Smartphone Cognitive Behavioral Therapy for Body Dysmorphic Disorder: A Randomized, Waitlist-control Trial
Phase: NA
Conditions: Body Dysmorphic Disorder
Sponsor: Massachusetts General Hospital

 
1 
 
Study Protocol and 
Statistical Analysis Plan (SAP) 
 
SMARTPHONE COGNITIVE BEHAVIORAL THERAPY FOR BODY DYSMORPHIC 
DISORDER: A RANDOMIZED, WAITLIST-CONTROL TRIAL 
 
Principal Investigator:  
 
Sabine Wilhelm, PhD 
Chief of Psychology 
Massachusetts General Hospital & Harvard Medical School 
Boston, MA, United States of America 
 
 
Ethical approval:  
 
 
Mass General Brigham Institutional Review Boards  
(protocol # 2017P000293, approved on 04/03/2017) 
 
 
ClinicalTrials.gov identifier:   
NCT03673046 
 
 
Funding:  
 
 
 
This study was funded by Koa Health (formerly Telefonica  
Alpha). Investigators from MGH developed the Perspectives 
app in collaboration with technologists and designers from 
Koa Health via a user-centered, iterative design approach. 
The investigators from MGH were responsible for the study 
design and for the execution of the study; authors from Koa 
Health supported the technical activities related to the 
development and deployment of the app, and provided 
funding for the project. Koa Health had no role in the 
recruitment of participants and had no access to data during 
the trial. 
 
 
Document Date:  
 
 
June 21, 2022 (shortened version) 
 
 
 
 
 
Last IRB-approved update: March 11, 2022 
 
 
Author  
 
 
 
Susanne Hoeppner, PhD, MApStat 
Assistant Professor of Psychology 
Massachusetts General Hospital & Harvard Medical School 
Boston, MA, United States of America 
 
 
Version 
 
 
 
Draft 1.0 
 

 
2 
 
 
 

 
3 
 
DEVELOPMENT OF A COGNITIVE BEHAVIORAL MOBILE APP FOR BODY 
DYSMORPHIC DISORDER – PHASE II: TEST OF EFFICACY 
 
I. 
BACKGROUND AND SIGNIFICANCE 
 
A. Background 
 
BDD is a psychiatric illness that involves a preoccupation with an imagined or greatly exaggerated defect 
in one’s physical appearance (American Psychiatric Association [APA], 2013). This obsessive 
preoccupation causes clinically significant distress or impairment in functioning (e.g., social, occupational 
functioning). BDD is also defined by repetitive, compulsive behaviors performed in response to 
appearance concerns, such as frequent mirror checking (Alliez & Robin, 1969), excessive grooming 
(Vallat et al., 1971), and skin picking (Phillips & Taub, 1995). BDD is classified as an Obsessive 
Compulsive Related Disorder in the DSM-5, to reflect its similarities with obsessive compulsive disorder 
(OCD).  
 
Individuals with BDD often have poor insight, such that the individual fixedly believes that their 
appearance is truly defective. In fact, approximately one third of patients have delusional beliefs (Phillips, 
2006a). Delusions in BDD focus solely on one’s appearance, in contrast to severe psychotic illnesses like 
schizophrenia. Individuals with BDD also experience high rates of comorbid major depression (i.e., in 53-
81% of cases) and elevated risk for suicide (Frare et al., 2004; Phillips et al., 2005; Phillips et al., 2007). 
BDD’s early onset and chronicity underscore the need to widely disseminate effective treatments.  
 
Cognitive-behavioral therapy (CBT) is the best-studied and most promising form of psychological 
treatment for BDD (for meta-analysis see Harrison et al., 2016). CBT for BDD is a time-limited 
psychotherapy focused on targeting maladaptive thinking and self-defeating behaviors. Specifically, CBT 
aims to teach patients how to identify and challenge maladaptive thoughts (“cognitive therapy,” [CT]), 
while reducing safety behaviors such as rituals and avoidance (“behavior therapy,” [BT]). Most studies 
have included both cognitive and behavioral components, consisting mainly of exposure and response 
prevention (ERP) to reduce social avoidance and repetitive behaviors (such as mirror checking) and have 
shown that CBT is effective for BDD in both group (Rosen, Reiter, and Orosan, 1995; Wilhelm et al., 
1999) and individual formats (McKay et al., 1997; Neziroglu et al., 1996; Veale et al., 1996; Wilhelm et 
al., 2019). Furthermore, one recent study has developed and pilot-tested an Internet-based CBT treatment 
for BDD (Enander et al., 2016). Participants were randomly assigned to receive either 12 weeks of CBT 
or supportive psychotherapy for their BDD over the Internet, with a very limited amount of therapist 
support via the online program. Those in the CBT group showed significantly greater improvement 
compared to those in the supportive psychotherapy arm, and 56% of those in the CBT group were 
treatment responders compared to 13% in the supportive psychotherapy arm (Enander et al., 2016). 
Secondary outcomes such as depression and quality of life also showed significantly greater improvement 
in the CBT group compared to supportive psychotherapy group, suggesting that technology-based CBT 
treatments for BDD may be feasible, safe, and effective.  
 
B. Rationale for Proposed Research, and Potential Benefits to Participants and/or Society: 
 
While well-validated treatment for BDD exists, CBT for BDD is highly specialized and, thus, very 
difficult for patients to access. At our specialty program (the MGH BDD Program), there are consistent 
waitlists of 3-6 months to obtain access to a CBT therapist for BDD. In rural locations, access to this 
specialized treatment is likely to be even more challenging. Untreated BDD has a chronic, unremitting 
course, underscoring the importance of access to treatment. Inadequate treatment access due to limited 
professionals offering this specialized treatment is compounded by economic barriers and shame 

 
4 
 
preventing many sufferers from seeking in-person care (Fang et al., 2014). Mobile app-based CBT would 
solve the access gap by addressing each of these barriers.  
 
To this end, development of a high-quality CBT mobile app based on our program’s empirically 
supported intervention is likely to benefit individuals with body image concerns, ranging from the severe 
end (i.e., BDD), which occurs in 1.7-2.4% of the population (Fang et al., 2014) to milder subclinical body 
image disturbances, which occur in nearly half the population (Cash & Henry, 1995), by providing low-
cost, rapid, widely available access to CBT for BDD.  The app may also benefit healthcare providers 
(e.g., psychologists, psychiatrists, dermatologists) as it could be used as either a stand-alone treatment or 
in conjunction with treatments with a provider. We recently developed a smartphone-delivered CBT 
treatment for BDD and examined its preliminary feasibility and acceptability in participants seeking 
treatment for BDD (see study record NCT03221738). In this trial, we sought to test the efficacy of the 
smartphone-delivered CBT treatment for BDD.  
 
II. 
SPECIFIC AIMS 
 
The purpose of this project was to test the efficacy of a mobile-app version of CBT treatment for BDD.  
 
Specific Aim 1: In a waitlist-controlled trial, we will test the efficacy of the active treatment arm 
compared to a waitlist in reducing primary (i.e., BDD severity) at end-of-treatment (week 12). 
 
Primary Hypothesis: We hypothesize that participants receiving app-based CBT for BDD will 
have greater improvement in BDD-YBOCS scores than those in the waitlist condition at 
treatment endpoint (week 12).  
 
