Evaluating the Feasibility of Central Executive Training for Children With ADHD
Phase: NA
Conditions: Attention Deficit Hyperactivity Disorder
Sponsor: Florida State University

This registration is a frozen, non-editable version of this project (/qekp8/)
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Study Information
Title
Authors
Research Questions
Hypotheses
Sampling Plan
Existing Data
Explanation
Data collection
procedures
Sample size
Sample size
rationale
Stopping rule
Variables
Manipulated
Measured
Indices
Design Plan
Study type
Blinding
Study design
Randomization
Analysis Plan
Study Information
Title
Authors
Research Questions
Hypotheses
Provide the working title of your study. It is helpful if this is the same title that you submit for publication of your ﬁnal manuscript, but it is not a 
requirement.
Central executive training (CET) for ADHD: Initial development and comparison to behavioral parent training (BPT)
The author who submits the preregistration is the recipient of the award money and must also be an author of the published manuscript. 
Additional authors may be added or removed at any time.
Michael Koﬂer
Please list each research question included in this study.
1. Is CET a feasible and acceptable intervention for caregivers and their children with ADHD? Is its feasibility and 
acceptability comparable to the current gold-standard psychosocial treatment for ADHD (BPT)?
2. Does CET improve working memory in children with ADHD, and are these improvements superior to those found for 
BPT (which is not expected to improve working memory)?
3. Does CET improve ADHD symptoms in children with ADHD, and are these improvements non-inferior to 
improvements associated with gold-standard BPT?
4. (Fidelity Check) Does BPT improve oppositional-deﬁant symptoms in children with ADHD, and how does CET compare 
to BPT for these expected improvements? 
For each of the research questions listed in the previous section, provide one or multiple speciﬁc and testable hypotheses. Please state if the 
hypotheses are directional or non-directional. If directional, state the direction. A predicted eﬀect is also appropriate here.
Primary Outcome
1. 
Near-transfer: Central executive training (CET) will produce greater improvements than behavioral parent training 
(BPT) on the Rapport phonological (PH) and visuospatial (VS) working memory tests (2 group x 2 task x 2 time points 
(pre, post)). Critical test is the group x time interaction. The 2 tasks are included in the omnibus ANOVA to (1) address 
recommendations to probe cognitive abilities using multiple tests, and (2) maximize power for the critical group x time 
interaction. The 2 working memory tests are considered to tap the same ‘central executive’ working memory; they diﬀer 
in whether that central executive is processing phonological or visuospatial information. If the group x time interaction 
is signiﬁcant at p = .05 or less, it will be followed by Bonferroni-corrected within-group post-hocs for each task and 
ANCOVA of post-treatment covaried for pre-treatment separately for each task (i.e., residualized gain scores). These 
post-hocs will also be performed if the main eﬀect of time is signiﬁcant (but not the group x time interaction) to allow us 
to better characterize change within each group (i.e., did each treatment produce signiﬁcant change?). Stimuli correct 
per trial will be used.

Statistical models
Transformations
Follow-up analyses
Inference criteria
Data exclusion
Missing data
Exploratory analysis
Scripts
Script
Other
Other
Sampling Plan
Existing Data
Explanation of existing data
Secondary Outcomes
2. 
Far-transfer subjective ADHD symptoms: BPT and CET will both show signiﬁcant reductions in ADHD symptoms 
measured by unblinded parent ratings. Two scales are used: the norm-referenced BASC-2 (T-scores based on age and 
gender norms) and CSI-IV (raw symptom severity scores). Both have separate Attention Problems and 
Hyperactivity/Impulsivity subscales. Both will be tested via 2 group x 2 subscale x 2 time point mixed-model ANOVA. 
Critical test is the group x time interaction for both. Post-hoc plan follows #1 above. 
3. 
Far-transfer objective (proximal) ADHD symptoms: CET will show greater reductions in actigraph-measured 
hyperactivity than BPT during the Rapport PH and VS working memory tests. Same 2 group x 2 task (PH-actigraphy, VS-
actigraphy) x 2 time points approach as above; same post-hoc plan. Critical test is the group x time interaction. 
Actigraph data will be PIM intensity scores, summed across 3 actigraphs (non-dominant wrist, left ankle, right ankle). 
4. 
Far-transfer objective (distal) ADHD symptoms: CET will show greater reductions in actigraph-measured 
hyperactivity than BPT during the low cognitive load Painting tasks at the beginning and end of each testing session. 
