Don't Throw Your Heart Away: Layperson Study 1
Phase: NA
Conditions: Cardiac Transplant Disorder
Sponsor: Carnegie Mellon University

Don’t Throw Your Heart Away: Layperson Study 1 
NCT04133831 
Last IRB Approval Check-in: January 10 2024 
 
 
 

Study Information 
Title 
Heart Transplant Tradeoff Study: 5-Condition Layperson Study 
Authors 
  
Description 
Publicly available outcome assessments for transplant programs do not make salient that some 
programs tend to reject many of the hearts they are offered, whereas other programs accept a 
broader range of donor offers. We use empirical studies to test whether transplant center 
performance data (i.e. transplant and waitlist outcome statistics) that reflect center donor 
acceptance rates influence laypersons to evaluate centers with high organ decline rates less 
favorably than centers with low organ decline rates. 1000 lay participants will be recruited from 
Amazon Mechanical Turk and randomized to one of five different information presentation 
conditions. Participants will be given an introduction to the donor organ match process, then 
asked to view the table of transplant outcomes corresponding to the condition they were 
randomized to. Each participant is asked to choose between two hospitals: one hospital with an 
non-selective, "accepting" strategy (takes all donor heart offers), and one hospital with a more 
selective, "cherrypicking" strategy (tends to reject donor offers that are less than “excellent” 
quality). In order to identify the decision process that underlies this choice pattern, we will 
examine a putative mediator. Specifically, participants will be asked to rate the extent to which 
they considered patients' chances of getting an excellent heart, avoiding a less-than-optimal 
heart, and getting any type of heart when making their choice between the two hospitals. 
Hypotheses 
Hypothesis 1: When centers must present information on their transplant success rate only, lay 
evaluators will respond by selecting hospitals with higher transplant success. However, if 
information presented on transplant outcomes is stratified by the number and quality of 
donors used, or displayed in addition to total survival rates, then participants will respond by 
selecting hospitals with higher organ acceptance rates rather than the hospital with higher 
transplant outcomes. Hypothesis 1a: Preference for the non-selective transplant center will be 
lower (than for the selective center) in condition 1 (baseline: combined transplant survival only), 
compared to the other 4 conditions. That is, a higher proportion of participants will prefer the 
non-selective center over the selective center in conditions 2, 3, 4, and 5, relative to condition 1. 
Hypothesis 1b: There will be a main effect of viewing total survival, such that in conditions 2 and 
4 (when total survival is displayed), participants will prefer the non-selective center over the 
selective center, relative to the baseline condition 1. Hypothesis 1c: There will be an additional 
main effect of viewing stratified transplant survival, such that in conditions 3 and 4 (when 
transplant survival is stratified by number and quality of donor hearts accepted at each center) 
participants will prefer the non-selective center over the selective center, relative to the 
baseline condition 1. Hypothesis 1d: There will be an interaction effect between total and 
stratified transplant survival, such that when participants view both stratified transplant 
survival and total survival outcomes together, preference for the non-selective center is higher 
relative to preferences at baseline (condition 1), but not higher relative to preferences when 
total survival information is added to the display (condition 2) or stratified transplant survival 