Specific Aim 2: In a waitlist-controlled trial, we will test the efficacy of the active treatment arm 
compared to a waitlist in reducing secondary outcomes (e.g., delusionality, quality of life, social and 
occupational functioning, depression) at end-of-treatment (week 12). 
 
Secondary Hypothesis: We hypothesize that participants receiving app-based CBT for BDD will 
have greater improvement on secondary clinical outcome measures (i.e., depression (QIDS-SR), 
delusionality (BABS), functional impairment (SDS), and quality of life (Q-LES-Q)) than those in 
the waitlist condition at treatment endpoint (week 12). 
 
 
III. 
SUBJECT SELECTION 
 
Overview: 
 
Massachusetts General Hospital was responsible for all participant recruitment and enrollment. We 
collaborated with Koa Health B.V., a in the testing of the app. 
 
For this Phase 2 randomized waitlist control trial, our target sample size was 80 eligible individuals with 
primary BDD (for details, see section VI-D “Power analysis”). Detailed eligibility criteria for each aim 
follow. Additionally, a detailed plan for safety and risk management is described below. 
 
Inclusion/Exclusion Criteria: 
 
1. Inclusion criteria 
a. at least 18 years of age  
b. current diagnosis of primary DSM-5 BDD, based on MINI 

 
5 
 
c. currently living in the United States 
2. Exclusion criteria 
a. Psychotropic medication changes within 2 months prior to enrollment 
i. Participants taking psychotropic medication must have been on a stable dose for 
at least 2 months prior to enrollment and not change medication during study 
period 
b. Past participation in > 4 sessions of CBT for BDD 
c. Current severe substance use disorder 
d. Lifetime bipolar disorder or psychosis 
e. Acute, active suicidal ideation as indicated by clinical judgment and/or a score > 2 on the 
suicidal ideation subscale of the C-SSRS. 
f. Current severe comorbid major depression, as indicated by clinical judgment and/or a 
QIDS-SR total score ≥ 21   
g. Concurrent psychological treatment 
h. Does not own a supported mobile Smartphone with a data plan  
i. 
Lack of technology literacy that would interfere with ability to engage with smartphone 
treatment 
 
  
A. Source of Subjects and Recruitment Methods: 
 
 
Overview: 
 
Participants were informed about the study through advertisements on public transportation, OCD and 
BDD-focused organizations nationally (e.g., International Obsessive Compulsive Disorder Foundation, 
Association for Behavioral and Cognitive Therapies), by OCD and BDD clinician and research colleagues 
nationally, fliers posted in specialty clinics and hospitals, coffee shops, restaurants, laundromats, barber 
shops, churches, daycares, libraries, newspapers, universities, other public locations, through our 
program’s website and the recruitment website created for this study, Partners Clinical Trials, listservs 
(e.g., MGH Broadcast), on the Internet, search engine platforms, and in online support groups and social 
media. Individuals were also recruited as part of the BDD clinic’s general recruitment protocol. Interested 
individuals were referred to the study research assistant (RA), who provided more information about the 
research study and assessed preliminary eligibility over the telephone. We also used a screening 
questionnaire on REDCap; the link to access this screener was embedded within our recruitment website.  
 
IV. 
SUBJECT ENROLLMENT 
 
A.  Procedures for obtaining informed consent and assessing eligibility 
 
Interested and eligible participants were invited to complete the baseline assessment with a trained 
independent evaluator (IE) by Healthcare secure Zoom, phone, or Virtual Visit, a Partners IS-approved, 
secure, HIPAA-compliant video calling program (see more Virtual Visit information below: “Monitoring 
and Quality Assurance”), as recruitment was nation-wide.  At that time, patients were informed about the 
study’s purpose and procedures in more detailed and were advised regarding alternative treatment 
options. Before eligibility was assessed, trained clinician-level staff obtained electronic informed consent 
through REDCap, a secure data capture system (see more REDCap information below: “Monitoring and 
Quality Assurance”). The person obtaining informed consent also verified the participant’s identity by 
requesting to view a form of identification (e.g., government-issued driver’s license). Subjects were given 
as much time as they needed to consider participation. Participants had the ability to download and print 
or save the electronic informed consent document. The research assistant also emailed participants a 
signed pdf copy of the consent form for their records.  
 

 
6 
 
B. Treatment assignment and randomization (if applicable) 
 
Eligible subjects were randomized to immediate app-based CBT for BDD or to a waitlist control 
condition (50/50 chance). Randomization was stratified by participants’ medication status, in order to 
evenly distribute any potential medication effects on treatment response across both study arms. The 
waitlist control group allowed us to determine whether active treatment is superior to gains afforded by 
the passage of time or other extraneous variables (e.g., history, maturation, testing). Those beginning the 
CBT treatment immediately were taught to download the app and received a brief tutorial in using the 
app-based treatment. Following the waitlist period, participants randomized to this condition were crossed 
over to app-based CBT to allow assessment of within-subject treatment gains for control participants. The 
duration of CBT for waitlist participants was the same as for participants who were treated first with 
CBT.  
 
Wait Period: To maximize the validity of our study, we matched the duration of the waitlist condition to 
that of the CBT condition. We successfully used a similar design in the PI's prior BDD trial assessing in-
person individual CBT. Furthermore, Veale et al (1996) has shown that patients do not improve on a 12-
week waitlist and that this duration is tolerated by BDD patients. To protect the safety of participants 
assigned to the waitlist condition, participants who had active suicidal ideation at the screening 
assessment were not eligible to participate in this trial (see Exclusion criteria). Additionally, individuals 
with severe comorbid major depression were not eligible to participate this trial (see Exclusion criteria). 
The waiting period for standard care for BDD at MGH is at least 3-6 months. Thus, being on a 3-month 
waitlist in the proposed study may enable the subject to start treatment sooner than being on the general 
clinic waitlist. However, we offered referral resources to study candidates who did not wish to be 
randomly assigned to a possible waitlist condition. 
 
V. STUDY PROCEDURES 
 
Following screening and randomization, participants completed self-report measures for the baseline 
assessment through a secure REDCap link emailed to them. In this trial, we aimed to evaluate changes in 
primary symptoms as well as to examine secondary and exploratory outcomes, including treatment 
feasibility and acceptability (e.g., retention and reasons for treatment refusal and dropout, expectancy, and 
motivation), and changes in depression, functional impairment, delusionality, and quality of life. 
Therapeutic progress will be broadly assessed with measures of beliefs, behaviors, mood, functioning, 
and quality of life before, during, and after treatment.  
 
Study Visits and Procedures 
 
Phone Screen: Phone screen procedures were as described above.  
 
Screening Calls and Randomization Procedures: Procedures were as described above.  
 
Assessments: Participants in both conditions were assessed at regular intervals: at baseline (week 0), mid-
treatment (week 6), end-of-treatment (week 12), and a 3-month follow-up visit (for details, see Table 1 
below). Masters or doctoral-level study IEs conducted clinician-rated assessments, and participants 
completed self-report questionnaires on the computer via REDCap, a secure data capture system. Please 
see the schedule of assessments and measures administered (relevant to the primary and secondary aims 
of this trial) at each time point in Table 1. Assessments required approximately 1 hour. These assessment 
lengths are like those used in other studies in our program and have been well-tolerated by participants. 
To avoid dropout, participants were paid $25 for mid-waitlist, end-of-waitlist, mid-treatment, end-of-
treatment, 3-month follow up assessments, and 12-month follow-up assessments. Despite our best efforts 
to retain participants, we expected dropouts. Except for subjects who withdrew consent to participate, all 

 
7 
 
who were withdrawn or dropped out of the study were asked to complete all scheduled assessments and 
were provided remuneration for participation in assessments. 
 
