Translational Research to Inform Interventions for Severe Challenging Behavior for Individuals With Intellectual and Developmental Disabilities
Phase: NA
Conditions: Behavior and Behavior Mechanisms
Sponsor: Vanderbilt University

 
 
 
 
 
 
 
 
Translational Research to Inform Interventions for Severe Challenging Behavior for 
Individuals with Intellectual and Developmental Disabilities 
 
PI: Joseph M. Lambert  
OMC 304B 
VU Mailbox: PMB 228 
Ph: (615) 343-0824 
Email: Joseph.m.lambert@vanderbilt.edu 
9/7/2021 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 

Table of Contents: 
 
Study Schema 
1.0 
Background 
2.0 
Rationale and Specific Aims 
3.0 
Inclusion/Exclusion Criteria 
4.0 
Enrollment/Randomization 
5.0 
Study Procedures 
6.0 
Reporting of Adverse Events or Unanticipated Problems involving Risk to 
Participants or Others 
7.0 
Study Withdrawal/Discontinuation 
8.0 
Statistical Considerations 
9.0 
Privacy/Confidentiality Issues 
10.0 
Follow-up and Record Retention 
 
 

Figure 1: Example of burst 
Figure 2: Value estimates derived from demand curve analysis 
1.0 
Background 
 
Extinction describes discontinuation of 
reinforcement that results in decreases in a 
measurable dimension of behavior (e.g., frequency, 
duration; Cooper et al., 2020). Bursts are the most 
common collateral effect of extinction (Ducharme 
& Van Houten, 1994) and are characterized by a 
temporary increase in behavior, relative to baseline 
(see Figure 1; Alessandri et al., 1990; Iwata et al., 
1990; Laws et al., 1971; Lerman & Iwata, 1995). 
Although the general prevalence of bursts can be 
estimated (e.g., Lerman & Iwata), no method exists 
to control their occurrence.  
 
Notwithstanding, control is valuable. Treatments 
of challenging behavior are less effective when they do not include extinction (Fisher, et al., 
1993; Hagopian et al., 1998; Mazaleski et al., 1993; Rooker et al., 2013; & Zarcone et al., 1994). 
However, when problem behavior is dangerous, practitioners may not risk increasing its rate or 
intensity. Thus, extinction is often omitted in the service of safety (and at the cost of efficacy). 
If we understood why bursts occurred, we could proactively work to mitigate their occurrence; 
thereby making extinction a viable treatment option in more settings.  
Available 
evidence suggests 
baseline reinforcement 
parameters influence 
responding (i.e., 
behavior) during 
extinction (Aiken, 
1957; Holton, 1961; 
Nevin et al., 1990; 
Perin, 1942; Siegel & 
Foshee, 1953; Young, 
1966). The reinforcing 
effects of stimuli; however, can be relative and volatile (Baum, 1974; Michael, 1975; Hineline, 
1984; Perone, 2003). Simply put, different reinforcers support different magnitudes/ qualities of 
responding (e.g., Hodos, 1961). Thus, although someone might be willing to share a thought for a 
penny, they are unlikely to build a house for one. This “not all reinforcers are created equal” 
epiphany has inspired scientists to study “value” (i.e., variables which alter the degree to which 
specified consequences support specified outputs). As bursts are likely a product of baseline 
reinforcement parameters, consideration of value is essential to understanding the 
phenomenon. 
 
