UPSTART: Using Peer Support to Aid in Prevention and Treatment in Prediabetes
Phase: NA
Conditions: PreDiabetes
Sponsor: University of Michigan

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Using Peer Support to Aid in Prevention and Treatment in Prediabetes (UPSTART) 
 
Study Protocol 
 
NCT# 03689530 
 
Version Date:  September 20, 2022; Approved by IRB October 27, 2022 
 
Principal Investigators: Michele Heisler and Julie Schmittdiel 
 
 

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A. SIGNIFICANCE 
The Challenge of Preventing Diabetes. In the US almost 30 million people have type 2 diabetes mellitus 
(T2DM), with projected prevalence by 2050 of 1 in 5 adults.1-3 T2DM results in high morbidity, mortality, and 
annual costs of $306 billion.4 The high prevalence of diabetes is due in large part to obesity, consumption of 
calorie-dense foods, and sedentary behaviors.3 86 million US adults—1 in 3—have prediabetes, defined as a 
fasting plasma glucose of 100-125 mg/dL, 2-hour plasma glucose of 149-199 mg/dL, or hemoglobin A1c (A1c) 
of 5.7%-6.4%.2,3,5 Annual incidence of T2DM is 5-10% in adults with prediabetes compared with 1% per year in 
the general population.6,7 Yet, only 1 in 13 adults with prediabetes are aware of their risk,8 and fewer are taking 
steps to avoid diabetes. There is an urgent need to develop and evaluate effective and scalable interventions 
to prevent or delay the onset of diabetes, enhance its early detection, and increase uptake of lifestyle and 
pharmacological diabetes prevention interventions. Identifying persons at high risk for developing diabetes, 
linking them to and supporting their engagement in structured diet and physical activity promotion programs 
that reduce incidence of diabetes by 50% could prevent 8.6 million new cases of T2DM over the next decade.9 
Low-income and Racial/Ethnic Minorities Experience Disproportionate Risk. The need to prevent T2DM 
is especially pressing for socioeconomically disadvantaged and for racial and ethnic minority populations. 
T2DM is up to two times as prevalent in US adults with low incomes and education levels compared to higher-
SES adults.10,11 African Americans, Asian Americans, and Latinos are 30-70% more likely to have T2DM than 
non-Latino whites.12 Low-income and Latino and African American adults on average have more risk factors for 
diabetes, including higher rates of overweight, obesity, and being sedentary, than non-Latino, higher-SES 
whites.13 Asian American and Latinos develop T2DM at lower body mass indices (BMI) than other racial/ethnic 
groups.14 Among Latino adults, decreasing BMI by 1 unit is estimated to reduce the incidence of diabetes by 
12%. And, after controlling for age and family history, prevention of weight gain from normal to overweight BMI 
categories would decrease the incidence of T2DM by 62% among Mexican Americans.12,15-17  
Structured Lifestyle Interventions Can Prevent or Delay T2DM. Randomized controlled trials (RCTs) 
conducted in the US, China, Finland, Japan, and India documented 30-60% reductions in diabetes incidence in 
high-risk adults.18-21 Several found an extended “legacy” effect.22-26 In the US Diabetes Prevention Program 
(DPP), adults with impaired glucose tolerance who lost 5-7% of their body weight and achieved 150 minutes of 
moderate physical activity per week reduced their chance of getting T2DM by 16% per year (58% over 3 
years).19,27,28 Diabetes incidence was decreased by 16% for every kilogram of weight lost.29 The DPP has been 
successfully adapted into group-based versions30-33 in multiple settings including YMCA’s,34-36 churches,37 and 
community health care centers.38-41 It has also been adapted for delivery via automated telephone system,42 
television, DVD, and e-health platforms.43-45 Culturally tailored DPP adaptations are effective among African 
American and Latino adults,46-49 as are those delivered by different providers and technologies.50-52 For 
example, DPP adaptations led by community health workers (CHWs) achieved weight loss of 6-7%.34,40,53-56 
Two systematic reviews concluded that programs achieving a mean weight loss at 1 year of just 2.5% confer a 
60% reduction in development of diabetes at 6 years, with half of participants reverting to normoglycemia.57,58  
Now a Wide Array of Evidence-Based Diabetes Prevention Programs and Increased Coverage. In 2012, 
the CDC’s National DPP Initiative began to support scaling up community-based DPP programs.59 In 2015, the 
US Preventive Services Task Force (USPSTF) recommended screening for abnormal blood glucose in 
overweight and obese adults aged 40 to 70 and referral to diabetes prevention interventions.60 The Community 
Preventive Services Task Force in turn recommended that health care systems and community organizations 
offer such programs.61 In 2016, Medicare joined many private insurers to reimburse CDC-recognized DPPs 
(including the Omada62 online program) for the estimated 22 million beneficiaries with prediabetes.63 If there is 
good uptake by Medicare beneficiaries, federal spending on diabetes treatment is estimated to decrease by 
$1.3 billion in the first decade, with even greater savings over the next decade.63 Both of the health systems for 
our proposed study—Michigan Medicine (MM) and Kaiser Permanente Northern CA (KPNC)—are now 
themselves offering structured diabetes prevention programs and encouraging referrals to online and the many 
locally available community programs (see Appendix A).  
The Problem of Poor Uptake of and Engagement in Diabetes Prevention Programs. Unfortunately, even 
when referred to programs, rates of uptake/participation (attending at least one session) and engagement 
(completing a sufficient number of sessions) of eligible adults are very low.64 Adults with prediabetes must 
have knowledge of their elevated but modifiable risk for T2DM and of recommended behaviors and available 

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programs as well as motivation, self-efficacy, and support to engage in and sustain behaviors.65-67 Low-income 
and racial and ethnic minorities in particular face multiple social and environmental barriers to participation in 
formal programs.68 These include competing demands, time constraints, erratic work schedules, food 
insecurity, poor access to healthy foods, and limited opportunities for physical activity. Latino immigrants may 
face additional barriers related to acculturation and language.68-70 Rates of uptake and engagement are thus 
disproportionately low. In trials of community-based diabetes prevention programs, participants on average 
attended only 40 to 60% of diabetes prevention sessions.35,49,71 Yet, active engagement is critically important. 
One review found that change in weight was similar whether the intervention was delivered by health 
professionals or lay workers,72 but there was a dose-response association between number of sessions 
attended and amount of weight loss—with a 1% greater weight loss for every four sessions attended.72 
Rates of uptake of formal programs are even lower than rates of engagement. Studies of referral from 
primary care to free community-based lifestyle programs indicate that uptake may be about 30% for any 
participation and as low as 5% for participation at a level necessary to achieve targets.8,45,65,73-75 A 2014 review 
of community-based US DPPs further lamented the lack of minority populations in the reviewed interventions 
and called for the identification of best practices under real life conditions to identify, recruit, enroll, and retain 
minority populations in community-based diabetes prevention programs. It is essential to identify the most 
effective recruitment methods to reach vulnerable populations at high risk for developing diabetes.51 
Need for Effective, Scalable Primary-Care based Programs to Increase Uptake and Engagement. It is 
encouraging that there are now many diabetes prevention options as well as increased insurance coverage of 
them. There is nationwide momentum to increase access to the DPP and other programs, but the vast majority 
of at-risk individuals do not participate. This is thus an opportune time to develop and evaluate the 
implementation in real-life settings of effective, scalable approaches to connect adults with prediabetes to 
available programs and provide support to help them maintain engagement and sustain achieved gains. Most 
adults are screened for, diagnosed with, and referred to programs for prediabetes by their primary care 
providers (PCPs). Thus, primary care-based programs to support patient uptake and engagement in diabetes 
prevention programs and behaviors could reach large numbers of at-risk individuals and improve their health 
outcomes. To date, most initiatives focus solely on increasing health care provider identification and referral of 
patients to programs.76,77 In light of the multiple barriers many low-income and ethnic and racial minority adults 
face to enrolling in and engaging in such programs, additional low-cost primary care-based approaches are 
necessary to link patients to and help them initiate and sustain engagement in health system, community-
based, or e-health programs and/or in healthy behaviors that decrease risk of progression to diabetes. 
B. INNOVATION 
Peer Support is an Innovative and Effective Approach to Improve Health Behaviors and Outcomes. One 
promising and highly scalable approach to motivate and support adults at risk for diabetes would be to pair 
them with a fellow patient with prediabetes who has completed a diabetes prevention program and is working 
to sustain their own healthy behaviors. There is a large and growing body of evidence on the feasibility, wide 
acceptability, and effectiveness of peer support for diabetes self-management and other areas of prevention 
and chronic disease management in diverse settings and populations.78-81 “Peer support” is “support from a 
person who has experiential knowledge of a specific behavior or stressor and similar characteristics as the 
target population.”82 In our and others’ prior RCTs of mutual peer support and of volunteer peer health coach 
models, peer support compared to other approaches including nurse care management led to improved health 
behaviors—such as diet, exercise, medication adherence—and clinical outcomes such as blood glucose 
control and weight loss.53,83-89 82.6% of 46 peer support interventions examined in a systematic review found 
significant benefits from peer support compared to a comparison group (52.2%) or from baseline (30.4%).90 
Within diabetes, a 2016 meta-analysis of 17 studies demonstrated significant benefits of peer support with an 
average decline in A1c of 0.5%, a clinically meaningful improvement.91 Peer support among patients with 
prediabetes is an innovative approach that could extend these benefits to encourage uptake and sustain 
engagement in formal programs and healthy behaviors to prevent diabetes. 
Why and for Whom Peer Support Could Be Especially Effective. A key reason peer support can be an 
effective complement to formal health care is the nonhierarchical, reciprocal relationship created between 
peers with shared characteristics, challenges, and experiences.92,93 In addition, peer supporters often have 
more time and are more accessible to patients than health care providers.94 Information and support from 
peers who share a common ethnic and socio-economic background may be particularly effective among racial 