3-month Follow-up Feedback to Technologists: Participants could choose to meet with technologists from 
Koa Health (sponsor) via a Partners-approved, secure, HIPAA-compliant clinical video platform 
(Healthcare secure Zoom) at the 3-month follow-up, for the technology experts to obtain input and 
feedback on the usability and feasibility of the CBT app. This meeting would take approximately 1.5 
hours, and participants would be reimbursed $25 for completion of the 3-month follow-up feedback visit 
with technologists.  
 
 
 

 
8 
 
Table 1: Measures table 
 
RANDOMIZED CONTROL TRIAL: ARM 1 
COMPASSIONATE CARE (WAITLIST CONDITION 
CROSSES TO APP) 
Measure 
Baseline 
Baseline 
Re-assess 
Weekly  
Week 4 
Mid-
Treatment 
Assess 
(wk 6) 
Post-
Treatment 
Assess 
(wk 12) † 
 
3-month 
Follow-up* 
12-month 
Follow-up* 
Weekly  
Week 4 
Mid-Treatment 
Assess (wk 6) 
Post-
Treatment 
Assess (wk 12) 
Treatment History 
Checklist 
 ᤰ
ᤱ 
 
 
 
 
 
 
 
 
 
 
 
Treatment History 
Medication  
 ᤰ
ᤱ 
 
 
 
 
 
 
 
 
 
 
 
Treatment History 
Psychosocial 
 ᤰ
ᤱ 
 
 
 
 
 
 
 
 
 
 
 
AE Form 
 
 ᤰ
ᤱ 
 
 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
 
 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
Body Parts of 
Concern Checklist 
(BPCC) 
 ᤰ
ᤱ 
 
 
 
 
 
 
 
 
 
 
 
BDD Y-BOCS 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
 
 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
 
 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
BABS 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
 
 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
 
 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
MINI 
 ᤰ
ᤱ 
 
 
 
 
 
 
 
 
 
 
 
C-SSRS Lifetime 
 ᤰ
ᤱ 
 
 
 
 
 
 
 
 
 
 
 
C-SSRS Update 
 
 ᤰ
ᤱ 
 
 
 
† 
 
 
 
 
 
 
CGI–C 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
 
 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
 
 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
Treatment 
Condition 
Questionnaire 
 
 
 
 
 
 ᤰ
ᤱ 
 
 
 
 
 
 
CONCOM Form 
 
 ᤰ
ᤱ 
 
 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
 
 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
BDD-PSR 
✔ 
✔ 
 
 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
 
 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
Life Events 
Question 
 
 ᤰ
ᤱ 
 
 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
 
 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
Technologist 
Interview Notes 
 
 
 
 
 
 
 ᤰ
ᤱ 
 
 
 
 
 
PHQ-2  
 
 
 ᤰ
ᤱ 
 
 
 
 
 
 ᤰ
ᤱ 
 
 
 
QIDS-SR – Q12  
 
 
 ᤰ
ᤱ 
 
 
 
 
 
 ᤰ
ᤱ 
 
 
 

 
9 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
If more than ten days elapse between a patient’s initial baseline screening assessment and the start of treatment, the study IE would re-administer the AE form, AE log, BDD-YBOCS, BABS, CONCOM 
form, CMED log, and CTHERAPY log to that participant, and they would complete an additional CGI-P (see “Baseline Re-Assess,” above).  
 
† Post-treatment assessment also functions as the baseline assessment for those in waitlist condition, who cross over into compassionate care. † indicates supplemental measures added only for 
compassionate care baseline.  
* Participants in CBT condition go directly into follow-up assessments after week 12. Those in waitlist condition complete follow-up assessments after compassionate care.  
᷉ Only administered in the RCT active treatment group (not waitlist) during the first 12 weeks of the trial. 
 
CGI-P  
 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
Demographics  
 ᤰ
ᤱ 
 
 
 
 
 
 
 
 
 
 
 
Lifetime Psychiatric 
Medications  
 ᤰ
ᤱ 
 
 
 
 
 
 
 
 
 
 
 
Credibility 
Expectancy Rating ᷉ 
 ᤰ
ᤱ 
 
 
 
 ᤰ
ᤱ 
† 
 
 
 
 
 ᤰ
ᤱ 
 
QIDS-SR 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
 
 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
 
 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
QLESQ 
 ᤰ
ᤱ 
 
 
 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
 
 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
SDS 
 ᤰ
ᤱ 
 
 
 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
 
 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
CSQ ᷉ 
 
 
 
 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
 
 
 
 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
Treatment 
Utilization 
Questionnaire ᷉ 
 
 
 
 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
 
 
 
 ᤰ
ᤱ 
 ᤰ
ᤱ 
App Feedback 
Questionnaire 
(Endpoint) ᷉ 
 
 
 
 
 
 ᤰ
ᤱ 
 
 
 
 
 
 ᤰ
ᤱ 
App Feedback 
Questionnaire 
(Baseline) ᷉ 
 ᤰ
ᤱ 
 
 
 
 
† 
 
 
 
 
 
 
App Feedback 
Questionnaire 
(Midpoint) ᷉ 
 
 
 
 
 ᤰ
ᤱ 
 
 
 
 
 
 ᤰ
ᤱ 
 

 
 
10 
 
Measures Descriptions 
 
Diagnostic Measures 
 
Mini International Neuropsychiatric Interview (M.I.N.I.): The M.I.N.I.  (Sheehan et al., 1998) is a 
semi-structured diagnostic assessment of DSM-5 psychiatric illnesses. The M.I.N.I. is efficient, reliable, 
and well-validated. It was the sole/primary diagnostic evaluation used to assess for psychiatric diagnoses 
and establish inclusion and exclusion criteria.  
 
Assessment of Body Image and Related Symptoms 
 
 
Yale Brown Obsessive Compulsive Scale Modified for BDD (BDD-YBOCS) : This gold-standard 
12-item semi-structured clinician-administered scale rates past-week BDD symptom severity (Phillips et 
al., 1997). It will be the study's primary outcome measure. The BDD-YBOCS has excellent internal 
consistency (α=.80), interrater and test-retest reliability (ICC for total score=.99 and .88, respectively), 
convergent validity (r=.55 with the CGI), and sensitivity to change (Phillips et al., 1997). 
 
 
BDD-Symptom Scale (BDD-SS): The PI developed the BDD-SS to rate the severity of specific 
BDD symptoms (Wilhelm et al., 2016). It will be used in the present study to obtain a broader assessment 
of participants’ BDD symptoms and associated thoughts, feelings, and behaviors.  
 