Concepts in consumer-demand theory (Bickel et al., 2000) may prove useful to this 
analysis. Specifically, in behavioral economics, demand describes the quantity of a given 
commodity (e.g., 10 gallons of gas) an individual consumes at an established price (e.g., 
$2/gallon). When demand is inelastic, consumers work harder (or pay more) as prices increase, to 
maintain baseline levels of consumption. For example, motorists are unlikely to purchase less gas 
if price increases by $0.05. However, demand can become elastic. That is, as price increases, 
consumption begins to share an inverse relation with those increases. In the previous example, 
motorists may eventually purchase less gas and drive to fewer places if the price of a gallon were 
to increase by $5.00. The shift in demand from inelastic to elastic is a point of interest because it 
quantifies commodity (reinforcer) value and helps identify optimal prices. The optimal price, or 
0
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60
Omax
 
FR 1
FR 4
FR 7
FR 10
FR 13
FR 16
FR 19
0
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Pmax
Unit Price
Obtained
Reinforcers
Response
Output
Demand for
commodity at
each unit price
0
20
40
60
Omax
2. Output when 
Unit Price is
Expensive
1. Output when 
Unit Price is
Cheap
 
FR 1
FR 4
FR 7
FR 10
FR 13
FR 16
FR 19
0
2
4
6
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10
a. AO
(additional consumption 
= low value)
b. EO
(Additional consumption
= high value)
Pmax
Hypothetical Demand Curve
Derivative Value Estimates
0
10
20
30
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50
0
10
20
30
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50
Baseline
Extinction
Peak Responding 
in Extinction
Peak Responding in BL
Peak Responding in BL
Burst
No Burst

Figure 3: Predictions 
Pmax, is the price that supports maximum consumer spending (or Omax, see top left panel of 
Figure 2). Prices below Pmax undervalue commodities because consumers would spend more 
than required. Similarly, prices above Pmax are suboptimal because these price points decrease 
the value of the commodity and consumers won’t spend as much to obtain it as they would if 
pricing had been more reasonable. For reasons expanded upon below, the concept of Pmax may 
prove useful for understanding bursts. 
 
Related, demand (defined above) can be used to quantify temporary shifts in value at a 
specified price because the value of additional consumption is decreased as consumption 
approximates demand. Individuals stop “paying” for reinforcers after they have crossed this 
threshold (see bottom panels of Figure 2). Laraway et al. (2003) accounts for this effect by 
distinguishing antecedent events (e.g., deprivation) that temporarily increase value of 
consequences (e.g. access to food) from other antecedent events (e.g., satiation) that work in the 
opposite direction and deplete value. The former is an establishing operation (EO) and the latter is 
an abolishing operation (AO). Using these terms, one might say the value of additional 
consumption is abolished (decreased) the closer consumption gets to demand. By contrast, the 
value of additional consumption is established (increased) when little/no consumption has 
occurred. 
 
Generally, Pmax and demand have not been considered in published treatments of bursts. 
However, as bursts are likely a product of baseline reinforcement conditions, and because value 
can fluctuate according to molar (i.e,. unit price) and molecular (i.e., satiation/deprivation) 
variables (right panel, Figure 2), consumer-demand theory may provide a useful framework from 
which to formulate and test hypotheses relevant to bursts. For example, it is possible that bursts 
are a product of baseline schedules of reinforcement (i.e., “unit prices”), relative to Pmax. 
Specifically, if baseline prices (i.e., number of responses required to obtain a reinforcer) are a 
bargain because they are “cheaper” than Pmax, consumers may be more inclined to increase 
output to a value that approximates Omax during extinction (a pattern typified by “bursts”). 
Likewise, if baseline prices are “more expensive” than Pmax, then output has already been 
diminished and bursts may be less likely. It is also possible that bursts are a product of the 
timing of extinction. Specifically, if, prior to extinction, consumption has approximated demand 
(thereby abolishing additional consumption as a reinforcer), responding during extinction may be 
less than if the inverse were true. Finally, it is possible that price (relative to Pmax) and 
timing (i.e., pre-extinction consumption relative to demand) interact. 
 