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and ethnic minorities and/or low-income individuals who face access barriers to health care and less trust in 
health care providers.95,96 Peer support is intrinsically culturally sensitive and tailored, as there is far less social 
distance between peers than between patients and health care professionals. Peer supporters who themselves 
report higher level of distress managing a condition89,97 and who are more ‘autonomy-supportive’86 are more 
effective in helping their partners achieve clinical goals. Participants who have lower levels of health literacy, 
lower social support, and higher levels of distress about managing their condition benefit most from peer 
support interventions.98 Moreover, peers who take on the helper role often gain competence and motivation in 
the target behaviors as much as those helped.99 Peer supporters can gain a greater sense of purpose through 
volunteering to help another that in turn can motivate them to improve their own health behaviors.100-102  
Reasons Some Peer Support Programs Fail. Three key lessons from unsuccessful prior peer support 
interventions must guide the development of new interventions. First, proactive outreach by peers through 
phone, text message, and/or email outreach is essential—unsuccessful interventions have relied on face-to-
face sessions with no outreach to participants.80,103,104 Second, effective initial and booster training and fidelity 
assessments as well as ongoing support of peer coaches are vital.103 In Leahey et al.’s RCT, the peer coaches 
in one arm had been poorly trained and were highly directive (“non-autonomy-supportive”) leading to little 
weight loss among their assigned participants.86 That and other studies reinforce a third lesson: the importance 
of participants feeling that they share important characteristics and experiences with their supporters. Rather 
than serving as inspiring role models, peer supporters who have never struggled with the behaviors an 
intervention is seeking to improve are less effective than supporters who themselves have also overcome 
challenges.86,97,105 Innovative peer support programs for diabetes prevention that address these concerns have 
the potential to harness the value of peer support for reducing diabetes risk and improving healthy lifestyles.  
Promise of Implementing Primary Care-based Peer Support Program for Prediabetes. This evidence 
supports the promise of a well-designed peer support program that pairs adults with prediabetes with a trained 
peer volunteer from the same primary care center and community. This approach could be a cost-effective 
strategy to increase uptake and engagement in prevention programs and to improve health behaviors if 
individuals are not able to participate at all or regularly in formal programs. To date, there have been no 
pragmatic clinical studies in real-life routine practice comparing this strategy with health care provider 
identification and referral alone. In addition to evaluating effectiveness of such an intervention, rigorous 
process evaluations are essential to inform broader dissemination and implementation. Such an evaluation is 
especially timely in our two study health systems as there is strong stakeholder support for adopting and 
scaling up such a program if found effective. For example, the University of Michigan Health System (MM) 
Patient and Family-centered Care (PFCC) Program has established infrastructure and staffing for a health 
system-wide volunteer peer support program. They have recruited, trained, and supervise over 70 volunteer 
patient peers working with other patients undergoing transplants and with burns and spinal cord injuries. They 
are now extending programs to patients with cystic fibrosis, HIV and for caregivers. PFCC leadership has 
expressed their commitment to assume all recruitment, training, and supervisory functions for this program if 
found effective (see support letter). Similarly, the Kaiser Permanente Northern California (KPNC) leadership for 
prediabetes population care has expressed strong interest in adding this program to their menu of system-wide 
programs to support behavior change if our study demonstrates its effectiveness (see letter of support).  
C. APPROACH 
Overview. The proposed UPSTART (Using Peer Support to Aid pRevenTion of Diabetes) intervention seeks to 
address the need to test in routine primary care evidence-based approaches to increase uptake, engagement, 
and maintenance of healthy behaviors necessary to decrease progression to diabetes among primary care 
patients with prediabetes, especially low-income and racial and ethnic minority adults with prediabetes. Our 
design will be an effectiveness-implementation hybrid design type 1: We will test effects of the intervention on 
outcomes while observing and gathering information on implementation.106 We will conduct a parallel, two-
armed, randomized controlled pragmatic clinical trial107 including adults with prediabetes at two primary care 
centers in two different health systems: KPNC and MM. The study primary care centers serve large numbers of 
low-income and racially and ethnically diverse patients. The trial will evaluate whether adding a 12-month 
predominantly telephone-based volunteer peer support program (UPSTART) to health care provider 
counseling and referral to diabetes prevention programs leads to greater uptake and engagement in formal 
diabetes prevention programs as well as improvements in A1c, weight loss, and waist circumference than 
health care provider counseling and referral alone (Aim 1). We will also compare differences in reported 