 
Clinical Global Impression – Improvement Scale (CGI-I) and severity scale (CGI-S): This rating 
scale, which ranges from 1 (very much improved) to 7 (very much worse), is commonly used in clinical 
trials (Guy, 1976). Participants completed a CGI for BDD symptoms (CGI-BDD) and the IEs completed a 
CGI for BDD symptoms (CGI-BDD) and overall symptoms (CGI-global). The CGI was a secondary 
outcome measure and was also used to determine clinical deterioration of BDD (see Minimizing Risks, 
below). The CGI also has a severity scale (CGI-S) which was rated by the IE at baseline. The CGI-S 
determines the patient’s level of severity, in comparison to others the IE (clinician) has treated or assessed 
with the same diagnosis.  
 
 
  Psychiatric Status Rating Scale for Body Dysmorphic Disorder (BDD PSR): The BDD PSR 
(Phillips et al., 2006b; Phillips et al., 2013) is a 7-item, clinician-completed rating scale of the patient’s 
BDD diagnostic status. It ranges from 1 (Full Remission) to 7 (Meets full diagnostic criteria with 
extreme/severe BDD).  
 
 Brown Assessment of Beliefs Scale (BABS): This 7-item semi-structured clinician-administered 
interview assesses delusional thinking related to one’s appearance concerns (Eisen et al., 1998). It has 
very strong psychometric properties, including internal consistency, interrater and test-retest reliability, 
convergent validity, divergent validity, and sensitivity to change (Eisen et al., 1998). 
 
Patient Health Questionnaire-2 (PHQ-2): The PHQ-2 (Kroenke & Spitzer, 2002) self-report 
measure of depression severity includes 2 Likert scale items ranging from 0 (not at all) to 3 (every day). 
The 2 items are taken from the longer PHQ-9 measure and are selected because they assess the core 
diagnostic symptoms of depression. The PHQ-2 was administered weekly via the app to monitor changes 
in depression symptom severity. 
 
 
Quick Inventory of Depressive Symptomatology- Self Report (QIDS-SR): The QIDS-SR (Rush et 
al., 2003) is a self-report measure of depressive symptoms consisting of 16 scale items with responses 
ranging from 0 to 3, including one suicide item (item #12). Higher scores correspond with greater 
depression severity, and the measure is well-validated, sensitive measure of symptom severity in 
depression. The response choices on the suicide item include 0: “I do not think of suicide or death”; 1: “I 

 
 
11 
 
feel that life is empty or wonder if it’s worth living”; 2: I think of suicide or death several times a week 
for several minutes”; and 3: “I think of suicide or death several times a day in some detail, or I have made 
specific plans for suicide or have actually tried to take my life”. Scores on the QIDS-SR were used to 
evaluate eligibility at the screening visit, and to measure self-reported depressive symptoms at subsequent 
assessment visits. The QIDS-SR i12 was delivered weekly to participants via the app (in the active group) 
or via REDCap (in the waitlist group) to monitor for risk concerns during the trial. Scores >0 triggered a 
popup message to the participant about calling 911/going to the ER, and participants were provided 
information about contacting a suicide hotline. Scores >1 also triggered a text message alert to the coach 
with the specific item response given by the participant (i.e., 2 vs. 3). Study clinicians followed up with 
the participant within 24 hours by phone to assess for risk, and to refer to a higher level of care if 
clinically indicated (see Minimizing Risks, below). After an initial alert for a participant, study clinicians 
used clinical judgement when determining follow-up for additional alerts.  
 
 
Columbia-Suicide Severity Rating Scale (C-SSRS): The C-SSRS (Posner et al., 2011) is a gold-
standard, clinician-administered assessment of suicidal ideation and suicide behaviors. The baseline 
version, which assesses both lifetime and recent time frames, was used to establish eligibility at the 
baseline/screening visit. The “Update” version, which assesses suicide risk since the last assessment, was 
used at subsequent study administrations. 
 
 
Body Parts of Concern List: This list names a wide range of body parts that are the most common 
areas of appearance concerns for BDD patients. The measure asks participants to indicate which body 
parts they are preoccupied with.  
 
Assessment of Functioning and Quality of Life 
 
 
Sheehan Disability Scale (SDS): The SDS uses a Likert scale from 0 (not at all) to 10 (extremely) 
to assess impairment in occupational, social, and family domains. It has strong internal consistency and 
validity (Sheehan et al., 1996).  
 
Quality of Life Enjoyment and Satisfaction Questionnaire – Short Form (Q-LES-Q-SF): The Q-
LES-Q-SF (Endicott, Nee, Harrison, & Blumenthal, 1993) is a self-report measure of subjective quality of 
life. Higher scores correspond with greater ratings of quality of life. The Q-LES-Q-SF has strong 
psychometric properties (Endicott et al., 1993).   
 
Assessment of Expectancy, Motivation and Satisfaction 
 
 
Credibility and Expectancy Questionnaire (CEQ): This 6-item self-report questionnaire assesses 
patients’ judgments about the credibility of the treatment rationale, expectancy of change, and treatment 
acceptability (Borkovec & Nau, 1972). It has good reliability (α=.81-.86), and validity is evident in its 
ability to differentiate between treatment rationales (Devilly & Borkovec, 2000).  
 
 
The Client Satisfaction Questionnaire (CSQ): The CSQ is a 25-item self-report questionnaire 
which assesses the satisfaction with clinical services received. It has excellent internal consistency and 
good discriminant validity (McMurtry & Hudson, 2000). 
 
 
Open-Ended Feedback Question: is a 1-item open-ended question to obtain feedback from the 
participant after completion of each treatment module. The question asks, “Can you describe what you 
liked and didn’t like about this activity?” Participants provide a free-text response.  
 
 
 
 

 
 
12 
 
Other Assessments 
 
Treatment History Medication, Treatment History Psychosocial, Treatment History Checklist 
forms: These forms together were used to assess any current medications (past 2 months) taken as well as 
any current or lifetime psychosocial treatment. 
 
Lifetime Psychiatric Medication Form: This self-report form collected lifetime psychiatric 
medications taken and was administered at the baseline screening visit. 
 
Concomitant medication and therapy form: This log tracked any changes in medication and 
therapy that the participant made since the prior assessment.  
 
 
Demographics Form: This self-report form collected basic demographic data and was 
administered at baseline.  
 
Treatment Utilization Questionnaire: This self-report form measures how much time participants 
are practicing treatment skills both on and off the app. It was completed as a self-report measure at the 
mid-treatment assessment and end of treatment visits. 
 
App Feedback Questionnaire (Baseline): This self-report questionnaire asks about participant’s 
expectations of using the app (e.g., “How frequently do you intend to use Perspectives?”) 
 
App Feedback Questionnaire (Midpoint): These multiple choice/open-ended questions ask 
participants to describe their ongoing perceptions of the app at midpoint (e.g., “How easy are the 
exercises to understand, overall?”).  
 
App Feedback Questionnaire (Endpoint): This self-report form collects participant feedback 
pertaining to the content and aesthetics of the app (e.g., “How clear was the layout of the app?”)  
 
Technologist Interview Notes: This interview guide asks about credibility/expectancy, client 
satisfaction, and improvements at trial completion. Of note, technologists from Koa Health who 
conducted over-the-phone feedback interviews were hired and paid by the sponsor, Koa Health. These 
interviews were not considered part of the human subjects research and was development work for the 
app. Therefore, they were not included as study staff, but the informed consent process fully informed 
participants about the interactions with technologists and as such, these procedures are described in full in 
this protocol. MGH study staff introduced participants to the technology experts via phone call or email 
introduction after the participant was fully consented. This served to protect participants’ identifying 
information (e.g., we did not share access to participants’ email addresses or phone numbers, but rather 
MGH study staff-initiated conference calls and scheduled appointments between participants and 
technologists). 
 