2.0 
Rationale and Specific Aims 
 
 
The Goal of this 
application is to identify 
mechanisms responsible 
for bursts, and to facilitate 
strategic extensions 
toward discovery for 
treatments of challenging 
behavior. To accomplish 
this, we present two 
related but distinct objectives. Objective 1 entails identification of 
an efficient, accurate, and reliable assessment of Pmax. AIM 1: 
Evaluate correspondence between Pmax values derived from assessments of varying 
efficiency. H1: Progressive ratio (PR) reinforcer analysis (more efficient) will produce estimates 
which align with values obtained by progressive fixed-ratio reinforcer analysis (PFRA; less 
efficient). Objective 2 entails determining the degree to which relative price and the timing of 
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Baseline
Ext
Responses Per Minute
Sessions
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1. Only Unit Price
(Relative to Pmax)
2. Only Proximity
to Demand Threshold 
3. Unit Price 
and Proximity
FR4
FR7
FR10
FR13
FR16
FR16
FR19
FR22
FR25
0.0
0.5
1.0
1.5
2.0
All: Magnitude Decreases
as Unit Price Increases
Baseline
Ext
Baseline
Ext
Random 
Assignment
Group of 4
(Matched by Breakpoints)
Block 2b
Expensive & EO
Block 2a
Expensive & AO
Block 1a
Cheap & AO
Block 1b
Cheap & EO
1a. Burst
1b: Burst
2a: No Burst
2b: No Burst
1a. Burst (low magnitude)
1b: Burst (high magnitude)
2a: No Burst (low magnitude)
2b: No Burst (high magnitude)
1a. No Burst
1b: Burst
2a: No Burst
2b: Burst
Outcomes
Peak Rate 
(Proportion of Baseline)
Unit Price

extinction interact to increase or abate responding during extinction (thereby highlighting 
mechanisms of control). AIM 2: Evaluate utility of manipulating baseline parameters for 
controlling bursts when variables are set according to demand and Pmax. H2: Peak response 
magnitude during extinction will decrease as unit price increases. Further, baseline will moderate 
bursts in one of three distinct ways. First, only unit price, relative to Pmax, will influence peak-
response magnitude. Second, only timing of extinction (i.e., proximity of baseline consumption to 
demand threshold) will influence peak-response magnitude. Third, unit price relative to Pmax, 
and consumption relative to demand, interact to influence peak-response magnitude during 
extinction. 
 
3.0 
Inclusion/Exclusion Criteria 
 
Inclusion Criteria 
(a) Biological age of 18 years or older 
(b) IDD diagnosis 
(c) Ability to correctly manipulate all items used in the study 
(d) Consent/assent prior to and throughout the study 
 
Exclusion Criteria 
(a) Biological age of 17 years or younger 
(b) No disability 
(c) Cannot correctly manipulate all items used in the study 
(d) Does not consent (or assent) to participate 
 
4.0 
Enrollment/Randomization 
 
Recruitment. Participants will be recruited across seven primary research sites. 
PLACEMENTS AND POINTS OF CONTACT ARE REDACTED will mediate contact and 
communication between potential participants and researchers. Importantly, these points of 
contact have no connection to the research study, are not invested in its execution, and have been 
commissioned to prioritize the rights and safety of their clients. Thus, recruitment efforts will be 
filtered by an unbiased third party. 
 
Participants interested in the study will then reach out to KSP, who will initiate the informed 
consent process and who will ask participants pertinent information about relevant disabilities. In 
the case that a participant's legal guardian reaches out on their behalf, we will follow the same 
procedures. However, after obtaining informed consent, we will also obtain assent from 
participants who understand language. If participants are non-verbal, we will ask their legal 
guardians to describe non-verbal actions accepted as proxies for assent or dissent, and we will 
treat these proxies as demonstrations of assent or dissent (and will honor them accordingly) 
throughout all phases of the study. 
 
Because REDACTED requires human rights committee (HRC) approval of all client 
programming (i.e., behavior intervention plans, medication changes, study participation), we have 
included additional documents relevant to that organization. The first is their established policy 
for research participant. The second is a consent from their clients for them to share client contact 
information with us (i.e., to learn more about study procedures and to provide informed consent), 
the third is a consent to share information document which will allow us to inform REDACTED 
administrators of client consent to participate so that said participation can be reviewed and 
approved by REDACTED regional HRC. 
 

