Adapting Diabetes Treatment Expert Systems to Patient's Expectations and Psychobehavioral Characteristics in Type 1 Diabetes
Phase: NA
Conditions: Diabetes Mellitus, Type 1
Sponsor: University of Virginia

 
UVA CENTER FOR DIABETES TECHNOLOGY 
 
 
Adapting Diabetes Treatment Expert 
Systems to Patient's Expectations and 
Psychobehavioral Characteristics in Type 1 
Diabetes 
 
 
 
 
 
Protocol Chair 
Marc Breton, PhD  
University of Virginia 
Center for Diabetes Technology 
 
Version Number: v2.0 
05-Oct-2021 
 

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KEY ROLES 
 
Protocol Principal Investigator 
 
Name, degree 
Marc Breton, Ph.D.  
Institution Name 
University of Virginia Center for Diabetes Technology  
 
 

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PROTOCOL VERSION HISTORY 
Version 
Number 
Author(s) 
Approver 
Effective 
Date 
Revision Description 
1.0 
 
 
24-Apr-2020 
Original Protocol 
1.1 
Mary Oliveri 
Mary Oliveri 
20-May-
2020 
Added  
• Demographic Data Survey added 
at screening   
1.2 
Mary Oliveri 
 
03-Aug-2020 
Full Board Revisions:  
• Clarified that participants may 
contact the study team at any 
time during the study to report 
adverse events (Section 5.1.1 
5.3.2, 6.4.3, 6.6.3, 7.6.3). 
• Corrected erroneous sentence 
referencing DHHS 46.405 (section 
10.3). 
• Corrected 
bullet 
formatting 
(section 12.3.2).  
• Removed references to Medical 
Monitor throughout protocol.  
• Added references to Data Safety 
Monitoring Board (section 12.10).  
1.3 
Jon Olson 
Mary Oliveri 
08-Nov-2020 
Study Team modifications:  
• Physical examination (may use a 
medical record within the past 6 
months) 
• Weight, height (participant may 
self-report this information) 
• Vital signs including measurement 
of blood pressure and pulse (may 
use a medical record within the 
past 6 months) 
• Participants will have the option 
to be given a receiver from the 
study team for medical needs.  
1.4 
Jon Olson 
Mary Oliveri 
22-Jan-2021 
DSMB Request: 
• If applicable, subjects will have a 
pregnancy test between phases 
(section 6.4). 
2.0 
Mary Oliveri 
Marc Breton, Ralf 
Nass 
05-Oct-2021 
Study Team Modifications:  
• Modified HbA1c limit to HbA1c 
6.0-11.0%, 
inclusive 
(section 
3.3)Edited 
Sensor 
Augmented 
Pump Therapy (SAP) to Sensor 

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Augmented 
Mode 
(SAM) 
throughout the document 
• Deleted inclusion of carbohydrate 
counting (section 3.3) 
• Added  NPH insulin as study 
exclusion (section 3.4) 
• Added Post-Screening Assessment 
section 
describing 
participant 
requirements (section 3.5) 
• Clarified Training visit definition 
(Chapter 4)Clarified pump and 
MDI training issues  (section 4.1.2, 
4.1.3) 
• Study physician may add up to two 
weeks to CGM run-in period 
(section 5.2.1) 
• Revised Figure 4 and Figure 5 
 
 
 

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SITE PRINCIPAL INVESTIGATOR STATEMENT OF COMPLIANCE 
Protocol Title:  Adapting Diabetes Treatment Expert Systems to Patient’s Expectations and 
Psychobehavioral Characteristics in Type 1 Diabetes 
Protocol Version/Date: v2.0/05-Oct-2021 
I have written the protocol specified above. In my formal capacity as a Site Principal Investigator, 
my duties include ensuring the safety of the study participants enrolled under my supervision. It 
is understood that all information pertaining to the study will be held strictly confidential and 
that this confidentiality requirement applies to all study staff at this site. 
This trial will be carried out in accordance with ICH E6 Good Clinical Practice (GCP) and as required 
by the following: United States (US) Code of Federal Regulations (CFR) applicable to clinical 
studies (45 CFR Part 46, 21 CFR Part 50, 21 CFR Part 56, 21 CFR Part 312, and/or 21 CFR Part 812). 
As the Principal Investigator, I 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), or other approved Ethics Committee, except where necessary 
to eliminate an immediate hazard(s) to the trial participants. 
All key personnel (all individuals responsible for the design and conduct of this trial) have 
completed Human Participants Protection Training and Good Clinical Practice Training. Further, I 
agree to ensure that all staff members involved in the conduct of this study are informed about 
their obligations in meeting the above commitments. 
 
Investigator’s Signature __________________________________Date: _____ / _____ / _____ 
Investigator’s Name: ________________________________ 
Site Name:  University of Virginia 
 
 

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LIST OF ABBREVIATIONS 
ABBREVIATION 
DEFINITION 
API 
Application Programming Interface  
ATI 
Acceptance and Trust Index 
BG 
Blood Glucose 
BT/BTLE 
Bluetooth, Bluetooth low energy 
CR 
Carbohydrate Ratio 
CLC 
Closed-Loop Control 
CGM 
Continuous Glucose Monitor 
CSII 
Continuous Subcutaneous Insulin Injection 
CV 
Coefficient of Variation 
DiAs 
Diabetes Assistant 
DCCT 
Diabetes Control and Complications Trial 
DKA 
Diabetic Ketoacidosis 
DSS 
Decision Support System 
DWM 
DiAs Web Monitoring 
eA1c 
Estimated Hemoglobin A1c 
EMA 
Ecological Momentary Assessment 
FDA 
Food and Drug Administration 
GCP 
Good Clinical Practice 
GLM 
General Linear Models 
GV 
Glucose Variability 
HbA1c 
Hemoglobin A1c 
HBGI 
High Blood Glucose Index  
HTTP 
Hypertext Transfer Protocol 
IDE 
Investigational Device Exemption 
IOB 
Insulin-on-Board 
ISF 
Insulin Sensitivity Factor 
JSON 
JavaScript Object Notation 
LBGI 
Low Blood Glucose Index  
NIH 
National Institutes of Health 
PF 
Personalized Feedback 
POC 
Point-of-Care 

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QC 
Quality Control 
QOL 
Quality of Life  
REST-ful 
Representational State Transfer 
SAM 
Sensor Augmented Mode 
SAP 
Sensor-Augmented Pump therapy 
SH 
Severe Hypoglycemia 
SI 
Insulin Sensitivity 
SMBG 
Self-Monitoring of Blood Glucose 
T1DM 
Type 1 Diabetes Mellitus 
T2DM 
Type 2 Diabetes Mellitus 
UI 
User Interface 
URL 
Uniform Resource Locator 
XML 
Extensible Markup Language 
 
 

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PROTOCOL SUMMARY 
PARTICIPANT AREA 
DESCRIPTION 
Title 
Adapting Diabetes Treatment Expert Systems to Patient’s Expectations and Psychobehavioral 
Characteristics in Type 1 Diabetes 
Investigational Device 
CGM-based Personalized Feedback (PF) and Decision Support System (DSS) 
Objectives 
Aim 1 (control of GV) We will confirm and contrast the efficacy of two previously designed technological 
interventions – Personalized Feedback (PF) and Decision Support System (DSS) - in reducing glucose 
variability (GV) in Type 1 Diabetes Mellitus (T1DM) during a 6-month randomized crossover clinical trial.  
Aim 2 (personalization of treatment policy) We hypothesize that the participants in this study will have 
technology intervention preferences (e.g. PF or DSS) that can be predicted by key psychosocial and 
behavioral parameters and are prognostic of the level of GV control achievable by the intervention.  
Aim 3 (monitoring of treatment policy) Finally, we propose to define a novel, measurable, technology 
Acceptance and Trust Index (ATI), passively observing and recording user-system interactions, and 
validate this new index using active Ecological Momentary Assessment (EMA) to track user subjective 
response to DSS. 
Study Design 
This is a randomized crossover study in T1DM adults designed to demonstrate the efficacy of 
personalized feedback (PF) and decision support (DSS) over sensor-augmented mode (SAM) therapy and 
to establish relationships between the level of glucose variability (GV) control achievable by the 
intervention and individual psycho-behavioral characteristics.  
Number of Sites 
1 
Outcomes 
A key advantage of the proposed study design (beyond the optimal statistical power) is the possibility to 
explore the glucose control and psycho-behavioral impact of features being added and/or enhanced 
with prescriptive components (DSS), vs. features being limited to information (PF) or even removed 
(SAM).  
Population 
Key Inclusion Criteria 
• 
Age 18 years and older 
• 
T1DM diagnosis for at least 1 year 
• 
Established insulin parameters  
Key Exclusion Criteria d 
• 
Hemoglobin A1c 6.0-11.0%, inclusive 
Sample Size  
Enrollment will proceed with the goal of completing 4 cohorts of about 25 participants each (expected 
retention 20 per cohort) 
Treatment Groups 
• 
De-escalation (DSS→PF→SAM) 
• 
Escalation (SAM→PF→DSS) 
Participant Duration 
The study duration for each participant is approximately 7 months. 
Protocol Overview/Synopsis 
Four cohorts of about 25 participants each (expected retention 20 per cohort). Each cohort will continue 
for ~7 months. Following recruitment, screening, and a run-in period of SAM, participants will be 
randomized into one of two groups: escalation vs. de-escalation of devices and function. Each treatment 
modality (SAM, PF, DSS) will continue for about 8 weeks, with the last 4 weeks used to assess GV from 
CGM data.  

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STUDY VISITS AND PROCEDURES SCHEDULE 
 
Visit 1 
Screening 
and 
Questionnaires 
Visit 2 
Study Device 
and 
Procedures 
Training 
SAM 
Run-in 
Visit 3 
Eligibility 
Assessment, 
Randomization 
and Training 
DiAs Use 
in Phase 1 
Mode 
Visit 4 
Phase 2 
Initiation 
DiAs Use 
in Phase 2 
Mode 
Visit 5 
Phase 3 
Initiation 
DiAs Use 
in Phase 3 
Mode 
Visit 6  
Study  
Exit 
Visit 7 
Post 
Study 
Check in 
Location 
Clinic 
Clinic 
Home x 
2-4 
weeks 
Web 
Conference 
or Clinic 
Home x 
8 weeks 
Web 
Conference 
or Clinic 
Home x 
8 weeks 
Web 
Conference 
or Clinic 
Home x 
8 weeks 
Phone 
or 
Clinic 
Phone 
or 
Clinic 
Informed Consent 
X 
 
 
 
 
 
 
 
 
 
 
Medical History 
X 
 
 
 
 
 
 
 
 
 
 
Medications 
X 
 
 
 
 
 
 
 
 
 
 
Physical Exam (including 
vital signs, height/weight) 
X 
 
 
 
 
 
 
 
 
 
 
Pregnancy Test (if 
childbearing potential) 
X 
 
 
 
 
X 
 
X 
 
 
 
Blood Testing: TSH, CMP 
(additional labs as 
necessary) 
X 
 
 
 
 
 
 
 
 
 
 
Questionnaires 
X 
 
X 
X 
X 
X 
X 
X 
X 
X 
 
Equipment Training 
 
X 
 
 
 
 
 
 
 
 
 
DiAs in SAM Training 
 
X 
 
 
 
 
 
 
 
 
 
Glycemic Treatment 
Guidelines Training 
 
X 
 
 
 
 
 
 
 
 
 
Glucagon Emergency Kit 
Training 
 
X 
 
 
 
 
 
 
 
 
 
Use of DiAs in SAM  
 
 
X 
 
 
 
 
 
 
 
 
Eligibility Assessment 
 
 
 
X 
 
 
 
 
 
 
 
AE Assessment 
 
 
 
X 
 
X 
 
X 
 
X 
 
Randomization 
 
 
 
X 
 
 
 
 
 
 
 
DiAs Phase 1 Mode Training 
 
 
 
X 
 
 
 
 
 
 
 
EMA Training 
 
 
 
X 
 
 
 
 
 
 
 

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Visit 1 
Screening 
and 
Questionnaires 
Visit 2 
Study Device 
and 
Procedures 
Training 
SAM 
Run-in 
Visit 3 
Eligibility 
Assessment, 
Randomization 
and Training 
DiAs Use 
in Phase 1 
Mode 
Visit 4 
Phase 2 
Initiation 
DiAs Use 
in Phase 2 
Mode 
Visit 5 
Phase 3 
Initiation 
DiAs Use 
in Phase 3 
Mode 
Visit 6  
Study  
Exit 
Visit 7 
Post 
Study 
Check in 
 
Visit 1 
Screening 
and 
Questionnaires 
Visit 2 
Study Device 
and 
Procedures 
Training 
SAM 
Run-in 
Visit 3 
Eligibility 
Assessment, 
Randomization 
and Training 
DiAs Use 
in Phase 1 
Mode 
Visit 4 
Phase 2 
Initiation 
DiAs Use 
in Phase 2 
Mode 
Visit 5 
Phase 3 
Initiation 
DiAs Use 
in Phase 3 
Mode 
Visit 6 
Study 
Exit 
Visit 7 
Post 
Study 
Check in 
Location 
Clinic 
Clinic 
Home x 
2-4 
weeks 
Web 
Conference 
or Clinic 
Home x 8 
weeks 
Web 
Conference 
or Clinic 
Home x 8 
weeks 
Web 
Conference 
or Clinic 
Home x 8 
weeks 
Phone 
or Clinic 
Phone 
or Clinic 
Use of DiAs in Phase 1 
Mode 
 
 
 
 
X 
 
 
 
 
 
 
EMA Surveys 
 
 
 
 
X 
 
X 
 
X 
 
 
DiAs Phase 2 Mode Training 
 
 
 
 
 
X 
 
 
 
 
 
Use of DiAs in Phase 2 
Mode 
 
 
 
 
 
 
X 
 
 
 
 
DiAs Phase 3 Mode Training 
 
 
 
 
 
 
 
X 
 
 
 
Use of DiAs in Phase 3 
Mode 
 
 
 
 
 
 
 
 
X 
 
 
Review diabetes 
management & AEs 
 
 
 
X 
 
X 
 
X 
 
X 
X 

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Table of Contents 
1 
 
Background .................................................................................................... 15 
2 
1.1. 
Introduction .................................................................................................................. 15 
3 
1.2. 
Specific Aims ................................................................................................................. 23 
4 
1.3. 
Outcomes ...................................................................................................................... 24 
5 
1.4. 
Study Design.................................................................................................................. 27 
6 
1.5. 
Study Participants ......................................................................................................... 28 
7 
1.6. 
Clinical Sites .................................................................................................................. 28 
8 
 
Study Devices ................................................................................................. 29 
9 
2.1. 
Diabetes Assistant (DiAs) .............................................................................................. 29 
10 
2.2. 
Insulin Pump ................................................................................................................. 29 
11 
2.3. 
Continuous Glucose Monitor (CGM) ............................................................................ 29 
12 
2.4. 
Ketone Meter and Strips ............................................................................................... 29 
13 
 
Study Screening .............................................................................................. 30 
14 
3.1. 
Informed Consent and Authorization Procedures ........................................................ 30 
15 
3.2. 
Visit 1 - Eligibility Screening Procedures ....................................................................... 30 
16 
3.3. 
Participant Inclusion Criteria......................................................................................... 31 
17 
3.4. 
Participant Exclusion Criteria ........................................................................................ 32 
18 
3.5. 
Post-screening assessments ......................................................................................... 33 
19 
 
Training Visit .................................................................................................. 34 
20 
4.1. 
Visit 2 - Study Equipment .............................................................................................. 34 
21 
4.2. 
Ecological Momentary Assessment Training ................................................................ 36 
22 
4.3. 
Glucagon Emergency Kit ............................................................................................... 36 
23 
 
Study Procedures ........................................................................................... 37 
24 
5.1. 
Study Contacts .............................................................................................................. 37 
25 

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5.2. 
Sensor-Augmented Mode (SAM) Run-in Period ........................................................... 37 
26 
5.3. 
Visit 3 – Eligibility Assessment, Randomization and Training ....................................... 38 
27 
 
Study Procedures - Escalation ......................................................................... 39 
28 
6.2. 
Sensor Augmented Mode ............................................................................................. 39 
29 
6.3. 
Home Use of DiAs in Phase 1 Mode ............................................................................. 39 
30 
6.4. 
Visit 4 – Phase 2 Initiation ............................................................................................. 40 
31 
6.5. 
Home Use of DiAs in Phase 2 Mode ............................................................................. 41 
32 
6.6. 
Visit 5 – Phase 3 Initiation ............................................................................................. 42 
33 
6.7. 
Home Use of DiAs in Phase 3 Mode ............................................................................. 43 
34 
6.8. 
Visit 6 - Study Exit.......................................................................................................... 43 
35 
6.9. 
Post Study Check-In Visit (Visit 7) ................................................................................. 44 
36 
 
Study Procedures – De-Escalation................................................................... 45 
37 
7.1. 
Randomization to De-Escalation ................................................................................... 45 
38 
7.2. 
Training on Phase 1 DiAs Mode .................................................................................... 45 
39 
7.3. 
Home Use of DiAs in Phase 1 Mode ............................................................................. 46 
40 
7.4. 
Visit 4 – Phase 2 Initiation ............................................................................................. 46 
41 
7.5. 
Home Use of DiAs in Phase 2 Mode ............................................................................. 47 
42 
7.6. 
Visit 5 – Phase 3 Initiation ............................................................................................. 48 
43 
7.7. 
Home Use of DiAs in Phase 3 Mode ............................................................................. 48 
44 
7.8. 
Visit 6 - Study Exit.......................................................................................................... 49 
45 
7.9. 
Post Study Check-In Visit (Visit 7) ................................................................................. 50 
46 
 
Testing Procedures ......................................................................................... 51 
47 
8.1. 
Laboratory / Point of Care Testing ................................................................................ 51 
48 
 
Questionnaires & Ecological Momentary Analysis .......................................... 52 
49 
9.1. 
Diabetes Specific Personality Questionnaire ................................................................ 52 
50 
9.2. 
ABACUS ......................................................................................................................... 52 
51 