Same 2 group x 2 task (PaintBeginning-actigraphy, PaintEnd-actigraphy) x 2 time points approach as above; same post-
hoc plan. Critical test is the group x time interaction. Actigraph data will be PIM intensity scores, summed across 3 
actigraphs (non-dominant wrist, left ankle, right ankle).
5. 
Far-transfer subjective oppositional-deﬁant symptoms: BPT will show greater improvements in unblinded parent 
reports of oppositional deﬁant symptoms on the CSI-IV. Only the ADHD and ODD sections of the CSI-IV were 
administered. Analysis will be 2 group x 2 timepoints mixed-model ANOVA. Critical test is the group x time interaction. 
CSI-IV raw symptom scores for the ODD dimension will be used as dependent variable. Bonferroni-corrected paired-
sample t-tests for each group separately (pre vs. post), and between-group at post covaried for pre-treatment ODD 
symptoms are tested because of compelling evidence that BPT improves these symptoms (manipulation check; if no 
signiﬁcant reductions in BPT group, may indicate limited BPT eﬃcacy).
Feasibility/Acceptability Outcomes
6. 
Client Satisfaction Questionnaire-8 (CSQ-8) parent report at post-treatment (total scores) will be compared across 
groups (BPT vs. CET). No signiﬁcant diﬀerences expected.
7. 
Barriers to Treatment Participation Scale (BTPS) parent report at post-treatment (total scores and all subscales). No 
signiﬁcant diﬀerences are expected. The Relevance of Treatment subscale will be interpreted as evidence of 
intervention expectancies. 
8. 
CET only: System Usability Scale (SUS). Child reported feasibility of CET system. Expected to be high (mean of at 
least 3.5 on 5-point Likert scale, where higher scores indicate better usability).
9. 
CET training duration. Total minutes trained and total training games completed will be reported. Descriptive; no 
hypotheses are oﬀered. 
Recommended elements
1. 
All hypothesized interactions are expected to look like Figure 1 in Redick (2015). In other words, no pre-treatment 
group diﬀerences, and diﬀerential improvements favoring the group hypothesized to improve. Should pre-treatment 
group diﬀerences be observed, diﬀerential improvements favoring the group hypothesized to improve would be 
observed when using post-treatment covaried for pre-treatment analysis (residualized gain scores). No diﬀerences in 
this test indicate equivalence between interventions.
2. 
P-values and Bayes Factors will be reported. P-values will be considered primary in cases of discrepant results (to 
follow current conventions in the ﬁeld). P-values of .05 or less will be considered signiﬁcant (after Bonferroni corrections 
for post-hoc tests). Bayes Factors of 3 or greater will be considered signiﬁcant. 
Preregistration is designed to make clear the distinction between conﬁrmatory tests, speciﬁed prior to seeing the data, and exploratory analyses 
conducted after observing the data. Therefore, creating a research plan in which existing data will be used presents unique challenges. Please 
select the description that best describes your situation. Please do not hesitate to contact us if you have questions about how to answer this 
question (prereg@cos.io).
Registration prior to accessing the data
If you indicate that you will be using some data that already exist in this study, please describe the steps you have taken to assure that you are 
unaware of any patterns or summary statistics in the data. This may include an explanation of how access to the data has been limited, who has 
observed the data, or how you have avoided observing any analysis of the speciﬁc data you will use in your study. The purpose of this question is 
to assure that the line between conﬁrmatory and exploratory analysis is clear.
The data exists in pieces on the PI's lab server, and we have begun to collate them into a united dataset that will be used 

Data collection procedures
for analyses. All data handling decisions were made by Co-PIs without access to the data, most of whom are at diﬀerent 
universities. The primary and secondary outcomes to be reported in this study were determined by Co-PIs without 
access to the data. 
Please describe the process by which you will collect your data. If you are using human subjects, this should include the population from which you 
obtain subjects, recruitment eﬀorts, payment for participation, how subjects will be selected for eligibility from the initial pool (e.g. inclusion and 
exclusion rules), and your study timeline. For studies that don’t include human subjects, include information about how you will collect samples, 
duration of data gathering eﬀorts, source or location of samples, or batch numbers you will use.
Description of essential elements
Preregistration is for data analysis; data collection is almost complete. All outcome measures and analyses were 
selected without access to the data.  
Study Timeline
Children were not randomized to treatment condition. Families recruited between June 2013 and December 2014 were 
oﬀered behavioral parent training (BPT). The ﬁnal BPT post-treatment session was completed in June 2015. Families 
recruited between June 2015 and December 2016 were oﬀered central executive training (CET). The ﬁnal CET post-
treatment session was completed in [TBD, likely May/June] 2017. Recruitment to CET was closed when the software for 
the active comparator was completed. We are currently conducting a pilot randomized trial of CET versus this active 
comparator (inhibition training). 