only is displayed (condition 3). Hypothesis 2: There will be an indirect (mediated) effect of 
providing participants with information about stratified transplant survival or total survival; this 
information will lead to higher preference for the non-selective hospital by leading participants 
to think that the chances a patient at either hospital will "get a heart at all" is a more important 
factor in their decision (about which hospital is a better choice for patients). Specifically ratings 
of importance (0-100 continuous scale) for the item "likelihood of getting any heart” will differ 
across conditions 1-4 such that “getting any heart” will be rated lower in condition 1 than in the 
other three conditions. Furthermore, ratings on this item will be associated with choice, such 
that higher ratings will be associated with choice of the non-selective center. Hypothesis 3: 
Participants who view total survival only (condition 5) will show a higher preference for the non-
selective center relative to participants in the baseline combined transplant survival display 
(condition 1) such that the effect of displayed total survival alone will be similar to the effect of 
displaying both stratified transplant survival and total survival outcomes together (as in 
condition 4). 
Design Plan 
Study type 
Experiment - A researcher randomly assigns treatments to study subjects, this includes field or lab 
experiments. This is also known as an intervention experiment and includes randomized controlled trials. 
Blinding 
• 
For studies that involve human subjects, they will not know the treatment group to which 
they have been assigned. 
Is there any additional blinding in this study? 
n/a 
Study design 
We have a between-subjects design in which participants are randomized to one of five 
information conditions. In each condition, they make a choice between two hospitals (one with 
a non-selective donor acceptance strategy, and another with a more selective donor acceptance 
strategy). The first four conditions (1-4) will be included in our main analysis, which is a 2x2 
design with 2 factors (total survival and transplant survival) and 2 levels per factor: (i) Total 
survival: "total not displayed" = reference level, in which only transplant survival rate (and not 
total or waitlist survival) is shown "total displayed" = transplant survival is displayed along with 
the overall survival rate at each center, which is computed from survival rates of both 
transplant and waitlist patients (ii) Transplant survival: "combined": reference level, in which 
transplant survival rate is not stratified by number and quality of donor hearts accepted at each 
center "stratified": transplant survival rate stratified into patients who received excellent donor 
organs and patients who received less than optimal donor organs The additional fifth condition, 
in which only total survival outcomes (and no transplant survival outcomes) are displayed, will 
be included in the study and analyzed separately. 
 
Randomization 

We will use simple randomization, where each participant will be randomly assigned to one of 
the five predetermined conditions. The Qualtrics randomizer function will be used for 
randomization into a condition. 
Sampling Plan 
Existing Data 
Registration prior to creation of data 
Explanation of existing data 
n/a 
Data collection procedures 
Recruitment: 1000 lay participants will be recruited from Amazon Mechanical Turk, an online 
crowdsourcing platform used for testing human intelligence tasks and research paradigms. 
Participants will be recruited via a "HIT" post titled "Healthcare Study (~10 minutes)" described 
as "choosing between heart transplant hospitals based on outcome data (Potential $0.20 
bonus)." They will be recruited for the HIT upon meeting two criteria. (1) 99% HIT approval rate 
or higher (2)1000 or more HITS approved Inclusion criteria: Participants who are already 
qualified mTurk workers with Worker Accounts meeting the above criteria will be asked to 
participate if they confirm the following inclusion criteria in the consent form. (1) 18 years of 
age or older (2) must read and understand the information in the consent form (3) must want 
to participate in the research and continue with the survey (4) must live in United States 
Payment: Participants will be paid $1.33 for completing the survey (raised to $1.43 if one bonus 
question is answered correctly and $1.53 if two bonus questions are answered correctly). 
Exclusion criteria: (1) Participants on mTurk will not be allowed to participate if they fail to pass 
the initial "bot screening", a multiple-choice question that asks, "What phone number should 
you dial when there is an emergency?" The obvious correct response in this screening question 
is "911", so participants who select one of the incorrect responses (i.e. "1-800-ANTIBOT", "1-877-
MTURKER", "123") are filtered out and not allowed to complete the survey. (2) Participants on 
mTurk will be allowed to participate, but excluded from data analysis, if they submit a nonsense 
response to the free-response question which reads, "In your own words, why do you think 
patients should choose the hospital you picked?" This question takes place after the participant 
has viewed the choice stimuli and selected their response. If participants input nonsense in the 
text response box, they will be permitted to complete the survey and paid, but filtered out from 
the data analysis 
Sample size 
Our target sample size is 1000 participants. We expect that this will amount to approximately 
200 participants per condition, although due to the nature of the randomization technique 
used (Qualtrics randomizer function), we may end up with slightly more or slightly less than 200 
per condition.  
Sample size rationale 