Thus, for REDACTED, interested participants will complete a "consent to share information" 
document and this information will be delivered to us by a director or coordinator. We will then 
set up a meeting to obtain informed consent. If consent is obtained, prospective participants will 
sign a "consent to share information" document which will allow us to report to REDACTED 
about their consent so that the process fo regional HRC review can be initiated. Contingent upon 
both participant consent and subsequent HRC approval, study activities can then begin. 
 
Enrollment & Randomization. Because this is a low-risk trial with a limited budget, the PI 
(Lambert) will be responsible for carrying out randomization procedures and for monitoring data. 
Enrollment and randomization procedures will entail: 
1. Enrolling participants in batches of 10 
2. Matching two blocks of four participants based on similarity in pertinent baseline 
assessment scores (i.e., progressive-ratio reinforcer analysis), and relegating participants 
with outlier scores to block participation with the next batch of enrolled participants.  
3. Using the randomization and sorting functions of Microsoft Excel, we will randomly 
assign each member of each block within each batch of participants to one of four 
experimental conditions (i.e., cheap+EO, cheap+AO, expensive+EO, expensive+AO). 
Registration. We have initiated the study registration process with clinicaltrials.gov. 
 
 
5.0 
Study Procedures 
 
 We will schedule 1 to 4 appointments per week with each participant across a 1-month period. 
All participants will complete the same progression: (1) interview (i.e., set appointments, 
identify programmed reinforcers and target-responses), (2) target-response training, (3) PRA, 
(4) PFRA, (5) extinction challenge. 
 
Experimental Design. Following completion of a small battery of intake assessments 
(listed above), we will evaluate between-groups differences in peak-response magnitudes during 
a single exposure to extinction using a 2x2 factorial, crossed, and randomized matched blocks 
design, employing batched randomization logic. Specifically, we will recruit participants in 
batches of ten and will match two tetrads according to similarity in PRA results (described 
below). The two participants not assigned to a group will be matched to subsequent tetrads. Or, 
(if recruited in the final batch), paid for their time and discharged. To assign members of each 
tetrad to one of four experimental groups (i.e., cheap EO, cheap AO, expensive EO, expensive 
AO), we will use randomization functions of appropriate computer software (e.g., Microsoft 
Excel). 
 
Settings, Participants, Consent, & Compensation.  Recruitment will occur across six 
primary research sites.  Best Buddies Tennessee, The Metro Parks DisABILITIES program, 
Habilitative and Training Services (HATS), Down Syndrome Association of Middle Tennessee 
(DSAMT) Next Steps at Vanderbilt, Friends Life Community, and MillarRich. ll have offered 
letters of support. Across the life of the study, we will recruit 80 adults in batches of 10. We do 
not anticipate biological variables (e.g., sex) to impact study outcomes. Inclusion criteria call for 
participants: (a) to be older than 18 (we exclude children to obey labor laws), (b) to have a 
developmental disability (unconstrained to specific diagnoses. We chose to work with a 
heterogenous sample to increase the generality of our findings), (c) to correctly manipulate all 
study items, and (d) to consent prior to and throughout the study. If participants cannot legally 
consent, we will obtain consent from guardians and will assess assent throughout the study (i.e., 
at the beginning of every session). Importantly, pilot-study participants consented to all 
procedures on an ongoing basis. We will pay participants with gift cards, on a schedule 
commensurate with minimum wage ($7.25/hr).   

 
Materials and Target Response. For each participant, we will individualize and define 
(a) a target response with a corresponding apparatus, (b) a preferred edible item or sound 
manipulation (Lambert et al., in press), and (c) a moderate- to low-preferred tangible item. All 
target responses will involve a two-step manipulation and restoration. The final step of each 
target response (i.e., restoration) will automatically set up another opportunity to complete the 
task (e.g., fold/unfold a hand towel).  
 