Identical procedures were used for both samples. Both treatments were delivered in small group format (2-4 families) 
or individually as needed to accommodate families’ schedules. Schedule changes were accommodated to the extent 
possible (e.g., make-up sessions the same week). 
Inclusion/Exclusion Criteria
All children and caregivers completed an identical evaluation, regardless of group assignment, that included detailed, 
semi-structured clinical interviewing (K-SADS; Kaufman et al., 1997). The K-SADS (2013 Update) assesses developmental 
history as well as onset, course, and impairment of DSM-5 (APA, 2013) disorders in children and adolescents. Parent and 
teacher ADHD ratings were obtained from the Behavior Assessment System for Children (BASC-2; Reynolds & 
Kamphaus, 2004) and Child Symptom Inventory (CSI-IV; Gadow & Sprafkin, 2002).
Study eligibility required all of the following (1) DSM-5 diagnosis of ADHD (any presentation) by the directing clinical 
psychologist based on K-SADS; (2) Borderline/clinical elevations on at least one parent and one teacher ADHD rating 
scale. A previous diagnosis of ADHD was also suﬃcient for inclusion. All children had current impairment (K-SADS). 
Comorbidities reﬂect clinical consensus best estimates. Positive screens for learning disabilities will be based on score(s) 
1 SD or more below age-norms on one or more Kaufman (KTEA-2/3; 2004, 2014) academic skills battery subtests. 
Medication rates will be reported. Psychostimulants were withheld for at least 24-hours prior to all research testing 
sessions (i.e., all working memory performance and actigraph hyperactivity data was collected oﬀ-medication). 
Following convention in our assessment clinic, children prescribed psychostimulants received their usual dose during 
the baseline psychoeducational assessment (IQ, achievement testing) to provide the best estimates of their child’s 
skills/abilities in the psychoeducational report provided to parents. Changes in medication status during treatment will 
be reported. 
Children were excluded for gross neurological, sensory, or motor impairment; seizure disorder, psychosis, or intellectual 
disability; or non-stimulant medications that could not be withheld for testing. No inclusion/exclusion based on working 
memory/executive functioning performance was set.
Procedures
Pre-treatment testing occurred during a larger battery of two, 3-hour sessions. Post-testing occurred during a single, 3-
hour session. A 90-minute mid-treatment testing session was conducted for children in the BPT group. As speciﬁed in 
the NIH R34 proposal, no mid-treatment sessions were completed for the ﬁrst CET groups. This design diﬀerence was 
considered acceptable because it favored the null (i.e., test-retest eﬀects, if present, would favor the BPT group). 
Statistical tests will therefore assess pre-post changes. 
All tests were counterbalanced within/across sessions to minimize order/fatigue eﬀects. Children received brief breaks 
after each task, and preset longer breaks every 2-3 tasks to minimize fatigue.
no ﬁle selected

Sample size
Sample size rationale
Stopping rule
Variables
Manipulated variables
Describe the sample size of your study. How many units will be analyzed in the study? This could be the number of people, birds, classrooms, plots, 
interactions, or countries included. If the units are not individuals, then describe the size requirements for each unit. If you are using a clustered or 
multilevel design, how many units are you collecting at each level of the analysis?
The ﬁnal analyzed sample size is expected to be BPT = 27, CET = 27. BPT collection is complete; the last CET group is 
anticipated to be complete in May/June 2017.
This could include a power analysis or an arbitrary constraint such as time, money, or personnel.
Families recruited between June 2013 and December 2014 were oﬀered behavioral parent training (BPT). The ﬁnal BPT 
post-treatment session was completed in June 2015. Families recruited between June 2015 and December 2016 were 
oﬀered central executive training (CET). The ﬁnal CET post-treatment session was completed in [TBD, likely May/June] 
2017. Recruitment to CET was closed when the software for the active comparator was completed. We are currently 
conducting a pilot randomized trial of CET versus this active comparator (inhibition training).
If your data collection procedures do not give you full control over your exact sample size, specify how you will decide when to terminate your data 
collection. 
Recruitment to BPT was stopped when CET was ready for testing. Recruitment to CET was stopped when the active 
comparator was ready for testing. Families are now being recruited to a pilot RCT of CET vs. this active comparator. That 
trial is registered at clinicaltrials.gov (NCT03042338).   