Sample sizes were calculated to yield at least 90% power to detect a 15 percentage point 
difference (e.g., 45% vs. 60%) between baseline condition 1 and the other 4 conditions, with 
α=0.05 (GPower 3.1.9.4).  
Stopping rule 
Participants will be recruited until a sample size of 1000 is achieved.  
Variables 
Manipulated variables 
We will manipulate how transplant center outcomes are presented. Different components of 
the same outcome statistics for two transplant centers will be varied over five different 
conditions. (1) Condition 1 ("baseline" condition): view only combined transplant survival (e.g. 
transplant survival rate not stratified by number and quality of donor hearts accepted at each 
center) (2) Condition 2: view combined transplant survival + total survival (e.g. overall survival 
rate at each center, computed from survival rates of both transplant and waitlist patients) (3) 
Condition 3: view only stratified transplant survival (e.g. transplant survival rate stratified into 
patients who received excellent donor organs and patients who received less than optimal 
donor organs) (4) Condition 4: view stratified transplant survival + total survival (5) Condition 5: 
view only total survival The first four conditions (1-4) will be included in our main analysis, which 
is a 2x2 design with 2 factors (total survival and transplant survival) and 2 levels per factor: (i) 
Total survival: "total not displayed" = reference level, in which only transplant survival rate (and 
no total or waitlist survival) is shown "total displayed" = transplant survival is displayed along 
with the overall survival rate at each center, which is computed from survival rates of both 
transplant and waitlist patients (ii) Transplant survival: "combined": reference level, in which 
transplant survival rate is not stratified by number and quality of donor hearts accepted at each 
center "stratified": transplant survival rate stratified into patients who received excellent donor 
organs and patients who received less than optimal donor organs The additional fifth condition, 
in which only total survival outcomes (and no transplant survival outcomes) are displayed, will 
be included in the study and analyzed separately. 
 
Measured variables 
The outcome variable will be a binary choice between two hospitals: one with a selective donor-
heart acceptance strategy and one with a non-selective donor heart acceptance strategy. 
Participants will respond to the question "Which Hospital is a better choice for patients? Please 
click on one of the two tables below to indicate which hospital is the better choice." Participants 
will choose been two outcome tables featuring the selective and non-selective hospital 
(counterbalanced, such that each of the two choices is equally likely to be presented at top of 
the choice scenario in each condition). The number of participants that choose each hospital 
will be the measured outcome variable used in analyses. On the next page of the survey, 
participants will respond to three mediator questions: "There are many reasons why one 
transplant hospital might outperform another. Which reasons were most important in your 
decision? Please move the slider to indicate how much you considered each of the reasons 
below (0=reason was not important, 100=reason was extremely important)." Participants will 
then move a slider bar (0-100) to indicate the importance of the following three items: (1) 

Patients were more likely to receive an excellent donor heart at the hospital I picked. (2) 
Patients were less likely to receive a marginal donor heart at the hospital I picked. (3) Patients 
were more likely to receive any kind of heart at the hospital I picked. The third item (more likely 
to receive any kind of heart) will be the only variable that is included in the planned mediation 
analysis. 
 