Dependent Variables, Procedural Fidelity, and Interobserver Reliability. We will 
collect continuous timed-event measures of the frequency of target responding and reinforcer 
delivery, latency from session onset to delivery of programmed reinforcers, and overall session 
duration. Derivative measures appropriate to each analysis will serve as our dependent variables 
and will include breakpoint (i.e., the schedule of the last obtained reinforcer prior to response 
cessation [PRA]), demand (i.e., the number of reinforcers obtained prior to response cessation 
[PFRA]), Pmax (defined above [PRA & PFRA]), and peak response rate during extinction 
(Figure 1), depicted as a proportion of baseline (e.g., Figure 4). We will monitor fidelity, and a 
second trained observer will collect reliability data on all dependent variables across no fewer 
than 30% of sessions. 
 
General Appointment Protocol. To minimize unintended coercive practice, all 
assessment-related activities will be framed as a choice. Specifically, facilitators will initiate 
appointments with a 5-min casual conversation. Prior to each session, facilitators will display the 
apparatus for target response and a low-preferred alternative activity and will say, “We are going 
to start a session, now. This just means I’m going to give you an opportunity to earn (reinforcer). 
During sessions I cannot talk to you. That’s just a rule I have to follow. It doesn’t mean I don’t 
want to talk or that I’m not happy. If you want (reinforcer) after the session starts, you can work 
on (target response). If you don’t want (reinforcer), or would rather talk to me, you only need to 
stop (target response) for one minute. You can also just say, ‘I’m done’. While you wait, you can 
(alternative activity) if you like.” All appointments will terminate the moment a participant 
indicates they would like it to end. 
 
Response Training. Will entail a forced-choice exposure and 10 opportunities to 
independently earn reinforcers (1/response). If independence is not achieved, we will target 
different responses and reinforcers. 
 
Progressive Ratio Reinforcer Analysis (PRA). Begins with free-access, followed by 
three PRAs interspersed with controls. Control will occur prior to PRA. To avoid satiation, only 
one PRA will be conducted per appointment. Thus, including free access, this assessment requires 
four appointments. Free access. Carefully measured units of the reinforcer will be delivered 
freely, independent of target responding. Participants will be informed they can consume (e.g., 
eat, listen to) reinforcers at will, and that reinforcers will be replaced (when relevant) as they are 
consumed. Sessions end when no reinforcers are consumed for one minute. Control. Facilitators 
will place the target-response apparatus in front of participants and indicate that responding will 
not result in reinforcement. Sessions end following 1 min without responding. PRA. Facilitators 
will indicate that responding results in reinforcement, but that more work will be required as time 
passes. Following every other reinforcer delivery, price will increase by three responses (i.e., 
FR1, FR4, FR7, etc.).   
 
Progressive Fixed-Ratio Reinforcer Analysis (PRFA). Will be similar to PRA with a 
few exceptions. First, no control condition. Next, within-session schedules are fixed. That is, 
requirements increase by 3 across sessions, rather than across reinforcers (this allows us to 
establish demand at each schedule). To control for satiation, we’ll conduct one PRFA session per 
appointment (session ends following 1 min without responding; or after 1 hour). The assessment 
ends after aggregate responses for one session fall below those of previous sessions (thus 
avoiding premature exposure to extinction). During our pilot study, this assessment was 
completed in six or fewer appointments, each ranging from 5 to 27 min.  

