Harnessing Digital Health to Understand Clinical Trajectories of Opioid Use Disorder
Conditions: Opioid-use Disorder
Sponsor: Dartmouth-Hitchcock Medical Center

NCT04535583  
 
 
 
 
 
 
 
 
 
NIDA CTN Protocol 0084-A2 
 
Harnessing Digital Health to Understand 
Clinical Trajectories of Opioid Use 
Disorder (D-TECT) 
 
 
Lead Investigators: 
Lisa A. Marsch, PhD 
 
Cynthia Campbell, PhD 
 
 
Sponsor: National Institute on Drug Abuse (NIDA) 
November 19, 2020 
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Lead Investigators (LIs): 
Lisa A. Marsch, PhD 
Northeast Node 
Geisel School of Medicine at Dartmouth 
 
Cynthia Campbell, PhD 
Health Systems Node 
Division of Research 
Kaiser Permanente Northern CA 
Co-Investigators (Co-Is): 
Ching-Hua Chen, PhD, RN 
Northeast Node 
Center for Computational Health 
IBM Research 
 
Saeed Hassanpour, PhD 
Northeast Node 
Geisel School of Medicine at Dartmouth 
 
David Kotz, PhD 
Northeast Node 
Geisel School of Medicine at Dartmouth 
 
Catherine Stanger, PhD 
Northeast Node 
Geisel School of Medicine at Dartmouth 
 
Kathleen Carroll, PhD 
Yale University 
Project Managers: 
Monique Does, MPH 
Health Systems Node 
Division of Research 
Kaiser Permanente Northern CA 
 
Chantal Lambert-Harris, MA 
Northeast Node 
Geisel School of Medicine at Dartmouth 
CCTN Scientific Officer: 
Geetha Subramaniam, MD 
National Institute on Drug Abuse 

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CONFIDENTIALITY STATEMENT 
This document is confidential communication. Acceptance of this document constitutes 
agreement by the recipient that no unpublished information contained herein will be published or 
disclosed without prior approval of the Lead Investigator or other participating study leadership 
and as consistent with the NIDA terms of award. 

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TABLE OF CONTENTS 
1.0 
LIST OF ABBREVIATIONS .............................................................................................................. 8 
2.0 
STUDY SYNOPSIS ......................................................................................................................... 11 
2.1 
Study Objectives ........................................................................................................... 12 
2.2 
Study Design and Outcomes (full description in Section 14.0) ..................................... 13 
2.3 
Sample Size and Study Population .............................................................................. 13 
2.4 
Treatment/Assessment/Intervention and Duration ....................................................... 13 
2.5 
Safety Reporting ........................................................................................................... 14 
2.6 
Analyses (Full Description in Section 14.0) .................................................................. 14 
3.0 
STUDY SCHEMA ........................................................................................................................... 16 
3.1 
Key Research Site Roles .............................................................................................. 17 
4.0 
INTRODUCTION ............................................................................................................................. 18 
4.1 
Background and Significance to the Field .................................................................... 18 
4.1.1 
Study Rationale ..................................................................................................... 18 
4.2 
Innovation ..................................................................................................................... 19 
5.0 
OBJECTIVES.................................................................................................................................. 20 
5.1 
Primary Objective ......................................................................................................... 20 
5.2 
Secondary Objective(s) ................................................................................................ 20 
6.0 
STUDY DESIGN ............................................................................................................................. 21 
6.1 
Overview of Study Design ............................................................................................ 21 
6.2 
Duration of Study and Visit Schedule ........................................................................... 21 
7.0 
OUTCOME MEASURES ................................................................................................................ 22 
7.1 
Primary Outcome Measure ........................................................................................... 22 
7.2 
Secondary Outcome Measure(s) .................................................................................. 22 
7.3 
Other Outcome Measures ............................................................................................ 22 
7.4 
Study Timeline .............................................................................................................. 22 
8.0 
STUDY POPULATION ................................................................................................................... 24 
8.1 
Participant Inclusion Criteria ......................................................................................... 24 
8.2 
Participant Exclusion Criteria ........................................................................................ 24 
8.3 
Strategies for Recruitment and Retention .................................................................... 24 
9.0 
SITE SELECTION ........................................................................................................................... 26 
9.1 
Number of Sites ............................................................................................................ 26 
9.2 
Site Characteristics ....................................................................................................... 26 
9.3 
Rationale for Site Selection .......................................................................................... 26 
10.0 
STUDY PROCEDURES .................................................................................................................. 27 
10.1 
Screening .................................................................................................................. 27 
10.2 
Consent and Baseline ............................................................................................... 27 
10.2.1 
Informed Consent Procedures for Participants ..................................................... 27 

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10.2.2 
HIPAA Authorization and Medical Record Release Forms ................................... 27 
10.2.3 
Baseline ................................................................................................................. 27 
10.3 
Premature Withdrawal of Participants ....................................................................... 28 
10.4 
Study Halting Rules .................................................................................................. 28 
10.5 
Follow-Up .................................................................................................................. 28 
10.6 
Participant Reimbursement ....................................................................................... 29 
11.0 
STUDY ASSESSMENTS ................................................................................................................ 30 
11.1 
Table of Study Assessments .................................................................................... 30 
11.2 
Active Study Phase Digital Health Assessments ...................................................... 32 
11.3 
Description of Measures ........................................................................................... 32 
11.3.1 
Prisoner Status Assessment ................................................................................. 32 
11.3.2 
Inclusion/Exclusion ................................................................................................ 32 
11.3.3 
Locator Form ......................................................................................................... 32 
11.3.4 
PhenX Substance Abuse and Addiction Core Tier 1 (PhenX Core Tier 1)............ 33 
11.3.5 
PhenX Substance Abuse and Addiction Core Tier 2 (PhenX Core Tier 2)/National 
Survey on Drug Use and Health (NSDUH) .......................................................................... 33 
11.3.6 
NetSCID-5 ............................................................................................................. 33 
11.3.7 
Urine Drug Screen ................................................................................................. 34 
11.4 
Follow-up .................................................................................................................. 34 
11.4.1 
Follow-up Assessment .......................................................................................... 34 
11.5 
Digital Health Technology ......................................................................................... 34 
11.5.1 
Ambulatory Physiological Assessment using Mobile Sensors .............................. 34 
11.5.2 
Ecological Momentary Assessment (EMA) ........................................................... 35 
11.5.3 
Momentary Self-Regulation Scale ......................................................................... 35 
11.5.4 
Social Media .......................................................................................................... 35 
11.6 
Other Measures ........................................................................................................ 35 
11.6.1 
Electronic Health Records (EHR) .......................................................................... 35 
11.7 
Clinical and Safety Assessments .............................................................................. 36 
11.7.1 
Safety Events ........................................................................................................ 36 
12.0 
TRAINING REQUIREMENTS ......................................................................................................... 37 
12.1 
Overall ....................................................................................................................... 37 
13.0 
CONCOMITANT THERAPY/INTERVENTION ............................................................................... 38 
13.1 
General ..................................................................................................................... 38 
13.2 
Medications Prohibited/Allowed During Trial ............................................................ 38 
14.0 
STATISTICAL DESIGN AND ANALYSES .................................................................................... 39 
14.1 
General Design ......................................................................................................... 39 
14.1.1 
Study Hypothesis .................................................................................................. 39 
14.1.2 
Primary and Secondary Outcomes (Endpoints) .................................................... 39 

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14.1.3 
Recruitment ........................................................................................................... 39 
14.1.4 
Randomization and Factors for Stratification ........................................................ 39 
14.2 
Rationale for Sample Size and Statistical Power ...................................................... 39 
14.2.1 
Projected Number of Sites .................................................................................... 39 
14.2.2 
Projected Number of Participants per Site ............................................................ 39 
14.3 
Statistical Methods for Primary and Secondary Outcomes ....................................... 39 
14.4 
Significance Testing .................................................................................................. 40 
14.5 
Types of Analyses ..................................................................................................... 40 
14.6 
Interim Analysis ......................................................................................................... 41 
14.7 
Exploratory Analysis ................................................................................................. 41 
14.8 
Missing Data and Dropouts ....................................................................................... 41 
14.9 
Demographic and Baseline Characteristics .............................................................. 41 
14.10 
Safety Analysis ......................................................................................................... 41 
15.0 
REGULATORY COMPLIANCE, REPORTING AND MONITORING ............................................. 42 
15.1 
Statement of Compliance .......................................................................................... 42 
15.2 
Institutional Review Board Approval ......................................................................... 42 
15.3 
Informed Consent ..................................................................................................... 42 
15.4 
Quality Assurance Monitoring ................................................................................... 43 
15.5 
Participant and Data Confidentiality .......................................................................... 43 
15.5.1 
Certificate of Confidentiality ................................................................................... 44 
15.5.2 
Health Insurance Portability and Accountability Act (HIPAA) ................................ 44 
15.6 
Investigator Assurances ............................................................................................ 44 
15.6.1 
Financial Disclosure/Conflict of Interest ................................................................ 45 
15.7 
Clinical Monitoring ..................................................................................................... 45 
15.8 
Inclusion of Women and Minorities ........................................................................... 45 
15.9 
Prisoner Certification ................................................................................................. 45 
15.10 
Regulatory Files ........................................................................................................ 46 
15.11 
Records Retention and Requirements ...................................................................... 46 
15.12 
Reporting to Sponsor ................................................................................................ 46 
15.13 
Audits ........................................................................................................................ 46 
15.14 
Study Documentation ................................................................................................ 46 
15.15 
Protocol Deviations ................................................................................................... 47 
15.16 
Safety Monitoring ...................................................................................................... 47 
15.16.1 
Data and Safety Monitoring Board (DSMB) ....................................................... 48 
15.16.2 
Safety Monitor/Medical Monitor ......................................................................... 48 
15.16.3 
Safety Events ..................................................................................................... 48 
16.0 
DATA MANAGEMENT ................................................................................................................... 49 

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16.1 
Design and Development .......................................................................................... 49 
16.2 
Data Center Responsibilities ..................................................................................... 49 
16.3 
Data Collection .......................................................................................................... 49 
16.4 
Data Acquisition and Entry ........................................................................................ 50 
16.5 
Data Editing .............................................................................................................. 50 
16.6 
Data Transfer/Lock ................................................................................................... 50 
16.6.1 
Data Training ......................................................................................................... 51 
16.6.2 
Data Quality Assurance ......................................................................................... 51 
17.0 
PUBLICATIONS AND OTHER RIGHTS ........................................................................................ 52 
18.0 
PROTOCOL SIGNATURE PAGE .................................................................................................. 53 
19.0 
REFERENCES ................................................................................................................................ 54 
20.0 
APPENDIX A: SAFETY EVENT REPORTING AND PROCEDURES ........................................... 58 
21.0 
APPENDIX B: DATA AND SAFETY MONITORING PLAN .......................................................... 62 
 
 

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1.0 
LIST OF ABBREVIATIONS 
Abbreviation 
Definition 
AE 
Adverse Event 
AMRS 
Addiction Medicine Recovery Services  
API 
Application Programming Interface 
CDC 
Center for Disease Control  
CCTN 
Center for Clinical Trials Network 
CLIA 
Clinical Laboratory Improvement Amendments 
CoC 
Certificate of Confidentiality 
CFR 
Code of Federal Regulations 
CRF 
Case Report Form 
CTN 
Clinical Trials Network 
DM 
Data Manager/Management 
DSC 
Data and Statistics Center  
DSMB 
Data and Safety Monitoring Board 
eCRF 
Electronic Case Report Forms  
EHR 
Electronic Health Record  
EMA 
Ecological Momentary Assessment 
ERC 
Ethics Review Committee  
FDA 
Food and Drug Administration 
FWA 
Federalwide Assurance  
GCP 
Good Clinical Practice  
GPS 
Global Positioning System 

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HEAL 
Helping to End Addiction Long-term 
HHS 
Department of Health and Human Services  
HIPAA 
Health Insurance Portability and Accountability Act 
HSP 
Human Subjects Protection  
ICH 
International Council for Harmonization 
IRB 
Institutional Review Board 
KPNC 
Kaiser Permanente System in Northern California 
LI 
Lead Investigator 
LN 
Lead Node 
MAR 
Missing at random 
MCAR 
Missing completely at random 
MNAR 
Missing not at random 
MOP 
Manual of Procedures 
MOUD 
Medications for Opioid Use Disorder 
NIDA 
National Institute on Drug Abuse 
NIH 
National Institutes of Health 
OHRP 
Office for Human Research Protection 
OUD 
Opioid Use Disorder 
PhenX 
Phenotypic traits and Environmental eXposures 
PI 
Principal Investigator 
PM 
Project Manager 
QA 
Quality Assurance 
RA 
Research Assistant 

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RC 
Research Coordinator 
SAE 
Serious Adverse Event 
NetSCID-5 
Web-based Structured Clinical Interview for DSM-5 
SUD 
Substance Use Disorder 
UDS 
Urine Drug Screen 
UP 
Unanticipated Problems 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

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2.0 
STUDY SYNOPSIS 
Across the U.S., the prevalence of opioid use disorder (OUD) and the rates of opioid overdoses 
have risen precipitously in recent years. Drug overdose is being called a “modern plague” (Katz, 
2017) and is now the leading cause of death of Americans under age 50, having surpassed 
peak death rates from gun violence, HIV, and car crashes (Centers for Disease Control and 
Prevention (CDC), 2018; Katz, 2017). This dramatic spike in OUD has also been accompanied 
by marked increases in injection-related infections (including infective endocarditis and Hepatitis 
C) (Centers for Disease Control and Prevention (CDC), 2016, 2017; Hartman et al., 2016; 
Keeshin & Feinberg, 2016), babies born with Neonatal Opioid Withdrawal Syndrome (Patrick, 
Davis, Lehmann, & Cooper, 2015) and healthcare and criminal justice costs (Rhyan, 2017). 
  
Several effective medication-assisted treatments for OUDs exist.  Treatment models for OUDs 
that include buprenorphine medication are among the most effective treatment models. 
Buprenorphine treatment for OUD has been shown to greatly increase opioid abstinence, 
reduce HIV/infectious disease risk behavior, and criminality.  Greater retention in such treatment 
models are associated with the most positive treatment outcomes (Connock et al., 2007; 
Johnson, Jaffe, & Fudala, 1992; Ling et al., 1998; Sordo et al., 2017a). However, given the 
chronic relapsing nature of the disease of addiction, many individuals continue to engage in 
opioid use during treatment.  Further, many individuals who enter buprenorphine treatment do 
not consistently take their medication or remain engaged in treatment – typically resulting in 
continued opioid use (which is accompanied by risk of overdose) (Fiellin et al., 2008; Schuman-
Olivier, Weiss, Hoeppner, Borodovsky, & Albanese, 2014). Although many factors (e.g., stress, 
mental health comorbidities, and continued exposure to high risk social networks or contexts) 
have been shown to predict non-adherence in substance use disorder treatment (Simon et al., 
2017; Weinstein et al., 2017), most studies have examined a small set of potential moderators 
or mediators of outcomes in treatment for OUD and may lead to over-simplified accounts of 
treatment non-adherence. 
  
More frequent and longer assessment of moderators, mediators, and outcome(s) are necessary 
to elucidate the temporal dynamics between changes in specific mechanisms and treatment 
non-adherence behavior (Collins & Graham, 2002). Examining a broad array of factors 
impacting treatment non-adherence at multiple levels of analysis will enable a more 
comprehensive picture and will increase our ability to develop more impactful interventions for 
OUD. 
  