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9.3. 
Diabetes Locus of Control ............................................................................................. 52 
52 
9.4. 
Confidence in Diabetes Self-Care Scale ........................................................................ 52 
53 
9.5. 
Clarke's Hypoglycemia Awareness Scale ...................................................................... 53 
54 
9.6. 
The Diabetes Distress Scale .......................................................................................... 53 
55 
9.7. 
Hypoglycemia Fear Survey ............................................................................................ 53 
56 
9.8. 
Hyperglycemia Avoidance Scale ................................................................................... 53 
57 
9.9. 
Pittsburgh Sleep Quality Index...................................................................................... 54 
58 
9.10. Technology Acceptance and Expectations Survey (burdens subscale only) ................ 54 
59 
9.11. INSPIRE (revised for DSS) .............................................................................................. 54 
60 
9.12. Ecological Momentary Analysis (EMA) ......................................................................... 54 
61 
9.13. Questionnaire Schedule ................................................................................................ 56 
62 
 
Risks, Benefits, and Risk Assessment .............................................................. 57 
63 
10.1. Potential Risks and Benefits of the Investigational Device ........................................... 57 
64 
10.2. Potential Benefits .......................................................................................................... 59 
65 
10.3. Risk Assessment ............................................................................................................ 59 
66 
10.4. General Considerations................................................................................................. 59 
67 
 
Device Cleaning Instructions ........................................................................... 61 
68 
 
Adverse Events, Device Issues, and Stopping Rules ......................................... 62 
69 
12.1. Definitions ..................................................................................................................... 62 
70 
12.2. Protocol Deviations ....................................................................................................... 63 
71 
12.3. Reportable Events ......................................................................................................... 63 
72 
12.4. Relationship of Adverse Event to Study Device ............................................................ 64 
73 
12.5. Intensity of Adverse Event ............................................................................................ 65 
74 
12.6. Coding of Adverse Events ............................................................................................. 65 
75 
12.7. Outcome of Adverse Events ......................................................................................... 65 
76 
12.8. Reportable Device Issues .............................................................................................. 66 
77 

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12.9. Timing of Event Reporting ............................................................................................ 67 
78 
12.10. Data and Safety Monitoring Board ............................................................................... 67 
79 
12.11. Stopping Criteria ........................................................................................................... 68 
80 
12.12. Independent Safety Oversight ...................................................................................... 68 
81 
 
Miscellaneous Considerations ........................................................................ 69 
82 
13.1. Prohibited Medications, Treatments, and Procedures................................................. 69 
83 
13.2. Participant Withdrawal ................................................................................................. 69 
84 
13.3. Confidentiality ............................................................................................................... 69 
85 
 
Statistical Consideration ................................................................................. 70 
86 
14.1. Design and Randomization ........................................................................................... 70 
87 
14.2. Sample Size ................................................................................................................... 70 
88 
14.3. Outcome Measures ....................................................................................................... 71 
89 
14.4. Exploration of the effect of treatment escalation vs. de-escalation ............................ 72 
90 
14.5. Psychological and Behavioral Questionnaires .............................................................. 72 
91 
14.6. Baseline Descriptive Statistics....................................................................................... 72 
92 
14.7. Device Issues ................................................................................................................. 72 
93 
 
Data Collection and Monitoring ...................................................................... 73 
94 
15.1. Case Report Forms and Device Data ............................................................................. 73 
95 
15.2. Study Records Retention .............................................................................................. 73 
96 
 
Ethics/Protection of Human Participants ........................................................ 74 
97 
16.1. Ethics Standard ............................................................................................................. 74 
98 
16.2. Institutional Review Boards .......................................................................................... 74 
99 
16.3. Informed Consent Procedures and Documentation ..................................................... 74 
100 
16.4. Participant and Data Confidentiality............................................................................. 74 
101 
 
References ..................................................................................................... 76 
102 

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103 
 
104 
 Background 
105 
 
106 
1.1.1. 
Significance 
107 
Type 1 diabetes mellitus (T1DM) is an autoimmune condition resulting in absolute insulin 
108 
deficiency and a life-long need for insulin replacement [1]. Glycemic control in T1DM remains a 
109 
challenge, despite the availability of modern insulin analogs [2], the improving accuracy of 
110 
glucose monitoring [3-4], and the widening use of intensive insulin therapy. While new 
111 
technologies have proven benefits in avoiding diabetes related complications [5] and may have 
112 
reduced excess mortality in some populations [6], excess mortality and complication rates remain 
113 
significantly higher in T1DM when compared to the general population [7-8]. 
114 
Glucose variability (GV) in T1DM is typically at the root of clinicians’ inability to safely achieve 
115 
near-normal average glycemia, as reflected by hemoglobin A1c (HbA1c) [9]. While target HbA1c 
116 
values of 7% or less result in decreased risk of micro- and macrovascular complications [10-13], 
117 
the risk for severe hypoglycemia (SH) increases with tightening glycemic control [14-16]. 
118 
Consequently, hypoglycemia has been implicated as the primary barrier to optimal control [17-
119 
18]. Thus, individuals with T1DM face a life-long optimization challenge: reduce average glucose 
120 
levels and postprandial hyperglycemia while simultaneously avoiding hypoglycemia. A strategy 
121 
for achieving such an optimization can only be effective if it reduces GV. This is because bringing 
122 
average glycemia down is only possible if GV is constrained – otherwise blood glucose (BG) 
123 
fluctuations would inevitably enter the range of hypoglycemia. However, averages and HbA1c 
124 
fail to capture GV and the attendant risks associated with extremes of hypo- and hyperglycemia. 
125 
Indeed, in addition to establishing HbA1c as the gold standard for average glycemic control, the 
126 
Diabetes Control and Complications Trial (DCCT) concluded that: “HbA1c is not the most 
127 
complete expression of the degree of glycemia. Other features of diabetic glucose control, which 
128 
are not reflected by HbA1c, may add to, or modify the risk of complications. For example, “the 
129 
risk of complications may be highly dependent on the extent of postprandial glycemic excursions” 
130 
[19]. Thus, more recent studies increasingly focused on the variability of BG fluctuations as an 
131 
independent risk factor for diabetes complications [9, 20-21], particularly cardiovascular disease 
132 
[22-25]. 
133 

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Intensive insulin therapy: Introduced in the 1980s, intensive insulin treatment by multiple daily 
134 
injections (MDI) or use of continuous subcutaneous insulin infusion (CSII), typically includes basal 
135 
insulin administered to cover the overnight and fasting periods and bolus insulin given with meals 
136 
to cover carbohydrate consumption and to correct postprandial hyperglycemia, in an attempt to 
137 
mimic insulin secretion in health [26]. Advanced insulin therapy relies on key individual 
138 
parameters such as basal rate, carbohydrate ratio (CR) and insulin sensitivity factor (ISF) [26].  
139 
Evidence-based resources are available to patients to control their insulin intake and schedules, 
140 
and clinicians to initiate and maintain CSII therapy by selecting appropriate basal rates, 
141 
carbohydrate ratios, and insulin sensitivity factor patterns [27].  
142 
Expert systems and Control of Glucose Variability: Periodic adjustments of basal rate, CR, and ISF 
143 
patterns are needed based on review of self-monitoring blood glucose (SMBG) profiles, or 
144 
continuous glucose monitoring (CGM). If a pattern is identified, optimized insulin dosing 
145 
parameters are calculated and implemented. This can be a time-consuming and onerous task, 
146 
requiring data to be downloaded from multiple devices and often subjectively evaluated. 
147 
Information technology is increasingly playing a positive role in improving the management of 
148 
chronic conditions [28-29], including diabetes [30]. For example, in T1DM, telemedicine and 
149 
online patient support has shown promising results [31-32]; and retrospectively linking behavior 
150 
to glycemic outcomes has proven effective as well [33]. With improvements in SMBG and CGM 
151 
technologies, a growing appreciation of the quantitative (algorithmic) aspect of the management 
152 
of T1DM has led to new tools for remote patient monitoring, data aggregation and visualization 
153 
[34]. Early research has developed algorithms for titrating individual insulin treatment 
154 
parameters, including iterative learning approaches such as ‘run-to-run’ with structured SMBG 
155 
[35-39]. Insulin titration and dosing tools for type 2 diabetes are beginning to enter the 
156 
marketplace [40], mostly using SMBG. Today, researchers are actively working on CGM-based 
157 
decision support for T1DM [26, 41-44], capable of providing specific feedback to the clinician 
158 
regarding suggested therapy changes. These expert systems have the potential to streamline 
159 
clinic visits and facilitate collaborative patient-centered interactions, but in their most advanced 
160 
form, they deliver advice directly to the patient [41], reducing burden and uncertainty when 
161 
making self-management decisions.  
162 
Automated Insulin Delivery: Closed loop control (CLC) technology (i.e. artificial pancreas or AP), 
163 
involves the pairing of CGM with CSII (insulin pump) via a closed loop control algorithm which 
164 
automatically adjusts insulin infusion in real-time [45]. In the past decade, AP studies have 
165 
advanced from short-term inpatient studies [46], to long-term clinical trials in free-living 
166 
conditions using wearable wireless automated AP systems [47]. Our AP studies have enrolled 
167 
>450 T1DM patients, who used our smartphone-based system for over 280,000 hours. 
168 

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Algorithmic advances and computational platforms from these efforts are at the core of this 
169 
investigation. 
170 
Smartphone based data acquisition and advice delivery platforms: This investigation brings 
171 
together two key pieces of mobile technology to advance T1DM treatment: The Diabetes 
172 
Assistant (DiAs) and Ecological Momentary Assessment (EMA). 
173 
Diabetes Assistant (DiAs): The Diabetes Assistant (DiAs) 
174 
[48-49] platform is a smartphone-based, modular, 
175 
portable device developed at the University of Virginia 
176 
(UVa), in collaboration with the University of Montpellier 
177 
(Figure 1).  DiAs operates on a commercial phone, using a 
178 
specifically modified Android operating system, to enable 
179 
wireless communication with satellite devices like insulin 
180 
pumps, CGMs, and any medical device using a standard 
181 
wireless protocol like BT or BTLE. Its modular architecture 
182 
allows different control modules to be swapped in real 
183 
time, enabling either automated control (CLC) or expert-
184 
decision support systems. The DiAs platform also 
185 
integrates automated data transfer to a secured server, 
186 
enabling cloud functionalities such as remote monitoring 
187 
and patient specific adaptation of treatment [50]. DiAs is 
188 
filed with the FDA (MAF 2109) and has been approved for 
189 
use by adults, adolescents, and children with T1DM in 
190 
over 20 clinical trials. DiAs is a powerful computation platform that enables both local control of 
191 
insulin and cloud applications; it is the most advanced research glucose control platform to date 
192 
and has been deployed for months in home CLC trials. DiAs enables the seamless integration and 
193 
sequential development of modular decision support systems in a form factor assessed by focus 
194 
groups to be acceptable by people with T1DM.  
195 
Leveraging EMA to assess user’s subjective reactions to the decision support system will enable 
196 
the first study with such detailed and dynamic investigation of daily trust levels, psychological, 
197 
and behavioral responses.  
198 
Remote computation and cloud analytics: DiAs is capable of real-time data transmission to secure 
199 
remote servers: the DiAs Web Monitoring (DWM) is a suite of functionalities located on a secure 
200 
server within the UVA Health System network. At its core is a database that receives real-time 
201 
data about the DiAs status, such as CGM, insulin delivered, connectivity status, and algorithm 
202 
status. The system is equipped with a dedicated interface to allow for third party applications to 
203 
•  
 
 
Figure 1: The DiAs system, a mobile Glucose
control platform 

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access data stored on the DWM server. It relies on the HTTP protocol and a Representational 
204 
State Transfer (REST-ful) architecture to provide authenticated users with access to the content 
205 
of the database, formatted as JSON or XML. The API uses a URL-based system of requests to 
206 
target and filter the data sent to the client. Several systems are already connected to DWM [50-
207 
52]. 
208 
Impact of technology trust and acceptance in glycemic control: Trust must be earned; it cannot 
209 
be assumed. The concept of trust plays an important role in an individual’s willingness to engage 
210 
in the use of a medical device.  In its basic definition ‘trust is to depend or rely on another’ [53]. 
211 
The “other” can be another person or a device. Trust and acceptance incorporate several key 
212 
constructs i.e. confidence versus fear, satisfaction versus burden, distress versus improved 
213 
quality of life. Additional factors include perceived usefulness, cost-benefit balance, perceived 
214 
ease of use, or impact on others as well as oneself (positive and negative) [54-55].   
215 
Human factors research indicates that such psychosocial variables play an important role when 
216 
it comes to technology uptake. In CGM, factors predictive of uptake and effectiveness, include 
217 
perceived system reliability and ease-of-use [53,56]. Prior CLC research has also shown that 
218 
clinical trials participants were quick to trust a novel device (CGM, CSII and algorithm), sacrificing 
219 
personal control over diabetes management to the system, whilst a negative experience impeded 
220 
trust, contributing to discontinued use. Other studies of CLC systems have found that, when users 
221 
lack trust, they tend to override the devices, while users who report trust in the system 
222 
experience decreases in diabetes burden and stress [57]. In general, trust is associated with 
223 
positive glycemic outcomes and improved psychosocial functioning and quality of life (QOL) [58]. 
224 
Barriers to trust and continued acceptance include frustration felt when expectations of the 
225 
system are not met; feelings of being overwhelmed by the amount of information provided, or 
226 
negative reactions from the social environment e.g. diabetes-related stigma, possibly resulting in 
227 
a perceived need to explain/justify why a technical device is worn constantly on the body [53]. In 
228 
addition to patients’ perceptions rooted in their previous experience, unrealistic expectations 
229 
may lead to disappointment and discontinuation of the device.  
230 
General ‘tech savviness’ can also play a role in acceptance in that those more familiar and 
231 
comfortable with technology may be more willing to trust the system. Furthermore, the time and 
232 
effort required to invest in building device-related skills, trust and acceptance may be 
233 
underestimated (and often is), as these range from technical handling to integrating the system 
234 
information into one’s diabetes self-management and everyday living without intrusive 
235 
disruptions. Therefore, psychological and behavioral factors play a critical role in the acceptance 
236 
of diabetes technologies and the trust patients put in them. It is crucial to determine the 
237 
psychosocial and behavioral predictors to uptake and continued use of technology in order to aid 
238 

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identification of those individuals most likely to realize benefits of any intervention as well as 
239 
those individuals who may require more support to succeed with technology. Additional 
240 
individual patient’s characteristics (e.g. diabetes belief systems and self-management skills) may 
241 
be predictive of technology acceptance, trust, use, and benefit. At present, little is known about 
242 
psychological, behavioral and social factors that contribute to diabetes technology adoption and 
243 
successful use.  
244 
This investigation will determine psychosocial and behavioral predictors of intervention efficacy, 
245 
providing data and psychological techniques to support future onboarding and successful use of 
246 
the DSS, as well as validate novel mechanisms to track trust and acceptance, allowing future 
247 
systems to adapt to the user’s needs, minimizing potential burden and lifestyle interference, and 
248 
ensuing individualized, person-centered support for optimal glycemic and psychosocial/quality 
249 
of life outcomes. 
250 
Hypothesis: We hypothesize that psycho-behavioral factors are likely to influence system 
251 
acceptance and trust, and ultimately the patients’ success in leveraging the device to achieve 
252 
their individual goals, e.g. better glycemic control with similar burden, or lower treatment burden 
253 
with similar glycemic control. To our knowledge, no technological intervention has been assessed 
254 
in terms of which mode of advice or information delivery is most appropriate to a patient’s 
255 
unique characteristics. Thus, the proposed study is the first to map key psycho-behavioral factors 
256 
to the expert system characteristics that are most beneficial for treatment success.  
257 
Tracking and Quantifying User/System Interactions: This study merges the expert platform 
258 
(DiAs) with software designed to detect, record, and contextualize the interactions between the 
259 
patient and a medical device. This unique combination of established mobile diabetes technology 
260 
and cutting-edge software previously unrelated to diabetes, will allow: (i) systematically record 
261 
treatment behaviors; (ii) track user/system interactions, and (iii) accurately quantify the resulting 
262 
glucose control. The new DiAs-EMA system is a key innovation and a new tool enabling us to 
263 
study the interplay of technology, behavior, and treatment of diabetes. 
264 
Using a tracking system, the investigators will be able to observe each user of the system; this in 
265 
turn allows for an internal quantification of the user level of trust and acceptance and its time 
266 
course.  
267 
Modular Design of Decision Support Systems: The AP and diabetes expert systems are 
268 
assembled from independent (but compatible) modules, each performing a specific control or 
269 
diagnostic function, e.g. prevention of hypoglycemia or postprandial insulin corrections [59-60]. 
270 
This architecture allowed for sequential testing and clinical deployment of AP and DSS 
271 
components and provided a structured framework for networks of control systems [60]. This 
272 

