Don't Throw Your Heart Away: Clinician Study 3
Phase: NA
Conditions: Cardiac Transplant Disorder
Sponsor: Carnegie Mellon University

Don’t Throw Your Heart Away: Clinician Study 3 Protocol 
NCT04455893 
Last IRB Check-In: Jan 10 2024 
 

Study Information 
Hypotheses 
Hypothesis 1 When transplant centers present information on their transplant success rate 
only, 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. Thus, preference for the non-selective transplant center (relative to the 
selective center) will be lower in condition 1 (baseline: combined transplant survival only), 
compared to condition 2. That is, a higher proportion of participants will prefer the non-
selective center over the selective center in condition 2, relative to condition 1. Hypothesis 2 
The effect of information condition on choice will be mediated by ratings of the importance of 
getting a heart at all. That is, viewing information about stratified transplant survival will lead 
participants to think that the chance to "get a heart at all" is a more important factor in their 
decision which will in turn be associated with higher preference for the non-selective hospital. 
Specifically, ratings of importance (0-100 continuous scale) for the item "likelihood of getting 
any heart” will be lower in condition 1 than in condition 2. Furthermore, ratings on this item will 
be associated with choice, such that higher ratings will be associated with choice of the non-
selective center. A bootstrapped mediation analysis will test for an indirect effect. Hypothesis 3 
The difference in hospital preference between the treatment (stratified transplant survival) and 
control (combined transplant survival) conditions for the clinician participants will be smaller 
than the analogous difference observed in a previous study of layperson (Amazon Mechanical 
Turk) participants exposed to the same two conditions. In an analysis combining the data from 
the current study and the layperson study from the same two conditions in the previous study, 
we predict a 2 (information condition) x 2 (participant population) interaction, such that that 
effect of information condition is smaller for expert clinicians than for lay people. 
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 two 
information conditions (independent variable). In each condition, they make a choice 
(dependent variable) between two hospitals (one with a non-selective donor acceptance 
strategy, and another with a more selective donor acceptance strategy). Independent variables: 
(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 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) These two conditions will be analyzed for our primary analysis: a 1x2 design with 
2 arms (control arm or combined transplant survival, and experimental arm or stratified 
transplant survival).  
 
Randomization 
We will use simple randomization, where each participant will be randomly assigned to one of 
the two 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 
125 transplant clinical personnel participants will be recruited from the International Society for 
Heart and Lung Transplantation (ISHLT) and the Pediatric Heart Transplant Society (PHTS). 
Participants will be recruited via (1) the ISHLTConnect Discussion Board webpage, (2) the PHTS 
Basecamp Discussion Board webpage and corresponding Listserv, and (3) the PHTS July 2020 
Live Webinar (via Zoom). Inclusion criteria: Participants who are transplant clinical personnel 
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 Payment: Participants 
will be given the option to select a transplant-related charity at the end of the survey that will 
receive a $1.50 donation (anonymously) if they complete the survey. 
 
Sample size 
Our target sample size is 122 participants. We expect that this will amount to approximately 61 
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 61 per 
condition.  
Sample size rationale 
A sample size of 61 per group was calculated to yield at least 90% power to detect a 30 
percentage point difference between conditions (e.g., 35% vs. 65%) with α=0.05 (GPower 
3.1.9.4). 
Stopping rule 
We will stop data collection after the first of the following three scenarios is achieved: (1) 122 
responses collected (2) August 31, 2020 and at least 100 responses collected (3) October 31, 
2020. 

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 two different 
conditions. (1) Condition 1 ("combined" 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 ("stratified" condition): 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) The two conditions will be included in 
our main analysis, which is a 2x1 design with 1 factors (transplant survival) and 2 levels per 
factor: "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 
 
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 do you consider to be higher 
performing? 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 
n//a 
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Analysis Plan 
Statistical models 

To test Hypotheses 1, we will use a binomial logistic regression analysis. The categorical 
independent variable will be 'stratified transplant survival'; the dependent variable is binary 
choice of hospital. -We will test whether the main effect of "stratified transplant survival" is 
statistically significant and in the predicted positive 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 the experimental information display condition (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 "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. To test Hypothesis 3, we will conduct an analysis combining the 
data from the current study and the layperson study from the same two conditions in the 
previous study. We predict a 2 (information condition) x 2 (participant population) interaction, 
such that that effect of information condition is smaller for expert clinicians than for laypeople. 
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Transformations 
Logistic regression analysis: 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 "transplant survival stratified" will be dummy coded (0=not stratified, 
1=stratified), with 'stratified' 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 
n/a 
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