Advances in digital technologies and data analytics have created new opportunities to assess 
and modify health behavior and thus accelerate the ability of science to understand and contribute 
to improved health behavior and health outcomes.  Given the ubiquity of access to digital 
technologies worldwide, digital tools allow for the examination of health behavior and clinical 
trajectories within-individuals through intensive collection of individual-level, real-time data 
collected via surveys on mobile device (referred to as Ecological Momentary Assessment [EMA]),  
wearable sensors (on smartphones and/or smartwatches), and mapping digital footprints. 
Digitally-derived data allow for the development of dynamic models of health behavior to 
understand behavior in real-time and in response to changing environmental, social, 
physiological, and intrapersonal factors (Naslund et al., 2017; Spruijt-Metz, 2014).  As applied to 
persons with OUD,  digital data that offers ongoing assessment of behavior as individuals live 
their daily lives can help us better understand the trajectory of clinically important behaviors (e.g., 
treatment retention; medication adherence over time) and identify fluctuating contextual factors 
that greatly influence such behaviors, (e.g., patterns leading to relapse or treatment dropout).    
  
 

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Parent Study 
This study is an ancillary study to CTN 0084 “Establishing an Opioid Registry Across Diverse 
Health Systems” (PI: Cynthia Campbell).  An aim of CTN 0084 focuses on the use of EHR data 
from several health systems to examine the relationship between different lengths of 
buprenorphine retention and mortality.   The optimal duration of buprenorphine treatment to 
reduce the risk of relapse, overdose, and mortality outcomes is unknown, although generally a 
longer length of treatment is related to better opioid use outcomes and lower risk of mortality 
(Dupouy et al., 2017; Sordo et al., 2017b; Weiss & Rao, 2017).  However, retention in treatment 
remains a well-documented challenge and factors such as relapse, other substance use, 
inability to adhere to program stipulations, loss of insurance, cost, patient preference, provider 
practice, or health system policies can be related to discontinuation. CTN 0084 examines the 
distribution of buprenorphine retention, associated patient and health system characteristics, 
and rates of mortality, providing a high level view of this problem. This ancillary study 
complements the parent study by offering a “deep dive” into key factors associated with 
treatment retention (examining EHR data complemented by digitally-derived data) through data 
collected in real-time from a subset of patients in buprenorphine treatment for OUD as they live 
their daily lives.  This ancillary study is a pilot, observational study and is not powered to test 
specific hypotheses. 
2.1 Study Objectives 
The primary objective of this study is to evaluate the feasibility of utilizing digital health technology 
(EMA and digital sensing) continuously over a 12-week period and collecting social media data. 
The secondary objective is to examine the utility of EMA, digital sensing, and social media data 
(separately and compared to one another) in predicting OUD treatment retention, buprenorphine 
medication adherence (as captured in EHR, medical claims, and EMA data).  
 
 

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2.2 Study Design and Outcomes (full description in Section 14.0) 
Individuals who are active in medication treatment for opioid use disorder (MOUD) with 
buprenorphine for at least 2 weeks will be invited to participate in the study. This project will 
evaluate the feasibility and benefits of digital health technologies that can be embedded in clinical 
trials. Feasibility will be evaluated by the percentage of eligible participants who enroll and adhere 
to a 12 week period of assessment using passive mobile sensing devices (smartwatch and 
smartphone), daily randomly prompted EMAs (that assess sleep, stress, pain severity, pain 
interference, pain catastrophizing, craving, withdrawal, substance use risk context, mood, 
context, substance use, self-regulation, MOUD adherence, and impact of COVID-19), self-
initiated substance use EMA, and social media data download. Participating in the social media 
data download portion of the study will be optional. The secondary outcomes will be treatment 
retention and buprenorphine adherence through EMA and EHR/medical claims data over 12 
weeks (specifically, the 12 weeks of study participation as well as the 12 months prior to when 
the individuals start EMAs). 
2.3 Sample Size and Study Population 
Participants in the study will include approximately 50 (if recruitment is faster than anticipated, we 
will recruit up to 75) individuals who at the time of consent are active in MOUD with buprenorphine 
for at least 2 weeks prior to study enrollment. The study population will include males and females, 
age 18 and older, English-speakers, identified from Kaiser Permanente in Northern California 
(KPNC) members who have received treatment at one of KPNC’s Addiction Medicine Recovery 
Services programs.  
2.4 Treatment/Assessment/Intervention and Duration 
This is an observational study designed to (1) evaluate the feasibility and utility of digital health 
technology in a MOUD treatment population, and (2) capitalize on the availability of EHR data to 
relate passive and active sensing data to treatment retention and medication adherence. This 
feasibility study will be conducted rapidly (e.g., within 1 year plus time to data lock) to generate 
data that can inform other HEAL (Helping to End Addiction Long-termSM) Initiative studies and 
clinical trials of populations with OUD. 
Eligible participants are identified through EHR records, sent an invitational letter through secure 
message, and then called to recruit and screen. Following verbal consent to screen, research 
staff will perform a screening assessment over the phone/video to determine preliminary study 
eligibility prior to scheduling the baseline phone/video visits. Following electronic signed informed 
consent, the Baseline assessment will consist of interviewer-administered measures examining 
participant characteristics, current substance use (e.g., tobacco, alcohol, opioids, and other 
drugs), and substance use and mental health disorders.  In addition to the screening and baseline 
assessments, the participants will be asked to wear a smartwatch and carry a smartphone 
continuously for a period of 12 weeks.  The smartwatch will passively collect data regarding 
distance traveled, physical activity (including metrics of energy expenditure and steps), sleep, and 
heart rate. Also, participants will be prompted to respond to questions through a smartphone (i.e., 
EMA) up to 3 times daily for 12 weeks. Responses to these questions (which include questions 
regarding sleep, stress, pain severity, pain interference, pain catastrophizing, craving, withdrawal, 
substance use risk context, mood, context, substance use, self-regulation, MOUD adherence, 
and impact of COVID-19) will take approximately 10 minutes to complete at each prompting. In 
addition to the EMA prompts, individuals will be asked to self-initiate EMAs if substance use 
occurred.  The responses to the self-initiated EMAs will take roughly 5 minutes to complete.  App 
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information, Wi-Fi & Bluetooth logs, sleep, ambient light, and proximity will be passively collected 
via smartphone. After the 12-week active study phase, participants complete a follow-up 
phone/video visit.  At the follow-up phone/video visit, research staff will administer an interview-
based assessment to measure current substance use (e.g., tobacco, alcohol, opioids, and other 
drugs), participant experience with the study devices (including wearing the smartwatch, carrying 
the smartphone, and responding to EMAs), treatment utilization, reasons for drop out (if 
appropriate), medication use/dose (if applicable), and overdose.  For those who consent, social 
media data will be downloaded by the participant directly from the social media platform to a 
secure server using a remote desktop at the beginning of the study and at the end of the study. 
EHR and medical claims data (e.g., pharmacy claims data for Kaiser and non-Kaiser pharmacies 
if a claim was paid for) will be extracted 16 weeks after study completion (data will be collected 
12 months prior to EMA start through 12 weeks after EMA start). Prior to each encounter 
(screening, baseline and follow-up), research staff will administer a brief prisoner status 
assessment to confirm study eligibility (non-prisoner status). 
2.5 Safety Reporting 
As this is an observational, non-intervention study, study-related Safety Events are anticipated to 
be rare. Nevertheless, this population is at elevated risk for overdose and other medical and 
psychiatric problems, and safety events may be elicited at baseline or spontaneously reported to 
study staff at any time while individuals are participating in the study. All project/site staff will be 
trained to recognize and report any safety event as described in Section 15.16. Safety events 
involving human participants, include, for example, suicidal ideation. 
The study has a Study Clinician who will review each safety event as it occurs, and details of the 
safety event will be recorded in a secure database. Safety events requiring reporting to the Kaiser 
Permanente Northern California Institutional Review Board will be reported. All events that are 
serious, related and unexpected, or that place subjects at greater risk of harm will be promptly 
reported to Kaiser IRB (IRB of Record), as outlined in KPNC IRB guidance (policy # N-CRSP 
HRP 071). The Lead Investigators will be responsible for reporting to external parties (including 
Kaiser IRB). 
The NIDA Program Officer must be informed of any death occurring during the study or coming 
to the attention of the study staff during the protocol-defined follow-up period.  This report is made 
to NIDA regardless of whether the death was study related or unanticipated. 
2.6 Analyses (Full Description in Section 14.0) 
In order to measure the feasibility of digital health technology, we will generate descriptive 
statistical summaries of the level of adherence of study participants to the desired protocol (e.g., 
EMA response rate, smartwatch and smartphone wear/carry rate).  No statistical inference is 
planned for this assessment.  Feasibility will be evaluated via the following three independent 
metrics:  1) the percentage of days during the 12-week active phase enrolled participants 
wore/carried the smartwatch and smartphone; 2) the response rate to EMA prompts during the 
12-week active phase; and 3) the percentage of participants who consent to social media data 
download and sparsity of social media data per participant. 
In digital health data (Jain, Powers, Hawkins, & Brownstein, 2015a), the spatio-temporal 
granularity of information about an individual is of higher resolution than that obtained through 
cross-sectional or traditional longitudinal studies. Therefore, we define endpoints (dependent 
variables) that may occur repeatedly over a 12-week observational period, and aim to use data 
from smartphones, wearable devices, social media and EMA to predict, explain and detect these 
endpoints.  

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Our analyses comprise three main efforts: Predicting endpoints using passively and actively 
collected digital health and social media data; Explaining temporal-causal relationships between 
factors determined to be useful for predicting endpoints; Detecting event-specific endpoints using 
passively collected digital health and social media data. 
Our approach to prediction will include regression-based methods (e.g., logistic regression), but 
we will also use common machine learning approaches for binary classification (e.g., random 
forest, support vector machines, K-nearest neighbor, gradient boosting). Although machine 
learning methods may often be more effective for prediction than regression-based methods, they 
may be difficult to explain, or may not reveal insights regarding the relationships between factors. 
Therefore, we also include a set of analyses that are conducive to generating such explanatory 
or descriptive insights. For example, we will apply supervised metric learning and prototypical 
case-based reasoning (Hsueh, Das, Maduri, & Kelly, 2018), topic-modeling (e.g., Latent Dirichlet 
Allocation) and causal inference methods (Hernan & Robins, 2006; Donald B. Rubin, 1974) 
(Kleinberg & Hripcsak, 2011). For detecting endpoints that currently rely on actively collected 
ecological momentary assessment, we will attempt to use only passively collected data to 
correctly classify whether the endpoint of interest has occurred. 

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3.0 
STUDY SCHEMA 
 
 

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3.1 Key Research Site Roles 
Site Principal Investigator (Site PI): The Site PI is the PI for the study who is at the site where 
research is taking place. This person is responsible for the oversight of study staff at the site and 
all aspects of protocol implementation at the site(s).  
*If the Site PI is not a PhD or PsyD (Clinician), then an additional role of Study Clinician (PhD or 
PsyD) is required to review Safety Events.  
Site Project Manager (Site PM): The Site PM is responsible for the oversight of RC/RAs at the 
site(s) and all aspects of study implementation at the site(s). 
Research Coordinator (RC) and/or Research Assistant (RA). The RC/RA is responsible for 
working with the Site PI to ensure all aspects of the study are being implemented and followed 
according to the protocol at the site. The RC/RA will focus on; recruitment, participant 
communication, administering assessments, data collection/cleaning, study supply tracking, and 
working with local Node staff and the Lead Node to review and monitor study progress. 

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4.0 
INTRODUCTION 
4.1 Background and Significance to the Field 
4.1.1 Study Rationale 
Across the U.S., the prevalence of OUD and the rates of opioid overdoses have risen precipitously 
in recent years. Drug overdose is being called a “modern plague” (Katz, 2017) and is now the 
leading cause of death of Americans under age 50, having surpassed peak death rates from gun 
violence, HIV, and car crashes (Centers for Disease Control and Prevention (CDC), 2018; Katz, 
2017). This dramatic spike in OUD has also been accompanied by marked increases in injection-
related infections (including infective endocarditis and Hepatitis C) (Centers for Disease Control 
and Prevention (CDC), 2016, 2017; Hartman et al., 2016; Keeshin & Feinberg, 2016), babies born 
with Neonatal Opioid Withdrawal Syndrome (Patrick, Davis, Lehmann, & Cooper, 2015) and 
healthcare and criminal justice costs (Rhyan, 2017). 
Although many factors have been shown to predict non-adherence in substance use disorder 
treatment (Simon et al., 2017; Weinstein et al., 2017); very few have been shown to be consistent 
across samples and most explain limited amounts of variance in outcome (DeVito, Carroll, & 
Sofuoglu, 2016). Most studies have examined a small set of potential moderators or mediators of 
outcomes in treatment retention and medication adherence for OUD, and thus may have led to 
over-simplified conceptions of a highly heterogeneous disorder.  
Advances in digital technologies and data analytics have created new opportunities to assess 
and modify health behavior and thus accelerate the ability of science to understand and contribute 
to improved health behavior and health outcomes. Given the ubiquity of access to digital 
technology worldwide, digital technologies afford new opportunities to examine within-person 
differences in health behavior through intensive collection of individual-level data using mobile 
devices, wearable sensors, continuous monitoring, and mapping digital footprints. Digital 
technologies can also enable widespread reach and scalability of evidence-based, 
anytime/anywhere access to personalized interventions (Marsch, Lord, & Dallery, 2014). 
Specifically, mobile technologies enable EMA, (Shiffman, Stone, & Hufford, 2008) a method that 
prompts individuals to respond to queries (e.g., regarding positive and negative affect, context, 
access to opioids, urge to use (craving), drug use, withdrawal, perceived stress, sleep/sleep 
disturbance, and perceived pain) on mobile devices, and which enables “automated hovering” 
(Asch, Muller, & Volpp, 2012) or real-time monitoring, of individuals’ behavior while they engage 
in everyday activities and over time. The frequent, longitudinal assessment afforded by EMA in 
naturalistic contexts may clarify the dynamic role of mechanisms, or reveal new mechanisms, 
contributing to health behavior (McCarthy et al., 2008) in individuals who use opioids or who are 
in treatment for opioid use.  
Digital technologies also enable passive sensing and inference from smartphones or sensing 
devices worn on the body, which is transforming how we understand human behavior, including 
health behavior. These mobile sensing technologies enable the continuous measurement of 
physiological and behavioral data in the real world as individuals move through their daily lives. 
This sensor data can be wirelessly streamed to a smartphone and processed in real-time on the 
mobile device to infer information about an individual’s behavior, health, and environment. These 
data from sensors can be combined with data from self-report EMA assessments embedded on 
mobile devices for real-time inference of environmental, social, and behavioral conditions 
(Marsch, 2018a, 2018b). In the future, this information could be used to prompt the delivery of 
interventions in real time (e.g., interventions that are directly responsive to the behavioral health 

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needs of an individual, such as a depressive state or craving of a substance of abuse) (Burns et 
al., 2011; Gustafson et al., 2014). 
Further, the use of social media sites (e.g., online forums, social blogs) has exploded in recent 
years. Social media enables multi-directional communication anywhere and anytime. Social 
media data have been used to predict many phenomena, ranging from purchasing patterns to 
health epidemics (Brownstein, Freifeld, & Madoff, 2009; Darden & Perreault, 1976). A growing 
body of literature is showing how social media data may enable a rich understanding of the 
topology and functioning of social networks and their relationships to health/risk behavior 
(Kazemi, Borsari, Levine, & Dooley, 2017; S. J. Kim, Marsch, Brunette, & Dallery, 2017; S.J. Kim, 
Marsch, Hancock, & Das, (Forthcoming 2017); Naslund, Kim, et al., 2017). For example, social 
media has been shown to contain signals of depression among individuals, such as via predictors 
of decreased social activity, increased negative affect, highly clustered egocentric networks, and 
heightened concerns about relations and medications (Choudhury, Gamon, Counts, & Horvitz, 
2013). Data derived from Facebook has been shown to predict a range of attributes including use 
of addictive substances (Kosinski, Stillwell, & Graepel, 2013); however, these have not been 
explored in individuals with OUD. 
Digitally-derived, empirical data can markedly refine and advance our understanding of health 
behavior. These data allow for the development of dynamic models of health behavior to 
understand behavior in real-time and in response to changing environmental, social, 
physiological, and intrapersonal factors (Naslund, Aschbrenner, et al., 2017; Spruijt-Metz & 
Nilsen, 2014). Digital health technology methodologies have enabled new insights into several 
areas of health behavior, including mental health disorders and physical well-being. (Barnett et 
al., 2018; Onnela & Rauch, 2016). Results from this study may help identify useful digital data 
sources that may enhance outcomes measurement in clinical trials by allowing for the assessment 
of dynamic interactions between treatment and symptom response (Mofsen et al., 2019; Nugent, 
Pendse, Schatten, & Armey, 2019; Roos & Witkiewitz, 2017). 
4.2 Innovation 
● The project would be the first in this population to employ passive mobile sensing; social 
media data; and active responses to queries on mobile devices using ecological 
momentary assessment (EMA) that assess sleep, stress, pain severity, pain 
interference, pain catastrophizing, craving, withdrawal, substance use risk context, 
mood, context, substance use, self-regulation, MOUD adherence and impact of COVID-
19 to obtain moment-by-moment quantification of an array of individual-level data that 
may predict treatment retention and medication adherence (in response to changing 
environmental, social, physiological, and intrapersonal factors). 
● Use of novel analytic methods, including machine learning, is also innovative.  
● Use of EHR to track MOUD retention and adherence is innovative, leverages existing 
CTN infrastructure to reduce patient burden, and, by definition, focuses on a “real world” 
outcome, thereby enhancing the potential clinical utility. 
 