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architecture is fundamental to the goals of this project: we plan to further refine and evaluate a 
273 
layered glucose variability control system activating different modules depending on the stage of 
274 
the proposed study (PF vs DSS). Moreover, a modular system is inherently capable of graceful 
275 
degradation-the capacity to ensure safety even if a module fails. Eventually, this architecture 
276 
would allow the system to adapt its function to maximize system use and adherence, sequentially 
277 
enabling more advanced functions as patients build trust and integrate DSS in their treatment. 
278 
The modules to be included in the PF and DSS have been validated in human clinical trials (see 
279 
1.1.2 Preliminary Data). These modules include: 
280 
• CGM value, trace, and threshold alarms (applicable to SAM & PF & DSS): Similar to 
281 
commercial real-time CGM (e.g. Dexcom G6), this module informs the user of the current 
282 
glucose level and how it has changed recently, enabling treatment decisions. Alerts are set by 
283 
the user to trigger if BG leaves a preset range. 
284 
• Hypoglycemia Risk Indicator (PF & DSS): Based on our group’s work in the 1990s and the 
285 
definition of the glycemic risk ranges [61], we have developed short (1-3 hours), medium (1-3 
286 
days), and long (1-3 weeks) term hypoglycemia risk indices. Prototypes of these modules have 
287 
been evaluated clinically (see Preliminary Data).  
288 
• Insulin Sensitivity Profile & Indicator (PF & DSS): We have designed an algorithm capable of 
289 
tracking changes in insulin sensitivity (SI) and creating daily and monthly SI profiles [62]. We 
290 
additionally validated a real-time SI indicator to inform insulin dosing (e.g. is the patient more 
291 
or less sensitive than usual?) [41].  
292 
• Insulin on Board (PF & DSS): IOB is a key index to avoid insulin stacking and is available to DiAs 
293 
through its insulin pump connectivity. DiAs uses a common 4-6 hours action curve derived 
294 
from encoparesis study [63]. 
295 
• Exercise Advice (DSS): From our modeling work [64], we have derived an advisory module that 
296 
ensures safety of mild to moderate exercise by predicting whether an exercise bout is likely to 
297 
result in hypoglycemia and providing a graded carbohydrate supplementation strategy. See 
298 
clinical validation in [64]. 
299 
• Bedtime Advice (DSS): Similar to the Exercise advisor, this module uses logistic regression and 
300 
recent data (CGM, insulin and meals) to gauge overnight hypoglycemia risk and provide 
301 
bedtime carbohydrate advice. 
302 
• Smart Bolus Calculator (DSS): DSS supports advanced bolus calculation capable of accounting 
303 
for several GV factors such as metabolic characteristics (correction based on 45 min predicted 
304 
glucose to account for insulin delays) and SI fluctuations (insulin sensitivity tracker).  
305 
• Automated Treatment Parameter Optimization (DSS): Based on replay simulation technology 
306 
[42], this optimization routine analyzes the previous 30 days of CGM, insulin, and meal data to 
307 
provide updated insulin treatment parameters (CR, ISF). 
308 

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1.1.2. 
Preliminary Data 
309 
SMBG 
Information-Based 
310 
Decision Support (PF, 2006-
311 
11): We have shown that 
312 
automated 
behavioral 
313 
feedback delivered in the field 
314 
by a portable device can 
315 
optimize glycemic control by 
316 
reducing 
HbA1c 
and/or 
317 
occurrence 
of 
severe 
318 
hypoglycemia [33]. We tested 
319 
the effect of an automated 
320 
system 
providing 
real-time 
321 
estimates of HbA1c, glucose 
322 
variability, 
and 
risk 
for 
323 
hypoglycemia. For 10 months, 
324 
120 
adults 
with 
T1DM, 
325 
performed SMBG and received 
326 
feedback at three increasingly 
327 
complex levels (3 months, each): (i) routine SMBG; (ii) estimated HbA1c, hypo risk, and glucose 
328 
variability; (iii) estimates of symptoms potentially related to hypoglycemia. HbA1c, and 
329 
hypoglycemia were evaluated at baseline and at the end of each level. This information-based 
330 
decision-support reduced HbA1c from 8.0 to 7.6%, p=0.001 (effect confined to subjects with 
331 
baseline HbA1c above 8.0. Incidence of symptomatic moderate/ severe hypoglycemia was 
332 
reduced from 5.72 to 3.74 episodes/person per month (p=0.019), more prominently for subjects 
333 
with history of SH or hypoglycemia unaware (Figure 2). We therefore concluded that feedback of 
334 
SMBG data and summary SMBG-based measures can result in improvement in average glycemic 
335 
control and reduction in moderate/severe hypoglycemia [33]. The system used in this study was 
336 
an early prototype of the PF developed here but leveraging only SMBG data [33]. This 
337 
technological limitation necessitated manual input of high measurement frequencies (4-10 
338 
SMBG per day). This investigation leverages automatically collected high frequency CGM data to 
339 
further improve the usability of the PF system, as well as comparing the effect and acceptability 
340 
of DSS to more prescriptive features. 
341 
Pilot study of Decision Support (DSS, 2012-2017): The feasibility and safety of a prototype DSS 
342 
was tested in 15 women and 9 men with T1DM on insulin pump (N=16) or MDI (N=8), 
343 
 
Figure 2: Results from 1-year automated decision-support intervention
based on SMBG data, with 3 levels of feedback to the patient 
 
5
6
7
8
9
10
Baseline
Level 1
Level 2
Level 3
Baseline A1c < 8.0
Baseline A1c >= 8.0
A: HbA1c Throughout the Study
0
0.1
0.2
0.3
0.4
0.5
Baseline
Level 1
Level 2
Level 3
No history of SH
History of SH
B: Severe Hypoglycemia
(episodes/subject/month)
P=0.001
P<0.005
n.s.
P<0.001
n.s.
P<0.05

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NCT02558491. Age was 37±11 years old, average T1DM duration was 21±11 years. Participants 
344 
were well controlled on average (HbA1c of 7.2±1%). Participants followed a non-blinded 
345 
randomized crossover design, with two 48-hours observation periods where patients were 
346 
exposed to a variety of meals and physical activities to challenge their own control strategies and 
347 
the DSS. DSS was shown to be feasible and safe (no adverse events). Furthermore, GV was 
348 
significantly improved (primary outcome, CGM coefficient of variation) from 0.36±0.08 during 
349 
standard of care to 0.33±0.06 using DSS, p=0.045, with maximum effect during daytime. Further 
350 
GV analysis using the Low and High blood glucose indices (LBGI, HBGI, [65]), confirmed that most 
351 
of the observed improvement was due to the hypoglycemia-related GV measured by the LBGI: 
352 
2.5±2.1 to 1.6±1.3, p=0.042. As depicted in (Figure 3), protection from hypoglycemia was 
353 
improved significantly while using the DSS: median percent time spent below 70mg/dL was 
354 
reduced 3.5-fold, from 3.2% to 0.9%, p=0.018, while maintaining average glycemia 155±27mg/dL 
355 
vs. 155±23mg/dL, p=0.86. [41] 
356 
 
357 
 
358 
 
359 
 
360 
 
361 
 
362 
 
363 
 
364 
 
365 
Ecological Momentary Analysis (EMA): Our research group has a long and prolific history in the 
366 
use of EMA to study associations between glycemic parameters and psychosocial and behavioral 
367 
variables. Our original EMA studies were conducted in the 1980s using pen and paper 
368 
questionnaires completed just before SMBG, 3-5/day over several weeks. We investigated 
369 
numerous aspects of living with T1D, including idiosyncratic symptoms associated with BG 
370 
fluctuations [66-67], patient ability to recognize hypo- and hyperglycemia [68-69], adherence to 
371 
SMBG recommendations, and relationships between BG extremes and mood state [70-71]. In the 
372 
1990s handheld personal computer technology replaced paper for the collection and storage of 
373 
more complex daily diary data with date & time stamps. This technological advance allowed us 
374 
to investigate relationships between diabetes self-management behaviors and BG patterns, as 
375 
well as treatment decision-making (e.g. to drive or not when BG is low) [72-75]. 
376 
Figure 3: Impact of DSS on exposure to hypoglycemia and average glucose. 
Control (grey dots and envelop) and Treatment (black dot and dark grey 
envelop) are linked by the dotted line for each subject. 

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As technology continued to advance, we were able to program daily diaries to include, not only 
377 
questionnaires, but also brief cognitive tasks, which could be timed and scored. In a series of 
378 
studies in the early 2000s [76-79], our group utilized PDAs to investigate cognitive performance 
379 
in real-world settings at different BG levels in adults with T1DM and T2DM [77] and school-aged 
380 
children [79]. Additionally, we conducted studies exploring the relationships between glycemic 
381 
fluctuations and symptoms/moods in patients with T2DM [76] and the ability of young children 
382 
and their parents to recognize hypoglycemia [78]. Leading to our first DSS system. 
383 
Over the past few years, our group has combined EMA approaches with CGM data collection in 
384 
innovative ways to address clinically important questions regarding relationships between BG 
385 
levels and behavioral variables, such as the association between psychological stress and BG 
386 
patterns using CLC algorithms [80]; where we found a small but significant association between 
387 
stress and glycemic instability. In 2017, we used the EMA approach in a study of the accuracy of 
388 
Diabetes Alert Dogs, comparing daily diaries of dog alerts to blinded CGM data [81-82]. That study 
389 
documented that accuracy at detecting hypoglycemia was highly variable across individual dogs 
390 
and highlighted the need for standardized training and performance. Most recently, our team 
391 
has completed a clinical trial using EMAs in a sample of older adults (age > 65) and children with 
392 
T1DM to assess the cognitive impact of CLC; the data collection process was a success, but the 
393 
analysis is still undergoing, and we expect to publish these results by the end of 2020. In addition 
394 
to the above studies, our group also has a long history of using EMA approaches to collect pre- 
395 
and post-intervention data in clinical trials of behavioral interventions [66-69], as proposed here. 
396 
Taken together, there is ample evidence of our group’s experience and expertise with research 
397 
using EMA methods. 
398 
Based on these pilot results, we propose to move forward with demonstrating the superior 
399 
efficacy of a CGM-based advisory system in T1DM, as compared to SAM, and with characterizing 
400 
the impact of psycho-behavioral factors on system performance, which will enable system 
401 
individualization and lead to automated adaptation of advice delivery to optimize glycemic 
402 
control and reduce the system’s psychological impact. 
403 
 
404 
Aim 1 (Control of Glucose Variability) We will confirm and contrast the efficacy of two previously 
405 
designed technological interventions – Personalized Feedback (PF) and Decision Support System 
406 
(DSS) - in reducing GV in T1DM during a 6-month randomized crossover clinical trial. This will 
407 
allow us to show: 
408 

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Aim 1.1 the superiority of the PF over Sensor-augmented mode (SAM) in controlling GV. PF is a 
409 
system designed to provide patients with actionable information about glucose control in general 
410 
and GV in particular (e.g. estimated HbA1c (eA1c), risk of hypoglycemia, and activity level); 
411 
Aim 1.2 the superiority of the DSS over SAM in controlling GV. DSS is a CGM-based system that 
412 
includes PF and further assists with treatment recommendations for common metabolic 
413 
challenges; 
414 
Aim 1.3 the overall non-inferiority of DSS over PF intervention to control GV and superiority of 
415 
DSS to maintain tight glycemic control over time (lower variations of GV in time). 
416 
Aim 2 (personalization of treatment policy) We hypothesize that the participants in this study 
417 
will have technology intervention preferences (e.g. PF or DSS) that can be predicted by key 
418 
psychosocial and behavioral parameters and are prognostic of the level of GV control achievable 
419 
by the intervention. We will: 
420 
Aim 2.1 confirm that technology acceptance and trust are predictive of the level of GV control 
421 
achieved during the study (see Aim 1), regardless of the type of DSS system in use. We 
422 
hypothesize that technology acceptance will correlate negatively with GV: i.e. higher technology 
423 
acceptance leads to lower GV; 
424 
Aim 2.2 explore the impact of technology expectations and experience on the performance of 
425 
each type of technology intervention (SAM, PF, DSS). For example, higher expectation will 
426 
negatively correlate with GV for the SAM treatment, but not the DSS treatment. 
427 
Aim 2.3 assess the correlation between relevant psycho-behavioral traits with the performance 
428 
of PF vs DSS, identifying potential pathways to the corresponding optimal technology-based 
429 
treatment policies. 
430 
 
431 
 
Glycemic outcomes
432 
The primary outcome of this study will be Glucose Variability (GV) as measured by CGM-based 
433 
Coefficient of Variation (CV), as recommended by the International Consensus on Use of 
434 
Continuous Glucose Monitoring. To further characterize glucose control, we will compute other 
435 
CGM Consensus outcomes as well:  
436 
Average  
437 
Percent in different ranges:  
438 
o <50 mg/dL  
439 
o <54 mg/dL  
440 

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o <60 mg/dL  
441 
o <70 mg/dL  
442 
o ≤70-≤180 mg/dL  
443 
o >180 mg/dL  
444 
o >250 mg/dL  
445 
o >300 mg/dL  
446 
 
447 
Each modality of treatment will be assessed using the last 4 weeks of CGM recordings, as we 
448 
expect most of the GV benefits of each intervention to be realized within the first 4 weeks of the 
449 
intervention, and a minimum of 24 days of data is considered optimal for CGM–based CV 
450 
determination.  
451 
1.3.2. 
Glucose Variability Reduction Achieved with CGM-based expert systems 
452 
General linear models (GLM) (repeated measures ANOVA) will be used to assess the significance 
453 
of the differences in average response between SAM, PF, and DSS across appropriate CGM-based 
454 
metrics. The particular design of the clinical study allow for Aims 1.1, 1.2, and 1.3 to each be 
455 
addressed independently in a randomized crossover analysis, as shown in Figure 4. While the 
456 
randomized order of the interventions (escalation vs de-escalation) allows for an objective 
457 
assessment of the average efficacy of each of them, we will introduce the order as a fixed factor 
458 
to verify if significant study effects can be detected. Finally, we will study the evolution of GV 
459 
within each modality period: GV and other CGM-based outcomes will be computed bi-weekly 
460 
(the minimum length of time for precise GV assessment) and entered in a repeated measures 
461 
GLM analysis; within-subject contrast (linear and polynomial) using 5 repeated measures per 
462 
condition to explore the evolution of the glycemic outcomes in time; Aim 1.3.  
463 
 
464 
Figure 4:  Multiple analyses enabled by study design to address Aim 1.1, 1.2 and 1.3 
465 

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1.3.3. 
Exploration of the effect of treatment escalation vs. de-escalation  
466 
A key advantage of the proposed study design (beyond the optimal statistical power) is the 
467 
possibility to explore the glucose control and psycho-behavioral impact of features being added 
468 
and/or enhanced with prescriptive components (DSS), vs. features being limited to information 
469 
(PF) or even removed (SAM). We will perform this analysis by looking at the between factors in 
470 
the repeated ANOVA analysis, contrasting the escalation group vs. de-escalation group. While 
471 
not powered, this analysis will provide key insights in the future feature adaptation schemes 
472 
based on the ATI. 
473 
1.3.4. 
Psychological and Behavioral Questionnaires  
474 
As part of Aim 2, we will conduct robust psychosocial analyses of factors important to participant 
475 
experience. This will examine relevant core constructs of trust, acceptance, satisfaction, 
476 
confidence as well as fear, worries, distress and burden. Validated and reliable measures will be 
477 
used to explore psycho-behavioral characteristics and outcomes in addition to specifically 
478 
adapted measures for SAM and DSS technologies to capture holistic, disease-specific and 
479 
technology-specific data. These questionnaires will evaluate how specific constructs are 
480 
predictive of successful glycemic outcomes associated with DSS. These questionnaires will enable 
481 
us to assess important non-glycemic treatment outcomes that are meaningful to patients 
482 
including those affecting Quality of Life (QOL) (e.g. fear of hypoglycemia and diabetes distress). 
483 
To those ends, participants will complete a battery of questionnaires related to diabetes 
484 
management, treatment satisfaction and QOL at baseline (before system use) and after each 
485 
treatment modality.  
486 
1.3.5. 
Ecological Momentary Assessment Data Collection  
487 
Participants will be trained on the EMA surveys and requirements. During each treatment 
488 
condition, over the course of 2-3 days every two weeks, the participant will be asked to complete 
489 
a “Daily Diary” with 3-5 entries of 3-4 questions each day, for a minimum total of 48 entries per 
490 
participant during each Phase. The DiAs phone will display a text message containing a link to the 
491 
survey. Surveys will be triggered at fixed times, including a morning survey ~1h after waking up 
492 
and an end-of-the-day survey around 8-9 PM. Participants will be able to delay (up to 30 min) or 
493 
skip (up to 2 per day excluding at wake up) surveys for their convenience. Participants will 
494 
respond to questions on a 5-point Likert scale (0=Not at All, 4=Extremely). The first Diary for each 
495 
day will contain two additional items for rating sleep quantity/quality. The Daily Diary questions 
496 
are intended to assess agreement, trust, treatment satisfaction, diabetes burden, self-efficacy, 
497 
mood valence, energy level, physical well-being, and concerns about hypo- and hyperglycemia. 
498 
The first Diary for each day will contain two additional items for rating sleep quantity/quality. 
499 

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1.3.6. 
Mapping of Psycho-behavioral Characteristics to DSS Preferences and Performance  
500 
Baseline assessments of psycho-behavioral traits will be introduced as covariates in the general 
501 
linear model when analyzing the glycemic performance of each treatment modality (SAM, PF, 
502 
DSS). Contrasts will be used to study each pair, specifically SAM vs any advisory system. For 
503 
constructs that can be changed by the intervention itself (e.g. Fear of hypoglycemia) and that are 
504 
therefore measured after each intervention, we will use repeated measures model with within-
505 
subject covariates (MIXED models) to understand their impact on DSS efficacy. This analysis will 
506 
shed light on the relationship between the efficacy of treatment modality and individual patient 
507 
characteristics; Aims 2.1 and 2.2  
508 
Using the cloud data system, we will isolate patient-system interactions for each advisory module 
509 
(e.g. eA1c, predictive hypoglycemia alert), and compute for each subject the probability of the 
510 
interaction to lead to the expected action, and positive glycemic outcomes. These probabilities 
511 
will then be used as outcome variables in separate analysis to assess whether psycho-behavioral 
512 
traits are associated with the acceptance of specific advisory functionalities (e.g. Fear of 
513 
Hypoglycemia could be lowered by the hypoglycemia prediction module); answering Aim 2.3. 
514 
1.3.7. 
Identification and Validation of the Acceptance & Trust Index 
515 
Finally, we will use the validated trust and acceptance measures obtained throughout the 
516 
protocol to validate the dynamic tracking of ATI. The 80 studied subjects will be divided in 4 
517 
cohorts of 20, the first 3 groups used to iteratively refine our estimation procedure (interaction 
518 
quantification and dynamical model parameters) to accurately reproduce acceptance and trust 
519 
fluctuations. The last group will be used to prospectively demonstrate the correlation between 
520 
ATI, trust, and acceptance, thereby addressing Aim 3.2; retrospectively we will use the finalized 
521 
method on all 80 participants to compute the auto-correlation between trust and acceptance 
522 
and ATI and study the ability of ATI to track changes in time; Aim 3.3. Such an index, shown to 
523 
follow the evolution of robustly assessed trust and acceptance (via standard methods) will enable 
524 
future systems to characterize its interactions with its user, detecting early drop in adherence 
525 
and disconnect with patient’s expectation (fault detection), and potentially associating them with 
526 
specific functionalities (fault classification), leading to self-adaptations capable of optimizing 
527 
system use and trust. 
528 
 