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physical activity, diet, and enrollment and engagement in diabetes prevention programs; potential mediators of 
autonomous motivation, behavior-specific self-efficacy, and perceived support; and moderators of health 
literacy, activation, and reported barriers to participation in diabetes prevention activities (Aim 2). To assist in 
both health systems’ efforts to create a menu of program options for patients, we will examine patient 
characteristics associated with participation and engagement in the intervention. To enhance adoption of the 
intervention by the two study health systems and dissemination to other health systems if effective, we will 
evaluate costs and use an integrated RE-AIM108 and Consolidated Framework for Implementation Research 
(CFIR)109,110 framework to evaluate processes of intervention implementation in the two primary care settings 
(Aim 3). The study duration will be 5 years, to allow for peer supporter and patient recruitment, completion of 
the 12-month program, and assessment of outcomes at 6 months and at 12 months.  
We will use mixed methods—i.e., the collection, analysis, and combining of both quantitative and 
qualitative data—to investigate elements important for implementation and dissemination.111 Specifically, we 
will use an “embedded” mixed methods design involving collecting qualitative data during the intervention to 
better understand the mechanisms influencing implementation and outcomes.112 We will gather data on how 
peer supporters, primary care clinic staff, and patients experience the intervention and how the experiences of 
participants together with the trial’s results suggest we should modify the intervention. Using this approach, we 
aim to ensure that the intervention has the greatest possible likelihood of adoption in both MM and KPNC 
health systems should we find it has positive effects on processes and outcomes of care.  
Preliminary Studies. The proposed intervention builds on the prior work of Michele Heisler, MD, MPA (MPI) 
and Julie Schmittdiel, PhD (MPI), as well as that of the multi-disciplinary team of co-investigators Caroline 
Richardson MD, Jeff Kullgren MD, Alyce Adams PhD, Richard Grant MD, Monique Hedderson, PhD, Romain 
Neugebeauer, PhD, and Laura Damschroder, MA. Drs. Heisler and Schmittdiel have led multi-site RCTs and 
implementation studies. Dr. Heisler’s evaluations of different peer support models to improve health behaviors 
and outcomes provide a strong foundation for the proposed intervention. Dr. Schmittdiel’s research on 
strategies to improve the performance of health care systems has included studies of natural experiments such 
as the Natural Experiments in Diabetes Translation (NEXT-D) study, which provided pilot data for the proposed 
study. Drs. Heisler and Schmittdiel have a strong track record of collaboration together. For example, they co-
led the five-site cluster randomized pragmatic trial funded by NIDDK and VA of the AIM intervention.113-116  
On the MM team, Dr. Richardson is the former Medical Director of the Ypsilanti Health Center, the 
proposed MM study site. The proposed study draws on lessons from her federally funded intervention and 
implementation studies of technology-mediated health behavior change programs for diet, exercise and 
weight loss117-119 and of the VA DPP Clinical Demonstration Project.120,121 Dr. Kullgren’s RCTs testing 
behavioral economic strategies to promote weight loss,122,123 physical activity,124 and treatment adherence125 
have informed the proposed intervention, as has a mixed-methods study he and Dr. Heisler recently 
completed examining engagement in behaviors to prevent diabetes among newly diagnosed adults with 
prediabetes.126 On the KPNC team, Dr. Hedderson contributes expertise and insights from her two RCTs 
evaluating diabetes prevention programs for at-risk pregnant women, one at the individual and one at the 
health system level.127-131 Our proposed recruitment and intervention strategies have been informed by Dr. 
Adams’s disparities-focused research. In multiple studies she has identified modifiable determinants of poor 
clinical outcomes among racial and ethnic minority adults with chronic conditions.132-134 She has then 
designed and evaluated health system and policy level strategies to address these.132-138 Dr. Grant’s prior 
work and current RCTs testing strategies to prepare adults with multiple conditions to negotiate priorities with 
their PCPs at clinic visits have informed the proposed intervention’s communication approaches.139 Dr. 
Neugebauer has provided biostatistical expertise for Dr. Schmittdiel’s pragmatic trials and evaluations of 
health plan experiments to reduce diabetes risk.140,141 His research on the most reliable, robust, and precise 
causal inferences in RCTs have guided our statistical approaches. Finally, our assessment of implementation 
will be guided by Laura Damschroder’s extensive prior work and expertise in mixed methods. She was the 
lead developer of the Consolidated Framework for Implementation Research (CFIR),109 which has been cited 
by >500 published articles.110 As we propose to do, she used the RE-AIM and CFIR frameworks to evaluate 
the VA DPP120 and the large-scale VA weight management program MOVE!,121 using CFIR to systemically 
assess contextual factors that influenced RE-AIM domains.120  
Lessons from Our Prior RCTs of Peer Support Interventions. The proposed pragmatic clinical trial has 
been informed by Dr. Heisler’s prior RCTs testing different peer models to help improve health behaviors and 
outcomes. One of her pragmatic clinical trials among adults with poorly controlled diabetes in two VA health 

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systems compared a reciprocal peer support model (P2P)—in which two participants were paired together 
and both gave to and received help from each other—with nurse care management (NCM).142 In that study, 
PCP participants had clinically and statistically significantly greater improvements in A1c and key patient-
centered outcomes after the 6-month intervention than those in the NCM arm. The P2P program was 
especially effective among participants with low health literacy, low social support, and high diabetes 
distress.98,143 Based on that trial’s success, we are now using RE-AIM and CFIR to evaluate the 
implementation of P2P in conjunction with shared medical appointments for adults with poorly controlled 
diabetes in five VA health systems.144 In two of our RCTs of reciprocal peer support among previously 
hospitalized heart failure patients145,146 and among adults with intractable depression,147 however, the peer 
support arm did no better than enhanced usual care. Lessons from these two null trials have informed the 
current application. For example, because engagement was very low in both populations, we concluded that 
for very ill individuals and for those grappling with depression in which activation is low, models in which 
trained peers reach out to participants would be more effective than mutual peer support models requiring 
both to reach out to each other.81,146,147  
We have also gained invaluable lessons from our prior RCTs testing volunteer peer supporter models 
among low-income Latino and African American adults with poorly controlled diabetes receiving care at urban 
primary care centers. In two RCTs, participants in the peer coach arm maintained gains from a diabetes self-
management program 12 months after the end of the program significantly better than usual care,148-150 and in 
another trial equally well as an arm that received support from salaried CHWs.151 Based on our earlier 
successful RCT in which we developed and tested whether an interactive, tailored e-health tool would 
enhance self-management support from CHWs for Latino and African American low-income adults with 
diabetes,152,153 we are now comparing peer coaching alone, peer coaching facilitated by an interactive, tailored 
e-health tool, and usual care for predominantly African American adults with poorly controlled diabetes.154 
From these peer coach trials, we have tested and refined a plethora of training and fidelity assessment 
resources that will be adapted for our proposed study. These include training curricula and manuals for initial 
training to peer supporters in Motivational Interviewing-based, autonomy supportive communication skills148,155 
(see Appendix A), in-depth peer supporter fidelity assessment check lists (Appendix B) and procedures, and 
protocols for monthly booster sessions. Our experiences have reinforced the critical importance of regular 
support sessions to allow exchange, reinforcement, and booster training for volunteer peer supporters.  
Needs Assessment among Latino and African American Adults with 
Prediabetes. In early 2016, we conducted interviews with 20 low-income African 
American and Spanish-speaking Latino adults with prediabetes who receive primary 
care from the Ypsilanti Health Center, one of the proposed study sites. We assessed 
barriers and facilitators of participation in structured behavior change programs and 
elicited their preferences for assistance in finding and engaging in diabetes 
prevention programs and/or activities. Interviewees liked the idea of participating in 
formal healthy behavior programs that would help them ‘get healthy’ and lose 
weight. Yet, they cited numerous barriers to regular participation in formal programs. 
These included time limitations, limited availability due to long hours, multiple jobs 
and/or changing work schedules, lack of childcare, and lack of transportation. Interviewees overwhelmingly 
agreed that additional support from somebody they trusted and who could reach out to them by phone, email, 
and/or text would be invaluable. Interviewees said they would prefer that such additional support come from a 
peer rather than a clinician or expert. They felt it would be helpful to have support from a peer to help them eat 
healthier and exercise more because it would be ‘moral support’ that would help motivate them to know 
someone was checking in on them who understood their barriers and difficulties. Almost all preferred receiving 
telephone calls approximately once a week while they were trying to initiate healthier behaviors. Most noted 
also appreciating email and/or texts but not as a substitute for calls. Most said an initial face-to-face meeting 
with their peer supporter would be ideal but beyond that trying to meet face-to-face would be too difficult. 
Characteristics they would like the supporter to have were confidence, ability to motivate, and understanding 
of the difficulties adults with pre-diabetes face as they had achieved something similar themselves (lost weight 
or increased physical activity).  
Recognition and Treatment of Prediabetes in Primary Care Visits. Despite the efficacy of formal diabetes 
prevention programs in reducing diabetes risk, as noted above, too few at-risk adults are benefiting from 
these. One barrier to wider adoption of lifestyle interventions and metformin may be a lack of strong evidence-
“It’s that I don’t have time, I 
have to work, and I work a 
lot, even on Sundays. This is 
what impedes me from 
joining because I am tired 
and it’s exhausting to get up 
and go to something like 
that. One wants to join but 
they are tired from working 
so much.”  