 

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5.0 
OBJECTIVES  
5.1 Primary Objective  
The primary objective of this study is to evaluate the feasibility of 1) utilizing digital health 
technology (EMA and digital sensing) to collect data continuously over a 12-week period and 2) 
collecting social media data.  
5.2 Secondary Objective(s)  
The secondary objective is to examine the utility of EMA, digital sensing, and social media data 
(separately and compared to one another) in predicting OUD treatment retention, and 
buprenorphine medication adherence (as captured in EHR, medical claims, and EMA data). 

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6.0 
STUDY DESIGN 
6.1 Overview of Study Design 
Individuals with OUD who are active in outpatient buprenorphine treatment for at least 2 weeks 
will be recruited for the study. Potentially eligible individuals will be identified through the EHR 
and sent an invitational letter through secure message. Subsequently, study staff will call potential 
participants, and individuals interested in the study will go through a verbal consent process and 
complete the screening assessment by phone/video. Once it is confirmed that eligibility criteria 
are met, the participant will provide electronic informed consent and complete the baseline 
assessment by phone/video. The baseline appointments will take approximately 2.0 hours to 
complete, which will be done in two to three visits (preferably in two visits).  Participants will wear 
a smartwatch and carry a smartphone (a study-supplied one or their own) that will passively collect 
sensor data. They will be asked to actively respond to EMA prompts through a smartphone up to 
3 times daily and to self-initiate EMAs daily if substance use occurred over the 12 week study. 
For those who consent, social media data will be downloaded by the participant directly from the 
social media platform to a secure server using a remote desktop at the beginning of the study  
and again at the end of the study. EHR and medical claims data extraction will occur at 
approximately 16 weeks after study completion and will collect data 12 months prior to EMA start 
through 12-weeks post-EMA start. A follow-up assessment (taking approximately 45 minutes to 
complete assessments plus 15 minutes to instruct participants on how to return study equipment) 
will occur approximately 12 weeks post-EMA start by phone/video.   
6.2 Duration of Study and Visit Schedule 
Participants will complete screening by phone/video (approximately 10 minutes) and two to three 
baseline phone/video appointments which will take approximately 2.0 hours. The study involves 
a 12-week active phase wherein participants will wear a smartwatch, carry a smartphone, and 
respond to EMA prompts and self-initiated EMAs through a smartphone. For those who consent, 
social media data will be downloaded by the participant directly from the social media platform to 
a secure server using a remote desktop at the beginning of the study and again at the end of the 
study. A follow-up phone/video appointment (approximately 60 minutes) will occur approximately 
12 weeks post-EMA start.  EHR and medical claims data will be extracted by the research staff 
approximately 16-weeks after study completion and includes data 12 months prior to EMA start 
through 12 weeks post-EMA start. 

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7.0 
OUTCOME MEASURES  
7.1 Primary Outcome Measure 
Primary outcome measures will include:  
1. Feasibility - the percentage of days during the 12-week active phase enrolled 
participants wore/carried the smartwatch and smartphone;  
2. Feasibility - response rate to EMA prompts during the 12-week active phase; and 
3. Feasibility - the percentage of participants who consent to social media data download 
and sparsity of social media data per participant. 
7.2 Secondary Outcome Measure(s)  
The secondary outcome measures will include:  
1. OUD treatment retention (days retained in OUD treatment program) based on EHR data;  
2. Days covered on MOUD based on EHR and EMA data; and  
3. Non-prescribed opioid use (including illicit opioid use) based on EMA data. 
7.3 Other Outcome Measures 
Other outcomes will include: 
1. Frequency of missed buprenorphine doses based on EMA data; 
2. Percentage of days with access to prescription medication exceeding a threshold (e.g., 
80%) over the 12-week study period (a dichotomous variable based on pharmacy 
dispensation and medication orders from the EHR data extraction);  
3. Number of days of non-prescribed opioid use (including illicit opioid use) in the last 4 
weeks (weeks 9-12 post study consent) based on EMA data; and 
4. Each non-prescribed opioid use event during the 12-week study period based on EMA 
data. 
5. Each missed dose event during the 12-week study period based on EMA data. 
6. Each missed visit to OUD treatment program during the 12-week study period based on 
EHR data. 
7.4 Study Timeline 
After receiving NIDA Center for Clinical Trials Network (CCTN) approval of the full/final protocol, 
approximately 6 months of trial preparation activities will elapse prior to commencing enrollment. 
Study preparation will include obtaining IRB approval, developing the data collection systems, 
refining the manual of procedures (MOP), hiring and training staff, and endorsing sites. We 
anticipate the study may be implemented in a single wave; however, sites may launch on a rolling 
basis if necessary.  
The research team will develop and refine the digital health data collection software, as well as, 
the data tracking and storage database (a duration of approximately 4 months). We will examine 
all procedures with approximately 5 individuals, during their first several weeks of study 
involvement, to ensure any potential glitches with the EMA prompt scheduling, sensor data 
collection, and/or data transfer are identified and if necessary, make further adjustments. 
Recruitment for the digital component is expected to take approximately 6 months. Follow-up 
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months after the last participant is enrolled. EHR and medical claims data extraction will be 
completed approximately 4 months after the active phases of study ends. Therefore, data lock is 
projected to be completed approximately 20 months after CCTN approval of the final protocol.  
 
Months 1-6: Study preparation  
Months 7-12: Recruitment 
Months 9-15: Active phase ends for participants   
Months 16-20: Data Lock (staggered lock depending on data source: sensor/EMA, social 
media, EHR/medical claims) 
 

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8.0 
STUDY POPULATION 
Approximately 50 (if recruitment is faster than anticipated, we will recruit up to 75) individuals who 
are active in outpatient buprenorphine treatment for at least two weeks. Participants will include 
males and females, aged 18 years or older, across all racial and ethnic categories. We will recruit 
from the Addiction Medicine Recovery Services (AMRS) program at Kaiser Permanente in 
Northern California (KPNC), which is part of the Health Systems Node. The KPNC AMRS 
programs provide integrated SUD treatment, including buprenorphine and other services. 
8.1 Participant Inclusion Criteria  
Individuals participating in the study must: 
1. Have been active in Kaiser outpatient buprenorphine treatment for OUD for the past 2 
weeks (determined at screening);  
2. Be ≥18 years old (determined at screening); 
3. Be able to understand English (determined at screening);  
4. Be available to participate in the full duration of the study (12 weeks) (determined at      
screening); 
5. Have an active email account and willing to provide the email address to researchers 
(determined at screening); 
6. Permit researchers to access personal electronic health record (EHR) and medical 
claims data (determined at screening); 
7. Be willing to carry and use personal or study provided smartphone for 12 weeks 
(determined at screening); and 
8. Be willing to wear a smartwatch continuously (except during pre-defined activities such 
as showering) for 12 weeks (determined at screening). 
 
8.2 Participant Exclusion Criteria  
Participants will be excluded from the study if they: 
1. Are unwilling or unable to provide informed consent (determined during the Consent 
process and during Consent Quiz); and 
2. Are currently in jail, prison or other overnight facility as required by court of law or have 
pending legal action that could prevent participation in study activities (determined by 
Prisoner Status Assessment at each study visit).  
8.3 Strategies for Recruitment and Retention  
Potentially eligible patients will be identified in the electronic health record and sent an invitational 
recruitment letter/secure message. Within approximately a week of mailing recruitment 
letters/sending a secure message, research staff will contact participants by phone to determine 
if they are interested and eligible, using the IRB-approved recruitment script, verbal consent and 
screening questions.  
Study participants will be compensated $75 for completing the Baseline appointments and 
baseline urine drug screen, and $100 for completing the 12-week Follow-up appointment and 
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During the 12-week active phase of the study (the 12 weeks of EMA and sensor data collection 
via smartphone and smartwatch), research staff will contact participants to encourage them to 
continue their participation and/or troubleshoot any problems that may arise with their 
smartphone, smartwatch or EMA. Staff will also contact (e.g., call, text, email) participants if 
sensor data is not being recorded from the smartphone, smartwatch and/or if there is a lapse in 
responding to EMA prompts on the smartphone. If there are unexpected issues or problems with 
the technology (study equipment, study apps, social media download) that research staff cannot 
resolve with the participant, research staff may need to contact technical support personnel at 
Dartmouth using a 3-way or conference call to assist the participant with troubleshooting technical 
issues. 
To be considered engaged in the study, an individual must respond to a minimum number of EMA 
prompts and have recorded a minimum number of smartphone/smartwatch sensor data on 7 out 
of the first 14 days of study participation. An individual will be contacted via phone, text, and/or e-
mail by research staff after two days with no EMA or sensor data collected. If an individual does 
not meet the engagement criterion AND is non-responsive to research staff outreach in the first 
14 days of study participation, then the individual will be considered a “non-engager” and the 
study team will continue to recruit until 50 (if recruitment is faster than anticipated, we will recruit 
up to 75) “engaged” individuals are enrolled. Non-engagers will not be withdrawn from the study, 
as we will attempt to collect all possible data from all participants. 
To aid retention and adherence with the digital health data collection, participants will be 
compensated up to $21 per week for completing EMAs, up to an additional $10 per week bonus 
for completing a minimum of 80% of received EMAs, and up to $14 per week for carrying their 
smartphone at least 8 hours per day and wearing the smartwatch at least 18 hours per day. At 
the end of the 12-week active phase of the study, participants will receive a $50 bonus for either 
using their personal smartphone (to help offset the cost of their data plan) or returning a study-
provided smartphone, and a $50 bonus for returning the study-provided smartwatch. Finally, 
participants who consent to the social media portion of the project will receive up to an additional 
$180. Total possible compensation will be up to $820 over the course of the 12-week active study 
phase. In addition to the earnings and bonuses (described above), an individual who completes 
a minimum of 80% of received EMAs within a given week will qualify for a drawing at the end of 
that week where the individual could win a $50 prize. Each individual will have an opportunity to 
participate in up to 12 drawings over the 12 weeks.  During the 12-week active study phase, any 
incentives, bonuses, and/or drawings earned will be uploaded weekly to a reloadable debit card. 
Total compensation will be up to $995 for participating in all study activities.  
 

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9.0 
SITE SELECTION 
9.1 Number of Sites 
We will recruit approximately 50 (if recruitment is faster than anticipated, we will recruit up to 75) 
participants from KPNC (part of the Health Systems Node) who have had treatment at KPNC’s 
Addiction Medicine Recovery Services (AMRS) programs.  
9.2 Site Characteristics 
The AMRS programs at Kaiser Permanente Northern California (KPNC) offer a broad range of 
services (medical services onsite, group and individual therapy, family therapy). Staffing includes 
physicians, social workers, and substance use counselors. The AMRS programs offer MOUD 
treatment for buprenorphine. 
We anticipate roughly 180 patients with OUD on buprenorphine for at least 2 weeks will be 
approached for recruitment.  Assuming a conservative 30% recruitment rate, we anticipate 
approximately 50 (if recruitment is faster than anticipated, we will recruit up to 75) patients enrolled 
over the 6-month study recruitment period. 
9.3 Rationale for Site Selection 
KPNC was selected based on its ability to (1) provide access to individuals who are in MOUD 
buprenorphine treatment and (2) provide access to EHR data on treatment retention, medication 
adherence, and service utilization. KPNC serves a mixed population (in terms of severity) of 
individuals in treatment for OUD. KPNC is an integrated healthcare system that maintains a data 
repository, the Virtual Data Warehouse, which has combined EHR data (e.g., demographics, 
membership, diagnoses, service utilization, pharmacy, lab data) with several other data sources, 
including medical claims data (e.g., non-Kaiser pharmacy data). Participant EHR data will include 
urine toxicology results, buprenorphine dispensation data, and treatment utilization data (e.g., 
substance use, primary care, psychiatry, emergency department, inpatient, phone appointments, 
secure messages) which reflects any encounters with the health system. 

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10.0 STUDY PROCEDURES  
10.1 Screening  
Patients will be screened by phone/video to determine eligibility. After briefly explaining the study, 
conducting prisoner assessment and obtaining verbal consent, research staff will perform the 
screening and complete the Inclusion/Exclusion form. If eligible, research staff will schedule the 
initial baseline phone/video appointment and send consent documents to participant for their 
review before their appointment. (see Section 11).   
The screening will take approximately 10 minutes to complete. 
10.2 Consent and Baseline  
10.2.1 Informed Consent Procedures for Participants 
Informed consent will be obtained by phone/video and documented online using an electronic 
signature. Participants will have been given an opportunity to review consent documents prior to 
the baseline phone/video appointment (see 10.1). At the initial baseline phone/video appointment, 
research staff will review all elements of consent with participant over the phone/video 
(procedures, risks, benefits, compensation, etc.) and provide an opportunity for participant to ask 
questions.  
Once questions are answered, the participant will be asked to pass a brief consent quiz to 
document comprehension of the study activities. Any incorrect responses will be reviewed with 
the participant by research staff. After providing an electronic signature, participants will be able 
to print a copy of the forms to keep for their records. The informed consent process and quiz will 
take approximately 30 minutes to complete. Patients will be provided two opportunities to pass 
the quiz, at which point they will be determined ineligible.  
10.2.2 HIPAA Authorization and Medical Record Release Forms 
The study site will obtain authorization from participants for use of protected health information, 
such as access to their EHR and medical claims data. The site will be responsible for 
communicating with their IRB(s) or Privacy Boards and obtaining the appropriate approvals or 
waivers to be in regulatory compliance.                
10.2.3 Baseline  
The baseline will be conducted in two or three phone/video appointments: the first appointment 
will consist of informed consent and the baseline assessment, and the second appointment will 
consist of urine drug screen, setting up study devices, installing study applications (“apps”), and 
learning to use devices and apps.  If needed, appointments will be conducted with HIPAA 
compliant IRB-approved video capability. 
Initial baseline appointment (1 hour): After conducting prisoner assessment and providing 
informed consent, participants will complete the Baseline assessment (see Section 11). The 
Baseline assessment consists of interviewer-administered measures examining participant 
characteristics, current substance use (e.g., tobacco, alcohol, opioids, and other drugs), 
substance use and mental health disorders, and the impact of COVID-19.   