529 
This is a randomized crossover study in T1DM designed to demonstrate the efficacy of 
530 
personalized feedback (PF) and decision support (DSS) over sensor-augmented mode (SAM) 
531 
therapy and to establish relationships between the level of glucose variability (GV) control 
532 
achievable by the intervention and individual psycho-behavioral characteristics.  
533 

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We plan to split the study into 4 cohorts of about 25 participants each (expected retention 20 
534 
per cohort). Each cohort will continue for ~7 months and will have the structure presented in 
535 
Figure 5. Following recruitment, screening, and a run-in period of SAM, participants will be 
536 
randomized into one of two groups: escalation vs. de-escalation of devices and function. Each 
537 
treatment modality (SAM, PF, DSS) will continue for about 8 weeks, with the last 4 weeks used 
538 
to assess GV from CGM data.  
539 
 
540 
Figure 5: Study design and timeline 
541 
 
542 
We anticipate recruiting a total of 100 adults aged 18 years and older. An equal numbers of males 
543 
and females will attempt to be recruited and all racial/ethnic groups will be eligible for 
544 
participation. Based on our experience in previous studies of this magnitude, we expect that 80% 
545 
of recruited subjects will complete the entire trial. Enrollment in the study will proceed with the 
546 
goal of completing approximately 80 subjects. Up to 150 participants may sign the consent form. 
547 
Eligibility criteria ensure that the subject will be able to fully deploy the technology in this study. 
548 
Exclusions include any known medical condition that in the judgment of the investigator might 
549 
interfere with the completion of the protocol.  
550 
 
551 
The study will be performed at the University of Virginia. 
 
552 

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 Study Devices 
553 
 
554 
The Diabetes Assistant (DiAs) system which is a medical platform that uses a smart-phone to 
555 
connect to a continuous glucose sensor to insulin pump and run closed-loop control. 
556 
 
557 
For CSII participants, the study system will  include a modified Tandem t:slim X2 insulin pump 
558 
(Tandem Diabetes Care, Inc., San Diego, CA), capable of communicating wirelessly with DiAs 
559 
(t:AP). 
560 
 
561 
The study CGM will include Dexcom G6® transmitter and sensors (Dexcom, Inc., San Diego, CA) 
562 
connected to the Diabetes Assistant (DiAs).  
563 
 
564 
Blood ketone levels will be measured using Precision Xtra® meters and strips (Abbott 
565 
Laboratories Inc., Alemeda, CA) in accordance with the manufacturer’s labeling. The blood 
566 
glucose meter component of the Precision Xtra® will not be used. 
567 
 
568 
 
569 
Figure 6: Study Equipment  
 
570 

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 Study Screening 
571 
 
572 
Before consent has been obtained, participants will be asked inclusion/exclusion criteria 
573 
questions during prescreening to determine study eligibility. Before completing any procedures 
574 
or collecting any data that are not part of usual care, written informed consent will be obtained. 
575 
Potential eligibility may be assessed as part of a routine-care examination.   
576 
 A participant is considered enrolled when the informed consent form has been signed by the 
577 
participant and the study team. 
578 
Consenting procedures and documentation is defined in section 16.3. 
579 
Virtual study visits may take the place of all in-person study visits as deemed feasible by the study 
580 
team.  
581 
 
582 
After informed consent has been signed, a potential participant will be evaluated for study 
583 
eligibility through the elicitation of a medical history, performance of a physical examination 
584 
by licensed study personnel, blood draw and urine pregnancy testing (if applicable) to screen for 
585 
exclusionary medical conditions. 
586 
The following procedures will be performed/data collected/eligibility criteria checked and 
587 
documented:  
588 
• Inclusion and exclusion criteria assessed 
589 
• Demographics (address, date of birth, gender, race, ethnicity) 
590 
• Contact information 
591 
• Diabetic history  
592 
• Medical history  
593 
• Medications  
594 
• Physical examination (may use a medical record within the past 6 months) 
595 
• Weight, height (participant may self-report this information) 
596 
• Vital signs including measurement of blood pressure and pulse (may use a medical record 
597 
within the past 6 months) 
598 
• Urine or serum pregnancy test for all females of child-bearing potential 
599 
• Chemistry panel, liver function tests, and thyroid stimulating hormone 
600 

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• Diabetes Management Information: participant’s typical insulin dosing routine including 
601 
average total daily insulin use (calculated over 1 week), basal rates, carbohydrate ratio(s), 
602 
and correction factor(s) 
603 
Screening procedures will last approximately 2 hours. Once all results of the screening 
604 
evaluations are available, a decision will be made to determine the participant’s eligibility for the 
605 
study or if one or more part of the screening will have to be repeated. If at the first screening or 
606 
repeat screening an exclusionary condition is identified, the participant will be excluded from 
607 
participation with follow up and referred to their primary care physician as needed. The study 
608 
physician may elect to rescreen participants and collect additional laboratory values if their 
609 
clinical situation changes.  
610 
 
611 
The participants must meet all of the following inclusion criteria in order to be eligible to 
612 
participate in the study. 
613 
• Age 18 years and older 
614 
• Clinical diagnosis, based on investigator assessment, of type 1 diabetes for at least one 
615 
year and using insulin for at least one year 
616 
• HbA1c 6.0-11.0%, inclusive 
617 
• Demonstration of proper mental status and cognition for the study 
618 
• If on a non-insulin hyperglycemic therapy, stability on that therapy for the prior 3 months 
619 
and willingness not to alter the therapy for the study duration. 
620 
• For females, not currently known to be pregnant 
621 
• If female and sexually active, must agree to use a highly effective form of contraception 
622 
to prevent pregnancy while a participant in the study.  A negative serum or urine 
623 
pregnancy test will be required for all premenopausal women who are not surgically 
624 
sterile.  Subjects who become pregnant will be discontinued from the study.  Also, 
625 
subjects who during the study develop and express the intention to become pregnant 
626 
within the timespan of the study will be discontinued. 
627 
• 
 Subjects must have Internet access and a computer system that meets the requirements 
628 
for uploading the study equipment and ability to participate in video conferencing. 
629 
• Investigator has confidence that the subject can successfully operate all study devices and 
630 
is capable of adhering to the protocol  
631 

CLINICAL PROTOCOL 
 
 
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632 
The participant must not have any exclusion criteria in order to be eligible to participate in the 
633 
study.  
634 
• NPH (neutral protamine hagedorn) insulin  
635 
• Use of any medication that at the discretion of the investigator is deemed to interfere 
636 
with the trial.  
637 
• Current treatment of a primary seizure disorder  
638 
• Coronary artery disease or heart failure, unless written clearance is received from a 
639 
cardiologist. 
640 
• Hemophilia or any other bleeding disorder 
641 
• A known medical condition, which in the opinion of the investigator or designee, would 
642 
put the participant or study at risk such as the following examples: 
643 
o Inpatient psychiatric treatment in the past 6 months  
644 
o Presence of a known adrenal disorder 
645 
o Abnormal liver function test results (Transaminase >3 times the upper limit of 
646 
normal) 
647 
o Abnormal renal function test results (calculated GFR <60 mL/min/1.73m2).  
648 
o Active gastroparesis requiring medical therapy 
649 
o Uncontrolled thyroid disease (TSH undetectable or >10 mlU/L). 
650 
o Abuse of alcohol or recreational drugs 
651 
o Infectious process not anticipated to be resolved prior to study procedures (e.g. 
652 
meningitis, pneumonia, osteomyelitis, deep tissue infection).  
653 
o Uncontrolled arterial hypertension (Resting diastolic blood pressure >100 mmHg 
654 
and/or systolic blood pressure >180 mmHg). 
655 
o Uncontrolled microvascular complications such as current active proliferative 
656 
diabetic retinopathy defined as proliferative retinopathy requiring treatment (e.g. 
657 
laser therapy or VEGF inhibitor injections) in the past 12 months. 
658 
• A recent injury to body or limb, muscular disorder, use of any medication, any 
659 
carcinogenic disease, or other significant medical disorder if that injury, medication or 
660 
disease in the judgment of the investigator will affect the completion of the protocol. 
661 
• Not familiar with smart phone technology 
662 
• Current use of the following drugs and supplements:   
663 

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o Oral steroids 
664 
o Any other medication that the investigator believes is a contraindication to the 
665 
subject’s participation 
666 
• Participation in another pharmaceutical or device trial at the time of enrollment or during 
667 
the study. 
668 
Screening procedures will last approximately 2 hours. Once all results of the screening 
669 
evaluations are available, a decision will be made to determine the participant’s eligibility for the 
670 
study or if one or more parts of the screening will have to be repeated. If at the first screening or 
671 
repeat screening an exclusionary condition is identified, the participant will be excluded from 
672 
participation with follow up and referred to their primary care physician as needed. The study 
673 
physician may elect to rescreen participants and collect additional laboratory values if their 
674 
clinical situation changes.  
675 
 
676 
If the subject is deemed eligible to participate in the study, the subject will elect to use either 
677 
continuous subcutaneous insulin infusion (CSII) or MDI therapy for the duration of the study, no 
678 
changes are allowed during the study. Furthermore, the participant will elect to use 
679 
carbohydrates counting or not for the computation of the meal bolus, this choice will apply to 
680 
the entire study.   
681 
Participants will then go through a baseline psycho-behavioral assessment. The following 
682 
questionnaires will be completed:  
683 
• Diabetes Specific Personality Questionnaire  
684 
• ABACUS  
685 
• Diabetes Locus of Control  
686 
• Confidence in Diabetes Self-Care Scale  
687 
• Clarke's Hypoglycemia Awareness Scale Participant Inclusion Criteria 
688 
• Demographic Data Survey (screening visit only) 
 
689 

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  Training Visit 
690 
Participants may use CSII or multiple daily insulin (MDI) injection therapy for their diabetes 
691 
management.  Participants will be asked to maintain this treatment throughout the study.  In the 
692 
event that MDI participants elects to change to CSII therapy (see section 3.5), the run-in period 
693 
will include a period of insulin stabilization for up to 6 weeks. The study physician may elect to 
694 
extend this time frame if additional time would be beneficial to the participant.  
695 
If participants intend on identifying carbohydrate counting (carbohydrate ratio, insulin sensitivity 
696 
factor and glucose goal) at mealtime, they will be asked to continue to provide this information 
697 
throughout  the study. 
698 
 
699 
4.1.1. 
Study Continuous Glucose Monitor Training 
700 
A Dexcom G6 CGM will be provided to all participants at the training session. The participants 
701 
will be provided with CGM equipment and instructed to use the study CGM on a daily basis. If 
702 
the participant has prior use of the CGM, re-training will be specific to the individual. The study 
703 
team may elect to have less frequent CGM users watch the Dexcom online training videos 
704 
(https://www.dexcom.com/training-videos) to assist in the training session.  Study staff training 
705 
may include review of study CGM in real-time to make management decisions and how to review 
706 
the data after an upload for retrospective review. Study staff will specifically identify how alarms 
707 
are set using the app and the frequency that these alarms will repeat when enabled.  
708 
The participants personal CGM will be discontinued. The participants will be observed placing the 
709 
sensor and will learn/review how to access the CGM trace. The participants will be asked to 
710 
perform fingerstick blood glucose measurements (if needed) in accordance with the labeling of 
711 
the study CGM device.  
712 
An electronic copy of the CGM user’s guide will be provided for the participants to take home. 
713 
The study team will be sure that the participants will leave the clinic knowing how to properly 
714 
use the CGM. 
715 
Upon request, the study team will provide a Dexcom receiver to allow participants to share their 
716 
CGM data with their personal care providers. 
717 
4.1.2. 
Study Pump (Tandem t:AP) Training (CSII participants) 
718 
Eligible participants will be fully instructed on the study insulin pump. A qualified staff member 
719 
will conduct the training and discuss particular differences from the home pump in important 
720 
aspects such as calculation of insulin on board and correction boluses.  
721 

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Additional training topics are not limited to but may include: infusion site initiation, 
722 
cartridge/priming procedures, setting up the pump, charging the pump, navigation through 
723 
menus, bolus procedures including stopping a bolus, etc. 
724 
The study pump will be programmed with the subject’s usual basal rates and pump parameters. 
725 
The study team will assist the subject in study pump infusion site initiation and will assist the 
726 
subject on starting the study pump.  
727 
The subject’s personal pump will be removed.  
728 
The subject will be supervised with the study pump during at least one meal or snack bolus to 
729 
ensure subject understanding of the pump features. 
730 
The subject will be encouraged to review the literature provided with the pump and infusion sets 
731 
after the training is completed. 
732 
4.1.3. 
DiAs Training 
733 
Prior to initial use, the DiAs will be initialized by a study team member with the participant’s 
734 
individual insulin dosing parameters, including carbohydrate ratio, insulin sensitivity factor and 
735 
basal insulin doses. If applicable, the study team will confirm the carbohydrate counting 
736 
parameters entered in the system with the study physician. 
737 
Qualified study team members will train the subject in performing specific tasks including the 
738 
following: 
739 
• How to view the CGM information including the most recent CGM value, trend arrow, and 
740 
CGM graph.  Low and high threshold alerts will be set. The patient may choose the 
741 
threshold alert values, but the low alert may not be set to <70 mg/dL and the high alert 
742 
may not exceed 300 mg/dL. 
743 
• How to connect the CGM transmitter to DiAs as well as troubleshooting techniques for 
744 
reconnecting. If the CGM values are not available, the subject will be asked to perform 
745 
fingerstick BG measurements for insulin dosing and treatment management.  
746 
• How to start and stop a sensor session with the DiAs APP. 
747 
• [for CSII participants] How to connect the pump to DiAs and troubleshooting steps for 
748 
reconnection.  
749 
• [For MDI participants] How to retroactively inform the system of past insulin doses 
750 
• How to activate the “meal” screen of the DiAs system any time meal insulin or additional 
751 
correction insulin is desired. And how to use the selected bolus calculator (different if 
752 
counting carbohydrates or not, see section 3.5). 
753 

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• How to inform the system of hypoglycemia treatment via a “hypoglycemia treatment” 
754 
button on the DiAs user interface after glucose is consumed that is not accompanied by 
755 
an insulin bolus. 
756 
• What to do when exercising while using the system and how to use a temporary basal 
757 
rate. 
758 
• How to accept DiAs mode changes sent remotely by the study team.  
759 
DiAs instructions will be provided in the study training manual.  
760 
4.1.4. 
Ketone Meter Training 
761 
Subjects will be provided with a study blood ketone meter, test strips, and standard control 
762 
solution to perform QC testing per manufacturer guidelines. QC will be completed prior to subject 
763 
receiving the study ketone meter. Only meters that read within the target range at two 
764 
concentrations per manufacturer labeling will be used in the study. The subject will be instructed 
765 
to contact study staff for a replacement of the meter, test strips, and control solution if a meter 
766 
fails QC testing at home.   
767 
Subjects will be instructed to perform blood ketone testing per the Glycemic Treatment 
768 
Guidelines located in the study training manual. 
769 
 
770 
After randomization, all participants will be trained on how to access and complete EMAs from 
771 
their study phone, how to postpone alerts, and enter a voluntary diary. Participants will be 
772 
informed when the EMAs are scheduled during each phase of the trial.   
773 
 
774 
A home glucagon emergency kit will be required. Participants who currently do not have one will 
775 
be given a prescription for the glucagon emergency kit. 
 
