Mental Imagery Therapy for Autism (MITA) - an Early Intervention Computerized Language Training Program for Children With ASD
Conditions: Autistic Disorder, Autism, ASD
Sponsor: ImagiRation, LLC

1 
 
Study Protocol and Statistical Analysis Plan 
Study Title: Mental Imagery Therapy for Autism (MITA) - an Early 
Intervention Computerized Brain Training Program for Children With ASD 
 
Clinical Trial ID: NCT02708290 
Principal Investigator: Dr. Andrey Vyshedskiy, Boston University,  
Founder and CEO, ImagiRation LLC 
Document Date: 09/30/2019 
 
Abstract 
Imagination exercises administered by caregivers were investigated in a three-year-long 
observational trial of 3,540 children with autism ages 2-12 years. Tablet-based verbal and 
nonverbal tasks modeled on language therapy and emphasizing mental juxtaposition of objects 
were organized into an app called Mental Imagery Therapy for Autism (MITA). MITA children 
were matched to the ‘treatment-as-usual’ participants (TaU, N=5,226) using propensity-score 
analysis. Both younger (2-5 years of age) and older children (5-12 YOA) in MITA and TaU 
groups improved their symptoms over time, but on an annualized basis, younger MITA children 
improved their language and communication skills 3-fold faster than TaU group. We conclude 
that imagination exercises delivered by caregivers may be an effective supplement to language 
therapy administered by specialists. 
 

2 
 
Study Protocol and Statistical Analysis Plan 
MITA group 
The MITA app was made available gratis at all major app stores in February 2016. Once the app 
was downloaded, the caregiver was asked to register and to provide demographic details, 
including the child’s diagnosis and age. Caregivers consented to anonymized data analysis and 
completed Autism Treatment Evaluation Checklist (ATEC) (Rimland & Edelson, 1999). The 
first evaluation was administered approximately one month after the first use of MITA and once 
100 puzzles had been completed. The subsequent evaluations were administered at three-month 
intervals. Parents were asked to complete evaluations independently of a child’s actual use of 
MITA.  
From this pool of potential study participants, we selected participants based on the following 
criteria: 
1) Consistency: Participants must have filled out at least three ATEC evaluations and the 
interval between the first and the last evaluation was six months or longer.  
2) Diagnosis: The subject must have self-reported their diagnosis as ASD.  
3) Maximum age: Participants older than twelve years of age were excluded from this study. 
4) Minimum age: Participants who completed their first evaluation before the age of two years 
were excluded from this study. 
5) Minimal ATEC severity: Participants with initial ATEC scores of less than 20 were 
excluded. 

3 
 
6) Language: Participants who indicated their primary language was not English were excluded 
from the study. 
After excluding participants that did not meet these criteria, there were 3,540 total participants.  
Control group 
Independently from MITA, ATEC responses were collected by the Autism Institute from 
participants voluntarily completing online ATEC evaluations from 2013 to 2019. Little is known 
about their treatment, but it is unlikely that many of them used MITA. Accordingly, these 
participants served as a ‘treatment as usual’ control. Participant selection was described in detail 
in Ref. (Mahapatra et al., 2018). In short, participants were selected based on the following 
criteria: 
1) Completeness: Participants who did not provide a date of birth (DOB) were excluded. As 
participants’ DOB were utilized to determine age, the availability of DOB was necessary.  
2) Consistency: Participants had to have completed at least three questionnaires and the interval 
between the first and the last evaluation was one year or longer.  
3) Maximum age: Participants older than twelve years of age were excluded from this study. 
As diagnosis was not part of the ATEC questionnaire, some neurotypical participants could be 
present in the database. To limit the contribution from neurotypical children, we excluded 
participants that may have represented the neurotypical population by using the Minimum age 
and the Minimal ATEC severity criteria.  
4) Minimum age: Participants who completed their first evaluation before the age of 2 were 

4 
 
excluded from this study, as the diagnosing of ASD in this age group is uncertain and the parents 
of some of these young cases may have completed the ATEC because they wanted to check 
whether their normal child had signs of autism. 
5) Minimal ATEC severity: Participants with initial ATEC scores of less than 20 were 
excluded. 
6) Language: Participants who indicated their primary language was not English were excluded 
from the study. 
After excluding participants that did not meet these criteria, there were 5,226 total participants.  
Outcome measures 
A caregiver-completed Autism Treatment Evaluation Checklist (ATEC) (Rimland & Edelson, 
1999) was used to track the efficacy of a treatment. ATEC is comprised of four subscales: 1) 
Speech/Language/Communication, 2) Sociability, 3) Sensory/Cognitive Awareness, and 4) 
Physical/Health/Behavior. The first subscale, Speech/Language/Communication, contains 14 
items and its score ranges from 0 to 28 points. The Sociability subscale contains 20 items within 
a score range from 0 to 40 points. The third subscale, Sensory/Cognitive awareness, has 18 items 
and scores range from 0 to 36 points. Finally, the Health/Physical/Behavior subscale contains 25 
items and scores range from 0 to 75 points. The scores from each subscale are combined in order 
to calculate a Total Score, which ranges from 0 to 179 points. A lower score indicates lower 
severity of ASD symptoms and a higher score correlates with more severe symptoms of ASD.   
 

5 
 
Statistical analysis 
The framework for evaluation of ATEC score changes over time was explained in detail in Ref. 
(Mahapatra et al., 2018). In short, the concept of a “Visit” was developed by dividing the three-
year-long observation interval into 3-month periods. All evaluations were mapped into 3-month-
long bins with the first evaluation placed in the first bin. When more than one evaluation was 
completed within a bin, their results were averaged to calculate a single number representing this 
3-month interval. It was then hypothesized that there was a three-way interaction between an age 
group, Visit, and treatment. Statistically, this hypothesis was modeled by applying the Linear 
Model with repeated measures, where a three-way interaction term was introduced to test the 
hypothesis. Least squares means (LS Means) and LS Means differences were calculated for all 
ATEC subscales (Language, Sociability, Cognitive awareness, and Health) at all visits. 
Participants in the MITA group were matched to those in TaU group using propensity score 
analysis (Schneider, Carnoy, Kilpatrick, Schmidt, & Shavelson, 2007) based on age and all four 
ATEC subscales at baseline.  
 
References 
Mahapatra, S., Khokhlovich, E., Martinez, S., Kannel, B., Edelson, S. M., & Vyshedskiy, A. 
(2018). Longitudinal Epidemiological Study of Autism Subgroups Using Autism 
Treatment Evaluation Checklist (ATEC) Score. Autism and Developmental Disorders, 
1(12). https://doi.org/10.1007/s10803-018-3699-2 
Rimland, B., & Edelson, S. (1999). Autism Research Institute. Autism Treatment Evaluation 

6 
 
Checklist (ATEC). 
Schneider, B., Carnoy, M., Kilpatrick, J., Schmidt, W. H., & Shavelson, R. J. (2007). Estimating 
causal effects using experimental and observational design. American Educational & 
Reseach Association.