Extinction Challenge. Baseline. Facilitator does not inform participants of active 
contingencies and reinforces responding according to participant-assigned schedule for 
participant-specific session duration (see below). This will continue for 10 sessions, with multiple 
session completed each day. Extinction. Occurs during a single appointment. Session format is 
similar to baseline but no programmed consequences for target responding. Sessions continue 
until responding reaches 10% (or less) of mean of the final three baseline sessions for two 
consecutive sessions (or until dissent). Individualization. Baseline schedules will be set 
according to PRA and PFRA results. Specifically, we will compare the difference of each 
participant’s PFRA-identified Pmax and their PRA-identified mean breakpoint. For participants 
assigned to expensive, we will add half of the calculated difference to Pmax and round up to the 
nearest whole number. For example, if Pmax was FR4 and breakpoint was FR8, half of the 
difference would be two, which we would add to Pmax to establish an expensive baseline of FR6. 
Similarly, for participants assigned to the cheap condition, we will subtract half of the difference 
from Pmax and round down to the nearest whole number (i.e., FR2). Default session duration for 
baseline and extinction will be five minutes. However, to ensure opportunity to obtain no fewer 
than five reinforcers per session, we will reference latency to the first obtained reinforcer of the 
matched PFRA session (i.e., the session with a schedule that most closely approximates the 
baseline schedule). For example, in our pilot study, participant AC was assigned to expensive. 
Based on the distance between his breakpoint and Pmax, baseline was set at FR6. We thus 
considered latency (i.e., 56 s) to first reinforcer obtained during the matched PFRA (FR7) to 
predict the number of obtained reinforcers during a typical 5-min session. Projecting consumption 
from this value, we concluded he could obtain at least five reinforcers at the default duration 
when the schedule was set at FR6, and thus maintained the 5-min session duration. However, had 
latency been 90 s, we would have increased session duration to 7.5 min. To set a maximum 
appointment duration, we will use the matched PFRA session duration as a proxy measure of AO 
(e.g., fatigue, satiation) and will ensure appointment duration approximates, but falls below, this 
value. Similar considerations will be made to ensure appointment-reinforcer consumption never 
surpasses demand. For example, AC consumed a maximum of 55 reinforcers during the FR1 
session of his PFRA. At FR6 (his assigned baseline schedule), we projected it would have taken 
11 sessions to consume 55 reinforcers, estimating (roughly) 60 s to earn each reinforcer (justified 
above). In response, we ensured that no appointment exceeded 10 sessions.  For AO participants, 
we will introduce extinction after appointment-reinforcer consumption falls one below demand. 
Previous appointments will thus be coordinated in such a way that extinction for the AO group is 
introduced toward the end of the relevant appointment (however, we will not cap appointment 
duration during extinction). Similarly, we will introduce extinction to EO participants during the 
first session of the relevant appointment, when consumption has been low. The first EO-
extinction session will be preceded by a single reinforcer delivery. 
 
Data Analysis Plan. We will evaluate between-groups differences in peak magnitudes of 
responding during a single exposure to extinction using a 2x2 factorial, crossed, and randomized 
matched blocks design, employing batched randomization logic. First, we will calculate observed 
and analytic Pmax values (Gilroy et al., 2019) generated from logarithmically transformed PRFA 
outcomes to evaluate accuracy, reliability, and correspondence of Pmax estimates generated from 
PRA calculations (Reed et al., 2009). PRFA-PRA Pmax comparisons will be performed for each 
of the 160 PRA/PRFA assessments. Correspondences in Pmax will be assessed using Pearson 
correlations. Then, we will conduct a simple linear regression to assess relations between unit 
price and peak response magnitudes. Then, to evaluate (a) the effect of the timing of extinction 
(EO/AO) on peak response magnitude, (b) the effect of relative price (cheap/expensive) on 
response magnitude, and (c) price by timing interaction (whether the effect of timing on peak 
response magnitude changes depending on price) we will conduct a multiple linear regression 
analysis with price and timing as dummy coded categorical predictors. We will replicate this 

analysis to evaluate collateral effects on duration of responding during extinction (a secondary 
analysis we anticipate will produce a less robust but potentially meaningful outcome). 
 