Describe all variables you plan to manipulate and the levels or treatment arms of each variable. For observational studies and meta-analyses, simply 
state that this is not applicable.
Treatments
Behavioral Parent Training (BPT)
Evidence-based behavioral parent training (BPT; Evans et al., 2014) was provided using the Barkley (2013) Deﬁant Child 
protocol. BPT was delivered with ﬁdelity in small group format by behaviorally trained, PhD-level clinicians (MJK, DES, 
HSS). 
Central Executive Training (CET)
CET is a translational, evidence-informed, hybrid (in-oﬃce and at-home), software-based treatment protocol that 
includes gaming elements and an automated token economy to reinforce training goals and improve player 
engagement. The ﬁnal 10-week protocol includes weekly, in-oﬃce sessions with the child (1 hour) and a concurrent 
parent psychoeducational group, combined with parent-supervised, in-home training (goal: 15-min/day, 2-3 days/week).
CET beta testing. The CET sample was recruited in 3 waves to facilitate software reﬁnements and testing of key design 
features. As speciﬁed in the NIH grant proposal (R34 MH102499), the ﬁrst subgroup trained on one game per week, the 
second subgroup had immediate access to all 9 training games, and the third subgroup (approximate n=9 per 
subgroup) received the ﬁnal protocol that implemented all CET features. To reduce child expectancies, children were 
told that they were “beta testers” for our video game design team. Breadth of training across the 9 games was facilitated 
by a software algorithm that limited initial access each day to three games the child had not completed recently (third 

Measured variables
subgroup only). Children earned additional rewards and access to all nine games for completing this daily “Mission 
Mode.” Leveling was set to ensure incremental increases in diﬃculty based on child performance. This process occurred 
during the current study and involved iterative changes and extensive testing with graduate/undergraduate Research 
Assistants (alpha testing) and children with ADHD (beta testing).   
CET focus groups. Caregivers in the ﬁrst two CET subgroups participated in focus groups. Key CET design changes based 
on these focus groups included overhauling the on-screen instructions, modifying the home screen to show child 
progress (daily games completed), and automation of the token economy via children earning on-screen ‘tickets’ that 
are exchanged for tangible, in-oﬃce rewards. Key logistical changes from these focus groups included improved 
communication with caregivers (e.g., access/login instructions, progress monitoring of days/games completed at home), 
modiﬁed expectations for at-home training duration (original goal of 30-minutes/day decreased to 15-minutes/day) and 
frequency (original daily training goal decreased to 2-3 days/week), and modiﬁed treatment duration (original 12-weeks 
decreased to 10-weeks). Finally, caregiver feedback resulted in the addition of a caregiver psychoeducational group that 
began mid-way through testing with subgroup 2. Most caregivers described homework as the biggest obstacle to at-
home CET training; opinions were split approximately evenly regarding priority of CET vs. homework, with diﬀerences 
focused primarily on weighing immediate vs. delayed consequences.
no ﬁle selected
Describe each variable that you will measure. This will include outcome measures, as well as any predictors or covariates that you will measure. You do 
not need to include any variables that you plan on collecting if they are not going to be included in the conﬁrmatory analyses of this study.
Measures
Intellectual Functioning (IQ)
IQ was estimated using the Verbal Comprehension Index from the WASI-II (BPT) or WISC-V (CET) (Wechsler, 2011, 2014). 
The changeover was made to provide caregivers the most up-to-date evaluation possible. Standard scores are used. 
Socioeconomic Status (SES)
Hollingshead (1975) SES was estimated based on caregiver(s)’ education and occupation. 
Primary Outcomes (Working Memory)
The Rapport et al. (2009) computerized working memory tests correctly classify children with vs. without ADHD at 
similar rates as parent and teacher ADHD rating scales (Tarle et al., 2017), and predict hyperactivity (Rapport et al., 
2009), inattention (Koﬂer et al., 2010), and impulsivity (Raiker et al., 2012). Reliability and validity evidence includes 
internal consistency (α=.82-.97), 1-3-week test-retest reliability (.76-.90; Sarver et al., 2015), and expected relations with 
criterion working memory complex span (r=.69) and updating tasks (r=.61)(Wells et al., under review). Six trials per set 
size were administered in randomized/unpredictable order (3-6 stimuli/trial; 1 stimuli/second) as recommended (Koﬂer 
et al., 2016). Five practice trials were administered before each task (80% correct required). Task duration was 
approximately 5 (visuospatial) to 7 (phonological) minutes. 
