Mobile After-Care Support Intervention for Patients With Schizophrenia Following Hospitalization (MACS)
Phase: NA
Conditions: Psychotic Disorders
Sponsor: Butler Hospital

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IRB-approved Study Protocol 
 
Mobile After-Care Intervention to Support Post-Hospital Transition (MACS) 
 
NCT03769493 
 
2/15/2019 
 
 

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Local IRB # Pending          IRBNet #1237369 
BUTLER HOSPITAL 
INSTITUTIONAL REVIEW BOARD 
PROTOCOL 
ATTENTION: 
 Before completing this protocol, go to the Butler IRB Forms library on IRBNet and 
 Download the most recent version.  Consult the IRB Guidelines for updated directions. 
1.) Project 
 
Title of Project:  Mobile After-Care Support Intervention for Patients with Schizophrenia following 
Hospitalization [Consent Form Title: “Mobile After-Care Intervention to Support Post-Hospital Transition” 
Principal Investigator (PI): Brandon Gaudiano, Ph.D. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Other Investigator(s):   Ethan Moitra, Ph.D., Lawrence Price, M.D., Michael Armey, Ph.D. 
 
 
                              
2.) Description of Study 
 
A.  Specific Aims   
Psychotic-spectrum disorders, including schizophrenia and schizoaffective disorder, are associated with 
disproportionately high societal costs related to treatment, disability, and morbidity/mortality. Patients' 
nonadherence to medications and missed appointments undermine the long-term management of these 
illnesses, making it difficult to achieve improved quality of life and ultimate recovery. The transition from 
inpatient to outpatient care confers the highest risk of nonadherence and premature drop out in this 
population. Despite post-discharge being a time of elevated risk, routine clinical settings often lack feasible and 
effective services to support patients' return to the community and reengagement with outpatient providers 
due to the current system of fragmented care. In the absence of such solutions, up to 50% of patients with 
psychosis will remain medication nonadherent, the healthcare system will continue to waste over $100 million 
annually on potentially preventable hospitalizations, and a substantial number of patients with psychotic 
disorders will continue to be at high risk for relapse and rehospitalization within the first month post-
discharge. 
The current project proposes to develop and examine the feasibility, acceptability, and potential 
effectiveness of our novel response-adaptive app intervention, Mobile After-Care Support (MACS), to improve 
treatment adherence and self-coping in psychosis following hospitalization, in preparation for a future full-
scale clinical trial. We propose to enroll hospitalized patients with schizophrenia spectrum disorders prior to 
discharge and provide them with the MACS app to use during the first 4 months post-discharge to improve 
adherence to oral antipsychotic medications, appointment attendance, and active self-coping with illness. We 
will conduct an initial open trial of MACS to refine the intervention. 
Aim 1: Informed by our previous pilot work, we will design the prototype of a new mobile app called MACS. 
MACS combines ecological momentary assessment linked to adaptive, personalized, response-adaptive self-
help strategies informed by the cognitive behavioral therapy for psychosis (CBTp) literature on empirically-
supported principles for improving medication/appointment adherence and self-coping.  
Aim 2: We will use an iterative process to refine a new mobile aftercare app by conducting an initial open 
trial (n = 20). MACS will be linked with hospital routine discharge planning and transition to community mental 
health services. We will conduct an open trial using an iterative process of implementing, refining, and re-
implementing the app intervention with a sample of patients with psychosis enrolled during their 
hospitalization. Patients will use MACS in the first 4 months post-discharge during which time we will 
longitudinally assess usage and outcomes.  

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B.  Background  
Recent hospitalization predicts treatment nonadherence1-3, and the transition from inpatient to outpatient 
services confers the highest risk of nonadherence and premature drop out4,5. Despite post-discharge being a 
time of elevated risk, routine clinical settings often lack feasible and effective services to support patients' 
return to the community and re-engagement with outpatient providers due to the current system of 
fragmented care. Cost, time, and other barriers limit the ability of clinicians to monitor transition problems 
when moving from inpatient to outpatient care. To our knowledge, there are no existing evidence-based 
interventions that are routinely used as a "warm hand-off" of patients from inpatient to outpatient care. 
To date, adherence interventions for psychosis have produced promising, albeit mixed results6-8. The most 
fruitful approaches have drawn on cognitive-behavioral therapy for psychosis (CBTp), sometimes also 
integrating motivational interviewing and family therapy7,8. These efficacious interventions have been 
delivered in group formats, individually, and sometimes with patients’ families. Most CBTp-based adherence 
interventions have been delivered as part of routine outpatient services and intervention length has ranged 
from 1 session to weekly sessions for up to 2 years. A recent review9 concluded that the most useful ways of 
improving adherence include strengthening communication with providers, increasing motivation to take 
medications/attend appointments, and addressing common adherence barriers. Schizophrenia guidelines10 
state that interventions “behaviorally tailored” to address adherence have shown the most benefit, but that 
there was insufficient evidence to recommend any one specific adherence intervention for schizophrenia. A 
recent review11 of 182 adherence RCTs concluded that many CBT interventions are efficacious, but more 
feasible formats are needed that can be implemented in real-world settings.  
Given the need for simple, low-cost service delivery methods, the field is turning to an mHealth approach 
as a means of supporting active self-coping with illness and medication/appointment adherence. Mobile 
devices, such as smartphones, have become the ideal technological platform for in vivo assessment and 
personalized interventions delivered via apps. These ecological momentary assessment (EMA) or ecological 
momentary intervention (EMI)12 methods reduce risk of retrospective biases in self-reports and can provide 
insights into patients' daily lives that could not be captured at clinic appointments alone. Also, ecological data 
collection can be used to trigger in-the-moment, tailored interventions, delivered electronically, thus reducing 
provider burden. 
Clinical characteristics associated with schizophrenia, such as low motivation and cognitive impairments13, 
may lead to pessimism about the feasibility of EMA in this population. Yet, accumulating research supports the 
short-term feasibility/acceptability of EMA in psychosis using mobile devices14,15. Various studies show that 
people with schizophrenia accept and can be trained to use EMA with compliance rates comparable to those 
of nonclinical populations15-20. Notably, EMA has demonstrated incremental validity over traditional 
retrospective reports in assessing symptoms associated with schizophrenia19,21.  
Most patients, even those acutely ill, have increasing familiarity with this technology22. For example, 81.4% 
of patients with severe mental illness (SMI) surveyed over the past 2 years reported mobile phone 
ownership23. Recent surveys have reported smartphone ownership in psychiatric populations of 62.5% in 
201424, which is comparable to rates found in the general public. Further, national data indicate that 
smartphone use is particularly prevalent among ethnic minorities and lower-income individuals as this is the 
most feasible method for them to access the internet25.  
There is a growing body of research showing that various mobile approaches can support coping and 
improve treatment adherence in outpatients with psychosis; although none of these interventions has been 
designed to support patients' return to the community immediately following hospitalization. For instance, 
Granholm et al.17 conducted a study of 42 individuals with psychosis engaged in EMI for 12-weeks. In response 
to 12 daily prompts, participants answered questions on mobile devices and based on their responses received 
an immediate intervention that drew on CBT principles, including self-management of hallucinations, 
medication adherence, and socialization. Results were encouraging and showed positive changes in these 
targeted domains. However, it should be noted that participants were recruited from stable outpatient 
residential and treatment settings. Further, results from a study by Depp et al.16 showed that EMI was feasible 
for patients with psychosis in 3 pilot clinical trials, but again, samples were limited to patients who were fairly 
stable and engaged in outpatient treatment in the community. Ben-Zeev et al.26 also piloted 1-month EMI in a 