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based guidelines for PCPs on appropriate care paths for prediabetes.156-158 Dr. Schmittdiel and colleagues 
examined PCPs’ recognition of and treatment for prediabetes from 2006 to 2011. Within KPNC <18% of 
patients with a blood sugar level indicating prediabetes were re-tested for FPG or A1c levels within six 
months, and <1% were prescribed metformin.159 These findings suggest that outreach beyond the traditional 
office visit, using methods such as those we propose, could be a useful strategy to improve prediabetes care.  
KPNC Regional Strategies for Population-Based Prediabetes Care. In response to the need for strategies 
to address prediabetes outside of office visits, in 2015 KPNC introduced the Prediabetes Online Tool. This 
web-based tool accessible through the KPNC patient portal offers health education information on prediabetes 
and direct links to KPNC programs. The main health-plan based program to help KPNC members improve 
healthy lifestyles that is linked to the Prediabetes Online Tool is the Motivational-Interviewing (MI)-based 
Telephonic Wellness Coaching Center (WCC). MI is a highly effective collaborative, person-centered form of 
guiding to elicit and strengthen motivation for behavioral change.160,161 A typical coaching engagement consists 
of one initial session and up to six follow up contacts, but participants determine the number of sessions based 
on their individual need and interest. Studies led by Dr. Schmittdiel demonstrated that participation in WCC 
sessions is associated with improved patient satisfaction, smoking cessation, and clinically meaningful weight 
loss.162-164 Participants lost more than 9 pounds on average in the 12 months after starting the program.164 This 
confirmed that programs to help patient with prediabetes connect to the WCC along with other local DPP 
programs could be a highly successful strategy for decreasing diabetes risk in the prediabetes population.  
Increasing Health Care Engagement for Prediabetes Patients. Despite the effectiveness of elements of the 
prediabetes population management strategy found in our previous studies, Dr. Schmittdiel and colleagues 
have shown that current levels of engagement among KPNC members with prediabetes are sub-optimal. In 
2013, her team conducted a randomized encouragement trial that reached out to prediabetes patients outlining 
the risks of high blood sugar and encouraging enrollment in the WCC.165 Patients were randomized to receive 
outreach via letter, interactive voice response (IVR) telephone message, secure email message, or no 
outreach. While email messages were the most effective mode of outreach, only 3% of the patients in this arm 
made and kept a WCC appointment. Most strikingly, over the 6-month period none of the prediabetes patients 
(0%) in the arm who received no proactive outreach enrolled in the program. This study underscores the need 
for new and innovative strategies, such as the peer-support program outlined in our current proposal.  
The Intervention  
Conceptual Framework of Intervention Design. The below figure illustrates the proposed causal pathways 
through which we hypothesize that the peer support intervention will improve health behaviors and outcomes.  
Self-Determination 
Theory (SDT) and 
Social Comparison 
Theory (SCT) provide 
the theoretical 
foundations for the 
intervention and for 
the Motivational 
Interviewing-based training the peer supporters will receive.166 SDT provides a conceptual framework for 
understanding human behavior across a continuum of motivation and suggests that cultivating autonomy, 
relatedness to others and competence (“self-efficacy”) is required for sustained behavioral change. Higher 
levels of autonomous motivation (i.e., when people perceive that reasons for a behavior are chosen, emanate 
from oneself and correspond to values and goals that are important to oneself) in contrast to controlled 
motivation (when people act because they feel pressured or compelled to do so) are associated with 
engagement in and maintenance of healthy behaviors.166-168  
 The UPSTART intervention167,169 is designed for peers to interact and provide support in a way that is 
autonomy supportive with the goal of enhancing autonomous motivation and self-efficacy for healthy 
behaviors. Motivational Interviewing (MI)-based approaches are congruent with SDT and aim to enhance 
autonomous motivation.170 To the extent that peer support facilitates satisfaction of participants’ needs for 
autonomy, competence, and relatedness, while also providing informational and emotional support, it may 
provide an effective means to increase participants’ uptake, engagement, and maintenance of diabetes 
prevention activities. Findings from Social Comparison Theory (SCT) show that lateral comparisons with 

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“similar” targets (e.g., peers trained to be autonomy supportive who themselves have prediabetes and struggle 
with similar problems as their matched participant) may promote greater motivation and health behavior 
change than upward comparisons with individuals with whom one does not identify and/or whose success 
seems unattainable so comparisons with whom can induce frustration and hinder performance.171-173 The key 
SDT and SCT constructs of the importance of generating a feeling of “relatedness” with the peer supporter, 
thereby enhancing social support, trust, mutual reciprocity, and competence/self-efficacy have been shown to 
be correlated with healthy behaviors among Latino and other low-income and racial/ethnic minority adults.174,175 
Conceptual Framework of Implementation Assessment. Two theoretical program change frameworks will 
guide our mixed methods, multi-dimensional evaluation of implementation of UPSTART. The first is the RE-
AIM framework108 that will be used to assess external validity and prospects for maintenance of UPSTART in 
the two study health centers and for dissemination throughout the two health systems. RE-AIM consists of five 
domains: 1) reach to targeted population; 2) effectiveness; 3) adoption; 4) implementation consistency, costs, 
and adaptations; and 5) maintenance of program benefits.108,176 The second is the CFIR to assess barriers and 
facilitators that may affect adoption, implementation, and/or maintenance.109,177 The CFIR comprises 39 
constructs across 5 domains culled from published implementation frameworks and models178-180 to 
systematically assess contextual factors that may influence program implementation: 1) intervention 
characteristics; 2) outer setting (e.g., external policies and incentives); 3) inner setting (e.g., leadership 
engagement); 4) individual characteristics; and 5) process by which implementation is accomplished.109,177 The 
adjacent figure shows 
the framework that 
integrates RE-AIM and 
CFIR to guide our 
process evaluation.  
Study Sites. KPNC 
Oakland Medical Center 
(OMC): KPNC’s OMC 
provides primary and specialty care to >210,000 predominantly non-white members: 28% are African-
American, 25% Latino, and 16% Asian. Approximately 37% of adults in Oakland are overweight, with higher 
rates among African Americans and Latinos. OMC has on-site lab, pharmacy, nutrition, and health education 
services. MM Ypsilanti Health Center (YHC) and East Ann Arbor Health and Geriatric Center: YHC provides 
primary care to >10,000 patients 18 years and older. Approximately 50% are Medicaid enrollees, 40% are 
African-American, 10% are Latino, and 5% are Asian. Over 30% of YHC patients have ICD-10 codes of 
obesity. Ypsilanti had a median household income of $32,000 in 2014, compared to the national household 
median of $53,000.181 Nearly 60% of county adult residents are overweight or obese.182 YHC has on-site lab, 
pharmacy, nutrition, and health education services including a DPP program. 
Peer Supporter Selection, Training, and Fidelity Assessment. If recruited peer supporters participate only 
for 12 months, we will recruit 75 peer supporters. Based on our and others’ prior interventions,53,83-85,87-
89,149,150,183 we anticipate that many peer supporters will choose to participate longer than 12 months so we will 
need to recruit fewer new supporters. Study participants who complete the initial 6 months of the intervention 
and are interested in becoming peer supporters will also be actively recruited—and about 20% of peer 
supporters in our interventions have been participants who became supporters after completing the program. 
In our discussions with YHC and OMC PCPs, most identified 2-5 of their patients they would recommend to be 
peer supporters. To recruit the initial cohort, we will first contact patients recommended by PCPs and from lists 
of patients who completed MM and KPNC diabetes prevention programs.  Peer supporters may be eligible if 
they meet the following inclusion criteria:  are aged 18 years and older and: 
1. have completed a formal diabetes prevention program in the past 36 months, or  
2. have completed the first six months of the intervention arm of the UPSTART program.  
Peer supporters may also be eligible if they are aged 18 or older and meet inclusion criteria that demonstrate 
improvements in BMI or A1c, through electronic medical record review, who: 
3. Had an HbA1c in the prediabetes range (5.7-6.4 %) in the prior 36 months, with most recent (in past 12 
months) measurement being either:  less than 5.7% or 0.4% A1c points less than prior A1c; or  
4. had a BMI score of >=25 or >=23 in Asian Americans in the past 36 months and have achieved at least 
a 2% decrease in body weight in the last 12 months.  