Phonological working memory. Children were presented a series of jumbled numbers and a letter (1 stimuli/second). 
The letter was never presented ﬁrst or last to minimize primacy/recency eﬀects, and was counterbalanced to appear 
equally in the other serial positions. Children reordered and recalled the numbers from least to greatest, and said the 
letter last (e.g., 4H62 is correctly recalled as 246H). Two trained research assistants, shielded from child view, 
independently recorded oral responses. Interrater reliability will be computed (% agreement = % of trials for which both 
RAs transcribed the identical sequence). 
Visuospatial working memory. Children were shown nine squares arranged in three oﬀset vertical columns. A series of 
2.5 cm dots were presented sequentially (1 stimuli/second); no two dots appeared in the same square on a given trial. 
All dots were black except one red dot that never appeared ﬁrst or last to minimize primacy/recency eﬀects. Children 
reordered the dot locations (black dots in serial order, red dot last) and responded on a modiﬁed keyboard. 
Dependent variables. Stimuli correct per trial were computed at each set size as recommended (Conway et al., 2005), 
and averaged to provide a single indicator for each task. Higher scores reﬂect better working memory. 
Secondary Outcomes (ADHD Symptoms)
Subjective report. Parent-reported Attention Problems and Hyperactivity/Impulsivity T-scores on the BASC-2 (age and 
gender norms) served as the primary subjective assessment of treatment eﬀects on ADHD symptoms. 
Objective measurement. Basic Motionlogger® (Ambulatory Monitoring, 201x) are acceleration-sensitive devices that 
sample movement intensity 16 times per second (16 Hz), collapsed into 1-second epochs. The estimated reliability for 

Indices
Design Plan
Study type
actigraphs placed at the same site on the same person ranges from .90 to .99 (Tryon et al., 1991). Children were told 
that the actigraphs were “special watches” that let them play the computer learning games. Observer XT (Noldus, 201X) 
software was used to code start and stop times for each task, which were matched to the time stamps from the 
actigraphs. 
Actigraphs were placed on the child’s non-dominant wrist and both ankles using Velcro watch bands. Following Rapport 
et al. (2009), a total hyperactivity score was computed by summing activity level across the three actigraphs. 
Hyperactivity scores were computed separately for movement during each of the working memory tests described 
above, as well as for movement during the control conditions that occurred as the ﬁrst and last activities of each testing 
session. Movement scores reﬂect movement intensity (Proportional Integrating Measure; PIM).
During these control conditions, children used Microsoft Paint for ﬁve consecutive minutes at the beginning and end of 
all pre- and post-treatment sessions. Children sat in the same chair and interacted with the same computer used for the 
working memory tasks while interacting with a program that placed relatively modest demands on working memory 
(i.e., the Paint program allows children to draw/paint anything they like on the monitor using a variety of interactive 
tools).
Feasibility/Acceptability Outcomes
Client Satisfaction Questionnaire (CSQ-8; Nguyen et al., 1983). The CSQ-8 is an extensively studied, 8-item generic 
measure of clients’ perceptions of the value of services received. Parents completed the CSQ-8 at post-treatment. Total 
scores will be used.
Barriers to Treatment Participation Scale (BTPS; Kazdin et al., 1997). The BTPS is a 44-item measure of perceived 
treatment barriers; item scores are summed to provide a Total Barriers score and 4 subscores: (1) Stressors/obstacles; 
(2) Treatment demands/issues; (3) Perceived relevance; and (4) Relationship with the Therapist. Parents completed the 
BTPS at post-treatment. Total scores will be used for each subscale.
System Usability Scale (SUS; Canon-Bowers & Bowers, 2010). The SUS is a 10-item, IRT-developed scale assessing ease of 
use on a 5-point Likert scale. Children in the CET group completed the SUS each week for a diﬀerent training game, and 
at post-treatment for the CET system overall. Total scores will be used. 
CET Training Duration. The CET software records training duration for each completed training task; total minutes 
trained and total completed games are reported.
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If any measurements are  going to be combined into an index (or even a mean), what measures will you use and how will they be combined? Include 
either a formula or a precise description of your method. If your are using a more complicated statistical method to combine measures (e.g. a factor 
analysis), you can note that here but describe the exact method in the analysis plan section.
Described for each measure above.
no ﬁle selected
Please check one of the following statements
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
Study design
Randomization
Analysis Plan
Statistical models
Blinding describes who is aware of the experimental manipulations within a study. Mark all that apply.
No blinding is involved in this study.