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Once the first Baseline appointment is completed, participants will be mailed their urine drug 
screen (UDS) kit, their smartwatch and study smartphone (if applicable) and technology training 
documentation.  
Second Baseline appointment (1 hour): Once the equipment is received, research staff will 
schedule a second phone/video appointment with participant to review the urine collection and 
technology training documentation. Research staff will walk through the set-up, use and care of 
smartphone and smartwatch, installation of the study app and the Garmin Connect app, as well 
as instructions for initiating and completing the daily EMAs. Research staff will also instruct 
participants to collect urine sample and upload results. If any technical issues arise, the research 
staff have the ability to upload the photographs into REDCap for the participant. Once the urine 
drug screen results are received, participants will be reimbursed $75 (via gift card) for completion 
of the baseline. 
A third baseline appointment can be arranged if needed.  We don’t anticipate this will occur 
frequently as the tasks should easily be completed within two baseline appointments. 
Research staff will explain to participants that EMA data will not be monitored in real-time, and 
participants will be instructed to call their medical providers or 911 if they have an immediate crisis 
or an emergency.  
Participants will be instructed on how to download social media (for those who consented to this 
part of the study). Social media data will be downloaded by the participant directly from the social 
media platform to a secure server at Dartmouth using a remote desktop at the beginning of the 
study.  
Additional compensation will be provided for social media data download, as well as participation 
in the active phase of the study (completing EMAs, wearing the smartwatch and carrying the 
smartphone) (described in Section 8.3). 
If there are unexpected issues or problems with the technology (study equipment, study apps, 
social media download) during the active phase of the study that research staff cannot resolve 
with the participant, research staff may need to contact technical support personnel at Dartmouth 
using a 3-way or conference call to assist the participant with troubleshooting technical issues. 
10.3 Premature Withdrawal of Participants 
All participants will be followed for the duration of the study unless they withdraw consent, die, or 
the investigator or sponsor decides to discontinue their enrollment for any reason. Reasons for 
the investigator or sponsor terminating a participant from the study may include, but are not limited 
to, the participant becoming a threat to self or others. 
Participants may withdraw voluntarily from the study at any time. 
10.4 Study Halting Rules 
As this is not a clinical trial and no treatment involved, risk is expected to be very low. There will 
be no study halting rules. 
10.5 Follow-Up 
A follow-up assessment will be completed approximately 12 weeks post-EMA start by 
phone/video. Research staff will administer an interviewer-based assessment to measure current 
substance use, participant experience with the study devices, treatment utilization, reasons for 
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and overdose. Participants will be mailed a UDS kit and asked to collect sample and upload test 
results to REDCap. If any technical issues arise, the research staff have the ability to upload the 
photographs into REDCap for the participant.  Once the UDS results are received, participants 
will receive $100 for completing the follow up assessment.  Additionally, EHR, medical claims, 
and social media (if consented) data will be extracted/downloaded after participants complete the 
12-week active phase of the study. Additional compensation will be provided for social media data 
downloads (if consented) and returning study equipment at the end of the active study phase 
(described in Section 8.3). 
10.6 Participant Reimbursement 
Participants will be compensated for their participation in this study (incentives described in 
Section 8.3). Compensation will be in accordance with the IRB of record’s policies and 
procedures, and subject to IRB approval. Total compensation will be up to $995 for participating 
in all study activities ($75 for baseline assessment, $100 for follow up assessment and up to $820 
for engagement in digital data collection). Payments for research participation in excess of 
$600.00 in one calendar year are reportable to the Internal Revenue Service (IRS). Participants 
may be required to pay taxes on this money, as required by law, and will be asked to provide 
home address and social security number to receive study payments in excess of $600.  
 

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11.0 STUDY ASSESSMENTS 
11.1 Table of Study Assessments 
Construct 
Subdomain 
Assessment Name 
Interview (I) 
Extraction (E) 
Download (D) 
Time estimate 
(minutes) 
 
Verbal Consent 
Verbal consent 
I 
5      
Screening 
Prisoner Status 
Prisoner Status 
Assessment (Repeat 
Prisoner Status 
Follow-up at each 
study visit 
I 
2 
Study eligibility 
Inclusion/Exclusion 
Form           
I 
3      
 
 
Total Time 
~10 minutes 
     Baseline 
Prisoner Status 
Prisoner Status 
Assessment 
I 
2 
Consent/Locator 
E-Consent  
E-HIPAA 
Authorization  
Consent Quiz 
Locator Form (to be 
completed at each 
call) 
I 
30 
Demographics 
Substance Use 
PhenX Core Tier 1, 
PhenX Core Tier 2, 
NSDUH (subset of 
measures/question: 
demographics & 
current substance 
use) 
I 
25 
COVID-19 
Baseline 
Assessment 
I 
2 
DSM-5 diagnosis 
NetSCID-5 
I 
20-45      
Recent use 
Urine Drug Screen 
I 
10 
 
 
Total Time 
~85-120 minutes 

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Social Media 
Social media 
images/texts of 
postings & 
comments, 
reactions, 
date/time 
D- from social 
media platform via 
remote desktop 
At the beginning of 
the study 
 
Prisoner Status 
Prisoner Status 
Assessment 
I 
2 
Follow-up 
Substance Use 
 
PhenX Core Tier 1 
(subset of 
measures: current 
substance use) 
I 
20 
Participant 
Experience 
Employment 
Treatment 
utilization 
Insurance coverage 
Follow-up 
Assessment 
 
15 
Recent use 
Urine Drug Screen 
I 
10 
 
 
Total Time 
~60 minutes* 
Social Media 
Social media 
images/texts of 
postings & 
comments, 
reactions, 
date/time 
D- from social 
media platform via 
remote desktop 
At the end of the 
study  
Health records 
EHR 
E** 
Retroactively from 
12 weeks post-EMA 
start to 12-months 
prior to EMA start 
Health records 
Medical Claims  
E** 
Retroactively from 
12 weeks post-EMA 
start to 12-months 
prior to EMA start     
*Follow-up appointment will take approximately 45 minutes to complete assessments plus 
another ~15 minutes to instruct participants on how to return study equipment (for a total of 
approximately 60 minutes). 
**Note: EHR/Medical Claims data will be extracted by the Data Analyst approximately 16-weeks after 
completion of study and includes data 12 months prior to EMA start through 12 weeks post-EMA start. 
 
 

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11.2 Active Study Phase Digital Health Assessments 
 
 
Construct/ 
domain 
Subdomain 
 
Assessment name 
 
Wearable (W) 
Carryable (C) 
Self-report (SR) 
 
Occurrence 
Smartwatch/ 
Smartphone/ 
Self-Report 
 
Distance, physical 
activity, sleep 
Ambulatory 
Physiological 
Assessment using 
Mobile Sensors 
 
W 
Wear at least 18 
hours/day, data 
transmitted real-
time for 12 weeks 
Phone activity, 
WiFi/Bluetooth 
logs, ambient light, 
proximity, location, 
audio/conversation 
Passive Assessment 
using Mobile 
Sensors 
C 
Carry smartphone 
at least 8 
hours/day, data 
transmitted real-
time, for 12 weeks  
Ecological Factors 
Ecological 
Momentary 
Assessment (EMA)  
(including self-
report of drug use) 
SR 
Up to 3x/day for 12 
weeks 
Self-Regulation 
Momentary Self-
Regulation Scale 
12-item 
SR 
Up to 3x/day for 12 
weeks 
 
11.3 Description of Measures 
11.3.1 Prisoner Status Assessment 
Prisoner status must be assessed for each participant at each separate encounter (i.e., all study 
contacts [e.g., screening appointment, baseline appointments, and follow-up appointment], as this 
study will not apply for OHRP Prisoner Certification). Due to the high-risk nature of this population 
becoming involved in the criminal justice system, assessment is required. 
11.3.2 Inclusion/Exclusion 
This form will be used to obtain information on inclusion and exclusion criteria to document 
eligibility. Eligibility is assessed continually as appropriate. Only participants who continue to meet 
study eligibility criteria will be permitted to continue with study procedures. 
11.3.3 Locator Form 
A locator form is used to obtain information to assist in finding participants through the 12-week 
active and follow-up phase of the study. This form collects the participant’s current address, email 
address, and phone numbers. In order to facilitate locating participants if direct contact efforts are 
unsuccessful, addresses and phone numbers of family/friends who may know how to reach the 

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participant are collected. This information will be collected at baseline and will be updated at each 
contact. 
No information from this form is used in data analyses, nor is this information captured in the data 
capture system.  The locator form is stored in a secure electronic folder with other participant PHI 
data. 
11.3.4 PhenX Substance Abuse and Addiction Core Tier 1 (PhenX 
Core Tier 1) 
The PhenX Core Tier 1 is a part of the Substance Abuse and Addiction Collections 
(https://www.phenxtoolkit.org/sub-collections/view/8) that are being adopted across NIDA-funded 
research.  We are using the following subset of measures from the Core Tier 1: demographics 
(age, ethnicity, gender, race, current educational attainment, current employment status, and 
current marital status) and current substance use (tobacco, alcohol, and drugs) (Hamilton et al, 
2011).  The demographics (except for employment status) will only be collected at baseline, while 
current substance use and current employment status will be collected at baseline and follow-up. 
11.3.5 PhenX Substance Abuse and Addiction Core Tier 2 (PhenX 
Core Tier 2)/National Survey on Drug Use and Health 
(NSDUH) 
The PhenX Core Tier 2 (https://www.phenxtoolkit.org/sub-collections/view/9) is a complementary 
set of 8 measures to the PhenX Core Tier 1 (e.g., annual family income, child-reported parental 
education attainment, family history of substance use problems, household roster-relationships, 
internalizing, externalizing, and substance use disorders screener, occupation/occupational 
history, peer/partner substance use and tolerance of substance use, and social networks).  We 
will only use a subset of questions from the Annual Family Income measure to get an estimate of 
total income of all family members (Hamilton et al, 2011).  If the participant is unsure of the total 
family income, then we will use a subset of questions from the Substance Abuse and Mental 
Health Services Administration (SAMHSA)’s NSDUH survey to determine which income category 
best characterizes total combined family income (Center for Behavioral Health Statistics and 
Quality, 2017).  Income will be collected at baseline only. 
11.3.6 NetSCID-5 
The Structured Clinical Interview for DSM-5 (SCID-5) is a semi-structured interview designed to 
assess substance use and mental health diagnoses (First et al, 2015). This study will use an     
electronic version of the SCID-5, the NetSCID-5, developed by TeleSage™.  The TeleSage™ 
NetSCID-5 is fully licensed by the American Psychiatric Association and has been validated 
(Brodey, First, Linthicum, Haman, Sasiela, & Ayer, 2016). The NetSCID is HIPAA-compliant, and 
data is maintained on a secure, encrypted, and geo-redundant server. TeleSage™ has the 
capability of customizing the NetSCID-5 measure, so only modules relevant for this study will be 
selected (bipolar I disorder, major depressive disorder,  panic disorder, social anxiety disorder, 
generalized anxiety disorder, posttraumatic stress disorder, adult attention deficit hyperactivity 
disorder, alcohol use disorder, cannabis, stimulants/cocaine, opioids, PCP, other hallucinogens, 
inhalants, sedative-hypnotic-anxiolytic, and other/unknown). 
At the end of the study, all data collected on the TeleSage™ platform and stored on their server(s) 
will be securely transferred to Dartmouth’s server and expunged from TeleSage™’s server(s). 

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11.3.7 Urine Drug Screen 
Urine drug screen kits (UDS), otherwise referred to as urine toxicology, will be mailed to 
participants, and participants will be asked to collect a urine sample, record and upload results to 
study team using a secure system (e.g. REDCap). In rare cases when there are technological 
issues with uploading the photos, the participant can send photos to research staff via text to a 
research staff member’s Kaiser cell phone (which is KPIT approved).  In this case, research staff 
will upload the photographs into REDCap for the participant. All urine specimens are collected 
using CLIA-Waived and FDA-approved one-step multi-drug screen test cup following the 
manufacturer's recommended procedures. The study will use the DrugConfirm™ Advance Urine 
Drug Test Kit which screens for: alcohol, amphetamine, barbiturate, buprenorphine, 
benzodiazepine, cocaine, fentanyl, MDMA [ecstasy/molly], methamphetamine, methadone, 
morphine 300 ng/mL, oxycodone, phencyclidine (PCP), tramadol and THC.                                  
11.4 Follow-up 
11.4.1 Follow-up Assessment 
The follow-up assessment will collect the following: current substance use (e.g., tobacco, alcohol, 
opioids, and other drugs), current employment status, participant experience with the study 
devices (including wearing the smartwatch, carrying the smartphone, and responding to EMAs), 
treatment utilization, reasons for drop out (if appropriate), insurance coverage, medication 
use/dose (if applicable), and overdose. 
11.5 Digital Health Technology 
11.5.1 Ambulatory Physiological Assessment using Mobile Sensors 
We will develop a smartphone application, that can sense and store contextual information about 
a participant, e.g., location, physical activity (steps), phone activity (non-identified audio 
information such as segments of silence, speech features such as pitch control and voice quality), 
app usage, call/text, screen on/off, phone lock/unlock, sleep, ambient light, and proximity (e.g., to 
user’s ear). Features will be derived from the raw sensing streams to create multiple relevant 
contextual variables. This application will be installed directly on the study provided smartphone 
(Moto G7 Power) or on a participant’s smartphone (if they have a compatible phone). The data 
collected will be stored on the smartphone and will be securely transmitted to a secure cloud-
based database hosted at Dartmouth.  
In addition to the smartphone, the participants will be provided with a smartwatch (Garmin 
Vivosmart 4). The participants will be asked to wear the smartwatch continuously (except during 
pre-determined exceptions periods, such as when the participants are showering or charging the 
device). In our experience, the Garmin Vivosmart 4 smartwatch (among others) is 
comfortable, lightweight, and has a long battery life and an easy-to-use interface. The device can 
reliably track distance traveled, physical activity (including metrics of energy expenditure and step 
count), sleep stages, as well as heart rate. Data from the Garmin smartwatch includes raw sensor 
data, like, heart-rate, and several high-level features computed by Garmin (using their 
proprietary algorithms including; sleep stage information, periods of light/deep sleep, stress 
levels, and others). This data will be transmitted to the Garmin Connect application installed on 
the smartphone, which would in turn send the data to Garmin cloud servers. Garmin will provide 
us with access keys for the research staff to pull the data from the Garmin servers to the cloud-
based database at Dartmouth College. 

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11.5.2 Ecological Momentary Assessment (EMA) 
Participants will be prompted up to 3 times per day over 12 weeks by the smartphone app to self-
report sleep, stress, pain severity, pain interference, pain catastrophizing, craving, withdrawal, 
substance use risk context, mood, context, substance use, self-regulation, MOUD adherence, 
and the impact of COVID-19 (Buysse, Reynolds, Monk, Berman, & Kupfer, 1989; Freeman & 
Gottfredson, 2018; Kuerbis et al., 2019; Preston et al., 2017, 2018). The EMA prompt delivery 
times will be randomized within each of the prompt timeframes (e.g., morning, mid-day, end of 
day). In addition to prompted EMAs, participants will be asked to self-initiate EMAs if substance 
use occurred (e.g., opioids, cocaine, or other stimulants).  All EMA data collected via the 
smartphone will be securely transmitted to a secure cloud-based database housed in the 
Research Computing Department at Dartmouth College. 
11.5.3 Momentary Self-Regulation Scale 
This brief 12-item questionnaire assesses self-regulation on a momentary basis as individuals 
move through their lives (S. J. Kim et al., Under Review). This information will be collected up to 
3 times daily over the 12-week study period by smartphone. All data collected via the smartphone 
will be securely transmitted to a secure cloud-based database housed in the Research Computing 
Department at Dartmouth College. 
11.5.4 Social Media 
Participants will be asked to download their social media data to a secure server using a remote 
desktop application. Images/texts of postings and comments as well as date/time and the 
number of reaction responses (e.g., Like, Sad, Angry) per posting and per comment will be 
extracted from the downloaded social media data through postprocessing for analysis. The 
download will occur at the beginning of the study and also at the end of the study. If participants 
have difficulty downloading the social media data, the research staff can provide 
guidance/instructions on how to download social media data and if needed can walk through the 
download process with the participant via phone or video.  Should a technical issue arise that 
the research staff cannot resolve, research staff may need to contact technical support 
personnel at Dartmouth using a 3-way or conference call to assist with troubleshooting technical 
issues.  All social media data will be securely stored on an encrypted server at the Williamson 
Translational Research Building in the Biomedical Data Science Department at Dartmouth 
College. 
11.6 Other Measures 
11.6.1 Electronic Health Records (EHR)       
EHR data extraction will include all outpatient and inpatient encounters, medications 
(buprenorphine and others*), procedures, and diagnoses for the 12 months prior to EMA start and 
the 12-week study period. In addition, we will extract lab results from urine drug screens, patient 
demographic information, and insurance deductible level. We will extract appointment data to 
determine if visits were cancelled or missed. We will examine membership data to determine if 
the patient’s membership became inactive in the study period. KPNC is an integrated healthcare 
delivery system, and the KPNC EHR includes both services provided inhouse and services 
obtained outside of KPNC, so long as the non-KPNC services were submitted as medical claims 
for reimbursement. 