Page 9 of 29 
 
We will exclude peer supporters if they have had a diagnosis of a serious psychiatric disorder (bi-polar, 
dementia, schizophrenia, or personality disorder) in the past 24 months; substance abuse in the last 12 
months; prior diagnosis of diabetes or taking a diabetes anti-hyperglycemic medication; any of the following 
concerns that would make it difficult to volunteer as a coach at this time:  too depressed or worried about other 
matters; active cancer treatment; dialysis; other life-threatening illness; or have taken weight loss drugs, 
underwent gastric bypass, or have participated in a medicated meal plan in the past 12 months.   
In our prior and current peer coach interventions,154 this two-stage approach has been successful, and we 
have developed effective recruitment, screening, and enrollment procedures.  
We will hold periodic ~3-4-hour initial trainings for new peer supporters over the study period. In 
addition, peer supporters will receive: 1) routine, structured check-ins that will include monthly peer support 
group meetings (teleconference or phone) to allow exchange; 2) back-up support: offering peer supporters 
contact information for staff who they can call; and 3) continuing education and booster training at the monthly 
group meetings to enrich their skill sets and knowledge. The initial training and booster sessions are adapted 
from peer and CHW trainings we have used successfully in prior interventions. The initial training will focus on 
key Motivational Interviewing (MI)-based communication skills and include role-playing activities. Peer 
supporters will also practice placing calls using the Interactive Voice Response (IVR)-supported telephone 
platform. A focus will be learning to help their partners create action plans and following up on how they are 
doing on their action plans (which will be the focus of the at-least weekly phone calls during the intervention’s 
first six months and monthly calls during the final six months). Peer supporters will be asked to reflect on their 
own troubles initiating and sustaining healthy behaviors and then discuss how they might work with others to 
help them overcome these challenges. They will also review information on evidence-based weight loss and 
physical activity targets to reduce risk of diabetes and on all available diabetes prevention programs in which 
patients in their health system can enroll. Finally, they will become familiar with the printed educational and 
local program curricular materials participants will receive. 
To assess fidelity, team members trained in MI will observe a random sample of kickoff sessions and 
IVR-facilitated telephone calls of each peer supporter, complete a fidelity check list and provide feedback to 
peer supporters. The IVR telephone platform peer supporters will use to contact participants will enable us to 
evaluate frequency and duration of contacts by each peer supporter-participant dyad to evaluate intervention 
engagement and dose. We will use these results to refine written training materials to be included in a “Train 
the Trainer” manual for a translation “toolkit” at the end of the grant period. Each supporter will be assigned 2  
participants for a 12-month period, with the option of coaching more if they are interested and participants are 
available. Although their role as volunteers will be emphasized, to cover any expenses they will receive a 
stipend for the initial training and different stipend amounts based on number of contacts per month 
documented by the IVR system with each of their assigned participants. We will assess how participation as 
coaches affects their own changes in some of the study measures. Thus, peer mentors will undergo informed 
consent and receive incentives to complete same baseline, 6-, and 12-month surveys as the participants they 
will be supporting.  
Patient Selection, Recruitment and Randomization. We will use a population-based approach to identify 
potentially eligible patients via KPNC and UM databases. Eligibility criteria will include: 18 years or older; no 
prior diagnosis of diabetes or use of anti-hyperglycemic drug use; BMI >=25 m2/kg or >=23 if Asian;14 and 1 
A1c of 5.7%-6.4% in the prior 3 months. We will exclude patients if they have had a diagnosis of a serious 
psychiatric disorder (bi-polar, dementia, schizophrenia, or personality disorder) in the past 24 months, 
substance abuse in the last 12 months, are pregnant or planning pregnancy, or have any of the following 
concerns that make it unimportant to them to work on decreasing their chances of developing diabetes right 
now:  too depressed or worried about other matters; active cancer treatment; dialysis; other life-threatening 
illness. 
A letter or email will be sent to eligible patients with a follow up call to provide more information about 
the study and further screen for eligibility.  
• 
Pre-COVID:  Eligible and interested patients will be scheduled for an enrollment visit at the clinic 
to complete in-person informed consent with a staff member, complete a baseline survey, get 
weighed and have their waist circumference measured, and have blood drawn at the lab for an 
A1c test.  
• 
During COVID: Eligible and interested patients will be scheduled to complete most of the 
informed consent process over the phone followed by online consent signing or signing and 

Page 10 of 29 
 
returning mailed hard copies.  Baseline assessments: survey completed by phone or online, 
followed by a short visit at the clinic to get weighed and have blood drawn at the lab for an A1c 
text. The measure of waist circumference was dropped.  
All participants will receive information on available local and online diabetes prevention programs and other 
local resources for healthy living. Participants will then be randomized to one of two arms. Randomization will 
be stratified by A1c and Latino ethnicity to allow for sub-analyses. Variable block sizes will preclude prediction 
of treatment assignments. Randomization lists will be established separately for each clinic site. After baseline 
assessment and receiving informational resources, participants will learn their study group assignment. 
Peer Support Arm. Participants randomized to peer support will be matched with a peer supporter of the 
same gender, race/ethnicity, and approximate age, as possible. Matching on shared characteristics has been 
found to lead to better peer relationships in prior studies. Peer supporters will receive information on times their 
partner(s) have indicated they are best contacted.  
• 
Pre-COVID: The dyads will meet for their kick-off session in person at the study site. 
• 
During COVID:  The dyads will meet for their kick-off session via phone or videoconference  
In the kick-off session, they will get to know one another and review together information on available diabetes 
prevention programs and discuss options that might best meet participants’ needs and preferences. They will 
also review provided educational materials and define together the participants’ behavior change goals and 
specific steps to take to meet goals over the next week (“action plan”).185 The supporter will be instructed to 
make at least one contact (call or text exchange) to each peer partner each week for the intervention’s first six 
months and at least once a month during the final six months. In our prior interventions, some dyads spoke 
and/or met more frequently. If the supporter does not make an initial contact using the study platform within the 
first 10 days, a team member will call to offer support. 
In the at-least weekly contacts, the peer supporters will check in on how the participant is doing, ask 
about their action plans, offer encouragement, help their partners brainstorm about solutions to barriers they 
have been facing meeting their action steps, or set a new or different action step or goal. For participants 
enrolled in formal diabetes prevention programs, they will discuss areas covered in that week’s session and 
targeted behaviors/goals for that week. For those participants enrolled in a structured program yet unable to 
attend program session/s (which we recognize for many participants may be often), the peer coach will help 
them review covered topics they missed and provide support for them to maintain their efforts until they can 
resume attending sessions. Peer supporters will be encouraged to use the toll-free IVR exchange system line 
to make contacts. We have used this system in prior peer support interventions,142 and it is an efficient way for 
coaches to contact their matched peer participant without exchanging personal telephone numbers. If the 
participant does not want to continue receiving coaching, they can call the study’s toll free number to be 
removed from the system. Research staff will monitor the contacts via a password-protected Internet web site. 
Through the automatic IVR monitoring system, we will be able to identify when contacts occurred, who made 
the contact, and how long participants talked. All these process data will be stored in a format accessible for 
statistical analysis as part of our process evaluation. Though often after an initial period in our prior 
interventions, participants and peer coaches have exchanged phone numbers (often bypassing the IVR 
system), peer coaches who complete 3-4 contacts each month to a peer participant via the IVR system receive 
increased stipend amounts and thus will have an incentive to use the IVR system. 
Enhanced Usual Care.  As described above, the enrollment session will include provision of informational and 
educational materials.  
Measures and Data Collection. We will collect multiple types of data for our mixed methods evaluations. At 
baseline, 6 months, and 12 months, participants will complete surveys, assessments of A1c, and weight (and 
height at baseline to calculate BMI). Each survey will take <30 minutes. Participants will receive $20 for each 
assessment. To assess program implementation and factors affecting each of the RE-AIM domains,108,176 we 
will conduct semi-structured interviews with peer supporters, participants, and clinic staff and leadership at 6 
and 12 months, complete fidelity assessments of peer supporter-participant interactions, observe peer 
supporter monthly sessions, and tabulate IVR data on frequency and duration of contacts. For example, to gain 
more in-depth understanding of factors associated with level of engagement and with outcomes, we will 
examine baseline survey data for key correlates of different levels of engagement based on IVR data on 
completed contacts and duration of calls. We will categorize patient-supporter dyads using these data into 