Indices 
No response 
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Analysis Plan 
Statistical models 
To test Hypotheses 1a /1b/1c/1d, we will use a binomial logistic regression analysis. The two 
categorical independent variables will be 'total survival displayed' and 'stratified transplant 
survival'; the model will also include an interaction term of these two variables. The dependent 
variable is binary choice of hospital. -We will test whether the main effect of "total survival 
displayed" is statistically significant and in the predicted positive direction. -We will test whether 
the main effect of "stratified transplant survival" is statistically significant and in the predicted 
positive direction. -We will test whether the interaction effect "total*stratified" is statistically 
significant in the predicted negative direction. To test Hypothesis 2, we will conduct a causal 
mediation analysis to determine whether information display had a mechanistic effect on 
hospital choice through our proposed mediator. We will estimate the average causal mediation 
effect (ACME), average direct effect (ADE), and the total effect. The ACME is the effect of each 
information display condition (total, stratified, or total*stratified) on the outcome of hospital 
choice (selective vs. non-selective), mediated through the hypothesized mediator (the 
importance of "getting any heart" at each hospital when considering the choice). The remaining 
effect of information display on hospital choice that is not mediated through the hypothesized 
mediator represents the ADE. The entire effect of the information display on hospital choice via 
the hypothesized mediator and the direct effect is the total effect. The proportion of the total 
effect that is accounted for by the ACME is called the proportion mediated.{Imai, 2010}. 
Analyses will be performed using the “mediation” package in R (The R Foundation for Statistical 
Computing).{Tingley, 2014}. We will generate 95% confidence intervals by using 1000 bootstrap 
simulations. The unstandardized point estimate of the ACME and its 95% confidence intervals 
will be interpreted. -A significant ACME for "total survival displayed" would suggest that 
displaying total survival works via increasing the perceived importance of "getting any heart" to 
increase preference for the non-selective hospital. If the ACME is non-significant, we will identify 
where the causal path breaks down. -A significant ACME for "stratified transplant survival" 
would suggest that stratifying transplant survival by number and quality of accepted donors 
works via increasing the perceived importance of "getting any heart" to increase preference for 
the non-selective hospital. If the ACME is non-significant, we will identify where the causal path 
breaks down. -A significant ACME for "total survival displayed*stratified transplant survival" 
would suggest that the combination of displaying total survival and stratifying transplant 
survival by number and quality of accepted donors works via increasing the perceived 

importance of "getting any heart" to increase preference for the non-selective hospital. If the 
ACME is non-significant, we will identify where the causal path breaks down. To test Hypothesis 
3, we will use a binomial logistic regression analysis with a contrast test for a difference in effect 
size between conditions 4 and 5. 
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Transformations 
Logistic regression analysis: The categorical predictor "total survival displayed" will be dummy 
coded (0=not displayed, 1=displayed), with 'not displayed' as the reference category. The 
categorical predictor "transplant survival stratified" will be dummy coded (0=not stratified, 
1=stratified), with 'stratified' as the reference category. The outcome variable "choice of 
hospital" will be dummy-coded (0=selective hospital, 1=non-selective hospital). The reference 
category is 'selective hospital'. Mediation analysis: The categorical predictor "total survival 
displayed" will be dummy coded (0=not displayed, 1=displayed), with 'not displayed' as the 
reference category. The categorical predictor "transplant survival stratified" will be dummy 
coded (0=not stratified, 1=stratified), with 'stratified' as the reference category. The categorical 
interaction term "total survival displayed*transplant survival stratified" will be dummy coded 
(0=total and stratified information not displayed together, 1=both total and stratified 
information displayed together), with 'both' as the reference category. The continuous mediator 
variable "get any heart" will be mean-centered for each analysis. The outcome variable "choice 
of hospital" will be dummy-coded (0=selective hospital, 1=non-selective hospital). The reference 
category is 'selective hospital'. 
Inference criteria 
We will use the standard p=0.05 criteria for determining if the results are significantly different 
from those expected if the null hypothesis were correct. 
Data exclusion 
(1) Participants on mTurk will not be allowed to participate if they fail to pass the initial "bot 
screening", a multiple-choice question that asks, "What phone number should you dial when 
there is an emergency?" The obvious correct response in this screening question is "911", so 
participants who select one of the incorrect responses (i.e. "1-800-ANTIBOT", "1-877-MTURKER", 
"123") are filtered out and not allowed to complete the survey. (2) Participants on mTurk will be 
allowed to participate, but excluded from data analysis, if they submit a nonsense response to 
the free-response question which reads, "In your own words, why do you think patients should 
choose the hospital you picked?" This question takes place after the participant has viewed the 
choice stimuli and selected their response. If participants input nonsense in the text response 
box, they will be permitted to complete the survey and paid, but filtered out from the data 
analysis. In addition, two attention checks will be used. The data will be analyzed with all 
participants, and with only the participants who pass both of these attention checks.  
Missing data 
If a participant does not complete the entire survey, they will not be included in the analysis. 
Exploratory analysis 
No response 

Other 
Other 
No response