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*Prescription data for opioids other than buprenorphine will be limited to patient-level dichotomous 
variables (yes/no) reflecting whether any non-buprenorphine opioid was ordered or dispensed 
during the time period. 
11.7 Clinical and Safety Assessments 
11.7.1 Safety Events 
Safety events may be elicited at baseline or spontaneously reported to study staff at any visit 
following consent. Safety events suggesting medical or psychiatric deterioration will be brought 
to the attention of the Study Clinician for further evaluation and management. Safety events 
reporting are according to the reporting definitions and procedures outlined in the protocol and in 
accordance with applicable regulatory requirements. See Appendix A for details. 

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12.0 TRAINING REQUIREMENTS 
12.1 Overall 
A comprehensive Training Plan will be developed to incorporate general training, study-specific 
training, mechanisms for competency assessment as well as a detailed description of training, 
supervision, and fidelity monitoring procedures. The Investigative Team is responsible for the 
development of a comprehensive Training Plan, instructional material, and delivery of the training, 
with the team comprised of the Lead Node and other participating Nodes, and subject matter 
experts, as applicable. The Northeast Node is the Lead Node.  
The CTN-0084-A2 study staff will be trained as specified in the study Training Plan. Training will 
include Human Subjects Protection (HSP) and Good Clinical Practice (GCP) as well as protocol-
specific training on assessments, study interventions, safety and safety event reporting, study 
procedures, data management, quality assurance, laboratory procedures, etc. The Lead Node 
and Local Node are responsible for development and delivery of study-specific training related to 
the study intervention(s) and procedures including data management, as well as, non-intervention 
training (e.g., regulatory and laboratory procedures, safety and safety event reporting, quality 
assurance and monitoring, etc.). Other parties will contribute as needed based on the subject 
matter and material to be covered. The various sub-teams will collaborate to deliver quality 
instructional material designed to prepare research staff to fully perform study procedures based 
on the assigned research roles and responsibilities. 
In addition to general and study-specific training, the Training Plan will include a description of 
the delivery methods to be used for each training module (e.g., via self-study, online, webcast, or 
teleconference). Study staff is required to complete institutionally required training per their 
research site, Institutional Review Board(s), and authorities with regulatory oversight. Tracking of 
training completion for individual staff as prescribed for assigned study role(s) will be documented, 
endorsed by the Lead Node. As changes occur in the prescribed training, the Training Plan and 
training documentation tracking forms will be amended to reflect these adjustments. 

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13.0 CONCOMITANT THERAPY/INTERVENTION 
13.1 General 
Not applicable for this study. 
13.2 Medications Prohibited/Allowed During Trial 
There will be no medications prohibited during the trial. Based on what we know about the 
population at the study site, participants will be receiving buprenorphine medications for 
substance use; psychiatric medications; and, medications for physical/medical ailments, in 
addition to behavioral treatments. 

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14.0 STATISTICAL DESIGN AND ANALYSES  
14.1 General Design 
14.1.1 Study Hypothesis 
Feasibility of digital health technologies: The collection of intensive longitudinal data requires 
participants to adhere to wearing and carrying a smartwatch and smartphone, respectively, 
consistently throughout the study. Participants are also expected to respond to assessment 
questions up to 3 times a day and self-initiate EMA if substance use occurred, on every day of 
the 12-week study. We hypothesize that the financial incentives provided to participants will 
adequately incentivize these adherence behaviors.  
Understanding behaviors of patients in treatment: We hypothesize that, intensive longitudinal data 
capturing of patient context and psychological state (via EMA) will be useful for predicting 
treatment retention, and buprenorphine medication adherence. 
14.1.2 Primary and Secondary Outcomes (Endpoints) 
The primary outcomes will include: (1) the percentage of days during the 12-week active phase 
enrolled participants wore/carried the smartwatch and smartphone; (2) response rate to EMA 
prompts during the 12-week phase; and (3) the percentage of participants who consent to social 
media data download and sparsity of social media data per participant. 
The secondary outcome measures will be: (1) OUD treatment retention (days retained in OUD 
treatment program) based on EHR data; (2) Days covered on MOUD based on EHR and EMA 
data; and (3) Non-prescribed opioid use based on EHR and EMA data. 
14.1.3 Recruitment 
Participants will be recruited from Kaiser Permanente Northern California patients who have been 
treated at the KPNC AMRS programs for OUD.  
14.1.4 Randomization and Factors for Stratification 
Does not apply to this study. 
14.2 Rationale for Sample Size and Statistical Power  
14.2.1 Projected Number of Sites 
We plan to recruit from Kaiser Permanente in Northern California (KPNC). 
14.2.2 Projected Number of Participants per Site 
Approximately 50 (if recruitment is faster than anticipated, we will recruit up to 75) participants are 
projected to be recruited from KPNC. 
14.3 Statistical Methods for Primary and Secondary Outcomes  
For our primary and secondary outcomes, we intend to use measures such as precision, recall 
(sensitivity) and specificity, F-score, to assess the quality of our predictions. The quality of the 

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identified digital phenotypes will be evaluated using cohesion (e.g., Silhouette score) and 
endpoint-differentiating power (e.g., Z-score). 
14.4 Significance Testing 
The primary outcome will be evaluated using a two-sided test with a type I error rate of 5%. There 
are several secondary outcomes; however, multiple comparisons will not be adjusted for since 
these are not part of the study’s primary objective as an observational study. 
14.5 Types of Analyses  
We are interested in measuring and predicting outcomes that may occur repeatedly over a 12-
week observational period (e.g., patterns of daily drug use) using digital health technology. In 
digital health (Jain et al., 2015a) the spatio-temporal granularity of information about an individual 
is of higher resolution than that obtained through cross-sectional or traditional longitudinal studies. 
We will therefore assess the utility of using data from smartphones, smartwatches, social media 
and ecological momentary assessment to predict, explain and detect these outcomes.  
Predicting outcomes using passively and actively collected digital health and social media data: 
Our approach to prediction will include regression-based methods (e.g., logistic regression), but 
we will also use common machine learning approaches for binary classification (e.g., random 
forest, support vector machines, K-means, gradient boosting). For each of these classification 
techniques, we will assess the utility of the various digital data for improving prediction quality. 
Typical evaluation methods used to assess the prediction quality include accuracy, precision, F-
score, sensitivity (recall), and specificity. The relative utility of the various data for predicting 
outcomes will be assessed at two levels - individual features level and aggregated feature level. 
Interpretability of each feature and its contribution in predicting the outcome variable will be 
assessed using an ensemble framework, SHAP (Lundberg & Lee, 2017). In addition, we will also 
assess mutual information (Kraskov, Stogbauer, & Grassberger, 2004), which is a non-parametric 
approach of estimating the dependency between individual features and the target outcome. In 
another approach, features will be aggregated based on their gross categories (e.g., Facebook, 
Twitter, GPS, step, sleep, mood). The relative importance of each category will be evaluated 
based on its performance in predicting outcome (e.g., F-score). 
1. Explaining temporal-causal relationships between factors determined to be useful for 
predicting outcomes: Although machine learning methods may often be more effective 
for prediction than simple regression or correlation, they may be difficult to explain, or 
may not reveal insights regarding the relationships between factors. Therefore, we also 
include a set of analyses that are conducive to generating such explanatory or 
descriptive insights. For example, we will apply supervised metric learning and 
prototypical case-based reasoning (Hsueh et al., 2018), topic-modeling (e.g., Latent 
Dirichlet Allocation) and causal inference methods (Cheng, Bahadori, & Liu, 2014; 
Kleinberg & Hripcsak, 2011).  
2. Outcome detection using passively collected digital health data: We plan to measure 
drug use and medication non-adherence events via EMA, multiple times a day. Since 
EMA requires a level of active engagement from participants that may not be realistic to 
expect outside of a research study, we plan to use machine learning to detect these 
events using only passively collected data. The methods used here would be similar to 
the machine learning methods previously described for binary classification. 
3. Feasibility of digital health technology: We will generate descriptive statistical summaries 
of the level of adherence of study participants to the desired protocol (e.g., EMA 
response rate, smartwatch and smartphone wear/carry rate). No statistical inference is 
planned for this assessment. 

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14.6 Interim Analysis 
No planned interim analyses. 
14.7 Exploratory Analysis 
See Extended Data Analytic Plan for more details. 
14.8 Missing Data and Dropouts 
Missing data will be classified into three classes according to the characteristics of the 
randomness: missing not at random (MNAR), missing at random (MAR), and missing completely 
at random (MCAR). Little’s MCAR test will be applied to identify if the characteristics of the missing 
variable are (Little, 1988). For the other two types, we will make use of the tests for interactions 
between observed variables. If a significant interaction exists, that will be treated as MNAR data. 
Missing samples will be imputed using previously suggested well-known approaches suitable for 
the category of the missing variable (Sarker, Tyburski, Rahman, et al., 2016). 
14.9 Demographic and Baseline Characteristics  
Descriptive summaries of the distribution of continuous baseline variables will be presented with 
percentiles (median, 25th and 75th percentiles), and with mean and standard deviation. 
Categorical variables will be summarized in terms of frequencies and percentages. 
14.10 Safety Analysis  
Not applicable, as no treatment/intervention is being provided for this study. 

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15.0 REGULATORY COMPLIANCE, REPORTING and MONITORING 
15.1 Statement of Compliance 
This study will be conducted in accordance with the current version of the protocol, in full 
conformity with the ethical principles outlined in the Declaration of Helsinki, the Protection of 
Human Subjects described in the International Council for Harmonization Good Clinical Practice 
(GCP) Guidelines, applicable United States (US) Code of Federal Regulations (CFR), the NIDA 
Terms and Conditions of Award, and all other applicable state, local, and federal regulatory 
requirements. The Principal Investigators will assure that no deviation from, or changes to the 
protocol will take place without prior agreement from the Sponsor and documented approval from 
the Institutional Review Board (IRB), except where necessary to eliminate an immediate hazard(s) 
to the trial participants. An Operations Manual will be provided as a reference guide and study 
quality assurance tool. 
15.2 Institutional Review Board Approval  
Prior to initiating the study, participating site investigators will obtain written approval from the 
Ethics Review Committee (ERC) or Institutional Review Board (IRB) to conduct the study at their 
respective site, which will include approval of the study protocol. If changes to the study protocol 
become necessary, protocol amendments will be submitted in writing by the investigators for IRB 
approval prior to implementation. In addition, IRBs will approve all consent forms, recruitment 
materials, and any materials given to the participant, and any changes made to these documents 
throughout study implementation. Approval of both the protocol and the consent form(s) must be 
obtained before any participant is consented. For changes to the consent form, a decision will be 
made regarding whether previously consented participants need to be re-consented. IRB 
continuing review will be performed annually, or at a greater frequency contingent upon the 
complexity and risk of the study. Each Site Principal Investigator is responsible for maintaining 
copies of all current IRB approval notices, IRB-approved consent documents, and approval for all 
protocol modifications. These materials must be received by the investigator prior to the initiation 
of research activities at the site and must be available at any time for audit. Unanticipated 
problems (UP) involving risk to study participants will be promptly reported to and reviewed by 
the IRB of record, according to its usual procedures. 
The Kaiser Permanente Northern California Institutional Review Board will be the single IRB of 
record for the protocol and will provide study oversight in accordance with 45 CFR 46. 
Participating institutions will agree to rely on Kaiser IRB and will enter into reliance/authorization 
agreements for Protocol CTN-0084-A2. Kaiser IRB will follow written procedures for reporting its 
findings and actions to appropriate officials at each participating institution. 
15.3 Informed Consent  
The informed consent process is a means of providing study information to each prospective 
participant and allows for an informed decision about participation in the study. Informed consent 
continues throughout the individual’s study participation. The informed consent form will include 
all of the required elements of informed consent and may contain additional relevant consent 
elements and NIDA CCTN specific additional elements. Each study site must have the study 
informed consent approved by Kaiser IRB. Prior to initial submission to the IRB and with each 
subsequent consent revision, the consent form must be sent to the Lead Node to confirm that 
each consent form contains the required elements of informed consent as delineated in 21 CFR 
50.25(a) and CFR 46.116(b), as well as pertinent additional elements detailed in 21 CFR 50.25(b) 
and 45 CFR 46.116(c) and any applicable CCTN requirements. Every study participant is required 
to sign a valid, IRB-approved current version of the study informed consent form prior to the 

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initiation of any study related procedures. The site must maintain the electronically signed 
informed consent for every participant on a secure server located at Kaiser that is in compliance 
with all applicable IRB and institutional policies and that is accessible to the study monitors. Every 
study participant should be given a copy of the signed consent form.  
During the informed consent process, research staff will explain the study to the potential 
participant by phone/video and provide the potential participant with a copy of the consent form 
to read and keep for reference. All participants will receive a verbal explanation in terms suited to 
their comprehension of the purposes, procedures, and potential risks of the study and their rights 
as research participants. Extensive discussion of risks and possible benefits will be provided to 
the participants. Participants will have the opportunity to carefully review the consent form and 
ask questions prior to signing. The participants should have the opportunity to discuss the study 
with their family and close friends or think about it prior to agreeing to participate. If the participant 
is interested in participating in the study, a qualified staff member will review each section of the 
IRB-approved informed consent form in detail and answer any questions the participant may 
pose. The participant will consent by providing an electronic date and signature. The person 
obtaining consent and a witness, if required by the IRB of record, will also electronically sign and 
date the consent document. It is strongly recommended that another research staff member 
review the consent after it is signed to ensure that the consent is properly executed and complete. 
Staff members delegated by the PI to obtain informed consent must be listed on the Delegation 
of Responsibility and Staff Signature Log and must be approved by the IRB, if required. All 
persons obtaining consent must have completed appropriate GCP and Human Subjects 
Protection training, as mandated by NIDA standard operating procedures. 
The informed consent form must be updated or revised whenever important new safety 
information is available, or whenever the protocol is amended in a way that may affect participants’ 
participation in the trial. The rights and welfare of the participants will be protected by emphasizing 
to them that the quality of their medical care will not be adversely affected if they decline to 
participate in this study. The participant will be informed that their participation is voluntary, and 
they may withdraw from the study at any time, for any reason without penalty. Individuals who 
refuse to participate or who withdraw from the study will be treated without prejudice. The study 
site will be responsible for maintaining electronically signed consent forms as source documents 
for quality assurance review and regulatory compliance. 
15.4 Quality Assurance Monitoring  
In accordance with federal regulations, the study sponsor is responsible for ensuring proper 
monitoring of an investigation and ensuring that the investigation is conducted in accordance with 
the protocol. Qualified monitors will oversee aspects of site conformity to make certain the site 
staff is operating within the confines of the protocol, and in accordance with GCP. This includes 
but is not limited to protocol compliance, documentation auditing, and ensuring the informed 
consent process is being correctly followed and documented. Non-conformity with protocol and 
federal regulations will be reported as a protocol deviation and submitted to the study sponsor 
and study IRB of record (as applicable) for further review. 
15.5 Participant and Data Confidentiality  
Participant confidentiality and privacy are strictly held in trust by the participating investigators, 
their staff, the safety and oversight monitor(s), and the sponsor(s) and funding agency, and will 
be maintained in accordance with all applicable federal regulations and/or state/Commonwealth 
law and regulations. This confidentiality is extended to the data being collected as part of this 
study. Data that could be used to identify a specific study participant will be held in strict 
confidence within the research team. No personally-identifiable information from the study will be 