Page 11 of 29 
 
different levels of intervention engagement and conduct semi-structured interviews with purposive samples of 
peer mentors and participants with low, medium, and high engagement. We will operationalize data collection 
of the CFIR as a codebook for qualitative analysis to understand how contextual factors influence RE-AIM 
domains.120  
Variables in our intervention conceptual framework will be measured according to the table of measures, 
below.   
Measures 
Measure 
Timeframe 
Instrument 
Primary Outcome Measures 
Change in Glycosylated 
Hemoglobin A1c (HbA1c)  
6 months 
Clinical laboratories at both study health centers 
Change in body weight  
6 months 
Digital Scale used in clinic 
Secondary Outcome Measures 
Change in Glycosylated 
Hemoglobin A1c (HbA1c)  
12 months 
Clinical laboratories at both study health centers  
Change in body weight  
12 months 
Digital Scale 
Change in whether participant 
enrolled in a formal program to 
prevent diabetes  
12 months 
Individual item on survey: Enrollment in diabetes prevention 
program (Yes/No) 
 
Change in number of sessions 
participant attended in a formal 
program to prevent diabetes  
12 months 
Individual item on survey:  asks participant to report number 
of sessions attended 
 
Change in frequency participant 
engages in moderate to vigorous 
physical activity  
12 months 
Individual item on survey:  asks participant number of days in 
week, on average, participant engages in moderate to 
vigorous physical activity; from the Godin Leisure Time 
Exercise Questionnaire206,207 
Change in duration participant 
engages in moderate to vigorous 
physical activity 
12 months 
Individual item on survey:  asks participant number of 
minutes per week, on average, participant engages in 
moderate to vigorous physical activity; from the Godin Leisure 
Time Exercise Questionnaire206,207 
Change in diet 
 
12 months 
Participants will self-report diet using a 10-item custom 
survey developed by the study team, adapted from the eating 
habits items in the Behavioral Risk Factor Surveillance System 
Survey Questionnaire208 
Change in patient activation  
 
 
12 months 
The Patient Activation Measure (PAM-13)209 is a 13-item scale 
that measures participant beliefs, perceived knowledge, and 
confidence for engaging in behaviors related participant's 
health condition. It has a 0-100 scale, where a low score 
indicates low activation (disengaged and overwhelmed) and a 
high score indicates high activation (patient considers self 
their own advocate). 
Change in participant's perceived 
confidence in their ability to take 
steps to prevent diabetes  
12 months 
Williams Perceived Competence Scale210,211 comprises 4 items 
measuring the participant's perception of their own ability to 
take steps to prevent diabetes 
Change in participant's reasons for 
starting or continuing steps to 
prevent diabetes  
12 months 
The Treatment Self-Regulation Questionnaire (TSRQ)210,212 
consists of 11 items that measure participants' perceptions of 
how true various reasons to take steps to help prevent 
diabetes may be to the participants 
Change in the participant's level of 
social support related to improving 
their own health behaviors  
12 months 
Adapted from the Diabetes Social Support Scale213 and 
consisting of 12 items that ask the participant to indicate their 
level of agreement with statements regarding accessibility of 
others who could provide social support in attempts to 
prevent diabetes via healthy lifestyle changes.  

Page 12 of 29 
 
Measures 
Measure 
Timeframe 
Instrument 
The role a participant's peer 
supporter played in assisting them 
to set and reach their goals  
6 months and  
12 months 
The Patient Assessment of Chronic Illness Care (PACIC)214 
consists of 5 items that ask the participant to state how often 
their peer supporter engaged in supportive behaviors 
regarding setting and achieving goals in order to make healthy 
lifestyle changes. 
Participant's perceived autonomy 
support from their peer supporter  
6 months and  
12 months 
The Health Care Climate Questionnaire (HCCQ, long form)215 
consists of 15 items that ask the participant to rank their 
agreement with statements that indicate degree of autonomy 
support 
Moderators 
Depression screener 
Baseline, 6, and 
12 months 
Two item version of the Patient Health Questionnaire (PHQ-
2)216 
Health Literacy 
 
baseline 
Single item from the Functional Health Literacy Screener217 
asking respondent to indicate their confidence in filling out 
health forms by themselves. 
Neighborhood characteristics 
baseline 
8 items from the Measurement Properties of Neighborhood 
Scales 218 that assess local access to food and neighborhood 
characteristics that promote or prevent outdoor physical 
activity 
Social Determinants of health 
6 and 12 months 
Adapted one item from the PRAPARE tool219 identifying 
unmet needs and the study team developed three items to 
determine how needs were addressed, needs that the peer 
supporter helped with, and resources and services they 
learned about from being in the study. 
Mediators 
Healthcare climate (autonomy-
support of health care provider) 
Baseline, 6, and 
12 months 
The Health Care Climate Questionnaire (HCCQ, short form)215 
consists of 5 items that ask the participant to rank their 
agreement with statements that indicate degree of autonomy 
support  
Dyads’ contacts, last 6 mo: method, 
frequency, frequency of texts* 
6 and 12 months 
3 items 
 
Cost data collected will include time spent recruiting, training, and supervising the peer coaches as well as total 
costs of the reimbursements provided to peer coaches throughout the intervention period. Staff will keep logs 
of all time spent in these activities. Finally, we will include the time and costs of proactively identifying and 
recruiting participants and of providing the teleconferencing system for peers (although this system is being 
used largely for research purposes and is not usual in actual practice for peer mentoring programs.) 
Sample Size. Based on our prior research and data from previous Diabetes Prevention studies, we made 
these assumptions for sample size estimation: (a) two-tailed test at an alpha level of 0.05; (b) power of .90; (c) 
a mean difference of 0.16% in change of HbA1C at 12-months between groups with a standard deviation of 
0.4%, and (d) a 10% attrition rate. In addition, we accounted for possible correlations between members of the 
peer-coach dyads (intraclass correlation, or rho) in the intervention group.186,187 We conducted the power 
analysis using the methods of Cohen.188 In our prior peer support interventions the within-pair intraclass 
correlation of 0.01 was not statistically different from zero, but we included this value in our assumptions.87,142 
We will stratify randomization by site and are using power calculation assumptions to detect site-specific 
effects. With these assumptions, 296 participants are required (148 in each arm). In addition, over half of our 
target patient population is African American or Latino. A sample size of 128 (64 per group) will give us over 
80% power (alpha = 0.05, two-tail) to detect a mean difference of 0.2% in change of HbA1C from baseline to 12 
months between the intervention and control groups for the combined ethnic minority subgroups (mainly Latino 
and African American).21 A recent meta-analysis examining reductions in A1c among racial/ethnic minority 
groups suggests this estimated effect size is conservative.189 With this sample size, we will also be able to 
detect clinically significant differences in weight and in our other self-reported secondary outcomes. 

Page 13 of 29 
 
Analysis Plans. Aim 1: Compare the effectiveness of the peer support program with enhanced usual 
care in decreasing A1c and weight. Our past experience in similar patient populations suggests that the 
primary outcome (change in A1c) will be close to normally distributed. To assess change in mean HbA1c, we 
will use a general linear mixed regression model: 
 