776 

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 Study Procedures 
777 
 
778 
5.1.1. 
Study Support 
779 
Participants will also receive study staff contact information to ask any questions they may have 
780 
during the study. Additionally, participants will be provided with study contact information for 
781 
technical support with DiAs System, the study insulin pump and the study CGM. The participant 
782 
will be asked to call the study team at any time during the study for any health-related issues 
783 
(adverse events), including hypoglycemia <54 mg/dL, frequent highs >300 mg/dL, or ketones ≥3.0 
784 
mmol/L. The participant may use the study pump and study CGM during periods of DiAs 
785 
disconnections or technical difficulties.  
786 
5.1.2. 
Web Conferencing 
787 
Study visits may be completed using HIPAA compliant web conference tool. The study team will 
788 
provide the participant with the meeting information in advance of the appointment.  
789 
 
790 
5.2.1. 
CGM use  
791 
Once all training activities are completed, the participant will be given adequate supplies to 
792 
complete the Run-in home use of the DiAs system in SAM.  
793 
Participants will complete a minimum of 14 days (if CGM use within the preceding 3 months) or 
794 
4 weeks (if no CGM use within the preceding 3 months) of home use of the DiAs system in SAM. 
795 
The study physician may request an additional run-in period of 2 weeks.  
796 
The participant will be informed that in order to be eligible for the study, the DiAs system in SAM 
797 
must be used on a minimum of 11 out of 14 days for CGM users or 22 out of 28 days CGM 
798 
nonusers. 
799 
An appointment for Visit 3 will be scheduled.  
800 
5.2.2. 
Questionnaires 
801 
Participants will be sent the following questionnaires on the final week of the Run-in Period and 
802 
will be asked to complete them within 1 week:                                                                              
803 
• T1-Diabetes Distress Scale    
804 
• Hypoglycemia Fear Survey  
805 

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• Hyperglycemia Avoidance Scale  
806 
 
807 
The participant may complete this visit via web conferencing and/or at the study site. 
808 
5.3.1. 
Eligibility Assessment 
809 
The CGM and insulin data will be reviewed to assess whether the subject has used the DiAs 
810 
system in SAM on at least 11 out of 14 days for CGM users or 22 out of 28 days for non-CGM 
811 
users. Subjects who are unable to meet the CGM and DiAs compliance requirement will be 
812 
withdrawn from the study, unless the investigator believes that there were extenuating 
813 
circumstances that prevented successful completion. In such cases, the investigator may ask the 
814 
participant to repeat this eligibility assessment.  
815 
5.3.2. 
Adverse Event Assessment 
816 
The participant will be asked about any of adverse events, adverse device effects, and device 
817 
issues since the last visit. The participant will also be asked if there were any low BGs <54 mg/dL, 
818 
high BGs >300 mg/dL, or ketones ≥3.0 mmol/L since the last visit. Participants will be encouraged 
819 
to contact the study team between visits as needed (i.e. report adverse events in real-time). 
820 

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 Study Procedures - Escalation 
821 
6.1.1. 
Randomization to Escalation  
822 
Eligible subjects will be randomized to therapy escalation (SAM→PF→DSS).  
823 
A baseline Hemoglobin A1C will be collected. The participant will receive a mode change for 
824 
Phase 1 according to the randomization scheme.  
825 
 
826 
Participants randomized to escalation will have any questions answered about continuing use of 
827 
the DiAs system in SAM. 
828 
6.2.1. 
SAM EMA Surveys  
829 
Over the course of 2-3 days every two weeks of Phase 2, the participant will be asked to complete 
830 
a “Daily Diary” with 3-5 entries of 3-4 questions each day, for a minimum total of 48 entries per 
831 
participant during each Phase.  
832 
6.2.2. 
Phase 1 Initiation Questionnaires 
833 
Participants randomized to escalation will complete the following questionnaires: 
834 
• Pittsburgh Sleep Quality Index  
835 
Once all training activities are completed, the participant will be given adequate supplies and 
836 
study devices to last until the subsequent clinic visit. An appointment for Visit 4 will be scheduled 
837 
 
838 
The participant will complete a minimum of 8 weeks of DiAs use in Phase 1 Mode at home. During 
839 
the course of Phase 1, participants will complete EMA surveys and post-phase questionnaires. 
840 
6.3.1. 
Phase 1 EMA Surveys 
841 
Over the course of 2-3 days every two weeks of Phase 1, the participant will be asked to complete 
842 
a “Daily Diary” with 3-5 entries of 3-4 questions each day, for a minimum total of 48 entries per 
843 
participant during each Phase.  
844 
6.3.2. 
Post-Phase 1 Questionnaires Week 7 
845 
Participants randomized to escalation will be sent the following questionnaires on week 7 (day 
846 
42 of Phase 1) and will be asked to complete them within 1 week: 
847 
• Pittsburgh Sleep Quality Index   
848 

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• Hyperglycemia Avoidance Scale  
849 
6.3.3. 
Post-Phase 1 Questionnaires Week 8 
850 
Participants randomized to escalation will sent the following questionnaires on week 8 (day 49 
851 
of Phase 1) and will be asked to complete them within 1 week: 
852 
• Confidence in Diabetes Self-Care Scale  
853 
• T1-Diabetes Distress Scale  
854 
• Hypoglycemia Fear Survey  
855 
 
856 
All participants in each randomization scheme use PF in Phase 2. Phase 2 initiation may be 
857 
conducted either via web conference or an office visit. The participant will remotely receive a 
858 
mode change for Phase 2. Study staff will review the features of the Personalized Feedback (PF) 
859 
mode and answer any questions. Participant will have a blood/urine pregnancy test that must be 
860 
negative in order to continue to participate in this study. 
861 
6.4.1. 
Training on Phase 2 DiAs Mode 
862 
The participant will be trained on the following features of the Personalized Feedback System: 
863 
• Tracking of estimated HbA1c: When properly calibrated, eA1c is within 0.3% of 
864 
reference HbA1c on average, and within 1% of HbA1c >95% of the time. 
865 
• Hypoglycemia Risk Indicator: Provides an indication of the current risk for 
866 
hypoglycemia. 
867 
• Insulin Sensitivity Profile & Indicator: Tracks changes in insulin sensitivity (SI) and 
868 
creates daily and monthly SI profiles. 
869 
• Insulin on Board: Tracks active insulin to avoid insulin stacking using a common 4-6 hour 
870 
action curve. 
871 
• Personalized weekly feedback. Provides advice to the user on what went well in terms 
872 
of glycemic control and system use in the past week and what may be a good thing to 
873 
focus on for the following week. 
874 
6.4.2. 
Phase 2 Initiation Questionnaires 
875 
Participants randomized to escalation will complete the following questionnaires: 
876 
• Technology Expectations (burdens subscale only)  
877 
• INSPIRE (revised for DSS)  
878 

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6.4.3. 
Adverse Event Assessment 
879 
The participant will be asked about any of adverse events, adverse device effects, and device 
880 
issues since the last visit. The participant will also be asked if there were any low BGs <54 mg/dL, 
881 
high BGs >300 mg/dL, or ketones ≥3.0 mmol/L since the last visit. 
882 
Once all training activities are completed, the participant will be given adequate supplies and 
883 
study devices to last until the subsequent clinic visit. An appointment for Visit  5 will be scheduled. 
884 
Participants will be encouraged to contact the study team between visits as needed (i.e. report 
885 
adverse events in real-time).  
886 
 
887 
The participant will complete a minimum of 8 weeks of DiAs use in Phase 2 Mode at home.  
888 
During the course of Phase 2, participants will complete EMA surveys and post-phase 
889 
questionnaires. 
890 
6.5.1. 
Phase 2 EMA Surveys 
891 
Over the course of 2-3 days every two weeks of Phase 2, the participant will be asked to complete 
892 
a “Daily Diary” with 3-5 entries of 3-4 questions each day, for a minimum total of 48 entries per 
893 
participant during each Phase.  
894 
6.5.2. 
Post-Phase 2 Questionnaires Week 7 
895 
All participants will be sent the following questionnaires on week 7 (day 42 of Phase 2) and will 
896 
be asked to complete them within 1 week: 
897 
• Technology Acceptance (burdens subscale only)  
898 
• Pittsburgh Sleep Quality Index  
899 
• T1-Diabetes Distress Scale  
900 
6.5.3. 
Post-Phase 2 Questionnaires Week 8 
901 
All participants will be sent the following questionnaires on week 8 (day 49 of Phase 2) and will 
902 
be asked to complete them within 1 week: 
903 
• Hypoglycemia Fear Survey  
904 
• Hyperglycemia Avoidance Scale  
905 
• Confidence in Diabetes Self-Care Scale  
906 

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907 
The participant will begin Phase 3 according to the randomization scheme either via web 
908 
conference or an office visit. The participant will remotely receive a mode change for Phase 3. 
909 
Study staff will review the features of the Phase 3 system and answer any questions. Participant 
910 
will have a blood/urine pregnancy test that must be negative in order to continue to participate 
911 
in this study. 
912 
6.6.1. 
Training on Phase 3 DiAs Mode  
913 
Participants randomized to escalation will be trained to use DiAs in DSS mode, including the 
914 
following features: 
915 
• Exercise Advice: An advisory module that ensures safety of mild to moderate exercise 
916 
by predicting whether an exercise bout is likely to result in hypoglycemia and providing 
917 
a graded carbohydrate supplementation strategy and possible reduction in insulin 
918 
advice. 
919 
• Bedtime Advice: Gauges overnight hypoglycemia risk and provides bedtime 
920 
carbohydrate advice. 
921 
• Smart Bolus Calculator: An advanced bolus calculator capable of accounting for several 
922 
factors such as exercise (activity on board), metabolic characteristics (correction based 
923 
on 45 min predicted glucose to account for insulin delays) and SI fluctuations (insulin 
924 
sensitivity tracker).  
925 
• Treatment Parameter Optimization: An optimization routine that analyzes the previous 
926 
30 days of CGM, insulin, and meal data to provide updated insulin treatment 
927 
parameters (CR, CF, and basal rate) to minimize glycemic risk.  
928 
6.6.2. 
Phase 3 Initiation Questionnaires 
929 
Participants randomized to escalation will complete the following questionnaires: 
930 
• Technology Expectations (burdens subscale only)  
931 
• INSPIRE (revised for DSS)  
932 
• Diabetes Locus of Control  
933 
6.6.3. 
Adverse Event Assessment 
934 
 The participant will be asked about any of adverse events, adverse device effects, and device 
935 
issues since the last visit. The participant will also be asked if there were any low BGs <54 mg/dL, 
936 
high BGs >300 mg/dL, or ketones ≥3.0 mmol/L since the last visit. Participants will be encouraged 
937 
to contact the study team between visits as needed (i.e. report adverse events in real-time). 
938 

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939 
The participant will complete a minimum of 8 weeks of Phase 3 at home. During the course of 
940 
Phase 3, participants will complete EMA surveys and post-phase questionnaires. 
941 
6.7.1. 
Phase 3 EMA Surveys 
942 
Over the course of 2-3 days every two weeks of Phase 3, the participant will be asked to complete 
943 
a “Daily Diary” with 3-5 entries of 3-4 questions each day, for a minimum total of 48 entries per 
944 
participant during each Phase. 
945 
6.7.2. 
Post-Phase 3 Questionnaires Week 7 
946 
Participants randomized to escalation will be sent the following questionnaires on week 7 (day 
947 
42 of Phase 1) and will be asked to complete them within 1 week: 
948 
• Technology Acceptance (burdens subscale only)  
949 
• Pittsburgh Sleep Quality Index.  
950 
• T1-Diabetes Distress Scale  
951 
6.7.3. 
Post-Phase 3 Questionnaires Week 8 
952 
Participants randomized to escalation will sent the following questionnaires on week 8 (day 49 
953 
of Phase 3) and will be asked to complete them within 1 week: 
954 
• Hypoglycemia Fear Survey 
955 
• Hyperglycemia Avoidance Scale  
956 
• Confidence in Diabetes Self-Care Scale  
957 
 
958 
Participants will participate in a Study Exit visit either via web conference or an office visit. 
959 
Participants will return to their standard diabetes care using their personal equipment.  The study 
960 
team will be available to answer questions about insulin parameters.   
961 
The participant will be asked to return all investigational study devices (e.g. study insulin pump, 
962 
study, CGM, study phone, other associated supplies) either via mail or at an office visit. 
963 
Participants may keep the study glucometer and ketone meter. 
964 
6.8.1. 
Study Exit Questionnaires 
965 
Participants randomized to escalation will complete the following questionnaires: 
966 
• ABACUS  
967 

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• INSPIRE (revised for DSS)  
968 
• Diabetes Locus of Control  
969 
6.8.2. 
Adverse Event Assessment 
970 
The participant will be asked about any of adverse events, adverse device effects, and device 
971 
issues since the last visit. The participant will also be asked if there were any low BGs <54 mg/dL, 
972 
high BGs >300 mg/dL, or ketones ≥3.0 mmol/L since the last visit. 
973 
 
974 
Approximately 48 hours after the home use of the equipment, the study team will contact the 
975 
participant via phone/email/text to assess:  
976 
• Adverse events, adverse device effects, and device issues  
977 
• Blood glucose values <60 mg/dL and >300 mg/dL  
 
978 

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 Study Procedures – De-Escalation 
979 
 
980 
Eligible subjects will be randomized to therapy de-escalation (DSS→PF→SAM).  
981 
A baseline Hemoglobin A1C will be collected.   
982 
The participant will receive a mode change for Phase 1 according to the randomization scheme.  
983 
 
984 
Participants randomized to de-escalation will be trained to use DiAs in DSS mode, including the 
985 
following features: 
986 
• Exercise Advice: An advisory module that ensures safety of mild to moderate exercise by 
987 
predicting whether an exercise bout is likely to result in hypoglycemia and providing a 
988 
graded carbohydrate supplementation strategy and possible reduction in insulin advice. 
989 
• Bedtime Advice: Gauges overnight hypoglycemia risk and provides bedtime carbohydrate 
990 
advice. 
991 
• Smart Bolus Calculator: An advanced bolus calculator capable of accounting for several 
992 
factors such as exercise (activity on board), metabolic characteristics (correction based 
993 
on 45 min predicted glucose to account for insulin delays) and SI fluctuations (insulin 
994 
sensitivity tracker).  
995 
• Treatment Parameter Optimization: An optimization routine that analyzes the previous 
996 
30 days of CGM, insulin, and meal data to provide updated insulin treatment parameters 
997 
(CR, CF, and basal rate) to minimize glycemic risk.  
998 
7.2.1. 
Phase 1 EMA Surveys 
999 
Over the course of 2-3 days every two weeks of Phase 2, the participant will be asked to complete 
1000 
a “Daily Diary” with 3-5 entries of 3-4 questions each day, for a minimum total of 48 entries per 
1001 
participant during each Phase.  
1002 
7.2.2. 
Phase 1 Initiation Questionnaires 
1003 
Participants randomized to de-escalation will complete the following questionnaires: 
1004 
• Pittsburgh Sleep Quality Index  
1005 
• Technology Expectations (burdens subscale only)  
1006 
• INSPIRE (revised for DSS)  
1007 
Once all training activities are completed, the participant will be given adequate supplies and 
1008 
study devices to last until the subsequent clinic visit. An appointment for Visit 4 will be scheduled.  
1009 

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1010 
The participant will complete a minimum of 8 weeks of DiAs use in Phase 1 Mode at home. During 
1011 
the course of Phase 1, participants will complete EMA surveys and post-phase questionnaires. 
1012 
7.3.1. 
Phase 1 EMA Surveys 
1013 
Over the course of 2-3 days every two weeks of Phase 1, the participant will be asked to complete 
1014 
a “Daily Diary” with 3-5 entries of 3-4 questions each day, for a minimum total of 48 entries per 
1015 
participant during each Phase.  
1016 
7.3.2. 
Post-Phase 1 Questionnaires Week 7 
1017 
Participants randomized to de-escalation will be sent the following questionnaires on week 7 
1018 
(day 42 of Phase 1) and will be asked to complete them within 1 week: 
1019 
• Technology Acceptance (burdens subscale only) 
1020 
• Pittsburgh Sleep Quality Index  
1021 
• T1-Diabetes Distress Scale  
1022 
7.3.3. 
Post-Phase 1 Questionnaires Week 8 
1023 
Participants randomized to de-escalation will be sent the following questionnaires on week 8 
1024 
(day 49 of Phase 1) and will be asked to complete them within 1 week: 
1025 
• Hypoglycemia Fear Survey  
1026 
• Hyperglycemia Avoidance Scale  
1027 
• Confidence in Diabetes Self-Care Scale  
1028 
 
1029 
All participants in each randomization scheme use PF in Phase 2. Phase 2 initiation may be 
1030 
conducted either via web conference or an office visit. The participant will remotely receive a 
1031 
mode change for Phase 2. Study staff will review the features of the Personalized Feedback (PF) 
1032 
mode and answer any questions.  
1033 
7.4.1. 
Training on Phase 2 DiAs Mode 
1034 
The participant will be trained on the following features of the Personalized Feedback System: 
1035 
• Tracking of estimated HbA1c: When properly calibrated, eA1c is within 0.3% of reference 
1036 
HbA1c on average, and within 1% of HbA1c >95% of the time. 
1037 
• Hypoglycemia Risk Indicator: Provides an indication of the current risk for hypoglycemia. 
1038 

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• Insulin Sensitivity Profile & Indicator: Tracks changes in insulin sensitivity (SI) and creates 
1039 
daily and monthly SI profiles. 
1040 
• Insulin on Board: Tracks active insulin to avoid insulin stacking using a common 4-6 hour 
1041 
action curve. 
1042 
• Personalized weekly feedback. Provides advice to the user on what went well in terms of 
1043 
glycemic control and system use in the past week and what may be a good thing to focus 
1044 
on for the following week. 
1045 
7.4.2. 
Phase 2 Initiation Questionnaires 
1046 
Participants randomized to de-escalation will complete the following questionnaires: 
1047 
• Technology Expectations (burdens subscale only)  
1048 
• INSPIRE (revised for DSS)  
1049 
• Diabetes Locus of Control  
1050 
7.4.3. 
AE Assessment 
1051 
The participant will be asked about any of adverse events, adverse device effects, and device 
1052 
issues since the last visit. The participant will also be asked if there were any low BGs <54 mg/dL, 
1053 
high BGs >300 mg/dL, or ketones ≥3.0 mmol/L since the last visit. 
1054 
Once all training activities are completed, the participant will be given adequate supplies and 
1055 
study devices to last until the subsequent clinic visit. An appointment for Visit 5 will be scheduled.  
1056 
 
1057 
The participant will complete a minimum of 8 weeks of DiAs use in Phase 2 Mode at home.  
1058 
During the course of Phase 2, participants will complete EMA surveys and post-phase 
1059 
questionnaires. 
1060 
7.5.1. 
Phase 2 EMA Surveys 
1061 
Over the course of 2-3 days every two weeks of Phase 2, the participant will be asked to complete 
1062 
a “Daily Diary” with 3-5 entries of 3-4 questions each day, for a minimum total of 48 entries per 
1063 
participant during each Phase.  
1064 
7.5.2. 
Post-Phase 2 Questionnaires Week 7 
1065 
All participants will be sent the following questionnaires on week 7 (day 42 of Phase 2) and will 
1066 
be asked to complete them within 1 week: 
1067 
• Technology Acceptance (burdens subscale only)  
1068 

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• Pittsburgh Sleep Quality Index  
1069 
• T1-Diabetes Distress Scale  
1070 
7.5.3. 
Post-Phase 2 Questionnaires Week 8 
1071 
All participants will be sent the following questionnaires on week 8 (day 49 of Phase 2) and will 
1072 
be asked to complete them within 1 week: 
1073 
• Hypoglycemia Fear Survey  
1074 
• Hyperglycemia Avoidance Scale  
1075 
• Confidence in Diabetes Self-Care Scale  
1076 
 