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released to any unauthorized third party without prior written approval of the sponsor/funding 
agency or the participant.  
All research activities will be conducted in as private a setting as possible.  
The study monitor, other authorized representatives of the sponsor or funding agency, 
representatives of the Institutional Review Board (IRB), regulatory agencies or representatives 
from companies or organizations supplying the product, may inspect all documents and records 
required to be maintained by the investigator, including but not limited to, medical records (office, 
clinic, or hospital) and pharmacy records for the participants in this study. The clinical study site 
will permit access to such records. 
Participant records will be held confidential by the use of study codes for identifying participants 
on CRFs, secure storage of any documents that have participant identifiers, and secure 
computing procedures for entering and transferring electronic data. The study participant’s 
contact information will be securely stored for internal use during the study. At the end of the 
study, all records will continue to be kept in a secure location for as long a period as denoted in 
Section 15.11.  
By signing the protocol signature page, the investigator affirms that information furnished to the 
investigator by NIDA will be maintained in confidence and such information will be divulged to the 
IRB/Privacy Board, Ethical Review Committee, or similar expert committee; affiliated institution; 
and employees only under an appropriate understanding of confidentiality with such board or 
committee, affiliated institution and employees.  
15.5.1 Certificate of Confidentiality 
To further protect the privacy of study participants, the Secretary, Health and Human Services 
(HHS), has issued a Certificate of Confidentiality (CoC) to all researchers engaged in biomedical, 
behavioral, clinical or other human subjects research funded wholly or in part by the federal 
government. Recipients of NIH funding for human subjects research are required to protect 
identifiable research information from forced disclosure per the terms of the NIH Policy (see 
https://humansubjects.nih.gov/coc/index). This protects participants from disclosure of sensitive 
information (e.g., drug use). It is the NIH policy that investigators and others who have access to 
research records will not disclose identifying information except when the participant consents or 
in certain instances when federal, state, or local law or regulation requires disclosure. NIH expects 
investigators to inform research participants of the protections and the limits to protections 
provided by a Certificate issued by this Policy. 
15.5.2 Health Insurance Portability and Accountability Act (HIPAA) 
The study site may be required by their institutions to obtain authorization from participants for 
use of protected health information. The site will be responsible for communicating with Kaiser 
IRB and obtaining the appropriate approvals or waivers to be in regulatory compliance. Releases 
of participant identifying information that are permitted by the HIPAA regulations, but which are 
prohibited by other applicable federal regulations and/or state/Commonwealth law and regulation, 
are prohibited.  
15.6 Investigator Assurances 
The site must have on file a Federalwide Assurance (FWA) with the HHS Office for Human 
Research Protection setting forth the commitment of the organization to establish appropriate 
policies and procedures for the protection of human research subjects in alignment with 45 CFR 

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46, Subpart A, with documentation sent to NIDA or its designee. Research covered by these 
regulations cannot proceed in any manner prior to NIDA receipt of certification that the research 
has been reviewed and approved by the IRB provided for in the assurance (45 CFR 46.103). Prior 
to initiating the study, the principal investigator at the study site will sign a protocol signature page 
and investigator agreement, providing assurances that the study will be performed according to 
the standards stipulated therein. 
15.6.1 Financial Disclosure/Conflict of Interest  
All investigators will comply with the requirements of 42 CFR Part 50, Subpart F to ensure that 
the design, conduct, and reporting of the research will not be biased by any conflicting financial 
interest. Everyone with decision-making responsibilities regarding the protocol will confirm to the 
sponsor annually that they have met their institutional financial disclosure requirements. 
15.7 Clinical Monitoring 
Qualified node personnel (Node QA monitors) or another designated party will provide site 
management for each site during the trial. Node QA staff or other designated party(ies) will audit 
source documentation, including electronic case report forms (eCRFs), informed consent forms 
and HIPAA forms. Node QA monitors will examine whether study procedures are conducted 
appropriately, and that the study data are generated, documented and reported in compliance 
with the protocol, GCP, and applicable regulations. This will take place as specified by the local 
protocol team, node PI(s) or Lead Node and will occur as often as needed to help prevent, detect, 
and correct problems at the study site. Node QA personnel will verify that study procedures are 
properly followed and that site personnel are trained and able to conduct the protocol 
appropriately. If the node personnel’s review of study documentation indicates that additional 
training of site study personnel is needed, node QA personnel will undertake or arrange for that 
training. Reports will be prepared following the site visit (may be conducted remotely as 
appropriate) and sent to the Lead Team, Node Principal Investigator(s), and site Principal 
Investigator. Details of the node QA, and data monitoring are found in Module 10 of the study 
Manual of Operating Procedures. 
15.8 Inclusion of Women and Minorities  
The study site will aim and take steps to enroll a diverse study population. We are targeting 
approximately 50% female and 40% minority. If difficulty is encountered in recruiting an adequate 
number of women and/or minorities, the difficulties involved in recruitment will be discussed in 
national conference calls and/or face-to-face meetings, encouraging such strategies as linkages 
with medical sites and or treatment programs that serve a large number of women and/or 
minorities, advertising in newspapers or radio stations with a high female/minority 
readership/listening audience, etc. 
15.9 Prisoner Certification 
As per 45 CFR 46 Subpart C, there are additional protections pertaining to prisoners as study 
participants. A prisoner is defined as any individual involuntarily confined or detained in a penal 
institution. The term is intended to encompass individuals sentenced to such an institution under 
a criminal or civil statute, individuals detained in other facilities by virtue of statutes or commitment 
procedures which provide alternatives to criminal prosecution or incarceration in a penal 
institution, and individuals detained pending arraignment, trial, or sentencing. 
If a participant in the study becomes incarcerated or otherwise meets the 45 CFR 46 Part C 
definition of a prisoner during the course of the study, and the relevant research proposal was not 
reviewed and approved by the Kaiser IRB in accordance with the requirements for research 

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involving prisoners under Subpart C of 45 CFR 46, the investigator must promptly notify the Kaiser 
IRB. All research interactions and interventions with, and obtaining identifiable private information 
about, the participant must be suspended immediately. 
15.10 Regulatory Files 
The regulatory files will contain all required regulatory documents, study-specific documents, and 
important communications. Regulatory files will be checked at the participating site for regulatory 
document compliance prior to study initiation, throughout the study, as well as at study closure. 
15.11 Records Retention and Requirements  
Research records for all study participants (e.g., electronic case report forms, source documents, 
signed consent forms, and regulatory files) are to be maintained by the investigator in a secure 
location for a minimum of 3 years after the study is completed and closed. These records are also 
to be maintained in compliance with IRB, state and federal requirements, whichever is longest. 
The Sponsor and Lead Investigator must be notified in writing and acknowledgment from these 
parties must be received by the site prior to the destruction or relocation of research records. 
15.12 Reporting to Sponsor 
The Site Principal Investigator agrees to submit accurate, complete, legible and timely reports to 
the Sponsor, as required. These include, but are not limited to, reports of any changes that 
significantly affect the conduct or outcome of the trial or increase risk to study participants. Safety 
reporting will occur as previously described. At the completion of the trial, the Lead Investigator 
will provide a final report to the Sponsor. 
15.13 Audits 
The Sponsor has an obligation to ensure that this trial is conducted according to good clinical 
research practice guidelines and may perform quality assurance audits for protocol compliance. 
The Lead Investigators and authorized staff from the Health Systems and Northeast Nodes; the 
National Institute on Drug Abuse Clinical Trials Network (NIDA CTN, the study sponsor); NIDA’s 
contracted agents, monitors or auditors; and other agencies such as the Department of Health 
and Human Services (HHS), the Office for Human Research Protection (OHRP) and the 
Institutional Review Board of record may inspect research records for verification of data, 
compliance with federal guidelines on human participant research, and to assess participant 
safety. 
15.14 Study Documentation 
The participating site will maintain appropriate study documentation (including medical and 
research records) for this trial, in compliance with ICH E6 R2 and regulatory and institutional 
requirements for the protection of confidentiality of participants. Study documentation includes all 
case report forms, workbooks, source documents, monitoring logs and appointment schedules, 
sponsor-investigator correspondence, and signed protocol and amendments, Ethics Review 
Committee or Institutional Review Board correspondence and approved consent form and signed 
participant consent forms. As part of participating in a NIDA-sponsored study, the site will permit 
authorized representatives from NIDA and regulatory agencies to examine (and when permitted 
by law, to copy) clinical records for the purposes of quality assurance reviews, audits, and 
evaluation of the study safety, progress, and data validity.  
Source documents include all recordings of observations or notations of clinical activities and any 
reports and records necessary for the evaluation and reconstruction of the clinical research study. 
Whenever possible, the original recording of an observation should be retained as the source 

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document; however, a photocopy is acceptable provided that it is a clear, legible, and exact 
duplication of the original document. 
15.15 Protocol Deviations 
This protocol defines a protocol deviation as any noncompliance with the clinical trial protocol. 
The noncompliance may be either on the part of the participant, the investigator, or the study site 
staff. As a result of deviations, corrective actions will be developed by the site and implemented 
promptly.  
These practices are consistent with ICH GCP: 
● Section 4.5 Compliance with Protocol, subsections 4.5.1, 4.5.2, and 4.5.3 
● Section 5.1 Quality Assurance and Quality Control, subsection 5.1.1 
● Section 5.20 Noncompliance, subsections 5.20.1, and 5.20.2. 
Any departure from procedures and requirements outlined in the protocol will be classified as 
either a major or minor protocol deviation. The difference between a major and minor protocol 
deviation has to do with the seriousness of the event and the corrective action required. A minor 
protocol deviation is considered an action (or inaction) that by itself is not likely to affect the 
scientific soundness of the investigation or seriously affect the safety, rights, or welfare of a study 
participant. Major protocol deviations are departures that may compromise the participant safety, 
participant rights, inclusion/exclusion criteria or the integrity of study data and could be cause for 
corrective actions if not rectified or prevented from re-occurrence. The site will be responsible for 
developing corrective action plans for both major and minor deviations as appropriate. Those 
corrective action plans may be reviewed/approved by the Lead Node and Kaiser IRB as needed. 
All protocol deviations will be monitored at the site for (1) significance, (2) frequency, and (3) 
impact on the study objectives, to ensure that site performance does not compromise the integrity 
of the trial. 
All protocol deviations will be recorded. The Lead Investigators must be contacted immediately if 
an unqualified or ineligible participant is randomized into the study. 
Additionally, the site is responsible for reviewing the IRB of record’s definition of a protocol 
deviation or violation and understanding which events need to be reported. The site must 
recognize that the CTN and IRB definition of a reportable event may differ and act accordingly in 
following all reporting requirements for both entities. 
15.16 Safety Monitoring 
The Lead Investigators (LI) may appoint a Study Clinician (PhD, PsyD) for this study, who will 
review or provide consultation for each reportable safety event as needed. These reviews will 
include an assessment of the possible relatedness of the event to the study intervention or other 
study procedures. The Study Clinician will also provide advice for decisions to exclude, refer, or 
withdraw participants as required. The Lead Investigators, along with input from the Study 
Clinicians, will determine which safety events require expedited reporting to NIDA and regulatory 
authorities. All events that are serious, related and unexpected, or that place subjects at greater 
risk of harm will be promptly reported to Kaiser IRB (IRB of Record), as outlined in KPNC IRB 
guidance (policy # N-CRSP HRP 071). The study staff will be trained to monitor for and report 
Safety Events.  See local SOP safety plan for more details.  

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15.16.1 Data and Safety Monitoring Board (DSMB) 
As this is a minimal risk study and no safety analysis will be performed (and no events are 
anticipated), an independent CTN DSMB will not be convened for this study. Instead, a Protocol 
Review Board (PRB) approved the protocol prior to implementation (January 21, 2020). As no 
data are being collected by the Data and Statistics Center (DSC), no annual review of 
accumulating data will occur. In the unlikely event that a safety issue arises, the safety events 
that are specified for reporting to Kaiser IRB will be reported following KPNC IRB’s reporting 
policies. 
15.16.2 Safety Monitor/Medical Monitor 
Detailed Safety Monitoring will not occur via the Lead Node, due to the minimal risk nature of this 
study. Kaiser IRB will be responsible for reviewing all safety events reported, should there be any. 
All safety events that occur will be reviewed by the study team on an approximately weekly basis 
as part of the study operations meeting to observe trends or unusual events. Although not 
anticipated, if a death occurs it will be reviewed immediately. Procedures will be developed to 
identify notification paths to the Lead Investigators, sponsor, and all study team members. Safety 
events will be reported to Kaiser IRB in accordance with their reporting policies. 
The Lead Investigators will in turn report safety events to the sponsor on an as needed basis (at 
least annually). 
15.16.3 Safety Events 
Standard definitions for safety events, their identification, and relationship to study and processing 
are described in Appendix A. 
Safety events may be elicited at baseline or spontaneously reported by the study participants at 
any time during participation in the study. 
We will only collect safety events related to suicidal ideation and death. 
The Study Clinician will review each safety event as it occurs, and details will be recorded in a 
secure database.  Safety events requiring reporting to the Kaiser IRB will be completed in 
accordance with Kaiser IRB’s policies and procedures.  Any death occurring during the study or 
comes to the attention of the study staff during the protocol-defined follow-up period will be 
reviewed with the Study Clinician and Principal Investigator(s) and will be reported to the Kaiser 
IRB promptly if unanticipated and possibly related to the study or otherwise at time of annual 
review (See Appendix A for more details). 
The NIDA Program Officer must be informed of any death occurring during the study or comes to 
the attention of the study staff during the protocol-defined follow-up period.  This report is made 
to NIDA regardless of whether the death was study related or unanticipated. 
 

