuals in total.

We choose to collect more observations in COMM than in NOCOMM to allow for heterogeneity analysis for different communication clusters. Having 60 independent observations allows us to have, if necessary, more than two clusters.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
With 40 observations in the NOCOMM treatment and 60 observations in the COMM treatment, alpha = 0.05 and pi = 80\%, we get d = 0.591 as the minimum detectable effect size.

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number