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sample (n=33) of patients with schizophrenia/schizoaffective disorder already engaged in outpatient treatment 
groups. Patients used the mobile device 86.5% of days (average 5.2 times per day) and showed improvements 
in psychotic symptoms and depression. More recently, Ben-Zeev et al.27 examined use of an EMI in 342 
individuals with psychotic disorders recruited within 60 days of a hospitalization (but not directly at inpatient 
through discharge) and followed them for up to 6-months. This naturalistic study found that 44% of the sample 
used the intervention an average of 4.3 days per week.  
We conducted a previous assessment only mobile study to assess the feasibility and acceptability of EMA 
in 65 patients with psychotic-spectrum disorders who were recently discharged from the hospital were 
assessed28,29. EMA was administered for four weeks via study-provided mobile devices. Feasibility was 
measured by study recruitment/retention rates, patients' connectivity, and completion rates. Quantitative and 
qualitative acceptability data were collected. Participants completed 28-31% of offered EMA assessments. The 
only significant predictor of reduced EMA completion was recent cannabis use. EMA completion was 
maintained from weeks 1 to 3 but significantly dropped at the fourth week. Patient acceptability feedback was 
generally positive; negative comments related primarily to technological problems. This was the first study to 
use EMA in recently discharged patients with psychotic-spectrum disorders. EMA is feasible and acceptable in 
this population, but completion rates were lower than in more stable samples. Future research should 
consider limiting the assessment period, screening for substance use, and integrating assessment with 
intervention elements to increase EMA engagement. 
To maintain stability in patients with schizophrenia requires effective self-management of symptoms and 
consistent treatment adherence. Perhaps the most notable period in the continuum of care when coping and 
medication/appointment adherence are jeopardized is during the first months following discharge from acute 
hospitalization. Various factors associated with adherence have been described in our pilot work, and we have 
used these data to inform the development of a theoretically- and empirically-grounded, mobile intervention 
app following hospitalization. Our preliminary findings lay the groundwork for the present project moving from 
assessment to intervention as we seek to examine the feasibility, acceptability, and potential effectiveness of a 
newly-designed mobile app, that we call Mobile After-Care Support (MACS), to improve the target mechanisms 
of active illness self-coping and medication/appointment adherence post-hospital discharge. We plan to 
develop and test the MACS app by conducting an open for patients recently hospitalized for psychosis.  
 
C.  Experimental Method 
 
C1.  Brief Description of Subjects 
Participants in this study will consist of 20 patients diagnosed with schizophrenia-spectrum disorders who have 
been hospitalized for acute psychiatric reasons at Butler Hospital. See detailed inclusion/exclusion criteria 
below. 
 
C2.  Study Design 
We will use the Open Trial to assess MACS acceptability/ feasibility. Midway (n=10) and at the end (n=20) of 
the open trial, the investigator team will meet to review recruitment, retention, and adherence to the 
protocol. We will review patient acceptability/ satisfaction ratings and ease of use of mobile devices as 
measured by the CSQ-8 and qualitative interviews. These data will inform refinements in the MACS app that 
will be used in a subsequent study. 
 
C3.  Specific Procedures or Treatments 
 
Mobile Device Procedures 
MACS Protocol. We will use an established mobile software service (ilumivu.com) which provides a secure 
platform (Android or Apple IOS compatible) that can be programmed to administer the MACS app. It does not 
require a high degree of IT support and allows for tailoring of content without the need for trained 
programmers. Further, we chose a mobile app that works with most smartphones, is easy to download/install, 
and runs largely autonomously. Because we are using a flexible software platform to deliver our mobile 

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intervention and not a static app specifically designed for this project, we have flexibility to make changes to 
the content of the app during the project in an iterative fashion based on what we learn from the data being 
collected. In addition, future implementation of the app can take advantages of ongoing improvements and 
updates to the platform that will be used in future iterations of our app-based interventions that would be 
proposed for a next step full-scale RCT if this project is successful. 
 The MACS app assesses and intervenes by fostering increased treatment adherence 
(medication/appointments) and self-coping with illness (active, planned, problem-solving focused) to reduce 
symptoms and improve functioning. Additionally, MACS will encourage participants who are already reporting 
adherence and healthy coping by using positive reinforcement strategies to maintain efforts and promote 
additional goal setting. MACS app strategies are linked to patients’ specific assessment responses, allowing for 
a highly personalized self-management intervention experience. Primarily, MACS is constructed from common 
components we adapted from CBTp studies, including those testing mobile interventions16,17 to improve self-
coping and adherence behaviors. The MACS app provides interactive exercises delivered by the device 
designed to teach patients coping skills that they can use now and in the future. Exercises will incorporate 
graphics, feedback, and interactive menus to increase engagement. For instance, participants will be instructed 
how to use common CBT exercises for coping with psychotic symptoms (e.g., “Is there another explanation for 
what is going on right now? Let’s explore some examples.” or “Try doing what you want despite what the 
voices say. Let’s practice how to do this now.”). Another example targeting improved socialization teaches 
patients the benefits of socializing and encourages them to identify and record the names and numbers of 
support persons in the device that they plan to contact. MACS responses to medication nonadherence and 
missed treatment appointments come partly from Dr. Gaudiano's previous traditional and mobile intervention 
work improving treatment adherence in those with SMI30. There are a variety of possible reasons for 
nonadherence. If the reported reason is primarily logistical (i.e., no transportation, ran out of pills, forgot to 
take them), participants will be instructed to set phone/calendar reminders or contact their provider at the 
community clinic to address the problem. This information will also be conveyed to providers (through periodic 
reports generated by the study team that will summarize app data) so that the community clinic can reach out 
to participants to address adherence issues. If nonadherence is attributed to medication concerns (e.g., does 
not believe medications help, experiencing side effects), we will use previously tested techniques that 
encourage participants to communicate concerns to providers, remind them of costs vs benefits of medication 
in terms of symptom management, and teach them to engage in other brief problem-solving strategies 
delivered through the app30. If appointment nonattendance is reported, similar problem-solving strategies will 
be suggested.  In response to negative affect and stressful life events, MACS provides various CBTp strategies31, 
such ameliorating or circumventing the stressor when possible, or exploring alternative approaches to coping 
with distress that might be more adaptive, including app-based emotion regulation exercises32. To address low 
life satisfaction, MACS will use CBTp techniques derived from positive psychology research focused on building 
strength and resiliency33. For example, app interventions will encourage patients to savor experiences, 
cultivate gratitude, and rehearse mental imagery related to previous positive experiences. In addition, if the 
patient reports positive coping and treatment adherence, the app will deliver exercises that reinforce positive 
behaviors (e.g., “You seem to doing well. Let’s identify a way to reward yourself for your hard work”) and 
encourage additional goal setting to foster continued improvement (e.g., “You seem to be making good 
progress toward your goals. Now let’s identify future goals that can build upon what you’ve accomplished so 
far.”) In response to reported substance abuse, MACS will deliver brief interventions drawn from motivational 
interviewing34,35, another approach in the CBT family, that probes for motivation for change based on an 
individual's self-reflection, consideration of pros and cons, and suggests stimulus control and reduced use 
goals36,37. Finally, safety risk will be assessed using one item from the Patient Health Questionnaire-9 ("Since 
the last survey, have you had thoughts that you would be better off dead or of hurting yourself in some 
way?"). Because patients' mobile device data will be uploaded remotely to secure servers, the safety risk item 
will be reviewed on a weekly basis by research staff. This type of “asynchronous communication” (i.e., a gap 
between patient and provider communication) is typical in mHealth applications because it is not feasible in 
real world practice to review patient data in real time by busy clinicians. Patients will be informed that their 
responses will not be reviewed in real time; instead, they will be given immediate instructions on the device 

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for addressing safety (e.g., contacting crisis hotline). Patients will be contacted and assessed further by a 
clinician when needed per study safety procedures. 
 