Describe your study design. Examples include two-group, factorial, randomized block, and repeated measures. Is it a between (unpaired), within-subject 
(paired), or mixed design? Describe any counterbalancing required. Typical study designs for observation studies include cohort, cross sectional, and 
case-control studies. 
Sequential, non-randomized design. The BPT sample was recruited while PI Koﬂer was at the University of Virginia. Data 
collection continued, led by co-PI Schaefer, when PI Koﬂer changed institutions to Florida State University in August, 
2014. The CET sample was collected at FSU (co-PI Holland for 2015-2016, co-PI Austin for 2016-present). Identical 
procedures were used for both samples. Both treatments were delivered in small group format (2-4 families) or 
individually as needed to accommodate families’ schedules. Schedule changes were accommodated to the extent 
possible (e.g., make-up sessions the same week). Families recruited between June 2013 and December 2014 were 
oﬀered behavioral parent training (BPT). The ﬁnal BPT post-treatment session was completed in June 2015. Families 
recruited between June 2015 and December 2016 were oﬀered central executive training (CET). The ﬁnal CET post-
treatment session was completed in [TBD, likely May/June] 2017. Recruitment to CET was closed when the software for 
the active comparator was completed. We are currently conducting a pilot randomized trial of CET versus this active 
comparator (inhibition training) that is registered at clinicaltrials.gov (NCT03042338).  
no ﬁle selected
If you are doing a randomized study, how will you randomize, and at what level? 
Participants are not randomized because the CET intervention was in development. Recruitment to BPT was closed 
when CET was ready for testing. Recruitment to CET was closed when the active comparator was ready for testing. 
What statistical model will you use to test each hypothesis? Please include the type of model (e.g. ANOVA, multiple regression, SEM, etc) and the 
speciﬁcation of the model (this includes each variable that will be included as predictors, outcomes, or covariates). Please specify any interactions that 
will be tested and remember that any test not included here must be noted as an exploratory test in your ﬁnal article.
Covariates and Data Handling
1. 
To describe the samples, the BPT and CET samples will be compared at pre-treatment on gender, age, SES 
(Hollingshead scores), WASI-II/WISC-IV Verbal Comprehension Index IQ standard scores, medication status (no/yes), 
race/ethnicity (US Census categories), comorbidities (no/yes), teacher reported ADHD symptoms (BASC-2 attention 
problems and hyperactivity T-scores), parent reported ADHD symptoms  (BASC-2 attention problems, hyperactivity T-
scores, CSI-IV raw severity scores for attention problems and hyperactivity/impulsivity), parent reported ODD symptoms 
(CSI-IV raw severity scores). Variables showing signiﬁcant between-group diﬀerences at p = .05 or less, corrected for 
multiple comparisons, will be used as covariates in all above analyses (simultaneous entry). We decided to sacriﬁce 
power if needed to control for any pre-treatment diﬀerences. 
2. 
The CET vs. BPT pre-treatment descriptive analyses will also be conducted for the treated vs. untreated samples. 
For the purposes of these analyses, the BPT and CET participants will be combined as the ‘treated’ sample, and those 
who declined or otherwise were oﬀered but did not participate in BPT and CET will be combined as ‘untreated.’ We will 
not conduct treated vs. untreated analyses separately for the BPT and CET groups due to low n. The same signiﬁcance 

criteria and correction for multiple comparisons will apply as for BPT vs. CET. 
3. 
All hypothesized interactions are expected to look like Figure 1 in Redick (2015). In other words, the expected 
interaction pattern would be due to no pre-treatment group diﬀerences, and diﬀerential improvements favoring the 
group hypothesized to improve.
Unless otherwise speciﬁed below, all omnibus tests will be 2 (group; between) x 2 (variable; within) x 2 time points (pre, 
post; within) mixed-model ANOVA or ANCOVA. ANOVA vs. ANCOVA decision will be based on whether there are 
signiﬁcant p =.05 (or lower) group diﬀerences on any pretreatment variables as detailed in previous section. Tests that 
specify independent-samples or paired-samples t-tests will be run as between-group and within-group ANCOVAs, 
respectively, if covariate adjustments are needed based on analysis of pretreatment characteristics described in 
previous section. 
Analyses will be run using JASP 0.8.1 (or current version). 
Primary Outcome
1. 