1077 
The participant will begin Phase 3 according to the randomization scheme either via web 
1078 
conference or an office visit. The participant will remotely receive a mode change for Phase 3. 
1079 
Study staff will review the features of the Phase 3 system and answer any questions.  
1080 
7.6.1. 
Training on Phase 3 DiAs Mode  
1081 
Participants randomized to de-escalation will have any questions answered about resuming use 
1082 
of the DiAs system in SAM. 
1083 
7.6.2. 
Phase 3 Initiation Questionnaires 
1084 
Participants randomized to de-escalation will complete the following questionnaires:  
1085 
• INSPIRE (revised for DSS)  
1086 
• Diabetes Locus of Control  
1087 
7.6.3. 
Adverse Event Assessment 
1088 
The participant will be asked about any of adverse events, adverse device effects, and device 
1089 
issues since the last visit. The participant will also be asked if there were any low BGs <54 mg/dL, 
1090 
high BGs >300 mg/dL, or ketones ≥3.0 mmol/L since the last visit. 
1091 
Once all training activities are completed, the participant will be given adequate supplies and 
1092 
study devices to last until the subsequent clinic visit. An appointment for Visit 6 will be scheduled. 
1093 
Participants will be encouraged to contact the study team between visits as needed (i.e. report 
1094 
adverse events in real-time). 
1095 
 
1096 
The participant will complete a minimum of 8 weeks of Phase 3 at home. During the course of 
1097 
Phase 3, participants will complete EMA surveys and post-phase questionnaires. 
1098 

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7.7.1. 
Phase 3 EMA Surveys 
1099 
Over the course of 2-3 days every two weeks of Phase 3, the participant will be asked to complete 
1100 
a “Daily Diary” with 3-5 entries of 3-4 questions each day, for a minimum total of 48 entries per 
1101 
participant during each Phase. 
1102 
7.7.2. 
Post-Phase 3 Questionnaires Week 7 
1103 
Participants randomized to de-escalation will be sent the following questionnaires on week 7 
1104 
(day 42 of Phase 1) and will be asked to complete them within 1 week: 
1105 
• Pittsburgh Sleep Quality Index  
1106 
• T1-Diabetes Distress Scale  
1107 
7.7.3. 
Post-Phase 3 Questionnaires Week 8 
1108 
Participants randomized to de-escalation will be sent the following questionnaires on week 8 
1109 
(day 49 of Phase 1) and will be asked to complete them within 1 week: 
1110 
• Hypoglycemia Fear Survey  
1111 
• Hyperglycemia Avoidance Scale (HAS)  
1112 
• Confidence in Diabetes Self-Care Scale  
1113 
 
1114 
Participants will participate in a Study Exit visit either via web conference or an office visit. 
1115 
Participants will return to their standard diabetes care using their personal equipment.  The study 
1116 
team will be available to answer questions about insulin parameters.   
1117 
The participant will be asked to return all investigational study devices (e.g. study insulin pump, 
1118 
study, CGM, study phone, other associated supplies) either via mail or at an office visit. 
1119 
Participants may keep the study glucometer and ketone meter. 
1120 
7.8.1. 
Study Exit Questionnaires 
1121 
Participants randomized to de-escalation will complete the following questionnaires:  
1122 
• ABACUS  
1123 
7.8.2. 
Adverse Event Assessment 
1124 
The participant will be asked about any of adverse events, adverse device effects, and device 
1125 
issues since the last visit. The participant will also be asked if there were any low BGs <54 mg/dL, 
1126 
high BGs >300 mg/dL, or ketones ≥3.0 mmol/L since the last visit.  
1127 

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1128 
Approximately 48 hours after the home use of the equipment, the study team will contact the 
1129 
participant via phone/email/text to assess:  
1130 
• Adverse events, adverse device effects, and device issues  
1131 
• Blood glucose values <60 mg/dL and >300 mg/dL  
 
1132 

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 Testing Procedures 
1133 
 
1134 
8.1.1. 
HbA1c  
1135 
• A blood sample will be obtained at screening to obtain a baseline hemoglobin A1c level.  
1136 
• HbA1c level may be measured by study team using the DCA2000, a comparable point of 
1137 
care device, at time of screening  
1138 
• Labs may be obtained at a local laboratory (e.g. LabCorp) convenient to the participant. 
1139 
• Blood test may be obtained within 14 days prior to enrollment may be used for eligibility 
1140 
purposes.   
1141 
• Sample collected at randomization and end of study will be used for statistical purposes.  
1142 
8.1.2. 
Comprehensive Metabolic Panel 
1143 
• A blood sample will be obtained at screening to assess kidney and liver functioning.  
1144 
• Labs may be obtained at a local laboratory (e.g. LabCorp) convenient to the participant. 
1145 
• Blood test may be obtained within 14 days prior to enrollment may be used for eligibility 
1146 
purposes. 
1147 
8.1.3. 
Thyroid Stimulating Hormone 
1148 
• A blood sample will be obtained at screening to assess thyroid function.  
1149 
• Labs may be obtained at a local laboratory (e.g. LabCorp) convenient to the participant. 
1150 
• Blood test may be obtained within 14 days prior to enrollment may be used for eligibility 
1151 
purposes.   
1152 
8.1.4. 
Pregnancy Test 
1153 
A blood/urine pregnancy test will be required for women of childbearing potential at the 
1154 
screening visit, and between each phase .  Tests must be negative to participate in the study.  
1155 

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 Questionnaires & Ecological Momentary Analysis 
1156 
 
1157 
The Diabetes Specific Personality Questionnaire is based on the original Six Factor Personality 
1158 
Questionnaire [81], a well-validated measure that was adapted for the diabetes-specific version 
1159 
of the questionnaire. The Six Factor Personality Questionnaire is a measure of six personality 
1160 
dimensions each consisting of three facet scales, measured by 108 Likert items. The Six Factor 
1161 
Personality Questionnaire facet scales are organized in terms of six factor scales.  The Diabetes 
1162 
Specific Personality Questionnaire assesses three personality factors – conscientiousness, 
1163 
obsessive-compulsiveness, and openness. In this study, the Diabetes Specific Personality 
1164 
Questionnaire is used to explore whether personality type is associated with willingness and/or 
1165 
ability to effectively engage with the DSS. Administration time is approximately 15 minutes. 
1166 
 
1167 
This is a structured interview used to provide a very brief assessment of carbohydrate counting 
1168 
and diabetes self-management skills important to effective engagement consisting of a series of 
1169 
25 questions assessing health literacy and health numeracy in people with T1DM [84].. The 
1170 
interviewer evaluates the subject answer to each question on a scale ranging from 1 (No 
1171 
competency) to 3 (Full competency); the sum yields to a total score. The higher the score, the 
1172 
higher the levels of health literacy and numeracy of the subject. Administration time is 
1173 
approximately 10-20 minutes. 
1174 
 
1175 
This questionnaire [85] was developed for use on adults (18-80 y.o.) The scale consists of 18 items 
1176 
measuring the individual’s personal beliefs about their control over their diabetes management 
1177 
and outcome: 6 items measuring internal locus of control, 6 items measuring powerful others 
1178 
locus of control, and 6 items measuring chance locus of control. A 6-point Likert-type scale is used 
1179 
in which 0 indicates ‘strongly disagree with the statement’ and 5 indicates ‘strongly agree with 
1180 
the statement.’ Administration time is approximately 5 minutes. 
1181 
 
1182 
This is a short 20-item self-report questionnaire assessing self-efficacy, the perceived ability to 
1183 
perform diabetes self-care tasks, in patients with T1DM [87]. Items are constructed to cover all 
1184 
domains of self-care as well as social skills. Each item is preceded by, “I believe I can…” with the 
1185 
strength of this belief rated on a 5-point Likert scale ranging from 1 (“No, I am sure I cannot”) to 
1186 
5 (“Yes, I am sure I can”). Administration time is approximately 10 minutes. 
1187 

CLINICAL PROTOCOL 
 
 
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1188 
The scale comprises eight questions characterizing the participant's level of hypoglycemia 
1189 
awareness, as well as risk for exposure to episodes of moderate and severe hypoglycemia [88]. 
1190 
It also examines the glycemic threshold for symptomatic responses to hypoglycemia. A score of 
1191 
four or more on a scale of 0 to 7 implies impaired awareness of hypoglycemia. Administration 
1192 
time is approximately 5 minutes. 
1193 
 
1194 
This is a measure that reflects diabetes-specific quality of life and emotional well-being [90]. The 
1195 
Diabetes Distress Scale is a measure of diabetes-related distress over a number of domains (e.g. 
1196 
diabetes management regimen, interpersonal distress) and consists of a scale of 17 items. These 
1197 
include items from each of four domains central to diabetes-related emotional distress. Patients 
1198 
rate the degree to which each item is currently problematic for them on a 6-point Likert scale, 
1199 
from 1 (no problem) to 6 (serious problem). Administration time is approximately 5 minutes. 
1200 
 
1201 
This questionnaire will be used to determine if the PF and DSS is associated with reduced fear of 
1202 
hypoglycemia. The Hypoglycemia Fear Survey-II [91] was developed to measure behaviors and 
1203 
worries related to fear of hypoglycemia in adults with T1DM. It is composed of 2 subscales, the 
1204 
Behavior and Worry. Behavior items describe behaviors in which patients may engage to avoid 
1205 
hypoglycemic episodes and/or their negative consequences (e.g., keeping blood glucose levels 
1206 
higher, making sure other people are around, and limiting exercise or physical activity). Worry 
1207 
items describe specific concerns that patients may have about their hypoglycemic episodes (e.g., 
1208 
being alone, episodes occurring during sleep, or having an accident). Items are rated on a 5-point 
1209 
Likert scale (0=never, 4=always), with higher scores indicating higher fear of hypoglycemia. 
1210 
Administration time is approximately 10 minutes. 
1211 
 
1212 
This measure is used to assess the extent of potentially problematic avoidant attitudes and 
1213 
behaviors in people with T1DM [91]. The Hypoglycemia Avoidance Scale reliably quantifies 
1214 
affective and behavioral aspects of hyperglycemia avoidance and is used to assess the extent of 
1215 
potentially problematic avoidant attitudes and behaviors regarding hyperglycemia in people with 
1216 
T1DM.  It has 24 items plus two additional optional items asking about the highest level of daily 
1217 
blood glucose or HbA1c measures the individual would feel comfortable having. Administration 
1218 
time is approximately 10 minutes. 
1219 

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1220 
This questionnaire will be used to assess whether the PF and DSS improve sleep quality and 
1221 
quantity. The Pittsburgh Sleep Quality Index [93] is a self-report questionnaire that assesses sleep 
1222 
quality over a 1-month time interval. The measure consists of 19 individual items, creating 7 
1223 
components that produce one global score: the higher the global score, the poorer the sleep 
1224 
quality. Administration time is approximately 5-10 minutes. 
1225 
 
1226 
The Technology Acceptance Surveys [94-95] were developed for an artificial pancreas camp study 
1227 
in adolescents. The 38 items in the questionnaire were based on interviews conducted with 
1228 
individuals who had participated in previous artificial pancreas trials about their experience 
1229 
regarding the device. It was subsequently adapted to assess these same measures for the PF and 
1230 
DSS. It assesses both positive and negative experiences with PF and DSS, including blood glucose 
1231 
management, device burden, and overall satisfaction. Items are rated on a 5-point scale. In this 
1232 
study only the burden subscale will be used.  The Technology Expectations Survey has the same 
1233 
items included on the Technology Acceptance Survey but asks whether the individual expects to 
1234 
experience the various benefits and burdens from use of a device. Administration time is 
1235 
approximately 10 minutes. 
1236 
 
1237 
This questionnaire will be used to assess patient preferences to support effective onboarding and 
1238 
successful continued use of the PF and DSS. The INSPIRE survey was developed to assess various 
1239 
aspects of a user’s experience regarding automated insulin delivery for both patients and family 
1240 
members. The surveys include various topics important to patients with T1DM and their family 
1241 
members based upon >200 hours of qualitative interviews and focus groups. It was adapted by 
1242 
its developer for use with the PF and DSS. The survey includes 22 items. Response options include 
1243 
a 5-point Likert scale from strongly agree to strongly disagree, along with an N/A option.  
1244 
Administration time is approximately 5 minutes.  
1245 
 
1246 
In addition to the behavioral data automatically recorded (e.g. insulin dosing, interactions with 
1247 
system), an EMA procedure will be used to track the users’ daily experiences of trust in the 
1248 
system, emotional well-being, treatment satisfaction, and diabetes-related concerns and burden.  
1249 
Using a brief daily survey, we will capture the dynamic changes in participant experience 
1250 
throughout the day and the associations between users’ subjective experience and their 
1251 
reactions to/interactions with the PF and DSS devices. This will be the first use of EMA with 
1252 
decision support systems. 
1253 

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During each treatment condition, over the course of 2-3 days every two weeks, the participant 
1254 
will be asked to complete a “Daily Diary” with 3-5 entries of 3-4 questions each day, for a 
1255 
minimum total of 48 entries per participant during each Phase.  
1256 
The DiAs phone will display a text message containing a link to the survey. Surveys will be 
1257 
triggered at fixed times, including a morning survey ~1h after waking up and an end-of-the-day 
1258 
survey around 8-9 PM. Participants will be able to delay (up to 30 min) or skip (up to 2 per day 
1259 
excluding at wake up) surveys for their convenience.  
1260 
Participants will respond to questions on a 5-point Likert scale (0=Not at All, 4=Extremely). The 
1261 
first Diary for each day will contain two additional items for rating sleep quantity/quality. 
1262 
The Daily Diary questions are shown below and are intended to assess agreement, trust, 
1263 
treatment satisfaction, diabetes burden, self-efficacy, mood valence, energy level, and physical 
1264 
well-being. 
1265 
• Quality of Life Parameters 
1266 
 
At this moment, to what extent do you feel... 
1267 
 Burdened by your diabetes treatment? 
1268 
 Worried about your blood sugar levels? 
1269 
 In a positive or good mood? 
1270 
 Physically well?  
1271 
• Sleep Items (only presented in the first Diary for each day) 
1272 
 
Was your sleep last night… 
1273 
 Long enough? 
1274 
 Restful enough? 
1275 
• Technology acceptance (only presented in the last Diary for each day) 
1276 
 
Today to what extent have you... 
1277 
 Found (name of program) easy to use? 
1278 
 Found (name of program) useful? 
1279 
 Trusted the information given by (name of program)? 
1280 
 Found (name of program) easy to use? 
1281 
 Found (name of program) useful? 
1282 
 Trusted the information given by (name of program)? 
 
1283 

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1284 
 
 
1285 
Timing 
Escalation 
De-escalation 
Visit 1 – Screening and 
Questionnaires 
Diabetes Specific Personality Questionnaire 
ABACUS 
Diabetes Locus of Control 
Confidence in Diabetes Self-Care Scale 
Clarke's Hypoglycemia Awareness Scale 
Visit 2 – Study Equipment 
Training 
None 
Final week of SAM Run-in 
T1-Diabetes Distress Scale 
Hypoglycemia Fear Survey 
Hyperglycemia Avoidance Scale 
Visit 3 Eligibility Assessment, 
Randomization and Training 
Pittsburgh Sleep Quality Index  
 
Pittsburgh Sleep Quality Index  
Technology Expectations (burdens subscale only)  
INSPIRE  
DiAs Use in Phase 1 Mode 
EMA Surveys 
EMA Surveys 
Week 7 of DiAs Use in Phase 
1 Mode 
Pittsburgh Sleep Quality  
Hyperglycemia Avoidance Scale  
Technology Acceptance (burdens subscale only)  
Pittsburgh Sleep Quality Index 
T1-Diabetes Distress Scale  
Week 8 of DiAs Use in Phase 
1 Mode 
Confidence in Diabetes Self-Care  
T1-Diabetes Distress Scale  
Hypoglycemia Fear Survey  
Hypoglycemia Fear Survey  
Hyperglycemia Avoidance Scale  
Confidence in Diabetes Self-Care Scale  
 
Visit 4 Phase 2 Initiation 
Technology Expectations (burdens subscale only)  
INSPIRE (revised for DSS)  
Technology Expectations (burdens subscale only)  
INSPIRE (revised for DSS) 
Diabetes Locus of Control  
DiAs Use in Phase 2 Mode 
EMA Surveys 
EMA Surveys 
Week 7 of DiAs Use in Phase 
2 Mode 
Technology Acceptance (burdens subscale only)  
Pittsburgh Sleep Quality Index  
T1-Diabetes Distress Scale  
Week 8 of DiAs Use in Phase 
2 Mode 
Hypoglycemia Fear  
Hyperglycemia Avoidance Scale  
Confidence in Diabetes Self-Care Scale 
 
Visit 5 Phase 3 Initiation 
Technology Expectations (burdens subscale only)  
INSPIRE (revised for DSS)  
Diabetes Locus of Control  
 
INSPIRE (revised for DSS)  
Diabetes Locus of Control  
DiAs Use in Phase 3 Mode 
EMA Surveys 
EMA Surveys 
Week 7 of DiAs Use in Phase 
3 Mode 
Technology Acceptance (burdens subscale only) to 
assess patients’ experienced burdens related to 
the use of DSS 
Pittsburgh Sleep Quality Index (PSQI) to assess 
whether DSS improves sleep quality and quantity.  
 