Treatment Condition Questionnaire: This brief measure will be used to assess whether the 
independent evaluator believes each subject was assigned to either immediate CBT or waitlist, as well as 
their confidence in this belief. This questionnaire was completed at the end-of-treatment assessment (i.e., 
the week 12 visit). This measure is based on Bang’s 2x5 Blinding Index (Bang et al., 2004). 
 
Life Events Questionnaire: This question will be used to assess whether any major life events 
occurred that might have had a psychological impact on the subject. 
 
 

 
 
13 
 
 
App-Based Data 
 
Data from sensors in participants’ mobile phones were collected, to optimize the program through 
personalization and improve the app. (For a detailed description of storage and protection of de-identified 
mobile data, see Monitoring and Quality Assurance, below.)  
 
Application Usage Metrics: To improve the usability of the application, usage metrics may be collected 
(for example, operating system version and device model, time and date when the application is opened or 
closed, time spent on each page visited, notification timing, etc.).  
  
The Treatment 
 
The CBT app included the following components of CBT for BDD: 1) education about a CBT model of 
BDD; 2) use of self-monitoring to record trigger situations and symptoms; 3) cognitive techniques to 
identify and challenge distorted thoughts related to one’s BDD; 4) exposure to avoided situations; 5) 
response prevention to decrease repetitive behaviors; 6) mindfulness/ perceptual retraining (to help 
patients to learn to balance distressing emotional states with rational thinking and to control their 
attentional processes); 7) increasing valued activities, and 8) relapse prevention (to teach patients to 
expect and react effectively to setbacks that may occur during times of stress). Details of the app-
treatment are described further in the manuscript of the pilot study (Wilhelm et al., 2020).  
 
Treatment Length: We tested a 12-week version of app-treatment. Twelve-week CBT treatments for BDD 
have been tested previously and shown to be acceptable and effective (e.g., Veale et al., 2014), including 
in a computer-delivered format (Enander et al., 2016). Participants had access to the Perspectives app and 
coach support throughout the 12-week treatment. During the follow-up phase of the study, participants 
continued to have access to the Perspectives app, but without the coach support or messaging system.   
 
Module Frequency and Duration: An advantage of app-based CBT for BDD is that participants were able 
to self-direct the frequency and duration of modules, and they were able to re-visit sessions as many times 
as is useful to them.  
 
Treatment Format: Each treatment component was presented through modules on the mobile app, and 
exercises were logged and practiced through the app on participants’ smartphones. Upon initiating the 
app-based CBT treatment, each participant was assigned a BA-level coach with some training in CBT and 
some familiarity with BDD; coaches will be supervised weekly by a licensed psychologist (see “Coach 
Training and Qualifications,” below). Participants were able to communicate with their coach through a 
secure messaging system incorporated into the app throughout the 12-week treatment. The coaches had a 
separate portal inside the Partners firewall to receive and respond to these in-app communications from 
patients. The coach communication aimed to provide support and additional motivational enhancement to 
patients, and to provide feedback about the skills and homework that the patients were learning through 
the app. Patients were notified that their coach would respond to all in-app communications within 36 
hours on weekdays. Moreover, brief phone check-ins could be arranged between the participants and 
coaches on an as-needed basis to supplement the chat system (e.g., to more thoroughly answer a 
participant question about a skill, help set goals for 2nd half of treatment at treatment mid-point, evaluate 
and enhance motivation). During the 3-month follow-up phase of the study, participants continued to have 
access to the app, but without the coach support or messaging system. Participants lost access to the app 
following the 3-month follow-up period and did not have access to the app between the 3-month and 12-
month follow-up assessments. Based on a similar, online CBT treatment for BDD (Enander et al., 2016) 

 
 
14 
 
and our own feasibility and acceptability trial (Wilhelm et al., 2020), we expected average coach contact 
per week to be minimal (e.g., less than 15 minutes per week, per patient). 
 
In-App Coach Training and Qualifications: BA-level coaches were study staff members with a 
Bachelor of Arts (BA) or Bachelor of Science (BS) degree in Psychology or a related field. Based on 
preliminary findings from our feasibility and acceptability trial, we anticipated that the coaches’ 
involvement would be light-touch and focus mostly on motivation and problem-solving, as needed, 
whereas the app itself would be the primary mode of treatment delivery. Specifically, in our pilot trial the 
coach spent less than 2.5 minutes per patient per week on average responding to chat messages. Research 
on technology-based treatments likewise suggests that coaches primarily serve to motivate patients and 
increase accountability and adherence. Coaches received training before assisting in treatment as a coach 
(e.g., completing the MGH Psychiatry Academy CBT training course for BDD) and were required to pass 
(>90% correct) the MGH Psychiatry Academy BDD knowledge test. To ensure ongoing high-quality 
treatment, study staff members who were licensed clinicians with expertise in CBT for BDD provided 
weekly supervision to coaches, with additional supervision as needed if questions arose. 
  
IE Training and Qualifications, and Procedures to Ensure Assessment Integrity and Interrater 
Reliability  
 
Assessments were conducted by independent evaluators (IE) who had Masters or Doctoral-level degree in 
clinical psychology or related mental health fields and who were employed at MGH. The IEs were 
otherwise uninvolved in study procedures. Training and reliability checks were done to ensure that IEs 
conducted ratings in a uniform way. Raters first received instruction in the SCID-I/P, MINI, SCID-II, 
BDD-YBOCS, BABS, and CGI from Dr. Wilhelm or another gold-standard expert rater, prior to 
beginning as an IE. The IEs were then supervised twice monthly by the PI. The IE were required to 
demonstrate reliability on the BDD-YBOCS and BABS at a criterion of .80 ICC, compared to measures 
rated by Dr. Wilhelm or another gold-standard rater. All assessments were audiotaped for reliability 
ratings. Names were not included on digital recordings. To reduce rater drift, a trained reliability rater 
meeting the same qualifications as the IE reviewed 15% of randomly selected audiotaped interviews at 
regular intervals. IEs were blind to randomized conditions.  
 
Privacy and Confidentiality  
 
All information gathered was kept strictly confidential. We adhered to the following procedures to protect 
privacy and confidentiality: 
1) Participants were assigned a code number (study ID) that was used in all email communications or 
shared data files outside of the secure MGH lab server or Partners Dropbox Business. Participants’ names 
or other identifying information did not appear on any questionnaires, study documents, digital 
recordings, computerized data files, or published reports. Case records were reviewed only by study 
personnel or, if necessary, by institutional, sponsor-assigned, state, or federal regulatory personnel. 
Research assistants and others working on this study (e.g., technologists) were educated about the 
importance of strictly protecting participants' rights to confidentiality. 
2) All personnel was trained in research confidentiality procedures and HIPAA, including completion of 
CITI training and Healthstream training. Only the study personnel (or, if necessary, institutional, sponsor-
assigned, state, or federal regulatory personnel) had access to the identifiable data.  
 