Mobile Device Use. The MACS protocol will consist of daily prompted sessions. Each session will take ≤ 5-
10 minutes and frequency of sessions will taper after the first month from three daily prompts to once daily for 
months 2-4. Every morning (9:00am default), afternoon (12:00pm default), and evening (9:00pm default) 
based on the person’s typical schedule, participants will begin by responding to survey questions about 
symptoms, functioning, and adherence. Those using MACS will receive brief self-management CBTp 
interventions that will be adaptively tailored to correspond to responses provided by the participant (e.g., if 
nonadherence is reported, strategies addressing this problem will be presented by the device). The MACS 
morning survey will also remind participants about being adherent to medications and treatment 
appointments and offer suggestions for staying on track (if adherence is reported) or improving any 
nonadherence behaviors for the upcoming day. We will include a feature that will allow participants to delay 
(e.g., 15 min) the administration of a mobile session, if the participant is too busy or otherwise unable to use 
the device. The prompted app sessions are to ensure use of the program on a regular schedule. In addition, 
patients will be permitted “free use” of the mobile apps whenever they desire to increase the use of the 
devices based on their personal needs and schedule. 
 
Mobile Software Service. We will use an established mobile software service (ilumivu.com) which provides 
a secure, HIPAA-compliant application (Android or Apple IOS compatible) that can be programmed to 
administer the MACS app. Our Co-I Dr. Armey has experience using this service in his current grant-funded 
mobile research and will assist with app programming and implementation. Responses will be uploaded when 
internet/cellular access is available to a web portal for remote access/downloading from a convenient web 
portal interface. Otherwise, responses are stored on the native app in an encrypted format until uploading can 
occur. App updates and fixes can also be sent remotely to the app when needed. Raw app data will not be 
automatically sent to providers. Instead, staff will review mobile data weekly to monitor safety and contact 
patients if safety risk is detected. Patients will be informed that mobile data will not be reviewed in real time 
and that they should contact providers/seek immediate help if needed. These risk data will also be included in 
the periodic reports that are sent to providers. Patients will be prompted by the device to contact a crisis 
hotline, their providers (numbers pre-programmed into the device), or 911/local hospital if they report an 
immediate safety risk.  
 
Mobile Device Training/Support. We will employ a master’s level clinician to instruct patients to use the 
app and review patients’ app data post-discharge. After obtaining consent at hospitalization (baseline), the 
clinician will help patients install the app on their own smartphone when possible for convenience. If a patient 
is unwilling to install the app or does not own a compatible smartphone, we will supply a dedicated mobile 
device to the participant for this purpose post-discharge and they will return the device at the end of the 
study. Patients will practice responding to app sessions to familiarize themselves with the program and 
troubleshoot technical problems. Patients will be instructed to contact the study if questions arise post-
discharge about using the device.  
 
Communication with outpatient providers. At baseline, an initial discharge report will be sent by the study 
clinician to patients’ outpatient providers (after obtained releases of information from the patient) based on 
assessment results. Additionally, to improve quality of care and timely communication between providers, 
periodic reports (e.g., bi-weekly the first month and monthly thereafter containing information on symptoms, 
safety, and adherence) will be sent to patients’ outpatient clinicians throughout the study to improve care 
coordination. These reports will be generated using data collected via the app. 
 
Assessment Procedures (see Table 1)  
 

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Participants will complete baseline measures, as well as diagnostic interviews at intake prior to hospital 
discharge (~1.5 hrs). Patients will return to our research office to complete traditional assessments at 1, 2, and 
4 months to assess longer-term effects (~1 hr each). 
 
MACS app assessments. MACS assessment items are adapted from traditional measures and those used in 
other mobile studies in psychosis: a) affect38, b) psychosis15, c) social support102, d) life satisfaction39, e) 
functioning40, f) treatment adherence41, g) substance use42, h) safety44. 
 
Target Mechanisms. Our target mechanisms are increases in: a) medication adherence, b) appointment 
adherence, and c) active self-coping with illness. a) We will employ MEMS45 to objectively measure medication 
adherence during the post-hospital period for the primary oral antipsychotic medication prescribed. MEMS 
uses an electronic pill cap that records bottle openings/closings and the corresponding time/date46,47. Patients 
will be trained by research staff to use MEMS at the start of the study. MEMS data will be downloaded at our 
research office at follow-up assessments and when patients receive medication refills. MEMS data will not be 
integrated into the MACS intervention and will be used instead for research data collection only. Similarly, pill 
counts also will be conducted at this time for back-up purposes. Electronic monitoring is recommended for 
objective adherence assessment48; MEMS has been used in studies of schizophrenia49, including in our R21 
pilot study. b) For appointment adherence, we will use the THI-450, which is a treatment utilization interview, 
to assess mental health appointments missed/scheduled. Medication/appointment adherence will be cross 
validated by obtaining releases for patients’ outpatient medical records, and any discrepancies will be re-
reviewed with the patient to obtain an accurate count. c) Coping with illness in schizophrenia will be assessed 
via the standardized and well-validated MACS-II51,52. MACS-II is an interview-based measure that assesses 
coping to 13 core symptoms of schizophrenia, including positive and negative psychotic symptoms, depression, 
cognition, hostility, and euphoria. Coping responses are then categorized based on 5 coping styles described by 
Carr53, including passive illness behavior (e.g., lying in bed and doing nothing), active problem-solving (e.g., 
professional help seeking), passive problem-avoiding (e.g., isolation), active problem-avoiding (e.g., 
indulgence), and symptomatic behavior (e.g., obeying voices). Research has shown the MACS-II to be reliable 
and valid when used in samples with schizophrenia54. We also will administer the following: the BARS59 which 
is a interview assessing the patient-reported percentage of missed doses over the past month for the primary 
antipsychotic medication; the SUS60 which is a 10 item self-report of app usability; the USE61 which is a 30 item 
self-report of app satisfaction; the Brief COPE62 which is a 28 item self-report measure of coping skills; and the 
PUQ which is a self-report measure we created for this study to collect data on participants’ use of mobile 
phones and related technology. 
 
Table 1. Traditional Assessments 
Construct assessed 
Method 
Time  
Structured Clinical Interview for DSM-5  
(SCID-5; Psychotic, Mood, Substance Use Modules)55  
Axis I diagnosis 
Interview 
Baseline 
(BL) 
Mini-Mental State Exam (MMSE)63 
Cognitive functioning 
Interview 
BL 
Phone Usage Questionnaire (PUQ) 
Phone use 
Self-Report 
BL 
Medication Event Monitoring System (MEMS)45 
Medication adherence 
Objective 
1,2,4 
Antipsychotic Medication Beliefs and Attitudes Scale (AMBAS)65 
Medication beliefs 
Self-report 
BL,1,2,4 
Brief Adherence Rating Scale (BARS)59 
Medication adherence 
Interview 
BL,1,2,4 
Treatment History Interview-4 (THI-4)50 
Appointment adherence 
Interview 
BL,1,2,4 
Outpatient chart/medical records review 
Treatment utilization 
Objective 
BL,1,2,4 
Maastricht Assessment of Coping Strategies (MACS-II)51,52 
Coping skills 
Interview 
BL,1,2,4 
Brief Coping Orientation to Problems Experienced (COPE)62 
Coping skills 
Self-Report 
BL,1,2,4 
Brief Psychiatric Rating Scale (BPRS)56 
Psychiatric symptoms 
Interview 
BL,1,2,4 
WHO Disability Assessment Sched. 2.0 (WHODAS-2)40 
Functioning 
Self-Report 
BL,1,2,4 
Alcohol Use Disorders Identification Test (AUDIT)42 
Alcohol use 
Self-Report 
BL,1,2,4 
Drug Use Disorder Identification Test (DUDIT)64 
Drug use 
Interview 
BL,1,2,4 
Usefulness, Satisfaction, and Ease of Use Questionnaire (USE)61 
Acceptability 
Self-Report 
1,4 
System Usability Scale (SUS)60 
Acceptability 
Self-Report 
1,4 
Client Satisfaction Quest.-8 (CSQ-8)57 
Acceptability 
Self-report 
1,4 
End of Treatment Interview 
Feedback 
Interview 
1,4 
 

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Clinical Outcomes and Other Measures. In addition to target mechanisms, we will assess clinical outcomes 
including: a) symptom severity (primary outcome), b) functioning, and c) re-hospitalization rates. a) We will 
use the BPRS,56 a well-established interview measure of overall psychiatric symptom severity, including 
positive/negative psychotic symptoms, as well as mood symptoms and suicidality; b) the WHODAS-239,40, which 
is a brief self-report measure of functional impairment; and c) rehospitalizations obtained from the THI-450 as 
described above (and cross-checked with patients’ medical records). In addition, the THI-4 will also be used to 
quantify overall treatment utilization, including the type and amount of mental health treatment received over 
follow-up (medications, psychosocial, hospitalizations, pharmacotherapy visits, ER visits, crisis calls, support 
groups). We also will administer the AUDIT/DUDIT, which measure alcohol/drug use and severity42,58,64. The 
MMSE63 will be used to assess cognitive functioning at baseline in order to describe patients’ baseline 
characteristics and to examine this variable as a potential predictor of treatment response in our analyses. The 
AMBAS65 is a brief self-report measure of medication beliefs. Acceptability/satisfaction with the mobile apps 
will be assessed using an adapted version of the CSQ-857 at the end of the study. Finally, participants will 
complete an end-of-treatment interview in which they will be asked what they liked and did not like about the 
app and study participation. 
 