Near-transfer: 2 group x 2 task x 2 time points (pre, post). Tasks are Rapport phonological (PH) and visuospatial (VS) 
working memory tests. Critical test is the group x time interaction. The 2 tasks are included in the omnibus ANOVA to (1) 
address recommendations to probe cognitive abilities using multiple tests, and (2) maximize power for the critical group 
x time interaction. The 2 working memory tests are considered to tap the same ‘central executive’ working memory; 
they diﬀer in whether that central executive is processing phonological or visuospatial information. If the group x time 
interaction is signiﬁcant at p =.05 (or lower), it will be followed by Bonferroni-corrected within-group post-hocs for each 
task and ANCOVA of post-treatment covaried for pre-treatment separately for each task (i.e., residualized gain scores). 
These post-hocs will also be performed if the main eﬀect of time is signiﬁcant (but not the group x time interaction) to 
allow us to better characterize change within each group (i.e., did each treatment produce signiﬁcant change?). Stimuli 
correct per trial will be used.
Secondary Outcomes
2. 
Far-transfer subjective ADHD symptoms: Two scales are used: the norm-referenced BASC-2 (T-scores based on age 
and gender norms) and CSI-IV (raw symptom severity scores). Both have separate Attention Problems and 
Hyperactivity/Impulsivity subscales. Both will be tested via 2 group x 2 subscale x 2 time point mixed-model ANOVA. 
Critical test is the group x time interaction for both. Post-hoc plan follows #1 above. 
3. 
Far-transfer objective (proximal) ADHD symptoms: Same 2 group x 2 task (PH-actigraphy, VS-actigraphy) x 2 time 
points approach as above; same post-hoc plan. Critical test is the group x time interaction. Actigraph data will be PIM 
intensity scores collected while the child was completing the PH and VS tests described above. Each data point reﬂects 
total hyperactivity score (Rapport et al., 2009), which is computed by summing the PIM activity counts for each of the 3 
actigraphs (non-dominant wrist, left ankle, right ankle). 
4. 
Far-transfer objective (distal) ADHD symptoms: Same 2 group x 2 task (PaintBeginning-actigraphy, PaintEnd-
actigraphy) x 2 time points approach as above; same post-hoc plan. Critical test is the group x time interaction. 
Actigraph data will be PIM intensity scores collected while the child was completing the beginning of session and end of 
session Paint activity (drawing using Microsoft Paint). Each data point reﬂects total hyperactivity score (Rapport et al., 
2009), which is computed by summing the PIM activity counts for each of the 3 actigraphs (non-dominant wrist, left 
ankle, right ankle). 
5. 
Far-transfer subjective oppositional-deﬁant symptoms: Included as ﬁdelity check based on evidence that BPT may 
produce greatest eﬀects on oppositional deﬁant symptoms. Analysis will be 2 group x 2 timepoints mixed-model 
ANOVA (only one measure of ODD symptoms was collected). Critical test is the group x time interaction. CSI-IV raw 
symptom scores for the ODD dimension will be used as dependent variable. Bonferroni-corrected paired-sample t-tests 
for each group separately (pre vs. post), and between-group at post covaried for pre-treatment ODD symptoms are 
tested because of compelling evidence that BPT improves these symptoms (manipulation check; if no signiﬁcant 
reductions in BPT group, may indicate limited BPT eﬃcacy).
Feasibility/Acceptability Outcomes
6. 
Client Satisfaction Questionnaire-8 (CSQ-8) parent report at post-treatment (total scores) will be compared across 
groups (BPT vs. CET) using independent samples T-test. 
7. 
Barriers to Treatment Participation Scale (BTPS) parent report at post-treatment (total scores and all subscales). 
Independent samples t-tests. The Relevance of Treatment subscale will be interpreted as evidence of intervention 
expectancies. 
8. 
CET only: System Usability Scale (SUS). Child reported feasibility of CET system. Expected to be high (mean of at 
least 3.5 on 5-point Likert scale, where higher scores indicate better usability). Descriptive statistics only. 
9. 
CET training duration. Total minutes trained and total training games completed will be reported. Descriptive 
statistics only. 
Recommended elements
10. All hypothesized interactions are expected to look like Figure 1 in Redick (2015). In other words, no pre-treatment 
group diﬀerences, and diﬀerential improvements favoring the group hypothesized to improve. Should pre-treatment 
group diﬀerences be observed, diﬀerential improvements favoring the group hypothesized to improve would be 
observed when using post-treatment covaried for pre-treatment analysis (residualized gain scores). No diﬀerences in 
this test indicate equivalence between interventions.
11. P-values and Bayes Factors will be reported. P-values will be considered primary in cases of discrepant results (to 
follow current conventions in the ﬁeld). P-values = .05or lower will be considered signiﬁcant (after Bonferroni 
corrections for post-hoc tests). Bayes Factors = 3 or greater will be considered signiﬁcant. 