where i represents the patient, l represents the intervention, j is the pair-group, βl are parameters estimated 
from the data, Xil is the value of the lth fixed effect (peer support versus usual care) for the ith patient, bj are 
parameters estimated from the data, Zij is the value of the jth random effect (pairs) for the ith patient, and εi is 
the residual error.190 We need to account for the possibility that members of peer-peer partner pairs, because 
of their interactions with each other, might show a small positive intraclass correlation (ICC), a component of 
the variance attributable to the group. As recommended for group-randomized trials, the mixed model analyses 
will address potentially inflated type I errors that could occur if such clustering were not taken into account.191 If 
patients drop out or request reassignment, they will be analyzed according to their initial pairing in an intent-to-
treat analysis. After unadjusted changes in A1c are determined, further analyses using mixed-model ANCOVA 
will adjust for confounding effects of any variables that differed substantially between treatment arms. Both 
unadjusted and adjusted means with 95% confidence intervals will be reported for both arms. While the 
primary endpoint is the mean difference between baseline and 6-month A1c, analyses will be conducted to 
determine whether the intervention also affects the difference between baseline and 12-month A1c (i.e., the 
sustainability of any treatment effects) using a repeated-measures mixed model ANCOVA. We will follow these 
same methods in assessing changes in weight (continuous and % weight loss) and in waist circumference. We 
will conduct sensitivity analyses and use standard approaches to account for missing data.192,193 
Aim 2: Identify patient characteristics associated with greater engagement in the peer support 
intervention and mediators and moderators of effectiveness. We will use multivariate modeling and path 
analyses.194 Many of these outcomes will be measured using Likert scales. Thus, we will begin these analyses 
by developing contingency tables for ordered categorical data. We will then use generalized estimating 
equations (GEE) appropriate for modeling ordinal outcomes with correlated data.190 We will use both 
quantitative and qualitative methods. We will compare patient characteristics and attitudes of participants and 
those not willing to participate in the study. Eligible refusers will be asked whether they would consent to a brief 
survey in which we will record information helpful in assessing the intervention's reach. We will model 
independent associations and pathways linking intervention exposure to outcomes using nested multivariate 
regression. Subsequent nested models will introduce potential mediators, and we will evaluate changes in the 
magnitude of the relationship between experimental condition and outcomes before and after the covariates 
are introduced. Analyses of potential moderators will use standard approaches to evaluate potential 
interactions between these covariates and patients’ experimental condition.194 Independent variables and 
moderators will be centered before testing interactions, so that multicollinearity between first order and higher-
order terms will be minimized. Statistically significant interactions will be interpreted by plotting regression lines 
for high and low values of the moderator variable. Stata routines facilitate the plotting of these relationships.195  
We will perform a thematic analysis of interview data using QSR NVivo, a qualitative data analysis 
package. Our overall approach to thematic analysis will be what Miller and Crabtree refer to as the “Editing 
Analysis Style,” which contains both deductive and inductive elements.196 Two investigators will independently 
read interview transcripts, break down responses into individual segments that express a single idea or theme 
and label these phrases with appropriate codes. An iterative process will be used to compare results until 
agreement is reached on the categories and criteria for inclusion.197 We will examine in more depth factors 
contributing both to successful and unsuccessful peer mentor-partner matches and outcomes. 
Aim 3: Evaluate program costs and barriers and facilitators to adoption, implementation, maintenance 
and spread using an integrated RE-AIM and CFIR framework. It is essential to collect and analyze 
information to determine the feasibility of (in terms of cost, effort, and interest) and most effective strategies to 
broadly disseminate and implement this intervention. We will examine costs from the perspective of the payer 
and create standard costs198-204 to ensure that while the costs reported may be specific to the health plans and 
clinics studied; they approximate general charges a patient might be billed if these same services were 
purchased. All costs will be adjusted to current dollars using medical and pharmaceutical components of the 
Consumer Price Index. Our cost analysis will also estimate the costs of delivering the intervention itself, 
including costs associated with training, supporting, and incentivizing peer coaches, recruitment, IVR, and 
peer-to-peer communications.205 Sensitivity analyses will be used to examine the impact of using different cost 
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Page 14 of 29 
 
estimates. We will provide stakeholders within KPNC and the Michigan Medicine clinics with all cost estimates 
but especially highlighting the costs of sustaining UPSTART over the long term.  
The five domains of RE-AIM will be analyzed as follows: Reach: Calculate the enrollment rate of 
contacted eligible adults and compare characteristics of participants to non-participants. Effectiveness. Aims 1 
and 2 will assess whether UPSTART is effective based on our primary and secondary outcome measures. We 
will also assess process measures such as differences in drop-out between groups or sub-groups. Qualitative 
data analysis will explore participant, peer, and staff experiences with the program and key elements 
contributing to whether it was effective.  
Protocol for semi-structured, qualitative interviews with coaches and peers: 
As enrolled participants complete their final, 12-month assessment, they are asked if they would be 
open to being contacted in the future about participating in an interview over the phone to describe 
their experiences in the study in their own words.   
 
Those who indicate that they are open to being contacted will be contacted by study staff by e-mail or 
phone to schedule a one-hour time slot for the phone interview. No more than three attempts will be 
made to connect with each participant.  Up to 65 participants (all consented and enrolled in the 
UPSTART study) will be interviewed; interviews will cease once thematic saturation has been 
reached.  Staff will first explain the purpose of the interview, its length, the fact that they will be 
listened to by a note-taker (a study staff member) and audio recorded, and how the participant will 
receive a $20 gift card for participating.  The audio recording is mandatory, so if someone does not 
want to be recorded, they can’t participate in this phone interview.  Staff will answer any questions, 
and if the participant is willing, the staff person will schedule a one-hour time block for the interview.  
The participant will be given the call-in number and code over the phone, via text, and/or via email, 
according to the participant’s preference. 
   
Shortly before the scheduled interview, staff will send the participant a reminder with the call-in 
information.  Once the participant calls in, the interviewer will introduce herself and the note-taker, 
and then explain that she is going to describe the interview and officially ask for the participant’s 
consent before starting the interview.  Then, she will follow the consent script (uploaded in Section 
10-1.1) to obtain verbal consent. 
 
The study staff will document that the consent process took place and whether or not the subject 
verbally agreed to continue participating. If the subject declines participation, the interview will not be 
conducted, and nothing will be audio recorded. If the participant consents, then she will begin audio 
recording and start the interview.  When audio recording begins, the system announces this to all on 
the call. 
 
In order to capture responses to the interview questions, a study team member will be on the 
conference call to take notes during the interview. We will audio record the interview to check that the 
notes are complete and accurate. We will use a cloud-based conferencing service to conduct these 
interviews and to audio record (for example, Zoom).  We will only use conferencing services where 
there is a Business Associate Agreement between the service and the University of Michigan, which 
means it complies with the Health Insurance Portability and Accountability Act of 1996 (also known as 
HIPAA) regulations.  Also, recordings of the interviews will be encrypted and stored either in the 
secure conferencing service or on a secure, encrypted server. Once the research team compares the 
notes taken during the interview to the audio recording, the audio recording will be destroyed. 
 
All participants who compete an interview will receive a $20 gift card in the mail, paid through the 
HSIP program.  All participants submitted the information required by HSIP when they enrolled in the 
UPSTART study. 

Page 15 of 29 
 
 
Interview recordings and notes will be labeled with a code to help protect confidentiality.  In order to 
analyze the data collected, two separate study team members will review interview notes in order to 
develop a code book.  This iterative process involves individual coding followed by meetings among 
the coders to come to agreement on a common list of codes.  Once the codebook is established, the 
study staff will use the agreed-upon codes to code all interview notes.  The study staff will use 
software such as NVivo to facilitate the coding and analysis of qualitative data.  Analyses will be used 
to optimize the intervention for future use and identify key elements contributing to the intervention’s 
effectiveness. 
 
Protocol for semi-structured, qualitative interviews with key informants 
In the final year of funding, we will conduct interviews with a selection of key informants who work at 
Michigan Medicine or the University of Michigan with the objective of judging prospects for sustained 
offering of UPSTART as part of usual care, identifying potential barriers to sustaining the program, 
and determining areas for modification. 
 
We plan to conduct 10-20 interviews.  Potential interviewees have been identified based on their role 
at MM; they are selected based on their likelihood of sharing information needed to meet our 
objective in the above paragraph.  In addition, at the end of each interview, we will ask each 
interviewee if they would recommend others we should interview. 
 
We plan to invite: 
• the Medical Directors at the two sites where we offered the program, Ypsilanti Health Center 
and East Ann Arbor 
• clinicians, social workers, and diabetes educators at these clinics 
• 1-2 staff or leadership from the Office of the Patient Experience 
• Leadership of Ambulatory Care Operations 
• Leadership of Community Health Services 
• Leadership the Office of Health Equity and Inclusion 
 
The Principal Investigator will send an email invitation to each individual; attached to the email will be 
a 2-page infographic describing the study and a one-page list of topics we hope to cover in the 
interview.  
 