C4.  Data Analysis  
Midway (n=10) and at the end of the open trial (n=20), we will examine development outcomes (e.g., mobile 
session completion rates, recruitment/retention, satisfaction). We will use descriptive statistics to summarize 
variables. If development targets are not met, the research team will investigate and discuss the issue, and 
depending on the perceived reasons for the discrepancy, may modify research procedures to address the 
issue. For example, if mobile completion rates are low, we will modify instructions or change procedures (e.g., 
frequency, length, timing) to increase rates. Further, we will calculate effect sizes to characterize changes over 
the follow-up in our target mechanisms of medication adherence (MEMS), appointment adherence (THI-4) and 
active self-coping (MACS-II). We will report clinical significance statistics (number-needed-to-treat/NNT, area 
under the curve/AUC) to further examine effects. We also will examine effect size changes in primary (overall 
symptom severity=BPRS) and secondary outcomes (functioning=WHODAS-2; rehospitalization rates=THI-4).  
 
D.  Material Inducements 
We will compensate patients for completion of in-person assessments ($30 each at the baseline, 1, 2, and 4 
month follow-ups, with an additional $20 for returning the electronic pill caps or a borrowed study phone, if 
applicable, for up to $140 total), but not mobile device use, to reflect real world practice. 
 
E.   Training of Research Personnel 
The research assistants (RAs) will be directly supervised by Drs. Gaudiano and Moitra.  All RAs in the 
psychosocial treatment program undergo extensive training in screening medical records (including the 
appropriate permissions to access electronic medical records), approaching patients on the units, obtaining 
consent to participate, collecting and entering data, and maintaining confidentiality.  All RAs have received 
training in the informed consent process and their ethical responsibilities when conducting research.  
Additionally, all RAs will receive specific training in the assessment instruments to be administered. Drs. 
Gaudiano and Moitra also will train and supervise the master’s level clinician who will meet with patients for 
the initial app session before discharge and send brief reports during the study to patients’ community 
clinicians based on assessment data collected.  
 
3)  Human Subjects 
 
A.  Subject Population (include number; gender; age; diagnosis; inpatient vs. outpatient; physical health; 
inclusion/exclusion criteria; rationale for use of special groups)  
 
Participants in this study will consist of 20 patients diagnosed with schizophrenia-spectrum disorders who have 

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been hospitalized for acute psychiatric reasons at Butler Hospital.  
 
Inclusion criteria are: (1) currently hospitalized; (2) DSM-5 criteria for schizophrenia or schizoaffective based on 
the Structured Clinical Interview for DSM-555 (SCID-5); (3) 18 years or older; (4) prescribed oral antipsychotic 
medication upon discharge; and (5) ability to speak and read English (materials written at a 5th grade reading 
level).  
 
Exclusion criteria are: (1) alcohol/drug use disorders at moderate or severe level based on SCID (mild 
substance use disorders will be permitted); (2) planned discharge to supervised living setting or participation in 
formal outpatient adherence programs (e.g., medication packaging); or (3) pregnancy or other medical 
condition (e.g., dementia as indicated by patients' medical charts) contraindicating use of antipsychotic 
medications.  
 
B.  Recruitment and Consent Procedures  
If the patient appears appropriate based on the routine electronic chart review of hospital admissions, the 
study will be explained to the patient's treating physician. If the physician agrees it is clinically appropriate, a 
member of the research team will then approach the patient. All participants will be asked to provide releases 
of information for their community treatment providers so that the investigators can obtain records to 
corroborate patient self-report of treatment utilization and send brief reports to clinicians at follow-up. We 
also will collect the names and numbers of additional contact persons and collect permission to contact them 
in the event that we are not able to reach the patient during the study. After obtaining permission for this 
purpose, we will contact participants via text and/or email to schedule follow-up contacts and check in with 
them periodically to prompt their use of the app. 
 
C.  Potential Risks   
Potential risks of study participation include: coercion, clinical deterioration/suicidality, loss of 
confidentiality/privacy, and adverse events (see details below). 
 
D.  Protection of the Subject  
 
D1. Measures to Minimize Potential Risks 
 
Coercion 
Risks. The risk of potential coercion is judged to be minimal. 
Minimization. The risk of coercion will be minimized by following standard procedures for obtaining informed 
consent. We will fully explain the study procedures, risks, benefits, and alternatives to all patients. Also, 
patients who do not consent or who withdraw at any time will receive usual clinical treatment with no 
prejudice. Additionally, participant remuneration will be set at modest monetary levels as used in similar 
studies, including our pilot work. We will obtain permission form the patient’s treating physician to ensure that 
approaching the patient for research participation is clinically appropriate. 
 
Risk of clinical deterioration/suicidality  
Risks.  In this type of population, the risk of clinical deterioration is present.   
Minimization.  Clinical deterioration, including suicidality will be monitored in multiple ways. 1) During in 
person interviews, study staff will assess for suicide risk, symptoms, and clinical deterioration and take 
appropriate action if needed. 2) The mobile app will contain questions regarding suicide risk and psychotic 
symptoms in every session, and will prompt participants to contact a crisis hotline, 911, and/or their local 
treatment provider/hospital if such risk is reported for immediate assistance. 3) Mobile device data will be 
uploaded onto secure servers remotely.  As real-time data review is not feasible or sustainable in typical 
clinical settings, mobile data will be reviewed weekly by the study clinician as part of his/her routine 
monitoring and report-writing duties. This type of strategy is known as asynchronous communication (where 
there is a gap between communications compared with synchronous or “live” communication) and is often 

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adopted in mobile health research. Patients will be informed that their responses will be reviewed periodically 
(not in real time), and that they may be contacted by study staff if safety risk is detected for the purposes of 
providing further assessment and assistance as necessary.  
If any patient manifests clinical deterioration or psychotic relapse during study assessments or other study 
contacts (based on ratings in the severe range of > 5 for the items assessing psychotic symptoms from the Brief 
Psychiatric Rating Scale), we will either: (1) inform the patient’s clinician, or (2) if the patient is not currently in 
treatment (at follow-up), we will provide the patient with a referral to a qualified clinician. This also applies if a 
participant manifests significant suicidal or homicidal ideation or risk, and we will take whatever steps 
necessary to ensure the patient’s and/or other’s safety. At the time that suicidality and/or clinical 
deterioration is identified, a study clinician will immediately evaluate the participant. In such cases, research 
staff will immediately contact one of the principal investigators, Drs. Moitra or Gaudiano, both of whom are 
licensed clinical psychologists and whom will be on-call at all times. Depending upon the specific situation, 
steps taken to ensure a participant’s safety may involve: (1) escorting the patient to the hospital’s ER for 
evaluation by an independent clinician and possible hospitalization, (2) alerting inpatient staff to the patient’s 
level of risk, (3) notifying the patient’s clinician, primary care physician, and/or family member for whom we 
have releases of information, or (4) calling the appropriate police departments. See adverse events reporting 
procedures below.  
 