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16.0 DATA MANAGEMENT 
16.1 Design and Development 
Screening, baseline, and follow-up assessments will be collected via REDCap and stored on 
Dartmouth College’s secure servers.  REDCap is a widely used, secure platform for administering 
assessments in clinical trials. The Lead Node will be responsible for programming all the 
assessments, the development and validation of study database, and ensuring data integrity and 
security.  Since many of the proposed assessments are already developed for use in REDCap, 
programming time should be minimal.  The Structured Clinical Interview for DSM-5 (SCID-5) will 
be collected via TeleSage™’s electronic version called the NetSCID-5, which is fully licensed by 
the American Psychiatric Association.  The NetSCID has been validated (Brodey, First, Linthicum, 
Haman, Sasiela, & Ayer, 2016). The NetSCID is HIPAA-compliant, and data is maintained on a 
secure, encrypted, and geo-redundant server.  At the end of the study, all data collected on the 
TeleSage™ platform and stored on their server(s) will be securely transferred to Dartmouth’s 
server and expunged from TeleSage™’s server(s).  TeleSage™ has the capability to allow for 
customization only modules relevant for this study will be selected, programming time should be 
minimal. 
The digital health technologies data will be collected by self-report EMAs via smartphone, 
smartwatch and smartphone sensors, and by social media (for those who consent). Data collected 
via smartphone and smartwatch (sensor and EMAs) will be encrypted and securely transferred to 
a secure database housed at the Research Computing Department at Dartmouth College. Social 
media data will be downloaded by the participant directly from the social media platform to a 
secure server using a remote desktop at the beginning of the study and at the end of the study. 
All social media data will be securely stored on an encrypted server at the Williamson 
Translational Research Building in the Biomedical Data Science Department at Dartmouth 
College. The EHR and medical claims data will be encrypted and securely transferred to a secure 
database housed at the Geisel School of Medicine at Dartmouth. 
The data management responsibilities of the site will be specified by the Lead Node and outlined 
in the Data Management section of the MOP. 
16.2 Data Center Responsibilities 
The Lead Node will 1) develop a data management plan and will conduct data management 
activities in accordance with that plan, 2) provide final guided source documents and eCRFs 
(guided source documents for Screening, Baseline, and Follow-up only; eCRFs for all 
assessments) for the collection of all data required by the study, 3) develop data dictionaries for 
each eCRF and EMA that will comprehensively define each data element, 4) conduct ongoing 
data monitoring activities on study data from the site, 5) monitor any preliminary analysis data 
cleaning activities as needed, and 6) rigorously monitor final study data cleaning. 
16.3 Data Collection 
The data collection process for screening, baseline, and follow-up assessments consists of direct 
data entry at the study site into the REDCap application or TeleSage™’s electronic version of the 
SCID-5 (NetSCID-5) (collected at baseline only). In the unlikely event that REDCap or NetSCID-
5 is not available, the site will reschedule the study appointment to a time when the electronic 
systems are available. Data entry into the REDCap system should be completed according to the 
instructions provided and project specific training. The investigator is responsible for maintaining 
accurate, complete and up-to-date records, and for ensuring the completion of the eCRFs for 
each research participant.  

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Digital health data will be collected by self-report EMAs via smartphone, smartwatch and 
smartphone sensors, and by social media (for those who consent). Data collected via smartphone 
and smartwatch (sensor and EMAs) will be encrypted and securely transferred to a secure 
database housed at the Research Computing Department at Dartmouth College. Social media 
data will be downloaded by the participant directly from the social media platform to a secure 
server using a remote desktop at the beginning of the study and at the end of the study. All social 
media data will be securely stored on an encrypted server at the Williamson Translational 
Research Building in the Biomedical Data Science Department at Dartmouth College. The EHR 
and medical claims data (limited data set) will be encrypted and securely transferred to a secure 
database house at the Geisel School of Medicine at Dartmouth. 
16.4 Data Acquisition and Entry 
For screening, baseline, and follow-up assessments, electronic data will be directly entered into 
REDCap by the research staff. The data is written to a file on the REDCap secure web server or 
TeleSage™ NetSCID-5 server, and data can only be accessed by logging in with a REDCap 
account or TeleSage™ NetSCID-5 account.  
Digital health data will be collected by self-report EMAs via smartphone, smartwatch and 
smartphone sensors, and by social media (for those who consent). Data collected via smartphone 
and smartwatch (sensor and EMAs) will be encrypted and securely transferred to a secure 
database housed at the Research Computing Department at Dartmouth College. Social media 
data will be downloaded by the participant directly from the social media platform to a secure 
server using a remote desktop at the beginning of the study and at the end of the study. All social 
media data will be securely stored on an encrypted server at the Williamson Translational 
Research Building in the Biomedical Data Science Department at Dartmouth College. The EHR 
and medical claims data as a limited dataset will be encrypted and securely transferred to a secure 
database house at the Geisel School of Medicine at Dartmouth. 
16.5 Data Editing  
For the screening, baseline, and follow-up assessments completed data will be entered directly 
into REDCap and TeleSage™ NetSCID-5. Validation checks will be programmed within forms to 
ensure data is complete when collected. Photos of urine drug screen results will be uploaded and 
then results will be manually entered into REDCap. The Local Node will be responsible for 
ensuring accuracy of data entered into REDCap from the photos (UDS source documents). All 
data downloads and reports will be run by the Local Node on a regular basis to identify incomplete 
or inaccurate data. The site will be notified to resolve data inconsistencies and errors. 
Digital health data will be collected passively via smartwatch and smartphone sensors and 
participants will be prompted to answer EMA questions and self-initiated EMAs via smartphone. 
In addition, for those who consent to the optional social media component, social media data will 
be retroactively downloaded by the participant directly from the social media platform to a secure 
server using a remote desktop at the beginning of the study and at the end of the study. All data 
will be collected via sensor or self-report, therefore, there will be no data editing. However, reports 
will be run on a regular basis on EMA and sensor data to ensure the smartwatches and 
smartphones are transmitting data. 
16.6 Data Transfer/Lock 
De-identified data will be made available by request from one of the Lead Nodes and with the 
approval of both PIs.  This approach has been employed successfully before with CTN-0072 
and is also the approach of CTN-0084. We employ this model because of potential concerns 
with privacy and re-identification. The study is recruiting from substance use treatment 

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programs from within a single health system, is only recruiting ~50 (if recruitment is faster than 
anticipated, we will recruit up to 75) patients, and has a brief recruitment time period. The 
number of some participants, particularly in the older age range, may be very small, further 
raising the concern for re-identification. The data collected also reflect very detailed data about 
participants’ daily lives. 
  
16.6.1 Data Training 
The training plan for site staff includes provisions for training on assessments, eCRF completion 
guidelines, data management procedures, participant compensation via gift card, the use of the 
REDCap data collection application, the use of the TeleSage™ data collection platform, the use 
of smartphone and smartwatch devices, use of Dartmouth app and Garmin Connect app, use of 
the study dashboard, and use of the payment system for participant compensation via reloadable 
debit card for the digital health data. 
16.6.2 Data Quality Assurance  
To address the issue of data entry quality, the Lead Node will follow a standard data monitoring 
plan. An acceptable quality level prior to study lock or closeout will be established as a part of the 
data management plan. Data quality summaries will be made available during the course of the 
protocol. 

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17.0 PUBLICATIONS AND OTHER RIGHTS  
This study will comply with the NIH Data Sharing Policy and Policy on the Dissemination of NIH-
Funded Clinical Trial Information and the Clinical Trials Registration and Results Information 
Submission rule. As such, this trial will be registered at ClinicalTrials.gov, and results information 
from this trial will be submitted to ClinicalTrials.gov. In addition, every attempt will be made to 
publish results in peer-reviewed journals. The planning, preparation, and submission of 
publications will follow the policies of the Publications Committee of the CTN. Considerations for 
ensuring confidentiality of any shared data are described in Section 15.5. 

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18.0 PROTOCOL SIGNATURE PAGE 
SPONSOR’S REPRESENTATIVE (CCTN SCIENTIFIC OFFICER OR DESIGNEE) 
 
 
 
 
 
      
 
 
 
 
Printed Name 
 
Signature 
 
Date 
ACKNOWLEDGEMENT BY INVESTIGATOR: 
● I am in receipt of version 4.0 of the protocol and agree to conduct this clinical study in 
accordance with the design and provisions specified therein. 
● I agree to follow the protocol as written except in cases where necessary to protect the 
safety, rights, or welfare of a participant, an alteration is required, and the sponsor and IRB 
have been notified prior to the action. 
● I will ensure that the requirements relating to obtaining informed consent and institutional 
review board (IRB) review and approval in 45 CFR 46 are met. 
● I agree to personally conduct or supervise this investigation at this site and to ensure that 
all site staff assisting in the conduct of this study are adequately and appropriately trained 
to implement this version of the protocol and that they are qualified to meet the 
responsibilities to which they have been assigned. 
● I agree to comply with all the applicable federal, state, and local regulations regarding the 
obligations of clinical investigators as required by the Department of Health and Human 
Services (DHHS), the state, and the IRB. 
 
SITE’S PRINCIPAL INVESTIGATOR 
      
 
 
 
 
Printed Name 
 
Signature 
 
Date 
 
Clinical Site Name  
 
      
Node Affiliation  
 
      
 
 

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DeVito, E. E., Carroll, K. M., & Sofuoglu, M. (2016). Toward Refinement of Our Understanding of 
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20.0 APPENDIX A: SAFETY EVENT REPORTING AND PROCEDURES  
The site’s Principal Investigator is responsible for study oversight, including ensuring human 
research subject protection by designating appropriately qualified and trained study personnel to 
assess, report, and monitor adverse events. 
 
Definition of Safety Events 
 
This is a minimal risk study; therefore, no causally related Adverse Events (AE) or Severe Adverse 
Events (SAE) are anticipated and will not be captured.  For the purposes of this protocol, safety 
reporting will be limited to reporting suicidal ideation and deaths only.  These safety events will 
be captured on a Safety Event Log.  The sites must follow local standard operating procedures 
for managing any medical or psychiatric emergencies. 
 
As hospitalizations and overdoses of participants will be collected as data in this study, these are 
not considered safety events and will not be tracked on the Safety Event Log. In the event that a 
participant death is reported, the local team will report this to the KPNC IRB and to the study 
sponsor following the guidelines set forth (see the study Manual of Operating Procedures for more 
details).  
 
Study staff will be trained to monitor and report all safety events on the Safety Event Log. The 
Log will be sent to the Lead Project Manager at least weekly, or stored on the shared drive to 
which all applicable study team members have access. If applicable, the Study Clinician and Lead 
Team will determine which safety events require reporting to KPNC IRB,  NIDA CCTN and any 
other relevant regulatory authorities.  
The study is a feasibility study, which involves three phone interviews (two baseline and one 12-
week post-EMA start follow-up), and collection of active and passive digital health data (EMA, 
smartphone and smartwatch sensor data, and EHR and medical claims data).  This study is not 
a clinical trial. Therefore, study safety events are expected to be extremely rare.  
 
 
Identifying Safety Events 
Safety events may be elicited at baseline during the NetSCID-5 assessment or spontaneously 
reported to study staff at any visit following consent. Examples of spontaneously reported 
(unsolicited) safety events include: 
● Receiving an unsolicited remark or complaint from the participant or a friend, family 
member or other person about the participant’s intent to harm themselves. 
● Information may be discovered after the participant spontaneously reports a complaint 
(e.g., plans to attempt suicide).  
When safety events are reported, study staff will obtain as much information as possible about 
the reported event to complete documentation of the Safety Event Log and will consult with the 
Study Clinician and Lead Investigators as warranted. Safety event assessment will begin with 
participant consent and follow-up will continue until resolution, stabilization or study end. All 
reported safety events will be followed until resolution or stabilization but will cease at the end of 
the 12-week active window for participants in the study. 
Documenting Safety Events 

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Any safety event that occurs after consent will be documented on the designated Safety Event 
Log. All safety events will be brought to the attention of the Lead Team and reviewed on the 
weekly study call.  
Suicidal ideation will not be captured as AEs or SAEs but instead will be reported on the Safety 
Event Log described below. 
Suicidal ideation may be reported via the NetSCID-5 assessment at baseline or via spontaneous 
report from the participant. In the event of suicidal ideation and behavior reporting, participants 
may need additional and immediate follow-up from the Study Clinician. Refer to the Critical 
Incident SOP for further details. 
  
Monitoring Safety Events 
Quality Assurance (QA) monitors will routinely review study records for any unreported safety 
events and ensure these events are promptly reported to the Lead Investigators, and to the IRB 
of record, per IRB reporting requirements. The monitor will document safety related information 
in the Site Visit Report. Any unreported safety events identified by monitors will be reported as 
protocol deviations. To ensure timely identification and reporting of future safety events, study 
staff education, re-training, or another appropriate corrective action plan may be implemented 
when unreported safety events are discovered. See Module 10 of the study Manual of Operating 
Procedures for specific guidelines on monitoring processes.   
 
Reporting Safety Events  
What to report? 
• 
This study has no reportable AEs or SAEs. Only safety events 
(i.e., suicidality and deaths) will be recorded in the Safety Event 
Log. If required, study staff will report safety events to the IRB of 
Record in accordance with the IRB’s policies and procedures. 
When to report? 
• 
Research staff will consult with Study Clinician about whenever 
suicidality is reported or insinuated. Safety events are to be 
reported on the Safety Event Log within 24 hours of event, and all 
entries will be reviewed by Study Clinician or Local PM within 48 
hours of the entry. Research staff should follow the guidelines of 
KPNC IRB to determine the reporting requirements of reportable 
safety events as described in Section 9.8.1. 
How to report? 
• 
Safety events are reported via the Safety Event Log.  
• 
The Log must be completed with as much relevant information as 
is available at the time of study staff awareness of the event. 
• 
A Study Clinician is responsible for reviewing all safety events and 
may also request additional and updated information, as well as 
request follow up actions.  
• 
Study staff should follow all instructions in the Critical Incident 
SOP.  
• 
The Local PM will email the Log to the Lead PM weekly (i.e., final 
business day) or upload it to the secure shared drive to which all 
appropriate study team members have access. 

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How 
will 
the 
event 
be 
monitored? 
• 
Study staff will follow local procedures outlined in the Critical 
Incident SOP. 
• 
The Study Clinician will report to the Local PM on the outcome of 
the assessment and will complete the Safety Event Log as 
needed. 
• 
The Lead Team will report study safety events to NIDA CCTN on 
an as-needed basis (at least annually).  The study sponsor retains 
the authority to suspend additional enrollment and participation for 
the entire study as applicable. 
 
The Lead Investigators are responsible for reviewing all safety events and may also request 
additional and updated information. The Lead Investigators, along with input from the Study 
Clinicians, will determine which safety events require expedited reporting to the IRB, NIDA CCTN, 
and regulatory authorities. All events that are serious, related, unexpected, or that place subjects 
at greater risk of harm will be promptly reported to Kaiser IRB (IRB of record), as outlined in KPNC 
IRB guidance (policy # N-CRSP HRP 071).  
If information related to the safety event is not completed when it is initially reported or if new 
information becomes available after the Safety Event Log is submitted, a follow-up report 
(containing any additional or updated information) must be submitted as soon as possible, but at 
most within 14 days after the study staff receives the updated information.  
The anticipated safety events for this study (i.e., suicidal ideation) are not required to be reported 
to the KPNC IRB unless there is evidence that they are causally related to the research 
procedures. If a site is ever unsure whether an event should be reported to the IRB, they should 
discuss with the KPNC IRB. 
While unlikely to occur in this low-risk study, unanticipated study-related problems involving risks 
to subjects or others must be reported via KPNC IRB’s Reportable New Information Form, with 
supporting documentation as soon as possible, but no later than 5 business days of becoming 
aware of the event and deaths unanticipated and possibly related to the study must be reported 
within 24 hours (see the study Manual of Operating Procedures for a description of these events 
and reporting requirements).  
All events should be followed up to resolution. 
Sponsor’s Role in Safety Management Procedures of Safety Events 
The Sponsor or designee will not be involved in safety management procedures for this study. 
The Study Clinician is responsible for reviewing all Safety Events. The Lead Investigators and 
designees will also be promptly informed of all reported Safety Events, for example via email. The 
Lead Investigators or designee will report to external parties as required, including the sponsor 
and IRB of record.  
 
 
Reporting Safety Events to the Data and Safety Monitoring Board 
There will be no DSMB for this study.  
 
Participant Discontinuation Due to a Safety Event 

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There may be some situations in which a safety event requires that a participant be discontinued 
from study participation. Participants may be discontinued from the study in the following 
situation(s):  
● Participant’s condition has deteriorated during the course of the study: 
- 
Emergence of psychosis, suicidal ideation, overdose, severe cognitive impairment, 
dangerous criminal behaviors; or 
- 
New onset of psychiatric or medical conditions requiring intervention that preclude 
continued study participation.  
The Study Clinician, in collaboration with the Site PI, should consult with the Lead Team in making 
the decision to withdraw a participant from the study.