No more than three attempts will be made to connect with each potential interviewee.  For those who 
are willing, the staff person will schedule a one-hour time block for the interview.  The participant will 
be given the call-in number and code over the phone, via text, and/or via email, according to the 
individual’s preference. 
   
Shortly before the scheduled interview, staff will send a reminder with the call-in information.  Once 
the interviewee calls in, the interviewer will introduce herself and the note-taker, and then explain that 
she is going to describe the interview and officially ask for the participant’s consent before starting the 
interview.  Then, she will follow the consent script (uploaded in Section 10-1.1) to obtain verbal 
consent. 
 
The study staff will document that the consent process took place and whether or not the subject 
verbally agreed to continue participating. If the subject declines participation, the interview will not be 
conducted and nothing will be audio recorded. If the participant consents, then she will begin audio 
recording and start the interview.  When audio recording begins, the system announces this to all on 
the call. 

Page 16 of 29 
 
 
In order to capture responses to the interview questions, a study team member will be on the 
conference call to take notes during the interview. We will audio record the interview to check that the 
notes are complete and accurate. We will use the cloud-based conferencing service Zoom to conduct 
these interviews and to audio record because there is a Business Associate Agreement between 
Zoom and the University of Michigan, which means it complies with HIPAA regulations.  Also, 
recordings of the interviews will be encrypted and stored either in the secure conferencing service or 
on a secure, encrypted server. Once the research team compares the notes taken during the 
interview to the audio recording, the audio recording will be destroyed. 
 
Interview recordings and notes will be labeled with a code to help protect confidentiality.  Analyses 
will be conducted in the same manner as described for the interviews with peers and coaches in the 
preceding section of this protocol. 
 
Adoption. Two sites have agreed to participate but staff may differ in their openness to referring their 
patients to a peer support intervention if formally adopted. We will analyze staff attitudes toward the value of 
the program over the course of the study period. Implementation. We will analyze degree of fidelity as 
documented on the check lists of observed encounters. Interview data will be analyzed to assess CFIR 
constructs to explore barriers and facilitators to implementation. Any adaptations will be documented through 
project notes. Differences in implementation and in barriers/facilitators across the two study sites will also be 
documented. Maintenance. Individual-level maintenance of engagement is captured by our IVR data and by 
our measured outcomes. At the clinic level, qualitative data will be used to judge prospects for sustained 
offering of UPSTART as part of usual care, to identify potential barriers to sustaining the program, and 
determining areas for modification. As part of our process evaluation, we will seek opportunities to streamline 
the intervention through more efficient protocols. Field notes will be kept and analyzed to inform the next 
generation program. With this aim’s findings, we will develop a tool kit of all training materials and protocols to 
guide dissemination efforts and to contribute to the field of implementation science.  
Study Timeline: The timeline contains the study’s activities for all years:
 
Potential Problems and Solutions: We anticipate four key potential problems. First, our proactive 
identification process requires that patients have had a fasting glucose or A1c within the prior 12 months during 
our enrollment period of 24 months. Thus, vulnerable patients who fall out of clinical care for extended periods 
will not be captured. Such patients are often among the highest risk patients. Fortunately, both study sites have 
systems in place to proactively identify and reach out to patients who have not seen a PCP within two years. 
Such measures will help mitigate this problem. Second, although both sites are engaged in active efforts to 
screen for prediabetes and refer all patients with prediabetes to programs, we and clinical leaders at the two 
sites recognize that some potentially eligible patients we contact will not be aware that they have blood sugar 
levels in the prediabetes range. In fact, the clinical sites see our identification and outreach to such people who 
have fallen through the cracks as a support for their efforts and we will share all identification lists with the 
clinical staff. We will work with clinical leadership at both sites to ensure that they endorse the language in 
recruitment scripts and in the initial information session informing patients about prediabetes and measures 
they can take to prevent progression to diabetes. Third, as in our prior interventions, a very few patients who 
have blood glucose levels within 12 months before baseline in the prediabetes range will have levels in the 

Page 17 of 29 
 
normal range when we check their A1c at baseline. Those of a slightly larger number will have progressed to 
levels consistent with diabetes (6.5% or greater). We will facilitate a nurse or PCP appointment with those who 
have progressed to diabetes. Those in the improved group will be invited to participate as a Peer Supporter. In 
both cases, we will give them information about the meaning of their A1c and provide educational materials 
and information on programs to improve health behaviors and/or for diabetes education. A fourth potential 
problem for this intervention targeting a lower-income, urban population is attrition. In our previous 
interventions with patients at federally qualified health centers, we have faced attrition of up to 20% over 12 
months. However, in our and our colleagues’ prior work at these two primary care centers, attrition rates have 
not exceeded 10%. Through our years of work with low-income, racial and ethnic minority populations, we 
have developed very effective strategies for recruitment and retention. Moreover, we will follow sound 
analytical approaches to address any missing data through intention to treat analyses that will aid in avoiding 
misleading interpretation of the data.  
Expected Outcomes: The proposed study will provide rigorous evidence on the effectiveness of peer support 
to enhance uptake, engagement, and maintenance of behaviors to reduce risk of progression to diabetes. 
Findings from the study will provide invaluable information on required staff effort, costs, and key facilitators 
and barriers to implementing and sustaining this type of volunteer patient-led program. At the end of the study, 
along with preparing manuscripts for publication, we will create and disseminate a ‘tool kit’ with all recruitment, 
initial and booster training materials, fidelity assessments, recommended oversight procedures, among other 
materials to facilitate adoption and implementation of the program at other health centers and systems. We will 
also share the findings with multiple audiences, including research participants, health center and system 
leaders, policy makers, community leaders, and academic and public audiences. Finally, through the rigor and 
innovativeness of our proposed mixed methods assessment grounded in an integrated RE-AIM and CFIR 
framework, the proposed research will contribute both to translational and implementation science. 
Future Directions: Perhaps the most important goal after the study’s completion is to ensure that the program 
if found effective is fully adopted in both of the study sites and sustained over the longer term. Additionally, we 
will be positioned for broader dissemination and implementation throughout two large health systems. To help 
ensure this, in preparing this submission we have met with and secured the support of key stakeholders at 
both study health centers and systems, ensuring that these programs address their key priorities and 
incorporate metrics that matter to them in deciding whether to adopt the program. At the end of the study, there 
will be a cadre of trained and experienced peer supporters who can help train and support future peer 
supporters. Because this program relies on trained patient volunteers, the principal future need is limited staff 
effort to help recruit new peer supporters and provide them training and oversight/support. At MM, these 
functions would be assumed by the already existing health system-wide peer mentor program run by the MM’s 
Patient- and Family-Centered Program that was established precisely to develop and oversee peer mentoring 
programs such as the one we propose to evaluate (see letter of support). At KPNC, the prediabetes population 
care leadership has also expressed strong interest in including support for this program among their other 
programs promoting healthy behaviors among KPNC members (see letter of support). One key reason KPNC 
and MM health system and health promotion leaders have strongly endorsed the proposed intervention (see 
letters of support) is that it is a low-cost, patient-led program that can provide flexible and frequent contact and 
support that many vulnerable patients need yet is beyond the scope of what health care providers can 
provide—and is thus an invaluable complement to formal health care.  
 
At a broader policy level, through Dr. Heisler and Dr. Schmittdiel’s leadership roles in their institutions’ 
Centers for Diabetes Translational Research (CDTR), they will work to inform local, state, and national policy 
makers, such as CDC staff leading efforts to broadly disseminate different versions of the DPP, about key 
lessons gleaned from this study about how better to increase uptake of and engagement in diabetes 
prevention activities as well as to maintain achieved gains. Finally, we will build on knowledge gained through 
this study to continue developing and testing different peer support models that activate patients to improve 
their health and that contribute to creating more patient-centered health care systems. Well-designed peer 
support models such as the one we propose to evaluate hold promise to help stem the epidemic of diabetes 
and address widening disparities based on income and race/ethnicity in diabetes and its complications. 
Lessons from this study will also fruitfully inform the design of peer support models for patients who have other 
health conditions and who are working to improve other health behaviors.  
 
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