Confidentiality and loss of privacy 
Risks. It is possible that a text message or email could be intercepted or sent to an incorrect email address or 
phone number; however the risk of loss of privacy is judged to be minimal. 
Minimization. Confidentiality will be maintained by numerically coding all data, by disguising identifying 
information, by keeping all data in locked file drawers, and by keeping electronic data on password-protected 
and secure servers. To further minimize risk, all electronic communications will be monitored by limiting access 
to authorized team members only, removing all PHI from messages, and transmitting all communications 
through a secure server. Text messages will be sent from a phone that is dedicated for use in this research 
study that only research staff have access to. Participant information will be accessible only to research staff. 
Identifying information will not be reported. Study provided phones will be password-protected and 
encrypted. If participants choose to use their own smartphones, they will be encouraged to password protect 
their devices. The app will not be password protected but data is stored in such a way that information cannot 
be accessed after entered. All data (apps, documents, pictures, etc.) will be wiped clean from the phone before 
reuse. Only research staff will have access to any email communications and the dedicated study phone. All 
text and email communications will be limited to scheduling research-related appointments or study-related 
reminders, and will not send any messages containing urgent information or protected health information.  
 
Risk of adverse events  
Risks.  In this type of population, the risk of adverse events occurring is present.   
Minimization. Although this population may be at high risk for adverse events, it is unlikely that an adverse 
event will be caused by the research study. Our proposed intervention was developed from empirically-
supported cognitive behavioral strategies for people with psychosis and therefore, does not pose the same 
risks that a pharmacology trial might hold. In the case an Adverse Effect (AE) or a Serious Adverse Effect (SAE) 
related to the intervention were to occur, a written report of the AE or SAE will be prepared for submission to 
Dr. Linda Carpenter, the Chair of the Butler Hospital IRB. Any such AEs or SAEs will be presented to the full 
committee of the Butler Hospital IRB as soon as it is feasible. The report of such intervention-related AEs or 
SAEs will include whether they were expected or unexpected, a rating of severity of the event, a brief narrative 
summary of the event, whether the informed consent should be changed as a result of the event and whether 
all enrolled participants should be notified of the event. Finally, as part of the annual progress report 
(noncompeting continuation application) to NIH, we would provide summary information on all AEs and SAEs 
that have occurred during that year.  
 
D2. Measures to Ensure Confidentiality 
Breach of confidentiality is unlikely because all staff with access to participant data and identifying information 
have been trained in the management of sensitive clinical information. All data will be treated as confidential, 

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and will only be available to research and clinical staff. Study data will be identified by participant code only, 
and no identifying information will ever be stored in association with participant data. Data will only be 
available to government or regulatory agencies as required by law. Prior to any assessment, participants will 
be informed of the limits of confidentiality regarding suicidal or homicidal intent, child or elder abuse, or 
inability to care for the self. All data will be stored on encrypted drives or a secure server within the Butler 
Hospital information technology system. Electronic data will be stored on password-protected computers. All 
electronic communications will be transmitted via secure, encrypted servers. No PHI will be included in any 
electronic communications. All paper records will be stored in a locked file cabinet within a locked office on 
Butler Hospital grounds. Butler Hospital has clear HIPAA regulations in place to ensure research compliance for 
both psychiatric and medical records. Additionally our mobile software service (ilumivu.com) is a HIPAA-
compliant platform for the collection of EMA data and secure transmission of those data to a cloud-based 
central server with dedicated data backup. Study phones will be encrypted and password-protected and wiped 
clean of data before reuse. Text messages will only be sent from a phone dedicated for use in this research 
study, and will only be accessible to research staff. All text and email communications will be limited to 
scheduling research-related appointments or study-related reminders, and will not send any messages 
containing urgent information or protected health information. 
 
D3. Data Safety Monitoring Plan 
 
 1.  Data management and protection.  
Drs. Gaudiano and Moitra will have responsibility for day-to-day monitoring of the quality of operations in all 
data collection. There are several sources of data. Research participants will complete questionnaires. 
Research assistants also code all data from research interviews. Only the participants’ study identification 
number will appear on any of the final paper data collection instruments. Finally, audio recordings of 
interviews with participants will be uploaded and stored on a secure server in a digital format. A study ID will 
be used to identify the recordings. Otherwise, they are not connected with the primary study database in any 
way.  
 
This study will use Care New England’s instance of REDCap for the collection and storage of data. The study will 
not collect or store any actual data within REDCap until the project has been moved into REDCap’s production 
environment. REDCap is a secure, web-based application developed by Vanderbilt University for building and 
managing surveys and databases. It is primarily designed to support online or offline data capture for research 
studies, quality improvement, and operations. REDCap provides easy data manipulation (with audit trails for 
reporting, monitoring and querying patient records), real-time data entry validation, and an automated export 
mechanism to common statistical packages. Care New England’s instance of REDCap is hosted within the Care 
New England data center in Warwick, RI. This REDCap instance is role-based and is fully integrated with CNE’s 
Active Directory structure. It enjoys 24/7/365 enterprise-level support and security inherit to CNE’s HIPAA-
compliant data center. Network transmissions (data entry, survey submission, and web browsing) to and from 
REDCap are protected via TLS 1.2 encryption.  REDCap’s data is stored on encrypted servers within CNE’s data 
center. The REDCap Consortium is composed of thousands of active institutional partners in over one hundred 
countries who utilize and support REDCap. REDCap was developed specifically around HIPAA-Security 
guidelines, and more information about the consortium and system security can be found at 
http://www.projectredcap.org/. 
 
All data collected by the research team are considered part of the subject's confidential record.  Paper data 
forms collected from research participants will be kept in a locked file cabinet.  All data will remain 
confidential. All data is stored on a secure research server, and backed up daily. Patient identifying information 
will be stored in a separate database and will be password protected in addition to being on a secure server.  
 
 2.  Safety Plan and Adverse Event Identification and reporting  

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Drs. Gaudiano and Moitra will be responsible for overseeing the daily safety of all participants. There are 
several ways in which they will become aware of adverse events. First, research staff will ask patients about 
serious adverse events (as defined by Office of Human Research Protections (OHRP); e.g., inpatient 
hospitalization). Second, all study staff will be trained in the OHRP definitions of adverse events that are also 
unanticipated problems; serious adverse events; or unanticipated problems that are not adverse events. All 
study staff are required to report any event that might meet one of these criteria to one of the PIs immediately 
both verbally and in writing. Any report of a serious adverse event will result in one of the PIs contacting the 
participant to further assess the event. 
 
Adverse Events Definitions 
Adverse Event – any unfavorable and unintended sign, symptom or disease temporally associated with 
the use of a medical or behavioral treatment or intervention regardless of whether it is considered 
related to the treatment or intervention. 
Expected Adverse Event – an event that may be reasonably anticipated to occur as a result of the study 
procedure and is described in the consent form. 
Unexpected Adverse Event – any adverse event which is not described in the consent form and is 
unanticipated.  An event that might have been anticipated but is more serious than expected or 
occurs more frequently than expected, would be considered an unexpected adverse event. 
Serious Adverse Event- (21 CFR 312) include any untoward medical occurrence that at any dose results 
in death or the immediate risk of death, hospitalization or prolonging of an existing hospitalization, 
persistent or significant disability/incapacity or a congenital anomaly/birth defect (NIH guide-
6/11/99). 
 
Study Definitions 
Specifically, we will consider the following events Serious Adverse Events (SAE): 
a. Death for any reason; 
b. A suicide attempt, defined as any action taken with intent to die, as stated by the patient or 
noted in the medical record; 
c. Inpatient psychiatric hospitalization 
Additionally, we will consider the following events non-serious Adverse Event (AE): 
a. Evidence of coercion to participate; 
b. Participant distress resulting in stopping of the assessment or intervention; 
c. Access of confidential information by a non-authorized person. 
 