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21.0 APPENDIX B: DATA AND SAFETY MONITORING PLAN 
1.0 
BRIEF STUDY OVERVIEW 
Across the U.S., the prevalence of opioid use disorder (OUD) and the rates of opioid overdoses 
have risen precipitously in recent years. Drug overdose is being called a “modern plague” (Katz, 
2017) and is now the leading cause of death of Americans under age 50, having surpassed peak 
death rates from gun violence, HIV, and car crashes (Centers for Disease Control and Prevention 
(CDC), 2018; Katz, 2017). This dramatic spike in OUD has also been accompanied by marked 
increases in injection-related infections (including infective endocarditis and Hepatitis C) (Centers 
for Disease Control and Prevention (CDC), 2016, 2017; Hartman et al., 2016; Keeshin & Feinberg, 
2016), babies born with Neonatal Opioid Withdrawal Syndrome (Patrick, Davis, Lehmann, & 
Cooper, 2015) and healthcare and criminal justice costs (Rhyan, 2017). 
Several effective medication-assisted treatments for OUDs exist.  Treatment models for OUDs 
that include buprenorphine medication are among the most effective treatment models. 
Buprenorphine treatment for OUD has been shown to greatly increase opioid abstinence, reduce 
HIV/infectious disease risk behavior, and criminality.  Greater retention in such treatment models 
are associated with the most positive treatment outcomes (Connock et al., 2007; Johnson, Jaffe, 
& Fudala, 1992; Ling et al., 1998; Sordo et al., 2017a). However, given the chronic relapsing 
nature of the disease of addiction, many individuals continue to engage in opioid use during 
treatment.  Further, many individuals who enter buprenorphine treatment do not consistently take 
their medication or remain engaged in treatment – typically resulting in continued opioid use 
(which is accompanied by risk of overdose) (Fiellin et al., 2008; Schuman-Olivier, Weiss, 
Hoeppner, Borodovsky, & Albanese, 2014)  Although many factors have been shown to predict 
non-adherence in substance use disorder treatment (Simon et al., 2017; Weinstein et al., 2017) 
(including stress, mental health comorbidities, and continued exposure to high risk social 
networks or contexts), most studies have examined a small set of potential moderators or 
mediators of outcomes in treatment for OUD and may lead to over-simplified accounts of 
treatment non-adherence. 
More frequent and longer assessment of moderators, mediators, and outcome(s) are necessary 
to elucidate the temporal dynamics between changes in specific mechanisms and treatment non-
adherence behavior (Collins & Graham, 2002).  Examining a broad array of factors impacting 
treatment non-adherence at multiple levels of analysis will enable a more comprehensive picture 
and will increase our ability to develop more impactful interventions for OUD. 
Advances in digital technologies and data analytics have created new opportunities to assess 
and modify health behavior and thus accelerate the ability of science to understand and contribute 
to improved health behavior and health outcomes.  Given the ubiquity of access to digital 
technologies worldwide, digital tools allow for the examination of health behavior and clinical 
trajectories within-individuals through intensive collection of individual-level, real-time data 
collected via surveys on mobile device (referred to as Ecological Momentary Assessment [EMA]),  
wearable sensors (on smartphones and/or smartwatches), and mapping digital footprints.  
Digitally-derived data allow for the development of dynamic models of health behavior to 
understand behavior in real-time and in response to changing environmental, social, 
physiological, and intrapersonal factors (Naslund et al., 2017; Spruijt-Metz, 2014).  As applied to 
persons with OUD,  digital data that offers ongoing assessment of behavior as individuals live 
their daily lives can help us better understand the trajectory of clinically important behaviors (e.g., 
treatment retention; medication adherence over time) and identify fluctuating contextual factors 
that greatly influence such behaviors, (e.g., patterns leading to relapse or treatment dropout).    
2.0 
OVERSIGHT OF CLINICAL RESPONSIBILITIES 

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A. Site Principal Investigator 
The Site PI is responsible for study oversight, including ensuring human research subject 
protection by designating appropriately qualified, trained research staff and medical clinicians to 
assess, report, and monitor adverse events. 
All reportable Safety Events occurring during the course of the study will be collected, 
documented, and reported by the investigator or designee to the Protocol. 
The occurrence of Safety Events will be assessed as appropriate. All Safety Events will be 
followed up to resolution as described in Appendix A of the Protocol.  
Most reportable Safety Events are required to be reported to the Kaiser IRB within 5 business 
days of the site staff becoming aware of the event. However, some reportable Safety Events 
(including death and unauthorized use or disclosure of confidential subject information or KP 
information) are required to be reported to the Kaiser IRB within 1 business day of site's 
knowledge of the event (see the study Manual of Operating Procedures for more detailed 
information). 
B. Safety Monitor/Medical Monitor 
Since this is a minimal risk study, a Safety Monitor/Medical Monitor will not be appointed. Safety 
Events will be reported to the Study Clinician and Lead Investigators who will, in turn, report to 
applicable regulatory bodies, including the IRB of Record. 
C. Data and Safety Monitoring Board (DSMB) 
Not applicable as there will be no DSMB. 
D. Quality Assurance (QA) Monitoring 
The monitoring of the study site will be conducted on a regular basis using the QA Monitors. 
Investigators will host periodic visits for the monitors (may be conducted remotely). The purpose 
of these visits is to assess compliance with the protocol, GCP requirements, and other applicable 
regulatory requirements, as well as to document the integrity of the trial progress. The 
investigative site will provide direct access to all trial related sites (e.g., pharmacy, research 
office), source data/documentation, and reports for the purpose of monitoring and auditing by 
monitors, as well as for inspection by local and regulatory authorities. Areas of particular concern 
will be the review of inclusion/exclusion criteria, participant Informed Consent Forms, protocol 
adherence, safety monitoring, IRB reviews and approvals, regulatory documents, participant 
records, and Principal Investigator supervision and involvement in the trial. The monitors will 
interact with the study staff to identify issues and re-train as needed to enhance research quality. 
QA Monitors site visit reports will be prepared following each site visit, as applicable. These 
reports are sent to those entities required of them by the study Lead Team, Node Principal 
Investigator(s), and site Principal Investigator. 
E. Management of Risks to Participants 
Confidentiality 
Confidentiality of participant records will be secured by the use of study codes for identifying 
participants on CRFs, and secure storage of any documents that have participant identifiers on 
site, as well as secure computing procedures for entering and transferring electronic data. The 
documents or logs linking the study codes with the study participant on site will be kept 

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locked/securely stored separately from the study files and the medical records. No identifying 
information will be disclosed in reports, publications or presentations. 
Information That Meets Reporting Requirements 
The consent form will specifically state the types of information that are required for reporting and 
that the information will be reported as required. These include suspected or known sexual or 
physical abuse of a child or elders or threatened violence to self and/or others. 
Participant Protection 
A designated and qualified individual at the site will evaluate all pertinent screening and baseline 
assessments prior to participant enrollment to ensure that the participant is eligible and safe to 
enter the study. Safety Events will be collected if elicited at baseline or spontaneously reported 
by participants during their participation in the study. Individuals who experience a Safety Event 
that compromises safe participation in a study will be discontinued from further participation and 
provided referrals for other treatment or to specialized care as needed.  
Pregnancy 
As there is no medication intervention, pregnancy will not be followed within the context of this 
study. 
Study Specific Risks 
Suicidal ideation is a possible risk. Other potential risks are low due to the data not being 
monitored in real time but being sent directly to a data warehouse. Participants will be told in case 
of immediate crisis or emergency, they should call 911 or a medical provider. The low potential 
risks may include: 
o Risk from EMAs: The types of risk associated with the data collected include possible 
fatigue, frustration, or the discussion of sensitive or personal information. If participants 
do not wish to answer particular mobile surveys, they may elect not to do so, and may 
continue in the remainder of the study without penalty. Additionally, participants may be 
concerned about confidentiality when using the smartphone to transmit EMA responses, 
even with data encryption and secure cloud-based data transfer. They may also be 
worried about prompts they receive on their mobile device designed to remind them to 
complete the EMA questions.  
▪ 
To protect against risk of fatigue and frustration, we have intentionally developed the 
EMAs to be brief (approximately 10 mins to complete). Anyone who experiences 
discomfort with the sensitive or personal EMA questions, can either elect not to 
answer the questions or are advised that they can discontinue their participation at 
any point without penalty. Finally, to protect against concerns that others may see 
when a participant receives an EMA prompt, the content of the prompt will be 
intentionally vague. The prompts will be designed to be meaningful to the participant, 
but they will not include specific references to study participation. 
o Risk from mobile sensing: Participants might experience slight initial discomfort while 
wearing the smartwatch, such as minor skin irritations. As with any electrical device, the 
sensors can theoretically cause electric shocks. Electric shocks can be a health concern 
with certain health conditions (e.g., heart conditions that require a pacemaker). 
Additionally, participants could have privacy concerns regarding mobile sensing 
(smartwatch or smartphone). 
▪ 
Although slight discomfort is possible from wearing the smartwatch, the smartwatch 

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has been used in multiple field studies with many participants, and no significant skin 
irritation has been reported. Therefore, we expect the severity of the discomfort and 
irritation of wearing the smartwatch to be minimal. If irritation persists to a point 
where the participant no longer wishes to participate, any irritation is reversible once 
the participant removes the smartwatch. 
▪ 
While electrical devices do introduce the risk of electric shocks, the probability of a 
participant experiencing even minor electrical shocks is negligible. High impedance 
circuitry is used to limit current flow, even in the case of external events (e.g., 
through physical breaking of the sensor board or shorting of the battery leads). All 
sensors in the smartwatch are commonly used in mobile phones and other activity 
monitors and pose minimal risk to participants. Previous studies with wristband 
sensors have indicated that after a brief adjustment period, the majority of the 
participants adjusted to wearing the bands and did not find them to be intrusive or 
restraining. We expect that the smartwatch, which have precedent of prior use in a 
research study or have otherwise been designed for everyday wear, will elicit similar 
acceptability among the participants in this study. 
▪ 
Regarding privacy concerns, participants’ contact information will be linked to their 
study data via a code. Participants will be informed of their rights to terminate their 
participation in the study at any time. Participants will also be informed of their rights 
to remove the smartwatch and/or not carry their smartphone if they so choose, if they 
do not wish to be tracked. 
o Risk from social media data: We will ask participants to provide us with information 
they post to their social media (e.g., Facebook, Instagram, and Twitter). We will evaluate 
each participant’s posted images, captions, and comments. Participants may feel 
uncomfortable sharing their social media communications. 
▪ 
We recognize that some participants may not have a social media account, and 
some may not want to share their social media data with researchers. Participants 
can choose not to share this information (consent to share social media data will be 
separate consent line(s) on the consent form) and they can still be eligible to 
participate in other parts of the study. Note that we will not directly collect data from 
friends/members of participants’ social networks but will only ask participants if they 
provide permission for us to learn about their relationships with their social network 
members via information participants post on their own social media. Additionally, we 
will never publish social media text quotations from participants or present 
participants’ information in ways that could potentially be identifiable. 
3.0 
DATA MANAGEMENT PROCEDURES 
For the screening, baseline, and follow-up assessments, electronic data will be entered into 
REDCap application and the SCID-5 assessment will be entered into TeleSage™ NetSCID-5 by 
the research staff during the assessment. The data is written to a file on the REDCap and 
TeleSage™ NetSCID-5 secure web servers, and data can only be accessed by logging in with a 
REDCap or TeleSage™ NetSCID-5 account. These electronic data capture systems will meet the 
guidelines and regulations surrounding the use of computerized systems in clinical trials.  
For the digital health technology, all data will be electronically captured either via study participant 
self-report or passively via smartwatch and smartphone sensors.  The sensor and EMA data will 
be encrypted and securely transferred to a secure database. Social media data will be 
downloaded by the participant (from those who consent) directly from the social media site to the 
study team’s server using a remote desktop and stored on a secure encrypted server housed at 

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the Williamson Translational Research Building in the Biomedical Data Science Department at 
Dartmouth College. The EHR and medical claims data will be encrypted and securely transferred 
to a secure database. Only research team members will have access to the secure servers 
housing the digital study data. 
4.0 
DATA AND STATISTICS CENTER RESPONSIBILITIES 
The Lead Node will 1) develop a data management plan and will conduct data management 
activities in accordance with that plan, 2) provide final guided source documents and eCRFs 
(guided source documents for Screening, Baseline, and Follow-up only; eCRFs for all 
assessments) for the collection of all data required by the study, 3) develop data dictionaries for 
each eCRF and EMA that will comprehensively define each data element, 4) conduct ongoing 
data monitoring activities on study data from the site, 5) monitor any preliminary analysis data 
cleaning activities as needed, and 6) rigorously monitor final study data cleaning. 
5.0 
DATA COLLECTION AND ENTRY 
Data will be collected at the study site via digital forms in the REDCap system and TeleSage™ 
NetSCID-5 system. In the event that REDCap or and TeleSage™ NetSCID-5 is not available, the 
research staff will reschedule the study appointment to a time when the electronic systems are 
available. Data will be entered into REDCap and TeleSage™ NetSCID-5 in accordance with the 
instructions provided during protocol-specific training and guidelines established by the Lead 
Node. Data entry into the eCRFs is performed by authorized individuals. In some situations, data 
collected on source documents will not be entered into REDCap, but when it is entered, it will 
follow the guidelines stated above. 
The project manager for the site is responsible for ensuring the site maintains accurate, complete, 
and up-to-date research records.  
Digital health data will be collected by self-report EMAs via smartphone, smartwatch and 
smartphone sensors, and by social media (for those who consent). All data will be collected 
electronically. Data collected via smartphone and smartwatch (sensor and EMAs) will be 
encrypted and securely transferred to a secure database housed at the Research Computing 
Department at Dartmouth College. Social media data will be downloaded by the participant 
directly from the social media platform to a secure server using a remote desktop at the beginning 
of the study and at the end of the study (if consented). All social media data will be securely stored 
on an encrypted server at the Williamson Translational Research Building in the Biomedical Data 
Science Department at Dartmouth College. The EHR and medical claims limited dataset will be 
encrypted and securely transferred to a secure database house at the Geisel School of Medicine 
at Dartmouth. 
6.0 
DATA MONITORING, CLEANING AND EDITING 
eCRFs will be monitored for completeness and accuracy throughout the study. Dynamic reports 
listing missing values and forms are available to site at all times in REDCap and TeleSage™ 
NetSCID-5. These reports will be monitored regularly by the Local Node.  
Digital health data will be collected passively via smartwatch and smartphone sensors and 
participants will be prompted to answer EMA questions via smartphone. In addition, for those who 
consent to the optional social media component, social media data will be retroactively 
downloaded by the participant directly from the social media platform to a secure server using a 
remote desktop at the beginning of the study and at the end of the study. All data will be collected 
via sensor or self-report, therefore, there will be no data editing. However, reports will be run on 
a regular basis on EMA and sensor data to ensure the smartwatches and smartphones are 
transmitting data. 

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Information on recruitment, availability of primary outcome, treatment exposure, attendance at 
long term follow-up visits, regulatory status, and data quality, may be generated approximately 
monthly, and will be made available to the site, the corresponding Node, the Lead Investigators, 
and NIDA CCTN, to monitor the site’s progress on the study. 
7.0 
DATABASE LOCK AND TRANSFER 
At the conclusion of data collection for the study, the Lead Node will perform final data cleaning 
activities and the study database will be “locked” from further modification. The final analysis will 
be completed by the Lead Investigators. De-identified data will be made available by request from 
one of the Lead Nodes and with the approval of both PIs.  This approach has been employed 
successfully before with CTN-0072 and is also the approach of CTN-0084. We employ this model 
because of potential concerns with privacy and re-identification. The study is recruiting from 
substance use treatment programs from within a single health system, is only recruiting ~50 (if 
recruitment is faster than anticipated, we will recruit up to 75) patients, and has a brief recruitment 
time period. The number of some participants, particularly in the older age range, may be very 
small, further raising the concern for re-identification. The data collected also reflect very detailed 
data about participants’ daily lives. 
Reference: http://grants.nih.gov/grants/guide/notice-files/not98-084.html