Pittsburgh Sleep Quality Index  
T1-Diabetes Distress Scale  
Week 8 of DiAs Use in Phase 
3 Mode 
Hypoglycemia Fear Survey  
Hyperglycemia Avoidance  
Confidence in Diabetes Self-Care Scale  
Hypoglycemia Fear Survey  
Hyperglycemia Avoidance Scale  
Confidence in Diabetes Self-Care Scale  
 Visit 6 Study Exit 
ABACUS  
INSPIRE (revised for DSS)  
Diabetes Locus of Control  
 
ABACUS  

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 Risks, Benefits, and Risk Assessment 
1286 
 
1287 
Risks and Benefits are detailed below. Loss of confidentiality is a potential risk; however, data are 
1288 
handled to minimize this risk. Hypoglycemia, hyperglycemia and ketone formation are always a 
1289 
risk in participants with T1DM and participants will be monitored for these symptoms.  
1290 
10.1.1. Venipuncture Risks 
1291 
A hollow needle will be placed in the arm for taking blood samples. Blood draws can cause some 
1292 
common reactions like pain, bruising, or redness at the sampling site. Less common reactions 
1293 
include bleeding from the sampling site, formation of a small blood clot or swelling of the vein 
1294 
and surrounding tissues, and fainting. 
1295 
There is the risk of contamination from blood sampling techniques. Hand washing with either 
1296 
soap & water or waterless hand sanitizer will be used prior to caring for the study subject. Gloves 
1297 
will be worn during blood sample collection and processing. Medical personnel will continue to 
1298 
practice hygiene for the subject’s protection (i.e. hand washing, changing gloves frequently, 
1299 
disposing needles properly). Gloves will be removed and hands washed or sanitized prior to 
1300 
leaving and upon return to the subject’s room. Soiled linen will be changed to minimize the 
1301 
transfer of pathogenic organisms. 
1302 
10.1.2. Fingerstick Risks 
1303 
About 2 drop of blood will be removed by fingerstick for measuring blood sugars and sometimes 
1304 
HbA1c or other tests. This is a standard method used to obtain blood for routine hospital 
1305 
laboratory tests. Pain is common at the time of lancing. In about 1 in 10 cases, a small amount of 
1306 
bleeding under the skin will produce a bruise. A small scar may persist for several weeks. The risk 
1307 
of local infection is less than 1 in 1000. This should not be a significant contributor to risks in this 
1308 
study as fingersticks are part of the usual care for people with diabetes. 
1309 
10.1.3. Subcutaneous Catheter Risks 
1310 
Participants using the study pump infusion sets will be at low risk for developing a local skin 
1311 
infection at the site of the infusion set placement. Though approved for 3 days of use, if a catheter 
1312 
is left under the skin for more than 24 hours it is possible to get an infection where it goes into 
1313 
the skin, with swelling, redness and pain. There may be bleeding where the catheter is put in and 
1314 
bleeding under the skin causing a bruise (1 in 10 risk). 
1315 

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10.1.4. Sensor Needle Risks 
1316 
Participants using the continuous glucose monitor (CGM) with sensor will be at low risk for 
1317 
developing a local skin infection at the site of the sensor needle placement. Though approved for 
1318 
10 days of use, if a catheter is left under the skin for more than 24 hours it is possible to get an 
1319 
infection where it goes into the skin, with swelling, redness and pain. There may be bleeding 
1320 
where the catheter is put in and bleeding under the skin causing a bruise (1 in 10 risk). 
1321 
Study staff should verbally alert the participant that on rare occasions, the CGM may break and 
1322 
leave a small portion of the sensor under the skin that may cause redness, swelling, or pain at 
1323 
the insertion site. The participant should be further instructed to notify the study coordinator 
1324 
immediately if this occurs. 
1325 
10.1.5. Risks of Hypoglycemia  
1326 
As with any person having T1DM and using insulin, there is always a risk of having a low blood 
1327 
sugar (hypoglycemia). The frequency of hypoglycemia should be no more and possibly less than 
1328 
it would be as part of daily living. Symptoms of hypoglycemia can include sweating, jitteriness, 
1329 
and not feeling well. Just as at home, there is the possibility of fainting or seizures (convulsions) 
1330 
and subsequently for a few days the participant may not be as aware of symptoms of 
1331 
hypoglycemia. A poorly functioning CGM can periodically display falsely high glucose values, 
1332 
which could lead to inappropriate insulin recommendation. 
1333 
10.1.6. Risks of Hyperglycemia  
1334 
Hyperglycemia and ketonemia could occur if insulin delivery is attenuated or suspended for an 
1335 
extended period or if the pump or infusion set is not working properly.  A poorly functioning CGM 
1336 
can periodically display falsely high glucose values, which could lead to inappropriate insulin 
1337 
recommendation.  
1338 
10.1.7. Risks of Device Reuse  
1339 
Participant will be informed that FDA or relevant national authorities have approved the insulin 
1340 
pump, CGM, glucometer and ketone meter for single use and that by using them among multiple 
1341 
patients, bloodborne pathogens (i.e. Hepatitis B) may be spread through the use of multiple 
1342 
users. 
1343 
The study CGM system is labelled for single use only. The sensor (the component of the system 
1344 
that enters the skin) will be single use only. The transmitter and receiver may be reused during 
1345 
the study after cleaning the device using a hospital-approved cleaning procedure. The transmitter 
1346 

CLINICAL PROTOCOL 
 
 
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is attached to the sensor but does not enter the skin and the receiver, if used, is a hand held 
1347 
device.  
1348 
The study insulin pumps are labelled for single-patient use. During the study, this device may be 
1349 
reused after adhering to a hospital-approved cleaning procedure. All infusion set equipment will 
1350 
be single patient use only (infusion set insertion kits, tubing, cartridges etc.). 
1351 
10.1.8. Other Risks  
1352 
Some participants may develop skin irritation or allergic reactions to the adhesives used to secure 
1353 
the CGM, or to secure the insulin infusion sets for the continuous subcutaneous insulin infusion.  
1354 
If these reactions occur, different adhesives or “under-taping” (such as with IV 3000, Tegaderm, 
1355 
etc.) will be tried, sites will be rotated frequently, and a mild topical steroid cream or other 
1356 
medication may be required. 
1357 
Whenever the skin is broken there is the possibility of an infection. The CGM and pump infusion 
1358 
sites are inserted under the skin. It is possible that any part that is inserted under the skin may 
1359 
cause an infection. These occur very infrequently, but, if an infection was to occur, oral and/or 
1360 
topical antibiotics can be used. The risk of skin problems could be greater if you use a sensor for 
1361 
longer than it is indicated for use. Therefore, participants will be carefully instructed about proper 
1362 
use of the sensor. 
1363 
 
1364 
It is expected that this protocol will yield increased knowledge about using a Decision Support 
1365 
System for insulin dosing suggestions. The individual participant may or may not benefit from 
1366 
study participation. 
1367 
 
1368 
Based on the facts that (1) adults with diabetes experience mild hypoglycemia and hyperglycemia 
1369 
frequently as a consequence of the disease and its management, (2) the study intervention 
1370 
involves feedback and advice for insulin dosing that may increase the likelihood of hypoglycemia, 
1371 
and hyperglycemia, (3) mitigations are in place, and have been tested in prior studies using the 
1372 
investigational device system in the home setting. . 
1373 
 
1374 
The study is being conducted in compliance with the policies described in the study policies 
1375 
document, with the ethical principles that have their origin in the Declaration of Helsinki, with 
1376 
the protocol described herein, and with the standards of Good Clinical Practice (GCP). 
1377 

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Whenever possible, data will be directly collected in electronic case report forms, which will be 
1378 
considered the source data.  
 
1379 

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 Device Cleaning Instructions 
1380 
CGM cleaning instructions are provided in the Dexcom G4 PLATINUM (Professional) Cleaning and 
1381 
Disinfection manual (current edition). The transmitter will be cleaned with Clorox Healthcare® 
1382 
Bleach Germicidal Cleaner or any disinfectant product in a spray bottle containing a bleach 
1383 
solution of 6500 parts per million with the EPA registration number 56392-7. The transmitter will 
1384 
be submerged in this solution and then placed on an absorbent wipe or clean surface. Two sprays 
1385 
will be dispensed from the Clorox cleaner onto each side of the transmitter. A nylon brush will 
1386 
be used to scrub the transmitter on all sides for 30 seconds. The transmitter will be placed in the 
1387 
Clorox Cleaner solution for one minute. The transmitter is then rinsed under flowing tap water 
1388 
for ten seconds. The transmitter will then be disinfected using a disinfectant product with EPA 
1389 
registration number 56392-7 using similar procedures as the cleaning process.   
1390 
Per the pump manufacturer, the insulin pump will be cleaned with a damp lint-free cloth. Use of 
1391 
household or industrial cleaners, solvents, bleach, scouring pads, chemicals, or sharp instruments 
1392 
are prohibited. The pump should never be submerged in water. If needed, a very mild detergent, 
1393 
such as a bit of liquid soap with warm water will be used. A soft towel will be used to dry the 
1394 
pump.  
1395 
Equipment that touches intact skin will be cleaned with ethyl or isopropyl alcohol (70-90%), 
1396 
quaternary ammonium germicidal detergent (i.e. Cavicide, EPA number 46781) or household 
1397 
bleach. The contact time on the surface depends on the method used to clean the equipment. 
1398 
Cavicide requires three minutes on the surface of the equipment. Clorox Germicidal Bleach Wipes 
1399 
require two minutes on the equipment. The surface should remain wet (i.e. slightly damp) with 
1400 
the disinfectant to be considered effective though not wet enough to leave drops of liquid.  
1401 
In the event a manufacturer update for cleaning procedures of their device, the study team will 
1402 
adhere to the most current recommendations.  
 
1403 

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 Adverse Events, Device Issues, and Stopping Rules 
1404 
The protocol is considered a significant risk device study due to the fact that the closed loop 
1405 
system is experimental. Therefore, an investigational device exemption (IDE) from the U.S. Food 
1406 
and Drug Administration (FDA) is required to conduct the study. 
1407 
 
1408 
12.1.1. Adverse Events (AE) 
1409 
A reportable adverse event includes any untoward medical occurrence that meets one of the 
1410 
following criteria: 
1411 
• A Serious Adverse Event as defined in section 12.1.2 
1412 
• An Adverse Device Effect as defined in section 12.1.4, unless excluded from reporting in 
1413 
section 12.8 
1414 
• An Adverse Event as defined in section 12.1.4 occurring in association with a study 
1415 
procedure 
1416 
• An AE as defined in section 12.1.1 which leads to discontinuation of  a study device for 2 
1417 
or more hours 
1418 
• Hypoglycemia meeting the definition of severe hypoglycemia as defined in section 12.3.1  
1419 
• Diabetic ketoacidosis (DKA) as defined in section 12.3.2 or in the absence of DKA, a 
1420 
hyperglycemic or ketosis event meeting the criteria defined below 
1421 
Hypoglycemia and hyperglycemia not meeting the criteria below will not be recorded as adverse 
1422 
events unless associated with an Adverse Device Effect. Skin reactions from sensor placement 
1423 
are only reportable if severe and/or required treatment. 
1424 
12.1.2. Serious Adverse Event (SAE) 
1425 
 Any untoward medical occurrence that: 
1426 
• Results in death. 
1427 
• Is life-threatening; (a non-life-threatening event which, had it been more severe, might 
1428 
have become life-threatening, is not necessarily considered a serious adverse event). 
1429 
• Requires inpatient hospitalization or prolongation of existing hospitalization. 
1430 
• Results in persistent or significant disability/incapacity or substantial disruption of the 
1431 
ability to conduct normal life functions (life threatening). 
1432 
• Is a congenital anomaly or birth defect. 
1433 

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• Is considered a significant medical event by the investigator based on medical judgment 
1434 
(e.g., may jeopardize the participant or may require medical/surgical intervention to 
1435 
prevent one of the outcomes listed above). 
1436 
12.1.3. Unanticipated Adverse Device Effect (UADE) 
1437 
Any serious adverse effect on health or safety or any life-threatening problem or death caused 
1438 
by, or associated with a device, if that effect, problem, or death was not previously identified in 
1439 
nature, severity, or degree of incidence in the investigational plan or application (including a 
1440 
supplementary plan or application), or any other unanticipated serious problem associated with 
1441 
a device that relates to the rights, safety, or welfare of participants (21 CFR 812.3(s)). 
1442 
12.1.4. Adverse Device Effect (ADE) 
1443 
Any untoward medical occurrence in a study participant which the device may have caused or to 
1444 
which the device may have contributed. 
1445 
12.1.5. Device Complaints and Malfunctions 
1446 
A device complication or complaint is something that happens to a device or related to device 
1447 
performance, whereas an adverse event happens to a participant.  A device complaint may occur 
1448 
independently from an AE, or along with an AE. An AE may occur without a device complaint or 
1449 
there may be an AE related to a device complaint. A device malfunction is any failure of a device 
1450 
to meet its performance specifications or otherwise perform as intended. Performance 
1451 
specifications include all claims made in the labeling for the device.  The intended performance 
1452 
of a device refers to the intended use for which the device is labeled or marketed. (21 CFR 803.3).   
1453 
 
1454 
A protocol deviation is any noncompliance with the clinical trial protocol, Good Clinical Practices 
1455 
(GCP), or procedure requirements. The noncompliance may be either on the part of the 
1456 
participant, the investigator, or the study site staff. As a result of deviations, corrective actions 
1457 
may be developed by the site and implemented as appropriate. Major deviations will be reported 
1458 
to the IRB-HSR within 7 calendar days of when the study team becomes aware of the event. 
1459 
 
1460 
12.3.1. Hypoglycemia Event 
1461 
Hypoglycemia not associated with an Adverse Device Effect is only reportable as an adverse event 
1462 
when the following definition for severe hypoglycemia is met:  
1463 

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• The event required assistance of another person due to altered consciousness, and 
1464 
required another person to actively administer carbohydrate, glucagon, or other 
1465 
resuscitative actions;  
1466 
• Impaired cognitively to the point that he/she was unable to treat himself/herself, was 
1467 
unable to verbalize his/ her needs, was incoherent, disoriented, and/or combative, or 
1468 
experienced seizure or coma. These episodes may be associated with sufficient 
1469 
neuroglycopenia to induce seizure or coma; 
1470 
• If plasma glucose measurements are not available during such an event, neurological 
1471 
recovery attributable to the restoration of plasma glucose to normal is considered 
1472 
sufficient evidence that the event was induced by a low plasma glucose concentration. 
1473 
12.3.2.  Hyperglycemia Events/Diabetes Ketoacidosis 
1474 
Hyperglycemia not associated with an Adverse Device Effect is only reportable as an adverse 
1475 
event when one of the following four criteria is met. 
1476 
The event involved DKA, as defined by the Diabetes Control and Complications Trial (DCCT) and 
1477 
described below: 
1478 
• Evaluation or treatment was obtained at a health care provider facility for an acute event 
1479 
involving hyperglycemia or ketosis 
1480 
• Blood ketone level ≥1.5 mmol/L and communication occurred with a health care provider 
1481 
at the time of the event 
1482 
• Blood ketone level ≥3.0 mmol/L, even if there was no communication with a health care 
1483 
provider 
1484 
• Hyperglycemic events are classified as DKA if the following are present: 
1485 
o Symptoms such as polyuria, polydipsia, nausea, or vomiting; 
1486 
o Serum ketones ≥1.5 mmol/L or large/moderate urine ketones; 
1487 
o Treatment provided in a health care facility 
1488 
All reportable Adverse Events—whether volunteered by the participant, discovered by study 
1489 
personnel during questioning, or detected through physical examination, laboratory test, or 
1490 
other means—will be reported on an adverse event form online. Adverse events  will be 
1491 
presented to the DSMB in accumulated manner during each meeting.  
1492 
 
1493 
The study investigator will assess the relationship of any adverse event to be related or unrelated 
1494 
by determining if there is a reasonable possibility that the adverse event may have been caused 
1495 
by the study device. 
1496 

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To ensure consistency of adverse event causality assessments, investigators should apply the 
1497 
following general guideline when determining whether an adverse event is related: 
1498 
• There is a plausible temporal relationship between the onset of the adverse event and 
1499 
the study intervention, and the adverse event cannot be readily explained by the 
1500 
participant’s clinical state, intercurrent illness, or concomitant therapies; and/or the 
1501 
adverse event follows a known pattern of response to the study intervention; and/or the 
1502 
adverse event abates or resolves upon discontinuation of the study intervention or dose 
1503 
reduction and, if applicable, reappears upon re-challenge. 
1504 
• Evidence exists that the adverse event has an etiology other than the study intervention 
1505 
(e.g., preexisting medical condition, underlying disease, intercurrent illness, or 
1506 
concomitant medication); and/or the adverse event has no plausible temporal 
1507 
relationship to study intervention. 
1508 
 
1509 
The intensity of an adverse event will be rated on a three point scale: (1) mild, (2) moderate, or 
1510 
(3) severe. It is emphasized that the term severe is a measure of intensity: thus, a severe adverse 
1511 
event is not necessarily serious. For example, itching for several days may be rated as severe, but 
1512 
may not be clinically serious. 
1513 
• MILD: Usually transient, requires no special treatment, and does not interfere with the 
1514 
participant’s daily activities. 
1515 
• MODERATE: Usually causes a low level of inconvenience or concern to the participant and 
1516 
may interfere with daily activities, but is usually ameliorated by simple therapeutic 
1517 
measures. 
1518 
• SEVERE: Interrupts a participant’s usual daily activities and generally requires systemic 
1519 
drug therapy or other treatment. 
1520 
 
1521 
Adverse events will be coded per the UVA IRB website instructions (i.e. mild, moderate, severe).   
1522 
Adverse events that continue after the participant’s discontinuation or completion of the study 
1523 
will be followed until their medical outcome is determined or until no further change in the 
1524 
condition is expected. 
1525 
 
1526 
The outcome of each reportable adverse event will be classified by the investigator as follows: 
1527 
• RECOVERED/RESOLVED – The participant recovered from the AE/SAE without sequelae.  
1528 
Record the AE/SAE stop date. 
1529 

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• RECOVERED/RESOLVED WITH SEQUELAE – The event persisted and had stabilized 
1530 
without change in the event anticipated. Record the AE/SAE stop date. 
1531 
• FATAL – A fatal outcome is defined as the SAE that resulted in death. Only the event that 
1532 
was the cause of death should be reported as fatal. AEs/SAEs that were ongoing at the 
1533 
time of death; however, were not the cause of death, will be recorded as “resolved” at 
1534 
the time of death. 
1535 
• NOT RECOVERED/NOT RESOLVED (ONGOING) – An ongoing AE/SAE is defined as the 
1536 
event was ongoing with an undetermined outcome. 
1537 
• An ongoing outcome will require follow-up by the site in order to determine the final 
1538 
outcome of the AE/SAE. 
1539 
• The outcome of an ongoing event at the time of death that was not the cause of death, 
1540 
will be updated and recorded as “resolved” with the date of death recorded as the stop 
1541 
date. 
1542 
• UNKNOWN – An unknown outcome is defined as an inability to access the participant or 
1543 
the participant’s records to determine the outcome (for example, a participant that was 
1544 
lost to follow-up). 
1545 
All clinically significant abnormalities of clinical laboratory measurements or adverse events 
1546 
occurring during the study and continuing at study termination should be followed by the 
1547 
participant’s physician and evaluated with additional tests (if necessary) until diagnosis of the 
1548 
underlying cause, or resolution. Follow-up information should be recorded on source documents. 
1549 
If any reported adverse events are present when a participant completes the study, or if a 
1550 
participant is withdrawn from the study due to an adverse event, the participant will be 
1551 
contacted for re-evaluation. If the adverse event has not resolved, additional follow-up will be 
1552 
performed as appropriate. Every effort should be made by the Investigator or delegate to contact 
1553 
the participant until the adverse event has resolved or stabilized. 
1554 
 