Severity 
Each adverse event will be graded in terms of severity: 
a. Non-severe adverse event 
b. Severe adverse event resulting in hospitalization or prolongation of existing hospitalization, a 
persistent or significant disability/incapacity. 
c. Life-threatening adverse event 
d. Fatal adverse event 
 
Attribution 
 
For each adverse event, one of the following attributions is assigned: 
Definite:       Adverse event is clearly related to intervention 
Probably:     Adverse event is likely related to intervention 
Possible:      Adverse event may be related to intervention 
Unlikely:       Adverse event is doubtfully related to intervention 
Unrelated:    Adverse event is clearly not related to intervention 
 

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Suicidality. Because we will be recruiting individuals with psychiatric disorders, we may have some 
participants who disclose having suicide ideation or behavior. At the time that suicidality is identified by any 
study staff member for in-person assessments, they will contact a study clinician who will immediately 
evaluate that person. All study staff (e.g., research assistants) are trained in the Psychosocial Research protocol 
for managing suicidality. All clinical faculty in our research group, including Drs. Gaudiano and Moitra are 
experienced in management of suicidality and other clinical emergencies. Drs. Gaudiano and Moitra, both 
licensed psychologists, will be available during regular business hours. After hours there is always a licensed 
mental health clinician (psychologist or psychiatrist) available on call by cell phone or pager in the Psychosocial 
Research Program.  
When a clinician is asked to conduct an immediate evaluation, he or she will use our standard guidelines 
for conducting a suicide risk assessment. The clinician will determine whether it is necessary to take immediate 
action to prevent the participant from causing harm to him/herself. If needed, the study clinician may have a 
family member bring the person to Butler Hospital, send an ambulance, or transfer the participant to the 
Emergency Department at Memorial Hospital. If the participant is not in immediate danger of hurting him or 
herself, we will take the following actions. First, we will inform the patient about procedures for contacting 
emergency services should they find themselves at risk for self-harm. Second, with the patient’s permission, 
we will contact their primary care physician or other clinician to inform them of the suicidality. We will urge 
the patient to make an appointment with that provider to discuss treatment options. Third, if the patient 
consents, we will speak with one of their family members to ensure that he/ she is aware of the seriousness of 
the patient’s symptoms and the agreed-upon treatment plan. We will provide treatment referrals if the patient 
wishes. Regardless of outcome, suicide assessments are always documented in writing.  
Mobile device data will be uploaded onto secure servers remotely.  As real-time data review is not feasible 
or sustainable in typical clinical settings, mobile data will be reviewed weekly by research staff. This type of 
strategy is known as asynchronous communication (where there is a gap between communications compared 
with synchronous or “live” communication) and is often adopted in mobile health research. Patients will be 
informed that their responses will be reviewed periodically (not in real time), and that they may be contacted 
by study staff if safety risk is detected for the purposes of providing further assessment and assistance as 
necessary.  
 
Adverse Event Reporting. Based on the sources of information detailed above as well as direct patient 
contact and/or consultation with the scientific team, Drs. Gaudiano and Moitra will determine if the event is: 
a) an adverse event that is also an unanticipated problem related to study procedures or intervention; b) a 
serious adverse event; or c) an unanticipated problem that is not an adverse event.  Considering the nature of 
the study and sample, we expect serious adverse events to occur, including suicide attempts and 
rehospitalizations (e.g., due to relapse). However, given the nature of the study, it is unlikely that SAEs will be 
related to the study procedures. The other adverse events that are possible include: inadvertent disclosure of 
protected health information and coercion. If any of these adverse events occur, or any other unanticipated 
events that are identified, the following procedure will be activated: 
              The research staff member who observes or is notified of an adverse event will contact the MPIs or 
their designee immediately. The MPIs or their designee will complete a Butler Hospital IRB Adverse Event Form 
for each event that will include a level of severity and determine attribution (intervention-related or 
not).  Reporting timeframes will vary by SAE type; 
1)     expected and unrelated SAEs: reviewed by the MPIs and reported to Butler IRB within 14 days 
ascertainment; provided to the DSMB in bi-annual data reports; 
2)     unexpected or related SAEs: to Butler IRB and DSMB within 10 days of ascertainment; 
3)     all deaths: to Butler IRB and DSMB within 5 days of ascertainment.   
 
 3. Data and Safety Monitoring Board (DSMB)  
The DSMB will be constituted and will be responsible for monitoring the safety of participants and the quality 
of the data, as well as deciding on the appropriate termination of the study either when significant benefits or 

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risks have been uncovered or when it appears that the clinical trial cannot be concluded successfully. Members 
of the DSMB include Kim Mueser, Ph.D. (Chair; Professor, Boston University), Louisa Sylvia, Ph.D. (Associate 
Professor, Massachusetts General Hospital), and Roger Vilardaga, Ph.D. (Assistant Professor, Duke University). 
These DSMB members have experience serving on other DSMBs and conducting research on severe mental 
illness and mobile technologies. 
Both MPIs and the DSMB Chair will develop the Data Safety Monitoring Plan. It will then be circulated to 
the rest of the DSMB for feedback and approval. The board members will review the initial DSMB protocol to 
ensure that it captures the information necessary to evaluate the safety and efficacy of the study. The DSMB 
will then receive DSM reports bi-annually. A DSM report will include concerns about significant safety and data 
monitoring issues such as recruitment, retention, and quality of data collected.  
Operating procedures of the DSMB include monitoring the protocol to evaluate the safety of the 
participants as pre-specified in the DSMP of the protocol, monitoring efficacy of the intervention being tested, 
and evaluating performance of the trial, as well as study admission data and protocol compliance. The specific 
content of the reports to the DSM include information about AEs and/or SAEs, treatment retention, 
recruitment, reasons for dropout, and interim efficacy data.  
Only reports that meet the criteria of being a death (within 5 calendar days) or unexpected and related to 
study procedures (within 10 calendar days) will be reported to the DSMB within the specified timeframe after 
learning of the event. Summary reports of all adverse events will be provided to DSMB in bi-annual reports. 
Finally, as part of the annual progress report (noncompeting continuation application) to NIH, we would 
provide summary information on all adverse events that have occurred during that year. 
As they deem necessary, the members of the DSMB will evaluate whether the presence of early 
unanticipated therapeutic results, side effects or adverse consequences are significant enough to warrant 
amendment, suspension, or early termination of the study and will independently make recommendations to 
the PIs to continue, to amend or to terminate the trial. Recommendations related to the study will be made in 
a written DSMB Report by the Board's Chairperson to the Principal Investigator and this DSMB Report, along 
with the DSMB meeting minutes, will be sent to the NIH Project Officer for the study. 
 
E.  Potential Benefits  
The anticipated benefits of the study are twofold: the results will be used to advance understanding of the 
factors related to aiding patients' transition from inpatient to outpatient services, and to gather significant 
knowledge about the potentially beneficial role of a mobile device-based aftercare support tool. By 
participating in the clinical research project, participants may benefit from the additional intervention that 
they will receive. The risks associated with participation are minimal.  
 
F.  Risk-Benefit Ratio  
Given the minimal level of risk(s) to the patients as outlined above for participating in the study, and the 
likelihood that some will benefit from the additional treatment, and the even greater possibility of benefits to 
the larger population of adults with psychosis transitioning out of the hospital, the risk/benefit ratio seems 
favorable. 
 
4) REFERENCES  
1. 
Kreyenbuhl J, Slade EP, Medoff DR, et al. Time to discontinuation of first- and second-generation antipsychotic 
medications in the treatment of schizophrenia. Schizophrenia Research. Sep 2011;131(1-3):127-132. 
2. 
Mullins CD, Obeidat NA, Cuffel BJ, Naradzay J, Loebel AD. Risk of discontinuation of atypical antipsychotic agents 
in the treatment of schizophrenia. Schizophrenia Research. Jan 2008;98(1-3):8-15. 
3. 
Novick D, Haro JM, Suarez D, Perez V, Dittmann RW, Haddad PM. Predictors and clinical consequences of non-
adherence with antipsychotic medication in the outpatient treatment of schizophrenia. Psychiat Res. Apr 30 
2010;176(2-3):109-113. 
4. 
Bergen J, Hunt G, Armitage P, Bashir M. Six-month outcome following a relapse of schizophrenia. Aust Nz J 
Psychiat. Dec 1998;32(6):815-822. 