3) Clinical data collected during MGH assessments: Computerized data and digital audio files were stored 
de-identified, in password protected files saved on the protected lab server. Data within Partners is stored 
automatically and securely on an MS SQL Server, accessed over industry standard SSL 128 bit RSA 

 
 
15 
 
encryption during data transfers.  Data is routinely backed up locally onto a redundancy server and stored 
in a separate database that is locked with 256 AES encryption. Long term storage on Partners servers 
occurs nightly and allows for incremental backup over multiple systems. Data servers are stored within 
PHS IS corporate firewall, in a secure, key access facility with password protected computers.  Only 
trained PHS security officials will have access to physical machines storing study data. Since data are 
stored on a protected server, a compromise of any individual computer at a research facility will not lead 
to a breach of the secure database. Hard copy data (paper forms) were stored securely in locked file 
cabinets, within locked offices in the MGH OCD and Related Disorders Program.  
 
4) Technologist data: Computerized data and digital audio files collected from feedback interviews with 
technologists were stored de-identified, in password protected files in the Partners Healthcare Dropbox 
Business folder.  
 
5) Mobile data: All mobile data was transmitted from the participant’s mobile device to the clinical study 
server via an encrypted Internet connection. The clinical study server was located in the PHS/MGH 
Secure Data Center. The collected data was linked to the study identifier only. Prior to deployment of the 
digital application, the application was scanned with Veracode. 
 
6) Telehealth assessments were conducted using the Partners-approved platform for clinical video calls, 
which has been vetted by Partners to be secure and HIPAA-compliant. Participants were instructed in 
advance to be in a private location (e.g., in a room with closed doors) during the calls.  
 
7) Only de-identified data is shared with the sponsor (Koa Health), under the terms of the Data Use 
Agreement (i.e., Statement of Work).  
 
 
B. Drugs to be used 
Not applicable 
 
C. Devices to be used 
Participants downloaded the CBT for BDD app onto their personal smartphone devices. The CBT for 
BDD app is an investigational device in the United States.  
 
D.  Procedures, surgical interventions, etc. 
Not applicable 
 
E. Data to be collected and when the data will be collected 
See above for the assessment schedules and assessment batteries.  
 
VI. BIOSTATISTICAL ANALYSES 
The IE and the RA will play the primary role in data entry. Data will be entered in REDCap, a HIPAA-
compliant, Partners-approved platform for electronic data capture that streamlines data collection and 
management, and ensures data integrity, resulting in improved data quality and reduced costs. For more 
information on REDCap, please see section IX, “Monitoring and Quality Assurance.” 
The Center for OCD and Related Disorders biostatistician was responsible for data management and 
analysis. All project staff received training in data management and data confidentiality procedures. Data 
checks were done regularly to assure that all forms were entered and available for analysis. Data and 

 
 
16 
 
analysis files were be backed up on the lab server and, if paper records were used, were stored in separate 
locked cabinets.  
 
To characterize our sample, data was displayed graphically, and summary statistics (e.g., means and 
frequencies) were calculated for all variables, including demographic and clinical descriptors (e.g., from 
the MINI).  
 
Baseline differences between the treatment arms in demographic and other potential prognostic variables 
were examined using chi-square analyses for discrete variables (if prevalence >10% in the treatment arm 
with the lower prevalence, or Fisher’s exact test if not) and t-tests for continuous variables. Prior to data 
analysis, all major variables were screened for inconsistent or abnormal values. Continuous measures 
were assessed for skewness and outliers (based on model residuals); no data transformations were 
necessary to meet modeling assumptions of normality and homogeneity of variance. A two-tailed p-value 
<.05 was considered evidence of statistical significance for the primary and secondary outcomes. Our 
primary and secondary analyses used generalized linear mixed-effects models (GLMMs). GLMMs can 
easily accommodate nesting of repeated observations within subjects, include all who complete at least 
one assessment (including the baseline assessment), and are the preferred method to analyze longitudinal 
data (Hamer and Simpson, 2009). Despite our best efforts to retain participants, we expected dropouts 
(subjects who are lost to follow-up or withdraw early from the study). We attempted to perform all 
scheduled assessments for subjects who were withdrawn from the protocol and provided financial 
incentives for participation in assessments. Our intent-to-treat sample included all randomized patients 
who completed at least one assessment, making our primary and secondary analyses intent-to-treat 
analyses. We also performed “per protocol” analyses. Our per protocol population included all 
randomized patients who completed the baseline and post-treatment assessments, and who did not initiate 
prohibited treatment during the study. We repeated our GLMM analyses using the per protocol sample. 
Dropout, study withdrawal, and loss to follow-up was tabulated by reason and treatment arm. Analyses 
were conducted to ascertain to what extent dropouts were nonrandom, and, if so, what factors were 
associated with dropout. To evaluate potential attrition bias, study dropouts were compared to study 
completers.  
 
A. Specific data variables collected for the study (e.g., data collection sheets) 
Specific variables that were collected and their timeline are presented above in Table 1 and described in 
the Study Procedures section.  
 
B. Study endpoints 
 
Primary endpoint: Difference in BDD severity (BDD-YBOCS) at the end of treatment/waitlist period. 
Hypothesis 1:  Participants receiving app-CBT will have greater improvement in BDD-YBOCS 
scores than those in the waitlist condition at treatment endpoint (week 12).  
 
Secondary endpoints: Difference in secondary clinical outcomes at the end of treatment/waitlist period 
Hypothesis 2:  Participants who receive app-CBT will have greater improvement on secondary 
clinical outcome measures (i.e., depression (QIDS-SR), delusionality (BABS), functional 
impairment (SDS), and quality of life (Q-LES-Q)) than those in the waitlist condition at treatment 
endpoint (week 12).  
 
 
C. Statistical methods 
 
Primary endpoint: Preliminary efficacy for reducing BDD symptom severity 
 
Analysis: 

 
 
17 
 
The primary outcome model was a hierarchical mixed model (i.e., GLMM) that included time 
(categorical; baseline, mid-point, and end-of-treatment), treatment (app-CBT vs. waitlist), and 
their interaction as fixed effects, and modeled time as a repeated measure using either an 
autoregressive (AR1), Toeplitz, compound symmetry, or unstructured covariance matrix, based 
on best fit determined by AIC and BIC.  The main hypothesis test was based on a specific 
contrast of treatment difference at week 12.  Because these analyses included all subjects who 
were randomized and completed at least one assessment, it was an intent-to-treat analysis. These 
analyses included only the 3 assessments from baseline to post-treatment and did not include the 
follow-up (FU) assessments, because treatment response could be affected by subjects seeking 
other treatments during the FU period.  Between-group effect sizes were calculated using Cohen’s 
d. This analysis was then repeated using the per-protocol sample. 
In addition to the analyses specified above, we described the proportion of subjects in 
each treatment arm who achieved response, where response was defined as a 30% or greater 
reduction in BDD-YBOCS score from baseline to end of treatment (week 12). This empirically 
derived cut-off of 30% reflects clinically significant improvement and is widely used in BDD 
treatment studies (Phillips et al., 1997). While no formal comparison was made between 
treatments, the reporting of response rates is clinically useful and will facilitate comparison to 
other studies in the field. We reported response as observed (excluding subjects with missing data 
at week 12).  
 