1555 
All UADEs, ADEs, device complaints, and device malfunctions will be reported irrespective of 
1556 
whether an adverse event occurred, except in the following circumstances.  
1557 
The following device issues are anticipated and will not be reported but will reported as an 
1558 
Adverse Event if the criteria for AE reporting described above are met: 
1559 
• Component disconnections 
1560 
• CGM sensors lasting fewer than the number of days expected per CGM labeling 
1561 
• CGM tape adherence issues 
1562 

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• Pump infusion set occlusion not leading to ketosis 
1563 
• Battery lifespan deficiency due to inadequate charging or extensive wireless 
1564 
communication 
1565 
• Intermittent device component disconnections/communication failures not leading to 
1566 
system replacement 
1567 
• Device issues clearly addressed in the user guide manual that do not require additional 
1568 
troubleshooting 
1569 
• Skin reactions from CGM sensor placement or pump infusion set placement that do not 
1570 
meet criteria for AE reporting 
1571 
 
1572 
• UADEs must be reported within 10 working days to the FDA after the sponsor first 
1573 
receives notice of the adverse effect. 
1574 
• Other reportable adverse events, device malfunctions (with or without an adverse event) 
1575 
and device complaints should be reported promptly, but there is no formal required 
1576 
reporting period. 
1577 
• The IDE Sponsor will investigate the UADE and if indicated, report the results of the 
1578 
investigation to the IRBs, FDA, and DSMB will within 10 working days of the study team 
1579 
becoming aware of the UADE per 21CFR 812.46(b).  
1580 
• The DSMB will determine if the UADE presents an unreasonable risk to participants. If so, 
1581 
the DSMB will must ensure that all investigations, or parts of investigations presenting 
1582 
that risk, are terminated as soon as possible but no later than 5 working days after the 
1583 
DSMB will makes this determination and no later than 15 working days after first receipt 
1584 
notice of the UADE. 
1585 
• In the case of a device system component malfunction (e.g. pump, CGM, control 
1586 
algorithm), information will be forwarded to the responsible manufacturer by the study 
1587 
personnel. 
1588 
 
1589 
An independent Data and Safety Monitoring Board (DSMB) will be establish to review compiled 
1590 
safety data at periodic intervals to oversee and monitor our randomized clinical trial to ensure 
1591 
the safety of participants, as well as the validity and integrity of the data.   
1592 
Details regarding membership, meetings, responsibilities will be documented in a separate DSMB 
1593 
Charter.  
1594 

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1595 
12.11.1. Participant Discontinuation  
1596 
Rules for discontinuing study device use are: 
1597 
• The investigator believes it is unsafe for the participant to continue on the intervention.  
1598 
This could be due to the development of a new medical condition or worsening of an 
1599 
existing condition; or participant behavior contrary to the indications for use of the device 
1600 
that imposes on the participant’s safety 
1601 
• The participant requests that the treatment be stopped 
1602 
• Two distinct episodes of DKA 
1603 
• Two distinct severe hypoglycemia events as defined in section 12.3.1 
1604 
12.11.2. Suspending/Stopping Overall Study 
1605 
In the case of an unanticipated system malfunction resulting in a severe hypoglycemia or severe 
1606 
hyperglycemia event, use of the study device system will be suspended while the problem is 
1607 
diagnosed. 
1608 
In addition, study activities could be similarly suspended if the manufacturer of any constituent 
1609 
study device requires stoppage of device use for safety reasons (e.g. product recall). The affected 
1610 
study activities may resume if the underlying problem can be corrected by a protocol or system 
1611 
modification that will not invalidate the results obtained prior to suspension.  
1612 
 
1613 
A Medical Monitor will review all DKA and severe hypoglycemia irrespective of relatedness to 
1614 
study device use, and all serious events (including UADEs) related to study device use at the time 
1615 
of occurrence. The Medical Monitor can request modifications to the study protocol or 
1616 
suspension or outright stoppage of the study if deemed necessary based on the totality of safety 
1617 
data available. Details regarding Medical Monitor review will be documented in a separate 
1618 
Medical Monitor document.   
 
1619 

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 Miscellaneous Considerations  
1620 
 
1621 
Participants using glulisine at the time of enrollment will be asked to contact their personal 
1622 
physician to change their prescribed personal insulin to lispro or aspart for the duration of the 
1623 
trial. 
1624 
The study devices (study insulin pump, study CGM) must be removed before Magnetic Resonance 
1625 
Imaging (MRI), Computed Tomography (CT) or diathermy treatment. Participants may continue 
1626 
in the trial after temporarily discontinuing use if requiring one of the treatments above. 
1627 
 
1628 
Participation in the study is voluntary. Participant may withdraw at any time. For participants 
1629 
who do withdraw from the study, the study team will determine if their data will be used in 
1630 
analysis.  
1631 
 
1632 
For security and confidentiality purposes, subjects will be assigned an identifier that will be used 
1633 
instead of their name. Protected health information gathered for this study may be shared with 
1634 
the third-party collaborators. De-identified subject information may also be provided to 
1635 
collaborators involved in the study after the appropriate research agreement has been executed.  
1636 

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 Statistical Consideration 
1637 
 
1638 
This is a randomized crossover study in T1DM designed to demonstrate the efficacy of 
1639 
personalized feedback (PF) and decision support (DSS) over sensor-augmented pump (SAM) 
1640 
therapy and to establish relationships between the level of glucose variability (GV) control 
1641 
achievable by the intervention and individual psycho-behavioral characteristics.  
1642 
We plan to split the study into 4 cohorts of about 25 participants each (expected retention 20 
1643 
per cohort). Each cohort will continue for ~7 months and will have the structure presented in 
1644 
Figure 5. Following recruitment, screening, and a run-in period of SAM, participants will be 
1645 
randomized into one of two groups: escalation vs. de-escalation of devices and function. Each 
1646 
treatment modality (SAM, PF, DSS) will continue for about 8 weeks, with the last 4 weeks used 
1647 
to assess GV from CGM data.  
1648 
Escalation: SAM → PF → DSS 
1649 
De-escalation: DSS → PF → SAM 
1650 
 
1651 
14.2.1. Sample Size Determination:  
1652 
Sample size determination is based on our related pilot studies of DSS. We estimate that the 
1653 
effect size of DSS vs. SAM will be f³0.22. Power calculations (G*Power 3.1.9.2) assuming a=0.017 
1654 
(corrected for multiple comparisons), 95% power, correlation of 0.55 between the repeated 
1655 
measures, and attrition of 20%, yield a sample size of N=100 subjects to be randomized at 
1656 
baseline, with N=80 subjects completing the study. PF vs. SAM assumes the same effect size. We 
1657 
expect that while overall DSS effect vs. PF will be smaller than vs. SAM, GV control over time will 
1658 
be more consistent. Aim 1.3 analysis therefore assumes a small effect size (0.15) but 5 repeated 
1659 
measures (bi-weekly) in each condition with higher correlation (0.65), leading to an achieved 
1660 
power of 97.2% for this Aim. 
1661 
14.2.2. Exploration of the effect of treatment escalation vs. de-escalation:  
1662 
A key advantage of the proposed study design (beyond the optimal statistical power) is the 
1663 
possibility to explore the glucose control and psycho-behavioral impact of features being added 
1664 
and/or enhanced with prescriptive components (DSS), vs. features being limited to information 
1665 
(PF) or even removed (SAM). We will perform this analysis by looking at the between factors in 
1666 
the repeated ANOVA analysis, contrasting the escalation group vs. de-escalation group. While 
1667 

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not powered, this analysis will provide key insights in the future feature adaptation schemes 
1668 
based on the ATI.  
1669 
 
1670 
 Glycemic outcomes: 
1671 
The primary outcome of this study will be Glucose Variability (GV) as measured by CGM-based 
1672 
Coefficient of Variation (CV), as recommended by the International Consensus on Use of 
1673 
Continuous Glucose Monitoring. To further characterize glucose control, we will compute other 
1674 
CGM Consensus outcomes as well:  
1675 
• 
Average  
1676 
• 
Percent in different ranges:  
1677 
o <50 mg/dL  
1678 
o <54 mg/dL  
1679 
o <60 mg/dL  
1680 
o <70 mg/dL  
1681 
o ≤70-≤180 mg/dL  
1682 
o >180 mg/dL  
1683 
o >250 mg/dL  
1684 
o >300 mg/dL  
1685 
• 
SD and coefficient of variation  
1686 
• 
LBGI, HBGI, ADRR 
1687 
Each modality of treatment will be assessed using the last 4 weeks of CGM recordings, as we 
1688 
expect most of the GV benefits of each intervention to be realized within the first 4 weeks of the 
1689 
intervention, and a minimum of 24 days of data is considered optimal for CGM–based CV 
1690 
determination.   
1691 
14.3.2. Glucose Variability Reduction Achieved with CGM-based expert systems:  
1692 
General linear models (GLM) (repeated measures ANOVA) will be used to assess the significance 
1693 
of the differences in average response between SAM, PF, and DSS across appropriate CGM-based 
1694 
metrics. The particular design of the clinical study allow for Aims 1.1, 1.2, and 1.3 to each be 
1695 
addressed independently in a randomized crossover analysis, as shown in Figure 4. While the 
1696 
randomized order of the interventions (escalation vs de-escalation) allows for an objective 
1697 
assessment of the average efficacy of each of them, we will introduce the order as a fixed factor 
1698 
to verify if significant study effects can be detected. Finally, we will study the evolution of GV 
1699 
within each modality period: GV and other CGM-based outcomes will be computed bi-weekly 
1700 
(the minimum length of time for precise GV assessment) and entered in a repeated measures 
1701 

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GLM analysis; within-subject contrast (linear and polynomial) using 5 repeated measures per 
1702 
condition to explore the evolution of the glycemic outcomes in time; Aim 1.3.  
1703 
 
1704 
A key advantage of the proposed study design (beyond the optimal statistical power) is the 
1705 
possibility to explore the glucose control and psycho-behavioral impact of features being added 
1706 
and/or enhanced with prescriptive components (DSS), vs. features being limited to information 
1707 
(PF) or even removed (SAM). We will perform this analysis by looking at the between factors in 
1708 
the repeated ANOVA analysis, contrasting the escalation group vs. de-escalation group. While 
1709 
not powered, this analysis will provide key insights in the future feature adaptation schemes 
1710 
based on the ATI. 
1711 
 
1712 
Quantitative data on usability and satisfaction will be analyzed using simple descriptive statistics. 
1713 
In addition, we will analyze scores from the measures in the psychosocial assessment battery to 
1714 
determine if changes occur over time and between groups. Using SPSS 26, we will construct 
1715 
predictive models in the general linear modeling (GLM) framework to examine each set of 
1716 
psychological factors (e.g., INSPIRE survey) over time, and their association with glycemic 
1717 
outcomes. Group assignment and Study Phases will be the primary covariate. 
1718 
 
1719 
Baseline demographic and clinical characteristics of the cohort of all randomized participants will 
1720 
be summarized in a table using summary statistics appropriate to the distribution of each 
1721 
variable. Descriptive statistics will be displayed overall and by treatment group. 
1722 
Will include: 
1723 
• Age 
1724 
• HbA1c collected at randomization and study end 
1725 
• Gender 
1726 
• Race/ethnicity 
1727 
• CGM use before enrollment 
1728 
• Diabetes duration 
1729 
• BMI 
1730 
 
1731 
We will count each time the participant interacted with the study Personalized Feedback and 
1732 
Decision Support System and perform a Wilcoxon paired rank test to determine if any differences 
1733 
exist in system interactions.  
 
1734 

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 Data Collection and Monitoring 
1735 
 
1736 
The study data are collected through a combination of case report forms (electronic and paper) 
1737 
and electronic device data files obtained from the software and individual hardware 
1738 
components. These electronic device files and electronic CRFs are considered the primary source 
1739 
documentation. 
1740 
When data are directly collected in electronic case report forms, this will be considered the 
1741 
source data. Records will be maintained in accordance with ICH E6 and institutional regulatory 
1742 
requirements for the protection of confidentiality of participants. 
1743 
 
1744 
Study documents will be retained for a minimum of 2 years after study close out. These 
1745 
documents may be retained for a longer period, however, if required by local regulations. No 
1746 
records will be destroyed without the consent of the Principal Investigator. It is the responsibility 
1747 
of the Principal Investigator to inform all co-investigators when these documents no longer need 
1748 
to be retained.  
1749 

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 Ethics/Protection of Human Participants 
1750 
 
1751 
The investigator will ensure that this study is conducted in full conformity with Regulations for 
1752 
the Protection of Human Participants of Research codified in 45 CFR Part 46, 21 CFR Part 50, 21 
1753 
CFR Part 56, and/or the ICH E6. 
1754 
 
1755 
The protocol, informed consent form(s), recruitment materials, and all participant materials will 
1756 
be submitted to the IRB for review and approval. Approval of both the protocol and the consent 
1757 
form must be obtained before any participant is enrolled. Any amendment to the protocol will 
1758 
require review and approval by the IRB before the changes are implemented to the study. All 
1759 
changes to the consent form will be IRB approved; a determination will be made regarding 
1760 
whether previously consented participants need to be re-consented. 
1761 
 
1762 
Informed consent is a process that is initiated prior to an individual’s agreement to participate in 
1763 
the study and continues throughout the individual’s study participation. Extensive discussion of 
1764 
risks and possible benefits of participation will be provided. Consent forms will be IRB approved 
1765 
and the participant will be asked to read and review the document. The investigator or their 
1766 
delegate will explain the research study to the participant and answer any questions that may 
1767 
arise. All participants will receive a verbal explanation in terms suited to their comprehension of 
1768 
the purposes, procedures, and potential risks of the study and of their rights as research 
1769 
participants. Participants will have the opportunity to carefully review the written consent form 
1770 
and ask questions prior to signing. 
1771 
The participant will sign the informed consent document prior to any procedures being done 
1772 
specifically for the study. A copy of the informed consent document will be given to the 
1773 
participant for their records. The rights and welfare of the participants will be protected by 
1774 
emphasizing to them that the quality of their medical care will not be adversely affected if they 
1775 
decline to participate in this study. 
1776 
 
1777 
The study monitor, representatives of the IRB or device company supplying study product may 
1778 
inspect all documents and records required to be maintained by the investigator, including but 
1779 
not limited to, medical records (office, clinic, or hospital) for the participants in this study.   
1780 

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The study participant’s contact information will be securely stored at the clinical site for internal 
1781 
use during the study. At the end of the study, all records will continue to be kept in a secure 
1782 
location for as long a period as dictated by local IRB and Institutional regulations. 
1783 
Study participant research data, which is for purposes of statistical analysis and scientific 
1784 
reporting, will be stored at the University of Virginia Center for Diabetes Technology.  The study 
1785 
data entry and study management systems used by research staff will be secured and password 
1786 
protected. At the end of the study, all study databases may be de-identified and archived at the 
1787 
University of Virginia Center for Diabetes Technology. 
 
1788 

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1789 
1. American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes 
1790 
care. 2014 Jan 1;37(Supplement 1): S81-90. 
1791 
2. Hirsch IB. Insulin analogues. New England Journal of Medicine. 2005 Jan 13;352(2):174-
1792 
83. 
1793 
3. Klonoff DC, Prahalad P. Performance of cleared blood glucose monitors. Journal of 
1794 
diabetes science and technology. 2015 Jun 30;9(4):895-910. 
1795 
4. Castle JR, Jacobs PG. Nonadjunctive use of continuous glucose monitoring for diabetes 
1796 
treatment decisions. Journal of diabetes science and technology. 2016 Sep;10(5):1169-
1797 
73. 
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5. Diabetes Control and Complications Trial. Intensive diabetes treatment and 
1799 
cardiovascular disease in patients with type 1 diabetes. N Engl J Med. 2005 Dec 
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22;2005(353):2643-53. 
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6. Secrest AM, Becker DJ, Kelsey SF, LaPorte RE, Orchard TJ. All-cause mortality trends in a 
1802 
large population-based cohort with long-standing childhood-onset type 1 diabetes. 
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Diabetes care. 2010 Dec 1;33(12):2573-9. 
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7. Lind M, Svensson AM, Kosiborod M, Gudbjörnsdottir S, Pivodic A, Wedel H, Dahlqvist S, 
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Clements M, Rosengren A. Glycemic control and excess mortality in type 1 diabetes. New 
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England Journal of Medicine. 2014 Nov 20;371(21):1972-82. 
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8. Nishimura R, LaPorte RE, Dorman JS, Tajima N, Becker D, Orchard TJ. Mortality trends in 
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9. McCall AL, Kovatchev BP. The Median is Not the Only Message: A Clinician's Perspective 
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10. Lachin JM, Genuth S, Nathan DM, Zinman B, Rutledge BN, DCCT/EDIC Research Group: 
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11. Santiago JV. Lessons from the Diabetes Control and Complications Trial, Diabetes, 
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13. UK Prospective Diabetes Study Group (UKPDS). Intensive blood-glucose control with 
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77. Cox D, Gonder-Frederick L, McCall A, Kovatchev B, Clarke W. The effects of glucose 
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78. Gonder-Frederick L, Zrebiec J, Bauchowitz A, Lee J, Cox D, Ritterband L, Kovatchev B, 
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79.  Gonder-Frederick, LA, Zrebiec, JF, Bauchowitz, AU, Ritterband, L, Magee, JC, Cox, DJ, 
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80. Gonder-Frederick LA, Grabman JH, Kovatchev, B, Brown SA, Patek S, Basu A, Pinsker JE, 
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