IRB v. 2016.05.24 
Date most recently revised (02/15/19) 
Protocol Version 1.2 
 
Page 15 of 18 
5. 
Ruscher SM, de Wit R, Mazmanian D. Psychiatric patients' attitudes about medication and factors affecting 
noncompliance. Psychiatric services. Jan 1997;48(1):82-85. 
6. 
Byerly MJ, Nakonezny PA, Lescouflair E. Antipsychotic medication adherence in schizophrenia. The Psychiatric 
clinics of North America. Sep 2007;30(3):437-452. 
7. 
Dolder CR, Lacro JP, Leckband S, Jeste DV. Interventions to improve antipsychotic medication adherence: review 
of recent literature. Journal of Clinical Psychopharmacology. 2003;23(4):389-399. 
8. 
Zygmunt A, Olfson M, Boyer CA, Mechanic D. Interventions to improve medication adherence in schizophrenia. 
The American Journal of Psychiatry. 2002;159(10):1653-1664. 
9. 
Julius RJ, Novitsky MA, Jr., Dubin WR. Medication adherence: A review of the literature and implications for 
clinical practice. Journal of Psychiatric Practice. 2009;15(1):34-44. 
10. 
Dixon LB, Dickerson F, Bellack AS, et al. The 2009 schizophrenia PORT psychosocial treatment recommendations 
and summary statements. Schizophrenia Bull. 2010;36(1):48-70. 
11. 
Nieuwlaat R, Wilczynski N, Navarro T, et al. Interventions for enhancing medication adherence. Cochrane 
Database Syst Rev. 2014;11:CD000011. 
12. 
Bolger N, Davis A, Rafaeli E. Diary methods: Capturing life as it is lived. Annu Rev Psychol. 2003;54:579-616. 
13. 
Barch DM. The relationships among cognition, motivation, and emotion in schizophrenia: How much and how 
little we know. Schizophrenia Bull. Oct 2005;31(4):875-881. 
14. 
Ben-Zeev D, Ellington K, Swendsen J, Granholm E. Examining a Cognitive Model of Persecutory Ideation in the 
Daily Life of People With Schizophrenia: A Computerized Experience Sampling Study. Schizophrenia Bull. Nov 
2011;37(6):1248-1256. 
15. 
Granholm E, Loh C, Swendsen J. Feasibility and validity of computerized ecological momentary assessment in 
schizophrenia. Schizophrenia Bull. May 2008;34(3):507-514. 
16. 
Depp CA, Mausbach B, Granholm E, et al. Mobile Interventions for Severe Mental Illness Design and Preliminary 
Data From Three Approaches. J Nerv Ment Dis. Oct 2010;198(10):715-721. 
17. 
Granholm E, Ben-Zeev D, Link PC, Bradshaw KR, Holden JL. Mobile Assessment and Treatment for Schizophrenia 
(MATS): A Pilot Trial of An Interactive Text-Messaging Intervention for Medication Adherence, Socialization, and 
Auditory Hallucinations. Schizophrenia Bull. May 2012;38(3):414-425. 
18. 
Swendsen J, Ben-Zeev D, Granholm E. Real-Time Electronic Ambulatory Monitoring of Substance Use and 
Symptom Expression in Schizophrenia. Am J Psychiat. Feb 2011;168(2):202-209. 
19. 
Ben-Zeev D, McHugo GJ, Xie H, Dobbins K, Young MA. Comparing Retrospective Reports to Real-Time/Real-Place 
Mobile Assessments in Individuals With Schizophrenia and a Nonclinical Comparison Group. Schizophr Bull. Feb 1 
2012. 
20. 
Edwards CJ, Cella M, Tarrier N, Wykes T. The optimisation of experience sampling protocols in people with 
schizophrenia. Psychiatry Res. Jul 26 2016;244:289-293. 
21. 
Oorschot M, Lataster T, Thewissen V, Wichers M, Myin-Germeys I. Mobile Assessment in Schizophrenia: A Data-
Driven Momentary Approach. Schizophr Bull. Nov 29 2011. 
22. 
Miller BJ, Stewart A, Schrimsher J, Peeples D, Buckley PF. How connected are people with schizophrenia? Cell 
phone, computer, email, and social media use. Psychiat Res. Feb 2015;225(3):458-463. 
23. 
Firth J, Cotter J, Torous J, Bucci S, Firth JA, Yung AR. Mobile Phone Ownership and Endorsement of "mHealth" 
Among People With Psychosis: A Meta-analysis of Cross-sectional Studies. Schizophrenia Bull. Mar 
2016;42(2):448-455. 
24. 
Torous J, Chan SR, Yee-Marie Tan S, et al. Patient Smartphone Ownership and Interest in Mobile Apps to Monitor 
Symptoms of Mental Health Conditions: A Survey in Four Geographically Distinct Psychiatric Clinics. JMIR Ment 
Health. Jul-Dec 2014;1(1):e5. 
25. 
Pew Research Center. The Smartphone Difference 2015. 2015:http://www.pewinternet.org/2015/2004/2001/us-
smartphone-usein-2015. 
26. 
Ben-Zeev D, Brenner CJ, Begale M, Duffecy J, Mohr DC, Mueser KT. Feasibility, Acceptability, and Preliminary 
Efficacy of a Smartphone Intervention for Schizophrenia. Schizophrenia Bull. Nov 2014;40(6):1244-1253. 
27. 
Ben-Zeev D, Scherer EA, Gottlieb JD, et al. mHealth for Schizophrenia: Patient Engagement With a Mobile Phone 
Intervention Following Hospital Discharge. JMIR Ment Health. 2016;3(3):e34. 
28. 
Gaudiano BA, Moitra E, Ellenberg S, Armey MF. The Promises and Challenges of Ecological Momentary 
Assessment in Schizophrenia: Development of an Initial Experimental Protocol. Healthcare (Basel). Sep 
2015;3(3):556-573. 