Secondary endpoint: Preliminary efficacy for secondary outcomes 
Analysis: 
We used the same hierarchical mixed model approach as described for the primary endpoint to 
examine significant differences in secondary outcome measures (i.e., depression severity, 
delusionality, functional impairment, and quality of life) at posttreatment for treated participants 
compared to waitlist control participants. We did not adjust for multiple testing among secondary 
outcomes based on the recommendation of Cook and Farewell (1996), who argue that multiplicity 
adjustments are not necessary if separate test results are interpreted marginally and address 
different aspects of the patient experience and decision-making process rather than alternative 
assessments of efficacy.  
  
 
D. Power analysis 
 
Pre-COVID-19, the sample size required to test a significant symptom severity difference between the 
app-CBT and the waitlist control conditions at the end of treatment was estimated to be n=64 (n=32 per 
group).  The sample size estimates were based on a single degree of freedom contrast in an ANOVA 
design, implemented in SAS for Windows version 9.4.  The power model used a two-sided alpha=0.05, a 
power of 0.90, equal allocation of participants into both treatment arms (app-CBT vs. waitlist), and an 
anticipated effect size of 0.9.  We further assumed a drop-out rate of 15% by the end of treatment.  This 
anticipated effect size of the app-CBT is in the range of effect sizes calculated using the published 
estimate of a waitlist control group BDD-YBOCS mean after 12 weeks (source: Wilhelm et al., 2014), 
compared to either the combined site mean at week 12 in an in-person CBT treatment study for people 
with BDD (d=0.93; Wilhelm et al., 2019) or the mean at week 12 in an internet-based CBT treatment 
study for people with BDD (d=1.02; Enander et al., 2016).  More generally, large effect sizes for CBT vs. 
waitlist are to be expected, based on meta-analysis by Ost and colleagues (2015) for the closely related 
disorder OCD, which found that the weighted mean effect size of CBT vs. waitlist control was Hedges 
g=1.31, 95%CI: [1.08, 1.55].  The anticipated drop-rate was based on the weighted mean of drop-out rates 
(14.4%) reported in three studies that examined the efficacy of CBT treatment in participants with BDD: 
one compared to waitlist (n=36, 19.4% drop-out at week 12; Wilhelm et al., 2014), one compared to SPT, 

 
 
18 
 
in person (n=120, 23.3% drop-out at week 24; Wilhelm et al., 2019), and one comparing internet-based 
CBT vs. SPT (n=94, 1.1% drop-out at week 12; Enander et al., 2016). 
 
In the wake of the COVID-19 pandemic, various negative mental health states and stressors - 
including anxiety, worry, depression, loneliness, financial strain, and trauma symptoms - were likely to 
increase in the US population. Furthermore, the variability of these negative mental health states and 
stressors would have likely increased as multiple waves of the pandemic and state-wide measures of 
social interaction restrictions swept the nation in the foreseeable future. In response, we increased the 
planned sample size to a total n of 80 (40 per group) of participants who start treatment (i.e., those who 
are eligible and willing and able to participate); this increase was intended to be reflective of a decrease in 
the anticipated effect size from 0.90 to 0.81 (i.e., a 10% decrease of the anticipated effect size).  The plan 
for and justification of the sample size increase was reviewed by the Institutional Review Board at MGB 
prior to implementation.     
 
 
VII. RISKS AND DISCOMFORTS 
 
A. Complications of surgical and non-surgical procedures 
Not applicable 
 
B. Drug side effects and toxicities 
Not applicable 
 
C. Device complications/malfunctions 
If the app or supporting clinician/coach dashboard malfunctions or does not work for a period of time, the 
patient may be unable to use the app to receive treatment or communicate with their coach.  Similarly, if 
the clinician/coach dashboard were inaccessible, the coach would not be able to communicate via the app 
with the patient. These risks could result in minor harms to users such as inconvenience or a delay in 
treatment. If device malfunctions resulted in the patient's in-app weekly questionnaire responses not being 
sent to the coach/clinician, this could result in a delay in clinical response to an elevated safety 
questionnaire. To mitigate risks of a temporary device malfunction, participants were given the study staff 
and investigators’ contact information in the consent document. Thus, the clinical and study staff can 
communicate with the participant by phone call instead of through the app. As with in-person therapy, 
there are times when a therapy session gets cancelled and treatment, as well as weekly symptom 
assessments, were thus temporarily delayed. Likewise, in face-to-face therapy, a therapist may be 
temporarily out of reach at times (e.g., on vacation) and backup lines of communication (e.g., pager 
coverage by a colleague) were put in place in case of emergencies. Thus, device malfunctions that lead to 
temporary delays in accessing the app functionality are similar to risks associated with temporary delays 
in traditional face-to-face therapy. See also, “Minimizing of Risks and Safety Reporting” under “D. 
Psychosocial (non-medical) risks” for further description of protections in place.  
 
 
D. Psychosocial (non-medical) risks 
Participants may feel uncomfortable due to the sensitive nature of the questions they may be asked. 
Likewise, some participants may feel uncomfortable about having assessment sessions digitally recorded 
and reviewed by project staff (which is necessary for rater supervision as well as assessment of the 
reliability of ratings adherence and competence). Participants could experience an increase in symptoms 
or suicidal ideation related to the natural waxing and waning of BDD or other psychiatric (e.g., 
depression) symptoms. BDD can be associated with other psychiatric symptoms (e.g., depression, 
anxiety), as well as suicidal thoughts and behaviors, which may also change over time. Breach of 
confidentiality represents a potential risk. Finally, the treatment procedures, particularly the exposure 

 
 
19 
 
exercises, will potentially provoke some anxiety. As discussed below, we took precautions to ensure that 
these potential risks were minimized (see Adequacy of Protection Against Risks below). 
 
Minimizing of Risks and Safety Reporting.  
 
The following procedures were implemented to protect participants against risks:  
 
1. Participants with active suicidal ideation at the screening assessment were excluded from 
participating (see Inclusion/Exclusion criteria). If a subject scored ≥21 on the QIDS-SR and/or 
>1 on the QIDS-SR item #12, the independent evaluator followed up with a phone evaluation 
within 24 hours and referred the participant to a higher level of care if clinically indicated. 
Suicidal ideation at screening was also measured using the C-SSRS (see Inclusion/Exclusion 
criteria), and if a potential participant scored ≥2, a study clinician, PI, or independent evaluator 
conducted a risk evaluation with the participant and referred the participant to a higher level of 
care if clinically indicated. 
 
2. Participants with severe major depressive disorder were excluded from participating (see 
Inclusion/Exclusion criteria).  
 
3. A disclaimer that is accessible from the home page of the digital CBT program was presented to 
remind participants that if they were experiencing suicidal thoughts, they should seek 
professional help or go to the emergency room right away. Links to 911 and suicide hotline 
numbers were provided along with this disclaimer.  
 
4. A general resources page was available on the app at all times to participants, which included a 
suicide hotline number.  
 
Participants’ clinical improvement or deterioration was assessed weekly via a participant-rated 
CGI-BDD collected via the app (or REDCap, in waitlist condition). Participants could be 
withdrawn from the study if their clinical condition deteriorated substantially. Deterioration was 
defined by a combination of (1) a rating of 6 (much worse) or 7 (very much worse) on the 
weekly, participant-rated CGI-BDD across 2 subsequent weeks and (2) PI judgment that 
remaining in the study was not in the participant’s best interest. Of note, a single rating of 6 or 7 
on the weekly, participant-rated BDD-CGI also triggered a notification to the clinician/coach via 
text message and email. In the case that a BA-level coach was notified that a participant’s CGI 
indicates deterioration, they notified a doctoral-level clinician as soon as possible (and within 24 
hours). A study clinician then followed up with a phone evaluation within 24 hours of the alert 
and referred the participant to a higher level of care if clinically indicated. After an initial alert for 
a participant, study clinicians could use clinical judgement when determining follow-up for 
additional alerts.  
 