Transformations
Follow-up analyses
Inference criteria
Data exclusion
no ﬁle selected
If you plan on transforming, centering, recoding the data, or will require a coding scheme for categorical variables, please describe that process.
No transformations are planned. If needed, categorical variables will be dummy coded as n-1 predictors. Reference 
categories would be: Medication changes (no change), race/ethnicity (Caucasian/Non-Hispanic), ADHD presentation 
(Combined Presentation). All other categorical variables are dichotomous and therefore would not require dummy 
coding. 
If not speciﬁed previously, will you be conducting any conﬁrmatory analyses to follow up on eﬀects in your statistical model, such as subgroup 
analyses, pairwise or complex contrasts, or follow-up tests from interactions? Remember that any analyses not speciﬁed in this research plan must 
be noted as exploratory.
Planned contrasts/post-hocs are described under the statistical model question above. Unless otherwise speciﬁed, 
signiﬁcant main eﬀects/interactions in the omnibus model will be followed by Bonferroni-corrected post hocs/contrasts 
to characterize the omnibus eﬀects. 
What criteria will you use to make inferences? Please describe the information you’ll use (e.g. specify the p-values, Bayes factors, speciﬁc model ﬁt 
indices), as well as cut-oﬀ criterion, where appropriate. Will you be using one or two tailed tests for each of your analyses? If you are comparing 
multiple conditions or testing multiple hypotheses, will you account for this? 
P-values and Bayes Factors will be reported. P-values will be considered primary in cases of discrepant results (to follow 
current conventions in the ﬁeld). P =.05 or lower and BF =3 or greater will indicate signiﬁcant eﬀects. 
For the Bayes Factors, BF10 or BF01 will be reported based on which value is greater than 1 as recommended. 
Post-hoc tests will be corrected using Bonferroni corrections for multiple comparisons. No corrections will be made for 
the omnibus tests. These omnibus tests already include 2 variables per outcome to minimize the number of tests. 
How will you determine which data points or samples (if any) to exclude from your analyses? How will outliers be handled?
Outliers (3 SD or more beyond group mean) will be windsorized relative to the group mean. Group = BPT or CET. 
Attrition: If available, mid-treatment data will be substituted for missing post-treatment data. If not available, the most 
proximal (non-pre-treatment) data point for that child will be substituted. If not available, single imputation will be used 
based on all available demographic and performance data. 
Duplicate Data: In cases of duplicate data with diﬀerent administration dates, the ﬁrst administration will be used unless 
there is compelling reason to select diﬀerently. If a child has duplicate task data from the same date, the ﬁle will be 
checked for notes (e.g., ﬁrst administration was invalidated by ﬁre alarm/child had to go to the bathroom). The ﬁrst 
administration will be used unless there is a clear documented reason to select otherwise. If a participant has duplicate 
rating scale data from the same date (e.g., mom and dad ﬁlled out forms separately), we will select the rater who 
completed forms at the other time point. Priority will be given to ratings from the caregiver involved in treatment. 
Maternal ratings will be prioritized if no other distinguishing criteria are met. All decisions will be made without looking 
at the scores.  

Missing data
Exploratory analysis
Scripts
Upload an analysis script with clear comments
Other
Other
No checks will be performed to determine eligibility for inclusion in data analyses besides veriﬁcation that each 
participant was consented and enrolled. 
How will you deal with incomplete or missing data?
Missing data: Patterns of missingness will be explored to identify potential reasons and determine whether a missing at 
random (MAR) assumption is reasonable. The steps outlined above for missing data due to attrition will be followed.
In the case of unanticipated data handling situations, decisions will be made by co-PIs without access to the data and 
without knowledge of the eﬀects of those decisions on the subsequent analyses. 
If you plan to explore your data set to look for unexpected diﬀerences or relationships, you may describe those tests here. An exploratory test is 
any test where a prediction is not made up front, or there are multiple possible tests that you are going to use. A statistically signiﬁcant ﬁnding in 
an exploratory test is a great way to form a new conﬁrmatory hypothesis, which could be registered at a later time.
None speciﬁed.
This optional step is helpful in order to create a process that is completely transparent and increase the likelihood that your analysis can be 
replicated. We recommend that you run the code on a simulated dataset in order to check that it will run without errors.
no ﬁle selected
If there is any additional information that you feel needs to be included in your preregistration, please enter it here.
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