Predicted relationship between timing, price, and response magnitude.    
We predict that the mean magnitude of 
peak responding for participants 
assigned to cheap conditions will be 
higher than those assigned to expensive 
conditions, holding timing constant. 
Additionally, we predict the mean 
magnitude of peak responding will be 
higher for those participants assigned to 
EO as compared to AO, holding price 
constant. Further, we predict a timing by 
price interaction such that the difference 
in mean peak responding in cheap and 
expensive conditions will be bigger in 
EO relative to AO.  
 
Power Analysis. Power analysis and sample size calculations were conducted using 
G*power software. Since our study represents a novel contribution to the field, we cannot rely on 
previous literature to estimate the population value of R-squared or the appropriate effect size. 
However, our pilot data suggest the effect size will not be small. Thus, we calculated sample size 
based on a benchmark value for Cohen’s 
 of 0.15 that corresponds to a medium effect size for 
R-squared (Cohen, 1988). To achieve 80% power in a regression model with three predictors and 
, the number of required participants is 77. With a sample of 77, the power to find any 
one of the three predicted effects (given medium effect size) is 88. Since participants will be 
equally distributed across four groups, we budgeted time/effort for 80 participants. Under our 
most conservative study assumptions, AIMS 1 & 2 are adequately powered. 
 
6.0 
Reporting of Adverse Events or Unanticipated Problems involving Risk to 
Participants or Others 
 
This is a low-risk study. The PI (Lambert) will review all data on a weekly basis and all adverse 
events (AE) will be logged on an AE form and will immediately be reported to the IRB. 
 
7.0 
Study Withdrawal/Discontinuation 
 
Prior to each appointment, we will re-assess assent to participate by asking clients if they would 
like to work with us. When/if assent is not given, we will not conduct appointments. We will 
individualize appointment parameters (i.e., appointment duration, responses targeted, reinforcers 
delivered) based on ongoing assessments of participant preferences (see study procedures). We 
will also provide periodic reminders of how participants can terminate sessions and/or 
appointments (by simply saying that they would like to stop). If participants indicate they no 
longer wish to participate in the study, we will promptly terminate their participation with no 
consequence to them (i.e., participants will be paid for all time spent in research activities, RAs 
will not try to convince participants to stay in the study, and RAs will continue to interact with 
participants in pleasant and respectful ways).  
 
8.0 
Statistical Considerations 

 
Power Analysis. Power analysis and sample size calculations were conducted using 
G*power software. Since our study represents a novel contribution, we cannot rely on previous 
literature to estimate the population value of R-squared or the appropriate effect size. However, 
our pilot suggests the effect size will not be small. Thus, we calculated sample size based on a 
benchmark value for Cohen’s 
 of 0.15 that corresponds to a medium effect size for R-squared 
(Cohen, 1988). To achieve 80% power in a regression model with three predictors and 
, 
77 participants are required. With this sample, the power to find any one of the three predicted 
effects (given medium effect size) is 88%. As participants will be equally distributed across four 
groups, we budgeted effort for 80 participants. Under our most conservative study assumptions, 
AIMS 1 & 2 are adequately powered. 
 
9.0 
Privacy/Confidentiality Issues 
 
Participant names will be replaced with pseudonyms on all study-related documents. A 
single Excel file will link participant names and contact information to pseudonyms. All other 
research documents will not include participant names and will only include associated 
pseudonyms. 
The above-mentioned Excel file will be stored on a secured and password protected 
computer, as well as on a server provided by Vanderbilt University and only accessible to 
research personnel.  This file will be destroyed at the study's conclusion, leaving no remaining 
link between identifying information and participant data. 
 
10.0 
Follow-up and Record Retention 
 
We anticipate that this study will require two years to complete. Intend to maintain all de-
identified records obtained during the study indefinitely. However, files linking participant names 
and contact information to pseudonyms will be destroyed (deleted) once the study has been 
completed. 
 

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