IRB v. 2016.05.24 
Date most recently revised (02/15/19) 
Protocol Version 1.2 
 
Page 16 of 18 
29. 
Moitra E, Gaudiano BA, Davis CH, Ben-Zeev D. Feasibility and Acceptability of Post-Hospitalization Ecological 
Momentary Assessment in Patients with Psychotic-Spectrum Disorders. Comprehensive Psychiatry. 2017;74:204-
213. 
30. 
Wenze SJ, Gaudiano BA, Weinstock LM, Tezanos KM, Miller IW. Adjunctive psychosocial intervention following 
Hospital discharge for Patients with bipolar disorder and comorbid substance use: A pilot randomized controlled 
trial. Psychiat Res. Aug 30 2015;228(3):516-525. 
31. 
Morrison AP, Barratt S. What Are the Components of CBT for Psychosis? A Delphi Study. Schizophrenia Bull. Jan 
2010;36(1):136-142. 
32. 
Rizvi SL, Dimeff LA, Skutch J, Carroll D, Linehan MM. A Pilot Study of the DBT Coach: An Interactive Mobile Phone 
Application for Individuals With Borderline Personality Disorder and Substance Use Disorder. Behav Ther. Dec 
2011;42(4):589-600. 
33. 
Seligman MEP, Steen TA, Park N, Peterson C. Positive psychology progress - Empirical validation of interventions. 
Am Psychol. Jul-Aug 2005;60(5):410-421. 
34. 
Miller WR. Motivational Interviewing with Problem Drinkers. Behav Psychother. 1983;11(2):147-172. 
35. 
Martins RK, McNeil DW. Review of Motivational Interviewing in promoting health behaviors. Clin Psychol Rev. Jun 
2009;29(4):283-293. 
36. 
Fleming MF. Screening and brief intervention in primary care settings. Alcohol Res Health. 2004;28(2):57-62. 
37. 
Williams EC, Johnson ML, Lapham GT, et al. Strategies to Implement Alcohol Screening and Brief Intervention in 
Primary Care Settings: A Structured Literature Review. Psychol Addict Behav. Jun 2011;25(2):206-214. 
38. 
Watson D, Clark L. The PANAS-X: Manual for the positive and negative affect schedule-expanded form. 1994. 
39. 
Harper A, Power M, Grp W. Development of the World Health Organization WHOQOL-BREF quality of life 
assessment. Psychol Med. May 1998;28(3):551-558. 
40. 
WHO. Measuring Health and Disability: Manual for WHO Disability Assessment Schedule (WHODAS 2.0). 2010. 
41. 
Weiden P, Rapkin B, Mott T, et al. Rating of medication influences (ROMI) scale in schizophrenia. Schizophr Bull. 
1994;20(2):297-310. 
42. 
Bush K, Kivlahan DR, McDonell MB, Fihn SD, Bradley KA, Project ACQI. The AUDIT alcohol consumption questions 
(AUDIT-C) - An effective brief screening test for problem drinking. Arch Intern Med. Sep 14 1998;158(16):1789-
1795. 
43. 
Goldberger L, Breznitz S, eds. Handbook of stress: Theoretical and clinical aspects. . New York, NY: The Free Press; 
1993; No. 2. 
44. 
Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. Journal of general 
internal medicine. Sep 2001;16(9):606-613. 
45. 
Cramer JA, Mattson RH, Prevey ML, Scheyer RD, Ouellette VL. How often is medication taken as prescribed? A 
novel assessment technique. JAMA. Jun 9 1989;261(22):3273-3277. 
46. 
Ailinger RL, Black PL, Lima-Garcia N. Use of electronic monitoring in clinical nursing research. Clinical nursing 
research. May 2008;17(2):89-97. 
47. 
O'Carroll R, Dennis M, Johnston M, Sudlow C. Improving adherence to medication in stroke survivors (IAMSS): a 
randomised controlled trial: study protocol. BMC neurology. 2010;10:15. 
48. 
Osterberg L, Blaschke T. Adherence to medication. The New England journal of medicine. Aug 4 2005;353(5):487-
497. 
49. 
Byerly MJ, Nakonezny PA, Rush AJ. The Brief Adherence Rating Scale (BARS) validated against electronic 
monitoring in assessing the antipsychotic medication adherence of outpatients with schizophrenia and 
schizoaffective disorder. Schizophrenia Research. Mar 2008;100(1-3):60-69. 
50. 
Linehan MM, Heard HL. Treatment History Interview (THI). Seattle, WA: University of Washington; 1987. 
51. 
Bak M, van der Spil F, Gunther N, Radstake S, Delespaul P, van Os J. MACS-II: does coping enhance subjective 
control over psychotic symptoms? Acta Psychiatr Scand. Jun 2001;103(6):460-464. 
52. 
Bak M, van der Spil F, Gunther N, Radstake S, Delespaul P, van Os J. Maastricht Assessment of Coping Strategies 
(MACS-I): a brief instrument to assess coping with psychotic symptoms. Acta Psychiatr Scand. Jun 
2001;103(6):453-459. 
53. 
Carr V. Patients' techniques for coping with schizophrenia: an exploratory study. The British journal of medical 
psychology. Dec 1988;61 ( Pt 4):339-352. 
54. 
Meyer B. Coping with severe mental illness: Relations of the brief COPE with symptoms, functioning, and well-
being. J Psychopathol Behav. Dec 2001;23(4):265-277. 
55. 
First MB, Williams JBW, Karg RS, Spitzer RL. Structured Clinical Interview for DSM-5—Research Version (SCID-5 for 
DSM-5, Research Version; SCID-5-RV). Arlington, VA: American Psychiatric Association; 2015. 

IRB v. 2016.05.24 
Date most recently revised (02/15/19) 
Protocol Version 1.2 
 
Page 17 of 18 
56. 
Overall JE, Gorham DR. The brief psychiatric rating scale. Psychol Report. 1962;10:799-812. 
57. 
Larsen D, Attkisson C, Hargreaves W, Nguyen T. Assessment of client/patient satisfaction: Development of a 
general scale. Eval Prog Planning. 1979;2:197-207. 
58. 
Mclellan AT, Luborsky L, Cacciola J, et al. New Data from the Addiction Severity Index - Reliability and Validity in 3 
Centers. J Nerv Ment Dis. 1985;173(7):412-423. 
59. 
Byerly MJ, Nakonezny PA, Rush AJ. The Brief Adherence Rating Scale (BARS) validated against electronic 
monitoring in assessing the antipsychotic medication adherence of outpatients with schizophrenia and 
schizoaffective disorder. Schizophrenia research. 2008 Mar 1;100(1-3):60-9. 
60. 
Brooke J. SUS-A quick and dirty usability scale. Usability evaluation in industry. 1996 Sep;189(194):4-7. 
61. 
Lund AM. Measuring usability with the use questionnaire. Usability interface. 2001;8(2):3-6. 
62. 
Carver CS. You want to measure coping but your protocol’s too long: Consider the brief cope. International 
journal of behavioral medicine. 1997 Mar 1;4(1):92. 
63. 
Folstein MF, Folstein SE, McHugh PR. "Mini-mental state": a practical method for grading the cognitive 
state of patients for the clinician. J Psychiatr Res. 1975;12:189-198. 
64. 
Berman AH, Bergman H, Palmstierna T, Schlyter F. The Drug Use Disorders Identification Test—manual. 
Stockholm: Karolinska Institutet; 2003. 16 p. 
65. 
Martins MJ, Pinto AM, Castilho P, Macedo AF, Pereira AT, Bajouco M, Leite R, Matos O, Morais S, Madeira N, 
Nogueira V. Assessing beliefs and attitudes towards antipsychotic medication from a recovery-based perspective: 
psychometric properties of a new scale. Psychiatry research. 2019 Jan 12. 
 
 
5) CRITERIA FOR WAIVER OF AUTHORIZATION FOR USE OF PROTECTED HEALTH INFORMATION (PHI) 
5A. Does the requested use of PHI involve more than minimal risk to privacy? 
 YES [if " YES," project is not eligible for PHI Waiver]    
 NO [if "NO," address 1-3 below] 
 
1. Plan to Protect Patient Identifiers from Improper Use and Disclosure: 
Potential risks due to loss of confidentiality will be minimized by having all information collected and handled 
by research staff trained to deal appropriately with sensitive clinical issues. All research personnel will receive 
training in research ethics and be approved by the institution to conduct research. All information will be kept 
in locked files. Electronic data will be stored on encrypted drives/servers and password protected.  Data will be 
available only to authorized personnel and subject codes will be used to store information in databases. No 
subject will be identified in any report of this project.  
 
2. Plan to Destroy Identifiers or Justification for Retaining Identifiers: 
PHI will be destroyed upon study completion plus 1 year. 
 
3. Assurances that the PHI will not be Re-used or Disclosed: 
Information collected will only be used for the purposes described below and will be treated as confidential 
material as described above. 
 
5B. Could the research be practicably conducted without a waiver? 
 YES    
 NO 
5C. Could the research be practicably conducted without access to and use of the PHI? 
 
 YES    
 NO 
5D. PHI is only needed for activities preparatory to research 
YES    
NO 
 
6) DESCRIPTION OF PHI TO BE COLLECTED UNDER WAIVER  
Chart reviews of new patients will be routinely conducted by study staff to determine if they are likely to meet 
inclusion/exclusions criteria for the study as described above.  PHI to be obtained:  patient demographic and 
contact information (name, address, telephone numbers, gender, age, race, marital status, occupation status) 

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Protocol Version 1.2 
 
Page 18 of 18 
and patient psychiatric/treatment history (diagnoses and suicide history, past and current psychological and/or 
pharmacological treatments, current mental health provider contact information, lab results).  
 
7) ADVERTISEMENTS 
N/A 
 
8) INFORMED CONSENT FORM (ICF), ASSENT OF MINOR & PARENTAL PERMISSION FORM 
See attached.