5. Ratings on the QIDS-SR item 12 (suicide item) were carefully monitored weekly via the app (or 
REDCap, in waitlist condition); a score >0 at any assessment triggered a pop up message to be 
presented to the patient within the mobile app reminding participants that if they were 
experiencing suicidal thoughts, they should seek professional help or go to the emergency room 
right away. Links to 911, as well as a national suicide hotline, were provided within this popup 
notification. A score >1 also triggered notification to the clinician/coach via text message or 
email. In the case that a BA-level coach was notified that a participant reported a score>1, they 
notified a doctoral-level study clinician as soon as possible (and within 24 hours). A study 
clinician, PI, or independent evaluator then followed up with a phone evaluation within 24 hours 
of the alert and referred the participant to a higher level of care if clinically indicated. After an 

 
 
20 
 
initial alert for a participant, study clinicians could use clinical judgement when determining 
follow-up for additional alerts.  
 
6. Participants could also be withdrawn if, in the judgment of the PI, remaining in the study posed a 
substantial risk to the participant or a higher level of care is needed.  
 
7. Treatment through app-based CBT was supplemented with electronic communication with a 
study coach, who could answer questions and guide participants through the treatment as needed. 
See In-App Coach Training and Qualifications, above, for details. 
 
8. The independent evaluator(s) were highly experienced, highly trained, and closely supervised. 
 
9. Dr. Wilhelm (the PI) was available, if necessary, to discuss the study, alternative treatments, or 
any concerns about the study with participants if requested by the participant, coaches, or raters. 
 
10. The PI and her co-investigator and the participants’ study coach were available to answer study 
questions via the app or phone. This was clearly communicated orally and in writing to study 
participants.  
 
11. All participants were provided with referral resources. 
 
12. The study coaches and raters (IEs) made every attempt to help participants feel comfortable 
when discussing sensitive material. Participants could skip questions on assessments that they 
were uncomfortable answering. 
 
13. If exposure exercises suggested through the treatment app were too anxiety provoking, 
participants were able to do alternative exercises that caused less anxiety. 
 
14. The CBT treatment initially emphasized cognitive restructuring, which we anticipated would be 
less anxiety provoking than exposure treatment alone and would make exposure more tolerable. 
 
15. Technologists from Koa Health who conducted the technology feedback interviews were trained 
professional staff with experience conducting patient interviews. They received additional 
training (including a multi-day workshop) from our team (MGH OCD and Related Disorders 
Program) on CBT and issues of confidentiality. They completed CITI training.  
 
16. Three clinical psychologists or researchers familiar with BDD were selected to serve as a Data 
Safety Monitoring Board, to review the study once a year.  
 
17. Participants designated a relative or friend who could be contacted should the subject be 
unavailable and the investigator had concerns about the subject’s well-being. 
 
We anticipated that the above procedures would be effective in protecting study participants against 
potential risks. 
 
Adverse event reporting:  
See below: “Adverse event reporting guidelines”  
 
E. Radiation risks 
Not applicable 
 

 
 
21 
 
 
 
 
VIII. POTENTIAL BENEFITS 
 
A. Potential benefits to participating individuals 
Participants may benefit from the comprehensive diagnostic assessment with a BDD expert, from careful 
clinical monitoring, and by experiencing some relief from their BDD symptoms through the CBT app.  
 
B. Potential benefits to society 
If app-based CBT for BDD were efficacious, it would offer increased, cost-effective access to CBT for 
BDD, a treatment which is otherwise difficult to access.  
 
IX. MONITORING AND QUALITY ASSURANCE 
 
A. Sponsor-initiated monitoring 
Decus Biomedical, Inc. were hired by Koa Health to serve as external study monitors. They visited MGH 
to provide feedback regarding ongoing study procedures and data quality. 
 
B. Independent monitoring of source data 
The PI had overall responsibility for study data and participant safety. All aspects of the study were 
conducted in accordance with the hospital’s policy on confidentiality.  
 
Paper research records were kept de-identified, in a locked file in a locked office at MGH. Self-report 
measures and some clinician administered measures were collected using REDCap. REDCap (Research 
Electronic Data Capture) is a free, secure, HIPAA compliant web-based application hosted by the 
Partners HealthCare Research Computing, Enterprise Research Infrastructure & Services (ERIS) group. 
Data collection projects rely on a study-specific data dictionary defined by members of the research team 
with planning assistance from Harvard Catalyst | The Harvard Clinical and Translational Science Center 
EDC Support Staff. The REDCap software allows researchers to design and implement study surveys for 
collecting, storing, retrieving, and manipulating data electronically. The iterative development and testing 
process results in a well-planned data collection strategy for individual studies.  Web-based self-report 
measures rely on a study-specific data dictionary built by members of the research team. Once built, 
participants and study staff can enter data directly into REDCap surveys via any computer or tablet with 
standard web access and browsers. Participants entered survey responses directly into an electronic 
assessment form on subject-facing REDCap, and the responses were then be transmitted and stored in the 
secured and confidential database. Each participant only had access to his or her own survey, but not any 
other survey data. All data was collected and stored in compliance with the Standards for Privacy of 
Individually Identifiable Health Information (“Privacy Rule”) of the Health Insurance Portability Act of 
1996 (HIPAA). Any data that was transmitted electronically was encrypted and password protected. This 
electronic data capture system precludes the need for subsequent data entry by staff, thus minimizing 
human error, and resulting in improved data integrity and quality.  All users had defined roles and 
privileges pre-determined by the system administrator.  Thus, the PI could determine the level of access 
for each study staff such that only a limited number or people had access to sensitive study data.  
 
We anticipated that the above procedures would ensure the confidentiality and integrity of study data.  
 
C. Safety monitoring 
Three clinical psychologists or researchers knowledgeable about BDD were selected to serve as a Data 
Safety Monitoring Board, to review the study once a year when the study was actively enrolling. The PI 
had overall responsibility for monitoring the integrity of study data and participant safety. Procedures for 

 
 
22 
 
managing participant safety, including the monitoring of participants throughout the trial and response to 
clinical deterioration (as defined above) should it occur, are detailed above in “Minimizing of Risks and 
Safety Reporting.”  
 
D. Outcomes monitoring 
Adverse events and data completeness were monitored regularly throughout the trial as described 
above.  
 
E. Adverse event reporting guidelines 
 
Adverse event reporting:  
Adverse events were reported per PHRC guidelines.  
 
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American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th 
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Bang, H., Ni, L., & Davis, C. E. (2004). Assessment of blinding in clinical trials. Control. clin. 
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Borkovec, T. D,. & Nau, S. D. (1972). Credibility for analogue therapy rationales. J Behav Ther Exp 
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Cash, T.F., & Henry, P.E. (1995). Women's body images: The results of a national survey in the 
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Cook, R. J., & Farewell, V. T. (1996). Multiplicity considerations in the design and analysis of clinical 
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